India’s Trade Data Analysis
Sahil Sharma
2026-03-26
Data analysis is the process of examining, cleaning, transforming, and modeling data to discover useful information and support decision-making.
In this project, we analyze India’s import and export data using R. The dataset contains multiple variables such as product category, country, trade value, and shipment details.
This project helps in understanding real-world trade patterns and applying R programming concepts.
1 Level : Understanding the Dataset
1.1 Question: How to load and view the dataset?
library(dplyr)## Warning: package 'dplyr' was built under R version 4.5.3##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2)## Warning: package 'ggplot2' was built under R version 4.5.3library(scales)## Warning: package 'scales' was built under R version 4.5.3data <- read.csv("india_trade_data (3).csv")
head(data)## Year Month Product_Category Product_Name Import_Export Quantity Value_USD
## 1 2024 October Agriculture Medicine Export 5414 72245.784
## 2 2023 April Textile Cotton Export 5189 24614.994
## 3 2024 March Automobile Cotton Import 415 7532.450
## 4 2020 December Electronics Medicine Export 6108 9767.587
## 5 2022 April Automobile Mobile Import 2951 72703.563
## 6 2020 March Agriculture Cotton Export 142 71831.337
## Country Port Transport_Mode Tariff GST Exchange_Rate
## 1 China Delhi Land 8.393855 15.633720 72.10798
## 2 USA Delhi Air 19.930770 12.699521 82.20563
## 3 Germany Kandla Air 5.384847 5.309774 80.85602
## 4 Japan Chennai Land 10.659926 11.137832 84.70135
## 5 UK Kandla Land 14.464991 5.959429 75.20845
## 6 Japan Mumbai Air 5.191173 5.838508 70.25781
## Shipment_Days Delivery_Status Trade_Agreement Date Value_INR Profit
## 1 21 Delayed Non-FTA 24-03-2019 5209497.3 692534.55
## 2 18 On Time Non-FTA 03-07-2022 2023491.1 393206.54
## 3 29 On Time FTA 11-03-2018 609043.9 94639.13
## 4 26 On Time FTA 05-08-2021 827327.7 90860.20
## 5 18 Delayed Non-FTA 07-08-2019 5467922.5 588212.45
## 6 14 On Time Non-FTA 09-01-2022 5046712.2 851753.59
## Loss Is_Delayed
## 1 131463.95 True
## 2 147679.02 False
## 3 31589.87 False
## 4 10806.93 False
## 5 229675.60 True
## 6 363622.75 FalseExplanation
The dataset is loaded using read.csv(). The head() function displays the first few rows to understand the structure.
1.2 Question: What is the structure of the dataset ?
str(data)## 'data.frame': 2500 obs. of 21 variables:
## $ Year : num 2024 2023 2024 2020 2022 ...
## $ Month : chr "October" "April" "March" "December" ...
## $ Product_Category: chr "Agriculture" "Textile" "Automobile" "Electronics" ...
## $ Product_Name : chr "Medicine" "Cotton" "Cotton" "Medicine" ...
## $ Import_Export : chr "Export" "Export" "Import" "Export" ...
## $ Quantity : int 5414 5189 415 6108 2951 142 2421 3551 1720 9274 ...
## $ Value_USD : num 72246 24615 7532 9768 72704 ...
## $ Country : chr "China" "USA" "Germany" "Japan" ...
## $ Port : chr "Delhi" "Delhi" "Kandla" "Chennai" ...
## $ Transport_Mode : chr "Land" "Air" "Air" "Land" ...
## $ Tariff : num 8.39 19.93 5.38 10.66 14.46 ...
## $ GST : num 15.63 12.7 5.31 11.14 5.96 ...
## $ Exchange_Rate : num 72.1 82.2 80.9 84.7 75.2 ...
## $ Shipment_Days : num 21 18 29 26 18 14 10 6 17 30 ...
## $ Delivery_Status : chr "Delayed" "On Time" "On Time" "On Time" ...
## $ Trade_Agreement : chr "Non-FTA" "Non-FTA" "FTA" "FTA" ...
## $ Date : chr "24-03-2019" "03-07-2022" "11-03-2018" "05-08-2021" ...
## $ Value_INR : num 5209497 2023491 609044 827328 5467923 ...
## $ Profit : num 692535 393207 94639 90860 588212 ...
## $ Loss : num 131464 147679 31590 10807 229676 ...
## $ Is_Delayed : chr "True" "False" "False" "False" ...Answer
The str() function shows the data types of each column such as numeric, character, logical, and date.
1.3 Question: What are the summary statistics?
summary(data)## Year Month Product_Category Product_Name
## Min. :2018 Length:2500 Length:2500 Length:2500
## 1st Qu.:2019 Class :character Class :character Class :character
## Median :2021 Mode :character Mode :character Mode :character
## Mean :2021
## 3rd Qu.:2023
## Max. :2041
## Import_Export Quantity Value_USD Country
## Length:2500 Min. : 103 Min. : 1018 Length:2500
## Class :character 1st Qu.:2522 1st Qu.: 26370 Class :character
## Mode :character Median :4935 Median : 51512 Mode :character
## Mean :5010 Mean : 50792
## 3rd Qu.:7570 3rd Qu.: 73731
## Max. :9992 Max. :336629
## Port Transport_Mode Tariff GST
## Length:2500 Length:2500 Min. : 5.003 Min. : 5.002
## Class :character Class :character 1st Qu.: 8.829 1st Qu.: 8.360
## Mode :character Mode :character Median :12.506 Median :11.620
## Mean :12.563 Mean :11.565
## 3rd Qu.:16.330 3rd Qu.:14.795
## Max. :56.152 Max. :49.357
## Exchange_Rate Shipment_Days Delivery_Status Trade_Agreement
## Min. :70.01 Min. : 1.00 Length:2500 Length:2500
## 1st Qu.:73.62 1st Qu.: 8.00 Class :character Class :character
## Median :77.26 Median : 16.00 Mode :character Mode :character
## Mean :77.38 Mean : 15.48
## 3rd Qu.:81.14 3rd Qu.: 23.00
## Max. :84.99 Max. :103.20
## Date Value_INR Profit Loss
## Length:2500 Min. : 73727 Min. : 6550 Min. : 1046
## Class :character 1st Qu.: 2020603 1st Qu.: 220607 1st Qu.: 77587
## Mode :character Median : 3990634 Median : 435482 Median : 176331
## Mean : 3922176 Mean : 486719 Mean : 218837
## 3rd Qu.: 5651695 3rd Qu.: 684530 3rd Qu.: 322383
## Max. :25781161 Max. :1598195 Max. :1925322
## Is_Delayed
## Length:2500
## Class :character
## Mode :character
##
##
## Answer The summary() function provides statistical measures like mean, minimum, maximum, and quartiles.
1.4 Question: What are the column names?
colnames(data)## [1] "Year" "Month" "Product_Category" "Product_Name"
## [5] "Import_Export" "Quantity" "Value_USD" "Country"
## [9] "Port" "Transport_Mode" "Tariff" "GST"
## [13] "Exchange_Rate" "Shipment_Days" "Delivery_Status" "Trade_Agreement"
## [17] "Date" "Value_INR" "Profit" "Loss"
## [21] "Is_Delayed"Explanation:
This shows all variable names present in the dataset.
1.5 Question : Check specific column
data$Country## [1] "China" "USA" "Germany" "Japan" "UK" "Japan" "USA"
## [8] "Germany" "Germany" "USA" "UAE" "Japan" "UAE" "UK"
## [15] "USA" "UK" "Germany" "Germany" "USA" "Japan" "UAE"
## [22] "UAE" "UAE" "Germany" "Japan" "UK" "China" "Germany"
## [29] "China" "USA" "UK" "UAE" "Japan" "Japan" "Germany"
## [36] "China" "USA" "UK" "USA" "UAE" "Germany" "Japan"
## [43] "Germany" "UK" "USA" "China" "China" "Japan" "Germany"
## [50] "China" "UAE" "UAE" "Germany" "Japan" "Japan" "Germany"
## [57] "Germany" "Germany" "Germany" "USA" "UK" "UK" "Japan"
## [64] "Germany" "USA" "China" "UAE" "UK" "UAE" "USA"
## [71] "UK" "UAE" "UAE" "UK" "Germany" "China" "Japan"
## [78] "Japan" "Germany" "USA" "Germany" "UAE" "USA" "Japan"
## [85] "Japan" "Germany" "USA" "UK" "Japan" "Germany" "UK"
## [92] "Japan" "China" "UAE" "Japan" "USA" "Germany" "Germany"
## [99] "China" "USA" "Japan" "UK" "UK" "UAE" "UAE"
## [106] "Germany" "Germany" "Japan" "USA" "Japan" "Japan" "UAE"
## [113] "USA" "Germany" "UAE" "UAE" "China" "UAE" "USA"
## [120] "China" "Japan" "UAE" "USA" "China" "UAE" "UAE"
## [127] "China" "Japan" "Germany" "Japan" "Germany" "Germany" "UAE"
## [134] "Japan" "UK" "China" "Germany" "UAE" "UAE" "Germany"
## [141] "Japan" "Japan" "UAE" "UAE" "Germany" "Japan" "USA"
## [148] "UAE" "UK" "Japan" "UAE" "UK" "UAE" "USA"
## [155] "China" "Japan" "UK" "USA" "UAE" "Germany" "USA"
## [162] "UK" "China" "China" "UK" "Germany" "Germany" "Germany"
## [169] "UAE" "UK" "China" "Germany" "Germany" "Japan" "Germany"
## [176] "China" "China" "UK" "UK" "China" "UK" "USA"
## [183] "UAE" "USA" "China" "USA" "UAE" "China" "USA"
## [190] "Japan" "Germany" "China" "Germany" "Japan" "Japan" "UK"
## [197] "Japan" "Germany" "UK" "Germany" "UAE" "USA" "UAE"
## [204] "Japan" "UAE" "USA" "Japan" "UAE" "UK" "UAE"
## [211] "China" "Germany" "UK" "UK" "UK" "USA" "Japan"
## [218] "UAE" "USA" "UK" "USA" "Japan" "Japan" "USA"
## [225] "China" "USA" "Germany" "Germany" "China" "China" "UK"
## [232] "UK" "UK" "Japan" "Japan" "UAE" "Japan" "China"
## [239] "Japan" "China" "China" "UAE" "Japan" "UAE" "USA"
## [246] "UK" "UAE" "China" "China" "UK" "Germany" "UK"
## [253] "UAE" "UK" "UAE" "Japan" "Japan" "USA" "UAE"
## [260] "USA" "UK" "China" "Germany" "Japan" "UK" "UK"
## [267] "USA" "Germany" "Germany" "UAE" "UAE" "UK" "China"
## [274] "Germany" "Japan" "UAE" "Germany" "UAE" "Germany" "Germany"
## [281] "UAE" "Japan" "UK" "Germany" "UAE" "China" "Japan"
## [288] "UAE" "UK" "China" "Japan" "China" "UK" "USA"
## [295] "Germany" "Japan" "UK" "Japan" "UAE" "China" "UAE"
## [302] "Germany" "UAE" "UK" "USA" "USA" "China" "Germany"
## [309] "Japan" "China" "China" "Japan" "Japan" "Japan" "UAE"
## [316] "China" "Germany" "USA" "China" "USA" "China" "UAE"
## [323] "UAE" "China" "UAE" "Germany" "UAE" "Germany" "China"
## [330] "UK" "Germany" "UAE" "China" "USA" "USA" "Germany"
## [337] "Germany" "Germany" "China" "Japan" "UAE" "UK" "Germany"
## [344] "China" "UAE" "Japan" "UK" "Germany" "UK" "UK"
## [351] "Japan" "China" "China" "UAE" "UAE" "UK" "China"
## [358] "UK" "Germany" "China" "UAE" "USA" "Germany" "UK"
## [365] "UAE" "UK" "UAE" "Japan" "China" "Japan" "UK"
## [372] "UK" "UK" "China" "USA" "Japan" "UK" "China"
## [379] "UAE" "USA" "USA" "UAE" "USA" "Japan" "Japan"
## [386] "USA" "USA" "UK" "China" "China" "China" "China"
## [393] "UAE" "China" "China" "USA" "UAE" "Germany" "UAE"
## [400] "China" "USA" "USA" "Germany" "USA" "Japan" "Germany"
## [407] "UAE" "UK" "UK" "USA" "USA" "Germany" "Japan"
## [414] "Japan" "Germany" "USA" "UAE" "Japan" "UK" "Japan"
## [421] "Japan" "Germany" "Germany" "China" "Japan" "China" "Germany"
## [428] "USA" "Japan" "Germany" "Germany" "UK" "Germany" "UAE"
## [435] "China" "USA" "Japan" "China" "Japan" "UK" "UK"
## [442] "Germany" "UAE" "China" "UAE" "Germany" "USA" "UAE"
## [449] "China" "Germany" "UK" "USA" "China" "USA" "Japan"
## [456] "China" "China" "UAE" "UAE" "UK" "USA" "China"
## [463] "China" "USA" "China" "UAE" "Germany" "USA" "Germany"
## [470] "China" "Japan" "UK" "UK" "USA" "Germany" "UK"
## [477] "Germany" "China" "Japan" "USA" "UAE" "UAE" "UAE"
## [484] "USA" "USA" "USA" "Germany" "Japan" "UK" "UAE"
## [491] "Germany" "China" "UAE" "UK" "Germany" "UAE" "Germany"
## [498] "UAE" "China" "UAE" "UAE" "UK" "UAE" "China"
## [505] "USA" "China" "UK" "UK" "China" "Japan" "UAE"
## [512] "USA" "UK" "UAE" "Japan" "Germany" "Japan" "USA"
## [519] "Japan" "Japan" "USA" "Japan" "UAE" "USA" "China"
## [526] "UAE" "Japan" "Japan" "China" "China" "UK" "USA"
## [533] "UAE" "UAE" "UAE" "UK" "UAE" "UAE" "UK"
## [540] "Japan" "USA" "Germany" "UAE" "Germany" "Japan" "Germany"
## [547] "China" "Japan" "UAE" "Japan" "USA" "Germany" "Germany"
## [554] "China" "USA" "Germany" "China" "UK" "Germany" "China"
## [561] "China" "UK" "China" "USA" "China" "USA" "Germany"
## [568] "Germany" "UAE" "China" "Germany" "Germany" "UK" "Japan"
## [575] "USA" "USA" "UAE" "China" "Japan" "UAE" "UK"
## [582] "USA" "USA" "Germany" "Germany" "USA" "China" "UK"
## [589] "UAE" "UK" "UAE" "UK" "UAE" "UAE" "USA"
## [596] "China" "China" "China" "China" "Germany" "UK" "UAE"
## [603] "UAE" "Germany" "Germany" "Germany" "Germany" "Germany" "Japan"
## [610] "UK" "China" "UK" "UAE" "UK" "China" "USA"
## [617] "UAE" "Germany" "Germany" "UK" "USA" "Germany" "UK"
## [624] "USA" "USA" "USA" "UAE" "Japan" "Japan" "UAE"
## [631] "Japan" "UAE" "UAE" "China" "UK" "USA" "China"
## [638] "China" "UK" "USA" "USA" "UK" "China" "UAE"
## [645] "USA" "USA" "Japan" "Japan" "UK" "Germany" "USA"
## [652] "Germany" "Germany" "UK" "UAE" "UK" "Germany" "UK"
## [659] "USA" "Germany" "UAE" "USA" "UAE" "UK" "UAE"
## [666] "UAE" "China" "Germany" "USA" "USA" "UK" "Germany"
## [673] "Japan" "Germany" "Japan" "UAE" "UAE" "China" "UAE"
## [680] "UK" "China" "China" "Japan" "UAE" "UK" "Germany"
## [687] "China" "UK" "China" "China" "UAE" "UAE" "Japan"
## [694] "Germany" "China" "UAE" "UAE" "China" "China" "Germany"
## [701] "UK" "China" "UAE" "Japan" "UAE" "Germany" "USA"
## [708] "Japan" "UK" "Germany" "Germany" "Japan" "UK" "Germany"
## [715] "UAE" "UAE" "UAE" "Japan" "China" "UAE" "China"
## [722] "China" "UAE" "UAE" "UK" "UK" "China" "USA"
## [729] "UK" "Germany" "UK" "UAE" "Germany" "Japan" "UAE"
## [736] "China" "Germany" "Japan" "China" "USA" "Japan" "UAE"
## [743] "USA" "China" "China" "USA" "Germany" "USA" "Japan"
## [750] "UAE" "UAE" "Japan" "USA" "China" "USA" "UAE"
## [757] "Germany" "Japan" "UK" "China" "UAE" "USA" "USA"
## [764] "Japan" "UAE" "USA" "Japan" "China" "UK" "China"
## [771] "Japan" "Japan" "UK" "USA" "UAE" "UK" "USA"
## [778] "Japan" "China" "USA" "UK" "UK" "UK" "China"
## [785] "UAE" "USA" "UAE" "China" "Germany" "Germany" "China"
## [792] "China" "Germany" "Germany" "Japan" "UAE" "UK" "USA"
## [799] "USA" "China" "USA" "UK" "Japan" "Japan" "Germany"
## [806] "Japan" "USA" "USA" "China" "USA" "Germany" "UAE"
## [813] "USA" "UAE" "USA" "Germany" "UK" "UAE" "China"
## [820] "UAE" "USA" "China" "USA" "UK" "USA" "Japan"
## [827] "China" "Japan" "UK" "UAE" "USA" "Germany" "UAE"
## [834] "Germany" "China" "UAE" "UK" "UAE" "Germany" "China"
## [841] "Japan" "China" "UK" "UK" "UK" "USA" "China"
## [848] "China" "Germany" "UK" "Germany" "China" "USA" "UAE"
## [855] "USA" "USA" "USA" "Germany" "UAE" "China" "Germany"
## [862] "UAE" "UAE" "UK" "UAE" "USA" "China" "UK"
## [869] "Germany" "UK" "UK" "Japan" "China" "Germany" "Japan"
## [876] "Germany" "Germany" "China" "Germany" "UAE" "USA" "USA"
## [883] "USA" "Germany" "UAE" "Japan" "UK" "Germany" "UK"
## [890] "UK" "China" "UAE" "UK" "China" "UK" "Germany"
## [897] "China" "UAE" "Japan" "Japan" "UK" "Germany" "Germany"
## [904] "UK" "UAE" "China" "Germany" "USA" "UK" "Germany"
## [911] "Japan" "UK" "UAE" "USA" "Japan" "UAE" "USA"
## [918] "UAE" "China" "China" "Japan" "Japan" "UK" "China"
## [925] "USA" "China" "Japan" "China" "UAE" "China" "Germany"
## [932] "Germany" "Japan" "Germany" "Japan" "Japan" "UK" "China"
## [939] "UAE" "USA" "UK" "USA" "UK" "China" "China"
## [946] "UAE" "Germany" "UK" "UAE" "Japan" "Germany" "Japan"
## [953] "UK" "UAE" "Japan" "UAE" "Germany" "USA" "UK"
## [960] "UK" "USA" "Japan" "UAE" "UK" "Germany" "Germany"
## [967] "Germany" "Germany" "UAE" "China" "USA" "Japan" "Germany"
## [974] "Germany" "Japan" "Japan" "Germany" "USA" "Germany" "USA"
## [981] "Japan" "USA" "UAE" "Japan" "USA" "Germany" "UAE"
## [988] "USA" "UAE" "China" "Japan" "Germany" "Germany" "UAE"
## [995] "Germany" "UAE" "UK" "Germany" "Japan" "UK" "Germany"
## [1002] "Japan" "Germany" "China" "UK" "UAE" "UK" "China"
## [1009] "UAE" "China" "China" "Japan" "China" "USA" "Japan"
## [1016] "UK" "Germany" "Japan" "UAE" "USA" "UK" "USA"
## [1023] "UAE" "Japan" "UAE" "China" "Japan" "Germany" "Japan"
## [1030] "UAE" "USA" "Japan" "UK" "China" "UAE" "UAE"
## [1037] "Japan" "Germany" "UAE" "Germany" "UAE" "Germany" "China"
## [1044] "UAE" "USA" "Germany" "UAE" "China" "China" "China"
## [1051] "China" "Germany" "China" "USA" "China" "Germany" "Japan"
## [1058] "Germany" "Germany" "UK" "Germany" "USA" "Germany" "Germany"
## [1065] "China" "UAE" "UK" "Japan" "UAE" "Germany" "UK"
## [1072] "UAE" "USA" "UAE" "Germany" "Germany" "Japan" "UAE"
## [1079] "UAE" "USA" "UAE" "Germany" "China" "Germany" "UAE"
## [1086] "USA" "Japan" "China" "Germany" "UK" "Germany" "UAE"
## [1093] "UAE" "Germany" "Japan" "UAE" "Japan" "USA" "Japan"
## [1100] "Germany" "Japan" "USA" "USA" "UK" "China" "USA"
## [1107] "Germany" "UAE" "UK" "Japan" "UAE" "Germany" "UAE"
## [1114] "China" "UAE" "UAE" "Japan" "UK" "Japan" "Germany"
## [1121] "UAE" "Japan" "Japan" "USA" "Japan" "USA" "UK"
## [1128] "Germany" "Japan" "UAE" "Japan" "UAE" "UAE" "Germany"
## [1135] "USA" "Japan" "USA" "Germany" "UK" "UAE" "Germany"
## [1142] "China" "USA" "Germany" "UAE" "USA" "UK" "Germany"
## [1149] "China" "UAE" "China" "China" "China" "China" "Germany"
## [1156] "UK" "UAE" "UAE" "UAE" "USA" "Japan" "China"
## [1163] "Japan" "Germany" "Germany" "Germany" "UAE" "UK" "UK"
## [1170] "USA" "Germany" "USA" "USA" "Germany" "USA" "UAE"
## [1177] "UAE" "UAE" "USA" "UAE" "UK" "China" "UK"
## [1184] "Germany" "UAE" "China" "China" "China" "Japan" "UK"
## [1191] "China" "UK" "China" "Japan" "UK" "USA" "China"
## [1198] "UK" "UK" "USA" "UAE" "UK" "China" "UK"
## [1205] "Japan" "Germany" "UAE" "Japan" "Germany" "China" "UAE"
## [1212] "Germany" "Germany" "UAE" "China" "UK" "China" "Germany"
## [1219] "UAE" "USA" "UAE" "USA" "USA" "Japan" "Japan"
## [1226] "China" "Germany" "UK" "USA" "Japan" "USA" "Japan"
## [1233] "UK" "Germany" "UK" "UAE" "China" "Germany" "Japan"
## [1240] "Germany" "Japan" "Germany" "China" "Germany" "Germany" "China"
## [1247] "China" "USA" "UAE" "UK" "USA" "Germany" "USA"
## [1254] "UK" "USA" "USA" "Germany" "UAE" "Japan" "Japan"
## [1261] "Germany" "UK" "China" "USA" "Germany" "China" "Japan"
## [1268] "China" "USA" "USA" "UK" "Japan" "USA" "USA"
## [1275] "Japan" "USA" "UK" "Japan" "UAE" "UK" "Japan"
## [1282] "Germany" "China" "Germany" "UK" "China" "UK" "China"
## [1289] "China" "UAE" "USA" "Japan" "USA" "UAE" "China"
## [1296] "Germany" "Germany" "Japan" "Germany" "USA" "Germany" "Japan"
## [1303] "Japan" "China" "China" "UK" "USA" "Germany" "USA"
## [1310] "Germany" "UK" "Japan" "China" "UAE" "Germany" "China"
## [1317] "Japan" "Japan" "China" "Germany" "UAE" "China" "Germany"
## [1324] "UAE" "UK" "UK" "UAE" "China" "USA" "Germany"
## [1331] "UK" "Japan" "USA" "UK" "UK" "China" "UAE"
## [1338] "Japan" "Germany" "UAE" "Germany" "UAE" "UK" "UAE"
## [1345] "Germany" "USA" "Japan" "UK" "UK" "UAE" "Germany"
## [1352] "UAE" "Japan" "Germany" "USA" "USA" "UAE" "China"
## [1359] "Japan" "USA" "UAE" "China" "USA" "UK" "Japan"
## [1366] "UAE" "Germany" "Germany" "UK" "Germany" "Germany" "USA"
## [1373] "UK" "Japan" "Japan" "Japan" "Germany" "China" "USA"
## [1380] "China" "UAE" "Japan" "Germany" "Germany" "China" "UK"
## [1387] "Germany" "UK" "Japan" "USA" "China" "Germany" "UAE"
## [1394] "Germany" "USA" "USA" "UK" "UK" "China" "Japan"
## [1401] "UAE" "Japan" "Germany" "Germany" "Japan" "UAE" "UK"
## [1408] "UK" "China" "Japan" "Germany" "UK" "USA" "Japan"
## [1415] "Japan" "China" "China" "UAE" "USA" "Japan" "UAE"
## [1422] "China" "China" "USA" "UK" "China" "Germany" "Japan"
## [1429] "China" "Japan" "Germany" "USA" "UK" "UAE" "Japan"
## [1436] "China" "China" "China" "Japan" "Japan" "China" "UAE"
## [1443] "USA" "Japan" "UAE" "UAE" "China" "USA" "Japan"
## [1450] "UAE" "UAE" "Germany" "Japan" "Germany" "China" "USA"
## [1457] "China" "UAE" "USA" "Germany" "UK" "Germany" "China"
## [1464] "Japan" "UAE" "Germany" "China" "Germany" "UK" "USA"
## [1471] "UK" "UAE" "Germany" "China" "UK" "China" "Germany"
## [1478] "UAE" "UK" "Japan" "Germany" "UAE" "USA" "Germany"
## [1485] "USA" "Germany" "Japan" "Japan" "Japan" "Japan" "Japan"
## [1492] "UK" "UAE" "China" "UK" "China" "Germany" "Germany"
## [1499] "Germany" "USA" "USA" "UK" "China" "Germany" "Germany"
## [1506] "UK" "China" "Germany" "USA" "Germany" "UAE" "USA"
## [1513] "UAE" "Japan" "USA" "Japan" "Germany" "China" "Germany"
## [1520] "Japan" "USA" "UAE" "China" "Japan" "UK" "UK"
## [1527] "Germany" "China" "Japan" "UK" "China" "China" "Japan"
## [1534] "Japan" "UAE" "Germany" "Japan" "China" "Germany" "Japan"
## [1541] "USA" "USA" "China" "UK" "Germany" "UK" "UAE"
## [1548] "USA" "Germany" "China" "USA" "USA" "Germany" "UK"
## [1555] "USA" "UAE" "UAE" "Japan" "UAE" "China" "China"
## [1562] "Japan" "China" "UK" "USA" "UK" "Germany" "USA"
## [1569] "UAE" "UAE" "Japan" "USA" "Germany" "UAE" "Germany"
## [1576] "UK" "Germany" "UK" "Japan" "UAE" "Japan" "China"
## [1583] "Japan" "UAE" "Germany" "USA" "Germany" "Germany" "Germany"
## [1590] "UK" "UK" "USA" "Germany" "Germany" "Japan" "USA"
## [1597] "UK" "China" "China" "UK" "UK" "Japan" "Germany"
## [1604] "UAE" "Germany" "China" "UAE" "Germany" "Germany" "UK"
## [1611] "UAE" "Germany" "UK" "China" "UAE" "China" "China"
## [1618] "Japan" "China" "Japan" "China" "UAE" "UK" "China"
## [1625] "Japan" "USA" "Japan" "UAE" "China" "Japan" "Japan"
## [1632] "UK" "UK" "Germany" "USA" "UAE" "Germany" "China"
## [1639] "China" "China" "Germany" "Japan" "Japan" "Japan" "Japan"
## [1646] "Germany" "Japan" "Japan" "USA" "UAE" "UAE" "UAE"
## [1653] "USA" "Germany" "China" "Germany" "Japan" "Japan" "China"
## [1660] "UK" "China" "Germany" "Germany" "Germany" "China" "USA"
## [1667] "Japan" "China" "Germany" "China" "Japan" "Japan" "USA"
## [1674] "Germany" "UAE" "UAE" "USA" "USA" "China" "Japan"
## [1681] "UK" "Germany" "Germany" "China" "Germany" "USA" "China"
## [1688] "UAE" "Germany" "UK" "UAE" "Germany" "UAE" "China"
## [1695] "USA" "Germany" "USA" "UAE" "USA" "USA" "USA"
## [1702] "UK" "Japan" "China" "China" "Germany" "UAE" "UAE"
## [1709] "Germany" "UK" "USA" "UAE" "Germany" "Germany" "China"
## [1716] "USA" "USA" "China" "Japan" "UK" "Japan" "UAE"
## [1723] "China" "Japan" "USA" "Japan" "Germany" "UAE" "USA"
## [1730] "UK" "China" "UAE" "UK" "UAE" "Japan" "Japan"
## [1737] "USA" "China" "USA" "USA" "UK" "Japan" "UK"
## [1744] "USA" "Japan" "USA" "UK" "USA" "Germany" "UAE"
## [1751] "UK" "USA" "USA" "UK" "China" "China" "UAE"
## [1758] "Japan" "Germany" "USA" "UAE" "UAE" "UK" "China"
## [1765] "Japan" "USA" "China" "China" "Germany" "UAE" "China"
## [1772] "UK" "Japan" "UAE" "USA" "China" "China" "UK"
## [1779] "China" "UK" "UAE" "USA" "USA" "Germany" "Germany"
## [1786] "China" "USA" "Germany" "China" "Japan" "USA" "China"
## [1793] "China" "China" "Japan" "USA" "Japan" "Japan" "USA"
## [1800] "USA" "UK" "Germany" "UAE" "Japan" "USA" "Germany"
## [1807] "Germany" "UK" "UAE" "UAE" "China" "Germany" "Germany"
## [1814] "UK" "USA" "Japan" "UK" "China" "UK" "UAE"
## [1821] "UAE" "Japan" "UK" "China" "UK" "UAE" "USA"
## [1828] "Japan" "UAE" "China" "USA" "USA" "UK" "USA"
## [1835] "UK" "Germany" "USA" "UAE" "USA" "UK" "Japan"
## [1842] "UAE" "China" "UAE" "China" "UK" "Germany" "Germany"
## [1849] "UAE" "Japan" "USA" "UK" "China" "USA" "Germany"
## [1856] "Japan" "UK" "UK" "Japan" "China" "Germany" "UK"
## [1863] "UAE" "China" "USA" "UK" "China" "UK" "UK"
## [1870] "China" "Japan" "Japan" "Japan" "China" "China" "Japan"
## [1877] "UAE" "Germany" "UK" "Germany" "China" "USA" "UK"
## [1884] "Japan" "China" "UK" "UAE" "UK" "UAE" "Germany"
## [1891] "China" "Germany" "China" "China" "Germany" "Japan" "USA"
## [1898] "UK" "China" "Japan" "China" "UK" "UK" "UK"
## [1905] "UAE" "Germany" "Japan" "Japan" "UK" "China" "UK"
## [1912] "UAE" "China" "UK" "Japan" "Japan" "USA" "USA"
## [1919] "UK" "China" "Japan" "USA" "UK" "UK" "Japan"
## [1926] "China" "China" "USA" "China" "Japan" "Japan" "UK"
## [1933] "UK" "Germany" "Japan" "UK" "Germany" "China" "USA"
## [1940] "Japan" "Germany" "China" "UK" "Japan" "Japan" "Germany"
## [1947] "USA" "Germany" "China" "Japan" "Japan" "Germany" "China"
## [1954] "Japan" "Germany" "USA" "UAE" "Germany" "Germany" "USA"
## [1961] "UAE" "UK" "Germany" "China" "UK" "UK" "Germany"
## [1968] "USA" "USA" "Japan" "USA" "UK" "USA" "Japan"
## [1975] "UK" "UAE" "USA" "Japan" "Germany" "Germany" "Japan"
## [1982] "China" "USA" "Germany" "Japan" "UAE" "Germany" "Germany"
## [1989] "China" "UK" "USA" "UK" "Japan" "UAE" "USA"
## [1996] "USA" "Japan" "UK" "Germany" "UK" "Germany" "Japan"
## [2003] "China" "China" "Germany" "USA" "UK" "Germany" "Germany"
## [2010] "UK" "UAE" "USA" "UK" "USA" "USA" "China"
## [2017] "UK" "UK" "USA" "China" "Japan" "USA" "Japan"
## [2024] "Japan" "UAE" "UAE" "UAE" "Germany" "UK" "Germany"
## [2031] "USA" "UAE" "USA" "Germany" "Japan" "Germany" "Japan"
## [2038] "USA" "UK" "USA" "Japan" "Japan" "Japan" "Japan"
## [2045] "UAE" "Germany" "UK" "China" "Japan" "UAE" "USA"
## [2052] "USA" "China" "Japan" "UAE" "China" "Germany" "UAE"
## [2059] "USA" "Japan" "Germany" "China" "Germany" "UAE" "UK"
## [2066] "China" "China" "Germany" "Germany" "Japan" "UAE" "China"
## [2073] "Germany" "Germany" "UAE" "USA" "USA" "UAE" "USA"
## [2080] "UAE" "UK" "UAE" "Japan" "UAE" "UAE" "UAE"
## [2087] "USA" "USA" "Germany" "UK" "China" "Germany" "UK"
## [2094] "Germany" "China" "USA" "USA" "UAE" "USA" "Germany"
## [2101] "USA" "UAE" "USA" "Japan" "UK" "Germany" "UAE"
## [2108] "Japan" "Germany" "UAE" "USA" "UAE" "Germany" "UK"
## [2115] "Germany" "UK" "USA" "UAE" "China" "USA" "USA"
## [2122] "Germany" "UK" "USA" "UAE" "UK" "China" "UK"
## [2129] "Germany" "Japan" "Japan" "USA" "Germany" "Germany" "Germany"
## [2136] "UAE" "Germany" "Japan" "UAE" "USA" "UAE" "UAE"
## [2143] "UK" "USA" "Germany" "UK" "UK" "USA" "Germany"
## [2150] "UK" "China" "UAE" "UK" "Japan" "USA" "USA"
## [2157] "Japan" "Germany" "Japan" "China" "Japan" "UK" "Germany"
## [2164] "China" "USA" "UAE" "UAE" "China" "Germany" "China"
## [2171] "Germany" "China" "UAE" "Japan" "USA" "Japan" "Japan"
## [2178] "USA" "Germany" "UK" "UK" "UK" "China" "UAE"
## [2185] "Germany" "Japan" "Japan" "China" "Germany" "UAE" "China"
## [2192] "Japan" "Germany" "UK" "Germany" "UK" "Germany" "Japan"
## [2199] "UK" "USA" "USA" "UAE" "China" "UK" "China"
## [2206] "UAE" "China" "China" "UK" "China" "Japan" "USA"
## [2213] "China" "UK" "Japan" "Germany" "USA" "UK" "UAE"
## [2220] "UAE" "UAE" "China" "UAE" "Germany" "Japan" "UAE"
## [2227] "UAE" "China" "UK" "UK" "China" "Germany" "UAE"
## [2234] "Germany" "China" "China" "UK" "UAE" "China" "UK"
## [2241] "Japan" "Japan" "USA" "Germany" "USA" "Japan" "Germany"
## [2248] "UAE" "UK" "China" "UAE" "Germany" "UK" "USA"
## [2255] "UAE" "Germany" "China" "Germany" "USA" "Japan" "UAE"
## [2262] "USA" "Germany" "Germany" "UAE" "Japan" "UK" "UK"
## [2269] "UAE" "USA" "China" "Germany" "USA" "Japan" "Germany"
## [2276] "China" "UK" "Japan" "Japan" "Germany" "Germany" "Germany"
## [2283] "USA" "UK" "UAE" "Germany" "Japan" "USA" "UK"
## [2290] "Germany" "UK" "UAE" "Germany" "Japan" "UAE" "China"
## [2297] "China" "Germany" "UAE" "Germany" "China" "Germany" "Germany"
## [2304] "Japan" "USA" "Japan" "USA" "China" "USA" "USA"
## [2311] "USA" "China" "UK" "USA" "USA" "UK" "Japan"
## [2318] "UAE" "China" "China" "UAE" "UAE" "UK" "UAE"
## [2325] "USA" "USA" "Germany" "Germany" "USA" "China" "USA"
## [2332] "Germany" "Japan" "USA" "UAE" "UK" "Japan" "UK"
## [2339] "USA" "Germany" "UK" "UAE" "Germany" "Japan" "UAE"
## [2346] "USA" "UAE" "China" "UAE" "Japan" "USA" "UK"
## [2353] "USA" "Japan" "Japan" "USA" "Germany" "China" "UK"
## [2360] "UAE" "Japan" "China" "Japan" "UK" "UAE" "Japan"
## [2367] "China" "USA" "UK" "USA" "UAE" "Germany" "Germany"
## [2374] "USA" "Germany" "Germany" "Japan" "USA" "UAE" "Japan"
## [2381] "UK" "Germany" "China" "UAE" "UAE" "UAE" "Germany"
## [2388] "UAE" "Germany" "UAE" "Japan" "UK" "USA" "USA"
## [2395] "Germany" "UAE" "Japan" "China" "UK" "USA" "China"
## [2402] "USA" "Japan" "China" "UAE" "Germany" "UAE" "USA"
## [2409] "UAE" "UAE" "Japan" "USA" "Japan" "UK" "China"
## [2416] "Germany" "USA" "UAE" "China" "USA" "China" "Japan"
## [2423] "USA" "UK" "Germany" "USA" "UAE" "UAE" "China"
## [2430] "USA" "China" "Germany" "Japan" "Japan" "UAE" "Japan"
## [2437] "UK" "China" "UAE" "USA" "Japan" "Japan" "UK"
## [2444] "USA" "Japan" "UK" "Japan" "Germany" "China" "UK"
## [2451] "UK" "UAE" "UK" "UAE" "Germany" "Germany" "USA"
## [2458] "China" "Germany" "Germany" "Germany" "Japan" "Japan" "UAE"
## [2465] "Germany" "Germany" "Germany" "UAE" "USA" "Japan" "UAE"
## [2472] "China" "UAE" "UK" "Japan" "China" "China" "China"
## [2479] "UK" "UK" "Germany" "UAE" "Japan" "USA" "UK"
## [2486] "Germany" "Germany" "USA" "UAE" "USA" "China" "Germany"
## [2493] "Germany" "USA" "UAE" "UAE" "UK" "China" "China"
## [2500] "UAE"2 Level: Data Cleaning and Preparation
2.1 Question: Are there any missing values in the dataset?
colSums(is.na(data))## Year Month Product_Category Product_Name
## 0 0 0 0
## Import_Export Quantity Value_USD Country
## 0 0 0 0
## Port Transport_Mode Tariff GST
## 0 0 0 0
## Exchange_Rate Shipment_Days Delivery_Status Trade_Agreement
## 0 0 0 0
## Date Value_INR Profit Loss
## 0 0 0 0
## Is_Delayed
## 0Explanation: This checks missing values in each column of the dataset.
2.2 Question: Convert categorical variables into factors
data$Month <- as.factor(data$Month)
data$Product_Category <- as.factor(data$Product_Category)
data$Import_Export <- as.factor(data$Import_Export)
data$Country <- as.factor(data$Country)
head(data)## Year Month Product_Category Product_Name Import_Export Quantity Value_USD
## 1 2024 October Agriculture Medicine Export 5414 72245.784
## 2 2023 April Textile Cotton Export 5189 24614.994
## 3 2024 March Automobile Cotton Import 415 7532.450
## 4 2020 December Electronics Medicine Export 6108 9767.587
## 5 2022 April Automobile Mobile Import 2951 72703.563
## 6 2020 March Agriculture Cotton Export 142 71831.337
## Country Port Transport_Mode Tariff GST Exchange_Rate
## 1 China Delhi Land 8.393855 15.633720 72.10798
## 2 USA Delhi Air 19.930770 12.699521 82.20563
## 3 Germany Kandla Air 5.384847 5.309774 80.85602
## 4 Japan Chennai Land 10.659926 11.137832 84.70135
## 5 UK Kandla Land 14.464991 5.959429 75.20845
## 6 Japan Mumbai Air 5.191173 5.838508 70.25781
## Shipment_Days Delivery_Status Trade_Agreement Date Value_INR Profit
## 1 21 Delayed Non-FTA 24-03-2019 5209497.3 692534.55
## 2 18 On Time Non-FTA 03-07-2022 2023491.1 393206.54
## 3 29 On Time FTA 11-03-2018 609043.9 94639.13
## 4 26 On Time FTA 05-08-2021 827327.7 90860.20
## 5 18 Delayed Non-FTA 07-08-2019 5467922.5 588212.45
## 6 14 On Time Non-FTA 09-01-2022 5046712.2 851753.59
## Loss Is_Delayed
## 1 131463.95 True
## 2 147679.02 False
## 3 31589.87 False
## 4 10806.93 False
## 5 229675.60 True
## 6 363622.75 FalseExplanation: Categorical variables are converted into factors for better analysis.
2.3 Question: Create a new variable (Profit Margin)
data$Profit_Margin <- data$Profit / data$Value_INR
head(data)## Year Month Product_Category Product_Name Import_Export Quantity Value_USD
## 1 2024 October Agriculture Medicine Export 5414 72245.784
## 2 2023 April Textile Cotton Export 5189 24614.994
## 3 2024 March Automobile Cotton Import 415 7532.450
## 4 2020 December Electronics Medicine Export 6108 9767.587
## 5 2022 April Automobile Mobile Import 2951 72703.563
## 6 2020 March Agriculture Cotton Export 142 71831.337
## Country Port Transport_Mode Tariff GST Exchange_Rate
## 1 China Delhi Land 8.393855 15.633720 72.10798
## 2 USA Delhi Air 19.930770 12.699521 82.20563
## 3 Germany Kandla Air 5.384847 5.309774 80.85602
## 4 Japan Chennai Land 10.659926 11.137832 84.70135
## 5 UK Kandla Land 14.464991 5.959429 75.20845
## 6 Japan Mumbai Air 5.191173 5.838508 70.25781
## Shipment_Days Delivery_Status Trade_Agreement Date Value_INR Profit
## 1 21 Delayed Non-FTA 24-03-2019 5209497.3 692534.55
## 2 18 On Time Non-FTA 03-07-2022 2023491.1 393206.54
## 3 29 On Time FTA 11-03-2018 609043.9 94639.13
## 4 26 On Time FTA 05-08-2021 827327.7 90860.20
## 5 18 Delayed Non-FTA 07-08-2019 5467922.5 588212.45
## 6 14 On Time Non-FTA 09-01-2022 5046712.2 851753.59
## Loss Is_Delayed Profit_Margin
## 1 131463.95 True 0.1329369
## 2 147679.02 False 0.1943209
## 3 31589.87 False 0.1553897
## 4 10806.93 False 0.1098237
## 5 229675.60 True 0.1075751
## 6 363622.75 False 0.1687740Explanation: A new variable is created to analyze profitability.
2.4 Question: Replace delayed status with logical values
data$Is_Delayed <- data$Delivery_Status == "Delayed"
head(data)## Year Month Product_Category Product_Name Import_Export Quantity Value_USD
## 1 2024 October Agriculture Medicine Export 5414 72245.784
## 2 2023 April Textile Cotton Export 5189 24614.994
## 3 2024 March Automobile Cotton Import 415 7532.450
## 4 2020 December Electronics Medicine Export 6108 9767.587
## 5 2022 April Automobile Mobile Import 2951 72703.563
## 6 2020 March Agriculture Cotton Export 142 71831.337
## Country Port Transport_Mode Tariff GST Exchange_Rate
## 1 China Delhi Land 8.393855 15.633720 72.10798
## 2 USA Delhi Air 19.930770 12.699521 82.20563
## 3 Germany Kandla Air 5.384847 5.309774 80.85602
## 4 Japan Chennai Land 10.659926 11.137832 84.70135
## 5 UK Kandla Land 14.464991 5.959429 75.20845
## 6 Japan Mumbai Air 5.191173 5.838508 70.25781
## Shipment_Days Delivery_Status Trade_Agreement Date Value_INR Profit
## 1 21 Delayed Non-FTA 24-03-2019 5209497.3 692534.55
## 2 18 On Time Non-FTA 03-07-2022 2023491.1 393206.54
## 3 29 On Time FTA 11-03-2018 609043.9 94639.13
## 4 26 On Time FTA 05-08-2021 827327.7 90860.20
## 5 18 Delayed Non-FTA 07-08-2019 5467922.5 588212.45
## 6 14 On Time Non-FTA 09-01-2022 5046712.2 851753.59
## Loss Is_Delayed Profit_Margin
## 1 131463.95 TRUE 0.1329369
## 2 147679.02 FALSE 0.1943209
## 3 31589.87 FALSE 0.1553897
## 4 10806.93 FALSE 0.1098237
## 5 229675.60 TRUE 0.1075751
## 6 363622.75 FALSE 0.16877402.5 Question: Detect Outliers using IQR Method
Q1 <- quantile(data$Value_INR, 0.25, na.rm = TRUE)
Q3 <- quantile(data$Value_INR, 0.75, na.rm = TRUE)
IQR_val <- IQR(data$Value_INR, na.rm = TRUE)
lower <- Q1 - 1.5 * IQR_val
upper <- Q3 + 1.5 * IQR_val
outliers <- data$Value_INR[data$Value_INR < lower | data$Value_INR > upper]
outliers## [1] 25781161Explanation Identifies extreme values beyond normal range.
2.6 Question: Removing outliers
# Remove outliers
data <- data[data$Value_INR >= lower & data$Value_INR <= upper, ]
# Check result
summary(data$Value_INR)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 73727 2019441 3989931 3913429 5650065 8322759Explanation This removes all values outside the IQR range.
3 Level : Data Extraction & Filtering
3.1 Question: Which are the top 10 countries with highest total trade value?
data %>%
group_by(Country) %>%
summarise(Total = sum(Value_INR)) %>%
arrange(desc(Total)) %>%
head(10)## # A tibble: 6 × 2
## Country Total
## <fct> <dbl>
## 1 Germany 1767492818.
## 2 UAE 1699138763.
## 3 China 1654206967.
## 4 USA 1577809373.
## 5 Japan 1576420701.
## 6 UK 1504591281.Explanation: This groups the data by country and calculates total trade value, then sorts to find top 10 countries.
3.2 Question: Which product category has the highest trade value?
data %>%
group_by(Product_Category) %>%
summarise(Total = sum(Value_INR)) %>%
arrange(desc(Total))## # A tibble: 5 × 2
## Product_Category Total
## <fct> <dbl>
## 1 Automobile 2052192223.
## 2 Pharma 1978667296.
## 3 Agriculture 1939844243.
## 4 Electronics 1913677902.
## 5 Textile 1895278240.Explanation: This identifies which product category contributes the most to trade. ### Question: What are the top 10 highest value transactions?
data %>%
arrange(desc(Value_INR)) %>%
head(10)## Year Month Product_Category Product_Name Import_Export Quantity Value_USD
## 1 2018 October Textile Car Export 2028 98041.47
## 2 2024 January Textile Wheat Import 7686 99135.20
## 3 2020 March Textile Medicine Import 9953 99081.53
## 4 2021 October Automobile Car Import 6302 99028.62
## 5 2019 May Pharma Mobile Import 3772 97161.84
## 6 2024 August Agriculture Car Export 1568 97885.58
## 7 2018 June Agriculture Car Import 2747 97456.06
## 8 2022 March Agriculture Wheat Export 4166 96051.96
## 9 2023 December Pharma Medicine Export 2109 96772.86
## 10 2020 October Automobile Mobile Export 3512 96484.52
## Country Port Transport_Mode Tariff GST Exchange_Rate
## 1 UAE Delhi Land 11.174415 9.078902 84.89018
## 2 Germany Kandla Sea 7.164945 10.042625 83.75195
## 3 USA Kandla Air 19.440984 11.026154 83.45255
## 4 China Mumbai Sea 17.887226 10.400409 83.30403
## 5 Japan Kolkata Air 10.713367 14.963586 84.50883
## 6 Japan Delhi Air 16.545236 11.897590 83.72937
## 7 China Chennai Land 16.341921 10.067352 83.69293
## 8 UAE Kandla Land 16.396022 10.803892 84.78803
## 9 China Mumbai Air 11.203306 15.247109 84.09672
## 10 Japan Mumbai Land 18.850484 5.219995 84.23356
## Shipment_Days Delivery_Status Trade_Agreement Date Value_INR Profit
## 1 19 Delayed Non-FTA 04-01-2018 8322759 1566511.2
## 2 19 Delayed Non-FTA 18-07-2019 8302767 1348056.7
## 3 27 Delayed FTA 16-10-2024 8268606 667116.1
## 4 29 On Time FTA 06-12-2023 8249483 1490473.4
## 5 24 On Time Non-FTA 04-01-2024 8211033 1318388.4
## 6 11 On Time FTA 12-07-2023 8195898 693509.6
## 7 29 On Time FTA 22-05-2019 8156384 1000770.7
## 8 21 Delayed Non-FTA 14-02-2023 8144056 470957.2
## 9 29 On Time FTA 12-11-2024 8138280 441052.3
## 10 4 On Time FTA 12-02-2021 8127235 1548634.1
## Loss Is_Delayed Profit_Margin
## 1 140446.5 TRUE 0.18822019
## 2 607842.7 TRUE 0.16236235
## 3 668617.4 TRUE 0.08068060
## 4 686439.8 FALSE 0.18067476
## 5 480604.3 FALSE 0.16056303
## 6 800543.0 FALSE 0.08461667
## 7 564227.4 FALSE 0.12269784
## 8 537980.1 TRUE 0.05782834
## 9 453476.4 FALSE 0.05419478
## 10 719448.9 FALSE 0.19054871Explanation: Sorts dataset by highest trade value and selects top 10 transactions.
3.3 Question: Which ports handle the most trade?
data %>%
group_by(Port) %>%
summarise(Total = sum(Value_INR)) %>%
arrange(desc(Total))## # A tibble: 5 × 2
## Port Total
## <chr> <dbl>
## 1 Kandla 2104047716.
## 2 Kolkata 2054876710.
## 3 Chennai 1930921935.
## 4 Delhi 1920695715.
## 5 Mumbai 1769117827.Explanation: Shows which ports handle the highest trade volume.
3.4 Question: Filter transactions where value is greater than 50,00,000 INR
data %>%
filter(Value_INR > 5000000) %>%
select(Country, Product_Category, Import_Export, Value_INR, Value_USD)## Country Product_Category Import_Export Value_INR Value_USD
## 1 China Agriculture Export 5209497 72245.78
## 2 UK Automobile Import 5467923 72703.56
## 3 Japan Agriculture Export 5046712 71831.34
## 4 USA Automobile Import 6639976 79679.16
## 5 Germany Agriculture Export 7450595 98653.15
## 6 USA Pharma Import 5364118 73066.92
## 7 Japan Electronics Import 7352062 99474.30
## 8 UAE Pharma Import 6131783 85738.58
## 9 Germany Pharma Export 6734334 94272.21
## 10 Japan Pharma Import 7431622 90548.87
## 11 Germany Electronics Export 5502150 67594.43
## 12 Japan Textile Import 6754290 90083.97
## 13 China Pharma Export 6196493 79725.53
## 14 UK Pharma Export 6235478 76472.60
## 15 Japan Pharma Export 5286869 64699.75
## 16 Germany Automobile Import 5140527 63674.56
## 17 USA Textile Import 6572657 80995.94
## 18 UAE Pharma Export 7432948 99039.52
## 19 Japan Pharma Export 5248926 70212.48
## 20 China Automobile Export 5872498 79831.74
## 21 Germany Textile Export 5367410 74815.05
## 22 UAE Textile Export 6789193 83824.56
## 23 Japan Agriculture Import 5094738 61875.68
## 24 Germany Automobile Export 7431460 99027.10
## 25 USA Electronics Export 5086466 67431.34
## 26 UK Electronics Import 5009040 67073.49
## 27 Japan Electronics Import 6009190 74478.97
## 28 UK Automobile Import 5267957 64850.05
## 29 UK Electronics Export 7613959 92244.14
## 30 Germany Agriculture Import 5348212 68771.42
## 31 China Pharma Import 6130481 73151.36
## 32 Germany Textile Import 8302767 99135.20
## 33 USA Textile Import 7528670 92168.64
## 34 Japan Automobile Export 6756820 81780.28
## 35 UK Automobile Export 7882698 93948.95
## 36 China Electronics Import 6868979 84095.67
## 37 UAE Automobile Import 6928525 93081.55
## 38 China Textile Export 7531622 99312.89
## 39 UK Electronics Import 7105022 85577.89
## 40 UK Pharma Export 6877698 97282.66
## 41 UAE Pharma Import 6452110 90744.14
## 42 UAE Automobile Export 5904866 83802.34
## 43 Germany Pharma Export 5090714 61425.03
## 44 Germany Agriculture Export 6797099 84389.82
## 45 UAE Textile Export 5011902 64632.19
## 46 UAE Pharma Export 5356320 72136.18
## 47 UAE Automobile Import 6977873 95237.76
## 48 Japan Textile Import 6198179 77280.99
## 49 Germany Automobile Export 7465737 96712.13
## 50 Japan Agriculture Import 7670872 96093.28
## 51 Germany Electronics Import 5896746 81478.39
## 52 Germany Textile Export 5352109 70253.25
## 53 UAE Textile Export 5866382 76305.67
## 54 UK Pharma Import 5338704 67172.99
## 55 UAE Pharma Import 5638420 79314.63
## 56 UAE Pharma Export 6548002 80001.81
## 57 Japan Textile Import 5945364 84791.37
## 58 Japan Automobile Import 5307816 74555.49
## 59 UK Agriculture Import 5508723 67747.95
## 60 China Pharma Export 6949687 82396.38
## 61 Japan Electronics Export 7976310 93853.34
## 62 UK Textile Export 5042348 65070.42
## 63 UAE Pharma Import 6749021 87930.28
## 64 Germany Agriculture Export 5678954 68785.87
## 65 USA Automobile Import 6741613 89008.74
## 66 UK Pharma Import 5117035 63282.23
## 67 Germany Textile Export 6814248 87048.91
## 68 China Textile Export 7089790 99790.81
## 69 China Pharma Import 6830982 85218.35
## 70 China Electronics Import 6975930 85194.81
## 71 Japan Agriculture Export 6491020 76926.72
## 72 UK Electronics Import 5301314 65624.30
## 73 UAE Agriculture Import 6293782 74587.58
## 74 UAE Electronics Export 6281717 85678.69
## 75 UAE Automobile Export 6084498 83679.21
## 76 Germany Agriculture Import 5016665 60672.96
## 77 USA Agriculture Export 5900015 83842.63
## 78 Japan Pharma Export 6421442 88734.01
## 79 UAE Electronics Import 5207408 62300.00
## 80 Japan Agriculture Import 7047662 89671.81
## 81 USA Electronics Export 6674431 82980.23
## 82 China Agriculture Import 5353430 69605.30
## 83 USA Agriculture Import 6377618 88478.25
## 84 Germany Automobile Export 7254971 88773.41
## 85 China Textile Export 5948678 70692.37
## 86 UK Pharma Import 5623460 74496.42
## 87 Japan Electronics Import 5922806 75911.35
## 88 Japan Agriculture Import 5174794 72660.72
## 89 China Agriculture Import 7508674 98006.84
## 90 USA Agriculture Export 6953137 85614.98
## 91 China Automobile Export 6970675 84699.54
## 92 UAE Pharma Import 5441620 69335.65
## 93 UK Agriculture Export 6788625 94073.69
## 94 UAE Agriculture Import 5787426 73757.98
## 95 Japan Textile Import 7790980 97484.80
## 96 Japan Agriculture Export 6838661 94261.12
## 97 UAE Electronics Import 6291938 87830.61
## 98 UK Automobile Import 5021846 60718.41
## 99 UK Agriculture Export 5157253 61666.26
## 100 Germany Electronics Export 5721514 67399.02
## 101 UAE Pharma Export 6479421 76937.61
## 102 China Automobile Import 5209133 72285.07
## 103 UAE Textile Import 5503613 77421.75
## 104 Germany Automobile Export 5528162 66261.97
## 105 UK Automobile Import 7073011 90388.78
## 106 China Agriculture Export 6776788 83520.37
## 107 Japan Automobile Import 7512832 97502.57
## 108 UAE Automobile Import 6512912 82823.60
## 109 UK Electronics Export 5751404 68631.64
## 110 Germany Agriculture Import 5510699 75982.99
## 111 USA Pharma Export 5199563 71312.47
## 112 China Automobile Import 8033195 98719.12
## 113 Germany Automobile Export 5151098 60976.64
## 114 China Automobile Import 6041133 71307.36
## 115 China Textile Import 5562740 69964.01
## 116 UAE Automobile Export 6961691 89314.49
## 117 China Automobile Export 6801805 86625.94
## 118 USA Agriculture Export 5433927 68775.65
## 119 China Automobile Export 6203906 79136.25
## 120 UAE Textile Export 7187959 94070.29
## 121 Japan Electronics Import 6503465 91844.20
## 122 China Automobile Export 5709600 75160.52
## 123 China Agriculture Import 6721440 92112.45
## 124 UAE Agriculture Import 6096675 82324.13
## 125 UK Agriculture Export 6987878 99405.94
## 126 China Textile Import 6721414 85686.20
## 127 UK Electronics Export 5460116 64266.16
## 128 USA Agriculture Import 6285518 84059.23
## 129 Japan Pharma Import 6361539 78477.78
## 130 UK Electronics Import 5188570 70534.82
## 131 USA Agriculture Import 5348047 73891.10
## 132 USA Electronics Export 6328989 74922.00
## 133 USA Pharma Import 6794646 81614.79
## 134 USA Textile Export 5021047 65249.92
## 135 USA Electronics Import 8102374 96650.37
## 136 China Electronics Export 5005827 63009.60
## 137 China Agriculture Export 6112803 81379.38
## 138 UAE Textile Import 5167792 65964.62
## 139 USA Automobile Import 6353301 84022.91
## 140 USA Electronics Export 7024899 92722.51
## 141 Japan Automobile Export 5363809 69864.02
## 142 UK Agriculture Export 6941500 86092.44
## 143 USA Textile Import 7113059 98718.44
## 144 USA Agriculture Export 6315060 88256.05
## 145 Japan Pharma Export 5463583 66710.71
## 146 UK Textile Import 5383328 64419.94
## 147 Japan Textile Export 5930263 71104.51
## 148 Germany Automobile Export 5964024 77483.28
## 149 China Pharma Import 5650815 73180.27
## 150 Germany Textile Import 6505555 92504.55
## 151 UK Textile Import 7549657 89766.75
## 152 China Agriculture Export 6978187 91035.14
## 153 USA Automobile Export 5100021 61384.11
## 154 China Electronics Import 7066340 94043.65
## 155 Germany Agriculture Export 6924130 89459.23
## 156 USA Pharma Import 5402645 66797.09
## 157 China Automobile Import 5455279 64778.44
## 158 China Automobile Export 5517549 67769.20
## 159 China Textile Export 5515047 73027.24
## 160 China Electronics Export 6144784 85065.55
## 161 USA Agriculture Export 5724222 75951.01
## 162 Japan Electronics Export 5441981 75529.54
## 163 UK Automobile Import 6758196 88834.03
## 164 USA Electronics Import 6729471 91103.66
## 165 Germany Automobile Import 6669833 91980.09
## 166 UK Agriculture Export 7458863 99393.53
## 167 USA Pharma Import 5761450 71570.24
## 168 UK Electronics Import 5860518 71471.10
## 169 UAE Agriculture Import 6672740 80178.69
## 170 UAE Textile Export 6806277 89674.37
## 171 USA Automobile Import 6628311 90780.74
## 172 UK Pharma Import 7785332 95130.73
## 173 UK Textile Export 5324273 69522.22
## 174 China Pharma Export 5364006 65147.22
## 175 UAE Automobile Import 7988732 96917.39
## 176 UK Electronics Import 5325566 73031.86
## 177 China Pharma Export 5412392 73733.48
## 178 UAE Textile Import 7588657 93595.98
## 179 Japan Automobile Import 5121545 71401.13
## 180 China Pharma Export 7033988 89271.02
## 181 UK Agriculture Export 5346972 73957.50
## 182 UAE Automobile Export 6460874 85380.28
## 183 UAE Pharma Import 6002228 80124.97
## 184 USA Automobile Export 5282878 63430.17
## 185 China Pharma Import 5804609 74396.53
## 186 Japan Agriculture Export 7865145 94144.60
## 187 Japan Automobile Export 7679511 96541.81
## 188 USA Pharma Export 6641712 86682.95
## 189 Germany Pharma Export 7976411 98231.48
## 190 USA Automobile Import 6671564 87596.16
## 191 UAE Agriculture Export 8144056 96051.96
## 192 Germany Electronics Export 7215883 85064.02
## 193 Japan Agriculture Import 7339643 99095.88
## 194 USA Textile Import 5560817 66050.70
## 195 USA Agriculture Export 5971465 83628.11
## 196 Germany Pharma Import 6878206 83140.79
## 197 UAE Automobile Export 6705999 92814.45
## 198 UK Pharma Import 5256502 70349.72
## 199 UAE Automobile Export 6731639 87234.29
## 200 UK Electronics Export 5494465 75131.27
## 201 China Pharma Import 7400528 94477.90
## 202 China Pharma Import 7736035 97042.17
## 203 Germany Agriculture Export 7719293 91480.56
## 204 Germany Textile Import 6120742 80182.55
## 205 UAE Automobile Export 5073724 62868.11
## 206 Germany Agriculture Export 5191454 65930.75
## 207 UK Pharma Export 5218980 63322.76
## 208 USA Automobile Import 5974985 85226.30
## 209 UK Electronics Export 6156838 83161.61
## 210 USA Agriculture Export 7198666 89755.75
## 211 USA Textile Export 5083044 67580.01
## 212 USA Automobile Import 6105548 75683.12
## 213 Japan Automobile Import 5468165 67584.43
## 214 UAE Automobile Import 5702815 78029.09
## 215 UAE Pharma Export 6895990 90443.22
## 216 UAE Automobile Import 7665694 97576.51
## 217 UK Pharma Import 7126769 84751.79
## 218 USA Textile Export 5467979 73130.88
## 219 China Pharma Export 6136375 78349.70
## 220 UAE Electronics Export 5757843 71427.29
## 221 USA Textile Export 5877249 76115.70
## 222 USA Agriculture Export 7647720 97394.57
## 223 Germany Textile Export 5866208 81277.89
## 224 UK Agriculture Import 7366949 88904.10
## 225 UK Agriculture Export 5292964 66071.70
## 226 USA Electronics Export 7861517 99426.32
## 227 UAE Textile Import 5059475 72038.85
## 228 UAE Electronics Export 6082027 81294.94
## 229 UAE Automobile Export 5613004 78242.29
## 230 China Pharma Export 6317026 83714.90
## 231 Germany Pharma Import 5845184 73987.99
## 232 Germany Automobile Export 6033564 81573.09
## 233 UAE Electronics Import 6372264 81815.09
## 234 UAE Electronics Import 5970167 76842.39
## 235 China Agriculture Import 5598826 69608.30
## 236 Germany Automobile Import 6372500 89431.06
## 237 UK Textile Export 6277622 87652.08
## 238 UK Electronics Export 5179954 72289.39
## 239 Germany Pharma Export 5025232 69002.14
## 240 Japan Electronics Export 5435440 71444.99
## 241 UAE Pharma Export 5645491 67111.40
## 242 UAE Agriculture Import 7554278 90886.29
## 243 USA Pharma Import 6217024 73401.91
## 244 Germany Textile Export 7408709 89782.74
## 245 Germany Pharma Import 6084964 84610.31
## 246 Japan Pharma Import 6571340 87809.87
## 247 China Pharma Import 6720885 90107.56
## 248 Germany Electronics Export 7430025 92812.04
## 249 UAE Electronics Export 6127088 73596.09
## 250 USA Automobile Export 6967064 91969.95
## 251 China Automobile Import 6506419 83113.55
## 252 USA Automobile Export 6864827 95288.45
## 253 China Textile Import 5866160 82857.34
## 254 Japan Electronics Export 7226783 87462.16
## 255 UK Textile Import 6441862 78637.64
## 256 UAE Automobile Import 5119403 62025.33
## 257 USA Automobile Export 8056302 98452.98
## 258 UAE Pharma Export 7759249 98658.70
## 259 USA Electronics Export 5034587 63715.64
## 260 Japan Agriculture Export 7547733 97614.53
## 261 China Textile Export 5222746 64484.44
## 262 UAE Automobile Export 5468884 69002.57
## 263 China Textile Import 7817339 99906.04
## 264 USA Automobile Export 6194030 88201.43
## 265 UK Agriculture Export 5054021 64048.85
## 266 China Agriculture Export 5052658 61410.10
## 267 China Pharma Import 6239192 76107.71
## 268 Germany Automobile Import 6250780 80659.74
## 269 Germany Agriculture Export 7261236 92642.01
## 270 Japan Agriculture Export 8195898 97885.58
## 271 UAE Electronics Export 6521985 83388.92
## 272 UK Textile Import 6625953 91843.77
## 273 USA Textile Import 6077679 83280.48
## 274 USA Textile Import 6502377 77282.33
## 275 China Automobile Import 7825730 99756.63
## 276 Japan Pharma Import 7055994 89272.69
## 277 USA Pharma Import 6355331 77262.21
## 278 USA Pharma Export 7253334 95394.16
## 279 Germany Automobile Export 6206606 86459.80
## 280 USA Textile Import 6650051 87587.41
## 281 UAE Electronics Import 5608751 70635.62
## 282 USA Pharma Import 5723910 71695.56
## 283 UK Automobile Import 6955849 85965.46
## 284 China Automobile Export 7188115 84575.62
## 285 UAE Electronics Export 5931984 71652.79
## 286 USA Pharma Import 7336587 90916.89
## 287 UK Textile Import 7971793 96261.13
## 288 China Agriculture Import 6207917 74788.49
## 289 UK Textile Import 7270426 87147.80
## 290 UAE Electronics Export 6538532 79470.60
## 291 USA Electronics Import 5277620 70092.61
## 292 Germany Agriculture Import 6949820 96772.46
## 293 China Pharma Export 6059136 72255.46
## 294 UAE Agriculture Import 5585382 65943.37
## 295 Japan Electronics Import 5574813 73349.14
## 296 China Agriculture Import 6413941 89070.03
## 297 UK Textile Export 6646862 81585.42
## 298 USA Electronics Import 6054127 83933.59
## 299 Germany Electronics Export 6752575 90854.23
## 300 Germany Pharma Import 7019603 99486.19
## 301 USA Agriculture Import 5583663 68032.15
## 302 USA Automobile Export 5658761 79588.14
## 303 USA Electronics Import 5604804 68238.93
## 304 Germany Pharma Import 5975620 80007.06
## 305 UAE Textile Export 7002210 90533.45
## 306 UK Electronics Export 8095160 96793.82
## 307 UK Agriculture Import 7938696 96427.27
## 308 UK Automobile Import 6542535 86829.29
## 309 UK Agriculture Export 5532982 67434.90
## 310 Japan Textile Import 6240826 81265.03
## 311 China Pharma Export 7374003 86905.62
## 312 Germany Electronics Export 5209812 74006.73
## 313 Germany Electronics Export 6163974 75716.46
## 314 Germany Agriculture Import 7138524 99267.82
## 315 Japan Agriculture Export 6991046 86103.83
## 316 UK Agriculture Import 6378000 84412.41
## 317 China Electronics Export 6363913 81581.20
## 318 UK Agriculture Import 6823040 97014.06
## 319 Japan Electronics Import 5307410 75363.65
## 320 UK Pharma Export 5220962 70751.95
## 321 UAE Textile Export 8322759 98041.47
## 322 USA Electronics Import 7359967 86659.32
## 323 UK Pharma Import 6464231 83274.96
## 324 Germany Pharma Import 6247759 74163.70
## 325 UAE Electronics Import 7234183 88936.10
## 326 China Agriculture Import 6052965 74019.16
## 327 Japan Electronics Import 5263699 66024.63
## 328 China Agriculture Export 6108933 75716.54
## 329 UAE Agriculture Export 5242999 65196.33
## 330 Germany Agriculture Import 5615855 72756.79
## 331 Japan Electronics Export 7427462 98442.34
## 332 Germany Automobile Import 6942417 86711.08
## 333 Japan Automobile Import 5658985 66671.18
## 334 UK Textile Import 6008458 77411.71
## 335 USA Textile Export 6431538 83459.02
## 336 UK Pharma Export 5917311 74970.78
## 337 UK Textile Export 6505726 84232.37
## 338 Japan Electronics Import 7702865 93442.32
## 339 UAE Electronics Import 6588321 89260.18
## 340 Japan Automobile Import 5541099 74423.72
## 341 Germany Automobile Import 5216890 63659.01
## 342 USA Textile Export 7017904 88656.69
## 343 UK Electronics Import 6786658 90071.26
## 344 USA Agriculture Import 5242907 74123.80
## 345 Japan Electronics Export 5855822 74211.16
## 346 UAE Automobile Export 5611072 70223.83
## 347 Germany Automobile Export 7855040 99008.66
## 348 UAE Automobile Export 7813287 92511.25
## 349 China Agriculture Export 5124541 68566.11
## 350 Germany Automobile Export 6817587 86412.23
## 351 Germany Textile Import 6213863 73426.40
## 352 USA Pharma Export 5282451 74920.97
## 353 USA Agriculture Export 5703323 69874.75
## 354 UAE Electronics Export 5366310 68028.37
## 355 Japan Pharma Import 5332644 70991.84
## 356 UAE Textile Import 5543329 65502.39
## 357 Germany Agriculture Import 7042144 83123.45
## 358 Germany Agriculture Import 5449302 73190.88
## 359 UAE Automobile Import 5487851 70061.74
## 360 UK Pharma Import 5303579 63417.19
## 361 Japan Pharma Export 7446841 88033.83
## 362 Germany Pharma Import 6048156 77144.74
## 363 UK Automobile Import 5829326 82892.35
## 364 China Agriculture Export 5642805 74275.45
## 365 UAE Electronics Export 5555157 74166.55
## 366 China Pharma Export 6728012 86998.13
## 367 China Automobile Export 6747137 84617.73
## 368 USA Automobile Export 5634521 76916.64
## 369 Germany Pharma Export 5841218 76587.75
## 370 USA Automobile Import 6390452 90318.74
## 371 Japan Automobile Export 7683162 97303.39
## 372 USA Automobile Export 5522787 76458.35
## 373 Japan Textile Import 5231755 68705.13
## 374 China Textile Export 8056341 96668.96
## 375 UAE Textile Import 5789561 82626.63
## 376 UAE Textile Import 5514740 68482.83
## 377 China Pharma Export 7966935 94853.16
## 378 UAE Electronics Import 5796583 74594.49
## 379 Germany Electronics Import 5038729 60731.22
## 380 UAE Automobile Export 6289071 74076.67
## 381 China Automobile Import 6414178 85328.70
## 382 China Pharma Export 6615272 88558.17
## 383 China Automobile Import 5693990 73834.78
## 384 Japan Automobile Export 5441005 74985.96
## 385 Germany Textile Export 6191827 74665.64
## 386 Germany Agriculture Export 6671219 90022.56
## 387 UK Automobile Export 6754246 80270.82
## 388 UAE Pharma Import 5527220 72353.66
## 389 Germany Electronics Export 5415554 75265.45
## 390 UAE Textile Import 5928047 82048.91
## 391 UAE Electronics Export 5174770 63405.04
## 392 Germany Agriculture Import 5060721 68710.89
## 393 Germany Textile Export 5933946 73292.78
## 394 UAE Electronics Import 5313393 73711.50
## 395 UAE Agriculture Export 6423143 83175.83
## 396 Japan Automobile Export 6143388 78700.83
## 397 USA Electronics Import 5206320 70228.96
## 398 Germany Electronics Export 7228985 88824.31
## 399 Germany Textile Import 6114415 78970.11
## 400 UAE Automobile Export 5108117 63287.00
## 401 UAE Electronics Import 5234779 65361.55
## 402 UK Textile Import 6922293 97982.60
## 403 Germany Textile Import 5139852 63482.53
## 404 Japan Electronics Export 5603937 68880.74
## 405 USA Automobile Import 5744884 70155.92
## 406 UK Textile Import 5108423 61446.07
## 407 UAE Agriculture Import 7317678 97169.25
## 408 Japan Pharma Import 6684857 92324.90
## 409 Germany Pharma Import 6043871 84185.48
## 410 China Pharma Import 5961718 79619.03
## 411 USA Agriculture Import 6198758 86853.34
## 412 China Automobile Import 6508854 78090.18
## 413 Germany Electronics Import 6781086 93602.13
## 414 Japan Electronics Export 6142691 80019.74
## 415 Japan Automobile Import 6149973 77191.43
## 416 Germany Textile Import 7305768 96028.96
## 417 Germany Electronics Import 7123514 91517.98
## 418 UAE Electronics Import 5569963 65558.13
## 419 USA Textile Export 7103268 86894.88
## 420 USA Textile Import 6963105 82762.05
## 421 UAE Electronics Import 5791652 70472.90
## 422 UAE Electronics Export 8033242 97230.36
## 423 UK Pharma Export 6465426 84622.82
## 424 UAE Pharma Import 5467110 66691.99
## 425 China Pharma Import 6198460 77920.73
## 426 China Automobile Export 6051125 77329.30
## 427 UK Textile Import 5412613 69173.17
## 428 China Electronics Import 5619610 75893.57
## 429 Japan Pharma Import 7379154 90929.48
## 430 USA Agriculture Export 6986338 86116.30
## 431 China Electronics Import 5569758 71854.72
## 432 UK Textile Export 5743140 78864.17
## 433 USA Agriculture Import 6975610 93213.33
## 434 UAE Textile Export 7185648 92599.10
## 435 UK Pharma Export 6597795 82128.17
## 436 UAE Automobile Import 6239395 81308.49
## 437 Japan Pharma Import 5441272 64817.65
## 438 Germany Pharma Export 6987541 98054.72
## 439 Germany Agriculture Export 7487023 88640.22
## 440 China Pharma Import 6072571 74473.57
## 441 UAE Electronics Import 5212946 72391.49
## 442 USA Textile Export 7318096 92170.94
## 443 USA Textile Export 7303792 86786.76
## 444 Japan Textile Import 5408013 72994.34
## 445 Japan Textile Import 6292716 85710.27
## 446 Germany Textile Import 7075309 90430.37
## 447 UK Electronics Import 6835498 83281.68
## 448 UK Pharma Export 6042293 81554.58
## 449 China Textile Export 5644124 69565.87
## 450 Germany Agriculture Import 5675873 78128.59
## 451 Germany Textile Export 5712886 71666.07
## 452 China Pharma Import 6569219 86188.42
## 453 China Textile Export 5490417 69001.73
## 454 UAE Automobile Export 5669711 72556.57
## 455 UK Textile Export 5605702 66319.44
## 456 Germany Agriculture Import 5320983 71288.95
## 457 USA Agriculture Export 6231044 81584.07
## 458 Germany Agriculture Import 6548616 80901.40
## 459 UK Textile Export 5170237 66165.11
## 460 China Pharma Export 5189383 61710.98
## 461 USA Pharma Export 6180498 80360.00
## 462 USA Textile Import 7432060 87583.12
## 463 Japan Pharma Import 5749324 72116.20
## 464 USA Textile Import 8268606 99081.53
## 465 USA Textile Import 5329657 67721.93
## 466 Japan Textile Export 7390977 98552.67
## 467 Japan Agriculture Import 5931571 81138.41
## 468 Japan Pharma Import 5364829 71910.86
## 469 Germany Agriculture Export 7689812 93390.78
## 470 UK Textile Export 6344307 77939.17
## 471 China Pharma Import 5634468 77112.48
## 472 UK Automobile Import 5686967 72766.54
## 473 USA Agriculture Export 5681181 70814.35
## 474 Japan Electronics Import 5811799 82262.64
## 475 Germany Electronics Import 6863932 95925.40
## 476 USA Textile Export 5277641 74669.10
## 477 China Agriculture Import 7365598 92114.36
## 478 UK Pharma Import 6872504 92523.24
## 479 UK Textile Export 5447645 70776.15
## 480 Germany Pharma Import 6690745 94244.44
## 481 Germany Automobile Import 5461187 70682.12
## 482 China Pharma Export 6869937 97153.12
## 483 USA Agriculture Import 5412146 71272.70
## 484 China Automobile Export 5501176 69651.30
## 485 Japan Automobile Export 6533189 88809.79
## 486 UAE Agriculture Import 6339840 76668.01
## 487 Germany Pharma Export 5586957 69535.74
## 488 Germany Agriculture Import 6427824 77157.77
## 489 USA Textile Import 5292557 73922.15
## 490 Japan Automobile Import 5806197 82567.07
## 491 UK Pharma Import 5406842 74199.36
## 492 UK Automobile Export 6989176 90945.68
## 493 USA Electronics Export 6464793 84588.47
## 494 USA Electronics Import 6319301 88033.29
## 495 UAE Automobile Import 7334767 86591.77
## 496 China Textile Export 7339510 89222.93
## 497 Japan Textile Export 8000999 97537.54
## 498 UAE Agriculture Export 6387276 81489.15
## 499 Germany Pharma Import 6849344 90588.51
## 500 Japan Pharma Export 5379244 67733.36
## 501 Japan Electronics Import 7217295 89077.69
## 502 Japan Automobile Export 5431964 75155.32
## 503 Germany Pharma Export 6110727 72633.41
## 504 China Textile Import 6920877 82355.99
## 505 Japan Electronics Export 6917163 93510.18
## 506 Germany Automobile Import 6011316 75893.32
## 507 Japan Textile Export 6339409 88388.49
## 508 Germany Electronics Export 5745660 69994.41
## 509 UK Pharma Import 5388796 74803.79
## 510 Japan Automobile Export 5397418 71104.34
## 511 Germany Electronics Import 6771219 86354.31
## 512 Japan Textile Import 7570731 90358.88
## 513 China Electronics Export 5649316 70789.01
## 514 Japan Textile Import 7125225 89743.80
## 515 China Agriculture Export 6336213 89179.80
## 516 Japan Agriculture Export 5772740 79166.13
## 517 China Electronics Import 5971222 71919.19
## 518 China Automobile Import 5750455 75187.99
## 519 Japan Electronics Export 5369304 70827.97
## 520 Germany Agriculture Export 5786297 75550.20
## 521 China Textile Export 7083960 84083.93
## 522 China Textile Import 6822120 90532.20
## 523 Japan Textile Export 5985908 84355.14
## 524 Japan Automobile Import 7859641 95171.48
## 525 Japan Automobile Export 8127235 96484.52
## 526 China Pharma Export 5656842 73782.39
## 527 China Agriculture Export 5384941 74692.13
## 528 USA Electronics Export 6826471 93069.88
## 529 UAE Electronics Import 7750614 99480.51
## 530 China Agriculture Import 8156384 97456.06
## 531 USA Automobile Import 7545642 91634.61
## 532 Germany Automobile Import 7876495 92953.21
## 533 China Agriculture Import 6979203 89459.17
## 534 Germany Automobile Import 5286920 63694.49
## 535 Japan Textile Export 5089508 62791.74
## 536 Germany Electronics Export 8125894 98696.74
## 537 Germany Agriculture Import 7310740 87812.04
## 538 Japan Textile Import 7376488 89932.29
## 539 China Pharma Import 7429572 95822.90
## 540 Germany Agriculture Export 6719259 88459.53
## 541 Germany Textile Import 5424262 74852.91
## 542 China Pharma Import 5186319 61620.72
## 543 Germany Pharma Export 6872260 95531.92
## 544 Germany Agriculture Export 7645330 99862.45
## 545 UAE Automobile Import 6984932 94126.39
## 546 USA Electronics Import 6602345 85407.92
## 547 China Pharma Import 6541635 79926.99
## 548 Japan Pharma Export 5120848 68824.28
## 549 Japan Electronics Import 5437160 73989.42
## 550 Japan Automobile Export 6665836 90730.50
## 551 China Agriculture Import 5782176 78089.99
## 552 Germany Electronics Import 5226981 63677.06
## 553 UAE Textile Export 7490769 88677.69
## 554 Germany Agriculture Export 7250240 86709.22
## 555 UK Agriculture Import 7540097 90865.55
## 556 Japan Automobile Export 5638070 68832.28
## 557 UAE Electronics Import 5858057 76913.38
## 558 China Agriculture Export 5441632 66604.42
## 559 Japan Agriculture Import 5567124 73047.97
## 560 Germany Pharma Export 5413633 66682.40
## 561 Germany Electronics Import 5791891 76653.46
## 562 UK Electronics Import 7025156 84502.46
## 563 Germany Electronics Import 5127194 72904.76
## 564 UK Textile Export 5513205 65464.51
## 565 UAE Agriculture Export 6376393 90974.73
## 566 Japan Automobile Import 5693255 74687.59
## 567 Germany Electronics Import 6003557 77756.61
## 568 Germany Textile Export 5981777 84747.74
## 569 Germany Electronics Import 7120284 97995.36
## 570 UK Automobile Export 7701794 92242.10
## 571 USA Automobile Export 7334712 99910.76
## 572 Germany Pharma Import 6725386 90155.32
## 573 Japan Textile Import 6614000 82263.87
## 574 UK Pharma Import 5381042 69697.34
## 575 China Agriculture Import 5474582 74782.47
## 576 Japan Pharma Import 5475127 73315.38
## 577 Germany Agriculture Export 7320821 93447.44
## 578 UK Pharma Import 7409045 91453.42
## 579 China Textile Export 5111409 70203.24
## 580 China Automobile Export 6020373 82054.05
## 581 UK Pharma Export 5942016 72113.53
## 582 Japan Electronics Export 6912537 89866.42
## 583 Japan Agriculture Import 5127636 65634.30
## 584 Japan Pharma Export 6817659 93892.90
## 585 UK Agriculture Import 6249776 87775.94
## 586 UAE Textile Import 7016774 82816.17
## 587 Germany Automobile Import 6049604 73322.68
## 588 China Electronics Export 6156696 86930.84
## 589 Japan Electronics Export 6523084 87748.08
## 590 Japan Electronics Import 6075523 77745.29
## 591 Japan Automobile Import 6053010 73441.05
## 592 USA Pharma Import 6574944 83950.40
## 593 China Textile Export 6571929 83229.98
## 594 UK Agriculture Import 8087044 99668.27
## 595 China Automobile Import 6195993 83123.13
## 596 Japan Electronics Export 6732985 95251.03
## 597 USA Agriculture Import 7009524 92038.29
## 598 Germany Electronics Export 7230836 90858.96
## 599 China Pharma Export 6917111 92515.37
## 600 China Agriculture Export 6597998 86782.34
## 601 USA Automobile Export 6399060 87284.57
## 602 Germany Textile Import 7837157 97622.31
## 603 UK Automobile Export 6664497 89190.43
## 604 UAE Agriculture Import 6926758 91075.17
## 605 USA Textile Import 7918942 93215.98
## 606 UAE Textile Export 6655669 80454.32
## 607 USA Pharma Import 5582023 76840.78
## 608 UK Textile Export 5597600 65899.99
## 609 USA Pharma Import 6810110 87848.84
## 610 China Electronics Export 5124406 64126.78
## 611 USA Textile Import 5980723 75422.19
## 612 UK Pharma Export 7264464 94519.47
## 613 UAE Electronics Export 7436237 96450.89
## 614 China Agriculture Export 6151295 74725.75
## 615 Japan Electronics Import 5220671 70972.16
## 616 USA Automobile Import 6531758 89624.60
## 617 Japan Agriculture Import 6760253 81618.43
## 618 UK Automobile Export 5186851 69255.30
## 619 China Textile Export 7165033 90033.31
## 620 China Agriculture Export 5109638 70377.22
## 621 Japan Pharma Export 5515887 67503.61
## 622 USA Electronics Export 5658405 75837.41
## 623 Japan Pharma Import 8211033 97161.84
## 624 UK Pharma Export 5027895 59304.38
## 625 Germany Electronics Import 5836076 71090.71
## 626 USA Electronics Import 5960807 70485.06
## 627 USA Automobile Import 5158412 60984.78
## 628 China Electronics Export 6908162 95709.42
## 629 Japan Electronics Export 5471157 75613.50
## 630 Germany Textile Import 5399893 68611.90
## 631 China Pharma Import 7345911 88467.10
## 632 China Pharma Import 6652758 94849.26
## 633 UK Electronics Import 6845887 82995.88
## 634 USA Agriculture Export 5131975 65826.88
## 635 China Electronics Export 5814497 72507.15
## 636 China Agriculture Export 6010317 75528.90
## 637 China Textile Import 6176841 74376.76
## 638 China Textile Export 5174807 63882.04
## 639 Germany Pharma Export 5302682 75674.51
## 640 UK Automobile Export 6666692 91482.46
## 641 UAE Electronics Export 5097949 63415.25
## 642 Japan Agriculture Import 5399608 72474.48
## 643 China Agriculture Import 6220492 87010.80
## 644 UAE Textile Import 5016800 71584.44
## 645 UK Textile Export 5761463 71397.43
## 646 UK Electronics Import 5564786 66890.92
## 647 Japan Electronics Import 6161218 80496.72
## 648 UAE Electronics Export 6914965 91870.99
## 649 China Automobile Export 5361648 74371.49
## 650 China Automobile Export 6992937 93245.18
## 651 UK Agriculture Export 6522054 80583.37
## 652 Japan Automobile Export 5245356 73321.94
## 653 USA Automobile Import 5924169 78313.13
## 654 UK Automobile Import 5793274 81333.02
## 655 USA Automobile Import 6538036 92011.31
## 656 USA Electronics Import 7269625 92468.10
## 657 UK Automobile Import 6157389 82157.61
## 658 Japan Pharma Import 6406425 81019.14
## 659 Japan Automobile Export 6456359 85628.99
## 660 China Electronics Export 5275603 72624.29
## 661 Japan Automobile Export 6738017 86003.13
## 662 UK Electronics Import 6916198 94975.71
## 663 UAE Textile Export 5759179 81600.49
## 664 UK Agriculture Export 5015937 59402.80
## 665 China Agriculture Export 7101193 87602.07
## 666 China Pharma Export 5058457 69720.13
## 667 China Pharma Export 6358127 80052.66
## 668 Germany Electronics Export 7400702 91786.06
## 669 USA Agriculture Import 6573851 88176.72
## 670 UK Electronics Export 5389076 67941.08
## 671 China Pharma Import 5732359 71115.91
## 672 Japan Textile Import 6709440 81469.81
## 673 UK Automobile Import 5965428 77206.52
## 674 Japan Pharma Import 6054441 78976.09
## 675 UK Electronics Import 5991438 81806.10
## 676 Japan Agriculture Export 8105264 97079.56
## 677 USA Automobile Export 7339546 93220.24
## 678 USA Electronics Import 5111237 61785.70
## 679 China Agriculture Import 5414051 75886.63
## 680 Japan Textile Export 7003131 89839.95
## 681 China Electronics Export 5426218 65876.28
## 682 USA Automobile Export 5618540 78912.36
## 683 Japan Automobile Export 7251862 88130.32
## 684 Japan Automobile Export 6445214 87720.32
## 685 Germany Automobile Import 7053411 93245.51
## 686 UK Textile Import 5446593 75031.62
## 687 China Textile Export 5398817 74330.42
## 688 Japan Textile Export 7089774 95865.60
## 689 Germany Agriculture Export 6580655 86273.75
## 690 China Electronics Import 7473671 95311.09
## 691 China Automobile Import 6726397 91631.19
## 692 China Pharma Import 5312198 67288.58
## 693 Japan Electronics Export 5381976 72508.51
## 694 Germany Pharma Export 6431142 78771.15
## 695 USA Automobile Import 5968891 79599.03
## 696 UAE Pharma Import 5358195 71660.20
## 697 USA Agriculture Export 6489323 90432.49
## 698 UK Automobile Export 6543581 89659.82
## 699 UK Pharma Export 6602060 91864.14
## 700 USA Automobile Import 7606861 91100.10
## 701 Germany Automobile Import 6164278 83292.92
## 702 Japan Pharma Import 5784445 78414.68
## 703 USA Textile Export 6299950 74988.42
## 704 China Automobile Import 5776132 69653.81
## 705 USA Automobile Export 5266149 72729.17
## 706 UK Automobile Export 7254100 98047.27
## 707 Germany Electronics Import 5680312 72084.41
## 708 UK Textile Export 7669586 94967.55
## 709 UK Automobile Export 5277852 63851.72
## 710 UAE Agriculture Import 5215457 62854.76
## 711 USA Automobile Import 6653816 87084.19
## 712 China Automobile Export 7322904 90538.12
## 713 UK Textile Export 5707333 73335.79
## 714 USA Agriculture Export 5555480 76246.93
## 715 USA Agriculture Import 5752376 70748.60
## 716 Japan Pharma Import 6996529 96422.83
## 717 UAE Automobile Export 7591232 95381.95
## 718 UAE Electronics Import 5367045 71609.65
## 719 Germany Pharma Import 6683179 82977.69
## 720 Japan Automobile Export 5707838 67706.64
## 721 Japan Electronics Export 7629999 94084.49
## 722 Japan Agriculture Export 6762235 90679.24
## 723 Japan Textile Export 5169161 64820.32
## 724 Japan Pharma Export 5128210 68472.88
## 725 UAE Electronics Import 7097705 92887.26
## 726 USA Pharma Import 7441897 88687.62
## 727 Japan Agriculture Export 6863119 85469.09
## 728 UK Pharma Export 5966942 71365.50
## 729 Japan Pharma Export 5331261 71645.20
## 730 Germany Automobile Import 7412970 93566.51
## 731 Germany Textile Export 7704321 97665.50
## 732 UAE Textile Export 6160384 73126.36
## 733 UK Textile Import 7499408 92176.74
## 734 UAE Pharma Import 6681756 91411.98
## 735 UAE Textile Import 5681506 76826.06
## 736 UAE Pharma Import 7245735 89123.43
## 737 USA Electronics Export 6857871 89220.21
## 738 Germany Pharma Import 7254501 91588.28
## 739 UK Automobile Export 5503473 67508.30
## 740 China Agriculture Export 6051255 80635.96
## 741 USA Automobile Export 5072593 65479.91
## 742 UAE Textile Export 5376500 65153.24
## 743 Japan Textile Import 5226962 67971.15
## 744 Germany Pharma Import 5349052 63788.35
## 745 UAE Textile Import 7352540 95492.70
## 746 Japan Agriculture Export 5775931 75587.34
## 747 UAE Agriculture Import 7535381 98466.82
## 748 USA Pharma Import 6802176 82452.37
## 749 UK Agriculture Import 7415079 89730.68
## 750 USA Pharma Import 7747604 91721.38
## 751 USA Automobile Import 7127191 89888.23
## 752 UAE Textile Import 6261248 79196.69
## 753 UK Automobile Import 5232310 64851.98
## 754 Germany Automobile Import 6072797 86439.24
## 755 Japan Automobile Import 7661600 91465.26
## 756 Germany Electronics Import 8001452 95836.37
## 757 UAE Electronics Export 7390175 92427.90
## 758 UAE Electronics Import 5802057 70018.20
## 759 UAE Pharma Import 7020409 84277.21
## 760 UK Electronics Export 6493942 90389.79
## 761 USA Automobile Import 5839513 70548.39
## 762 China Automobile Export 6122103 73135.85
## 763 USA Electronics Import 7118980 91661.58
## 764 UAE Electronics Import 7214870 90472.52
## 765 China Textile Export 7850481 94494.79
## 766 China Automobile Import 6637177 78288.25
## 767 Japan Electronics Import 5317250 62628.54
## 768 USA Automobile Export 6281541 81917.49
## 769 UK Textile Export 5404383 75846.18
## 770 UAE Pharma Import 5175338 72678.77
## 771 Germany Automobile Export 6878554 86555.20
## 772 UAE Textile Export 5090534 65905.17
## 773 Germany Pharma Export 5447862 73888.54
## 774 UK Pharma Export 6887939 94271.14
## 775 USA Automobile Export 7197984 90724.06
## 776 UAE Automobile Export 5293604 64007.71
## 777 UK Pharma Import 5454941 70799.77
## 778 China Electronics Export 5561482 68024.08
## 779 USA Agriculture Export 7633141 91371.43
## 780 China Pharma Export 5461820 73010.94
## 781 UK Automobile Export 5578810 77365.01
## 782 USA Agriculture Export 7105400 99433.16
## 783 UAE Agriculture Import 6244477 80272.21
## 784 China Agriculture Export 6345740 80344.31
## 785 UK Agriculture Import 7029955 89444.13
## 786 UAE Textile Import 5222665 69611.02
## 787 Japan Automobile Export 6935462 91735.55
## 788 USA Textile Import 5236367 70770.94
## 789 Germany Automobile Import 5182163 69895.09
## 790 China Pharma Import 6421523 91259.29
## 791 Germany Pharma Import 7767844 93094.40
## 792 UK Automobile Export 5858638 72475.85
## 793 UAE Pharma Import 6480354 86296.77
## 794 Germany Textile Export 5079061 70532.37
## 795 Germany Pharma Import 5499725 66485.24
## 796 USA Agriculture Import 6058595 75590.85
## 797 USA Agriculture Import 6386863 90293.73
## 798 UAE Agriculture Export 5372627 64271.35
## 799 Japan Automobile Export 6540836 77965.18
## 800 China Electronics Export 8007527 96767.64
## 801 China Textile Import 5487251 73729.86
## 802 Germany Electronics Import 6472991 83490.02
## 803 Germany Textile Import 7249436 88826.79
## 804 UAE Electronics Export 6578699 80788.69
## 805 Japan Electronics Export 7656778 98661.70
## 806 USA Electronics Import 7641969 331120.37
## 807 Germany Textile Import 6812531 81452.80
## 808 Germany Pharma Import 5117328 62589.54
## 809 UAE Agriculture Export 6002390 75367.39
## 810 China Agriculture Export 5208088 72017.50
## 811 UAE Electronics Import 6178351 74914.79
## 812 China Agriculture Import 7680528 96694.07
## 813 Japan Automobile Export 7939264 95973.60
## 814 China Electronics Import 6954567 97882.86
## 815 USA Pharma Export 6261696 88295.25
## 816 Japan Electronics Export 6384166 88317.48
## 817 UAE Pharma Export 6225555 86212.68
## 818 UAE Pharma Export 7175831 86414.57
## 819 UAE Pharma Import 5259652 69488.75
## 820 Germany Textile Import 5654335 75640.69
## 821 Germany Automobile Import 5790879 74829.25
## 822 USA Textile Import 6578320 90968.05
## 823 UAE Pharma Import 6088930 77200.57
## 824 Japan Pharma Import 5379834 73921.30
## 825 UK Electronics Import 7669218 92747.73
## 826 Germany Agriculture Export 6315555 83953.99
## 827 USA Pharma Import 5206836 68276.30
## 828 Germany Pharma Export 5299042 74764.44
## 829 UK Agriculture Export 5432420 70684.23
## 830 Japan Electronics Import 6674631 78643.01
## 831 UK Pharma Export 5981615 76724.67
## 832 UAE Textile Export 5530587 69960.58
## 833 Japan Agriculture Export 5430944 75386.50
## 834 USA Agriculture Import 7077958 99901.77
## 835 UK Electronics Import 5937015 76954.25
## 836 USA Electronics Export 6193288 77914.48
## 837 UAE Automobile Export 7123980 93916.61
## 838 USA Agriculture Import 6831220 86020.48
## 839 Germany Agriculture Import 5153408 64283.51
## 840 UK Electronics Export 5302132 68660.64
## 841 Germany Automobile Export 7754969 92645.40
## 842 UAE Pharma Import 5243724 70115.00
## 843 UAE Textile Import 6219802 84331.40
## 844 UAE Pharma Export 7926432 97087.08
## 845 UAE Textile Import 7396888 91478.76
## 846 USA Electronics Import 6876323 94912.79
## 847 Germany Agriculture Import 7419979 89208.22
## 848 UAE Automobile Import 6471646 76297.16
## 849 USA Automobile Import 6869145 96071.10
## 850 Japan Agriculture Import 5579021 73458.88
## 851 USA Automobile Export 7844511 95925.34
## 852 UK Pharma Export 5528254 69251.88
## 853 China Agriculture Import 7560945 98964.44
## 854 Germany Agriculture Import 6394291 78418.20
## 855 UAE Pharma Import 6988867 83501.35
## 856 USA Agriculture Export 5607959 71735.12
## 857 Japan Electronics Import 7232120 97452.56
## 858 USA Automobile Import 7363935 90267.15
## 859 USA Textile Export 6114648 79620.18
## 860 China Pharma Import 6311919 89064.39
## 861 Germany Agriculture Export 7023307 90647.31
## 862 Japan Automobile Import 6462899 81579.41
## 863 Japan Agriculture Export 7845326 96253.66
## 864 China Pharma Export 5086077 63414.89
## 865 USA Electronics Export 5693043 74983.59
## 866 UK Pharma Export 6757458 84004.64
## 867 UK Pharma Import 6278957 84471.66
## 868 China Automobile Import 6821225 90062.63
## 869 UK Textile Export 7158445 92365.13
## 870 UK Automobile Import 6752850 79827.78
## 871 China Electronics Import 7209017 91857.48
## 872 Germany Automobile Export 7161556 91940.68
## 873 Japan Automobile Import 5789617 71539.99
## 874 Germany Agriculture Import 6921053 95105.02
## 875 USA Textile Import 6084823 81534.56
## 876 UAE Pharma Export 5703336 67859.12
## 877 UK Electronics Import 7082055 90238.40
## 878 China Automobile Import 8249483 99028.62
## 879 China Electronics Import 6716739 80437.65
## 880 UK Agriculture Import 6458244 87785.96
## 881 UK Automobile Export 6802667 84274.75
## 882 UAE Automobile Import 5330837 64827.56
## 883 Germany Pharma Import 8097934 97622.74
## 884 USA Textile Import 6197262 85345.97
## 885 China Automobile Export 6745140 89750.44
## 886 China Pharma Export 8138280 96772.86Explanation: Filters transactions where trade value is greater than 50 lakh INR. ### Question: Sort data based on shipment days
data %>%
arrange(Shipment_Days)## Year Month Product_Category Product_Name Import_Export Quantity
## 1 2022.000 September Agriculture Mobile Export 4499
## 2 2021.000 October Automobile Mobile Import 4615
## 3 2019.000 August Electronics Cotton Import 9877
## 4 2019.000 February Automobile Mobile Import 5832
## 5 2020.000 November Electronics Cotton Import 9281
## 6 2023.000 May Pharma Car Import 7673
## 7 2021.000 October Pharma Wheat Import 3258
## 8 2021.000 May Agriculture Car Export 9652
## 9 2022.000 October Electronics Cotton Import 8073
## 10 2021.000 July Electronics Car Import 8587
## 11 2020.000 May Automobile Wheat Export 737
## 12 2020.000 April Pharma Cotton Import 2279
## 13 2019.000 January Automobile Mobile Export 3163
## 14 2018.000 November Automobile Mobile Export 8352
## 15 2020.000 January Automobile Wheat Export 6447
## 16 2020.000 March Electronics Medicine Import 8780
## 17 2020.000 May Agriculture Car Import 3784
## 18 2019.000 February Automobile Wheat Import 2561
## 19 2018.000 November Agriculture Car Import 8195
## 20 2021.000 July Electronics Cotton Import 622
## 21 2023.000 April Textile Mobile Import 3855
## 22 2021.000 March Pharma Car Export 4573
## 23 2022.000 February Pharma Medicine Export 8628
## 24 2022.000 June Automobile Car Import 9546
## 25 2024.000 September Textile Mobile Import 8838
## 26 2018.000 September Automobile Wheat Export 1772
## 27 2022.000 December Electronics Cotton Export 1810
## 28 2019.000 September Agriculture Cotton Import 348
## 29 2024.000 August Textile Wheat Export 2861
## 30 2019.000 April Agriculture Medicine Import 4569
## 31 2021.000 May Pharma Medicine Export 7839
## 32 2023.000 October Electronics Wheat Import 8619
## 33 2018.000 July Automobile Medicine Export 8843
## 34 2024.000 May Automobile Mobile Import 1446
## 35 2023.000 December Electronics Medicine Import 7892
## 36 2022.000 January Textile Mobile Export 3147
## 37 2018.000 April Pharma Cotton Export 6463
## 38 2019.000 November Agriculture Medicine Export 8245
## 39 2019.000 September Textile Cotton Export 8900
## 40 2018.000 March Pharma Mobile Import 5718
## 41 2018.000 March Electronics Wheat Export 3754
## 42 2019.000 July Pharma Wheat Export 2970
## 43 2020.000 January Automobile Mobile Export 7987
## 44 2019.000 September Textile Car Import 1677
## 45 2019.000 April Textile Wheat Export 8021
## 46 2021.000 September Textile Mobile Export 4830
## 47 2022.000 July Pharma Wheat Export 3522
## 48 2022.000 May Electronics Car Import 1472
## 49 2022.000 November Textile Wheat Import 3499
## 50 2024.000 January Agriculture Cotton Import 1331
## 51 2023.000 June Pharma Car Import 7022
## 52 2021.000 November Electronics Wheat Export 9578
## 53 2023.000 June Textile Medicine Export 3082
## 54 2020.000 June Electronics Cotton Import 1992
## 55 2021.000 May Automobile Wheat Export 7112
## 56 2022.000 August Automobile Mobile Export 5946
## 57 2022.000 September Automobile Cotton Import 4881
## 58 2022.000 March Electronics Mobile Import 7421
## 59 2020.000 December Textile Cotton Export 9537
## 60 2019.000 August Textile Cotton Import 1599
## 61 2019.000 October Agriculture Cotton Import 9962
## 62 2023.000 July Electronics Car Export 240
## 63 2022.000 August Agriculture Cotton Export 3702
## 64 2021.000 October Automobile Wheat Import 8517
## 65 2020.000 May Agriculture Wheat Export 4849
## 66 2022.000 February Electronics Mobile Export 7526
## 67 2021.000 November Textile Cotton Export 8620
## 68 2019.000 September Pharma Medicine Import 5921
## 69 2021.000 August Electronics Car Export 9640
## 70 2018.000 October Textile Wheat Export 2750
## 71 2020.000 January Textile Wheat Export 9649
## 72 2020.000 July Electronics Wheat Export 4719
## 73 2020.000 July Electronics Car Export 6179
## 74 2022.000 November Pharma Wheat Import 1471
## 75 2019.000 April Agriculture Mobile Import 4805
## 76 2018.000 December Pharma Car Import 3403
## 77 2022.000 January Pharma Mobile Import 6077
## 78 2019.000 August Pharma Mobile Import 3580
## 79 2020.000 February Agriculture Car Export 8837
## 80 2022.000 July Automobile Wheat Import 5675
## 81 2019.000 February Pharma Car Import 9979
## 82 2020.000 July Electronics Wheat Export 5397
## 83 2019.000 April Pharma Medicine Export 9812
## 84 2024.000 February Agriculture Car Import 2351
## 85 2019.000 June Agriculture Medicine Export 5232
## 86 2019.000 August Agriculture Cotton Export 9660
## 87 2023.000 May Pharma Car Import 5545
## 88 2021.000 December Pharma Car Import 8588
## 89 2018.000 August Agriculture Car Import 1571
## 90 2024.000 December Pharma Car Export 261
## 91 2022.000 September Automobile Cotton Import 841
## 92 2023.000 October Textile Mobile Export 9001
## 93 2020.000 April Pharma Mobile Import 4959
## 94 2021.000 February Agriculture Mobile Export 140
## 95 2024.000 April Electronics Car Import 5628
## 96 2024.000 March Automobile Car Export 156
## 97 2019.000 April Textile Mobile Export 5563
## 98 2019.000 February Textile Mobile Import 2529
## 99 2019.000 July Electronics Mobile Import 8353
## 100 2024.000 November Electronics Medicine Import 3016
## 101 2023.000 July Automobile Wheat Export 861
## 102 2018.000 March Automobile Car Export 8176
## 103 2023.000 October Electronics Medicine Import 544
## 104 2023.000 March Agriculture Wheat Import 8097
## 105 2018.000 November Agriculture Mobile Export 3221
## 106 2019.000 June Pharma Car Export 4312
## 107 2020.000 July Pharma Wheat Export 7255
## 108 2023.000 May Agriculture Car Import 2975
## 109 2018.000 June Textile Cotton Import 3776
## 110 2023.000 May Automobile Car Export 6946
## 111 2023.000 December Agriculture Mobile Import 4157
## 112 2020.000 April Textile Mobile Import 4972
## 113 2024.000 February Automobile Medicine Export 8964
## 114 2019.000 November Agriculture Medicine Export 2803
## 115 2024.000 December Agriculture Car Import 2206
## 116 2024.000 August Textile Cotton Export 1256
## 117 2018.000 March Electronics Medicine Export 6822
## 118 2019.000 November Textile Cotton Export 6323
## 119 2018.000 February Pharma Medicine Export 2808
## 120 2024.000 April Agriculture Car Import 4591
## 121 2022.000 August Electronics Cotton Import 1089
## 122 2021.000 January Automobile Wheat Import 5972
## 123 2023.000 May Textile Car Export 5813
## 124 2018.000 February Automobile Cotton Export 4025
## 125 2022.000 May Textile Wheat Import 2227
## 126 2024.000 March Textile Wheat Import 5422
## 127 2021.000 May Pharma Wheat Import 3945
## 128 2021.000 April Electronics Mobile Export 2117
## 129 2019.000 August Agriculture Cotton Export 5114
## 130 2022.000 March Automobile Medicine Import 2662
## 131 2021.000 October Textile Wheat Export 2605
## 132 2024.000 March Automobile Cotton Export 810
## 133 2020.000 October Electronics Car Import 682
## 134 2020.000 May Electronics Mobile Export 6638
## 135 2020.000 July Textile Wheat Export 4719
## 136 2021.000 March Agriculture Cotton Export 6075
## 137 2018.000 July Textile Cotton Import 3774
## 138 2020.000 September Pharma Mobile Import 4938
## 139 2022.000 March Pharma Cotton Import 5847
## 140 2018.000 April Pharma Cotton Import 6320
## 141 2021.000 January Agriculture Car Import 3670
## 142 2021.000 September Textile Car Import 726
## 143 2022.000 July Electronics Car Import 5541
## 144 2023.000 October Electronics Medicine Import 287
## 145 2022.000 September Agriculture Car Import 8680
## 146 2023.000 July Agriculture Cotton Export 3974
## 147 2020.000 June Agriculture Medicine Export 2502
## 148 2022.000 November Automobile Mobile Import 5758
## 149 2019.000 November Electronics Wheat Export 5436
## 150 2024.000 May Textile Wheat Export 6802
## 151 2021.000 January Pharma Car Export 419
## 152 2022.000 September Textile Wheat Import 4130
## 153 2021.000 June Pharma Medicine Import 9665
## 154 2018.000 November Electronics Mobile Import 5459
## 155 2019.000 September Pharma Mobile Import 7092
## 156 2018.000 January Electronics Cotton Import 4855
## 157 2019.000 November Textile Cotton Export 9632
## 158 2024.000 November Automobile Car Export 9589
## 159 2018.000 April Automobile Wheat Import 6297
## 160 2020.000 November Pharma Cotton Export 8175
## 161 2023.000 December Pharma Car Export 5479
## 162 2021.000 December Electronics Car Export 3869
## 163 2018.000 January Textile Mobile Export 4214
## 164 2018.000 March Textile Mobile Import 6444
## 165 2022.000 April Automobile Mobile Import 7723
## 166 2024.000 February Automobile Mobile Import 4839
## 167 2022.000 February Textile Mobile Import 2757
## 168 2022.000 December Automobile Wheat Import 3955
## 169 2019.000 April Automobile Cotton Export 1375
## 170 2019.000 September Electronics Mobile Import 7788
## 171 2020.000 October Automobile Mobile Export 8060
## 172 2018.000 November Textile Cotton Export 8903
## 173 2024.000 January Electronics Medicine Export 5303
## 174 2021.000 July Electronics Mobile Export 864
## 175 2021.000 October Textile Medicine Import 8411
## 176 2019.000 March Textile Cotton Export 141
## 177 2020.000 June Pharma Cotton Export 2869
## 178 2019.000 October Agriculture Mobile Export 1126
## 179 2023.000 July Automobile Mobile Import 9500
## 180 2018.000 November Electronics Mobile Export 6654
## 181 2023.000 November Agriculture Mobile Import 2576
## 182 2020.000 September Electronics Wheat Export 2071
## 183 2021.000 March Automobile Cotton Export 813
## 184 2021.000 February Agriculture Medicine Import 5742
## 185 2024.000 May Automobile Car Import 6848
## 186 2018.000 November Textile Cotton Export 3769
## 187 2023.000 December Electronics Medicine Import 9113
## 188 2018.000 November Textile Cotton Import 8221
## 189 2021.000 December Pharma Mobile Export 9984
## 190 2020.000 August Automobile Wheat Import 7347
## 191 2020.000 April Agriculture Medicine Import 1968
## 192 2020.000 October Automobile Mobile Export 9535
## 193 2023.000 March Agriculture Car Import 2293
## 194 2019.000 November Agriculture Mobile Import 594
## 195 2022.000 June Agriculture Medicine Export 8230
## 196 2022.000 April Automobile Medicine Import 4229
## 197 2024.000 July Textile Medicine Export 3870
## 198 2024.000 January Electronics Wheat Import 5489
## 199 2021.000 February Agriculture Car Import 9052
## 200 2024.000 September Electronics Medicine Import 9686
## 201 2020.000 November Agriculture Medicine Export 5600
## 202 2022.000 July Textile Wheat Import 991
## 203 2023.000 November Textile Cotton Import 1961
## 204 2019.000 October Agriculture Car Import 8822
## 205 2018.000 October Textile Medicine Import 9420
## 206 2022.000 August Electronics Car Export 9849
## 207 2023.000 November Textile Car Import 5784
## 208 2018.000 April Textile Car Import 5420
## 209 2023.000 January Pharma Car Import 6300
## 210 2019.000 March Agriculture Mobile Import 2409
## 211 2024.000 August Agriculture Wheat Import 8509
## 212 2021.000 June Pharma Wheat Import 1164
## 213 2021.000 February Electronics Cotton Export 1351
## 214 2023.000 September Electronics Cotton Export 1240
## 215 2023.000 May Electronics Wheat Export 6213
## 216 2018.000 February Textile Wheat Export 7204
## 217 2021.000 November Electronics Cotton Export 4357
## 218 2023.000 October Pharma Cotton Export 8817
## 219 2019.000 March Automobile Mobile Export 5113
## 220 2022.000 October Automobile Car Import 6388
## 221 2019.000 September Automobile Car Export 1764
## 222 2019.000 May Electronics Wheat Export 6703
## 223 2024.000 April Automobile Medicine Export 629
## 224 2018.000 June Textile Cotton Export 3322
## 225 2022.000 November Electronics Wheat Import 5270
## 226 2021.000 March Electronics Car Export 9611
## 227 2018.000 April Agriculture Wheat Export 7398
## 228 2021.000 June Pharma Medicine Export 2141
## 229 2024.000 June Pharma Wheat Import 4539
## 230 2021.000 November Textile Cotton Import 6323
## 231 2019.000 March Pharma Car Export 978
## 232 2020.000 March Automobile Car Export 9393
## 233 2022.000 August Electronics Mobile Export 7272
## 234 2023.000 February Agriculture Mobile Export 6639
## 235 2021.000 November Textile Car Import 8967
## 236 2023.000 February Pharma Mobile Import 4771
## 237 2024.000 August Electronics Car Export 7161
## 238 2024.000 May Pharma Cotton Import 4512
## 239 2018.000 May Electronics Mobile Import 1357
## 240 2022.000 January Automobile Wheat Export 2185
## 241 2019.000 January Electronics Medicine Import 4512
## 242 2021.000 June Textile Wheat Export 3902
## 243 2019.000 December Automobile Medicine Import 5869
## 244 2024.000 December Textile Car Import 6075
## 245 2023.000 July Agriculture Wheat Export 1216
## 246 2019.000 September Electronics Car Import 1517
## 247 2022.000 March Automobile Wheat Import 3479
## 248 2024.000 June Textile Car Export 9366
## 249 2021.000 July Electronics Mobile Import 461
## 250 2024.000 November Automobile Mobile Export 5773
## 251 2024.000 August Automobile Medicine Export 5201
## 252 2022.000 September Agriculture Medicine Export 4961
## 253 2024.000 December Agriculture Wheat Import 433
## 254 2024.000 December Automobile Wheat Import 5869
## 255 2024.000 April Pharma Medicine Import 5233
## 256 2021.000 November Textile Wheat Export 6967
## 257 2023.000 April Automobile Mobile Import 5048
## 258 2024.000 November Textile Medicine Export 7615
## 259 2023.000 May Pharma Cotton Import 6307
## 260 2023.000 August Pharma Car Import 3559
## 261 2020.000 October Electronics Mobile Export 3953
## 262 2023.000 April Pharma Mobile Export 9919
## 263 2024.000 April Agriculture Medicine Export 9313
## 264 2024.000 November Electronics Medicine Export 4616
## 265 2023.000 March Automobile Mobile Export 6763
## 266 2019.000 July Textile Mobile Export 2174
## 267 2020.000 July Automobile Wheat Export 8078
## 268 2022.000 April Electronics Car Import 9404
## 269 2021.000 November Pharma Mobile Export 3139
## 270 2023.000 May Textile Car Import 3764
## 271 2022.000 July Textile Medicine Import 8125
## 272 2018.000 May Textile Mobile Export 4123
## 273 2024.000 May Pharma Medicine Export 3198
## 274 2021.000 June Automobile Wheat Export 6659
## 275 2021.000 November Textile Cotton Export 5990
## 276 2019.000 December Pharma Car Import 6692
## 277 2024.000 April Textile Medicine Export 1484
## 278 2021.000 January Electronics Wheat Import 3661
## 279 2019.000 July Automobile Cotton Import 2327
## 280 2021.000 March Automobile Medicine Import 3319
## 281 2021.000 December Agriculture Mobile Export 6508
## 282 2018.000 December Electronics Medicine Import 1835
## 283 2024.000 March Automobile Car Export 9009
## 284 2024.000 August Agriculture Mobile Import 229
## 285 2024.000 May Textile Wheat Import 1245
## 286 2021.000 September Pharma Medicine Import 8635
## 287 2024.000 December Agriculture Car Export 3993
## 288 2021.000 December Automobile Mobile Import 802
## 289 2023.000 February Automobile Mobile Import 1686
## 290 2022.000 September Textile Car Export 7476
## 291 2023.000 February Textile Medicine Import 8690
## 292 2020.000 June Textile Wheat Export 1182
## 293 2020.000 March Pharma Mobile Export 8558
## 294 2021.000 March Electronics Medicine Export 5963
## 295 2023.000 December Textile Medicine Import 3023
## 296 2024.000 August Electronics Mobile Import 2819
## 297 2024.000 May Electronics Cotton Import 2602
## 298 2020.000 July Pharma Car Import 7054
## 299 2022.000 May Pharma Medicine Import 9311
## 300 2021.000 January Textile Car Import 3883
## 301 2022.000 March Textile Wheat Export 4428
## 302 2018.000 May Textile Car Import 9759
## 303 2020.000 May Electronics Cotton Export 5331
## 304 2024.000 December Pharma Mobile Export 1226
## 305 2020.000 January Textile Car Export 9836
## 306 2020.000 October Electronics Cotton Export 2843
## 307 2023.000 December Textile Wheat Export 264
## 308 2023.000 March Automobile Mobile Import 5982
## 309 2019.000 May Automobile Mobile Export 4728
## 310 2020.000 July Textile Mobile Import 1800
## 311 2021.000 March Electronics Medicine Import 4964
## 312 2018.000 October Automobile Wheat Export 3759
## 313 2018.000 October Automobile Medicine Import 5568
## 314 2021.000 October Textile Cotton Import 7026
## 315 2020.000 December Textile Car Import 9478
## 316 2019.000 November Pharma Car Export 9633
## 317 2018.000 October Textile Medicine Export 6417
## 318 2021.000 February Electronics Cotton Export 1600
## 319 2020.000 August Agriculture Cotton Import 8840
## 320 2024.000 March Textile Medicine Export 4287
## 321 2021.000 November Textile Car Import 8254
## 322 2022.000 July Electronics Medicine Export 9992
## 323 2023.000 August Pharma Cotton Import 9032
## 324 2020.000 October Automobile Mobile Export 3512
## 325 2021.000 September Electronics Medicine Export 8117
## 326 2019.000 October Automobile Mobile Import 3266
## 327 2024.000 August Textile Mobile Import 3861
## 328 2024.000 December Agriculture Cotton Import 9814
## 329 2024.000 March Automobile Car Import 9033
## 330 2024.000 November Automobile Medicine Import 9879
## 331 2018.000 October Pharma Medicine Export 6426
## 332 2021.000 March Textile Car Export 4205
## 333 2023.000 January Electronics Cotton Export 7123
## 334 2024.000 September Automobile Medicine Export 1622
## 335 2019.000 January Pharma Mobile Import 3939
## 336 2018.000 December Textile Cotton Export 6876
## 337 2023.000 March Agriculture Mobile Import 9837
## 338 2023.000 July Textile Cotton Import 1719
## 339 2021.000 March Textile Mobile Import 5158
## 340 2024.000 February Electronics Mobile Import 9233
## 341 2020.000 March Pharma Mobile Import 6435
## 342 2023.000 May Pharma Wheat Export 2276
## 343 2019.000 February Textile Car Import 2235
## 344 2021.000 February Automobile Mobile Import 5682
## 345 2020.000 March Agriculture Cotton Export 6583
## 346 2019.000 June Textile Cotton Import 8478
## 347 2018.000 September Electronics Car Export 654
## 348 2024.000 July Pharma Medicine Import 5274
## 349 2023.000 July Agriculture Mobile Export 6037
## 350 2019.000 August Electronics Medicine Export 7751
## 351 2022.000 September Automobile Car Import 8113
## 352 2020.000 August Automobile Car Import 9395
## 353 2024.000 March Pharma Cotton Import 8535
## 354 2021.000 April Automobile Car Import 4167
## 355 2018.000 October Pharma Mobile Export 3525
## 356 2023.000 May Textile Medicine Export 8413
## 357 2021.000 May Textile Cotton Export 4386
## 358 2021.000 December Pharma Cotton Import 1693
## 359 2018.000 March Pharma Cotton Import 3190
## 360 2023.000 December Textile Cotton Import 6726
## 361 2020.000 July Automobile Car Export 3551
## 362 2024.000 November Electronics Medicine Export 7379
## 363 2021.000 February Agriculture Car Import 2927
## 364 2020.000 September Agriculture Cotton Export 7749
## 365 2022.000 February Agriculture Mobile Import 8926
## 366 2021.000 May Pharma Car Export 1645
## 367 2018.000 July Automobile Mobile Import 9376
## 368 2019.000 March Pharma Cotton Import 5341
## 369 2024.000 October Textile Cotton Import 9923
## 370 2023.000 August Textile Wheat Import 3020
## 371 2021.000 October Electronics Medicine Import 4477
## 372 2019.000 April Agriculture Car Export 2220
## 373 2021.000 February Agriculture Cotton Export 7633
## 374 2024.000 February Automobile Wheat Export 2601
## 375 2020.000 July Agriculture Mobile Export 3852
## 376 2024.000 November Textile Wheat Import 5568
## 377 2024.000 January Automobile Mobile Import 4007
## 378 2019.000 January Textile Wheat Import 7772
## 379 2022.000 December Textile Cotton Export 4324
## 380 2020.000 March Agriculture Mobile Export 8315
## 381 2022.000 February Automobile Cotton Import 7014
## 382 2023.000 April Automobile Wheat Import 6452
## 383 2023.000 May Agriculture Cotton Export 7922
## 384 2018.000 May Agriculture Wheat Export 6331
## 385 2024.000 November Electronics Cotton Export 1801
## 386 2020.000 November Electronics Medicine Import 3853
## 387 2022.000 May Automobile Car Import 5855
## 388 2020.000 March Agriculture Cotton Export 397
## 389 2024.000 September Pharma Car Import 2909
## 390 2018.000 April Automobile Medicine Export 1045
## 391 2024.000 March Textile Car Export 7646
## 392 2020.000 December Textile Wheat Import 498
## 393 2024.000 May Electronics Cotton Export 2301
## 394 2022.000 January Electronics Mobile Export 3122
## 395 2019.000 June Textile Car Import 5368
## 396 2020.000 March Textile Car Import 4747
## 397 2023.000 December Textile Cotton Export 4599
## 398 2018.000 March Pharma Medicine Import 7653
## 399 2024.000 October Electronics Car Export 5188
## 400 2022.000 November Agriculture Medicine Import 397
## 401 2021.000 May Automobile Car Export 4254
## 402 2022.000 November Electronics Car Import 6696
## 403 2018.000 December Textile Mobile Import 9279
## 404 2024.000 December Automobile Car Import 943
## 405 2022.000 June Pharma Medicine Export 139
## 406 2024.000 August Pharma Cotton Export 4521
## 407 2024.000 November Textile Medicine Export 2296
## 408 2018.000 June Electronics Cotton Import 1582
## 409 2019.000 February Electronics Mobile Export 1940
## 410 2021.000 January Textile Wheat Export 7082
## 411 2022.000 April Agriculture Cotton Import 7622
## 412 2018.000 February Pharma Cotton Import 1335
## 413 2021.000 September Agriculture Cotton Import 9591
## 414 2020.000 July Agriculture Cotton Import 6878
## 415 2020.000 December Automobile Cotton Export 2995
## 416 2020.000 April Automobile Medicine Export 4435
## 417 2019.000 January Textile Car Import 6310
## 418 2022.000 March Electronics Wheat Import 1571
## 419 2018.000 July Automobile Cotton Import 5891
## 420 2021.000 August Textile Mobile Export 5062
## 421 2022.000 November Automobile Car Export 2017
## 422 2023.000 October Electronics Car Export 7453
## 423 2023.000 January Agriculture Medicine Export 7493
## 424 2021.000 September Agriculture Car Export 9618
## 425 2021.000 April Pharma Medicine Export 2251
## 426 2019.000 October Pharma Medicine Import 3679
## 427 2020.000 October Electronics Medicine Import 5029
## 428 2020.000 May Pharma Car Import 5782
## 429 2018.000 October Automobile Medicine Export 3510
## 430 2023.000 January Agriculture Cotton Export 5692
## 431 2021.000 March Agriculture Car Import 9904
## 432 2022.000 November Automobile Mobile Export 8664
## 433 2018.000 July Pharma Medicine Import 3451
## 434 2024.000 October Pharma Medicine Export 5794
## 435 2018.000 April Agriculture Mobile Export 5360
## 436 2021.000 September Electronics Mobile Import 7446
## 437 2021.000 December Agriculture Cotton Export 1125
## 438 2020.000 September Agriculture Cotton Export 8089
## 439 2024.000 August Agriculture Car Export 149
## 440 2021.000 June Automobile Mobile Export 9632
## 441 2018.000 April Electronics Medicine Export 6126
## 442 2019.000 April Textile Medicine Export 3551
## 443 2021.000 July Pharma Cotton Export 8336
## 444 2023.000 January Electronics Mobile Import 7059
## 445 2021.000 September Textile Wheat Export 4225
## 446 2019.000 July Pharma Mobile Export 5039
## 447 2024.000 September Agriculture Mobile Export 8649
## 448 2023.000 July Pharma Cotton Import 535
## 449 2022.000 January Pharma Cotton Import 5545
## 450 2018.000 February Automobile Cotton Export 3725
## 451 2020.000 November Textile Car Import 5411
## 452 2022.000 May Pharma Medicine Import 8813
## 453 2024.000 November Textile Car Import 368
## 454 2021.000 July Pharma Cotton Export 659
## 455 2020.000 March Agriculture Cotton Import 4006
## 456 2024.000 March Textile Cotton Import 870
## 457 2020.000 August Electronics Car Import 6771
## 458 2020.000 February Textile Medicine Import 4995
## 459 2020.000 September Agriculture Wheat Import 3377
## 460 2023.000 September Automobile Cotton Export 7997
## 461 2018.000 May Electronics Mobile Export 8836
## 462 2018.000 August Textile Cotton Import 3102
## 463 2023.000 May Electronics Mobile Export 9764
## 464 2021.000 August Pharma Mobile Export 8599
## 465 2018.000 October Pharma Mobile Export 8670
## 466 2023.000 August Textile Car Export 5040
## 467 2022.000 June Automobile Medicine Import 4854
## 468 2024.000 March Electronics Wheat Import 7451
## 469 2018.000 September Agriculture Wheat Export 3006
## 470 2018.000 September Agriculture Mobile Import 527
## 471 2024.000 February Pharma Car Import 4306
## 472 2022.000 May Electronics Mobile Import 9436
## 473 2019.000 February Automobile Wheat Import 717
## 474 2022.000 December Textile Wheat Import 2019
## 475 2023.000 October Automobile Mobile Export 4680
## 476 2018.000 March Textile Mobile Export 2707
## 477 2023.000 December Automobile Mobile Export 2534
## 478 2021.000 March Textile Mobile Import 4575
## 479 2023.000 January Electronics Cotton Import 4713
## 480 2023.000 September Textile Car Import 3059
## 481 2018.000 December Pharma Medicine Import 604
## 482 2018.000 January Textile Mobile Import 1582
## 483 2022.000 April Textile Mobile Import 6009
## 484 2021.000 March Automobile Mobile Import 9221
## 485 2024.000 March Agriculture Wheat Export 7523
## 486 2021.000 January Textile Wheat Import 942
## 487 2020.000 June Electronics Car Import 1211
## 488 2024.000 September Agriculture Car Import 3927
## 489 2018.000 June Automobile Cotton Export 221
## 490 2023.000 August Automobile Mobile Import 4261
## 491 2022.000 April Automobile Mobile Import 4302
## 492 2023.000 February Agriculture Wheat Import 8569
## 493 2022.000 March Textile Car Import 7274
## 494 2022.000 January Agriculture Car Export 3984
## 495 2021.000 February Pharma Medicine Import 8324
## 496 2023.000 March Automobile Wheat Import 5569
## 497 2021.000 November Pharma Cotton Import 932
## 498 2019.000 February Pharma Mobile Import 7078
## 499 2021.000 April Pharma Car Export 1427
## 500 2024.000 September Automobile Medicine Import 2785
## 501 2021.000 August Automobile Medicine Import 2830
## 502 2020.000 September Textile Medicine Import 2216
## 503 2022.000 December Electronics Wheat Export 7205
## 504 2023.000 October Automobile Wheat Export 8310
## 505 2020.000 April Pharma Medicine Import 9286
## 506 2018.000 August Electronics Mobile Export 3974
## 507 2020.000 February Electronics Mobile Import 6232
## 508 2023.000 October Automobile Wheat Import 589
## 509 2021.000 August Textile Mobile Import 529
## 510 2023.000 January Pharma Cotton Export 2750
## 511 2020.000 January Agriculture Cotton Import 3738
## 512 2023.000 January Pharma Car Export 3551
## 513 2023.000 January Textile Mobile Import 4295
## 514 2021.000 May Textile Cotton Import 7780
## 515 2019.000 July Pharma Car Import 5832
## 516 2019.000 May Electronics Cotton Import 5850
## 517 2021.000 June Agriculture Mobile Export 5848
## 518 2021.000 November Textile Wheat Export 3577
## 519 2021.000 September Textile Mobile Import 9682
## 520 2019.000 April Pharma Cotton Export 9572
## 521 2023.000 May Electronics Medicine Export 6283
## 522 2023.000 December Automobile Cotton Export 5672
## 523 2018.000 September Textile Car Import 1051
## 524 2024.000 February Textile Cotton Export 8608
## 525 2022.000 September Electronics Wheat Export 3938
## 526 2024.000 June Automobile Mobile Import 6061
## 527 2023.000 December Pharma Cotton Import 626
## 528 2019.000 August Agriculture Medicine Export 5872
## 529 2019.000 July Pharma Cotton Import 7830
## 530 2024.000 November Automobile Cotton Import 685
## 531 2024.000 December Automobile Cotton Import 6601
## 532 2022.000 July Pharma Cotton Import 9769
## 533 2018.000 April Electronics Medicine Import 432
## 534 2021.000 September Electronics Wheat Export 6554
## 535 2023.000 September Electronics Wheat Import 9428
## 536 2024.000 December Agriculture Medicine Import 9834
## 537 2019.000 May Agriculture Wheat Export 3088
## 538 2022.000 April Electronics Medicine Import 7245
## 539 2021.000 June Electronics Car Import 9961
## 540 2023.000 September Automobile Medicine Export 4088
## 541 2023.000 June Automobile Medicine Export 9560
## 542 2018.000 January Agriculture Mobile Import 3092
## 543 2024.000 April Pharma Medicine Export 872
## 544 2019.000 February Textile Mobile Export 8486
## 545 2021.000 July Automobile Medicine Export 7035
## 546 2020.000 May Agriculture Mobile Import 1204
## 547 2021.000 April Automobile Mobile Import 4062
## 548 2018.000 June Agriculture Mobile Export 3150
## 549 2022.000 October Textile Medicine Import 2657
## 550 2018.000 July Agriculture Mobile Import 2561
## 551 2018.000 November Textile Mobile Export 9793
## 552 2019.000 August Pharma Mobile Export 9358
## 553 2024.000 December Pharma Cotton Export 5427
## 554 2020.000 March Agriculture Car Import 4478
## 555 2020.000 January Textile Mobile Export 6534
## 556 2018.000 August Agriculture Wheat Import 4758
## 557 2018.000 October Pharma Mobile Export 8018
## 558 2018.000 November Pharma Car Export 786
## 559 2019.000 September Automobile Car Import 3906
## 560 2018.000 August Electronics Cotton Export 1267
## 561 2020.000 November Agriculture Mobile Export 8911
## 562 2018.000 December Pharma Wheat Import 3519
## 563 2023.000 March Agriculture Cotton Import 1928
## 564 2023.000 March Automobile Cotton Export 3130
## 565 2021.000 August Textile Medicine Export 9758
## 566 2023.000 August Pharma Mobile Import 3078
## 567 2019.000 July Textile Wheat Export 6223
## 568 2022.000 June Electronics Wheat Import 3596
## 569 2020.000 February Textile Mobile Import 8071
## 570 2018.000 September Automobile Wheat Import 8859
## 571 2018.000 September Electronics Mobile Export 4919
## 572 2020.000 October Automobile Wheat Import 5455
## 573 2020.000 August Automobile Cotton Export 1593
## 574 2024.000 February Textile Cotton Import 7141
## 575 2018.000 August Pharma Mobile Import 2634
## 576 2019.000 June Pharma Cotton Export 1939
## 577 2021.000 November Textile Car Export 3366
## 578 2024.000 September Pharma Medicine Import 5228
## 579 2019.000 June Electronics Cotton Export 9063
## 580 2020.000 January Automobile Cotton Export 5934
## 581 2020.000 May Textile Medicine Import 8298
## 582 2023.000 October Electronics Mobile Export 9446
## 583 2022.000 August Agriculture Mobile Export 1399
## 584 2024.000 September Textile Wheat Export 628
## 585 2022.000 June Agriculture Medicine Import 5430
## 586 2018.000 July Electronics Medicine Import 4503
## 587 2023.000 November Textile Car Export 2398
## 588 2023.000 December Automobile Mobile Import 2402
## 589 2018.000 March Agriculture Cotton Import 1686
## 590 2023.000 May Electronics Medicine Import 6490
## 591 2020.000 March Pharma Medicine Export 4328
## 592 2019.000 December Agriculture Medicine Export 1728
## 593 2023.000 February Pharma Cotton Import 7367
## 594 2024.000 June Textile Cotton Import 2694
## 595 2021.000 August Electronics Cotton Export 9543
## 596 2020.000 May Pharma Cotton Import 7074
## 597 2020.000 April Automobile Wheat Import 8375
## 598 2022.000 November Automobile Medicine Import 4838
## 599 2019.000 October Pharma Medicine Import 8889
## 600 2022.000 December Textile Car Import 5812
## 601 2020.000 October Agriculture Medicine Export 5299
## 602 2023.000 May Automobile Car Import 6244
## 603 2023.000 August Electronics Wheat Import 2554
## 604 2018.000 November Textile Mobile Export 8341
## 605 2023.000 December Electronics Medicine Export 8803
## 606 2021.000 December Agriculture Mobile Export 5589
## 607 2024.000 October Automobile Mobile Import 1203
## 608 2019.000 July Agriculture Car Import 1469
## 609 2018.000 December Pharma Car Import 4707
## 610 2020.000 November Textile Wheat Export 9754
## 611 2022.000 December Pharma Wheat Import 9229
## 612 2024.000 September Textile Cotton Export 3805
## 613 2023.000 December Agriculture Mobile Export 9175
## 614 2019.000 November Electronics Medicine Export 9521
## 615 2022.000 May Pharma Car Import 1784
## 616 2020.000 June Automobile Medicine Export 2415
## 617 2021.000 August Textile Mobile Export 8099
## 618 2022.000 April Pharma Wheat Import 9886
## 619 2024.000 August Automobile Wheat Export 7561
## 620 2023.000 August Automobile Cotton Import 7773
## 621 2023.000 December Pharma Wheat Export 1380
## 622 2020.000 August Textile Mobile Import 3078
## 623 2023.000 June Automobile Car Import 5582
## 624 2019.000 March Agriculture Cotton Export 1598
## 625 2020.000 September Agriculture Medicine Import 4165
## 626 2018.000 April Electronics Medicine Import 8080
## 627 2018.000 May Pharma Medicine Import 9148
## 628 2020.000 July Textile Car Import 5020
## 629 2022.000 September Pharma Cotton Import 1851
## 630 2023.000 February Pharma Wheat Export 8851
## 631 2020.000 November Automobile Cotton Export 6334
## 632 2020.000 November Electronics Cotton Export 7837
## 633 2018.000 October Textile Medicine Export 8873
## 634 2021.000 February Agriculture Mobile Export 6170
## 635 2018.000 December Automobile Medicine Import 4273
## 636 2024.000 October Agriculture Mobile Import 6945
## 637 2023.000 November Agriculture Car Export 6198
## 638 2021.000 May Automobile Mobile Import 4831
## 639 2019.000 August Pharma Cotton Export 4643
## 640 2022.000 December Agriculture Medicine Export 8382
## 641 2023.000 September Electronics Mobile Export 3600
## 642 2023.000 June Electronics Medicine Import 8861
## 643 2022.000 December Electronics Cotton Export 6599
## 644 2018.000 June Automobile Medicine Export 602
## 645 2022.000 November Agriculture Mobile Import 2489
## 646 2023.000 March Electronics Cotton Export 5443
## 647 2021.000 February Textile Mobile Export 7086
## 648 2021.000 December Agriculture Mobile Export 2793
## 649 2021.000 April Pharma Cotton Import 3017
## 650 2020.000 September Textile Car Export 4969
## 651 2018.000 November Agriculture Medicine Import 6079
## 652 2018.000 July Electronics Medicine Export 3722
## 653 2023.000 January Automobile Wheat Export 7612
## 654 2021.000 January Agriculture Wheat Export 4247
## 655 2018.000 June Electronics Wheat Import 1084
## 656 2020.000 April Electronics Car Import 6810
## 657 2022.000 June Pharma Car Export 7744
## 658 2024.000 August Textile Medicine Export 5797
## 659 2019.000 April Textile Mobile Import 1747
## 660 2018.000 February Automobile Cotton Import 4307
## 661 2021.000 January Agriculture Medicine Import 5544
## 662 2021.000 January Automobile Car Export 4628
## 663 2024.000 August Pharma Mobile Export 3228
## 664 2019.000 March Agriculture Cotton Export 4719
## 665 2019.000 February Automobile Medicine Import 9061
## 666 2024.000 December Automobile Cotton Export 1927
## 667 2019.000 October Automobile Car Import 1630
## 668 2022.000 August Agriculture Cotton Import 5814
## 669 2023.000 May Textile Mobile Export 8689
## 670 2023.000 May Electronics Wheat Import 3205
## 671 2020.000 June Textile Medicine Export 175
## 672 2019.000 May Pharma Car Import 6127
## 673 2023.000 April Automobile Medicine Export 1320
## 674 2024.000 June Pharma Wheat Export 8633
## 675 2024.000 January Pharma Cotton Import 9438
## 676 2021.000 February Textile Wheat Export 6224
## 677 2021.000 March Pharma Wheat Export 8185
## 678 2020.000 July Automobile Wheat Export 321
## 679 2018.000 June Textile Medicine Import 1499
## 680 2019.000 September Electronics Medicine Export 8575
## 681 2019.000 February Pharma Car Export 9576
## 682 2023.000 January Automobile Car Import 9023
## 683 2021.000 March Pharma Wheat Import 2246
## 684 2021.000 November Agriculture Car Export 6499
## 685 2018.000 February Textile Medicine Export 6374
## 686 2020.000 September Pharma Cotton Export 3170
## 687 2019.000 January Agriculture Medicine Import 9667
## 688 2018.000 December Agriculture Cotton Import 6353
## 689 2019.000 June Pharma Medicine Export 8660
## 690 2023.000 November Pharma Cotton Export 4825
## 691 2023.000 January Pharma Car Export 2244
## 692 2022.000 January Textile Mobile Export 1178
## 693 2018.000 November Pharma Car Export 1823
## 694 2019.000 September Automobile Cotton Import 1896
## 695 2022.000 July Pharma Mobile Import 250
## 696 2020.000 November Pharma Car Import 7907
## 697 2020.000 May Automobile Mobile Export 758
## 698 2021.000 June Agriculture Medicine Export 8786
## 699 2019.000 August Automobile Car Import 7513
## 700 2018.000 June Electronics Cotton Export 1624
## 701 2021.000 May Pharma Medicine Import 5565
## 702 2023.000 September Electronics Wheat Import 3267
## 703 2023.000 November Automobile Wheat Import 1741
## 704 2023.000 January Electronics Wheat Export 8960
## 705 2020.000 May Pharma Car Import 2263
## 706 2021.000 January Automobile Car Import 5104
## 707 2019.000 July Agriculture Cotton Export 6816
## 708 2018.000 January Agriculture Car Import 7880
## 709 2023.000 May Agriculture Mobile Import 5112
## 710 2024.000 February Automobile Wheat Import 4982
## 711 2020.000 March Textile Mobile Import 2082
## 712 2022.000 August Agriculture Medicine Export 1322
## 713 2019.000 April Textile Medicine Import 2024
## 714 2021.000 September Textile Wheat Import 2267
## 715 2020.000 November Agriculture Car Import 5572
## 716 2018.000 July Pharma Cotton Import 9700
## 717 2018.000 December Pharma Car Export 6282
## 718 2022.000 September Electronics Car Import 5530
## 719 2018.000 April Electronics Medicine Export 1636
## 720 2020.000 March Textile Mobile Export 7706
## 721 2024.000 August Electronics Car Import 6840
## 722 2021.000 August Automobile Car Import 7183
## 723 2021.000 July Automobile Car Import 4568
## 724 2018.000 December Agriculture Car Export 9899
## 725 2024.000 July Automobile Wheat Export 748
## 726 2041.092 December Agriculture Medicine Export 7217
## 727 2024.000 December Automobile Car Export 4410
## 728 2023.000 September Pharma Medicine Import 5245
## 729 2023.000 October Electronics Car Export 1630
## 730 2020.000 December Electronics Cotton Import 5778
## 731 2022.000 January Automobile Wheat Export 6140
## 732 2022.000 December Textile Car Import 4110
## 733 2021.000 February Automobile Car Export 441
## 734 2020.000 February Pharma Car Import 6806
## 735 2024.000 December Pharma Cotton Export 9209
## 736 2020.000 September Textile Medicine Import 5662
## 737 2022.000 June Textile Car Import 7447
## 738 2020.000 March Electronics Cotton Export 9814
## 739 2018.000 October Electronics Car Import 5612
## 740 2020.000 January Electronics Car Export 282
## 741 2018.000 August Automobile Wheat Export 1873
## 742 2023.000 October Automobile Car Import 6454
## 743 2018.000 December Textile Car Import 3287
## 744 2023.000 April Textile Medicine Export 7048
## 745 2021.000 October Electronics Medicine Import 1296
## 746 2020.000 August Automobile Mobile Export 1348
## 747 2023.000 February Electronics Mobile Import 7047
## 748 2023.000 January Pharma Medicine Import 8165
## 749 2020.000 December Agriculture Car Import 5904
## 750 2024.000 June Agriculture Cotton Import 9666
## 751 2021.000 June Textile Wheat Import 6223
## 752 2019.000 July Agriculture Car Import 1494
## 753 2019.000 June Textile Wheat Export 9133
## 754 2023.000 April Textile Wheat Export 3039
## 755 2023.000 September Automobile Wheat Import 2196
## 756 2019.000 August Automobile Medicine Export 481
## 757 2024.000 February Automobile Wheat Export 839
## 758 2023.000 May Pharma Car Import 9197
## 759 2023.000 February Textile Cotton Import 1823
## 760 2024.000 August Automobile Wheat Import 2421
## 761 2023.000 December Automobile Wheat Export 2464
## 762 2022.000 April Textile Medicine Export 4079
## 763 2018.000 January Automobile Cotton Import 8210
## 764 2018.000 November Pharma Mobile Export 3365
## 765 2024.000 February Agriculture Mobile Import 2503
## 766 2022.000 February Electronics Mobile Export 1267
## 767 2018.000 September Textile Wheat Export 4167
## 768 2018.000 February Agriculture Mobile Import 1946
## 769 2022.000 April Automobile Wheat Import 2428
## 770 2019.000 March Agriculture Mobile Import 9435
## 771 2022.000 April Textile Mobile Import 6779
## 772 2024.000 January Automobile Cotton Export 6900
## 773 2019.000 March Electronics Wheat Export 846
## 774 2019.000 March Textile Mobile Import 695
## 775 2021.000 July Electronics Medicine Import 8580
## 776 2019.000 November Textile Mobile Import 7875
## 777 2018.000 September Automobile Mobile Import 6879
## 778 2021.000 March Textile Cotton Import 8918
## 779 2023.000 December Agriculture Medicine Export 8843
## 780 2018.000 January Pharma Medicine Export 7298
## 781 2021.000 February Automobile Wheat Import 8035
## 782 2023.000 November Electronics Mobile Export 1837
## 783 2023.000 July Automobile Cotton Import 4961
## 784 2018.000 October Electronics Wheat Export 8077
## 785 2018.000 December Electronics Medicine Export 7435
## 786 2024.000 February Electronics Car Import 5073
## 787 2022.000 February Agriculture Medicine Export 2807
## 788 2021.000 November Automobile Mobile Export 7833
## 789 2020.000 January Electronics Car Export 2577
## 790 2023.000 February Electronics Medicine Import 3803
## 791 2021.000 June Agriculture Medicine Export 2560
## 792 2024.000 July Agriculture Medicine Import 9496
## 793 2024.000 April Pharma Medicine Export 5075
## 794 2020.000 January Automobile Car Export 974
## 795 2023.000 March Agriculture Car Import 6313
## 796 2019.000 December Electronics Cotton Export 8879
## 797 2018.000 April Agriculture Wheat Import 8968
## 798 2020.000 September Automobile Mobile Import 6619
## 799 2022.000 August Electronics Mobile Export 4494
## 800 2023.000 July Pharma Wheat Import 1192
## 801 2020.000 January Textile Car Import 2050
## 802 2021.000 August Textile Mobile Import 4849
## 803 2024.000 July Agriculture Mobile Export 2430
## 804 2023.000 April Automobile Car Export 4430
## 805 2019.000 May Agriculture Medicine Export 4798
## 806 2022.000 August Automobile Car Export 4285
## 807 2023.000 November Textile Cotton Import 5380
## 808 2021.000 August Electronics Wheat Import 7859
## 809 2022.000 July Textile Wheat Export 9842
## 810 2019.000 October Textile Car Export 2354
## 811 2021.000 July Agriculture Cotton Export 2782
## 812 2022.000 January Electronics Medicine Import 3096
## 813 2023.000 April Pharma Cotton Export 2683
## 814 2021.000 April Pharma Cotton Export 9006
## 815 2023.000 June Pharma Medicine Export 7575
## 816 2019.000 November Electronics Mobile Import 1546
## 817 2022.000 June Pharma Medicine Import 7856
## 818 2021.000 December Electronics Wheat Export 9464
## 819 2019.000 September Agriculture Mobile Export 9227
## 820 2020.000 October Electronics Mobile Export 4456
## 821 2018.000 November Agriculture Cotton Import 7326
## 822 2019.000 July Agriculture Wheat Import 6943
## 823 2021.000 September Textile Car Import 3004
## 824 2019.000 August Electronics Cotton Export 2927
## 825 2023.000 October Agriculture Mobile Import 5286
## 826 2021.000 November Electronics Medicine Export 5302
## 827 2024.000 February Agriculture Mobile Export 1787
## 828 2024.000 November Electronics Cotton Import 1606
## 829 2023.000 February Automobile Cotton Export 1751
## 830 2020.000 January Textile Car Export 1039
## 831 2023.000 January Automobile Car Export 1292
## 832 2024.000 June Automobile Mobile Export 9826
## 833 2022.000 April Textile Mobile Import 2864
## 834 2022.000 August Pharma Wheat Export 6591
## 835 2019.000 December Automobile Mobile Export 9983
## 836 2019.000 December Pharma Mobile Export 7133
## 837 2018.000 December Pharma Car Export 1981
## 838 2021.000 February Automobile Wheat Export 4263
## 839 2022.000 August Textile Mobile Export 5205
## 840 2021.000 November Pharma Medicine Import 3699
## 841 2018.000 March Electronics Cotton Export 3500
## 842 2020.000 February Agriculture Wheat Export 738
## 843 2018.000 April Agriculture Wheat Import 6171
## 844 2020.000 January Textile Cotton Import 516
## 845 2024.000 October Automobile Mobile Import 1607
## 846 2023.000 August Pharma Car Export 7586
## 847 2018.000 June Automobile Medicine Import 1006
## 848 2024.000 August Pharma Mobile Import 4396
## 849 2024.000 May Pharma Wheat Import 4257
## 850 2020.000 May Automobile Wheat Import 3675
## 851 2021.000 December Automobile Car Import 3978
## 852 2022.000 September Textile Medicine Import 8065
## 853 2018.000 July Electronics Car Import 5287
## 854 2022.000 May Pharma Cotton Export 8659
## 855 2020.000 June Automobile Wheat Import 7015
## 856 2019.000 November Automobile Mobile Export 8556
## 857 2023.000 May Agriculture Wheat Import 1704
## 858 2021.000 June Automobile Cotton Export 5079
## 859 2024.000 December Pharma Mobile Export 4316
## 860 2024.000 March Pharma Medicine Import 1229
## 861 2022.000 April Textile Wheat Export 2906
## 862 2021.000 December Electronics Car Export 1895
## 863 2018.000 December Textile Cotton Import 438
## 864 2018.000 September Agriculture Medicine Export 8174
## 865 2021.000 May Pharma Car Import 9554
## 866 2018.000 September Automobile Mobile Import 8112
## 867 2019.000 June Electronics Wheat Export 8573
## 868 2024.000 November Pharma Wheat Import 9320
## 869 2022.000 February Textile Medicine Import 662
## 870 2020.000 February Agriculture Mobile Import 4378
## 871 2019.000 June Electronics Cotton Export 3115
## 872 2018.000 September Textile Car Import 2598
## 873 2022.000 June Agriculture Cotton Import 4825
## 874 2021.000 November Electronics Cotton Import 2334
## 875 2019.000 July Agriculture Car Export 3322
## 876 2018.000 September Electronics Mobile Import 8158
## 877 2019.000 June Automobile Cotton Export 9698
## 878 2023.000 November Textile Cotton Export 7954
## 879 2019.000 April Textile Wheat Import 1445
## 880 2021.000 April Automobile Cotton Export 5361
## 881 2019.000 February Pharma Cotton Export 2653
## 882 2024.000 March Automobile Mobile Import 9962
## 883 2024.000 August Agriculture Car Export 1568
## 884 2019.000 October Textile Mobile Export 7379
## 885 2019.000 August Automobile Mobile Export 1832
## 886 2018.000 August Electronics Wheat Export 2592
## 887 2023.000 April Electronics Wheat Import 3874
## 888 2020.000 November Textile Mobile Import 3481
## 889 2023.000 July Textile Mobile Import 7719
## 890 2023.000 October Agriculture Medicine Import 7923
## 891 2018.000 November Pharma Mobile Export 1790
## 892 2023.000 February Pharma Wheat Import 2548
## 893 2024.000 March Textile Car Export 570
## 894 2021.000 November Agriculture Cotton Import 3071
## 895 2021.000 May Automobile Medicine Export 4576
## 896 2023.000 May Pharma Mobile Import 1567
## 897 2022.000 June Textile Wheat Import 1919
## 898 2022.000 July Pharma Mobile Export 5288
## 899 2019.000 October Agriculture Mobile Export 2264
## 900 2023.000 August Electronics Car Import 9711
## 901 2020.000 April Electronics Wheat Import 9619
## 902 2024.000 September Electronics Medicine Import 7221
## 903 2020.000 July Pharma Wheat Export 2862
## 904 2023.000 September Agriculture Car Export 486
## 905 2021.000 February Electronics Wheat Import 4680
## 906 2018.000 January Agriculture Medicine Import 301
## 907 2019.000 December Textile Car Export 6292
## 908 2022.000 August Agriculture Wheat Export 9367
## 909 2018.000 December Textile Mobile Export 8834
## 910 2021.000 April Pharma Mobile Import 7090
## 911 2020.000 February Textile Car Export 692
## 912 2018.000 July Automobile Wheat Export 8159
## 913 2020.000 June Textile Cotton Export 9837
## 914 2018.000 September Agriculture Wheat Export 2036
## 915 2018.000 July Agriculture Wheat Import 7759
## 916 2021.000 April Electronics Wheat Import 6755
## 917 2019.000 March Electronics Wheat Import 4641
## 918 2019.000 July Electronics Medicine Import 6970
## 919 2022.000 October Pharma Car Export 248
## 920 2024.000 January Automobile Medicine Export 7762
## 921 2024.000 February Pharma Mobile Export 2123
## 922 2018.000 January Pharma Wheat Import 6983
## 923 2023.000 October Electronics Medicine Import 8533
## 924 2024.000 November Automobile Medicine Import 6846
## 925 2022.000 September Textile Car Export 3933
## 926 2021.000 October Pharma Medicine Import 8241
## 927 2020.000 September Textile Medicine Export 4791
## 928 2020.000 February Textile Mobile Export 2171
## 929 2024.000 December Textile Car Export 1084
## 930 2024.000 January Textile Cotton Export 5550
## 931 2019.000 December Agriculture Mobile Import 3824
## 932 2024.000 March Automobile Wheat Import 5911
## 933 2021.000 April Pharma Wheat Import 4005
## 934 2020.000 August Agriculture Wheat Export 1279
## 935 2020.000 June Electronics Medicine Export 2178
## 936 2018.000 August Pharma Wheat Import 8798
## 937 2023.000 July Electronics Cotton Export 189
## 938 2020.000 April Agriculture Medicine Import 9419
## 939 2021.000 November Pharma Wheat Import 9249
## 940 2023.000 July Automobile Medicine Export 3811
## 941 2018.000 August Textile Wheat Import 4728
## 942 2022.000 January Pharma Wheat Export 3743
## 943 2018.000 December Electronics Medicine Export 1779
## 944 2020.000 March Automobile Wheat Import 4038
## 945 2019.000 July Automobile Cotton Import 6026
## 946 2020.000 November Agriculture Wheat Import 8806
## 947 2024.000 September Automobile Mobile Import 2114
## 948 2018.000 November Automobile Mobile Export 1136
## 949 2020.000 December Automobile Car Import 1773
## 950 2022.000 May Automobile Medicine Export 7024
## 951 2020.000 December Automobile Mobile Export 223
## 952 2019.000 May Agriculture Wheat Export 6167
## 953 2018.000 November Electronics Mobile Export 6199
## 954 2024.000 March Automobile Car Import 1814
## 955 2023.000 October Pharma Car Export 9771
## 956 2020.000 January Electronics Cotton Export 7262
## 957 2021.000 July Automobile Wheat Export 3186
## 958 2021.000 June Agriculture Medicine Import 8874
## 959 2021.000 February Electronics Wheat Import 873
## 960 2023.000 January Textile Mobile Export 1622
## 961 2022.000 July Agriculture Cotton Export 8801
## 962 2023.000 April Pharma Wheat Import 1901
## 963 2022.000 March Agriculture Wheat Import 3590
## 964 2018.000 December Electronics Wheat Import 2311
## 965 2021.000 November Electronics Medicine Export 4948
## 966 2020.000 April Automobile Medicine Export 4611
## 967 2019.000 August Textile Medicine Import 6938
## 968 2019.000 August Textile Medicine Import 4932
## 969 2023.000 May Textile Wheat Import 4256
## 970 2021.000 March Electronics Car Export 3208
## 971 2022.000 September Automobile Mobile Import 6412
## 972 2021.000 July Electronics Wheat Import 4002
## 973 2018.000 June Textile Wheat Import 4856
## 974 2021.000 May Pharma Medicine Export 5170
## 975 2022.000 June Agriculture Mobile Import 5073
## 976 2023.000 September Automobile Medicine Export 1109
## 977 2021.000 June Automobile Cotton Import 144
## 978 2022.000 January Agriculture Cotton Export 6873
## 979 2019.000 February Automobile Wheat Import 1194
## 980 2020.000 February Pharma Mobile Export 770
## 981 2024.000 November Pharma Mobile Export 3094
## 982 2018.000 July Textile Cotton Export 4617
## 983 2023.000 June Automobile Car Export 5994
## 984 2018.000 November Agriculture Cotton Export 8248
## 985 2019.000 February Electronics Car Export 2884
## 986 2021.000 January Electronics Mobile Export 5089
## 987 2019.000 February Pharma Mobile Export 2419
## 988 2022.000 May Pharma Medicine Import 394
## 989 2021.000 October Electronics Cotton Import 6056
## 990 2020.000 February Electronics Car Export 4094
## 991 2021.000 October Agriculture Wheat Import 6753
## 992 2023.000 March Pharma Wheat Export 6252
## 993 2019.000 November Automobile Mobile Export 5298
## 994 2018.000 September Textile Wheat Export 7929
## 995 2021.000 July Electronics Medicine Export 4215
## 996 2024.000 April Agriculture Cotton Export 1002
## 997 2023.000 March Automobile Mobile Export 2706
## 998 2023.000 September Automobile Mobile Export 2253
## 999 2023.000 March Textile Cotton Export 4661
## 1000 2022.000 July Electronics Wheat Import 2599
## 1001 2023.000 April Pharma Car Import 8300
## 1002 2019.000 September Agriculture Medicine Export 2027
## 1003 2024.000 April Agriculture Wheat Export 1945
## 1004 2018.000 August Textile Mobile Export 9131
## 1005 2022.000 March Pharma Medicine Import 4301
## 1006 2019.000 August Agriculture Cotton Export 9952
## 1007 2018.000 April Automobile Mobile Import 4314
## 1008 2020.000 May Textile Medicine Import 2042
## 1009 2018.000 February Automobile Medicine Export 2571
## 1010 2020.000 December Agriculture Medicine Export 4887
## 1011 2019.000 May Automobile Car Export 7748
## 1012 2024.000 September Agriculture Mobile Import 873
## 1013 2021.000 August Pharma Wheat Export 4090
## 1014 2020.000 September Textile Cotton Import 5224
## 1015 2023.000 May Agriculture Cotton Export 3908
## 1016 2023.000 January Automobile Cotton Export 6751
## 1017 2022.000 May Electronics Car Import 3651
## 1018 2024.000 February Textile Cotton Export 5788
## 1019 2018.000 July Agriculture Mobile Export 5072
## 1020 2022.000 July Pharma Mobile Export 2510
## 1021 2024.000 October Electronics Car Export 4361
## 1022 2023.000 May Electronics Car Import 2517
## 1023 2019.000 October Electronics Mobile Import 6176
## 1024 2024.000 September Agriculture Medicine Export 8206
## 1025 2023.000 September Automobile Cotton Import 9238
## 1026 2023.000 October Pharma Cotton Export 3442
## 1027 2024.000 February Textile Cotton Import 7682
## 1028 2018.000 May Pharma Car Import 4087
## 1029 2023.000 May Agriculture Mobile Import 9584
## 1030 2024.000 July Automobile Car Import 8976
## 1031 2021.000 May Automobile Mobile Import 4776
## 1032 2020.000 March Automobile Medicine Export 1438
## 1033 2022.000 October Electronics Wheat Import 8380
## 1034 2018.000 January Electronics Wheat Import 7427
## 1035 2019.000 September Agriculture Car Import 4307
## 1036 2020.000 February Textile Cotton Export 1884
## 1037 2019.000 November Electronics Car Import 5652
## 1038 2024.000 December Textile Wheat Export 932
## 1039 2019.000 September Agriculture Car Export 8474
## 1040 2024.000 November Automobile Mobile Export 4520
## 1041 2024.000 November Automobile Mobile Export 5042
## 1042 2022.000 November Pharma Cotton Import 8409
## 1043 2019.000 January Automobile Car Export 1347
## 1044 2022.000 April Automobile Car Import 2212
## 1045 2021.000 February Textile Medicine Export 5547
## 1046 2019.000 October Automobile Cotton Import 368
## 1047 2023.000 August Automobile Mobile Export 4340
## 1048 2024.000 February Agriculture Cotton Export 9984
## 1049 2024.000 January Agriculture Mobile Export 4440
## 1050 2019.000 November Textile Cotton Export 3182
## 1051 2019.000 September Textile Cotton Export 4313
## 1052 2024.000 December Textile Mobile Export 641
## 1053 2022.000 February Agriculture Wheat Export 4809
## 1054 2023.000 June Automobile Car Import 1861
## 1055 2019.000 February Agriculture Wheat Import 382
## 1056 2019.000 June Textile Wheat Export 3921
## 1057 2018.000 November Electronics Car Export 2118
## 1058 2022.000 February Textile Car Export 8327
## 1059 2019.000 June Electronics Cotton Import 219
## 1060 2018.000 February Agriculture Mobile Import 2779
## 1061 2022.000 February Textile Cotton Import 5272
## 1062 2020.000 May Electronics Cotton Import 6712
## 1063 2018.000 January Agriculture Wheat Export 5350
## 1064 2023.000 November Pharma Medicine Export 5447
## 1065 2024.000 August Agriculture Cotton Export 3413
## 1066 2018.000 July Agriculture Wheat Export 8563
## 1067 2018.000 April Automobile Mobile Export 9693
## 1068 2021.000 October Automobile Mobile Export 1132
## 1069 2021.000 March Textile Medicine Import 5518
## 1070 2021.000 September Electronics Cotton Export 5467
## 1071 2018.000 May Automobile Medicine Import 5509
## 1072 2021.000 June Agriculture Mobile Export 4746
## 1073 2019.000 November Automobile Medicine Import 6829
## 1074 2018.000 December Electronics Car Export 5349
## 1075 2019.000 July Automobile Medicine Export 4556
## 1076 2022.000 August Textile Mobile Import 677
## 1077 2018.000 June Pharma Car Import 7473
## 1078 2021.000 January Electronics Cotton Import 1712
## 1079 2021.000 December Automobile Mobile Import 526
## 1080 2020.000 September Agriculture Medicine Export 5906
## 1081 2020.000 November Automobile Wheat Export 9863
## 1082 2024.000 January Agriculture Mobile Export 8332
## 1083 2020.000 June Pharma Car Import 7463
## 1084 2023.000 April Textile Cotton Import 6176
## 1085 2020.000 June Automobile Cotton Export 3809
## 1086 2023.000 September Textile Medicine Export 9807
## 1087 2020.000 November Agriculture Car Import 2912
## 1088 2023.000 December Electronics Medicine Import 8529
## 1089 2022.000 May Pharma Medicine Import 8209
## 1090 2021.000 June Pharma Car Import 2732
## 1091 2024.000 August Pharma Medicine Export 8406
## 1092 2022.000 January Electronics Wheat Import 7365
## 1093 2020.000 March Agriculture Cotton Export 142
## 1094 2019.000 February Electronics Car Import 4787
## 1095 2019.000 February Pharma Mobile Import 1250
## 1096 2020.000 January Textile Cotton Export 9332
## 1097 2024.000 May Agriculture Medicine Export 1603
## 1098 2019.000 December Textile Mobile Import 1900
## 1099 2022.000 June Textile Wheat Import 333
## 1100 2022.000 October Textile Wheat Export 7605
## 1101 2021.000 June Agriculture Mobile Export 5757
## 1102 2021.000 June Automobile Medicine Import 8504
## 1103 2019.000 November Pharma Medicine Import 5325
## 1104 2018.000 September Textile Cotton Export 8646
## 1105 2024.000 January Automobile Medicine Import 2582
## 1106 2023.000 January Textile Wheat Import 6540
## 1107 2020.000 February Pharma Cotton Export 7909
## 1108 2021.000 December Automobile Car Export 8186
## 1109 2019.000 August Pharma Wheat Export 1176
## 1110 2020.000 February Pharma Car Import 7545
## 1111 2021.000 September Automobile Wheat Export 9956
## 1112 2018.000 August Electronics Medicine Import 9874
## 1113 2021.000 March Automobile Medicine Import 8066
## 1114 2018.000 August Pharma Wheat Export 5242
## 1115 2020.000 March Agriculture Medicine Import 6142
## 1116 2018.000 November Pharma Medicine Export 8661
## 1117 2018.000 February Electronics Medicine Export 6797
## 1118 2024.000 July Agriculture Medicine Export 8751
## 1119 2023.000 June Automobile Wheat Export 6933
## 1120 2024.000 February Electronics Medicine Import 5007
## 1121 2024.000 October Pharma Car Export 5570
## 1122 2024.000 December Electronics Medicine Import 4589
## 1123 2021.000 July Pharma Cotton Export 1468
## 1124 2023.000 January Agriculture Mobile Import 8056
## 1125 2021.000 January Agriculture Car Export 9304
## 1126 2020.000 September Agriculture Car Import 3940
## 1127 2019.000 July Textile Mobile Export 7173
## 1128 2021.000 February Agriculture Cotton Export 4969
## 1129 2023.000 April Automobile Car Export 722
## 1130 2021.000 July Agriculture Cotton Export 1070
## 1131 2018.000 October Electronics Mobile Import 4193
## 1132 2024.000 February Automobile Wheat Export 8522
## 1133 2024.000 February Textile Wheat Export 5177
## 1134 2018.000 August Electronics Wheat Export 6801
## 1135 2018.000 September Automobile Medicine Export 3615
## 1136 2020.000 July Pharma Cotton Import 5642
## 1137 2020.000 December Pharma Cotton Export 6066
## 1138 2023.000 August Textile Car Export 2640
## 1139 2024.000 May Electronics Wheat Import 3679
## 1140 2022.000 June Textile Mobile Export 2081
## 1141 2022.000 January Agriculture Cotton Import 231
## 1142 2020.000 April Automobile Car Import 6001
## 1143 2024.000 November Automobile Medicine Import 9793
## 1144 2021.000 November Agriculture Mobile Export 3813
## 1145 2024.000 April Electronics Mobile Import 9988
## 1146 2020.000 April Textile Medicine Import 8585
## 1147 2021.000 May Automobile Car Export 3241
## 1148 2018.000 December Textile Mobile Export 8095
## 1149 2021.000 November Electronics Cotton Import 1909
## 1150 2020.000 February Automobile Car Export 6281
## 1151 2021.000 October Pharma Medicine Export 473
## 1152 2018.000 June Agriculture Car Import 6377
## 1153 2023.000 October Pharma Mobile Export 3435
## 1154 2018.000 August Pharma Mobile Export 9131
## 1155 2024.000 February Pharma Wheat Export 2206
## 1156 2024.000 December Agriculture Cotton Import 904
## 1157 2022.000 December Electronics Car Import 9364
## 1158 2022.000 February Agriculture Wheat Export 5443
## 1159 2019.000 December Textile Medicine Import 4761
## 1160 2018.000 October Pharma Medicine Import 265
## 1161 2019.000 November Automobile Mobile Export 2079
## 1162 2024.000 July Electronics Medicine Import 2726
## 1163 2022.000 July Pharma Wheat Import 9883
## 1164 2020.000 December Agriculture Car Export 8112
## 1165 2022.000 July Agriculture Wheat Export 8349
## 1166 2021.000 March Textile Car Export 3689
## 1167 2020.000 November Electronics Cotton Export 2914
## 1168 2020.000 December Automobile Mobile Import 753
## 1169 2021.000 December Pharma Mobile Export 610
## 1170 2021.000 December Automobile Mobile Export 1948
## 1171 2022.000 March Agriculture Mobile Import 5128
## 1172 2022.000 May Electronics Cotton Import 8611
## 1173 2021.000 May Agriculture Cotton Export 5369
## 1174 2021.000 February Pharma Car Import 7717
## 1175 2020.000 February Automobile Car Import 1613
## 1176 2020.000 August Automobile Car Import 2121
## 1177 2024.000 October Agriculture Cotton Import 503
## 1178 2022.000 September Automobile Medicine Import 9303
## 1179 2021.000 September Electronics Cotton Export 5030
## 1180 2018.000 February Automobile Cotton Import 2673
## 1181 2023.000 November Automobile Cotton Export 4952
## 1182 2024.000 January Electronics Car Export 8987
## 1183 2020.000 September Pharma Car Export 6231
## 1184 2019.000 February Pharma Mobile Import 627
## 1185 2018.000 October Textile Mobile Export 1709
## 1186 2024.000 April Automobile Car Export 2456
## 1187 2024.000 October Textile Wheat Export 8111
## 1188 2024.000 July Pharma Car Export 5504
## 1189 2018.000 October Pharma Wheat Import 9619
## 1190 2022.000 July Textile Wheat Export 3095
## 1191 2022.000 December Electronics Medicine Export 3695
## 1192 2020.000 September Agriculture Medicine Import 6131
## 1193 2022.000 June Agriculture Medicine Export 4423
## 1194 2024.000 September Electronics Cotton Export 3796
## 1195 2024.000 October Pharma Wheat Export 5285
## 1196 2021.000 May Agriculture Medicine Export 5929
## 1197 2019.000 April Pharma Cotton Import 4080
## 1198 2020.000 December Pharma Mobile Export 7521
## 1199 2019.000 August Automobile Medicine Export 1334
## 1200 2021.000 September Agriculture Medicine Export 8363
## 1201 2024.000 February Agriculture Wheat Import 8984
## 1202 2018.000 February Agriculture Medicine Export 7736
## 1203 2019.000 December Automobile Cotton Import 3361
## 1204 2021.000 March Electronics Wheat Export 2854
## 1205 2021.000 January Agriculture Wheat Import 5526
## 1206 2023.000 October Electronics Wheat Import 7056
## 1207 2024.000 May Agriculture Medicine Import 5349
## 1208 2021.000 April Pharma Medicine Import 4926
## 1209 2021.000 April Textile Mobile Import 1144
## 1210 2024.000 July Electronics Car Import 4898
## 1211 2020.000 October Automobile Cotton Import 5708
## 1212 2023.000 December Pharma Medicine Import 626
## 1213 2024.000 March Textile Car Import 3871
## 1214 2018.000 October Agriculture Car Import 3837
## 1215 2019.000 March Agriculture Car Import 6492
## 1216 2024.000 December Electronics Cotton Export 4044
## 1217 2022.000 September Agriculture Medicine Export 3754
## 1218 2019.000 March Pharma Wheat Import 545
## 1219 2023.000 November Agriculture Medicine Import 8387
## 1220 2023.000 December Electronics Cotton Export 9024
## 1221 2021.000 August Agriculture Car Import 1194
## 1222 2020.000 July Textile Wheat Import 6766
## 1223 2022.000 March Agriculture Car Import 3534
## 1224 2019.000 June Agriculture Car Export 9765
## 1225 2024.000 October Automobile Wheat Import 2162
## 1226 2018.000 January Textile Car Import 3123
## 1227 2021.000 May Pharma Wheat Export 1901
## 1228 2020.000 October Pharma Car Import 9684
## 1229 2024.000 August Electronics Wheat Import 661
## 1230 2024.000 December Agriculture Medicine Export 4924
## 1231 2023.000 April Automobile Wheat Export 3788
## 1232 2021.000 November Automobile Cotton Import 6934
## 1233 2023.000 January Agriculture Car Import 2880
## 1234 2019.000 January Electronics Cotton Import 8484
## 1235 2020.000 August Textile Medicine Export 3299
## 1236 2024.000 December Pharma Mobile Import 4413
## 1237 2021.000 June Electronics Wheat Export 2652
## 1238 2024.000 May Automobile Cotton Export 1905
## 1239 2019.000 July Automobile Medicine Export 6694
## 1240 2020.000 December Agriculture Wheat Import 1577
## 1241 2023.000 April Textile Wheat Export 2926
## 1242 2023.000 September Automobile Cotton Import 5867
## 1243 2022.000 September Electronics Medicine Export 4971
## 1244 2022.000 June Pharma Car Export 3153
## 1245 2022.000 November Agriculture Cotton Import 1392
## 1246 2022.000 July Electronics Cotton Import 7362
## 1247 2020.000 March Electronics Cotton Import 626
## 1248 2019.000 January Electronics Cotton Export 1539
## 1249 2019.000 February Electronics Cotton Import 2339
## 1250 2022.000 July Pharma Wheat Export 8854
## 1251 2021.000 September Textile Medicine Export 2505
## 1252 2024.000 December Electronics Medicine Export 478
## 1253 2023.000 March Electronics Medicine Export 7357
## 1254 2021.000 January Electronics Medicine Export 9601
## 1255 2024.000 November Electronics Mobile Import 235
## 1256 2022.000 February Electronics Mobile Export 3076
## 1257 2023.000 May Automobile Mobile Import 652
## 1258 2019.000 August Automobile Car Import 1382
## 1259 2024.000 November Electronics Cotton Export 9076
## 1260 2023.000 April Textile Car Import 2524
## 1261 2024.000 December Agriculture Medicine Export 2454
## 1262 2021.000 April Electronics Wheat Import 5879
## 1263 2023.000 March Agriculture Medicine Import 2699
## 1264 2022.000 March Textile Wheat Export 1838
## 1265 2018.000 November Textile Mobile Export 801
## 1266 2022.000 March Automobile Car Import 6432
## 1267 2019.000 February Textile Car Import 2946
## 1268 2018.000 April Pharma Wheat Import 9863
## 1269 2024.000 May Agriculture Wheat Export 9028
## 1270 2024.000 February Agriculture Medicine Import 7819
## 1271 2023.000 May Pharma Medicine Export 6242
## 1272 2023.000 October Pharma Wheat Import 9052
## 1273 2023.000 June Textile Car Import 8254
## 1274 2018.000 March Pharma Cotton Export 6030
## 1275 2023.000 June Electronics Cotton Import 9674
## 1276 2022.000 January Textile Cotton Import 1647
## 1277 2018.000 January Automobile Medicine Import 2217
## 1278 2023.000 September Textile Car Export 6693
## 1279 2021.000 January Automobile Cotton Import 8032
## 1280 2020.000 October Pharma Wheat Import 905
## 1281 2020.000 January Agriculture Medicine Export 6857
## 1282 2022.000 December Automobile Medicine Export 6157
## 1283 2023.000 December Agriculture Car Export 5068
## 1284 2018.000 April Textile Medicine Export 377
## 1285 2024.000 January Pharma Cotton Export 9891
## 1286 2021.000 October Pharma Car Export 3555
## 1287 2018.000 June Pharma Medicine Import 8885
## 1288 2024.000 March Agriculture Car Import 9682
## 1289 2020.000 June Textile Cotton Import 6754
## 1290 2019.000 March Pharma Medicine Import 8588
## 1291 2021.000 July Automobile Mobile Import 6097
## 1292 2019.000 May Agriculture Wheat Export 1823
## 1293 2018.000 September Automobile Mobile Export 3321
## 1294 2020.000 August Automobile Wheat Import 7042
## 1295 2022.000 May Textile Cotton Export 8527
## 1296 2018.000 November Electronics Medicine Export 1598
## 1297 2023.000 November Electronics Wheat Export 8313
## 1298 2018.000 March Agriculture Medicine Import 8685
## 1299 2023.000 March Agriculture Medicine Export 5832
## 1300 2022.000 August Pharma Mobile Import 1821
## 1301 2019.000 December Automobile Mobile Import 6525
## 1302 2021.000 October Automobile Car Import 8840
## 1303 2019.000 April Textile Car Export 412
## 1304 2020.000 May Pharma Medicine Export 2391
## 1305 2019.000 December Pharma Car Export 7045
## 1306 2019.000 June Automobile Wheat Import 348
## 1307 2020.000 September Textile Mobile Import 2138
## 1308 2023.000 July Electronics Car Export 7836
## 1309 2019.000 July Pharma Cotton Export 4245
## 1310 2020.000 March Textile Cotton Import 3755
## 1311 2018.000 September Automobile Car Export 3524
## 1312 2020.000 September Pharma Mobile Export 5388
## 1313 2020.000 November Automobile Car Import 7902
## 1314 2024.000 September Automobile Wheat Import 213
## 1315 2023.000 April Pharma Wheat Export 6579
## 1316 2022.000 May Agriculture Medicine Export 449
## 1317 2024.000 July Automobile Cotton Export 2450
## 1318 2023.000 August Electronics Wheat Export 4294
## 1319 2022.000 May Pharma Wheat Import 6583
## 1320 2024.000 May Agriculture Wheat Import 2736
## 1321 2023.000 December Agriculture Medicine Import 8211
## 1322 2019.000 June Automobile Medicine Export 918
## 1323 2023.000 April Automobile Wheat Export 9007
## 1324 2021.000 March Agriculture Wheat Export 1720
## 1325 2023.000 March Automobile Cotton Import 3915
## 1326 2018.000 April Textile Car Export 5611
## 1327 2024.000 June Agriculture Medicine Export 8440
## 1328 2019.000 September Pharma Car Export 9148
## 1329 2024.000 December Pharma Medicine Import 1981
## 1330 2018.000 August Automobile Medicine Export 3270
## 1331 2024.000 January Automobile Medicine Export 9381
## 1332 2021.000 April Pharma Wheat Import 1826
## 1333 2018.000 September Agriculture Medicine Import 6402
## 1334 2020.000 October Agriculture Car Import 5634
## 1335 2021.000 April Textile Car Export 4165
## 1336 2024.000 May Textile Medicine Export 7131
## 1337 2020.000 September Agriculture Medicine Export 7825
## 1338 2021.000 March Pharma Cotton Export 9712
## 1339 2020.000 August Agriculture Mobile Export 3799
## 1340 2023.000 September Automobile Wheat Import 4997
## 1341 2021.000 December Automobile Car Export 8920
## 1342 2018.000 September Textile Cotton Import 3597
## 1343 2024.000 August Electronics Car Export 3707
## 1344 2021.000 July Agriculture Cotton Import 9582
## 1345 2019.000 February Textile Cotton Import 6143
## 1346 2019.000 October Electronics Wheat Import 3638
## 1347 2022.000 April Automobile Mobile Import 5512
## 1348 2020.000 November Automobile Medicine Export 4197
## 1349 2021.000 December Agriculture Medicine Import 3882
## 1350 2024.000 March Automobile Mobile Export 5894
## 1351 2024.000 February Automobile Car Import 2027
## 1352 2022.000 August Textile Medicine Import 6983
## 1353 2024.000 September Agriculture Mobile Import 8851
## 1354 2019.000 April Electronics Medicine Export 4878
## 1355 2020.000 October Electronics Wheat Import 9771
## 1356 2021.000 December Textile Cotton Export 1731
## 1357 2019.000 February Pharma Cotton Export 4159
## 1358 2019.000 May Textile Medicine Import 7807
## 1359 2019.000 July Pharma Cotton Import 451
## 1360 2018.000 February Textile Cotton Export 6140
## 1361 2019.000 August Pharma Wheat Import 9678
## 1362 2024.000 June Automobile Car Export 500
## 1363 2022.000 February Electronics Mobile Export 8083
## 1364 2023.000 May Pharma Car Import 6223
## 1365 2018.000 February Pharma Car Export 2783
## 1366 2023.000 January Automobile Wheat Import 4664
## 1367 2020.000 December Electronics Wheat Import 6435
## 1368 2019.000 June Textile Car Export 1529
## 1369 2020.000 December Electronics Wheat Import 5717
## 1370 2022.000 March Textile Wheat Import 211
## 1371 2018.000 November Automobile Medicine Export 8744
## 1372 2018.000 February Pharma Mobile Import 5106
## 1373 2022.000 October Agriculture Cotton Export 1790
## 1374 2023.000 April Electronics Cotton Import 6279
## 1375 2019.000 June Electronics Mobile Export 8158
## 1376 2020.000 July Electronics Car Export 496
## 1377 2022.000 April Agriculture Mobile Import 264
## 1378 2021.000 May Electronics Car Import 1505
## 1379 2024.000 July Automobile Medicine Export 4897
## 1380 2019.000 August Textile Wheat Import 4565
## 1381 2020.000 February Agriculture Mobile Import 6393
## 1382 2022.000 August Automobile Car Export 9733
## 1383 2022.000 October Pharma Cotton Export 9964
## 1384 2020.000 August Electronics Wheat Export 3549
## 1385 2018.000 August Electronics Wheat Export 3868
## 1386 2024.000 November Pharma Cotton Export 4868
## 1387 2020.000 October Pharma Cotton Export 1887
## 1388 2019.000 December Agriculture Car Import 4088
## 1389 2020.000 March Agriculture Mobile Export 3122
## 1390 2018.000 November Pharma Car Import 3703
## 1391 2020.000 March Automobile Wheat Import 4342
## 1392 2024.000 April Automobile Medicine Import 4626
## 1393 2023.000 October Pharma Cotton Import 3589
## 1394 2018.000 November Textile Car Import 5586
## 1395 2020.000 September Automobile Cotton Import 8330
## 1396 2024.000 May Automobile Wheat Import 9648
## 1397 2021.000 May Textile Cotton Import 3885
## 1398 2021.000 November Automobile Mobile Export 3190
## 1399 2019.000 December Textile Wheat Import 5084
## 1400 2021.000 January Pharma Car Import 1634
## 1401 2022.000 April Agriculture Cotton Export 8960
## 1402 2023.000 December Electronics Cotton Import 5738
## 1403 2019.000 October Agriculture Medicine Import 6538
## 1404 2023.000 April Textile Cotton Export 5189
## 1405 2022.000 April Automobile Mobile Import 2951
## 1406 2024.000 June Electronics Wheat Export 3519
## 1407 2020.000 July Electronics Cotton Import 4558
## 1408 2019.000 November Automobile Cotton Import 9845
## 1409 2019.000 May Electronics Mobile Import 9986
## 1410 2024.000 January Textile Mobile Export 3406
## 1411 2024.000 May Electronics Car Export 7261
## 1412 2022.000 June Electronics Cotton Export 5709
## 1413 2020.000 November Automobile Medicine Import 5008
## 1414 2024.000 November Textile Car Export 4066
## 1415 2022.000 August Textile Car Export 8516
## 1416 2021.000 December Pharma Mobile Export 250
## 1417 2019.000 October Electronics Mobile Import 3960
## 1418 2023.000 March Automobile Mobile Import 9389
## 1419 2020.000 February Pharma Cotton Export 7795
## 1420 2024.000 September Electronics Wheat Export 9959
## 1421 2023.000 July Electronics Mobile Import 2148
## 1422 2019.000 July Textile Mobile Export 257
## 1423 2021.000 April Pharma Medicine Import 1128
## 1424 2022.000 January Automobile Medicine Import 1375
## 1425 2024.000 September Automobile Wheat Export 4690
## 1426 2020.000 January Pharma Wheat Export 1446
## 1427 2023.000 July Automobile Car Import 3800
## 1428 2023.000 May Textile Wheat Import 5623
## 1429 2022.000 July Electronics Cotton Export 3385
## 1430 2020.000 May Automobile Mobile Export 5746
## 1431 2021.000 May Electronics Mobile Export 7499
## 1432 2021.000 November Electronics Wheat Export 5133
## 1433 2019.000 July Textile Mobile Import 1761
## 1434 2022.000 December Electronics Wheat Import 9176
## 1435 2020.000 June Pharma Medicine Export 1972
## 1436 2020.000 September Electronics Mobile Export 2074
## 1437 2023.000 April Pharma Wheat Export 2583
## 1438 2021.000 September Automobile Medicine Export 6138
## 1439 2022.000 June Textile Medicine Import 4826
## 1440 2024.000 September Electronics Medicine Import 1860
## 1441 2019.000 December Agriculture Mobile Import 5663
## 1442 2019.000 December Agriculture Car Export 9052
## 1443 2019.000 September Textile Mobile Import 4223
## 1444 2024.000 October Electronics Mobile Import 3188
## 1445 2022.000 January Agriculture Mobile Import 9796
## 1446 2019.000 June Pharma Wheat Import 3349
## 1447 2023.000 March Electronics Medicine Import 8456
## 1448 2019.000 March Agriculture Medicine Import 5467
## 1449 2023.000 January Textile Medicine Import 2706
## 1450 2022.000 May Automobile Cotton Import 1270
## 1451 2024.000 February Textile Mobile Export 4510
## 1452 2024.000 September Pharma Medicine Import 4975
## 1453 2020.000 August Textile Car Export 3256
## 1454 2023.000 January Electronics Cotton Export 8817
## 1455 2022.000 December Electronics Medicine Import 1783
## 1456 2020.000 September Pharma Mobile Export 5457
## 1457 2022.000 November Pharma Car Import 1058
## 1458 2020.000 September Pharma Mobile Export 847
## 1459 2021.000 October Electronics Wheat Import 2947
## 1460 2020.000 June Automobile Cotton Export 1412
## 1461 2019.000 May Electronics Mobile Export 4152
## 1462 2019.000 October Automobile Wheat Export 4510
## 1463 2019.000 July Agriculture Cotton Export 2336
## 1464 2023.000 August Electronics Wheat Export 1579
## 1465 2020.000 June Automobile Medicine Import 5300
## 1466 2024.000 September Textile Wheat Import 7590
## 1467 2024.000 August Textile Car Export 7663
## 1468 2022.000 March Textile Wheat Export 992
## 1469 2021.000 April Electronics Mobile Export 3409
## 1470 2021.000 January Textile Car Export 1582
## 1471 2023.000 October Automobile Cotton Import 5315
## 1472 2018.000 March Automobile Cotton Import 2969
## 1473 2024.000 May Automobile Car Export 2801
## 1474 2020.000 August Electronics Mobile Import 5935
## 1475 2018.000 December Pharma Mobile Import 4836
## 1476 2023.000 September Agriculture Car Import 5840
## 1477 2021.000 August Pharma Wheat Import 6410
## 1478 2020.000 September Agriculture Medicine Import 7078
## 1479 2023.000 December Automobile Medicine Export 8869
## 1480 2022.000 July Pharma Mobile Export 491
## 1481 2018.000 June Pharma Mobile Export 8239
## 1482 2023.000 August Textile Medicine Export 2305
## 1483 2020.000 March Agriculture Mobile Import 5868
## 1484 2024.000 June Agriculture Wheat Export 3902
## 1485 2018.000 May Pharma Medicine Export 8600
## 1486 2022.000 March Automobile Medicine Import 7070
## 1487 2019.000 July Automobile Car Import 6365
## 1488 2020.000 October Automobile Wheat Import 7081
## 1489 2024.000 January Textile Wheat Import 7686
## 1490 2024.000 February Pharma Mobile Import 3493
## 1491 2022.000 January Agriculture Mobile Import 1367
## 1492 2020.000 January Pharma Medicine Import 4386
## 1493 2024.000 August Automobile Medicine Import 2882
## 1494 2018.000 August Automobile Mobile Export 2277
## 1495 2023.000 March Textile Mobile Import 3316
## 1496 2019.000 February Agriculture Mobile Import 4248
## 1497 2024.000 April Electronics Car Import 8245
## 1498 2023.000 February Textile Car Import 6194
## 1499 2018.000 July Textile Car Import 7571
## 1500 2022.000 February Electronics Medicine Import 982
## 1501 2019.000 February Agriculture Mobile Export 9923
## 1502 2021.000 November Agriculture Cotton Import 5720
## 1503 2021.000 November Agriculture Wheat Export 2358
## 1504 2023.000 August Electronics Wheat Import 3508
## 1505 2019.000 November Pharma Wheat Export 6443
## 1506 2022.000 June Pharma Mobile Import 6315
## 1507 2023.000 September Automobile Medicine Export 519
## 1508 2023.000 September Pharma Car Import 2677
## 1509 2024.000 July Textile Wheat Export 251
## 1510 2020.000 February Textile Cotton Import 210
## 1511 2024.000 October Agriculture Wheat Export 5119
## 1512 2020.000 August Textile Cotton Export 9699
## 1513 2021.000 July Pharma Car Export 8987
## 1514 2019.000 October Automobile Car Export 2331
## 1515 2018.000 July Textile Car Export 7883
## 1516 2023.000 October Pharma Car Export 2626
## 1517 2019.000 November Electronics Mobile Export 6031
## 1518 2019.000 July Pharma Medicine Import 1089
## 1519 2021.000 August Pharma Cotton Export 7854
## 1520 2018.000 October Textile Car Export 2028
## 1521 2021.000 March Agriculture Mobile Export 4014
## 1522 2018.000 September Electronics Car Export 5292
## 1523 2021.000 May Textile Car Import 9899
## 1524 2022.000 February Pharma Cotton Import 9071
## 1525 2022.000 May Textile Medicine Import 8306
## 1526 2021.000 January Agriculture Cotton Export 2987
## 1527 2024.000 February Textile Mobile Import 1109
## 1528 2018.000 April Agriculture Cotton Import 9178
## 1529 2024.000 May Textile Car Export 674
## 1530 2022.000 June Electronics Medicine Export 171
## 1531 2020.000 September Electronics Mobile Export 1746
## 1532 2021.000 December Agriculture Cotton Export 4996
## 1533 2024.000 August Electronics Car Export 9348
## 1534 2022.000 August Agriculture Car Export 7535
## 1535 2021.000 March Automobile Medicine Import 4105
## 1536 2023.000 April Automobile Car Export 7988
## 1537 2022.000 November Electronics Mobile Import 6077
## 1538 2019.000 May Textile Mobile Import 5304
## 1539 2023.000 April Electronics Cotton Export 2728
## 1540 2020.000 January Electronics Car Export 3166
## 1541 2024.000 September Pharma Cotton Import 9445
## 1542 2024.000 May Textile Car Import 8447
## 1543 2018.000 September Electronics Wheat Import 3944
## 1544 2022.000 December Automobile Wheat Export 1526
## 1545 2019.000 October Textile Cotton Export 5602
## 1546 2020.000 December Electronics Cotton Export 1166
## 1547 2022.000 May Textile Car Import 5900
## 1548 2024.000 August Agriculture Mobile Import 524
## 1549 2020.000 May Textile Medicine Import 2959
## 1550 2020.000 December Electronics Cotton Export 9144
## 1551 2019.000 September Pharma Mobile Import 4636
## 1552 2018.000 September Textile Cotton Import 8553
## 1553 2023.000 September Textile Cotton Import 1125
## 1554 2023.000 September Agriculture Medicine Export 5298
## 1555 2022.000 January Agriculture Medicine Import 9370
## 1556 2024.000 June Textile Wheat Export 9295
## 1557 2018.000 May Automobile Cotton Import 7431
## 1558 2020.000 March Electronics Medicine Import 4237
## 1559 2018.000 January Agriculture Cotton Import 8711
## 1560 2023.000 March Automobile Wheat Import 3560
## 1561 2018.000 December Electronics Mobile Import 6956
## 1562 2021.000 January Textile Car Import 1331
## 1563 2018.000 December Pharma Wheat Import 8428
## 1564 2018.000 December Pharma Wheat Export 3250
## 1565 2022.000 April Pharma Wheat Export 3668
## 1566 2024.000 January Textile Wheat Import 5013
## 1567 2018.000 November Electronics Car Export 2849
## 1568 2023.000 May Automobile Car Export 2966
## 1569 2021.000 June Agriculture Cotton Import 7544
## 1570 2021.000 November Pharma Medicine Export 2666
## 1571 2021.000 January Pharma Car Import 3725
## 1572 2021.000 November Pharma Car Import 2621
## 1573 2020.000 December Automobile Medicine Import 2445
## 1574 2018.000 July Agriculture Mobile Export 5551
## 1575 2021.000 July Agriculture Mobile Import 3648
## 1576 2021.000 September Electronics Car Export 9655
## 1577 2023.000 October Automobile Car Import 5911
## 1578 2019.000 October Agriculture Wheat Export 2043
## 1579 2024.000 August Textile Mobile Export 7541
## 1580 2018.000 October Agriculture Cotton Export 8623
## 1581 2019.000 May Textile Car Import 1115
## 1582 2018.000 December Agriculture Cotton Export 4818
## 1583 2021.000 May Agriculture Cotton Import 554
## 1584 2024.000 March Automobile Medicine Import 8517
## 1585 2023.000 December Electronics Car Export 1294
## 1586 2022.000 December Electronics Wheat Export 9862
## 1587 2019.000 September Pharma Medicine Import 4507
## 1588 2021.000 October Pharma Cotton Import 6506
## 1589 2021.000 October Textile Wheat Import 4021
## 1590 2022.000 December Automobile Cotton Import 9295
## 1591 2024.000 April Textile Medicine Import 2038
## 1592 2021.000 December Textile Car Import 9358
## 1593 2022.000 July Electronics Medicine Import 4438
## 1594 2020.000 August Automobile Medicine Import 1507
## 1595 2024.000 October Automobile Wheat Export 6750
## 1596 2019.000 December Pharma Wheat Export 5253
## 1597 2019.000 September Textile Cotton Export 3575
## 1598 2018.000 August Pharma Wheat Import 9400
## 1599 2024.000 October Textile Medicine Import 9399
## 1600 2020.000 May Textile Wheat Export 3135
## 1601 2021.000 October Textile Mobile Export 5717
## 1602 2024.000 October Pharma Mobile Export 8190
## 1603 2022.000 February Pharma Wheat Import 5748
## 1604 2018.000 February Automobile Medicine Export 5619
## 1605 2019.000 September Electronics Wheat Export 5891
## 1606 2019.000 May Electronics Mobile Import 4852
## 1607 2019.000 February Electronics Cotton Export 5574
## 1608 2018.000 December Electronics Medicine Import 5229
## 1609 2019.000 June Automobile Medicine Import 555
## 1610 2021.000 February Automobile Mobile Export 1335
## 1611 2024.000 January Textile Wheat Import 4477
## 1612 2020.000 July Agriculture Medicine Import 1528
## 1613 2019.000 December Automobile Mobile Import 9580
## 1614 2023.000 August Pharma Medicine Export 7608
## 1615 2018.000 December Textile Medicine Export 3555
## 1616 2018.000 September Pharma Mobile Import 7245
## 1617 2021.000 April Agriculture Car Export 7335
## 1618 2024.000 April Agriculture Wheat Import 8020
## 1619 2019.000 November Electronics Wheat Import 4785
## 1620 2019.000 February Pharma Medicine Import 4493
## 1621 2023.000 February Automobile Car Export 4119
## 1622 2023.000 May Electronics Mobile Export 5829
## 1623 2020.000 October Agriculture Wheat Export 531
## 1624 2018.000 January Automobile Medicine Import 5131
## 1625 2019.000 May Textile Wheat Export 5300
## 1626 2019.000 May Electronics Car Import 7937
## 1627 2021.000 January Automobile Wheat Export 631
## 1628 2021.000 August Pharma Mobile Import 7656
## 1629 2020.000 January Pharma Medicine Export 2511
## 1630 2021.000 May Automobile Mobile Import 7598
## 1631 2018.000 November Electronics Medicine Export 606
## 1632 2021.000 July Textile Cotton Import 4972
## 1633 2019.000 April Automobile Car Import 9836
## 1634 2019.000 March Textile Cotton Export 8811
## 1635 2018.000 December Textile Wheat Import 5457
## 1636 2023.000 December Agriculture Car Export 121
## 1637 2020.000 February Agriculture Mobile Export 897
## 1638 2020.000 December Agriculture Wheat Import 4268
## 1639 2023.000 March Textile Medicine Export 314
## 1640 2024.000 February Electronics Cotton Import 9552
## 1641 2018.000 April Electronics Wheat Import 4795
## 1642 2019.000 August Electronics Car Import 5141
## 1643 2022.000 July Automobile Medicine Import 3430
## 1644 2019.000 August Pharma Mobile Import 399
## 1645 2021.000 October Pharma Cotton Import 7219
## 1646 2024.000 October Agriculture Medicine Export 5414
## 1647 2018.000 June Electronics Car Import 9175
## 1648 2022.000 October Agriculture Medicine Export 5137
## 1649 2020.000 February Pharma Cotton Import 129
## 1650 2018.000 February Textile Mobile Import 9604
## 1651 2018.000 July Pharma Car Import 1255
## 1652 2021.000 January Electronics Medicine Import 8756
## 1653 2022.000 August Agriculture Wheat Export 3047
## 1654 2021.000 April Textile Wheat Export 8400
## 1655 2019.000 July Automobile Car Export 8361
## 1656 2021.000 August Agriculture Car Export 3001
## 1657 2024.000 November Agriculture Car Import 1962
## 1658 2021.000 July Agriculture Car Import 6172
## 1659 2022.000 October Textile Wheat Import 9144
## 1660 2023.000 May Agriculture Cotton Import 1855
## 1661 2019.000 February Agriculture Wheat Export 1046
## 1662 2019.000 April Textile Cotton Export 4048
## 1663 2022.000 October Electronics Medicine Import 3247
## 1664 2023.000 April Automobile Cotton Export 9545
## 1665 2021.000 March Automobile Car Export 7029
## 1666 2021.000 November Automobile Cotton Export 197
## 1667 2022.000 March Agriculture Wheat Export 4166
## 1668 2019.000 June Electronics Wheat Export 7850
## 1669 2022.000 August Agriculture Car Export 197
## 1670 2021.000 July Agriculture Medicine Export 9188
## 1671 2023.000 March Textile Mobile Export 3344
## 1672 2024.000 June Pharma Wheat Import 8306
## 1673 2023.000 February Automobile Car Import 4171
## 1674 2024.000 November Agriculture Medicine Export 8589
## 1675 2018.000 April Electronics Wheat Export 1329
## 1676 2021.000 March Agriculture Wheat Export 5923
## 1677 2022.000 July Textile Car Import 5119
## 1678 2021.000 November Pharma Cotton Import 2997
## 1679 2023.000 January Agriculture Cotton Export 9926
## 1680 2019.000 August Agriculture Mobile Export 432
## 1681 2024.000 January Pharma Medicine Import 4372
## 1682 2022.000 August Textile Car Export 5645
## 1683 2020.000 September Textile Mobile Import 488
## 1684 2023.000 December Pharma Medicine Export 9347
## 1685 2019.000 March Textile Wheat Import 9709
## 1686 2022.000 January Electronics Cotton Import 3608
## 1687 2021.000 September Agriculture Cotton Import 7555
## 1688 2021.000 August Agriculture Cotton Export 9194
## 1689 2018.000 November Agriculture Wheat Import 1058
## 1690 2020.000 June Pharma Mobile Export 670
## 1691 2024.000 November Agriculture Car Import 2002
## 1692 2023.000 March Agriculture Mobile Import 2670
## 1693 2021.000 July Automobile Car Export 3080
## 1694 2020.000 February Pharma Car Import 4113
## 1695 2018.000 July Pharma Car Import 2051
## 1696 2018.000 March Textile Wheat Export 2728
## 1697 2022.000 October Textile Medicine Import 2271
## 1698 2020.000 July Agriculture Medicine Export 3421
## 1699 2019.000 November Pharma Wheat Export 1496
## 1700 2024.000 September Agriculture Wheat Export 9823
## 1701 2024.000 September Pharma Car Export 3179
## 1702 2023.000 March Textile Mobile Import 7590
## 1703 2019.000 July Agriculture Medicine Import 5927
## 1704 2022.000 August Pharma Wheat Import 2505
## 1705 2022.000 August Textile Wheat Export 6005
## 1706 2021.000 March Textile Mobile Export 7425
## 1707 2020.000 July Electronics Cotton Export 8288
## 1708 2024.000 February Automobile Wheat Export 9487
## 1709 2019.000 December Pharma Mobile Import 2083
## 1710 2024.000 June Pharma Medicine Import 5961
## 1711 2021.000 November Automobile Cotton Export 7846
## 1712 2024.000 December Automobile Mobile Export 9885
## 1713 2020.000 May Automobile Car Import 2594
## 1714 2019.000 July Pharma Mobile Export 2655
## 1715 2024.000 December Pharma Car Import 8983
## 1716 2023.000 March Textile Cotton Import 650
## 1717 2018.000 June Electronics Car Export 5636
## 1718 2023.000 May Agriculture Car Export 5423
## 1719 2020.000 February Electronics Mobile Import 4337
## 1720 2020.000 September Automobile Wheat Import 3646
## 1721 2020.000 October Agriculture Car Import 4115
## 1722 2023.000 January Automobile Medicine Export 7762
## 1723 2022.000 January Textile Cotton Import 1562
## 1724 2021.000 April Electronics Wheat Import 1026
## 1725 2022.000 August Agriculture Cotton Import 8815
## 1726 2018.000 February Textile Medicine Import 2787
## 1727 2018.000 January Pharma Car Import 863
## 1728 2018.000 December Electronics Mobile Import 2717
## 1729 2024.000 February Electronics Medicine Import 8644
## 1730 2024.000 September Electronics Cotton Export 1951
## 1731 2024.000 October Automobile Medicine Import 8948
## 1732 2024.000 January Agriculture Car Export 5181
## 1733 2020.000 December Agriculture Wheat Import 4094
## 1734 2018.000 January Electronics Mobile Export 9595
## 1735 2024.000 December Electronics Medicine Export 9006
## 1736 2022.000 June Electronics Wheat Export 4897
## 1737 2022.000 March Pharma Wheat Export 9552
## 1738 2020.000 September Automobile Medicine Export 4997
## 1739 2024.000 September Electronics Car Export 5747
## 1740 2022.000 June Textile Mobile Export 2800
## 1741 2023.000 August Pharma Medicine Export 3530
## 1742 2018.000 November Electronics Car Export 7876
## 1743 2024.000 September Electronics Car Export 882
## 1744 2023.000 December Electronics Wheat Import 304
## 1745 2018.000 July Pharma Wheat Import 5675
## 1746 2019.000 October Pharma Mobile Import 1259
## 1747 2020.000 October Automobile Mobile Export 652
## 1748 2020.000 August Agriculture Car Import 1900
## 1749 2019.000 May Pharma Cotton Export 3549
## 1750 2018.000 February Pharma Car Import 4888
## 1751 2018.000 June Automobile Wheat Export 8464
## 1752 2023.000 August Agriculture Mobile Export 4203
## 1753 2023.000 November Agriculture Car Import 3320
## 1754 2018.000 November Electronics Wheat Import 7737
## 1755 2019.000 May Textile Medicine Import 9481
## 1756 2020.000 January Agriculture Cotton Export 989
## 1757 2022.000 June Agriculture Medicine Export 4062
## 1758 2018.000 January Agriculture Mobile Import 9350
## 1759 2021.000 February Electronics Wheat Import 3032
## 1760 2019.000 July Pharma Cotton Import 9651
## 1761 2022.000 September Agriculture Wheat Export 3469
## 1762 2018.000 November Agriculture Wheat Import 726
## 1763 2023.000 December Electronics Medicine Export 6000
## 1764 2024.000 January Textile Wheat Export 1072
## 1765 2024.000 January Automobile Wheat Import 7695
## 1766 2020.000 August Pharma Wheat Import 3515
## 1767 2024.000 February Pharma Mobile Import 518
## 1768 2020.000 July Electronics Mobile Export 4294
## 1769 2018.000 January Automobile Medicine Import 622
## 1770 2021.000 April Pharma Wheat Import 9427
## 1771 2021.000 September Textile Car Import 4601
## 1772 2021.000 November Automobile Car Import 8318
## 1773 2021.000 March Automobile Cotton Export 5122
## 1774 2021.000 December Pharma Medicine Export 817
## 1775 2022.000 February Agriculture Medicine Export 1490
## 1776 2024.000 December Pharma Medicine Export 9469
## 1777 2021.000 March Textile Medicine Export 9550
## 1778 2021.000 January Agriculture Mobile Export 9222
## 1779 2023.000 November Textile Mobile Export 2449
## 1780 2023.000 June Textile Medicine Import 3107
## 1781 2020.000 February Electronics Car Export 2156
## 1782 2019.000 November Electronics Wheat Import 6768
## 1783 2018.000 July Electronics Wheat Export 9588
## 1784 2019.000 July Automobile Mobile Import 1482
## 1785 2020.000 April Automobile Cotton Export 4890
## 1786 2022.000 September Pharma Mobile Export 1744
## 1787 2023.000 August Electronics Wheat Export 546
## 1788 2022.000 May Automobile Cotton Import 6832
## 1789 2024.000 November Textile Mobile Import 9254
## 1790 2022.000 July Automobile Mobile Import 3564
## 1791 2021.000 April Automobile Mobile Import 6424
## 1792 2021.000 July Automobile Mobile Export 5718
## 1793 2022.000 November Electronics Car Export 7253
## 1794 2020.000 May Automobile Cotton Export 843
## 1795 2019.000 October Pharma Mobile Export 4620
## 1796 2024.000 March Pharma Wheat Export 408
## 1797 2022.000 January Pharma Cotton Export 8222
## 1798 2019.000 November Textile Car Export 3833
## 1799 2021.000 October Automobile Wheat Export 7767
## 1800 2020.000 November Textile Car Import 2717
## 1801 2024.000 November Automobile Wheat Export 4254
## 1802 2018.000 November Textile Car Export 2607
## 1803 2023.000 October Agriculture Medicine Import 5841
## 1804 2019.000 August Pharma Medicine Import 6091
## 1805 2019.000 May Automobile Mobile Import 4112
## 1806 2021.000 March Agriculture Car Import 4517
## 1807 2020.000 January Agriculture Medicine Import 6017
## 1808 2019.000 June Automobile Car Import 5097
## 1809 2023.000 June Electronics Medicine Import 3669
## 1810 2024.000 October Textile Car Import 8300
## 1811 2023.000 October Agriculture Mobile Export 9100
## 1812 2018.000 April Textile Cotton Export 5573
## 1813 2020.000 November Textile Mobile Export 7684
## 1814 2023.000 July Agriculture Car Import 2266
## 1815 2019.000 November Agriculture Cotton Import 1089
## 1816 2020.000 January Agriculture Mobile Import 8306
## 1817 2020.000 October Pharma Cotton Export 128
## 1818 2022.000 July Electronics Wheat Import 3915
## 1819 2023.000 October Automobile Cotton Import 7559
## 1820 2023.000 June Electronics Wheat Import 5007
## 1821 2023.000 February Automobile Mobile Import 5525
## 1822 2019.000 October Electronics Car Export 8715
## 1823 2019.000 November Textile Cotton Import 2674
## 1824 2024.000 May Automobile Mobile Export 5442
## 1825 2018.000 January Electronics Car Import 5836
## 1826 2021.000 September Agriculture Mobile Import 2205
## 1827 2023.000 December Textile Wheat Export 8350
## 1828 2022.000 August Textile Wheat Export 5397
## 1829 2018.000 May Agriculture Wheat Import 2915
## 1830 2019.000 April Pharma Mobile Import 2966
## 1831 2019.000 July Textile Cotton Import 8200
## 1832 2024.000 September Electronics Car Export 8751
## 1833 2022.000 June Agriculture Mobile Export 1599
## 1834 2023.000 November Electronics Medicine Export 2183
## 1835 2022.000 August Textile Mobile Import 877
## 1836 2020.000 September Agriculture Medicine Export 3103
## 1837 2023.000 May Pharma Wheat Import 9657
## 1838 2019.000 February Pharma Mobile Import 6796
## 1839 2018.000 October Agriculture Mobile Import 2134
## 1840 2019.000 January Agriculture Medicine Import 6741
## 1841 2018.000 January Electronics Car Import 6283
## 1842 2020.000 January Agriculture Medicine Import 6635
## 1843 2020.000 May Textile Car Import 6490
## 1844 2018.000 June Pharma Mobile Import 2091
## 1845 2023.000 April Agriculture Mobile Export 1363
## 1846 2021.000 March Agriculture Cotton Import 3972
## 1847 2021.000 December Agriculture Medicine Import 2254
## 1848 2023.000 November Agriculture Mobile Import 1913
## 1849 2018.000 June Pharma Mobile Import 1129
## 1850 2020.000 September Textile Mobile Import 9430
## 1851 2022.000 October Agriculture Car Import 3289
## 1852 2022.000 April Textile Cotton Export 8003
## 1853 2019.000 May Pharma Wheat Import 3538
## 1854 2020.000 September Agriculture Car Import 8539
## 1855 2023.000 March Pharma Cotton Export 7933
## 1856 2018.000 February Pharma Cotton Import 8220
## 1857 2018.000 April Automobile Cotton Import 6892
## 1858 2020.000 November Agriculture Mobile Import 4037
## 1859 2021.000 August Agriculture Wheat Import 6286
## 1860 2022.000 March Pharma Car Import 9601
## 1861 2022.000 June Agriculture Car Import 4169
## 1862 2023.000 October Automobile Wheat Import 7218
## 1863 2020.000 December Electronics Car Import 6719
## 1864 2024.000 January Agriculture Medicine Export 2727
## 1865 2022.000 May Electronics Wheat Import 2169
## 1866 2023.000 November Pharma Car Export 5310
## 1867 2018.000 November Pharma Wheat Import 2212
## 1868 2024.000 January Automobile Cotton Export 7396
## 1869 2020.000 October Agriculture Car Export 8310
## 1870 2018.000 November Textile Mobile Import 1458
## 1871 2020.000 September Electronics Mobile Import 6954
## 1872 2022.000 April Electronics Mobile Export 1052
## 1873 2022.000 September Agriculture Car Import 8258
## 1874 2023.000 June Automobile Mobile Export 3019
## 1875 2022.000 August Automobile Cotton Export 4246
## 1876 2021.000 September Automobile Medicine Import 9131
## 1877 2023.000 December Textile Wheat Import 2636
## 1878 2021.000 March Agriculture Car Import 3782
## 1879 2018.000 March Electronics Wheat Export 996
## 1880 2019.000 February Electronics Car Import 2980
## 1881 2020.000 September Pharma Medicine Export 2935
## 1882 2021.000 July Agriculture Mobile Import 9767
## 1883 2022.000 July Textile Wheat Export 4540
## 1884 2018.000 August Agriculture Mobile Import 5221
## 1885 2022.000 March Automobile Car Import 399
## 1886 2024.000 March Textile Medicine Export 6416
## 1887 2019.000 March Pharma Cotton Import 6244
## 1888 2024.000 September Textile Car Export 6836
## 1889 2019.000 October Agriculture Cotton Import 3224
## 1890 2018.000 March Electronics Mobile Import 5016
## 1891 2023.000 August Electronics Wheat Import 7594
## 1892 2022.000 January Pharma Cotton Import 9987
## 1893 2022.000 June Pharma Car Import 5772
## 1894 2020.000 December Pharma Mobile Import 3383
## 1895 2023.000 June Automobile Cotton Export 4383
## 1896 2021.000 May Agriculture Mobile Export 7273
## 1897 2023.000 May Textile Car Export 5820
## 1898 2024.000 October Pharma Cotton Export 1715
## 1899 2024.000 October Automobile Mobile Import 9546
## 1900 2023.000 January Pharma Medicine Import 7750
## 1901 2022.000 August Agriculture Medicine Import 7565
## 1902 2022.000 July Automobile Car Export 6878
## 1903 2023.000 November Electronics Wheat Export 3026
## 1904 2019.000 December Pharma Mobile Import 8945
## 1905 2021.000 February Automobile Wheat Export 6672
## 1906 2019.000 February Textile Car Import 4060
## 1907 2018.000 September Pharma Wheat Import 6558
## 1908 2023.000 May Pharma Cotton Import 7778
## 1909 2019.000 September Textile Wheat Export 3397
## 1910 2018.000 August Electronics Wheat Export 3446
## 1911 2022.000 June Automobile Medicine Import 4675
## 1912 2024.000 April Textile Mobile Export 974
## 1913 2021.000 September Automobile Medicine Export 9750
## 1914 2024.000 January Agriculture Mobile Import 1207
## 1915 2024.000 May Electronics Cotton Import 8394
## 1916 2018.000 February Agriculture Mobile Import 8550
## 1917 2023.000 July Agriculture Cotton Import 2042
## 1918 2021.000 July Agriculture Cotton Import 1736
## 1919 2021.000 July Textile Wheat Export 9604
## 1920 2024.000 September Agriculture Wheat Export 4736
## 1921 2019.000 November Agriculture Wheat Export 8163
## 1922 2023.000 February Electronics Mobile Import 1812
## 1923 2020.000 January Agriculture Mobile Export 7167
## 1924 2018.000 September Automobile Mobile Export 7035
## 1925 2024.000 March Textile Mobile Import 720
## 1926 2018.000 October Agriculture Cotton Export 304
## 1927 2019.000 April Automobile Medicine Export 5435
## 1928 2022.000 January Electronics Mobile Import 8579
## 1929 2023.000 December Electronics Medicine Import 244
## 1930 2021.000 October Pharma Cotton Import 2372
## 1931 2023.000 July Agriculture Car Export 6297
## 1932 2020.000 July Agriculture Cotton Export 8380
## 1933 2022.000 May Pharma Wheat Import 6850
## 1934 2019.000 September Automobile Cotton Import 5361
## 1935 2024.000 December Automobile Wheat Import 8847
## 1936 2024.000 September Pharma Cotton Import 5655
## 1937 2020.000 November Electronics Cotton Export 8818
## 1938 2018.000 October Automobile Cotton Import 5300
## 1939 2021.000 December Pharma Wheat Import 9021
## 1940 2022.000 April Textile Mobile Import 6976
## 1941 2018.000 January Textile Car Import 6623
## 1942 2023.000 December Electronics Mobile Import 6890
## 1943 2024.000 August Agriculture Medicine Import 5080
## 1944 2019.000 October Electronics Cotton Export 704
## 1945 2021.000 December Agriculture Medicine Export 4650
## 1946 2020.000 September Electronics Mobile Import 4506
## 1947 2020.000 September Automobile Car Export 620
## 1948 2018.000 August Textile Wheat Import 2200
## 1949 2019.000 December Pharma Wheat Export 934
## 1950 2024.000 November Electronics Mobile Export 7808
## 1951 2020.000 May Electronics Wheat Export 810
## 1952 2018.000 March Electronics Wheat Import 2329
## 1953 2023.000 September Agriculture Cotton Import 9960
## 1954 2020.000 April Electronics Mobile Import 8873
## 1955 2021.000 February Electronics Wheat Export 1857
## 1956 2024.000 June Pharma Wheat Import 4469
## 1957 2022.000 November Agriculture Mobile Export 7570
## 1958 2022.000 July Agriculture Wheat Export 9959
## 1959 2022.000 September Textile Medicine Import 5178
## 1960 2023.000 November Electronics Mobile Import 1713
## 1961 2018.000 November Automobile Wheat Export 9432
## 1962 2022.000 February Textile Wheat Export 2342
## 1963 2023.000 January Agriculture Car Import 9426
## 1964 2018.000 June Electronics Medicine Import 713
## 1965 2019.000 January Textile Medicine Export 5830
## 1966 2020.000 November Electronics Car Import 1844
## 1967 2020.000 January Textile Cotton Export 1348
## 1968 2022.000 March Textile Medicine Export 3290
## 1969 2021.000 February Agriculture Medicine Import 8838
## 1970 2018.000 December Textile Mobile Import 555
## 1971 2018.000 April Automobile Medicine Export 3828
## 1972 2018.000 October Automobile Wheat Import 3508
## 1973 2020.000 March Electronics Cotton Export 2002
## 1974 2019.000 July Agriculture Medicine Import 2403
## 1975 2024.000 April Agriculture Medicine Export 7834
## 1976 2021.000 October Agriculture Car Import 9819
## 1977 2022.000 December Automobile Car Export 2924
## 1978 2021.000 April Agriculture Mobile Export 4770
## 1979 2024.000 December Pharma Medicine Import 1416
## 1980 2019.000 May Pharma Mobile Import 3772
## 1981 2024.000 October Electronics Car Import 3373
## 1982 2022.000 December Textile Medicine Import 2317
## 1983 2023.000 September Pharma Cotton Import 9989
## 1984 2024.000 October Agriculture Medicine Import 8687
## 1985 2024.000 April Agriculture Mobile Export 4900
## 1986 2022.000 October Textile Mobile Import 9607
## 1987 2018.000 November Automobile Cotton Export 996
## 1988 2023.000 June Pharma Car Import 388
## 1989 2018.000 October Pharma Medicine Export 4590
## 1990 2022.000 July Electronics Cotton Import 9695
## 1991 2023.000 September Agriculture Cotton Export 9752
## 1992 2021.000 May Agriculture Cotton Import 9811
## 1993 2022.000 December Textile Medicine Export 2073
## 1994 2018.000 December Electronics Wheat Import 4100
## 1995 2024.000 May Pharma Wheat Import 2010
## 1996 2022.000 December Agriculture Wheat Import 4174
## 1997 2021.000 March Electronics Mobile Import 3915
## 1998 2023.000 June Agriculture Medicine Import 1402
## 1999 2021.000 September Pharma Mobile Import 8502
## 2000 2020.000 March Automobile Car Import 2896
## 2001 2019.000 May Pharma Medicine Export 3786
## 2002 2018.000 March Automobile Cotton Import 7618
## 2003 2024.000 September Pharma Wheat Import 2142
## 2004 2018.000 December Pharma Mobile Export 3395
## 2005 2019.000 December Automobile Medicine Import 6950
## 2006 2021.000 March Pharma Medicine Export 1449
## 2007 2024.000 October Pharma Mobile Import 9904
## 2008 2022.000 February Agriculture Wheat Export 6148
## 2009 2023.000 November Pharma Cotton Export 666
## 2010 2021.000 August Electronics Mobile Import 5923
## 2011 2020.000 May Agriculture Mobile Export 947
## 2012 2021.000 May Textile Wheat Export 146
## 2013 2023.000 July Electronics Medicine Export 1021
## 2014 2024.000 November Electronics Wheat Import 242
## 2015 2020.000 December Automobile Wheat Import 6274
## 2016 2023.000 July Textile Cotton Export 8917
## 2017 2018.000 September Pharma Wheat Export 8377
## 2018 2020.000 December Agriculture Medicine Import 7085
## 2019 2018.000 October Electronics Medicine Import 6805
## 2020 2021.000 November Agriculture Wheat Import 7344
## 2021 2020.000 November Textile Cotton Import 3563
## 2022 2024.000 October Agriculture Medicine Import 2388
## 2023 2023.000 October Pharma Car Export 5476
## 2024 2021.000 June Agriculture Wheat Export 8817
## 2025 2022.000 July Pharma Medicine Import 1474
## 2026 2019.000 February Agriculture Mobile Export 5585
## 2027 2022.000 February Pharma Wheat Export 2921
## 2028 2021.000 February Automobile Medicine Export 1842
## 2029 2020.000 October Agriculture Cotton Import 2481
## 2030 2020.000 April Agriculture Medicine Export 5574
## 2031 2020.000 January Pharma Cotton Import 6174
## 2032 2019.000 April Pharma Cotton Import 5556
## 2033 2024.000 March Electronics Cotton Export 2812
## 2034 2024.000 February Automobile Cotton Export 2085
## 2035 2018.000 October Pharma Medicine Export 2263
## 2036 2018.000 July Automobile Medicine Export 333
## 2037 2024.000 February Textile Cotton Export 3274
## 2038 2024.000 February Agriculture Medicine Import 3620
## 2039 2019.000 July Textile Medicine Import 1774
## 2040 2020.000 January Electronics Car Import 111
## 2041 2019.000 March Electronics Wheat Export 6906
## 2042 2024.000 December Pharma Cotton Export 9557
## 2043 2020.000 January Textile Cotton Import 328
## 2044 2022.000 August Agriculture Medicine Export 1650
## 2045 2023.000 August Agriculture Medicine Export 785
## 2046 2019.000 October Electronics Medicine Import 3988
## 2047 2022.000 June Automobile Medicine Import 6863
## 2048 2023.000 April Automobile Car Export 2391
## 2049 2021.000 January Agriculture Wheat Export 6844
## 2050 2023.000 November Agriculture Wheat Import 387
## 2051 2024.000 March Automobile Car Export 1198
## 2052 2023.000 December Textile Medicine Import 6952
## 2053 2023.000 March Agriculture Car Import 3475
## 2054 2024.000 February Pharma Wheat Export 9684
## 2055 2024.000 May Automobile Mobile Import 5077
## 2056 2024.000 May Automobile Car Export 1738
## 2057 2023.000 May Pharma Medicine Export 4999
## 2058 2022.000 March Pharma Cotton Export 3021
## 2059 2018.000 February Pharma Cotton Import 7955
## 2060 2021.000 May Automobile Cotton Import 4803
## 2061 2019.000 April Textile Medicine Export 6139
## 2062 2018.000 June Pharma Medicine Export 8243
## 2063 2020.000 March Electronics Cotton Export 982
## 2064 2021.000 May Electronics Medicine Import 9102
## 2065 2019.000 January Electronics Car Export 1124
## 2066 2018.000 June Automobile Wheat Import 9095
## 2067 2024.000 July Automobile Mobile Export 8086
## 2068 2020.000 June Pharma Car Import 7583
## 2069 2020.000 July Agriculture Medicine Import 748
## 2070 2022.000 May Electronics Wheat Import 6189
## 2071 2021.000 February Pharma Medicine Import 2370
## 2072 2020.000 December Electronics Medicine Export 6108
## 2073 2021.000 March Agriculture Wheat Export 6798
## 2074 2024.000 May Electronics Medicine Export 8320
## 2075 2018.000 May Electronics Wheat Import 8737
## 2076 2021.000 March Agriculture Cotton Import 4319
## 2077 2020.000 August Agriculture Mobile Import 2685
## 2078 2018.000 May Agriculture Cotton Export 3246
## 2079 2022.000 December Pharma Wheat Import 4746
## 2080 2019.000 October Automobile Cotton Export 2525
## 2081 2020.000 July Pharma Medicine Export 5206
## 2082 2019.000 June Pharma Wheat Export 9674
## 2083 2019.000 December Electronics Cotton Export 3273
## 2084 2018.000 October Agriculture Mobile Export 2351
## 2085 2018.000 January Pharma Mobile Export 7661
## 2086 2019.000 May Electronics Medicine Export 6229
## 2087 2021.000 June Automobile Mobile Import 5926
## 2088 2023.000 February Pharma Medicine Import 7080
## 2089 2023.000 July Pharma Wheat Import 3441
## 2090 2019.000 May Electronics Medicine Export 5235
## 2091 2024.000 January Agriculture Wheat Export 9411
## 2092 2022.000 January Agriculture Mobile Import 3270
## 2093 2018.000 March Automobile Cotton Export 802
## 2094 2018.000 July Agriculture Mobile Export 2195
## 2095 2019.000 September Pharma Wheat Import 8591
## 2096 2020.000 March Pharma Medicine Export 8262
## 2097 2021.000 December Electronics Cotton Import 8805
## 2098 2024.000 June Pharma Medicine Export 1656
## 2099 2020.000 September Pharma Wheat Export 2265
## 2100 2020.000 June Pharma Wheat Import 8376
## 2101 2020.000 November Automobile Mobile Export 4789
## 2102 2022.000 September Automobile Car Export 8702
## 2103 2018.000 April Pharma Mobile Export 7672
## 2104 2021.000 April Automobile Car Export 897
## 2105 2018.000 November Pharma Car Import 9968
## 2106 2020.000 February Agriculture Wheat Export 5435
## 2107 2018.000 January Pharma Cotton Import 5599
## 2108 2022.000 January Pharma Cotton Export 5679
## 2109 2024.000 August Automobile Car Import 7428
## 2110 2022.000 December Agriculture Wheat Import 6623
## 2111 2022.000 December Textile Medicine Import 2680
## 2112 2019.000 May Automobile Medicine Export 6129
## 2113 2019.000 May Textile Cotton Import 2813
## 2114 2021.000 February Agriculture Medicine Import 7038
## 2115 2023.000 February Agriculture Wheat Import 1302
## 2116 2023.000 February Agriculture Wheat Import 5824
## 2117 2019.000 July Electronics Car Import 304
## 2118 2024.000 April Pharma Mobile Export 2829
## 2119 2018.000 May Pharma Wheat Import 9428
## 2120 2023.000 August Agriculture Wheat Import 1939
## 2121 2024.000 April Automobile Cotton Import 1990
## 2122 2020.000 December Automobile Mobile Import 2565
## 2123 2019.000 July Electronics Mobile Export 240
## 2124 2024.000 February Pharma Medicine Import 9113
## 2125 2022.000 January Textile Car Export 5967
## 2126 2018.000 August Electronics Mobile Export 8958
## 2127 2021.000 July Textile Medicine Import 3599
## 2128 2021.000 March Pharma Wheat Import 3689
## 2129 2020.000 July Automobile Mobile Import 2891
## 2130 2019.000 July Textile Cotton Import 6052
## 2131 2019.000 July Pharma Medicine Import 3059
## 2132 2020.000 September Electronics Wheat Import 1124
## 2133 2023.000 April Electronics Car Export 1304
## 2134 2019.000 August Automobile Mobile Export 962
## 2135 2019.000 June Electronics Cotton Import 5720
## 2136 2021.000 April Automobile Car Export 4544
## 2137 2020.000 November Pharma Cotton Import 1175
## 2138 2024.000 March Textile Medicine Import 5165
## 2139 2018.000 June Electronics Cotton Export 3524
## 2140 2023.000 July Pharma Wheat Import 9773
## 2141 2019.000 May Electronics Mobile Export 2406
## 2142 2023.000 July Pharma Wheat Import 2794
## 2143 2021.000 November Pharma Cotton Import 5306
## 2144 2024.000 March Electronics Car Export 5178
## 2145 2020.000 February Agriculture Cotton Import 2000
## 2146 2021.000 November Electronics Cotton Import 5422
## 2147 2018.000 August Automobile Medicine Import 9256
## 2148 2019.000 August Electronics Medicine Import 4301
## 2149 2021.000 March Agriculture Mobile Export 4018
## 2150 2024.000 October Pharma Wheat Export 2335
## 2151 2022.000 April Pharma Medicine Import 2299
## 2152 2022.000 November Agriculture Wheat Import 7089
## 2153 2024.000 February Automobile Wheat Import 5097
## 2154 2020.000 September Automobile Medicine Export 3145
## 2155 2023.000 January Automobile Car Export 2582
## 2156 2023.000 May Electronics Car Export 4981
## 2157 2022.000 December Pharma Medicine Export 5881
## 2158 2019.000 June Pharma Car Export 2811
## 2159 2023.000 May Textile Car Export 1272
## 2160 2021.000 January Pharma Wheat Export 3856
## 2161 2020.000 December Automobile Medicine Export 4407
## 2162 2024.000 April Electronics Cotton Import 369
## 2163 2024.000 April Agriculture Car Import 6079
## 2164 2018.000 April Textile Car Import 9693
## 2165 2021.000 October Agriculture Medicine Import 8627
## 2166 2019.000 August Pharma Cotton Import 8084
## 2167 2018.000 June Agriculture Cotton Import 511
## 2168 2021.000 May Electronics Car Import 9807
## 2169 2022.000 December Automobile Cotton Import 1111
## 2170 2019.000 June Agriculture Medicine Export 1322
## 2171 2020.000 January Automobile Mobile Export 7637
## 2172 2024.000 June Agriculture Mobile Export 9073
## 2173 2023.000 January Pharma Cotton Import 1489
## 2174 2023.000 December Electronics Wheat Export 8328
## 2175 2024.000 September Textile Mobile Import 6536
## 2176 2024.000 November Pharma Wheat Export 5927
## 2177 2024.000 April Electronics Wheat Import 3047
## 2178 2019.000 July Agriculture Cotton Export 1396
## 2179 2024.000 December Textile Wheat Import 2999
## 2180 2021.000 November Textile Medicine Import 847
## 2181 2019.000 April Electronics Cotton Import 7112
## 2182 2022.000 December Electronics Wheat Import 2824
## 2183 2023.000 March Pharma Medicine Export 3120
## 2184 2018.000 March Automobile Mobile Import 7346
## 2185 2024.000 December Agriculture Cotton Import 871
## 2186 2022.000 August Pharma Medicine Export 2348
## 2187 2019.000 October Agriculture Car Import 9332
## 2188 2022.000 May Textile Wheat Import 4658
## 2189 2020.000 January Pharma Medicine Export 5591
## 2190 2021.000 August Electronics Car Import 8967
## 2191 2020.000 March Electronics Car Import 4199
## 2192 2024.000 October Electronics Medicine Import 6482
## 2193 2022.000 February Automobile Wheat Export 8422
## 2194 2021.000 December Pharma Mobile Import 338
## 2195 2023.000 September Pharma Medicine Export 4584
## 2196 2019.000 July Automobile Medicine Export 172
## 2197 2018.000 March Pharma Cotton Import 2082
## 2198 2018.000 February Automobile Wheat Import 9223
## 2199 2020.000 July Textile Cotton Import 8589
## 2200 2020.000 April Pharma Wheat Export 464
## 2201 2020.000 March Textile Medicine Import 9953
## 2202 2019.000 September Pharma Cotton Export 3426
## 2203 2019.000 April Electronics Cotton Export 9445
## 2204 2021.000 February Automobile Car Import 2108
## 2205 2021.000 January Automobile Car Export 8571
## 2206 2019.000 September Electronics Medicine Export 8167
## 2207 2018.000 September Electronics Medicine Import 558
## 2208 2024.000 July Textile Medicine Import 4054
## 2209 2024.000 May Pharma Wheat Import 4985
## 2210 2022.000 May Pharma Car Import 3177
## 2211 2020.000 April Textile Car Export 1178
## 2212 2021.000 May Textile Medicine Export 1475
## 2213 2022.000 August Agriculture Cotton Export 7859
## 2214 2018.000 October Pharma Car Export 1781
## 2215 2022.000 July Electronics Car Export 6653
## 2216 2024.000 March Electronics Cotton Export 7819
## 2217 2024.000 July Textile Cotton Import 7581
## 2218 2023.000 August Electronics Mobile Export 3515
## 2219 2021.000 July Automobile Car Import 7180
## 2220 2020.000 April Electronics Car Export 5737
## 2221 2018.000 September Automobile Cotton Import 799
## 2222 2019.000 July Automobile Mobile Import 208
## 2223 2019.000 December Electronics Medicine Import 3344
## 2224 2022.000 August Pharma Mobile Import 1507
## 2225 2019.000 January Textile Cotton Export 8205
## 2226 2024.000 December Pharma Cotton Import 6075
## 2227 2024.000 November Electronics Medicine Import 3098
## 2228 2024.000 February Agriculture Medicine Import 2104
## 2229 2023.000 September Electronics Mobile Export 2945
## 2230 2022.000 November Textile Car Export 103
## 2231 2022.000 April Electronics Car Import 1761
## 2232 2018.000 September Electronics Medicine Export 6300
## 2233 2024.000 December Automobile Medicine Export 2471
## 2234 2019.000 October Electronics Car Export 1854
## 2235 2021.000 January Pharma Cotton Import 8634
## 2236 2020.000 September Textile Cotton Export 728
## 2237 2022.000 May Textile Medicine Import 4366
## 2238 2020.000 July Agriculture Cotton Import 4915
## 2239 2024.000 October Agriculture Medicine Export 9709
## 2240 2021.000 September Automobile Wheat Export 5966
## 2241 2021.000 September Textile Cotton Import 2103
## 2242 2019.000 June Textile Mobile Import 4753
## 2243 2022.000 February Agriculture Wheat Export 4719
## 2244 2024.000 August Automobile Wheat Export 5755
## 2245 2018.000 June Automobile Cotton Export 2961
## 2246 2023.000 January Pharma Medicine Export 1924
## 2247 2019.000 July Electronics Mobile Import 1815
## 2248 2021.000 August Pharma Medicine Export 6627
## 2249 2024.000 April Textile Cotton Export 8415
## 2250 2019.000 April Textile Cotton Export 1539
## 2251 2018.000 December Textile Cotton Export 4199
## 2252 2022.000 August Automobile Cotton Export 9819
## 2253 2019.000 July Electronics Mobile Import 5016
## 2254 2022.000 December Textile Medicine Import 5390
## 2255 2019.000 December Textile Cotton Export 9102
## 2256 2020.000 May Pharma Car Import 5827
## 2257 2021.000 December Automobile Wheat Import 7302
## 2258 2020.000 November Automobile Cotton Export 7927
## 2259 2022.000 November Pharma Car Export 5252
## 2260 2021.000 November Textile Car Import 1146
## 2261 2024.000 March Electronics Medicine Import 9138
## 2262 2023.000 May Automobile Cotton Import 8138
## 2263 2022.000 May Textile Cotton Export 2769
## 2264 2020.000 August Automobile Car Import 516
## 2265 2023.000 April Automobile Car Export 4905
## 2266 2019.000 April Automobile Car Export 1810
## 2267 2019.000 May Agriculture Mobile Import 8299
## 2268 2019.000 April Pharma Car Export 7123
## 2269 2023.000 November Electronics Mobile Import 7728
## 2270 2020.000 May Pharma Car Export 7855
## 2271 2019.000 September Textile Wheat Import 4138
## 2272 2021.000 August Pharma Mobile Import 3583
## 2273 2021.000 January Automobile Cotton Export 9645
## 2274 2024.000 September Textile Wheat Import 9383
## 2275 2023.000 September Electronics Cotton Import 8364
## 2276 2018.000 September Textile Cotton Export 9346
## 2277 2024.000 June Textile Wheat Export 1631
## 2278 2022.000 August Textile Wheat Export 8951
## 2279 2021.000 November Textile Mobile Export 4523
## 2280 2018.000 June Electronics Medicine Export 8247
## 2281 2022.000 July Electronics Medicine Import 6579
## 2282 2019.000 December Textile Medicine Export 2811
## 2283 2022.000 July Electronics Car Import 5717
## 2284 2023.000 August Automobile Medicine Import 2481
## 2285 2021.000 September Automobile Car Import 6065
## 2286 2023.000 September Textile Medicine Import 267
## 2287 2021.000 November Pharma Mobile Import 7711
## 2288 2020.000 January Agriculture Mobile Import 188
## 2289 2019.000 September Agriculture Cotton Export 8931
## 2290 2023.000 December Automobile Medicine Export 9323
## 2291 2023.000 May Electronics Mobile Import 8672
## 2292 2018.000 November Textile Medicine Export 5469
## 2293 2018.000 March Pharma Medicine Import 8903
## 2294 2018.000 September Textile Mobile Export 8505
## 2295 2024.000 November Agriculture Wheat Import 4165
## 2296 2020.000 December Electronics Mobile Export 6085
## 2297 2019.000 February Electronics Car Export 1271
## 2298 2022.000 February Textile Medicine Export 9982
## 2299 2023.000 March Electronics Car Export 3176
## 2300 2020.000 April Agriculture Medicine Import 6933
## 2301 2018.000 September Automobile Cotton Export 9746
## 2302 2021.000 October Automobile Medicine Import 5440
## 2303 2021.000 April Pharma Medicine Export 1232
## 2304 2021.000 May Electronics Cotton Export 3585
## 2305 2020.000 March Pharma Cotton Import 1950
## 2306 2021.000 January Automobile Medicine Import 8008
## 2307 2023.000 January Textile Car Export 8075
## 2308 2018.000 November Automobile Cotton Import 8432
## 2309 2024.000 April Agriculture Mobile Import 9012
## 2310 2021.000 June Pharma Medicine Export 7308
## 2311 2024.000 April Electronics Cotton Export 9403
## 2312 2024.000 September Textile Cotton Export 2074
## 2313 2024.000 May Automobile Wheat Export 4636
## 2314 2020.000 November Automobile Wheat Export 7412
## 2315 2022.000 March Textile Mobile Export 451
## 2316 2022.000 October Automobile Medicine Import 1411
## 2317 2020.000 April Automobile Cotton Export 5489
## 2318 2021.000 October Electronics Mobile Import 1163
## 2319 2019.000 March Textile Car Import 4606
## 2320 2022.000 April Textile Cotton Import 5235
## 2321 2024.000 March Automobile Cotton Import 415
## 2322 2019.000 April Textile Cotton Export 6834
## 2323 2024.000 September Electronics Car Import 233
## 2324 2021.000 December Pharma Cotton Import 8923
## 2325 2021.000 January Textile Wheat Export 7686
## 2326 2019.000 November Pharma Cotton Import 7046
## 2327 2023.000 May Agriculture Car Export 2328
## 2328 2023.000 June Automobile Medicine Export 9760
## 2329 2022.000 September Electronics Medicine Import 865
## 2330 2024.000 November Pharma Mobile Import 5590
## 2331 2024.000 October Pharma Car Import 9508
## 2332 2021.000 November Electronics Wheat Import 4881
## 2333 2019.000 February Agriculture Cotton Import 3633
## 2334 2021.000 February Agriculture Cotton Export 2641
## 2335 2023.000 March Textile Medicine Import 4555
## 2336 2020.000 September Electronics Car Import 6629
## 2337 2019.000 December Automobile Wheat Export 4327
## 2338 2018.000 April Electronics Cotton Export 2250
## 2339 2018.000 August Electronics Car Import 5083
## 2340 2022.000 April Agriculture Mobile Export 398
## 2341 2024.000 September Textile Car Export 8830
## 2342 2022.000 December Agriculture Car Import 7443
## 2343 2022.000 October Textile Mobile Import 6575
## 2344 2024.000 February Automobile Wheat Import 9539
## 2345 2019.000 March Electronics Car Import 6165
## 2346 2021.000 June Textile Car Import 6607
## 2347 2023.000 June Electronics Cotton Export 8091
## 2348 2024.000 April Electronics Car Export 1070
## 2349 2019.000 November Pharma Cotton Import 6895
## 2350 2024.000 December Pharma Wheat Export 987
## 2351 2018.000 November Agriculture Mobile Export 4021
## 2352 2018.000 June Automobile Mobile Import 5861
## 2353 2024.000 February Automobile Cotton Export 1962
## 2354 2018.000 July Agriculture Wheat Import 5737
## 2355 2022.000 April Electronics Wheat Import 9028
## 2356 2023.000 January Automobile Medicine Import 2231
## 2357 2018.000 October Electronics Cotton Export 618
## 2358 2021.000 December Agriculture Car Export 3631
## 2359 2019.000 December Pharma Wheat Import 3975
## 2360 2019.000 May Agriculture Cotton Import 4451
## 2361 2018.000 September Textile Car Import 4582
## 2362 2018.000 January Textile Medicine Import 690
## 2363 2021.000 August Automobile Car Import 788
## 2364 2020.000 January Textile Cotton Import 1046
## 2365 2020.000 November Textile Medicine Import 2764
## 2366 2024.000 April Textile Mobile Import 2391
## 2367 2021.000 February Agriculture Cotton Export 1086
## 2368 2019.000 April Agriculture Wheat Import 6024
## 2369 2020.000 February Textile Mobile Import 4121
## 2370 2024.000 November Textile Car Export 5948
## 2371 2019.000 October Pharma Medicine Export 9217
## 2372 2022.000 December Textile Wheat Export 4728
## 2373 2021.000 October Electronics Medicine Import 9539
## 2374 2022.000 June Electronics Medicine Import 8020
## 2375 2020.000 February Pharma Wheat Export 4286
## 2376 2022.000 April Textile Car Import 6695
## 2377 2018.000 July Automobile Medicine Export 186
## 2378 2018.000 January Textile Mobile Export 9582
## 2379 2022.000 August Automobile Medicine Import 5432
## 2380 2019.000 August Electronics Cotton Export 4477
## 2381 2021.000 March Agriculture Medicine Export 5216
## 2382 2024.000 July Pharma Car Export 4545
## 2383 2023.000 August Electronics Cotton Export 3552
## 2384 2023.000 July Pharma Wheat Export 4540
## 2385 2021.000 October Pharma Wheat Import 3687
## 2386 2018.000 June Agriculture Car Import 2747
## 2387 2021.000 September Electronics Cotton Import 3668
## 2388 2020.000 January Automobile Cotton Import 7009
## 2389 2019.000 May Agriculture Car Export 411
## 2390 2024.000 December Agriculture Medicine Export 7417
## 2391 2023.000 July Pharma Car Import 148
## 2392 2024.000 March Electronics Car Export 3866
## 2393 2022.000 September Agriculture Car Import 8345
## 2394 2022.000 May Electronics Mobile Export 6862
## 2395 2019.000 December Textile Medicine Export 4671
## 2396 2021.000 September Electronics Mobile Export 369
## 2397 2021.000 July Pharma Car Export 7690
## 2398 2021.000 June Agriculture Wheat Import 8975
## 2399 2022.000 June Electronics Medicine Import 9990
## 2400 2022.000 November Automobile Cotton Export 9060
## 2401 2020.000 April Automobile Car Import 488
## 2402 2020.000 October Electronics Medicine Export 2099
## 2403 2018.000 April Agriculture Cotton Export 6796
## 2404 2019.000 March Pharma Mobile Export 4185
## 2405 2024.000 July Automobile Medicine Import 6392
## 2406 2024.000 May Pharma Medicine Export 8398
## 2407 2022.000 January Textile Mobile Import 6280
## 2408 2023.000 February Pharma Car Import 2188
## 2409 2020.000 May Pharma Mobile Export 2335
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## 2413 2020.000 September Automobile Wheat Export 7497
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## 2415 2018.000 May Electronics Medicine Import 1526
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## 2417 2023.000 October Textile Medicine Import 9357
## 2418 2022.000 October Electronics Medicine Import 8218
## 2419 2018.000 May Pharma Mobile Import 6551
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## 2421 2018.000 June Textile Wheat Export 9543
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## 2423 2020.000 May Automobile Wheat Import 7165
## 2424 2019.000 January Automobile Wheat Export 2045
## 2425 2021.000 October Automobile Car Import 6302
## 2426 2023.000 December Pharma Medicine Export 2109
## 2427 2020.000 June Pharma Cotton Import 9274
## 2428 2022.000 September Electronics Mobile Export 3104
## 2429 2019.000 June Pharma Wheat Export 3674
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## 2431 2022.000 October Textile Cotton Import 607
## 2432 2019.000 April Pharma Car Export 2184
## 2433 2024.000 May Automobile Mobile Export 1335
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## 2436 2022.000 July Electronics Car Export 1529
## 2437 2024.000 July Automobile Cotton Import 4134
## 2438 2024.000 July Automobile Car Export 3118
## 2439 2024.000 March Pharma Medicine Export 7651
## 2440 2018.000 March Electronics Medicine Import 4849
## 2441 2020.000 March Electronics Cotton Export 7004
## 2442 2021.000 November Automobile Mobile Import 2864
## 2443 2019.000 July Pharma Medicine Import 8125
## 2444 2018.000 January Agriculture Medicine Import 2290
## 2445 2020.000 April Agriculture Medicine Import 9656
## 2446 2023.000 December Automobile Medicine Export 7159
## 2447 2023.000 November Textile Wheat Import 3333
## 2448 2018.000 October Automobile Car Export 440
## 2449 2024.000 April Pharma Medicine Import 1385
## 2450 2022.000 April Agriculture Car Export 5425
## 2451 2023.000 July Automobile Mobile Import 3270
## 2452 2023.000 January Agriculture Mobile Export 8512
## 2453 2022.000 November Agriculture Medicine Export 9057
## 2454 2023.000 April Pharma Wheat Export 6154
## 2455 2021.000 April Automobile Car Import 8988
## 2456 2020.000 March Automobile Cotton Export 4124
## 2457 2024.000 December Automobile Wheat Export 3753
## 2458 2018.000 February Pharma Car Import 8203
## 2459 2018.000 October Electronics Car Export 6055
## 2460 2018.000 March Automobile Mobile Import 3097
## 2461 2022.000 October Textile Car Import 4599
## 2462 2021.000 April Agriculture Car Import 8351
## 2463 2023.000 November Textile Car Export 4246
## 2464 2024.000 September Agriculture Cotton Import 6355
## 2465 2019.000 October Pharma Car Export 9572
## 2466 2023.000 April Electronics Medicine Import 3850
## 2467 2022.000 September Agriculture Car Export 4115
## 2468 2018.000 May Agriculture Wheat Import 6594
## 2469 2023.000 March Agriculture Medicine Import 6114
## 2470 2024.000 August Textile Cotton Export 5424
## 2471 2022.000 June Pharma Wheat Export 8797
## 2472 2019.000 July Automobile Mobile Import 6032
## 2473 2023.000 November Agriculture Wheat Import 7805
## 2474 2018.000 February Agriculture Car Export 3400
## 2475 2022.000 April Agriculture Medicine Import 4560
## 2476 2022.000 September Pharma Car Import 7503
## 2477 2019.000 July Agriculture Cotton Import 602
## 2478 2024.000 January Pharma Car Export 8564
## 2479 2021.000 June Pharma Mobile Import 2201
## 2480 2020.000 January Textile Car Export 6826
## 2481 2024.000 November Automobile Car Import 6038
## 2482 2022.000 March Electronics Mobile Export 5665
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## 2484 2020.000 September Agriculture Wheat Export 5113
## 2485 2018.000 July Textile Cotton Export 3469
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## 2489 2022.000 July Textile Cotton Export 7483
## 2490 2022.000 March Automobile Medicine Export 9647
## 2491 2020.000 May Pharma Car Export 9581
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## 2494 2020.000 January Automobile Wheat Export 6801
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## 2496 2023.000 July Pharma Car Import 499
## 2497 2021.000 January Electronics Medicine Import 6963
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## Value_USD Country Port Transport_Mode Tariff GST
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## 1411 9156.828 China Chennai Air 15.536033 17.645306
## 1412 67399.015 Germany Kandla Air 14.115674 16.952316
## 1413 72285.067 China Delhi Air 12.915191 12.339117
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## 1415 14999.227 UAE Kolkata Land 10.569613 15.200235
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## 1418 34116.599 USA Chennai Air 11.369036 9.145079
## 1419 17348.894 UAE Chennai Air 17.012625 12.287600
## 1420 61671.494 China Chennai Land 5.410524 15.081337
## 1421 35232.706 UAE Kandla Sea 10.774582 9.226188
## 1422 67580.006 USA Delhi Land 19.982073 10.738860
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## 1424 45892.268 China Kolkata Sea 6.589766 13.304227
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## 1428 87147.802 UK Kolkata Air 16.453628 11.893749
## 1429 90854.228 Germany Delhi Sea 14.488325 15.424776
## 1430 2239.719 UK Chennai Air 17.664983 13.840592
## 1431 81581.197 China Mumbai Sea 17.156848 13.769120
## 1432 63212.766 Japan Delhi Sea 11.706852 12.860704
## 1433 24051.265 USA Mumbai Land 7.974292 17.229698
## 1434 61915.015 China Chennai Air 17.242780 13.862485
## 1435 86998.131 China Kandla Land 19.501836 16.875125
## 1436 52681.577 UAE Chennai Land 18.755120 6.322738
## 1437 43630.180 China Delhi Sea 19.053876 5.728962
## 1438 49944.811 UAE Chennai Land 15.323447 11.684882
## 1439 96028.964 Germany Chennai Air 11.502172 12.933501
## 1440 65558.128 UAE Delhi Land 8.988371 9.483749
## 1441 93213.333 USA Delhi Land 16.497666 14.214194
## 1442 10037.853 Germany Kolkata Land 16.096909 12.415130
## 1443 72994.337 Japan Mumbai Air 6.550745 16.036469
## 1444 59484.646 Japan Chennai Sea 13.347764 14.491889
## 1445 71272.700 USA Mumbai Land 5.236901 5.987414
## 1446 52748.599 UK Chennai Sea 14.927978 13.630164
## 1447 47492.966 Japan Kolkata Land 7.644895 11.654759
## 1448 5387.591 China Kandla Air 18.062860 7.451336
## 1449 90532.196 China Mumbai Sea 16.480265 8.192275
## 1450 27769.637 USA Kolkata Land 55.288747 7.657979
## 1451 5007.912 Germany Chennai Air 17.895705 5.561742
## 1452 33175.995 UK Kandla Sea 17.005416 16.967756
## 1453 88677.694 UAE Delhi Sea 10.458107 11.938055
## 1454 39575.420 USA Kolkata Sea 17.881984 10.354541
## 1455 49864.172 Germany Kandla Sea 16.598929 11.804708
## 1456 56520.085 Germany Kolkata Land 12.606069 11.636711
## 1457 22745.164 Germany Chennai Air 15.149133 15.879633
## 1458 92515.374 China Kandla Air 11.375035 12.635699
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## 1460 8181.613 Germany Kolkata Air 6.246550 9.368154
## 1461 53308.966 China Delhi Sea 12.988491 5.096436
## 1462 63397.838 USA Chennai Land 17.348524 13.707232
## 1463 75528.901 China Kolkata Air 18.941486 8.959412
## 1464 35880.215 UK Kolkata Land 10.710978 13.839662
## 1465 17585.769 China Kolkata Sea 14.775857 7.119724
## 1466 71584.438 UAE Delhi Sea 17.987895 5.121002
## 1467 12418.457 Germany Chennai Sea 19.395580 7.235482
## 1468 5982.226 China Chennai Land 16.187264 9.943270
## 1469 45461.477 China Kandla Land 5.018197 13.472016
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## 1471 91631.194 China Delhi Land 16.970796 14.188187
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## 1473 34412.278 USA Delhi Air 15.973174 13.915191
## 1474 34831.899 UK Chennai Air 14.111992 13.982568
## 1475 40370.854 UAE Chennai Air 11.099237 7.724908
## 1476 55994.721 UAE Kolkata Air 5.474265 17.802017
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## 1478 98466.824 UAE Delhi Land 19.947013 7.143668
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## 1480 33845.635 Germany Delhi Air 13.729239 13.886712
## 1481 86212.680 UAE Mumbai Land 8.290819 6.602256
## 1482 31459.459 Japan Chennai Air 13.293631 7.290899
## 1483 5295.742 USA Kolkata Air 15.551148 16.136277
## 1484 71735.118 USA Chennai Air 12.676584 9.816003
## 1485 26885.342 China Kandla Land 18.116732 7.038628
## 1486 63674.565 Germany Mumbai Air 5.566796 15.443878
## 1487 27919.669 USA Chennai Sea 15.974072 14.347983
## 1488 27948.517 Germany Kandla Sea 9.712442 9.166327
## 1489 99135.198 Germany Kandla Sea 7.164945 10.042625
## 1490 49239.832 China Chennai Land 18.219410 14.800778
## 1491 36357.166 China Kolkata Land 18.837874 6.616027
## 1492 85218.351 China Kandla Sea 8.170439 14.757199
## 1493 48077.641 USA Kolkata Land 16.834859 15.808202
## 1494 84699.535 China Delhi Air 19.826728 5.996621
## 1495 77421.754 UAE Kolkata Land 16.667682 17.090163
## 1496 18914.388 UAE Kolkata Land 17.121563 9.246482
## 1497 60471.505 China Chennai Air 14.052839 16.746221
## 1498 69964.008 China Mumbai Sea 10.603574 7.199857
## 1499 27325.198 UAE Mumbai Land 17.478623 11.422755
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## 1502 67449.992 Germany Delhi Land 11.541440 13.218287
## 1503 89459.233 Germany Chennai Sea 10.056341 16.639886
## 1504 33616.872 Japan Mumbai Air 14.396398 12.698358
## 1505 23275.272 USA Mumbai Sea 19.779133 9.864038
## 1506 70349.718 UK Kolkata Air 16.571229 10.183173
## 1507 46945.275 China Chennai Land 9.027694 17.794143
## 1508 58182.739 Germany Kolkata Sea 19.647561 9.801531
## 1509 76115.700 USA Kolkata Air 12.721097 13.074558
## 1510 44903.333 Germany Delhi Air 8.091071 13.292520
## 1511 16887.381 UK Kandla Air 10.207076 17.467581
## 1512 21787.265 Japan Mumbai Land 17.907725 16.049253
## 1513 46740.549 Japan Chennai Air 15.676757 10.400850
## 1514 88201.429 USA Chennai Land 13.635777 14.632998
## 1515 41862.150 UAE Kandla Air 17.899145 14.716955
## 1516 37169.793 Germany Mumbai Sea 17.048030 6.408277
## 1517 3481.318 UAE Mumbai Land 16.846073 12.614793
## 1518 99486.192 Germany Delhi Air 9.546295 8.702506
## 1519 48176.683 Germany Mumbai Sea 12.299443 16.150509
## 1520 98041.470 UAE Delhi Land 11.174415 9.078902
## 1521 16461.477 UAE Kolkata Land 6.484871 5.626451
## 1522 50222.545 Japan Kolkata Land 10.524247 15.229374
## 1523 18203.905 UK Mumbai Land 8.376512 5.449626
## 1524 70991.842 Japan Chennai Land 14.637500 7.088977
## 1525 55713.445 Japan Kandla Sea 5.094372 14.408902
## 1526 36997.714 Japan Delhi Air 16.443904 11.207980
## 1527 2473.603 UAE Chennai Air 19.931470 10.876066
## 1528 30288.013 UAE Kolkata Sea 8.656741 6.984440
## 1529 16451.402 USA Chennai Land 12.563127 15.173560
## 1530 56354.165 China Mumbai Land 19.870427 12.712192
## 1531 15646.756 UK Delhi Sea 19.307501 6.398262
## 1532 34844.929 UAE Chennai Land 19.317220 7.053770
## 1533 4286.427 UAE Delhi Air 14.180287 11.168597
## 1534 21810.136 China Delhi Land 5.968896 15.814913
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## 1537 11554.595 Germany Mumbai Land 12.136941 10.247218
## 1538 20660.078 Germany Chennai Air 13.434322 6.616166
## 1539 17453.757 UK Mumbai Sea 9.374095 12.351142
## 1540 49065.759 USA Mumbai Land 15.141167 12.174420
## 1541 54097.403 UAE Delhi Air 6.541631 8.595832
## 1542 18012.904 China Delhi Land 8.829864 15.506935
## 1543 70972.160 Japan Mumbai Sea 15.800132 11.883330
## 1544 69255.295 UK Mumbai Air 13.894287 14.542573
## 1545 63882.038 China Chennai Sea 18.082222 12.955880
## 1546 13469.881 USA Delhi Land 8.435067 9.861986
## 1547 6527.377 USA Mumbai Land 12.757398 5.013365
## 1548 22452.331 UK Delhi Land 11.924091 15.229447
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## 1550 72508.510 Japan Chennai Land 6.929015 5.915673
## 1551 96422.827 Japan Kolkata Land 19.786034 13.133442
## 1552 43486.622 USA Kandla Air 13.159320 13.068185
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## 1557 70548.389 USA Chennai Land 10.451619 6.997860
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## 1574 99405.937 UK Kolkata Sea 9.750099 15.951415
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## 1583 26415.690 UK Kandla Air 12.072334 8.706526
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## 1595 74985.964 Japan Delhi Air 18.684575 15.991848
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## 1606 4767.829 Japan Kandla Air 6.339833 10.556828
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## 1609 55573.583 China Kandla Sea 12.187155 8.645788
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## 1613 45843.075 China Mumbai Sea 11.445173 7.554721
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## 1629 37153.866 China Mumbai Air 5.892500 12.935554
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## 1632 95492.701 UAE Delhi Land 19.747155 13.679342
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## 1634 8717.537 China Kolkata Sea 5.539450 10.545437
## 1635 12077.335 UK Mumbai Air 16.438238 17.247486
## 1636 7346.442 Japan Mumbai Land 13.689267 16.979705
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## 1639 21656.625 Japan Chennai Air 16.121143 10.314585
## 1640 42720.462 USA Delhi Air 16.706718 5.311659
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## 1643 76297.160 UAE Delhi Sea 18.942506 17.751796
## 1644 83501.353 UAE Kandla Land 15.740463 13.706814
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## 1652 37221.797 Japan Chennai Sea 9.782011 6.231539
## 1653 20995.534 USA Chennai Land 16.007587 9.566354
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## 1656 66661.774 UK Chennai Air 9.334387 5.333412
## 1657 69605.303 China Kolkata Land 17.432781 15.873124
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## 1662 49074.253 UAE Mumbai Air 10.617380 12.026790
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## 1673 53196.698 Germany Kolkata Air 19.324709 10.991422
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## 1678 83274.960 UK Kandla Air 13.688330 6.239680
## 1679 38462.767 Germany Mumbai Air 7.281434 15.328608
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## 1683 82626.627 UAE Mumbai Sea 5.598091 12.820902
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## 1685 53466.532 UAE Chennai Sea 6.789653 7.076132
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## 1691 39379.764 China Chennai Air 10.045999 9.835533
## 1692 77157.768 Germany Mumbai Air 12.169101 8.438941
## 1693 6445.945 UAE Chennai Sea 6.797605 7.004914
## 1694 45180.766 UK Chennai Land 19.724536 11.900683
## 1695 4253.555 UAE Kolkata Sea 8.076067 13.262526
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## 1697 74852.911 Germany Chennai Sea 13.387872 6.651377
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## 1700 17070.668 UK Kolkata Sea 8.816648 10.561065
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## 1709 48070.836 UAE Kolkata Air 16.439017 15.550915
## 1710 78976.090 Japan Chennai Air 19.345338 17.222839
## 1711 50747.272 Japan Mumbai Sea 13.614080 7.854919
## 1712 88130.322 Japan Chennai Land 12.154928 12.688131
## 1713 57236.903 UK Chennai Air 13.848462 14.853995
## 1714 31428.183 UK Chennai Air 19.006669 14.725194
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## 1716 50430.778 UK Mumbai Air 12.311984 17.130484
## 1717 37618.528 UAE Mumbai Air 14.595145 9.065172
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## 1720 20540.606 China Chennai Land 16.987681 7.995181
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## 1722 34429.334 UAE Mumbai Land 16.895712 8.592357
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## 1725 50284.140 UK Mumbai Air 16.901139 16.154168
## 1726 81452.803 Germany Kolkata Sea 12.913177 8.641932
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## 1729 2059.025 USA Mumbai Air 12.053016 10.659754
## 1730 88317.484 Japan Kandla Air 9.248898 12.956313
## 1731 6094.495 UK Kandla Air 16.701213 5.908848
## 1732 75386.497 Japan Kolkata Sea 9.114512 7.973138
## 1733 73458.885 Japan Delhi Sea 7.855585 7.694600
## 1734 2173.984 UAE Mumbai Land 18.926307 6.456521
## 1735 74983.589 USA Chennai Sea 15.754620 15.326490
## 1736 4425.220 Germany Kolkata Sea 5.578423 8.330298
## 1737 67495.325 Germany Mumbai Land 16.172964 5.530596
## 1738 81780.280 Japan Kolkata Land 16.442747 14.047151
## 1739 93853.339 Japan Chennai Air 7.374775 16.132058
## 1740 65070.420 UK Mumbai Land 11.260099 11.600947
## 1741 58752.268 Germany Delhi Air 19.107425 16.580256
## 1742 39260.552 USA Mumbai Air 9.807992 8.699385
## 1743 45912.849 UK Mumbai Land 7.290160 15.964167
## 1744 75911.354 Japan Delhi Sea 16.493379 13.105475
## 1745 20270.604 UK Kandla Land 17.678218 13.128699
## 1746 27471.886 Germany Delhi Land 11.686544 13.626334
## 1747 66261.965 Germany Mumbai Sea 16.616299 9.473117
## 1748 22139.463 Japan Kolkata Air 8.562473 15.943468
## 1749 71312.465 USA Chennai Air 15.416132 7.858856
## 1750 26840.938 Germany Kolkata Air 12.682806 7.802964
## 1751 8909.825 Germany Kolkata Sea 16.929976 7.104381
## 1752 20665.363 UAE Kolkata Air 10.830898 11.550295
## 1753 58796.600 UAE Kandla Sea 14.420592 6.941822
## 1754 31704.067 UAE Kandla Sea 8.421941 6.312162
## 1755 17675.384 China Kolkata Sea 14.358847 13.734299
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## 1758 16854.648 Germany Kandla Air 17.925775 17.960238
## 1759 56895.531 UAE Delhi Sea 14.217395 9.939687
## 1760 1846.068 UAE Delhi Air 7.486653 15.540340
## 1761 45366.274 China Mumbai Sea 12.903353 15.383911
## 1762 69608.298 China Kolkata Land 7.530625 10.132328
## 1763 72289.391 UK Kandla Sea 10.683040 17.020548
## 1764 49983.111 Germany Kolkata Air 6.962941 6.203005
## 1765 4985.388 Japan Mumbai Sea 7.846484 12.844445
## 1766 55043.382 Germany Kandla Land 17.272349 12.800492
## 1767 27078.135 China Mumbai Land 6.465126 14.244882
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## 1769 66671.178 Japan Delhi Air 10.996910 16.432605
## 1770 28178.647 Germany Delhi Air 12.106457 10.368080
## 1771 61358.118 UAE Delhi Air 12.431974 17.709271
## 1772 31037.050 UAE Chennai Sea 9.584668 8.759462
## 1773 74076.669 UAE Kolkata Land 8.184895 7.971800
## 1774 50064.628 China Chennai Air 5.011520 48.609158
## 1775 6848.545 Germany Kandla Air 18.838820 15.917877
## 1776 50719.524 UAE Kolkata Land 12.976256 8.869937
## 1777 29585.107 China Chennai Sea 8.960224 7.219164
## 1778 93390.785 Germany Delhi Sea 16.388201 13.226811
## 1779 77939.174 UK Mumbai Land 8.790345 15.630920
## 1780 73922.151 USA Mumbai Air 19.800227 10.362682
## 1781 49178.048 Japan Mumbai Land 14.664752 14.629001
## 1782 66636.061 UK Kandla Air 6.112066 7.606114
## 1783 1209.597 Japan Mumbai Land 18.685399 5.814910
## 1784 94126.394 UAE Delhi Land 11.999887 9.393144
## 1785 20059.148 UAE Chennai Air 17.050490 16.886252
## 1786 57176.554 USA Delhi Air 16.442618 9.782151
## 1787 2186.653 UK Delhi Land 17.542691 9.074785
## 1788 39010.460 China Kandla Land 10.757300 17.117229
## 1789 74376.762 China Kandla Sea 9.124262 5.400333
## 1790 54132.812 Japan Delhi Sea 5.687568 10.576531
## 1791 49341.200 Germany Kandla Sea 13.291135 17.801157
## 1792 91482.459 UK Chennai Air 18.021524 8.268955
## 1793 91870.988 UAE Kolkata Sea 16.333429 12.109097
## 1794 85628.986 Japan Kandla Sea 11.359519 8.573557
## 1795 36550.064 Germany Delhi Sea 5.103827 13.896675
## 1796 37585.865 China Delhi Air 6.646121 10.228982
## 1797 41356.854 Japan Kandla Air 17.940884 16.453365
## 1798 2596.981 Japan Chennai Air 13.979658 15.092966
## 1799 81917.487 USA Kolkata Air 6.766048 17.335145
## 1800 42261.599 UAE Chennai Sea 8.090270 15.154100
## 1801 12940.573 Japan Chennai Air 19.257429 7.226036
## 1802 49383.438 Japan Delhi Sea 13.392081 16.696759
## 1803 90293.729 USA Kolkata Land 9.749025 13.592563
## 1804 11539.457 UAE Kandla Sea 11.403108 7.442707
## 1805 96071.104 USA Mumbai Sea 9.142637 16.091734
## 1806 95105.025 Germany Kolkata Sea 9.043830 8.872117
## 1807 4501.618 Japan Kolkata Air 13.254903 10.502272
## 1808 53999.409 Germany Kolkata Air 14.624597 13.647106
## 1809 27006.483 Germany Kandla Air 11.137502 5.228764
## 1810 84791.368 Japan Kandla Air 11.618251 12.873997
## 1811 8565.568 Japan Chennai Sea 11.514288 8.230747
## 1812 87048.911 Germany Kolkata Air 5.610429 6.662419
## 1813 67984.781 Japan Chennai Air 13.262516 13.878132
## 1814 8805.721 Japan Kandla Air 14.370196 17.464542
## 1815 19275.928 Germany Mumbai Air 15.374736 9.487220
## 1816 72660.720 Japan Delhi Air 7.808854 14.690234
## 1817 5779.909 UAE Mumbai Sea 10.160041 11.035540
## 1818 21716.695 China Mumbai Sea 18.855635 8.307294
## 1819 1140.553 UAE Chennai Air 17.455055 10.152599
## 1820 55044.624 Germany Kolkata Sea 10.719795 14.381142
## 1821 21791.735 UK Kandla Air 10.434314 13.958168
## 1822 64266.161 UK Kolkata Air 7.481955 17.196035
## 1823 38394.307 Japan Chennai Sea 8.123909 6.895956
## 1824 59388.054 Japan Delhi Land 17.766862 12.882584
## 1825 24016.940 China Delhi Sea 13.854833 5.810734
## 1826 21110.210 UAE Chennai Sea 17.647658 16.114254
## 1827 5351.551 UAE Mumbai Land 9.045606 16.345714
## 1828 36840.918 Germany Kandla Air 6.369544 9.946279
## 1829 80178.687 UAE Kandla Land 12.525335 15.340937
## 1830 95130.735 UK Kandla Air 11.434879 8.062353
## 1831 50049.961 USA Kolkata Sea 19.762853 7.371371
## 1832 62351.601 Germany Kolkata Land 10.021937 16.731570
## 1833 55593.772 UAE Kandla Land 17.744774 11.796618
## 1834 40460.234 China Kandla Land 17.943388 9.129636
## 1835 63388.264 Germany Mumbai Air 7.123747 13.117146
## 1836 92642.011 Germany Kolkata Sea 12.836374 7.895750
## 1837 71695.561 USA Delhi Land 12.566766 6.678580
## 1838 90916.886 USA Mumbai Land 11.304184 6.436139
## 1839 89070.029 China Delhi Land 6.696959 9.842905
## 1840 68032.148 USA Mumbai Land 11.018013 11.161795
## 1841 2383.271 USA Chennai Sea 15.514557 9.802717
## 1842 42312.542 Germany Kolkata Land 14.972938 7.079540
## 1843 59189.606 UAE Chennai Land 17.066289 9.434189
## 1844 21799.070 UAE Kolkata Sea 13.923014 12.369778
## 1845 35492.717 Japan Mumbai Sea 5.926386 16.931381
## 1846 51232.933 Germany Kolkata Sea 12.112586 7.590764
## 1847 28512.639 USA Delhi Air 7.322506 14.321216
## 1848 97169.251 UAE Mumbai Land 7.913752 10.412358
## 1849 79619.026 China Kandla Air 15.747161 9.889407
## 1850 47035.118 Germany Kandla Land 16.432004 13.995855
## 1851 22455.646 UK Delhi Land 18.483150 13.567564
## 1852 92599.102 UAE Delhi Air 5.317912 5.342591
## 1853 64817.653 Japan Kolkata Land 7.025765 15.900813
## 1854 27806.097 USA Delhi Sea 15.492989 15.885494
## 1855 46590.520 Japan Chennai Air 10.018361 14.846780
## 1856 29868.524 China Chennai Sea 15.665852 17.408844
## 1857 10022.674 Japan Kolkata Air 16.540260 7.627645
## 1858 18034.505 Japan Kolkata Land 5.539222 10.221687
## 1859 81138.408 Japan Kandla Land 17.575890 10.313167
## 1860 94244.437 Germany Kandla Air 10.492427 17.791738
## 1861 53129.772 Japan Delhi Air 13.399495 11.674892
## 1862 70682.123 Germany Kandla Land 10.027720 16.074953
## 1863 88033.287 USA Kandla Sea 13.987156 8.707966
## 1864 81489.149 UAE Kandla Sea 16.296382 16.582946
## 1865 59149.803 USA Kolkata Land 16.268539 7.789241
## 1866 21161.399 Germany Chennai Land 17.148412 17.885270
## 1867 63147.067 USA Mumbai Land 5.309294 16.721061
## 1868 71104.336 Japan Kolkata Sea 17.106562 10.306601
## 1869 5400.043 China Kandla Air 6.081021 13.531691
## 1870 47404.625 USA Mumbai Sea 19.320270 14.406601
## 1871 46843.910 China Chennai Sea 14.990311 12.590487
## 1872 62757.935 China Mumbai Sea 10.611097 7.070372
## 1873 90865.553 UK Kandla Land 19.986461 12.703256
## 1874 58091.336 China Kandla Land 5.816509 15.015559
## 1875 82054.050 China Kandla Air 12.206467 17.278212
## 1876 73441.051 Japan Mumbai Land 18.413597 14.144409
## 1877 60027.133 Germany Kandla Sea 19.990958 9.946792
## 1878 3631.030 Germany Kandla Sea 19.239117 14.071737
## 1879 96450.888 UAE Kolkata Sea 16.004833 17.889335
## 1880 23291.491 China Chennai Air 10.719132 8.914365
## 1881 35211.409 UAE Delhi Land 8.907756 6.010415
## 1882 72474.478 Japan Kolkata Sea 8.274805 5.678499
## 1883 45421.188 USA Chennai Land 11.761460 16.028375
## 1884 50751.143 UAE Kandla Sea 15.804166 17.221725
## 1885 11047.964 China Chennai Land 18.665092 6.520108
## 1886 12993.366 Japan Kandla Land 16.267353 14.050394
## 1887 32934.198 UAE Kolkata Land 19.899044 15.860860
## 1888 12185.904 Japan Delhi Land 15.239124 17.133914
## 1889 43744.760 Japan Kandla Air 8.956131 6.849477
## 1890 95311.087 China Chennai Sea 10.009395 12.736114
## 1891 8827.567 USA Kandla Sea 7.640006 8.165346
## 1892 42309.662 Germany Chennai Land 5.543474 9.065434
## 1893 26600.825 Germany Kolkata Sea 18.961935 14.804538
## 1894 91588.279 Germany Mumbai Air 16.537203 16.278763
## 1895 65479.914 USA Delhi Land 19.912562 5.069935
## 1896 21081.713 Germany Kolkata Land 15.952682 10.668523
## 1897 65905.171 UAE Kandla Air 16.423484 8.161574
## 1898 73888.538 Germany Kolkata Sea 17.381441 12.845650
## 1899 18960.830 China Kolkata Land 14.982274 10.124696
## 1900 24153.236 UK Mumbai Air 13.428248 9.603187
## 1901 51963.699 Germany Chennai Air 5.044836 15.604135
## 1902 26924.113 China Kandla Land 5.466023 15.296380
## 1903 29671.449 USA Mumbai Land 11.062084 6.299877
## 1904 66485.238 Germany Chennai Sea 17.611020 12.991013
## 1905 41786.184 USA Chennai Land 15.887848 5.442928
## 1906 73729.859 China Delhi Land 17.433652 12.104126
## 1907 35507.593 China Delhi Land 5.772011 14.788667
## 1908 26606.688 Germany Delhi Air 13.756639 15.136642
## 1909 51441.272 UK Kolkata Sea 6.572557 17.486149
## 1910 63064.317 UK Kandla Land 18.240841 9.204219
## 1911 59938.057 UAE Kandla Air 10.764287 10.187112
## 1912 41284.808 Germany Delhi Sea 6.624990 16.592856
## 1913 99027.104 Germany Kandla Air 5.338229 16.074536
## 1914 96093.276 Japan Chennai Land 14.259520 12.146910
## 1915 32182.136 China Kandla Land 19.551024 10.167620
## 1916 74587.576 UAE Chennai Sea 14.854110 11.908029
## 1917 56180.208 UK Chennai Sea 8.578347 17.414851
## 1918 88478.252 USA Mumbai Land 13.669726 16.121197
## 1919 60660.236 UAE Kandla Sea 7.595015 17.909142
## 1920 33278.566 China Delhi Land 18.829397 11.175221
## 1921 94261.118 Japan Kandla Air 18.292426 5.992187
## 1922 25288.612 UK Delhi Land 6.942694 12.072675
## 1923 41390.977 UK Kandla Sea 13.502002 7.547178
## 1924 62620.346 Germany Kolkata Land 17.923418 5.273778
## 1925 64419.938 UK Chennai Land 8.081555 15.511590
## 1926 91035.137 China Chennai Land 16.159264 13.060062
## 1927 61384.114 USA Delhi Sea 8.190114 16.957794
## 1928 27641.383 Germany Kandla Land 5.668645 10.214014
## 1929 73031.864 UK Kolkata Air 15.923805 7.013580
## 1930 74396.530 China Mumbai Air 6.514057 6.302999
## 1931 26390.159 China Kolkata Land 16.924944 5.039090
## 1932 83628.106 USA Kandla Air 16.155569 9.537291
## 1933 97042.175 China Mumbai Air 12.025256 11.625952
## 1934 78029.093 UAE Delhi Land 9.151740 14.134191
## 1935 5459.824 UK Chennai Sea 8.456682 7.322923
## 1936 34457.442 UK Kandla Sea 8.036745 15.256020
## 1937 81294.936 UAE Chennai Air 13.895568 17.952960
## 1938 43504.291 Germany Delhi Land 17.399716 15.923117
## 1939 87809.872 Japan Kandla Sea 14.750545 8.075891
## 1940 87587.411 USA Mumbai Sea 17.766164 16.661723
## 1941 3277.270 USA Kolkata Air 12.965392 15.217924
## 1942 61305.809 China Chennai Sea 19.171042 10.008317
## 1943 58230.926 China Chennai Air 16.559975 9.850339
## 1944 96793.817 UK Kandla Air 12.710870 17.004133
## 1945 54847.119 UK Kolkata Sea 9.371448 15.036355
## 1946 66024.633 Japan Chennai Sea 11.002236 8.761260
## 1947 65310.020 Germany Kolkata Land 19.699761 11.117357
## 1948 54835.913 Japan Kolkata Air 13.389485 15.806732
## 1949 94853.165 China Delhi Air 12.140580 11.715640
## 1950 46069.741 Japan Chennai Sea 19.179428 12.611962
## 1951 24333.866 China Mumbai Sea 12.237508 15.838129
## 1952 93602.127 Germany Mumbai Air 17.274341 14.737869
## 1953 4053.786 China Delhi Air 10.295659 7.504907
## 1954 70472.905 UAE Kolkata Sea 6.191210 7.761686
## 1955 97230.360 UAE Kolkata Sea 14.359709 13.800492
## 1956 66691.985 UAE Mumbai Sea 18.868648 5.086412
## 1957 54003.312 USA Kolkata Air 14.867510 8.178880
## 1958 81584.069 USA Delhi Land 6.016198 16.351004
## 1959 25223.586 Japan Kandla Air 7.557712 10.015508
## 1960 61621.020 Germany Mumbai Air 13.195102 12.793306
## 1961 69651.296 China Kandla Land 5.605101 11.227160
## 1962 97537.542 Japan Delhi Land 6.678358 12.126509
## 1963 48729.409 Germany Kandla Air 17.528675 13.990345
## 1964 41210.597 USA Kolkata Land 18.370700 14.895237
## 1965 88388.493 Japan Mumbai Sea 5.181776 8.055113
## 1966 25935.345 UAE Chennai Air 11.430912 14.549531
## 1967 30075.732 USA Mumbai Land 14.354033 15.136355
## 1968 84083.928 China Kandla Sea 13.898465 7.123457
## 1969 64635.300 USA Chennai Land 17.595169 7.175260
## 1970 21851.564 UAE Mumbai Land 5.922231 5.019197
## 1971 3391.004 UAE Kolkata Land 16.985562 12.718395
## 1972 92953.210 Germany Chennai Land 6.424502 6.561940
## 1973 17255.098 China Delhi Air 16.805019 12.280861
## 1974 78089.987 China Kolkata Land 18.374699 8.331861
## 1975 31370.418 USA Delhi Air 7.868855 13.704265
## 1976 44277.665 USA Mumbai Land 17.097939 7.036929
## 1977 87284.571 USA Delhi Sea 5.382448 8.506041
## 1978 70377.221 China Chennai Land 13.692879 10.622879
## 1979 27497.586 UK Chennai Air 8.618227 9.477861
## 1980 97161.838 Japan Kolkata Air 10.713367 14.963586
## 1981 12518.355 China Chennai Air 13.133844 16.435623
## 1982 68611.904 Germany Kandla Sea 13.274480 14.794955
## 1983 20944.256 Japan Chennai Air 10.145990 6.827826
## 1984 37239.209 Japan Kolkata Sea 6.897755 13.203820
## 1985 50118.451 UAE Kandla Air 10.366170 15.784960
## 1986 39439.322 Germany Chennai Air 16.392224 17.278184
## 1987 63851.721 UK Kandla Air 14.492769 6.305784
## 1988 26235.450 UK Kolkata Air 19.700672 12.808484
## 1989 61178.002 Germany Chennai Land 11.290644 6.224843
## 1990 61934.309 UK Delhi Air 16.501741 9.421585
## 1991 66008.794 USA Kolkata Sea 7.999367 13.173091
## 1992 89730.676 UK Chennai Sea 19.266682 9.699210
## 1993 67444.542 UK Kolkata Air 8.171012 16.695872
## 1994 57010.093 Japan Kandla Air 11.248843 12.793003
## 1995 40153.870 Germany Chennai Sea 19.234824 5.550896
## 1996 10157.967 UK Delhi Air 16.403471 11.794900
## 1997 27327.928 Japan Chennai Air 12.141705 5.827507
## 1998 89208.216 Germany Delhi Sea 17.650933 9.715322
## 1999 5835.837 USA Delhi Air 15.534879 11.751223
## 2000 90062.629 China Kandla Sea 7.301488 8.256858
## 2001 67859.120 UAE Mumbai Land 17.868766 11.937550
## 2002 64827.564 UAE Delhi Land 9.268341 8.975295
## 2003 85738.578 UAE Kolkata Air 17.089705 14.458680
## 2004 79725.534 China Chennai Land 7.361256 5.811229
## 2005 93081.550 UAE Delhi Sea 18.704946 12.025304
## 2006 61425.027 Germany Kandla Sea 12.718671 6.874221
## 2007 11179.185 USA Mumbai Air 17.572979 6.058186
## 2008 57914.162 UAE Kandla Sea 9.727909 13.084152
## 2009 40328.467 UK Delhi Air 18.700830 13.813253
## 2010 65624.302 UK Kolkata Land 7.081911 14.576194
## 2011 61666.263 UK Chennai Air 19.138385 12.779666
## 2012 2505.169 Germany Mumbai Air 16.203280 13.344680
## 2013 68631.638 UK Kolkata Land 6.552661 17.538310
## 2014 91844.203 Japan Kolkata Air 8.210763 16.274653
## 2015 36163.948 Germany Delhi Air 11.633219 7.322773
## 2016 73027.244 China Delhi Air 9.685349 14.374097
## 2017 98231.481 Germany Kandla Air 11.033290 11.101816
## 2018 41853.754 China Kandla Land 11.982389 11.884448
## 2019 33436.389 Germany Kandla Sea 10.097880 9.674437
## 2020 23608.945 USA Delhi Air 8.336725 16.103920
## 2021 56281.099 UAE Chennai Sea 13.690193 10.505936
## 2022 15387.919 Japan Delhi Land 14.281236 17.265557
## 2023 90443.220 UAE Delhi Land 6.984544 14.839930
## 2024 50414.727 UK Kolkata Land 14.235086 8.176807
## 2025 26309.712 Germany Mumbai Land 18.366754 13.408936
## 2026 45271.242 China Kandla Land 15.915753 12.492279
## 2027 70751.953 UK Chennai Land 7.015047 11.067943
## 2028 62305.383 UK Kandla Land 13.281567 12.527318
## 2029 72756.787 Germany Delhi Air 10.715387 15.510457
## 2030 69874.753 USA Kandla Sea 11.388089 11.089941
## 2031 63417.185 UK Delhi Air 11.370291 8.607053
## 2032 77144.742 Germany Kolkata Sea 10.376854 12.884258
## 2033 63405.040 UAE Kandla Sea 7.505193 15.250034
## 2034 49912.162 UAE Mumbai Sea 13.952832 5.062257
## 2035 27972.440 Germany Delhi Air 6.885860 14.200574
## 2036 77329.303 China Chennai Air 12.663992 7.738985
## 2037 86786.762 USA Kolkata Land 14.300182 11.735211
## 2038 43588.255 China Delhi Sea 12.592470 14.821014
## 2039 82355.995 China Mumbai Land 7.297119 10.764627
## 2040 53661.196 China Chennai Land 17.413620 6.548117
## 2041 52731.087 China Delhi Sea 13.283935 5.107998
## 2042 6981.098 Japan Chennai Land 17.568891 14.569686
## 2043 34245.066 UAE Kolkata Land 16.335746 8.116012
## 2044 63357.528 UAE Mumbai Land 5.974920 15.868156
## 2045 86782.338 China Kolkata Air 9.837476 17.676624
## 2046 16558.682 USA Mumbai Air 12.504144 10.374710
## 2047 82157.615 UK Kandla Land 13.762466 16.403437
## 2048 86003.129 Japan Kandla Air 5.882946 15.776448
## 2049 87602.074 China Kandla Land 13.939435 16.080762
## 2050 75886.633 China Kandla Air 10.335593 17.082334
## 2051 36332.096 UAE Delhi Air 12.684832 17.981513
## 2052 25278.316 USA Chennai Sea 17.421425 10.241123
## 2053 61519.905 UAE Kandla Land 5.321943 6.651466
## 2054 2177.945 UK Mumbai Air 8.249748 5.861785
## 2055 64851.980 UK Kandla Sea 8.980834 12.390932
## 2056 37306.909 UK Kandla Sea 6.469679 12.855399
## 2057 51457.486 Germany Kolkata Air 6.256961 6.195791
## 2058 37278.618 Japan Kolkata Sea 17.495971 15.469354
## 2059 91259.286 China Mumbai Air 13.880350 7.880013
## 2060 11316.197 Japan Delhi Land 15.500977 15.082978
## 2061 60857.506 USA Delhi Land 5.707209 16.658254
## 2062 35291.723 UK Kolkata Sea 13.791119 12.619016
## 2063 80788.690 UAE Kandla Sea 16.664805 15.263605
## 2064 74914.789 UAE Delhi Land 18.094656 17.723895
## 2065 58594.412 USA Delhi Sea 18.678335 10.474910
## 2066 74829.251 Germany Kolkata Land 11.948299 12.161460
## 2067 5087.769 Germany Chennai Land 11.511937 6.717240
## 2068 77200.573 UAE Kolkata Sea 11.049100 15.585021
## 2069 78418.201 Germany Chennai Sea 14.075352 5.883681
## 2070 97452.557 Japan Mumbai Land 5.801528 13.251758
## 2071 58938.558 Japan Kolkata Land 5.972076 10.014538
## 2072 9767.587 Japan Chennai Land 10.659926 11.137832
## 2073 29042.213 UAE Kandla Sea 11.442856 16.258943
## 2074 67594.427 Germany Delhi Air 6.009317 10.032519
## 2075 32325.066 Germany Mumbai Sea 12.163414 11.589120
## 2076 61875.685 Japan Mumbai Land 10.330912 9.897248
## 2077 68771.423 Germany Delhi Sea 5.772362 14.424469
## 2078 23012.133 UAE Kolkata Sea 10.656150 16.448806
## 2079 36076.084 UK Kolkata Land 7.812080 8.741807
## 2080 37011.301 UK Delhi Air 12.788234 16.315089
## 2081 39178.695 UK Chennai Sea 9.219488 5.113699
## 2082 88734.007 Japan Kolkata Sea 10.040614 17.309286
## 2083 82980.235 USA Chennai Land 10.983475 14.220044
## 2084 94073.691 UK Kolkata Sea 12.682994 12.032697
## 2085 76937.607 UAE Kandla Sea 18.244068 17.661248
## 2086 27928.589 Germany Mumbai Air 13.423839 16.914444
## 2087 82823.601 UAE Kandla Air 5.599582 14.523172
## 2088 14097.340 Japan Kolkata Air 18.240454 9.293040
## 2089 31924.225 UAE Delhi Land 15.645843 13.172010
## 2090 22026.970 UK Mumbai Land 13.820529 9.169422
## 2091 19036.998 USA Kolkata Sea 12.278332 16.615352
## 2092 29265.886 Germany Kolkata Air 10.817847 15.683875
## 2093 30103.025 Germany Kolkata Air 16.868410 5.655192
## 2094 99393.526 UK Kandla Air 8.749076 17.564844
## 2095 45777.076 China Chennai Sea 19.156535 8.364754
## 2096 65147.221 China Kolkata Sea 13.533418 15.157813
## 2097 23347.493 Japan Kandla Land 13.164648 15.395652
## 2098 57749.488 UAE Mumbai Sea 17.055193 10.902803
## 2099 73733.484 China Kandla Sea 17.418974 8.237292
## 2100 80124.966 UAE Mumbai Sea 9.644395 17.123458
## 2101 63430.174 USA Mumbai Sea 16.537273 6.856126
## 2102 13279.934 Germany Delhi Sea 16.355758 11.911408
## 2103 86682.949 USA Mumbai Air 13.737623 8.758310
## 2104 92814.446 UAE Kolkata Sea 8.218962 11.044221
## 2105 8547.750 China Kandla Air 7.705210 14.315991
## 2106 56278.002 Japan Chennai Land 11.801118 16.071838
## 2107 45800.031 Japan Kolkata Land 10.941844 5.759564
## 2108 34765.645 Japan Mumbai Land 19.994470 10.259703
## 2109 89431.059 Germany Kandla Sea 10.340920 5.174202
## 2110 35919.409 China Kolkata Sea 18.295460 16.333193
## 2111 29582.871 UAE Kolkata Air 13.638244 9.436983
## 2112 59816.214 UAE Kolkata Sea 15.088853 7.850439
## 2113 99906.036 China Kolkata Air 17.238732 16.131899
## 2114 65943.373 UAE Chennai Air 18.790495 15.668302
## 2115 5972.373 USA Kandla Sea 17.643498 15.334917
## 2116 7715.258 Germany Kandla Sea 19.440519 13.186326
## 2117 89260.176 UAE Kandla Land 16.774083 7.911924
## 2118 74920.967 USA Chennai Air 9.368986 11.152686
## 2119 31630.220 Germany Delhi Land 12.495230 5.972705
## 2120 73190.877 Germany Chennai Land 10.129947 5.458495
## 2121 36879.603 UAE Kandla Land 16.150325 10.015756
## 2122 27525.040 Germany Mumbai Land 12.793974 15.326684
## 2123 37241.505 Germany Kandla Sea 13.947118 17.815082
## 2124 86188.423 China Mumbai Land 16.792508 17.686959
## 2125 5401.058 Japan Kandla Land 6.889359 9.382359
## 2126 37935.200 UAE Delhi Air 8.292971 10.854559
## 2127 14829.308 Germany Delhi Sea 8.740866 17.176213
## 2128 74199.359 UK Kandla Land 10.104819 16.691587
## 2129 39767.446 UK Chennai Sea 7.262633 10.047125
## 2130 30824.981 China Kolkata Air 5.936050 10.283094
## 2131 32461.103 China Chennai Sea 16.793974 6.959486
## 2132 34664.697 Japan Chennai Sea 13.089745 7.568536
## 2133 70827.973 Japan Kandla Sea 10.855208 8.946342
## 2134 33819.812 Japan Kandla Land 8.657992 16.398813
## 2135 77756.612 Germany Chennai Land 17.441227 8.516128
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## 2489 73335.792 UK Kandla Land 15.118935 9.427551
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## 2494 13087.605 USA Chennai Air 14.188466 15.588356
## 2495 21391.763 Japan Mumbai Air 7.688699 15.264728
## 2496 73921.298 Japan Kolkata Sea 16.902714 12.608899
## 2497 94912.792 USA Kolkata Land 10.485186 9.676441
## 2498 8948.989 China Chennai Sea 10.381797 13.000610
## 2499 65769.369 Germany Kandla Land 13.704801 8.886004
## Exchange_Rate Shipment_Days Delivery_Status Trade_Agreement Date
## 1 81.32515 1.0000 On Time FTA 14-03-2020
## 2 70.68105 1.0000 On Time Non-FTA 23-02-2021
## 3 83.02403 1.0000 On Time FTA 13-07-2019
## 4 70.58662 1.0000 On Time Non-FTA 21-10-2024
## 5 72.37191 1.0000 Delayed Non-FTA 03-12-2021
## 6 71.08928 1.0000 Delayed FTA 07-05-2021
## 7 82.83220 1.0000 On Time Non-FTA 16-12-2020
## 8 75.58205 1.0000 Delayed FTA 29-11-2024
## 9 81.88210 1.0000 Delayed FTA 03-09-2019
## 10 83.58600 1.0000 Delayed Non-FTA 19-12-2021
## 11 81.72460 1.0000 Delayed FTA 11-10-2022
## 12 75.48632 1.0000 Delayed Non-FTA 06-01-2018
## 13 72.81812 1.0000 On Time FTA 22-08-2023
## 14 77.69373 1.0000 On Time FTA 21-04-2019
## 15 81.94828 1.0000 Delayed Non-FTA 30-11-2018
## 16 72.85250 1.0000 On Time Non-FTA 04-02-2023
## 17 71.39977 1.0000 Delayed FTA 17-02-2023
## 18 79.30628 1.0000 On Time FTA 05-10-2019
## 19 70.12786 1.0000 On Time Non-FTA 28-11-2019
## 20 70.74068 1.0000 Delayed FTA 10-07-2020
## 21 71.19598 1.0000 On Time Non-FTA 10-09-2018
## 22 76.81986 1.0000 Delayed FTA 30-06-2018
## 23 79.04102 1.0000 Delayed Non-FTA 24-12-2021
## 24 76.56776 1.0000 Delayed Non-FTA 14-05-2020
## 25 84.50640 1.0000 Delayed Non-FTA 18-06-2021
## 26 73.96513 1.0000 Delayed FTA 04-10-2019
## 27 75.91424 1.0000 Delayed Non-FTA 23-01-2021
## 28 84.51308 1.0000 On Time FTA 04-07-2024
## 29 84.12713 1.0000 Delayed Non-FTA 04-07-2018
## 30 82.45508 1.0000 Delayed Non-FTA 22-03-2021
## 31 79.39084 1.0000 On Time Non-FTA 29-12-2020
## 32 73.68143 1.0000 On Time FTA 01-12-2021
## 33 81.14333 1.0000 On Time FTA 11-04-2022
## 34 76.02757 1.0000 On Time FTA 07-01-2018
## 35 82.28625 1.0000 On Time Non-FTA 04-07-2018
## 36 70.13933 1.0000 Delayed FTA 06-10-2022
## 37 78.92824 1.0000 Delayed FTA 02-12-2019
## 38 75.18387 1.0000 Delayed FTA 30-03-2021
## 39 79.15820 1.0000 On Time Non-FTA 07-03-2023
## 40 72.20139 1.0000 Delayed FTA 23-02-2024
## 41 78.88341 1.0000 Delayed Non-FTA 10-05-2024
## 42 83.58237 1.0000 Delayed FTA 07-11-2024
## 43 73.25491 1.0000 Delayed Non-FTA 20-02-2020
## 44 76.14796 1.0000 On Time FTA 28-06-2018
## 45 80.32026 1.0000 On Time FTA 09-12-2024
## 46 70.77701 1.0000 On Time Non-FTA 22-08-2021
## 47 75.47380 1.0000 On Time Non-FTA 13-04-2024
## 48 72.01048 1.0000 Delayed Non-FTA 30-11-2019
## 49 84.91855 1.0000 Delayed Non-FTA 29-09-2024
## 50 84.23122 1.0000 Delayed Non-FTA 03-06-2021
## 51 75.60942 1.0000 On Time Non-FTA 17-01-2018
## 52 82.08742 1.0000 On Time FTA 26-03-2022
## 53 80.85725 1.0000 Delayed FTA 16-11-2020
## 54 83.02682 1.0000 On Time FTA 01-02-2023
## 55 82.13091 1.0000 Delayed Non-FTA 05-10-2019
## 56 70.32052 1.0000 Delayed FTA 28-07-2018
## 57 73.78652 1.0000 Delayed Non-FTA 21-09-2021
## 58 72.65940 1.0000 On Time Non-FTA 11-02-2021
## 59 73.19293 1.0000 On Time FTA 10-01-2024
## 60 75.55298 1.0000 On Time Non-FTA 23-08-2018
## 61 81.13960 1.0000 Delayed FTA 13-10-2022
## 62 78.41691 1.0000 On Time FTA 26-01-2022
## 63 77.96169 1.0000 Delayed Non-FTA 06-09-2020
## 64 81.22579 1.0000 Delayed Non-FTA 17-08-2021
## 65 80.93548 1.0000 Delayed FTA 03-07-2020
## 66 71.31974 1.0000 Delayed FTA 29-11-2022
## 67 70.57775 1.0000 Delayed FTA 02-03-2020
## 68 81.70028 1.0000 On Time Non-FTA 08-08-2022
## 69 84.81190 1.0000 On Time Non-FTA 06-01-2024
## 70 73.14655 1.0000 Delayed FTA 21-10-2021
## 71 80.08861 1.0000 Delayed Non-FTA 11-04-2023
## 72 73.23034 1.0000 Delayed Non-FTA 03-04-2022
## 73 74.56019 1.0000 On Time Non-FTA 18-09-2022
## 74 72.16734 1.0000 On Time Non-FTA 10-12-2021
## 75 82.97632 1.0000 On Time FTA 24-09-2019
## 76 79.29480 1.0000 On Time Non-FTA 21-06-2019
## 77 73.38532 1.0000 Delayed FTA 05-03-2020
## 78 82.49825 1.0000 On Time FTA 23-05-2018
## 79 84.62445 1.0000 Delayed Non-FTA 15-01-2022
## 80 77.88014 1.0000 Delayed Non-FTA 01-07-2019
## 81 70.79233 1.0000 On Time FTA 24-12-2020
## 82 74.45270 1.0000 Delayed Non-FTA 01-08-2021
## 83 72.10645 1.0000 Delayed Non-FTA 05-12-2022
## 84 80.14985 1.0000 Delayed Non-FTA 20-02-2021
## 85 72.31698 1.0000 Delayed FTA 27-05-2024
## 86 75.22638 1.0000 On Time FTA 18-03-2020
## 87 84.86654 1.0000 Delayed Non-FTA 06-10-2024
## 88 74.78748 1.0000 On Time FTA 23-11-2023
## 89 71.39071 1.0000 Delayed FTA 02-06-2023
## 90 79.82821 1.0000 On Time FTA 25-11-2018
## 91 75.58179 2.0000 On Time Non-FTA 28-08-2023
## 92 83.67727 2.0000 On Time Non-FTA 23-02-2018
## 93 74.63764 2.0000 On Time Non-FTA 16-11-2020
## 94 77.89366 2.0000 On Time FTA 17-08-2021
## 95 77.78807 2.0000 On Time Non-FTA 17-11-2022
## 96 79.72678 2.0000 On Time FTA 31-03-2023
## 97 71.61771 2.0000 Delayed FTA 23-01-2020
## 98 82.31814 2.0000 On Time Non-FTA 21-09-2024
## 99 73.56040 2.0000 Delayed FTA 23-10-2023
## 100 80.24255 2.0000 Delayed Non-FTA 15-10-2022
## 101 70.05702 2.0000 Delayed Non-FTA 26-03-2022
## 102 81.41677 2.0000 On Time FTA 12-12-2022
## 103 81.99843 2.0000 On Time Non-FTA 26-05-2018
## 104 81.86577 2.0000 Delayed FTA 07-06-2020
## 105 81.52961 2.0000 On Time FTA 01-02-2018
## 106 79.06875 2.0000 Delayed Non-FTA 25-01-2022
## 107 82.41872 2.0000 On Time Non-FTA 30-07-2018
## 108 76.16048 2.0000 Delayed FTA 23-12-2022
## 109 81.49437 2.0000 On Time FTA 18-05-2023
## 110 77.09915 2.0000 Delayed Non-FTA 26-05-2023
## 111 73.10037 2.0000 On Time Non-FTA 01-04-2020
## 112 70.79832 2.0000 On Time FTA 14-02-2022
## 113 79.25624 2.0000 On Time FTA 30-01-2023
## 114 82.27730 2.0000 Delayed FTA 22-03-2018
## 115 71.22606 2.0000 Delayed Non-FTA 01-04-2019
## 116 77.34390 2.0000 On Time FTA 02-02-2023
## 117 81.85571 2.0000 On Time Non-FTA 10-08-2022
## 118 71.70225 2.0000 On Time Non-FTA 11-12-2020
## 119 72.38635 2.0000 On Time Non-FTA 28-08-2023
## 120 81.61655 2.0000 Delayed Non-FTA 08-09-2019
## 121 78.24548 2.0000 Delayed FTA 15-06-2022
## 122 83.50615 2.0000 Delayed Non-FTA 16-11-2018
## 123 82.71335 2.0000 On Time FTA 08-05-2018
## 124 76.51725 2.0000 Delayed FTA 22-10-2022
## 125 80.96483 2.0000 On Time Non-FTA 29-01-2018
## 126 73.39363 2.0000 Delayed FTA 16-05-2018
## 127 79.54828 2.0000 Delayed FTA 17-12-2024
## 128 71.13467 2.0000 Delayed FTA 08-09-2020
## 129 79.51998 2.0000 On Time FTA 14-06-2018
## 130 70.14162 2.0000 Delayed Non-FTA 20-07-2023
## 131 79.27590 2.0000 Delayed FTA 09-12-2023
## 132 83.38092 2.0000 Delayed FTA 28-06-2021
## 133 70.64931 2.0000 On Time Non-FTA 17-04-2019
## 134 72.47679 2.0000 Delayed FTA 04-06-2021
## 135 77.35545 2.0000 Delayed Non-FTA 04-01-2018
## 136 76.58877 2.0000 Delayed Non-FTA 06-04-2024
## 137 83.36483 2.0000 Delayed FTA 06-04-2021
## 138 72.37436 2.0000 Delayed FTA 12-11-2019
## 139 78.04706 2.0000 Delayed Non-FTA 15-11-2019
## 140 72.22255 2.0000 On Time FTA 14-10-2023
## 141 73.54805 2.0000 Delayed Non-FTA 25-06-2019
## 142 70.68302 2.0000 Delayed Non-FTA 14-11-2023
## 143 82.08577 2.0000 Delayed Non-FTA 01-06-2020
## 144 76.16723 2.0000 On Time Non-FTA 19-09-2019
## 145 83.37360 2.0000 On Time FTA 02-10-2019
## 146 81.70077 2.0000 On Time Non-FTA 12-02-2024
## 147 78.34160 2.0000 Delayed FTA 02-06-2020
## 148 70.77977 2.0000 Delayed Non-FTA 26-10-2021
## 149 70.68675 2.0000 Delayed Non-FTA 06-12-2023
## 150 73.16290 2.0000 On Time FTA 23-11-2021
## 151 76.16168 2.0000 Delayed FTA 24-06-2023
## 152 76.80941 2.0000 Delayed FTA 11-08-2018
## 153 72.47115 2.0000 On Time FTA 16-11-2021
## 154 72.82070 2.0000 Delayed Non-FTA 09-11-2021
## 155 80.60586 2.0000 On Time Non-FTA 16-04-2023
## 156 73.23950 2.0000 On Time FTA 06-04-2021
## 157 74.95125 2.0000 On Time FTA 12-04-2018
## 158 77.57350 2.0000 Delayed Non-FTA 05-02-2023
## 159 71.23766 2.0000 Delayed FTA 05-09-2018
## 160 80.23452 2.0000 On Time FTA 17-02-2024
## 161 78.32531 2.0000 Delayed Non-FTA 08-08-2018
## 162 81.09731 2.0000 On Time FTA 04-05-2024
## 163 79.74600 2.0000 Delayed FTA 10-10-2019
## 164 74.17125 2.0000 On Time Non-FTA 03-06-2023
## 165 76.59206 2.0000 Delayed FTA 13-02-2018
## 166 81.95896 2.0000 On Time FTA 07-02-2021
## 167 76.89972 2.0000 Delayed Non-FTA 27-07-2023
## 168 79.26398 2.0000 Delayed Non-FTA 26-04-2023
## 169 77.55237 2.0000 On Time Non-FTA 26-02-2020
## 170 78.03263 2.0000 Delayed Non-FTA 22-11-2020
## 171 82.70260 2.0000 On Time Non-FTA 03-12-2020
## 172 74.25984 2.0000 On Time FTA 21-11-2020
## 173 70.52274 2.0000 Delayed Non-FTA 22-12-2018
## 174 81.55942 2.0000 Delayed FTA 10-08-2020
## 175 81.61318 2.0000 On Time FTA 30-01-2020
## 176 75.20322 2.0000 On Time Non-FTA 30-06-2020
## 177 74.74089 2.0000 On Time FTA 04-09-2020
## 178 75.11299 2.0000 On Time FTA 02-07-2021
## 179 75.27279 2.0000 Delayed Non-FTA 04-02-2022
## 180 70.60749 2.0000 On Time FTA 01-07-2018
## 181 78.04437 2.0000 On Time Non-FTA 27-03-2020
## 182 75.43178 3.0000 Delayed Non-FTA 23-06-2024
## 183 70.46183 3.0000 On Time FTA 07-07-2019
## 184 76.83731 3.0000 On Time FTA 28-02-2019
## 185 78.81282 3.0000 On Time Non-FTA 23-01-2020
## 186 71.04652 3.0000 Delayed FTA 25-01-2020
## 187 71.63719 3.0000 Delayed Non-FTA 06-08-2022
## 188 70.95353 3.0000 Delayed Non-FTA 19-12-2021
## 189 72.14083 3.0000 On Time FTA 22-08-2019
## 190 83.06397 3.0000 Delayed Non-FTA 02-07-2020
## 191 72.52544 3.0000 On Time Non-FTA 22-04-2022
## 192 73.13156 3.0000 On Time FTA 07-03-2018
## 193 72.96994 3.0000 Delayed Non-FTA 06-07-2018
## 194 72.37742 3.0000 Delayed Non-FTA 14-10-2019
## 195 76.43851 3.0000 On Time Non-FTA 08-05-2021
## 196 72.51387 3.0000 On Time Non-FTA 20-12-2020
## 197 75.89992 3.0000 On Time FTA 24-04-2021
## 198 82.14716 3.0000 On Time Non-FTA 17-06-2022
## 199 74.06608 3.0000 Delayed FTA 14-02-2020
## 200 81.50889 3.0000 On Time FTA 09-04-2023
## 201 84.38179 3.0000 On Time Non-FTA 26-07-2019
## 202 76.33509 3.0000 Delayed FTA 15-07-2022
## 203 72.15176 3.0000 On Time Non-FTA 26-03-2020
## 204 80.82348 3.0000 Delayed FTA 14-07-2023
## 205 72.94055 3.0000 On Time Non-FTA 19-08-2018
## 206 80.61125 3.0000 Delayed Non-FTA 21-01-2024
## 207 74.92454 3.0000 Delayed FTA 22-11-2022
## 208 78.42621 3.0000 Delayed Non-FTA 22-06-2024
## 209 83.61303 3.0000 Delayed FTA 24-11-2022
## 210 81.16730 3.0000 Delayed FTA 12-02-2018
## 211 83.00632 3.0000 On Time FTA 20-05-2020
## 212 74.68865 3.0000 Delayed FTA 23-01-2019
## 213 71.12971 3.0000 On Time Non-FTA 09-08-2021
## 214 77.04400 3.0000 On Time FTA 11-03-2018
## 215 75.44987 3.0000 On Time FTA 05-09-2022
## 216 79.89008 3.0000 Delayed Non-FTA 25-06-2019
## 217 71.54899 3.0000 On Time Non-FTA 23-06-2022
## 218 70.70991 3.0000 On Time Non-FTA 07-05-2018
## 219 71.67746 3.0000 On Time Non-FTA 11-03-2019
## 220 70.75443 3.0000 On Time FTA 20-03-2022
## 221 84.14322 3.0000 On Time Non-FTA 04-01-2022
## 222 72.93081 3.0000 Delayed Non-FTA 14-09-2022
## 223 78.06002 3.0000 On Time Non-FTA 29-08-2021
## 224 84.73087 3.0000 On Time Non-FTA 24-07-2023
## 225 72.95485 3.0000 Delayed FTA 02-10-2023
## 226 81.25762 3.0000 On Time Non-FTA 23-06-2019
## 227 74.21384 3.0000 On Time Non-FTA 22-05-2023
## 228 77.09086 3.0000 On Time Non-FTA 14-04-2019
## 229 80.13517 3.0000 On Time Non-FTA 04-04-2018
## 230 84.85721 3.0000 On Time FTA 25-04-2020
## 231 81.45479 3.0000 Delayed FTA 04-04-2020
## 232 77.76162 3.0000 Delayed FTA 30-08-2021
## 233 73.97229 3.0000 Delayed Non-FTA 05-05-2024
## 234 80.84722 3.0000 Delayed FTA 09-05-2020
## 235 71.13979 3.0000 On Time FTA 31-10-2020
## 236 72.02978 3.0000 On Time Non-FTA 17-05-2019
## 237 78.56177 3.0000 On Time Non-FTA 21-11-2020
## 238 81.84513 3.0000 Delayed Non-FTA 20-01-2022
## 239 70.09602 3.0000 On Time FTA 17-11-2019
## 240 80.14552 3.0000 On Time Non-FTA 11-03-2019
## 241 84.05911 3.0000 Delayed Non-FTA 11-02-2020
## 242 75.61597 3.0000 On Time Non-FTA 17-05-2021
## 243 70.29471 3.0000 Delayed Non-FTA 06-08-2020
## 244 79.29659 3.0000 Delayed Non-FTA 22-10-2019
## 245 78.60159 3.0000 On Time Non-FTA 13-06-2023
## 246 82.48465 3.0000 On Time FTA 11-02-2024
## 247 78.77290 3.0000 On Time Non-FTA 11-05-2020
## 248 70.96018 3.0000 Delayed Non-FTA 04-11-2024
## 249 70.64998 3.0000 Delayed FTA 19-10-2018
## 250 71.19974 3.0000 Delayed Non-FTA 16-04-2021
## 251 78.33844 3.0000 Delayed Non-FTA 24-02-2019
## 252 82.04015 3.0000 Delayed FTA 30-06-2024
## 253 81.30729 3.0000 On Time Non-FTA 22-05-2020
## 254 71.43563 3.0000 On Time FTA 30-12-2024
## 255 83.91134 3.0000 Delayed FTA 22-06-2021
## 256 79.46925 3.0000 Delayed Non-FTA 14-11-2022
## 257 79.22675 3.0000 On Time Non-FTA 28-08-2024
## 258 71.15068 3.0000 On Time FTA 18-05-2020
## 259 75.13337 3.0000 On Time Non-FTA 11-09-2021
## 260 70.06428 3.0000 Delayed FTA 08-04-2023
## 261 77.60639 3.0000 On Time Non-FTA 29-10-2024
## 262 78.37142 3.0000 Delayed Non-FTA 08-04-2022
## 263 79.17901 3.0000 Delayed Non-FTA 08-12-2023
## 264 71.07811 3.0000 On Time Non-FTA 05-10-2024
## 265 74.84657 3.0000 On Time Non-FTA 26-05-2023
## 266 81.21734 3.0000 On Time Non-FTA 11-04-2021
## 267 83.42891 3.0000 Delayed Non-FTA 12-06-2018
## 268 76.75225 3.0000 On Time FTA 07-03-2018
## 269 76.16214 4.0000 Delayed FTA 24-02-2022
## 270 81.14798 4.0000 Delayed Non-FTA 03-07-2019
## 271 74.65962 4.0000 On Time FTA 27-06-2021
## 272 75.83731 4.0000 On Time FTA 12-06-2024
## 273 70.69809 4.0000 On Time FTA 23-11-2024
## 274 74.91549 4.0000 On Time Non-FTA 08-11-2018
## 275 82.02371 4.0000 On Time FTA 13-06-2019
## 276 79.47696 4.0000 Delayed Non-FTA 22-08-2024
## 277 84.14099 4.0000 On Time FTA 11-04-2022
## 278 83.56395 4.0000 On Time FTA 25-04-2019
## 279 81.86068 4.0000 Delayed Non-FTA 31-05-2024
## 280 77.05265 4.0000 Delayed FTA 05-09-2020
## 281 83.95197 4.0000 On Time FTA 10-01-2022
## 282 72.89800 4.0000 On Time Non-FTA 02-07-2021
## 283 76.03369 4.0000 Delayed Non-FTA 25-11-2020
## 284 84.64069 4.0000 On Time FTA 11-02-2022
## 285 83.62278 4.0000 On Time Non-FTA 30-03-2022
## 286 80.88144 4.0000 On Time FTA 03-04-2023
## 287 74.95875 4.0000 On Time FTA 31-05-2020
## 288 76.07666 4.0000 On Time Non-FTA 13-07-2018
## 289 72.31654 4.0000 Delayed FTA 06-11-2018
## 290 76.58375 4.0000 Delayed Non-FTA 05-03-2022
## 291 73.29074 4.0000 Delayed Non-FTA 22-05-2023
## 292 72.10951 4.0000 Delayed Non-FTA 28-07-2020
## 293 73.33052 4.0000 On Time Non-FTA 12-02-2021
## 294 81.08347 4.0000 On Time Non-FTA 17-11-2022
## 295 75.88925 4.0000 Delayed FTA 06-01-2022
## 296 71.50828 4.0000 Delayed Non-FTA 16-07-2020
## 297 82.75379 4.0000 On Time FTA 04-01-2022
## 298 78.50534 4.0000 Delayed FTA 11-08-2020
## 299 84.08990 4.0000 Delayed Non-FTA 07-03-2024
## 300 83.77357 4.0000 Delayed Non-FTA 08-07-2021
## 301 73.12001 4.0000 On Time Non-FTA 01-12-2022
## 302 72.72550 4.0000 Delayed FTA 04-09-2020
## 303 71.28048 4.0000 Delayed Non-FTA 26-02-2024
## 304 72.82719 4.0000 On Time Non-FTA 14-07-2021
## 305 82.51818 4.0000 Delayed Non-FTA 14-11-2020
## 306 79.01651 4.0000 Delayed Non-FTA 17-01-2022
## 307 80.99234 4.0000 Delayed FTA 26-12-2023
## 308 75.29718 4.0000 On Time FTA 09-01-2021
## 309 72.88753 4.0000 On Time Non-FTA 02-03-2019
## 310 72.78017 4.0000 Delayed FTA 14-03-2021
## 311 75.30617 4.0000 Delayed FTA 10-08-2021
## 312 79.90268 4.0000 On Time Non-FTA 10-02-2022
## 313 70.32405 4.0000 Delayed FTA 30-04-2018
## 314 75.04720 4.0000 On Time Non-FTA 19-11-2020
## 315 74.71223 4.0000 On Time Non-FTA 27-10-2020
## 316 79.32824 4.0000 On Time Non-FTA 20-05-2024
## 317 82.22376 4.0000 On Time FTA 09-06-2023
## 318 75.64785 4.0000 Delayed FTA 05-08-2024
## 319 73.60884 4.0000 On Time FTA 29-07-2018
## 320 82.26035 4.0000 Delayed FTA 18-11-2021
## 321 78.27693 4.0000 Delayed Non-FTA 10-03-2022
## 322 81.16557 4.0000 On Time Non-FTA 31-03-2024
## 323 83.13586 4.0000 Delayed FTA 16-07-2022
## 324 84.23356 4.0000 On Time FTA 12-02-2021
## 325 82.33195 4.0000 Delayed Non-FTA 01-08-2018
## 326 75.70138 4.0000 Delayed FTA 26-12-2018
## 327 74.12061 4.0000 On Time Non-FTA 11-03-2021
## 328 74.78145 4.0000 Delayed FTA 29-09-2019
## 329 76.22759 4.0000 Delayed FTA 16-06-2021
## 330 74.92527 4.0000 Delayed FTA 24-10-2022
## 331 72.42172 4.0000 On Time Non-FTA 27-10-2021
## 332 73.28132 4.0000 On Time Non-FTA 20-07-2022
## 333 74.33876 4.0000 On Time Non-FTA 18-01-2022
## 334 82.62491 4.0000 On Time Non-FTA 06-09-2024
## 335 83.49780 4.0000 On Time Non-FTA 26-07-2019
## 336 84.94083 4.0000 Delayed FTA 22-12-2019
## 337 82.82753 4.0000 On Time Non-FTA 18-05-2020
## 338 75.83898 4.0000 Delayed Non-FTA 16-09-2021
## 339 82.61684 4.0000 Delayed FTA 23-11-2018
## 340 82.09337 4.0000 On Time Non-FTA 11-01-2020
## 341 83.50826 4.0000 Delayed FTA 07-10-2024
## 342 71.06085 4.0000 On Time FTA 06-05-2019
## 343 72.25230 4.0000 On Time FTA 07-02-2019
## 344 75.64720 4.0000 On Time FTA 01-06-2022
## 345 77.47799 4.0000 Delayed FTA 30-11-2020
## 346 77.48357 4.0000 On Time Non-FTA 25-12-2023
## 347 72.64241 4.0000 Delayed Non-FTA 07-01-2019
## 348 70.99586 4.0000 Delayed Non-FTA 27-07-2021
## 349 83.49094 4.0000 Delayed FTA 05-03-2022
## 350 76.14991 4.0000 On Time FTA 17-12-2019
## 351 84.02764 4.0000 Delayed FTA 21-05-2018
## 352 79.91441 4.0000 Delayed FTA 07-05-2019
## 353 80.54187 4.0000 On Time Non-FTA 02-05-2024
## 354 74.22494 4.0000 Delayed Non-FTA 20-06-2023
## 355 76.28153 4.0000 On Time FTA 18-04-2022
## 356 81.94075 4.0000 On Time FTA 12-08-2023
## 357 84.24300 4.0000 On Time FTA 06-05-2020
## 358 84.46890 4.0000 Delayed Non-FTA 04-08-2018
## 359 82.21039 4.0000 On Time Non-FTA 20-07-2022
## 360 80.41649 4.0000 Delayed Non-FTA 22-03-2020
## 361 72.11025 4.0000 On Time FTA 13-10-2022
## 362 73.20463 4.0000 Delayed Non-FTA 03-04-2019
## 363 78.59605 4.0000 Delayed FTA 17-05-2021
## 364 83.59286 4.0000 Delayed FTA 15-04-2022
## 365 81.98987 4.0000 Delayed FTA 29-09-2022
## 366 70.91770 4.0000 On Time FTA 18-09-2023
## 367 80.82753 4.0000 Delayed FTA 15-11-2020
## 368 75.69071 4.0000 Delayed Non-FTA 08-07-2021
## 369 78.97087 4.0000 Delayed Non-FTA 21-12-2024
## 370 78.04723 4.0000 Delayed FTA 04-08-2020
## 371 78.33740 4.0000 On Time Non-FTA 15-01-2021
## 372 82.79201 5.0000 Delayed FTA 05-07-2019
## 373 72.36663 5.0000 On Time Non-FTA 10-07-2020
## 374 72.55985 5.0000 Delayed Non-FTA 19-12-2019
## 375 71.55396 5.0000 Delayed FTA 22-05-2020
## 376 72.39698 5.0000 Delayed FTA 30-12-2021
## 377 73.26792 5.0000 Delayed Non-FTA 01-04-2020
## 378 78.73583 5.0000 Delayed FTA 21-12-2018
## 379 71.57007 5.0000 Delayed FTA 06-10-2022
## 380 72.14931 5.0000 On Time FTA 07-03-2019
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## 748 72.20637 9.0000 Delayed FTA 26-03-2022
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## 757 80.72011 9.0000 Delayed Non-FTA 12-02-2020
## 758 82.95131 9.0000 Delayed Non-FTA 25-12-2021
## 759 72.61341 9.0000 On Time FTA 23-02-2024
## 760 83.33391 10.0000 On Time Non-FTA 16-11-2021
## 761 73.56093 10.0000 Delayed Non-FTA 02-12-2023
## 762 76.88003 10.0000 On Time FTA 06-03-2018
## 763 75.21794 10.0000 Delayed Non-FTA 22-11-2023
## 764 81.84817 10.0000 On Time FTA 04-05-2021
## 765 83.21940 10.0000 Delayed Non-FTA 22-08-2023
## 766 78.63988 10.0000 On Time Non-FTA 23-05-2022
## 767 71.90949 10.0000 Delayed Non-FTA 02-09-2021
## 768 81.64116 10.0000 On Time Non-FTA 26-03-2020
## 769 82.70713 10.0000 Delayed Non-FTA 27-05-2018
## 770 78.64910 10.0000 On Time Non-FTA 30-03-2019
## 771 73.11226 10.0000 Delayed Non-FTA 05-06-2019
## 772 78.51926 10.0000 Delayed FTA 01-06-2020
## 773 81.25770 10.0000 On Time Non-FTA 20-07-2023
## 774 84.10305 10.0000 On Time FTA 18-01-2022
## 775 74.65672 10.0000 Delayed Non-FTA 29-09-2024
## 776 71.88295 10.0000 On Time FTA 23-03-2022
## 777 73.01450 10.0000 On Time Non-FTA 24-09-2019
## 778 81.07887 10.0000 Delayed FTA 21-08-2018
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## 780 70.07670 10.0000 Delayed FTA 09-12-2022
## 781 80.67251 10.0000 Delayed Non-FTA 15-08-2022
## 782 80.05454 10.0000 On Time FTA 04-07-2022
## 783 82.53729 10.0000 On Time FTA 10-12-2024
## 784 76.06876 10.0000 Delayed FTA 17-12-2022
## 785 77.01842 10.0000 Delayed FTA 13-02-2021
## 786 76.64352 10.0000 On Time Non-FTA 09-01-2024
## 787 78.90886 10.0000 On Time Non-FTA 08-10-2019
## 788 83.47535 10.0000 On Time Non-FTA 25-05-2023
## 789 81.36600 10.0000 On Time Non-FTA 03-08-2023
## 790 82.13498 10.0000 On Time FTA 19-05-2020
## 791 75.29520 10.0000 Delayed Non-FTA 03-10-2020
## 792 70.33042 10.0000 Delayed Non-FTA 01-02-2020
## 793 79.85271 10.0000 Delayed FTA 26-08-2019
## 794 79.33690 10.0000 Delayed FTA 13-08-2021
## 795 84.71910 10.0000 Delayed Non-FTA 04-11-2019
## 796 82.68746 10.0000 Delayed FTA 07-04-2020
## 797 83.67805 10.0000 Delayed Non-FTA 03-03-2022
## 798 77.11799 10.0000 Delayed FTA 31-01-2021
## 799 71.95272 10.0000 On Time FTA 16-06-2018
## 800 71.69506 10.0000 On Time FTA 06-08-2020
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## 802 71.12145 10.0000 On Time Non-FTA 08-09-2023
## 803 84.24198 10.0000 Delayed Non-FTA 17-10-2024
## 804 70.58799 10.0000 On Time FTA 10-07-2020
## 805 81.12678 10.0000 On Time FTA 31-08-2021
## 806 73.71189 10.0000 On Time Non-FTA 10-07-2022
## 807 80.40820 10.0000 Delayed FTA 07-01-2020
## 808 73.67055 10.0000 Delayed Non-FTA 12-09-2024
## 809 83.76653 10.0000 On Time Non-FTA 05-12-2020
## 810 74.63139 10.0000 On Time Non-FTA 04-06-2022
## 811 73.20212 10.0000 Delayed Non-FTA 16-09-2024
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## 813 80.34655 10.0000 On Time FTA 23-10-2019
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## 816 83.19282 10.0000 On Time Non-FTA 29-08-2019
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## 819 71.44303 10.0000 On Time FTA 13-09-2020
## 820 76.80109 10.0000 On Time FTA 04-03-2018
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## 824 76.92013 10.0000 On Time FTA 28-08-2020
## 825 73.18118 10.0000 On Time Non-FTA 26-06-2022
## 826 79.91055 10.0000 Delayed FTA 19-11-2022
## 827 80.57069 10.0000 On Time Non-FTA 18-07-2024
## 828 71.44870 10.0000 Delayed Non-FTA 20-08-2021
## 829 76.58590 10.0000 On Time FTA 26-03-2022
## 830 80.69567 10.0000 Delayed Non-FTA 01-03-2021
## 831 74.99516 10.0000 Delayed Non-FTA 23-08-2024
## 832 71.53869 10.0000 On Time Non-FTA 27-07-2023
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## 834 81.17264 10.0000 Delayed FTA 13-03-2020
## 835 81.30478 10.0000 Delayed FTA 24-10-2019
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## 837 72.34403 10.0000 Delayed Non-FTA 15-10-2018
## 838 84.83434 10.0000 Delayed Non-FTA 05-07-2022
## 839 83.37980 10.0000 On Time Non-FTA 27-07-2020
## 840 82.58590 10.0000 Delayed Non-FTA 24-08-2020
## 841 71.12533 10.0000 Delayed FTA 13-12-2020
## 842 74.57313 10.0000 Delayed FTA 30-07-2018
## 843 84.10614 10.0000 On Time Non-FTA 03-02-2024
## 844 74.67894 10.0000 Delayed Non-FTA 11-01-2024
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## 846 74.80824 10.0000 On Time FTA 14-05-2019
## 847 77.11708 10.0000 On Time FTA 27-06-2021
## 848 80.36095 10.0000 On Time Non-FTA 02-08-2020
## 849 83.44050 10.0000 Delayed Non-FTA 12-03-2018
## 850 84.84164 10.0000 On Time Non-FTA 29-08-2020
## 851 70.29675 10.0000 Delayed Non-FTA 12-03-2019
## 852 70.31385 10.0000 Delayed Non-FTA 04-10-2023
## 853 84.87252 10.0000 On Time Non-FTA 01-09-2018
## 854 77.96207 10.0000 Delayed Non-FTA 28-12-2024
## 855 72.41980 10.0000 Delayed Non-FTA 05-07-2020
## 856 81.77726 10.0000 Delayed Non-FTA 15-10-2023
## 857 76.40062 10.0000 On Time Non-FTA 03-06-2020
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## 860 82.07305 11.0000 Delayed Non-FTA 19-07-2019
## 861 76.89421 11.0000 Delayed FTA 29-05-2021
## 862 82.54138 11.0000 Delayed FTA 27-06-2019
## 863 71.70530 11.0000 Delayed Non-FTA 15-05-2021
## 864 73.98214 11.0000 Delayed Non-FTA 30-05-2019
## 865 76.07617 11.0000 Delayed FTA 28-12-2020
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## 867 77.55803 11.0000 On Time Non-FTA 04-02-2020
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## 869 79.88108 11.0000 Delayed FTA 13-01-2022
## 870 79.67501 11.0000 Delayed Non-FTA 01-10-2020
## 871 72.05103 11.0000 Delayed Non-FTA 03-05-2019
## 872 76.36001 11.0000 On Time Non-FTA 21-12-2022
## 873 82.20834 11.0000 Delayed Non-FTA 02-07-2024
## 874 71.15500 11.0000 Delayed Non-FTA 13-09-2021
## 875 76.45546 11.0000 On Time Non-FTA 19-10-2023
## 876 71.75287 11.0000 On Time Non-FTA 18-07-2023
## 877 77.16735 11.0000 Delayed Non-FTA 30-05-2023
## 878 72.17471 11.0000 On Time Non-FTA 13-10-2021
## 879 81.92520 11.0000 Delayed FTA 06-10-2021
## 880 81.82893 11.0000 On Time FTA 04-10-2019
## 881 78.64739 11.0000 Delayed FTA 11-10-2019
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## 884 81.47119 11.0000 On Time Non-FTA 26-08-2021
## 885 71.10055 11.0000 Delayed Non-FTA 17-05-2019
## 886 78.90757 11.0000 On Time FTA 23-03-2023
## 887 74.13351 11.0000 Delayed Non-FTA 02-12-2021
## 888 70.64818 11.0000 On Time Non-FTA 24-02-2019
## 889 79.69478 11.0000 On Time Non-FTA 26-02-2018
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## 892 81.53995 11.0000 On Time FTA 06-05-2019
## 893 74.86004 11.0000 On Time FTA 24-06-2023
## 894 72.64784 11.0000 On Time Non-FTA 14-09-2021
## 895 81.40358 11.0000 On Time FTA 31-05-2018
## 896 74.60387 11.0000 On Time Non-FTA 29-03-2023
## 897 83.76248 11.0000 Delayed FTA 20-03-2020
## 898 74.30816 11.0000 On Time FTA 22-08-2018
## 899 77.81247 11.0000 On Time Non-FTA 01-11-2020
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## 901 80.03773 11.0000 Delayed FTA 17-01-2022
## 902 77.91088 11.0000 On Time FTA 12-09-2019
## 903 78.03544 11.0000 Delayed FTA 20-06-2020
## 904 76.55861 11.0000 Delayed Non-FTA 03-12-2019
## 905 76.16434 11.0000 On Time FTA 08-05-2022
## 906 73.20675 11.0000 On Time FTA 21-08-2018
## 907 72.80873 11.0000 Delayed FTA 16-09-2018
## 908 74.42984 11.0000 Delayed Non-FTA 03-03-2019
## 909 82.21054 11.0000 On Time FTA 08-10-2020
## 910 71.38513 11.0000 Delayed FTA 23-02-2019
## 911 79.19931 11.0000 On Time Non-FTA 18-02-2021
## 912 74.72211 11.0000 On Time Non-FTA 30-07-2019
## 913 73.70773 11.0000 Delayed Non-FTA 07-08-2024
## 914 81.97953 11.0000 On Time Non-FTA 23-07-2022
## 915 78.13843 11.0000 Delayed FTA 01-05-2018
## 916 75.39590 11.0000 Delayed Non-FTA 20-01-2024
## 917 83.82775 11.0000 On Time FTA 19-08-2023
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## 919 72.49497 11.0000 On Time FTA 04-11-2019
## 920 74.19445 11.0000 On Time FTA 12-10-2024
## 921 71.86764 11.0000 Delayed FTA 27-09-2021
## 922 70.55741 11.0000 Delayed FTA 15-05-2019
## 923 74.94863 11.0000 Delayed Non-FTA 20-08-2024
## 924 78.82720 11.0000 On Time Non-FTA 11-02-2018
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## 926 83.30140 11.0000 On Time FTA 31-10-2023
## 927 82.46368 11.0000 On Time FTA 19-12-2019
## 928 72.43929 11.0000 On Time FTA 21-12-2024
## 929 71.25451 11.0000 Delayed Non-FTA 08-04-2022
## 930 78.76269 11.0000 Delayed FTA 19-12-2024
## 931 75.77531 11.0000 Delayed Non-FTA 12-07-2022
## 932 79.22219 11.0000 Delayed Non-FTA 04-07-2020
## 933 74.33211 11.0000 Delayed FTA 24-03-2021
## 934 74.27482 11.0000 Delayed Non-FTA 28-04-2021
## 935 71.71387 11.0000 On Time FTA 30-12-2018
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## 937 76.51180 12.0000 On Time FTA 27-01-2023
## 938 75.30734 12.0000 Delayed FTA 05-02-2018
## 939 82.17804 12.0000 On Time FTA 22-10-2018
## 940 77.19546 12.0000 Delayed Non-FTA 02-07-2018
## 941 79.86056 12.0000 On Time FTA 07-05-2023
## 942 84.82540 12.0000 On Time Non-FTA 24-09-2020
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## 946 82.26383 12.0000 On Time FTA 05-05-2023
## 947 76.45683 12.0000 On Time FTA 04-08-2019
## 948 72.17483 12.0000 Delayed FTA 16-02-2018
## 949 84.38063 12.0000 Delayed FTA 07-04-2019
## 950 84.47658 12.0000 On Time FTA 03-12-2022
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## 952 84.09393 12.0000 Delayed FTA 06-12-2021
## 953 75.68798 12.0000 Delayed Non-FTA 20-06-2018
## 954 82.03696 12.0000 Delayed Non-FTA 06-02-2020
## 955 77.54564 12.0000 Delayed FTA 05-08-2018
## 956 79.70087 12.0000 On Time FTA 25-10-2023
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## 959 71.55366 12.0000 On Time FTA 29-02-2020
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## 961 70.20326 12.0000 Delayed Non-FTA 30-04-2019
## 962 70.98318 12.0000 Delayed Non-FTA 08-07-2020
## 963 79.51073 12.0000 Delayed Non-FTA 23-01-2024
## 964 77.29075 12.0000 On Time Non-FTA 13-11-2022
## 965 71.12573 12.0000 On Time FTA 13-08-2020
## 966 73.69282 12.0000 Delayed Non-FTA 21-03-2019
## 967 76.79596 12.0000 Delayed FTA 27-02-2021
## 968 82.01160 12.0000 Delayed Non-FTA 21-12-2022
## 969 84.62710 12.0000 On Time Non-FTA 17-01-2023
## 970 81.38654 12.0000 On Time Non-FTA 10-07-2022
## 971 71.83694 12.0000 Delayed Non-FTA 23-11-2019
## 972 71.02736 12.0000 On Time FTA 21-07-2021
## 973 71.12502 12.0000 On Time Non-FTA 01-02-2020
## 974 74.32934 12.0000 Delayed Non-FTA 25-11-2020
## 975 70.24684 12.0000 On Time FTA 28-02-2018
## 976 72.27651 12.0000 On Time FTA 18-05-2020
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## 979 82.58400 12.0000 On Time FTA 24-07-2019
## 980 76.66927 12.0000 On Time FTA 27-01-2023
## 981 77.12563 12.0000 On Time Non-FTA 16-01-2021
## 982 79.00223 12.0000 Delayed FTA 28-05-2023
## 983 81.22379 12.0000 Delayed FTA 06-10-2023
## 984 71.62865 12.0000 Delayed Non-FTA 27-06-2018
## 985 79.90485 12.0000 On Time FTA 05-06-2021
## 986 72.17850 12.0000 Delayed Non-FTA 03-08-2022
## 987 75.84208 12.0000 On Time FTA 03-11-2024
## 988 70.14033 12.0000 On Time FTA 04-05-2023
## 989 78.62254 12.0000 Delayed FTA 12-09-2024
## 990 84.48636 12.0000 On Time Non-FTA 06-05-2022
## 991 72.16463 12.0000 Delayed FTA 18-09-2018
## 992 72.55376 12.0000 Delayed Non-FTA 03-05-2022
## 993 72.71971 12.0000 On Time Non-FTA 24-07-2018
## 994 84.01231 12.0000 On Time Non-FTA 10-03-2018
## 995 84.75314 12.0000 On Time Non-FTA 24-03-2024
## 996 79.76205 12.0000 On Time Non-FTA 23-02-2021
## 997 74.11827 12.0000 On Time Non-FTA 30-08-2018
## 998 76.49568 12.0000 Delayed Non-FTA 01-11-2024
## 999 81.82211 12.0000 On Time Non-FTA 06-12-2018
## 1000 78.53002 12.0000 Delayed Non-FTA 04-08-2023
## 1001 76.68245 12.0000 Delayed Non-FTA 16-11-2021
## 1002 72.05092 12.0000 On Time Non-FTA 17-12-2020
## 1003 71.45905 12.0000 On Time FTA 10-06-2024
## 1004 77.55574 12.0000 Delayed FTA 25-02-2021
## 1005 81.76012 12.0000 On Time FTA 31-08-2019
## 1006 79.64174 12.0000 On Time FTA 06-07-2020
## 1007 74.42898 12.0000 On Time Non-FTA 26-07-2018
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## 1009 77.86335 12.0000 On Time FTA 11-09-2020
## 1010 80.26940 12.0000 On Time Non-FTA 19-07-2019
## 1011 83.77642 12.0000 On Time Non-FTA 27-09-2023
## 1012 79.41388 12.0000 On Time FTA 30-12-2019
## 1013 73.51009 12.0000 Delayed FTA 15-07-2020
## 1014 73.75428 12.0000 On Time FTA 10-07-2024
## 1015 74.71611 12.0000 Delayed Non-FTA 29-06-2018
## 1016 72.44658 12.0000 On Time FTA 26-09-2020
## 1017 78.48161 12.0000 On Time Non-FTA 09-09-2023
## 1018 77.90712 12.0000 Delayed FTA 01-03-2019
## 1019 73.12307 13.0000 On Time FTA 08-05-2022
## 1020 74.75773 13.0000 On Time Non-FTA 15-11-2020
## 1021 80.10065 13.0000 On Time Non-FTA 29-11-2024
## 1022 75.78968 13.0000 On Time FTA 24-01-2020
## 1023 78.93858 13.0000 Delayed Non-FTA 17-03-2018
## 1024 72.48516 13.0000 Delayed FTA 27-08-2018
## 1025 71.19282 13.0000 Delayed FTA 25-03-2022
## 1026 84.34457 13.0000 Delayed Non-FTA 14-09-2022
## 1027 76.16754 13.0000 On Time Non-FTA 06-09-2021
## 1028 77.51537 13.0000 Delayed FTA 10-12-2023
## 1029 82.68370 13.0000 On Time FTA 25-01-2022
## 1030 79.05952 13.0000 Delayed FTA 01-02-2019
## 1031 75.86462 13.0000 Delayed Non-FTA 18-06-2022
## 1032 73.33900 13.0000 On Time FTA 25-09-2024
## 1033 70.69056 13.0000 Delayed Non-FTA 07-04-2019
## 1034 74.89662 13.0000 On Time Non-FTA 23-11-2024
## 1035 81.20044 13.0000 Delayed FTA 18-11-2019
## 1036 76.41050 13.0000 On Time FTA 16-09-2019
## 1037 81.06356 13.0000 On Time FTA 07-07-2024
## 1038 77.80239 13.0000 Delayed FTA 11-10-2020
## 1039 78.68477 13.0000 Delayed Non-FTA 06-06-2023
## 1040 79.54597 13.0000 Delayed FTA 25-08-2019
## 1041 77.37285 13.0000 Delayed Non-FTA 19-02-2023
## 1042 80.55475 13.0000 On Time Non-FTA 06-05-2024
## 1043 80.70426 13.0000 On Time Non-FTA 25-07-2019
## 1044 80.90865 13.0000 Delayed Non-FTA 24-07-2023
## 1045 76.78708 13.0000 On Time FTA 02-01-2019
## 1046 80.91446 13.0000 On Time FTA 19-06-2018
## 1047 80.24232 13.0000 Delayed FTA 10-08-2020
## 1048 70.00762 13.0000 On Time FTA 29-09-2019
## 1049 76.54041 13.0000 Delayed Non-FTA 18-01-2022
## 1050 82.62244 13.0000 Delayed Non-FTA 04-05-2019
## 1051 70.44496 13.0000 On Time Non-FTA 27-11-2022
## 1052 81.86688 13.0000 Delayed Non-FTA 14-10-2019
## 1053 71.20424 13.0000 Delayed FTA 27-04-2018
## 1054 76.23748 13.0000 On Time Non-FTA 01-03-2021
## 1055 70.69418 13.0000 On Time Non-FTA 19-07-2020
## 1056 78.27596 13.0000 On Time Non-FTA 18-07-2019
## 1057 81.63726 13.0000 Delayed Non-FTA 23-04-2020
## 1058 84.06785 13.0000 Delayed FTA 01-03-2020
## 1059 71.02016 13.0000 Delayed FTA 26-02-2024
## 1060 76.31396 13.0000 Delayed Non-FTA 24-12-2021
## 1061 83.78513 13.0000 Delayed FTA 22-09-2024
## 1062 71.02950 13.0000 On Time Non-FTA 13-05-2023
## 1063 72.09516 13.0000 Delayed Non-FTA 14-06-2024
## 1064 80.38032 13.0000 On Time Non-FTA 21-09-2020
## 1065 76.05489 13.0000 Delayed Non-FTA 13-09-2019
## 1066 72.98277 13.0000 Delayed Non-FTA 17-06-2024
## 1067 73.35799 13.0000 Delayed Non-FTA 12-09-2019
## 1068 74.88019 13.0000 On Time FTA 26-09-2018
## 1069 71.60214 13.0000 Delayed Non-FTA 17-05-2020
## 1070 80.53003 13.0000 Delayed Non-FTA 20-11-2020
## 1071 80.41680 13.0000 On Time FTA 11-12-2018
## 1072 83.74212 13.0000 On Time FTA 22-04-2022
## 1073 79.69407 13.0000 On Time FTA 09-03-2020
## 1074 79.31984 13.0000 Delayed FTA 15-07-2020
## 1075 72.98231 13.0000 On Time FTA 28-12-2021
## 1076 78.14120 13.0000 On Time Non-FTA 20-11-2020
## 1077 83.04954 13.0000 On Time Non-FTA 08-11-2019
## 1078 76.41204 13.0000 Delayed Non-FTA 31-08-2019
## 1079 71.52531 13.0000 On Time FTA 07-12-2024
## 1080 76.41400 13.0000 Delayed FTA 22-05-2022
## 1081 84.10677 13.0000 Delayed Non-FTA 22-09-2024
## 1082 83.53969 13.0000 Delayed FTA 06-07-2021
## 1083 74.56347 13.0000 Delayed FTA 22-08-2023
## 1084 73.99036 13.0000 On Time Non-FTA 24-02-2023
## 1085 80.74156 13.0000 Delayed FTA 08-07-2020
## 1086 79.81686 13.0000 Delayed Non-FTA 25-08-2024
## 1087 80.16073 13.0000 On Time FTA 06-02-2021
## 1088 77.14993 13.0000 On Time FTA 14-12-2019
## 1089 81.34442 13.0000 Delayed Non-FTA 24-06-2023
## 1090 70.86916 13.0000 On Time Non-FTA 06-05-2023
## 1091 80.44148 13.0000 On Time FTA 23-01-2022
## 1092 78.48045 13.0000 Delayed FTA 17-06-2024
## 1093 70.25781 14.0000 On Time Non-FTA 09-01-2022
## 1094 73.90917 14.0000 Delayed FTA 02-06-2020
## 1095 76.70249 14.0000 Delayed Non-FTA 27-12-2020
## 1096 75.34349 14.0000 On Time Non-FTA 03-07-2020
## 1097 75.92975 14.0000 On Time FTA 03-04-2022
## 1098 80.20316 14.0000 On Time FTA 04-04-2022
## 1099 80.27424 14.0000 Delayed Non-FTA 14-09-2024
## 1100 84.14880 14.0000 On Time Non-FTA 13-01-2021
## 1101 74.07441 14.0000 On Time Non-FTA 23-09-2018
## 1102 70.66582 14.0000 On Time Non-FTA 15-10-2024
## 1103 81.06166 14.0000 Delayed Non-FTA 25-09-2021
## 1104 76.95100 14.0000 Delayed FTA 16-08-2018
## 1105 75.61392 14.0000 Delayed FTA 05-05-2024
## 1106 72.05400 14.0000 On Time FTA 07-01-2019
## 1107 81.89965 14.0000 Delayed Non-FTA 09-06-2021
## 1108 76.97175 14.0000 Delayed FTA 19-12-2018
## 1109 81.63857 14.0000 On Time FTA 22-03-2018
## 1110 73.05644 14.0000 Delayed Non-FTA 18-06-2023
## 1111 72.99159 14.0000 On Time FTA 24-03-2019
## 1112 73.86609 14.0000 On Time FTA 26-07-2023
## 1113 82.42826 14.0000 On Time FTA 13-04-2021
## 1114 78.79363 14.0000 Delayed FTA 09-01-2024
## 1115 74.21406 14.0000 On Time Non-FTA 26-07-2019
## 1116 75.83759 14.0000 Delayed FTA 08-04-2018
## 1117 80.20302 14.0000 On Time FTA 01-09-2019
## 1118 80.72877 14.0000 On Time Non-FTA 25-11-2024
## 1119 76.49637 14.0000 Delayed Non-FTA 03-09-2024
## 1120 80.93157 14.0000 On Time FTA 04-11-2024
## 1121 78.54109 14.0000 On Time Non-FTA 22-09-2024
## 1122 76.00380 14.0000 On Time Non-FTA 08-06-2019
## 1123 84.85070 14.0000 On Time Non-FTA 22-05-2020
## 1124 75.55762 14.0000 On Time FTA 17-12-2018
## 1125 73.74786 14.0000 On Time FTA 22-07-2019
## 1126 81.77565 14.0000 On Time FTA 03-10-2021
## 1127 77.23546 14.0000 On Time FTA 16-10-2021
## 1128 74.73868 14.0000 On Time Non-FTA 15-02-2023
## 1129 78.89609 14.0000 On Time Non-FTA 29-03-2021
## 1130 76.80008 14.0000 Delayed FTA 08-05-2018
## 1131 82.96770 14.0000 On Time Non-FTA 29-02-2024
## 1132 74.78420 14.0000 Delayed Non-FTA 24-04-2024
## 1133 80.96222 14.0000 Delayed Non-FTA 27-07-2021
## 1134 81.21736 14.0000 Delayed FTA 01-05-2020
## 1135 76.31565 14.0000 On Time Non-FTA 09-07-2022
## 1136 70.05102 14.0000 On Time FTA 08-12-2023
## 1137 71.26165 14.0000 Delayed Non-FTA 09-12-2019
## 1138 84.52577 14.0000 Delayed FTA 06-12-2020
## 1139 71.55489 14.0000 Delayed FTA 10-05-2023
## 1140 70.68038 14.0000 On Time Non-FTA 15-01-2020
## 1141 84.02184 14.0000 Delayed FTA 21-11-2019
## 1142 70.32097 14.0000 On Time FTA 25-05-2023
## 1143 77.49997 14.0000 On Time Non-FTA 14-02-2019
## 1144 75.54736 14.0000 Delayed FTA 15-05-2023
## 1145 77.25599 14.0000 Delayed FTA 07-09-2023
## 1146 79.92258 14.0000 Delayed Non-FTA 21-02-2021
## 1147 76.15170 14.0000 On Time Non-FTA 11-04-2022
## 1148 81.61382 14.0000 Delayed Non-FTA 23-05-2022
## 1149 83.13552 14.0000 On Time FTA 27-09-2023
## 1150 81.04682 14.0000 Delayed FTA 22-01-2021
## 1151 72.61102 14.0000 Delayed FTA 14-06-2023
## 1152 80.42950 14.0000 On Time FTA 13-04-2021
## 1153 80.26513 14.0000 On Time Non-FTA 25-03-2023
## 1154 84.78118 14.0000 Delayed Non-FTA 29-12-2021
## 1155 80.95780 14.0000 Delayed FTA 30-08-2023
## 1156 71.49103 14.0000 Delayed Non-FTA 03-11-2024
## 1157 83.19195 14.0000 Delayed FTA 28-05-2024
## 1158 80.47913 14.0000 Delayed Non-FTA 30-03-2021
## 1159 71.72696 14.0000 Delayed Non-FTA 05-06-2018
## 1160 73.38430 14.0000 Delayed Non-FTA 24-02-2020
## 1161 73.47458 14.0000 On Time Non-FTA 10-01-2023
## 1162 77.58638 14.0000 Delayed FTA 13-10-2023
## 1163 70.53629 14.0000 Delayed Non-FTA 04-12-2021
## 1164 84.94779 14.0000 Delayed Non-FTA 06-06-2018
## 1165 80.29942 14.0000 On Time Non-FTA 01-01-2022
## 1166 77.24515 14.0000 On Time Non-FTA 27-05-2021
## 1167 72.80571 14.0000 On Time FTA 23-12-2023
## 1168 70.25510 14.0000 On Time FTA 23-07-2022
## 1169 72.13713 14.0000 Delayed Non-FTA 29-09-2024
## 1170 76.21886 14.0000 Delayed FTA 06-04-2018
## 1171 72.67793 14.0000 On Time Non-FTA 21-08-2022
## 1172 74.44751 14.0000 Delayed FTA 30-06-2023
## 1173 81.50678 14.0000 Delayed Non-FTA 16-04-2021
## 1174 83.63392 14.0000 On Time Non-FTA 13-07-2023
## 1175 75.33327 14.0000 On Time FTA 08-05-2020
## 1176 74.43339 15.0000 Delayed FTA 04-06-2022
## 1177 73.06567 15.0000 On Time Non-FTA 03-06-2024
## 1178 79.72063 15.0000 On Time FTA 30-04-2021
## 1179 80.92053 15.0000 On Time FTA 03-11-2021
## 1180 78.25098 15.0000 On Time FTA 24-11-2022
## 1181 70.43902 15.0000 On Time Non-FTA 14-02-2024
## 1182 72.40244 15.0000 On Time Non-FTA 11-02-2020
## 1183 77.12978 15.0000 On Time FTA 14-09-2018
## 1184 83.25263 15.0000 Delayed FTA 20-05-2024
## 1185 83.40208 15.0000 On Time Non-FTA 13-04-2019
## 1186 81.69187 15.0000 Delayed Non-FTA 21-07-2020
## 1187 78.45617 15.0000 On Time Non-FTA 23-07-2021
## 1188 72.39524 15.0000 On Time FTA 14-09-2019
## 1189 80.50063 15.0000 On Time FTA 12-10-2021
## 1190 84.61460 15.0000 On Time Non-FTA 14-09-2018
## 1191 74.37783 15.0000 Delayed FTA 09-08-2018
## 1192 74.67992 15.0000 Delayed Non-FTA 10-01-2018
## 1193 77.66380 15.0000 Delayed FTA 13-06-2024
## 1194 79.06877 15.0000 On Time Non-FTA 23-10-2018
## 1195 77.29078 15.0000 On Time Non-FTA 23-11-2024
## 1196 77.32182 15.0000 On Time Non-FTA 06-06-2024
## 1197 74.52351 15.0000 Delayed Non-FTA 14-12-2021
## 1198 76.03540 15.0000 On Time Non-FTA 06-11-2021
## 1199 81.47914 15.0000 Delayed FTA 28-10-2019
## 1200 75.58220 15.0000 On Time Non-FTA 20-11-2020
## 1201 71.91176 15.0000 Delayed FTA 11-10-2020
## 1202 77.93124 15.0000 On Time FTA 01-01-2019
## 1203 80.06379 15.0000 On Time FTA 26-08-2020
## 1204 74.90112 15.0000 On Time Non-FTA 12-11-2020
## 1205 74.72729 15.0000 On Time FTA 22-11-2021
## 1206 77.70793 15.0000 Delayed FTA 07-12-2022
## 1207 78.98915 15.0000 Delayed FTA 24-12-2022
## 1208 76.39170 15.0000 Delayed Non-FTA 07-11-2018
## 1209 83.13670 15.0000 On Time Non-FTA 12-10-2023
## 1210 79.04530 15.0000 On Time Non-FTA 28-04-2022
## 1211 84.70513 15.0000 On Time FTA 10-01-2019
## 1212 84.42384 15.0000 On Time FTA 18-10-2020
## 1213 79.39518 15.0000 On Time FTA 09-09-2018
## 1214 75.05535 15.0000 On Time FTA 07-03-2020
## 1215 83.25441 15.0000 Delayed Non-FTA 07-01-2018
## 1216 82.62372 15.0000 Delayed Non-FTA 18-10-2024
## 1217 83.61556 15.0000 On Time Non-FTA 02-10-2021
## 1218 77.20585 15.0000 On Time FTA 07-08-2020
## 1219 72.33551 15.0000 Delayed FTA 26-04-2018
## 1220 72.79557 15.0000 Delayed FTA 18-01-2019
## 1221 82.33186 15.0000 On Time FTA 21-11-2021
## 1222 84.72710 15.0000 Delayed Non-FTA 14-07-2019
## 1223 80.64698 15.0000 On Time Non-FTA 02-08-2019
## 1224 78.54430 15.0000 On Time FTA 25-04-2018
## 1225 74.11837 15.0000 On Time Non-FTA 25-09-2023
## 1226 77.96983 15.0000 On Time FTA 27-07-2021
## 1227 76.04312 15.0000 On Time FTA 10-04-2019
## 1228 79.07299 15.0000 Delayed Non-FTA 07-03-2018
## 1229 78.76768 15.0000 On Time Non-FTA 03-02-2023
## 1230 74.31142 15.0000 On Time FTA 19-05-2019
## 1231 76.38597 15.0000 On Time Non-FTA 08-01-2024
## 1232 75.64344 15.0000 Delayed FTA 10-03-2019
## 1233 76.67709 15.0000 Delayed FTA 19-08-2023
## 1234 79.70966 15.0000 On Time Non-FTA 15-07-2019
## 1235 77.31699 15.0000 Delayed Non-FTA 25-12-2024
## 1236 76.61666 15.0000 Delayed FTA 20-06-2022
## 1237 71.84376 15.0000 On Time FTA 23-02-2020
## 1238 80.01074 15.0000 Delayed FTA 21-04-2023
## 1239 79.47014 15.0000 On Time FTA 29-06-2022
## 1240 80.82987 15.0000 On Time FTA 09-09-2023
## 1241 72.44846 15.0000 On Time Non-FTA 29-03-2023
## 1242 80.57520 15.0000 Delayed FTA 02-04-2019
## 1243 77.22230 15.0000 Delayed Non-FTA 03-04-2020
## 1244 81.64250 15.0000 On Time Non-FTA 21-03-2024
## 1245 79.37193 15.0000 Delayed Non-FTA 26-11-2022
## 1246 76.97289 15.0000 On Time FTA 25-04-2019
## 1247 82.31655 15.0000 Delayed FTA 17-10-2023
## 1248 77.20933 15.0000 On Time Non-FTA 24-02-2019
## 1249 71.52439 16.0000 On Time FTA 30-08-2018
## 1250 81.71390 16.0000 Delayed FTA 28-04-2020
## 1251 71.74239 16.0000 On Time Non-FTA 17-10-2022
## 1252 75.42238 16.0000 Delayed Non-FTA 31-05-2023
## 1253 74.16182 16.0000 On Time FTA 28-11-2018
## 1254 73.31715 16.0000 On Time Non-FTA 08-12-2022
## 1255 73.29251 16.0000 Delayed Non-FTA 21-06-2022
## 1256 75.92152 16.0000 On Time FTA 02-09-2020
## 1257 71.55306 16.0000 On Time FTA 16-10-2022
## 1258 74.01282 16.0000 Delayed FTA 04-07-2019
## 1259 74.90558 16.0000 On Time FTA 30-12-2024
## 1260 73.02579 16.0000 Delayed FTA 22-12-2021
## 1261 71.55385 16.0000 On Time FTA 15-01-2023
## 1262 79.12593 16.0000 On Time Non-FTA 03-07-2024
## 1263 78.28681 16.0000 On Time FTA 22-01-2018
## 1264 71.18561 16.0000 On Time FTA 10-11-2019
## 1265 83.14016 16.0000 Delayed FTA 20-02-2019
## 1266 77.57455 16.0000 On Time FTA 07-04-2022
## 1267 84.19013 16.0000 Delayed Non-FTA 05-05-2018
## 1268 79.00180 16.0000 On Time FTA 17-06-2022
## 1269 70.09426 16.0000 On Time Non-FTA 13-08-2024
## 1270 72.54016 16.0000 Delayed FTA 11-03-2023
## 1271 82.48043 16.0000 On Time FTA 11-03-2018
## 1272 82.96606 16.0000 On Time FTA 20-09-2022
## 1273 81.91830 16.0000 On Time FTA 15-02-2022
## 1274 77.63045 16.0000 On Time Non-FTA 04-06-2024
## 1275 80.31108 16.0000 Delayed Non-FTA 14-05-2018
## 1276 82.81424 16.0000 On Time Non-FTA 23-03-2019
## 1277 77.36913 16.0000 On Time Non-FTA 25-07-2023
## 1278 76.25766 16.0000 Delayed FTA 08-12-2018
## 1279 76.73115 16.0000 On Time FTA 28-07-2018
## 1280 71.42198 16.0000 Delayed FTA 14-11-2020
## 1281 73.32421 16.0000 On Time FTA 10-10-2023
## 1282 77.79237 16.0000 On Time Non-FTA 02-08-2024
## 1283 72.61713 16.0000 On Time FTA 17-07-2023
## 1284 75.19980 16.0000 Delayed FTA 26-07-2019
## 1285 72.70959 16.0000 On Time Non-FTA 28-11-2023
## 1286 75.80045 16.0000 Delayed Non-FTA 29-05-2024
## 1287 81.17607 16.0000 Delayed FTA 06-09-2020
## 1288 70.34943 16.0000 On Time FTA 20-05-2024
## 1289 77.59624 16.0000 Delayed Non-FTA 12-07-2022
## 1290 74.22732 16.0000 On Time FTA 02-12-2018
## 1291 84.89087 16.0000 Delayed FTA 11-08-2018
## 1292 83.65773 16.0000 Delayed Non-FTA 17-03-2021
## 1293 79.25415 16.0000 On Time FTA 16-01-2020
## 1294 79.20744 16.0000 On Time FTA 28-05-2024
## 1295 70.96080 16.0000 On Time FTA 12-05-2022
## 1296 77.71802 16.0000 On Time Non-FTA 27-11-2019
## 1297 73.34780 16.0000 On Time FTA 05-01-2018
## 1298 78.01551 16.0000 On Time FTA 13-08-2022
## 1299 78.45990 16.0000 Delayed Non-FTA 03-10-2019
## 1300 76.67140 16.0000 On Time FTA 15-09-2024
## 1301 70.69331 16.0000 On Time Non-FTA 25-01-2020
## 1302 76.27367 16.0000 On Time FTA 11-02-2024
## 1303 74.25835 16.0000 Delayed FTA 03-01-2023
## 1304 77.97753 16.0000 Delayed Non-FTA 04-08-2023
## 1305 70.07224 16.0000 On Time FTA 03-08-2018
## 1306 71.22905 16.0000 Delayed FTA 04-12-2019
## 1307 81.21242 16.0000 On Time Non-FTA 30-03-2019
## 1308 73.33260 16.0000 Delayed Non-FTA 22-08-2019
## 1309 81.64337 16.0000 Delayed FTA 01-10-2023
## 1310 75.44689 16.0000 On Time FTA 15-01-2019
## 1311 71.15527 16.0000 On Time FTA 10-09-2023
## 1312 79.44064 16.0000 On Time Non-FTA 02-11-2018
## 1313 84.77871 16.0000 On Time FTA 08-05-2022
## 1314 84.55618 16.0000 On Time Non-FTA 05-11-2023
## 1315 73.06520 16.0000 Delayed FTA 03-05-2019
## 1316 73.45094 16.0000 Delayed FTA 06-07-2022
## 1317 75.60278 16.0000 Delayed Non-FTA 07-11-2019
## 1318 74.30987 16.0000 On Time Non-FTA 12-02-2020
## 1319 74.19781 16.0000 On Time FTA 12-05-2019
## 1320 80.16688 16.0000 On Time Non-FTA 10-07-2021
## 1321 72.87417 16.0000 Delayed Non-FTA 26-02-2021
## 1322 82.55411 16.0000 On Time Non-FTA 06-03-2024
## 1323 75.15440 16.0000 Delayed FTA 14-04-2023
## 1324 75.52313 17.0000 Delayed FTA 03-05-2020
## 1325 81.23289 17.0000 Delayed FTA 25-06-2022
## 1326 77.54498 17.0000 On Time Non-FTA 24-09-2018
## 1327 82.55990 17.0000 Delayed Non-FTA 30-06-2024
## 1328 72.78012 17.0000 Delayed Non-FTA 17-03-2022
## 1329 84.33950 17.0000 On Time FTA 16-02-2022
## 1330 72.20472 17.0000 Delayed Non-FTA 10-07-2019
## 1331 76.77498 17.0000 On Time FTA 23-05-2024
## 1332 77.21774 17.0000 Delayed FTA 06-06-2018
## 1333 73.56820 17.0000 Delayed Non-FTA 07-12-2020
## 1334 78.11583 17.0000 On Time FTA 12-03-2018
## 1335 84.04321 17.0000 Delayed FTA 05-07-2024
## 1336 84.12237 17.0000 On Time FTA 07-04-2022
## 1337 70.54564 17.0000 Delayed Non-FTA 14-08-2022
## 1338 76.10890 17.0000 Delayed Non-FTA 02-07-2019
## 1339 70.27869 17.0000 On Time Non-FTA 22-04-2020
## 1340 73.42724 17.0000 Delayed FTA 22-11-2023
## 1341 83.83478 17.0000 On Time Non-FTA 24-02-2020
## 1342 77.77278 17.0000 On Time Non-FTA 11-10-2019
## 1343 83.25291 17.0000 On Time Non-FTA 13-06-2018
## 1344 74.40027 17.0000 Delayed FTA 29-09-2021
## 1345 75.72599 17.0000 On Time FTA 03-03-2021
## 1346 81.34136 17.0000 On Time Non-FTA 28-08-2023
## 1347 74.45341 17.0000 On Time Non-FTA 10-02-2022
## 1348 84.45769 17.0000 Delayed FTA 07-02-2021
## 1349 74.98217 17.0000 Delayed Non-FTA 04-05-2023
## 1350 73.69886 17.0000 Delayed Non-FTA 08-10-2021
## 1351 75.17024 17.0000 On Time Non-FTA 26-05-2023
## 1352 74.90035 17.0000 On Time Non-FTA 16-06-2023
## 1353 76.34906 17.0000 On Time FTA 29-08-2019
## 1354 76.76470 17.0000 On Time FTA 01-10-2021
## 1355 77.83732 17.0000 Delayed Non-FTA 12-09-2022
## 1356 76.95942 17.0000 Delayed Non-FTA 23-08-2019
## 1357 74.08895 17.0000 Delayed FTA 10-06-2022
## 1358 78.69914 17.0000 On Time FTA 21-09-2018
## 1359 73.06817 17.0000 On Time FTA 27-02-2021
## 1360 71.61277 17.0000 On Time FTA 25-12-2019
## 1361 74.27868 17.0000 On Time Non-FTA 01-07-2024
## 1362 72.75084 17.0000 Delayed FTA 16-07-2018
## 1363 79.74474 17.0000 On Time FTA 02-07-2023
## 1364 81.62828 17.0000 On Time FTA 01-10-2021
## 1365 80.17267 17.0000 On Time FTA 20-06-2024
## 1366 83.00435 17.0000 Delayed FTA 10-04-2024
## 1367 73.48565 17.0000 Delayed FTA 12-08-2018
## 1368 72.03751 17.0000 On Time Non-FTA 01-03-2019
## 1369 75.55942 17.0000 On Time Non-FTA 26-08-2024
## 1370 84.91146 17.0000 On Time FTA 01-11-2019
## 1371 76.11101 17.0000 On Time FTA 06-06-2018
## 1372 73.06161 17.0000 On Time Non-FTA 06-01-2021
## 1373 83.06459 17.0000 Delayed FTA 28-03-2024
## 1374 72.93270 17.0000 On Time FTA 13-06-2024
## 1375 74.61232 17.0000 Delayed Non-FTA 02-01-2024
## 1376 73.88425 17.0000 On Time Non-FTA 29-07-2022
## 1377 79.44041 17.0000 Delayed Non-FTA 16-01-2021
## 1378 82.42938 17.0000 On Time Non-FTA 13-03-2020
## 1379 82.47028 17.0000 Delayed Non-FTA 20-04-2022
## 1380 73.25904 17.0000 Delayed FTA 20-03-2022
## 1381 74.55313 17.0000 Delayed FTA 07-03-2020
## 1382 78.73339 17.0000 On Time Non-FTA 25-07-2023
## 1383 77.58195 17.0000 Delayed Non-FTA 28-02-2022
## 1384 73.69054 17.0000 Delayed FTA 06-06-2024
## 1385 70.79472 17.0000 On Time FTA 06-11-2023
## 1386 77.22113 17.0000 On Time FTA 05-08-2021
## 1387 74.89403 17.0000 Delayed Non-FTA 15-06-2019
## 1388 74.76554 17.0000 Delayed Non-FTA 06-09-2023
## 1389 75.04412 17.0000 Delayed Non-FTA 22-03-2019
## 1390 83.85626 17.0000 Delayed Non-FTA 12-09-2024
## 1391 73.37507 17.0000 Delayed FTA 15-12-2020
## 1392 79.00499 17.0000 Delayed Non-FTA 23-01-2023
## 1393 77.37331 17.0000 On Time FTA 26-08-2024
## 1394 78.12983 17.0000 On Time FTA 02-09-2018
## 1395 75.81133 17.0000 On Time Non-FTA 01-12-2023
## 1396 80.71328 17.0000 On Time FTA 17-12-2021
## 1397 82.58395 17.0000 On Time Non-FTA 02-03-2022
## 1398 80.61321 17.0000 Delayed FTA 15-03-2018
## 1399 74.34541 17.0000 On Time Non-FTA 30-12-2018
## 1400 73.63908 17.0000 On Time Non-FTA 05-05-2023
## 1401 75.51641 17.0000 Delayed FTA 03-03-2018
## 1402 82.28183 17.0000 On Time FTA 17-12-2024
## 1403 72.61821 17.0000 Delayed Non-FTA 07-08-2022
## 1404 82.20563 18.0000 On Time Non-FTA 03-07-2022
## 1405 75.20845 18.0000 Delayed Non-FTA 07-08-2019
## 1406 73.93622 18.0000 Delayed Non-FTA 19-10-2019
## 1407 74.67987 18.0000 On Time Non-FTA 16-05-2024
## 1408 83.47293 18.0000 On Time FTA 09-10-2019
## 1409 75.17793 18.0000 Delayed Non-FTA 10-05-2020
## 1410 79.13068 18.0000 Delayed Non-FTA 30-01-2023
## 1411 73.16881 18.0000 Delayed FTA 24-04-2023
## 1412 84.89017 18.0000 Delayed FTA 14-11-2020
## 1413 72.06375 18.0000 Delayed Non-FTA 02-02-2022
## 1414 81.29849 18.0000 On Time FTA 25-08-2020
## 1415 80.48264 18.0000 Delayed FTA 18-09-2021
## 1416 71.51407 18.0000 Delayed FTA 22-06-2023
## 1417 80.31075 18.0000 On Time FTA 04-03-2018
## 1418 76.76456 18.0000 On Time Non-FTA 05-12-2023
## 1419 70.34866 18.0000 Delayed FTA 22-12-2023
## 1420 70.86238 18.0000 On Time Non-FTA 23-09-2022
## 1421 81.89561 18.0000 Delayed FTA 28-04-2019
## 1422 75.21521 18.0000 Delayed Non-FTA 09-11-2019
## 1423 82.54907 18.0000 On Time FTA 03-10-2019
## 1424 78.12926 18.0000 On Time Non-FTA 03-02-2019
## 1425 75.75370 18.0000 On Time Non-FTA 08-06-2022
## 1426 74.28024 18.0000 On Time Non-FTA 06-05-2024
## 1427 83.61810 18.0000 On Time Non-FTA 25-09-2021
## 1428 83.42638 18.0000 On Time FTA 24-09-2019
## 1429 74.32318 18.0000 On Time Non-FTA 07-07-2023
## 1430 80.51028 18.0000 Delayed Non-FTA 20-03-2020
## 1431 78.00710 18.0000 Delayed Non-FTA 10-08-2022
## 1432 73.16344 18.0000 Delayed FTA 14-11-2019
## 1433 82.14755 18.0000 Delayed Non-FTA 27-09-2020
## 1434 78.35859 18.0000 On Time FTA 12-11-2024
## 1435 77.33513 18.0000 On Time Non-FTA 23-11-2020
## 1436 82.96708 18.0000 Delayed Non-FTA 27-02-2019
## 1437 76.27068 18.0000 On Time Non-FTA 30-09-2022
## 1438 83.38551 18.0000 On Time Non-FTA 19-02-2019
## 1439 76.07879 18.0000 Delayed FTA 21-06-2019
## 1440 84.96220 18.0000 Delayed FTA 05-12-2020
## 1441 74.83490 18.0000 On Time FTA 07-11-2019
## 1442 79.12226 18.0000 Delayed Non-FTA 08-05-2022
## 1443 74.08811 18.0000 Delayed Non-FTA 02-11-2019
## 1444 73.74693 18.0000 On Time FTA 19-08-2023
## 1445 75.93575 18.0000 On Time Non-FTA 26-06-2022
## 1446 75.86904 18.0000 On Time Non-FTA 04-04-2020
## 1447 70.98077 18.0000 On Time Non-FTA 16-09-2021
## 1448 74.02543 18.0000 Delayed FTA 02-01-2021
## 1449 75.35573 18.0000 Delayed Non-FTA 16-12-2021
## 1450 75.81229 18.0000 On Time Non-FTA 24-07-2023
## 1451 75.06368 18.0000 Delayed FTA 26-01-2019
## 1452 77.26943 18.0000 Delayed FTA 03-09-2020
## 1453 84.47185 18.0000 On Time Non-FTA 17-06-2024
## 1454 70.87778 18.0000 Delayed FTA 05-12-2023
## 1455 74.26394 18.0000 Delayed FTA 27-04-2023
## 1456 76.64675 18.0000 Delayed Non-FTA 23-01-2022
## 1457 72.44408 18.0000 On Time FTA 28-02-2024
## 1458 74.76715 18.0000 Delayed FTA 08-10-2020
## 1459 72.16363 18.0000 On Time FTA 03-07-2023
## 1460 72.58977 18.0000 Delayed FTA 03-05-2021
## 1461 76.69403 18.0000 On Time FTA 15-03-2019
## 1462 73.16317 18.0000 On Time FTA 26-11-2021
## 1463 79.57639 18.0000 On Time FTA 13-08-2021
## 1464 71.98977 18.0000 On Time Non-FTA 01-01-2024
## 1465 78.04993 18.0000 On Time FTA 30-09-2019
## 1466 70.08228 18.0000 On Time FTA 02-10-2022
## 1467 78.50698 18.0000 Delayed Non-FTA 22-09-2023
## 1468 77.29014 18.0000 On Time Non-FTA 01-02-2020
## 1469 83.17368 18.0000 On Time FTA 29-03-2020
## 1470 73.95535 18.0000 On Time Non-FTA 10-08-2018
## 1471 73.40728 18.0000 On Time Non-FTA 26-03-2022
## 1472 74.98699 18.0000 Delayed FTA 19-09-2022
## 1473 76.83056 18.0000 On Time Non-FTA 14-04-2019
## 1474 71.24671 18.0000 Delayed FTA 27-09-2019
## 1475 77.86115 18.0000 On Time Non-FTA 02-10-2019
## 1476 77.10612 18.0000 On Time FTA 24-05-2023
## 1477 81.30001 18.0000 On Time FTA 11-05-2018
## 1478 76.52711 18.0000 On Time Non-FTA 29-12-2019
## 1479 84.21607 18.0000 On Time FTA 03-01-2023
## 1480 73.41633 18.0000 Delayed FTA 15-12-2021
## 1481 72.21159 18.0000 On Time FTA 10-08-2022
## 1482 80.39806 18.0000 On Time Non-FTA 20-10-2019
## 1483 81.31043 18.0000 On Time FTA 25-02-2024
## 1484 78.17592 18.0000 Delayed Non-FTA 28-01-2019
## 1485 76.23808 18.0000 On Time FTA 01-12-2023
## 1486 80.73125 19.0000 On Time Non-FTA 26-08-2019
## 1487 84.34789 19.0000 On Time Non-FTA 10-11-2020
## 1488 81.41711 19.0000 On Time FTA 24-09-2020
## 1489 83.75195 19.0000 Delayed Non-FTA 18-07-2019
## 1490 79.46331 19.0000 On Time Non-FTA 21-08-2023
## 1491 79.05032 19.0000 Delayed FTA 30-01-2021
## 1492 80.15858 19.0000 Delayed Non-FTA 12-10-2024
## 1493 82.58834 19.0000 Delayed FTA 27-01-2023
## 1494 82.29886 19.0000 Delayed FTA 17-05-2024
## 1495 71.08613 19.0000 On Time FTA 04-09-2020
## 1496 79.43766 19.0000 On Time Non-FTA 28-08-2020
## 1497 73.61254 19.0000 Delayed FTA 28-01-2020
## 1498 79.50859 19.0000 Delayed FTA 10-07-2020
## 1499 77.20482 19.0000 On Time FTA 21-04-2021
## 1500 79.36665 19.0000 On Time Non-FTA 20-02-2023
## 1501 82.27724 19.0000 On Time FTA 06-10-2022
## 1502 72.53566 19.0000 On Time Non-FTA 09-07-2021
## 1503 77.39984 19.0000 On Time FTA 01-03-2020
## 1504 72.70998 19.0000 Delayed FTA 25-09-2018
## 1505 83.50004 19.0000 Delayed Non-FTA 12-03-2021
## 1506 74.71959 19.0000 On Time FTA 13-11-2024
## 1507 79.23330 19.0000 On Time Non-FTA 16-06-2024
## 1508 70.14871 19.0000 Delayed FTA 14-02-2023
## 1509 77.21468 19.0000 On Time Non-FTA 11-04-2020
## 1510 77.68636 19.0000 Delayed FTA 11-08-2020
## 1511 80.45351 19.0000 On Time Non-FTA 18-09-2020
## 1512 77.55997 19.0000 Delayed FTA 13-02-2021
## 1513 80.86418 19.0000 Delayed Non-FTA 06-10-2023
## 1514 70.22596 19.0000 On Time Non-FTA 12-09-2021
## 1515 80.96779 19.0000 Delayed Non-FTA 14-07-2019
## 1516 70.61202 19.0000 Delayed Non-FTA 21-08-2023
## 1517 75.10799 19.0000 On Time FTA 16-02-2022
## 1518 70.55857 19.0000 On Time Non-FTA 30-03-2020
## 1519 82.84789 19.0000 Delayed Non-FTA 28-10-2021
## 1520 84.89018 19.0000 Delayed Non-FTA 04-01-2018
## 1521 75.85678 19.0000 On Time FTA 04-03-2019
## 1522 80.60878 19.0000 Delayed Non-FTA 09-04-2024
## 1523 72.59294 19.0000 Delayed FTA 19-11-2019
## 1524 75.11629 19.0000 Delayed Non-FTA 18-06-2023
## 1525 70.17435 19.0000 Delayed FTA 02-12-2021
## 1526 75.54747 19.0000 On Time Non-FTA 28-03-2023
## 1527 79.15892 19.0000 On Time Non-FTA 05-12-2023
## 1528 71.24151 19.0000 On Time FTA 21-11-2023
## 1529 71.71175 19.0000 On Time Non-FTA 31-07-2018
## 1530 71.28446 19.0000 Delayed Non-FTA 24-12-2020
## 1531 80.77710 19.0000 On Time Non-FTA 22-06-2018
## 1532 76.40163 19.0000 Delayed Non-FTA 10-11-2019
## 1533 84.04946 19.0000 On Time FTA 09-10-2019
## 1534 71.72516 19.0000 On Time FTA 14-03-2020
## 1535 82.34489 19.0000 Delayed FTA 30-05-2023
## 1536 76.04952 19.0000 On Time Non-FTA 16-08-2023
## 1537 74.47780 19.0000 On Time Non-FTA 06-03-2022
## 1538 71.77694 19.0000 Delayed FTA 30-04-2019
## 1539 78.40356 19.0000 On Time FTA 14-03-2020
## 1540 73.72444 19.0000 Delayed FTA 08-12-2022
## 1541 78.87706 19.0000 On Time FTA 08-02-2021
## 1542 78.96667 19.0000 On Time FTA 15-11-2019
## 1543 73.55942 19.0000 On Time Non-FTA 31-01-2019
## 1544 74.89464 19.0000 On Time FTA 29-04-2020
## 1545 81.00567 19.0000 On Time Non-FTA 31-12-2020
## 1546 73.24262 19.0000 Delayed FTA 14-06-2018
## 1547 72.90146 19.0000 On Time Non-FTA 20-12-2018
## 1548 82.57194 19.0000 Delayed Non-FTA 07-08-2021
## 1549 82.35493 19.0000 Delayed FTA 08-11-2024
## 1550 74.22543 19.0000 Delayed FTA 20-08-2024
## 1551 72.56092 19.0000 On Time FTA 25-05-2023
## 1552 71.48635 19.0000 On Time Non-FTA 12-02-2020
## 1553 73.95284 19.0000 On Time Non-FTA 11-07-2024
## 1554 83.37677 19.0000 Delayed FTA 11-02-2024
## 1555 74.42985 19.0000 Delayed Non-FTA 27-11-2021
## 1556 83.04810 19.0000 Delayed FTA 29-10-2018
## 1557 82.77316 19.0000 On Time Non-FTA 06-01-2023
## 1558 84.90139 19.0000 Delayed Non-FTA 07-08-2019
## 1559 71.08681 19.0000 Delayed FTA 04-08-2020
## 1560 74.14201 19.0000 On Time Non-FTA 20-12-2018
## 1561 78.37830 19.0000 Delayed Non-FTA 22-04-2022
## 1562 81.05596 19.0000 Delayed FTA 01-01-2018
## 1563 81.92421 19.0000 Delayed Non-FTA 02-02-2020
## 1564 78.91188 20.0000 Delayed FTA 01-04-2020
## 1565 76.07764 20.0000 On Time Non-FTA 26-11-2021
## 1566 75.42834 20.0000 On Time Non-FTA 02-05-2024
## 1567 78.67109 20.0000 Delayed FTA 27-11-2020
## 1568 70.57193 20.0000 On Time Non-FTA 01-04-2019
## 1569 81.31202 20.0000 Delayed FTA 16-06-2018
## 1570 81.84196 20.0000 On Time FTA 26-08-2021
## 1571 76.85908 20.0000 On Time FTA 23-10-2022
## 1572 74.72191 20.0000 On Time FTA 22-07-2023
## 1573 83.02742 20.0000 On Time FTA 24-12-2018
## 1574 70.29639 20.0000 Delayed Non-FTA 07-11-2019
## 1575 74.77487 20.0000 On Time Non-FTA 06-05-2019
## 1576 79.44546 20.0000 Delayed FTA 25-03-2020
## 1577 76.34167 20.0000 Delayed FTA 16-09-2022
## 1578 80.62846 20.0000 On Time Non-FTA 12-01-2019
## 1579 84.11549 20.0000 Delayed FTA 05-07-2019
## 1580 77.46485 20.0000 On Time FTA 07-06-2020
## 1581 82.97777 20.0000 Delayed Non-FTA 06-02-2024
## 1582 72.29790 20.0000 On Time Non-FTA 09-02-2024
## 1583 73.51347 20.0000 On Time FTA 22-11-2020
## 1584 76.16274 20.0000 Delayed Non-FTA 21-10-2023
## 1585 84.15013 20.0000 Delayed FTA 22-04-2022
## 1586 71.04542 20.0000 Delayed FTA 11-11-2022
## 1587 84.43027 20.0000 On Time Non-FTA 14-06-2021
## 1588 84.69839 20.0000 On Time FTA 29-02-2020
## 1589 81.59581 20.0000 Delayed FTA 13-03-2021
## 1590 73.07544 20.0000 On Time Non-FTA 22-12-2021
## 1591 84.13795 20.0000 Delayed FTA 13-06-2024
## 1592 70.62757 20.0000 On Time FTA 07-05-2018
## 1593 75.34765 20.0000 Delayed Non-FTA 20-11-2022
## 1594 75.36178 20.0000 Delayed Non-FTA 18-04-2020
## 1595 72.56031 20.0000 On Time FTA 01-10-2021
## 1596 70.90922 20.0000 Delayed FTA 15-09-2022
## 1597 82.92740 20.0000 Delayed Non-FTA 02-04-2020
## 1598 73.94357 20.0000 Delayed Non-FTA 09-12-2020
## 1599 73.41846 20.0000 On Time FTA 20-04-2024
## 1600 79.71535 20.0000 Delayed FTA 03-12-2019
## 1601 79.56927 20.0000 On Time FTA 26-06-2021
## 1602 76.91013 20.0000 On Time Non-FTA 14-03-2023
## 1603 79.72305 20.0000 On Time FTA 22-08-2022
## 1604 82.59509 20.0000 On Time FTA 07-11-2022
## 1605 76.42641 20.0000 On Time Non-FTA 15-06-2021
## 1606 74.10545 20.0000 On Time Non-FTA 23-07-2020
## 1607 70.77953 20.0000 Delayed FTA 09-01-2019
## 1608 76.32687 20.0000 On Time Non-FTA 01-04-2019
## 1609 79.13981 20.0000 On Time FTA 25-08-2020
## 1610 75.87602 20.0000 Delayed Non-FTA 26-11-2021
## 1611 80.39982 20.0000 On Time Non-FTA 17-08-2020
## 1612 71.09006 20.0000 Delayed FTA 24-06-2024
## 1613 72.51601 20.0000 Delayed FTA 29-06-2021
## 1614 70.72815 20.0000 Delayed FTA 13-02-2022
## 1615 78.96108 20.0000 Delayed Non-FTA 10-10-2020
## 1616 77.52077 20.0000 Delayed FTA 24-09-2023
## 1617 83.64742 20.0000 On Time Non-FTA 04-05-2023
## 1618 71.38492 20.0000 On Time FTA 09-12-2022
## 1619 71.71106 20.0000 On Time Non-FTA 13-03-2021
## 1620 75.41886 20.0000 Delayed Non-FTA 24-02-2021
## 1621 72.79820 20.0000 Delayed Non-FTA 12-01-2022
## 1622 77.25896 20.0000 On Time FTA 18-02-2021
## 1623 75.77169 20.0000 Delayed Non-FTA 23-09-2020
## 1624 71.05687 20.0000 Delayed FTA 08-11-2019
## 1625 84.84823 20.0000 On Time Non-FTA 15-05-2023
## 1626 80.38496 20.0000 On Time FTA 25-11-2024
## 1627 79.58772 20.0000 Delayed Non-FTA 06-11-2019
## 1628 72.00620 20.0000 Delayed Non-FTA 20-10-2024
## 1629 74.97245 20.0000 Delayed Non-FTA 14-09-2023
## 1630 78.47435 20.0000 Delayed FTA 09-08-2022
## 1631 73.25729 20.0000 Delayed FTA 08-03-2024
## 1632 76.99584 20.0000 On Time FTA 06-05-2024
## 1633 83.76515 20.0000 Delayed Non-FTA 11-11-2021
## 1634 81.91605 20.0000 Delayed Non-FTA 04-11-2021
## 1635 73.86165 20.0000 Delayed Non-FTA 28-08-2022
## 1636 84.90130 20.0000 Delayed Non-FTA 29-07-2022
## 1637 78.12188 20.0000 Delayed Non-FTA 27-06-2023
## 1638 83.52970 20.0000 On Time Non-FTA 17-09-2020
## 1639 82.62617 20.0000 On Time Non-FTA 21-04-2022
## 1640 83.59789 20.0000 Delayed FTA 05-06-2020
## 1641 79.95654 20.0000 On Time Non-FTA 08-12-2019
## 1642 82.68901 20.0000 Delayed Non-FTA 13-08-2018
## 1643 84.82159 20.0000 On Time FTA 15-12-2019
## 1644 83.69765 20.0000 Delayed Non-FTA 25-09-2021
## 1645 82.05436 20.0000 Delayed Non-FTA 20-02-2018
## 1646 72.10798 21.0000 Delayed Non-FTA 24-03-2019
## 1647 80.67289 21.0000 Delayed Non-FTA 25-04-2022
## 1648 76.48171 21.0000 On Time Non-FTA 25-05-2019
## 1649 70.70322 21.0000 On Time Non-FTA 29-07-2024
## 1650 78.63063 21.0000 Delayed Non-FTA 14-12-2019
## 1651 83.80542 21.0000 On Time Non-FTA 30-04-2018
## 1652 80.36387 21.0000 On Time Non-FTA 14-03-2020
## 1653 70.03863 21.0000 Delayed Non-FTA 02-06-2021
## 1654 76.18308 21.0000 On Time FTA 27-03-2023
## 1655 72.71218 21.0000 Delayed Non-FTA 09-07-2019
## 1656 72.13246 21.0000 Delayed FTA 22-09-2023
## 1657 76.91124 21.0000 Delayed FTA 05-10-2024
## 1658 79.92758 21.0000 On Time Non-FTA 06-06-2022
## 1659 79.91995 21.0000 On Time FTA 16-12-2023
## 1660 74.79337 21.0000 On Time Non-FTA 09-06-2022
## 1661 80.14007 21.0000 On Time Non-FTA 15-10-2024
## 1662 84.87643 21.0000 Delayed FTA 22-11-2023
## 1663 83.83179 21.0000 On Time Non-FTA 20-01-2019
## 1664 72.46549 21.0000 Delayed Non-FTA 13-06-2018
## 1665 72.77610 21.0000 Delayed Non-FTA 20-12-2020
## 1666 75.67174 21.0000 On Time FTA 22-07-2019
## 1667 84.78803 21.0000 Delayed Non-FTA 14-02-2023
## 1668 76.57715 21.0000 Delayed FTA 08-05-2018
## 1669 80.20284 21.0000 On Time Non-FTA 15-07-2021
## 1670 78.52306 21.0000 Delayed FTA 07-09-2022
## 1671 71.61977 21.0000 On Time FTA 06-04-2021
## 1672 78.50683 21.0000 On Time Non-FTA 04-09-2021
## 1673 73.22248 21.0000 Delayed FTA 16-04-2020
## 1674 72.83658 21.0000 Delayed FTA 16-08-2024
## 1675 83.70316 21.0000 Delayed FTA 01-11-2019
## 1676 71.04091 21.0000 Delayed Non-FTA 10-11-2022
## 1677 81.56011 21.0000 Delayed FTA 14-04-2021
## 1678 77.62514 21.0000 Delayed FTA 08-03-2020
## 1679 81.03055 21.0000 Delayed Non-FTA 23-12-2022
## 1680 76.56366 21.0000 On Time Non-FTA 08-01-2019
## 1681 84.31780 21.0000 Delayed Non-FTA 28-11-2022
## 1682 83.33948 21.0000 Delayed FTA 30-03-2018
## 1683 70.06895 21.0000 Delayed FTA 01-09-2019
## 1684 74.69974 21.0000 On Time FTA 02-04-2020
## 1685 76.78052 21.0000 Delayed Non-FTA 11-07-2018
## 1686 78.14671 21.0000 On Time Non-FTA 13-08-2019
## 1687 77.58139 21.0000 Delayed Non-FTA 14-10-2019
## 1688 82.52928 21.0000 On Time Non-FTA 08-09-2022
## 1689 70.84430 21.0000 Delayed Non-FTA 04-08-2022
## 1690 72.83601 21.0000 On Time Non-FTA 04-12-2023
## 1691 84.02376 21.0000 Delayed FTA 08-12-2018
## 1692 83.30754 21.0000 Delayed Non-FTA 20-03-2019
## 1693 70.69448 21.0000 On Time FTA 05-08-2019
## 1694 80.47961 21.0000 On Time FTA 10-03-2018
## 1695 74.77401 21.0000 On Time FTA 14-06-2018
## 1696 81.05379 21.0000 Delayed Non-FTA 14-01-2023
## 1697 72.46561 21.0000 Delayed FTA 27-11-2019
## 1698 79.40176 21.0000 On Time Non-FTA 28-07-2023
## 1699 74.40467 21.0000 Delayed FTA 23-11-2023
## 1700 75.34681 21.0000 Delayed Non-FTA 20-05-2024
## 1701 81.18533 21.0000 Delayed Non-FTA 10-01-2020
## 1702 79.49090 21.0000 On Time FTA 13-01-2024
## 1703 80.70589 21.0000 On Time Non-FTA 04-03-2024
## 1704 78.31938 21.0000 Delayed Non-FTA 13-04-2020
## 1705 82.72606 21.0000 On Time Non-FTA 23-08-2023
## 1706 79.58202 21.0000 On Time FTA 27-03-2018
## 1707 76.21946 21.0000 Delayed Non-FTA 13-06-2018
## 1708 75.30703 21.0000 On Time FTA 03-03-2020
## 1709 78.77419 21.0000 Delayed FTA 22-01-2024
## 1710 76.66170 21.0000 Delayed FTA 12-06-2021
## 1711 70.81723 21.0000 On Time FTA 23-10-2018
## 1712 82.28567 21.0000 Delayed Non-FTA 11-04-2024
## 1713 80.24419 21.0000 Delayed FTA 14-02-2020
## 1714 78.16160 21.0000 On Time Non-FTA 22-09-2023
## 1715 73.76738 21.0000 Delayed FTA 11-10-2022
## 1716 78.15549 21.0000 On Time Non-FTA 02-03-2024
## 1717 80.38101 21.0000 On Time FTA 19-05-2023
## 1718 76.20278 21.0000 Delayed FTA 26-12-2020
## 1719 82.86498 21.0000 Delayed Non-FTA 22-08-2023
## 1720 77.57753 21.0000 On Time Non-FTA 18-10-2023
## 1721 77.79127 21.0000 On Time Non-FTA 22-11-2021
## 1722 70.70776 21.0000 Delayed FTA 10-08-2024
## 1723 73.55016 21.0000 Delayed FTA 14-04-2024
## 1724 70.49075 21.0000 Delayed Non-FTA 30-12-2022
## 1725 73.23849 21.0000 On Time Non-FTA 29-02-2024
## 1726 83.63777 21.0000 On Time FTA 26-12-2020
## 1727 83.74180 21.0000 On Time Non-FTA 23-06-2024
## 1728 71.04990 21.0000 On Time Non-FTA 07-07-2023
## 1729 76.43142 21.0000 Delayed FTA 10-08-2020
## 1730 72.28655 21.0000 Delayed FTA 20-02-2021
## 1731 84.52298 21.0000 On Time Non-FTA 22-12-2019
## 1732 72.04134 21.0000 On Time FTA 05-08-2024
## 1733 75.94753 21.0000 On Time Non-FTA 04-10-2023
## 1734 74.06145 21.0000 Delayed Non-FTA 26-11-2018
## 1735 75.92385 21.0000 On Time Non-FTA 25-09-2024
## 1736 73.70586 22.0000 On Time FTA 30-11-2018
## 1737 71.40248 22.0000 Delayed Non-FTA 16-01-2022
## 1738 82.62163 22.0000 Delayed FTA 14-09-2021
## 1739 84.98696 22.0000 On Time FTA 13-05-2021
## 1740 77.49064 22.0000 On Time FTA 27-04-2019
## 1741 70.19353 22.0000 On Time FTA 16-09-2023
## 1742 78.42345 22.0000 Delayed FTA 25-07-2023
## 1743 84.88850 22.0000 On Time Non-FTA 24-03-2022
## 1744 78.02267 22.0000 On Time FTA 20-08-2019
## 1745 72.61964 22.0000 On Time FTA 21-08-2024
## 1746 72.11201 22.0000 Delayed FTA 15-12-2024
## 1747 83.42888 22.0000 On Time Non-FTA 26-07-2020
## 1748 81.77329 22.0000 On Time Non-FTA 08-08-2019
## 1749 72.91240 22.0000 Delayed FTA 30-06-2018
## 1750 79.05813 22.0000 On Time Non-FTA 30-05-2019
## 1751 77.66724 22.0000 Delayed FTA 11-01-2021
## 1752 75.37728 22.0000 On Time Non-FTA 09-04-2023
## 1753 76.00090 22.0000 On Time Non-FTA 23-10-2020
## 1754 84.66510 22.0000 On Time Non-FTA 19-04-2018
## 1755 70.79951 22.0000 Delayed FTA 07-02-2023
## 1756 78.16965 22.0000 On Time FTA 28-03-2023
## 1757 83.47899 22.0000 On Time Non-FTA 10-12-2023
## 1758 82.63491 22.0000 On Time FTA 14-12-2023
## 1759 78.12935 22.0000 Delayed FTA 02-08-2021
## 1760 76.07128 22.0000 Delayed Non-FTA 10-07-2022
## 1761 77.04706 22.0000 On Time FTA 29-12-2018
## 1762 80.43331 22.0000 On Time FTA 11-04-2018
## 1763 71.65580 22.0000 Delayed FTA 09-02-2018
## 1764 71.68001 22.0000 Delayed FTA 30-08-2018
## 1765 76.83727 22.0000 Delayed FTA 01-09-2021
## 1766 76.48132 22.0000 On Time FTA 25-05-2019
## 1767 73.03791 22.0000 Delayed Non-FTA 07-05-2019
## 1768 74.44467 22.0000 Delayed FTA 08-05-2023
## 1769 84.87904 22.0000 Delayed Non-FTA 07-04-2024
## 1770 79.33953 22.0000 On Time FTA 15-04-2024
## 1771 71.57496 22.0000 Delayed FTA 12-09-2024
## 1772 71.42204 22.0000 Delayed FTA 09-05-2018
## 1773 84.89949 22.0000 Delayed FTA 03-12-2018
## 1774 72.23476 22.0000 On Time FTA 29-10-2023
## 1775 74.91260 22.0000 On Time FTA 12-01-2019
## 1776 80.51994 22.0000 On Time Non-FTA 30-05-2023
## 1777 75.38775 22.0000 On Time Non-FTA 05-03-2020
## 1778 82.34015 22.0000 Delayed Non-FTA 19-12-2024
## 1779 81.40074 22.0000 Delayed Non-FTA 10-12-2023
## 1780 71.59637 22.0000 On Time FTA 08-12-2020
## 1781 81.09107 22.0000 Delayed Non-FTA 13-01-2018
## 1782 70.04384 22.0000 Delayed FTA 14-09-2020
## 1783 74.55032 22.0000 On Time Non-FTA 27-11-2019
## 1784 74.20800 22.0000 Delayed FTA 15-06-2019
## 1785 75.83972 22.0000 On Time Non-FTA 06-11-2024
## 1786 84.34138 22.0000 On Time Non-FTA 13-04-2023
## 1787 80.31262 22.0000 Delayed Non-FTA 26-06-2022
## 1788 70.71896 22.0000 Delayed Non-FTA 25-08-2021
## 1789 83.04800 22.0000 On Time Non-FTA 28-01-2024
## 1790 80.71468 22.0000 Delayed FTA 30-10-2021
## 1791 83.64172 22.0000 Delayed FTA 14-04-2023
## 1792 72.87399 22.0000 Delayed Non-FTA 12-11-2024
## 1793 75.26821 22.0000 Delayed FTA 10-07-2020
## 1794 75.39923 22.0000 Delayed Non-FTA 27-07-2019
## 1795 77.50551 22.0000 On Time Non-FTA 08-10-2019
## 1796 78.18871 22.0000 On Time FTA 06-03-2024
## 1797 84.15643 22.0000 On Time Non-FTA 16-12-2019
## 1798 75.76163 22.0000 On Time Non-FTA 25-09-2023
## 1799 76.68132 22.0000 Delayed Non-FTA 19-05-2023
## 1800 70.33763 22.0000 On Time FTA 10-08-2021
## 1801 80.51142 22.0000 Delayed FTA 05-05-2024
## 1802 77.30160 22.0000 Delayed Non-FTA 07-05-2023
## 1803 70.73429 22.0000 On Time FTA 08-07-2024
## 1804 70.80189 22.0000 On Time Non-FTA 09-10-2023
## 1805 71.50063 22.0000 Delayed FTA 05-07-2023
## 1806 72.77274 22.0000 On Time Non-FTA 14-06-2020
## 1807 77.96816 23.0000 Delayed FTA 04-04-2023
## 1808 72.19313 23.0000 On Time Non-FTA 13-10-2022
## 1809 72.40437 23.0000 On Time Non-FTA 07-07-2019
## 1810 70.11756 23.0000 Delayed Non-FTA 07-03-2024
## 1811 70.48706 23.0000 Delayed FTA 01-10-2019
## 1812 78.28068 23.0000 On Time Non-FTA 27-03-2019
## 1813 73.09115 23.0000 On Time Non-FTA 12-06-2024
## 1814 81.38451 23.0000 On Time Non-FTA 11-01-2022
## 1815 72.90174 23.0000 On Time Non-FTA 15-06-2023
## 1816 71.21858 23.0000 Delayed FTA 16-11-2024
## 1817 78.72575 23.0000 Delayed Non-FTA 01-07-2019
## 1818 84.48208 23.0000 On Time Non-FTA 05-06-2020
## 1819 71.29854 23.0000 Delayed Non-FTA 09-12-2018
## 1820 74.64450 23.0000 On Time Non-FTA 15-02-2018
## 1821 76.66545 23.0000 Delayed Non-FTA 15-06-2023
## 1822 84.96098 23.0000 On Time FTA 22-11-2023
## 1823 70.75471 23.0000 On Time FTA 04-07-2021
## 1824 82.15421 23.0000 Delayed Non-FTA 05-08-2020
## 1825 77.32873 23.0000 Delayed FTA 14-01-2021
## 1826 77.99489 23.0000 On Time FTA 27-07-2022
## 1827 80.67653 23.0000 Delayed FTA 04-07-2019
## 1828 80.57255 23.0000 Delayed Non-FTA 30-07-2024
## 1829 83.22336 23.0000 On Time Non-FTA 18-08-2020
## 1830 81.83824 23.0000 On Time FTA 03-08-2022
## 1831 84.82181 23.0000 On Time FTA 30-04-2020
## 1832 73.73945 23.0000 On Time Non-FTA 28-09-2022
## 1833 82.39299 23.0000 On Time FTA 19-12-2021
## 1834 79.66583 23.0000 Delayed FTA 23-06-2018
## 1835 72.56212 23.0000 Delayed Non-FTA 21-08-2018
## 1836 78.37952 23.0000 Delayed FTA 28-08-2020
## 1837 79.83633 23.0000 Delayed Non-FTA 13-02-2020
## 1838 80.69554 23.0000 On Time Non-FTA 29-11-2023
## 1839 72.01009 23.0000 Delayed Non-FTA 07-05-2022
## 1840 82.07390 23.0000 Delayed FTA 25-06-2019
## 1841 78.04357 23.0000 On Time Non-FTA 24-11-2020
## 1842 71.80268 23.0000 Delayed Non-FTA 06-12-2018
## 1843 74.06662 23.0000 Delayed FTA 20-05-2023
## 1844 71.14690 23.0000 Delayed Non-FTA 06-06-2024
## 1845 74.61268 23.0000 On Time Non-FTA 12-11-2019
## 1846 80.21848 23.0000 On Time FTA 12-11-2022
## 1847 82.74865 23.0000 On Time Non-FTA 26-05-2022
## 1848 75.30857 23.0000 Delayed FTA 11-01-2023
## 1849 74.87805 23.0000 On Time Non-FTA 20-10-2023
## 1850 77.85491 23.0000 On Time FTA 27-04-2022
## 1851 70.51323 23.0000 On Time FTA 03-09-2020
## 1852 77.59955 23.0000 On Time Non-FTA 22-10-2022
## 1853 83.94738 23.0000 Delayed Non-FTA 09-09-2021
## 1854 81.28547 23.0000 Delayed Non-FTA 18-09-2022
## 1855 82.03975 23.0000 Delayed Non-FTA 15-10-2023
## 1856 73.04454 23.0000 On Time Non-FTA 08-07-2019
## 1857 81.24306 23.0000 On Time FTA 05-03-2019
## 1858 76.66729 23.0000 On Time Non-FTA 08-07-2024
## 1859 73.10436 23.0000 On Time FTA 13-01-2024
## 1860 70.99352 23.0000 Delayed Non-FTA 26-04-2019
## 1861 81.34153 23.0000 Delayed Non-FTA 06-07-2022
## 1862 77.26405 23.0000 On Time Non-FTA 05-02-2020
## 1863 71.78309 23.0000 Delayed FTA 29-11-2021
## 1864 78.38192 23.0000 Delayed FTA 28-05-2022
## 1865 80.84136 23.0000 Delayed FTA 21-06-2022
## 1866 82.66602 23.0000 Delayed FTA 15-09-2018
## 1867 76.55455 23.0000 Delayed FTA 11-08-2020
## 1868 75.90842 23.0000 On Time Non-FTA 19-02-2024
## 1869 75.94577 23.0000 On Time Non-FTA 23-03-2018
## 1870 76.08649 23.0000 On Time FTA 08-10-2022
## 1871 84.98715 23.0000 On Time FTA 28-09-2021
## 1872 74.22100 23.0000 Delayed FTA 10-05-2021
## 1873 82.98081 23.0000 Delayed FTA 19-05-2023
## 1874 72.59653 23.0000 On Time Non-FTA 04-03-2024
## 1875 73.37082 23.0000 On Time FTA 31-10-2020
## 1876 82.41997 23.0000 Delayed FTA 18-12-2021
## 1877 74.78858 23.0000 On Time Non-FTA 12-01-2018
## 1878 75.49661 23.0000 Delayed FTA 08-06-2019
## 1879 77.09869 23.0000 On Time Non-FTA 10-02-2023
## 1880 76.49765 23.0000 Delayed FTA 26-01-2023
## 1881 83.54634 23.0000 Delayed FTA 10-09-2021
## 1882 74.50358 23.0000 Delayed FTA 11-05-2021
## 1883 71.75080 23.0000 On Time Non-FTA 23-09-2024
## 1884 73.89785 23.0000 Delayed Non-FTA 12-02-2024
## 1885 78.09299 23.0000 On Time Non-FTA 15-11-2020
## 1886 78.19202 23.0000 On Time FTA 28-01-2023
## 1887 84.48641 23.0000 On Time Non-FTA 25-01-2023
## 1888 73.87511 23.0000 On Time FTA 21-11-2021
## 1889 74.60207 23.0000 On Time FTA 28-07-2018
## 1890 78.41345 23.0000 On Time FTA 28-08-2023
## 1891 82.95784 23.0000 On Time FTA 10-08-2024
## 1892 80.75647 23.0000 Delayed Non-FTA 05-03-2018
## 1893 74.35088 23.0000 On Time Non-FTA 12-07-2021
## 1894 79.20774 23.0000 Delayed FTA 07-04-2018
## 1895 77.46793 23.0000 Delayed Non-FTA 05-04-2021
## 1896 78.94277 23.0000 On Time Non-FTA 04-05-2020
## 1897 77.24028 23.0000 Delayed Non-FTA 29-01-2018
## 1898 73.73082 23.0000 Delayed Non-FTA 30-03-2022
## 1899 76.72572 23.0000 Delayed Non-FTA 23-10-2020
## 1900 70.40955 23.0000 On Time FTA 04-02-2023
## 1901 72.95553 23.0000 On Time Non-FTA 16-03-2022
## 1902 84.48190 23.0000 Delayed FTA 02-12-2019
## 1903 83.15373 23.0000 Delayed Non-FTA 29-07-2024
## 1904 82.72099 23.0000 On Time Non-FTA 15-04-2024
## 1905 77.53988 23.0000 On Time FTA 16-07-2023
## 1906 74.42373 23.0000 On Time Non-FTA 26-09-2022
## 1907 83.96736 23.0000 Delayed Non-FTA 09-03-2020
## 1908 77.11409 23.0000 Delayed Non-FTA 19-04-2024
## 1909 72.05115 23.0000 Delayed Non-FTA 10-06-2020
## 1910 77.98541 23.0000 On Time FTA 12-02-2023
## 1911 74.94972 23.0000 On Time FTA 10-04-2024
## 1912 84.88482 24.0000 On Time Non-FTA 27-12-2022
## 1913 75.04471 24.0000 On Time FTA 07-05-2024
## 1914 79.82735 24.0000 On Time Non-FTA 01-04-2019
## 1915 73.59799 24.0000 On Time Non-FTA 12-08-2018
## 1916 84.38110 24.0000 Delayed FTA 19-10-2022
## 1917 82.97007 24.0000 Delayed FTA 27-07-2020
## 1918 72.08120 24.0000 On Time FTA 13-03-2022
## 1919 72.65408 24.0000 Delayed FTA 11-12-2018
## 1920 82.65233 24.0000 Delayed FTA 02-03-2024
## 1921 72.55018 24.0000 Delayed FTA 20-09-2023
## 1922 75.17313 24.0000 Delayed FTA 10-02-2018
## 1923 81.14138 24.0000 On Time Non-FTA 06-08-2020
## 1924 75.34682 24.0000 On Time FTA 20-09-2019
## 1925 83.56618 24.0000 Delayed Non-FTA 25-10-2024
## 1926 76.65378 24.0000 On Time FTA 04-09-2020
## 1927 83.08373 24.0000 On Time FTA 02-12-2019
## 1928 74.37279 24.0000 Delayed FTA 05-07-2019
## 1929 72.92112 24.0000 On Time FTA 01-11-2018
## 1930 78.02258 24.0000 Delayed FTA 29-12-2020
## 1931 70.10225 24.0000 Delayed FTA 06-11-2022
## 1932 71.40500 24.0000 Delayed FTA 21-05-2019
## 1933 79.71828 24.0000 On Time FTA 13-07-2020
## 1934 73.08575 24.0000 Delayed FTA 13-04-2018
## 1935 81.32145 24.0000 Delayed FTA 21-03-2021
## 1936 72.64909 24.0000 On Time FTA 23-12-2024
## 1937 74.81434 24.0000 On Time Non-FTA 02-01-2019
## 1938 77.78508 24.0000 Delayed FTA 05-03-2018
## 1939 74.83600 24.0000 On Time FTA 04-07-2018
## 1940 75.92473 24.0000 On Time Non-FTA 25-04-2020
## 1941 78.85661 24.0000 On Time FTA 16-04-2018
## 1942 79.30999 24.0000 Delayed Non-FTA 05-07-2022
## 1943 73.50778 24.0000 On Time FTA 22-10-2024
## 1944 83.63302 24.0000 On Time Non-FTA 20-07-2022
## 1945 74.04224 24.0000 On Time FTA 27-08-2018
## 1946 79.72326 24.0000 Delayed FTA 12-07-2018
## 1947 71.18355 24.0000 Delayed FTA 15-02-2022
## 1948 74.49752 24.0000 On Time Non-FTA 18-04-2024
## 1949 83.99230 24.0000 On Time Non-FTA 19-09-2019
## 1950 84.43159 24.0000 Delayed FTA 11-11-2022
## 1951 71.62088 24.0000 Delayed Non-FTA 15-05-2022
## 1952 72.44585 24.0000 On Time Non-FTA 03-05-2022
## 1953 80.62713 24.0000 On Time Non-FTA 05-12-2019
## 1954 82.18268 24.0000 Delayed Non-FTA 29-03-2019
## 1955 82.62072 24.0000 On Time Non-FTA 28-06-2024
## 1956 81.97552 24.0000 On Time Non-FTA 28-01-2023
## 1957 80.93885 24.0000 On Time Non-FTA 15-04-2018
## 1958 76.37574 24.0000 Delayed FTA 05-03-2023
## 1959 84.35251 24.0000 On Time Non-FTA 14-03-2021
## 1960 70.28490 24.0000 On Time FTA 21-03-2018
## 1961 78.98167 24.0000 Delayed Non-FTA 20-09-2023
## 1962 82.02994 24.0000 On Time Non-FTA 03-10-2024
## 1963 73.35508 24.0000 Delayed Non-FTA 28-12-2023
## 1964 71.80665 24.0000 Delayed Non-FTA 12-05-2023
## 1965 71.72211 24.0000 Delayed FTA 21-12-2020
## 1966 83.73628 24.0000 On Time FTA 31-08-2019
## 1967 70.48292 24.0000 On Time Non-FTA 29-09-2018
## 1968 84.24868 24.0000 Delayed Non-FTA 22-12-2023
## 1969 73.54551 24.0000 Delayed Non-FTA 16-01-2019
## 1970 76.72956 24.0000 Delayed Non-FTA 25-09-2019
## 1971 75.02513 24.0000 Delayed Non-FTA 08-12-2022
## 1972 84.73613 24.0000 On Time Non-FTA 01-11-2020
## 1973 84.01551 24.0000 On Time Non-FTA 18-05-2019
## 1974 74.04503 24.0000 Delayed Non-FTA 26-05-2019
## 1975 77.66628 24.0000 Delayed Non-FTA 20-05-2021
## 1976 77.20603 24.0000 Delayed FTA 14-07-2020
## 1977 73.31261 24.0000 Delayed Non-FTA 26-11-2023
## 1978 72.60358 24.0000 On Time Non-FTA 12-03-2024
## 1979 84.48497 24.0000 On Time FTA 10-05-2020
## 1980 84.50883 24.0000 On Time Non-FTA 04-01-2024
## 1981 78.26386 24.0000 On Time FTA 08-09-2021
## 1982 78.70199 24.0000 On Time Non-FTA 06-05-2023
## 1983 75.83484 24.0000 Delayed Non-FTA 06-12-2020
## 1984 76.72264 24.0000 Delayed FTA 01-04-2023
## 1985 76.21062 24.0000 Delayed Non-FTA 29-05-2021
## 1986 80.07238 24.0000 On Time FTA 22-06-2022
## 1987 82.65794 24.0000 On Time FTA 14-05-2021
## 1988 76.01469 24.0000 On Time Non-FTA 15-12-2021
## 1989 70.25209 24.0000 Delayed Non-FTA 03-05-2023
## 1990 72.41852 24.0000 On Time FTA 01-08-2022
## 1991 75.30953 24.0000 On Time Non-FTA 01-06-2020
## 1992 82.63706 24.0000 Delayed Non-FTA 22-02-2021
## 1993 70.40056 24.0000 Delayed Non-FTA 23-08-2023
## 1994 81.36218 24.0000 Delayed FTA 29-10-2019
## 1995 71.44627 24.0000 On Time Non-FTA 08-08-2021
## 1996 73.74737 24.0000 Delayed FTA 27-08-2024
## 1997 76.02245 24.0000 On Time FTA 21-12-2019
## 1998 83.17597 24.0000 Delayed FTA 27-12-2022
## 1999 78.73046 24.0000 On Time FTA 03-07-2019
## 2000 75.73868 24.0000 On Time Non-FTA 18-08-2023
## 2001 84.04671 24.0000 On Time FTA 18-03-2021
## 2002 82.23102 24.0000 Delayed FTA 12-07-2019
## 2003 71.51720 25.0000 On Time Non-FTA 07-12-2022
## 2004 77.72281 25.0000 Delayed FTA 06-04-2021
## 2005 74.43500 25.0000 Delayed FTA 18-09-2019
## 2006 82.87687 25.0000 On Time FTA 11-12-2018
## 2007 71.31080 25.0000 Delayed Non-FTA 29-12-2018
## 2008 75.15139 25.0000 On Time FTA 18-04-2018
## 2009 75.62083 25.0000 Delayed FTA 29-05-2018
## 2010 80.78279 25.0000 On Time FTA 10-06-2024
## 2011 83.63168 25.0000 On Time Non-FTA 27-04-2018
## 2012 70.39137 25.0000 On Time Non-FTA 02-06-2018
## 2013 83.80106 25.0000 On Time Non-FTA 13-12-2018
## 2014 70.80975 25.0000 On Time Non-FTA 05-06-2023
## 2015 75.23089 25.0000 Delayed FTA 03-04-2021
## 2016 75.52041 25.0000 On Time Non-FTA 28-12-2024
## 2017 81.20015 25.0000 Delayed FTA 07-02-2021
## 2018 82.13408 25.0000 Delayed FTA 17-02-2021
## 2019 71.80294 25.0000 Delayed FTA 03-05-2022
## 2020 79.32654 25.0000 On Time FTA 07-04-2024
## 2021 80.51001 25.0000 Delayed FTA 02-04-2019
## 2022 80.24710 25.0000 Delayed FTA 02-04-2023
## 2023 76.24662 25.0000 On Time Non-FTA 11-03-2020
## 2024 76.98430 25.0000 On Time Non-FTA 08-08-2022
## 2025 84.46642 25.0000 On Time FTA 05-06-2023
## 2026 70.72563 25.0000 Delayed FTA 16-10-2022
## 2027 73.79247 25.0000 On Time Non-FTA 27-05-2022
## 2028 79.74443 25.0000 On Time FTA 12-06-2022
## 2029 77.18669 25.0000 On Time Non-FTA 10-08-2023
## 2030 81.62209 25.0000 Delayed Non-FTA 02-01-2019
## 2031 83.63000 25.0000 Delayed Non-FTA 26-01-2020
## 2032 78.40010 25.0000 On Time Non-FTA 17-11-2021
## 2033 81.61449 25.0000 Delayed Non-FTA 23-02-2020
## 2034 73.19008 25.0000 On Time FTA 24-11-2021
## 2035 78.67141 25.0000 On Time Non-FTA 22-10-2022
## 2036 78.25138 25.0000 On Time FTA 15-03-2019
## 2037 84.15790 25.0000 On Time FTA 23-02-2018
## 2038 73.75099 25.0000 On Time FTA 03-05-2018
## 2039 84.03611 25.0000 Delayed FTA 14-11-2024
## 2040 82.54376 25.0000 On Time Non-FTA 15-08-2023
## 2041 75.56315 25.0000 On Time Non-FTA 10-10-2022
## 2042 70.02637 25.0000 On Time FTA 03-10-2023
## 2043 73.34353 25.0000 On Time Non-FTA 12-10-2020
## 2044 75.01948 25.0000 On Time Non-FTA 06-09-2018
## 2045 76.02928 25.0000 Delayed Non-FTA 02-05-2022
## 2046 73.11632 25.0000 Delayed FTA 30-05-2022
## 2047 74.94605 25.0000 On Time FTA 06-03-2019
## 2048 78.34618 25.0000 Delayed Non-FTA 05-01-2023
## 2049 81.06193 25.0000 On Time Non-FTA 12-08-2018
## 2050 71.34393 25.0000 On Time Non-FTA 10-04-2018
## 2051 82.72438 25.0000 On Time Non-FTA 29-10-2020
## 2052 71.40880 25.0000 On Time Non-FTA 08-06-2019
## 2053 75.68707 25.0000 On Time FTA 03-07-2018
## 2054 79.48247 25.0000 On Time FTA 26-06-2021
## 2055 80.68081 25.0000 On Time Non-FTA 15-02-2024
## 2056 73.30229 25.0000 On Time Non-FTA 08-10-2022
## 2057 73.78066 25.0000 On Time Non-FTA 27-01-2022
## 2058 70.08001 25.0000 On Time FTA 14-02-2022
## 2059 70.36570 25.0000 Delayed Non-FTA 03-02-2023
## 2060 80.25662 25.0000 Delayed Non-FTA 28-04-2024
## 2061 77.80456 25.0000 Delayed FTA 01-05-2023
## 2062 77.32271 25.0000 Delayed Non-FTA 14-06-2018
## 2063 81.43094 25.0000 On Time FTA 27-01-2021
## 2064 82.47172 25.0000 Delayed FTA 29-09-2023
## 2065 72.30958 25.0000 On Time FTA 24-09-2021
## 2066 77.38790 25.0000 On Time FTA 11-05-2024
## 2067 70.87840 25.0000 On Time Non-FTA 15-12-2021
## 2068 78.87157 25.0000 Delayed FTA 26-03-2024
## 2069 81.54090 25.0000 Delayed Non-FTA 07-07-2024
## 2070 74.21170 25.0000 Delayed FTA 19-11-2019
## 2071 75.90986 25.0000 Delayed FTA 27-12-2023
## 2072 84.70135 26.0000 On Time FTA 05-08-2021
## 2073 81.39674 26.0000 On Time Non-FTA 08-12-2019
## 2074 81.39947 26.0000 On Time FTA 08-06-2023
## 2075 75.51236 26.0000 Delayed Non-FTA 12-01-2021
## 2076 82.33828 26.0000 On Time Non-FTA 27-06-2023
## 2077 77.76794 26.0000 On Time FTA 22-05-2021
## 2078 73.53652 26.0000 Delayed Non-FTA 12-12-2020
## 2079 71.53894 26.0000 On Time Non-FTA 17-05-2020
## 2080 75.87476 26.0000 On Time FTA 05-08-2024
## 2081 73.86110 26.0000 Delayed Non-FTA 09-06-2023
## 2082 72.36732 26.0000 On Time Non-FTA 03-12-2022
## 2083 80.43399 26.0000 On Time Non-FTA 14-05-2018
## 2084 72.16284 26.0000 On Time FTA 27-04-2023
## 2085 84.21656 26.0000 On Time FTA 22-07-2023
## 2086 73.47294 26.0000 On Time FTA 24-01-2024
## 2087 78.63594 26.0000 Delayed Non-FTA 03-05-2022
## 2088 83.20807 26.0000 Delayed FTA 08-10-2018
## 2089 77.58255 26.0000 On Time FTA 14-05-2018
## 2090 83.47324 26.0000 On Time FTA 18-11-2019
## 2091 74.67338 26.0000 On Time FTA 08-06-2021
## 2092 78.48081 26.0000 Delayed Non-FTA 14-03-2024
## 2093 79.88038 26.0000 Delayed FTA 04-09-2024
## 2094 75.04375 26.0000 Delayed Non-FTA 19-07-2023
## 2095 73.05060 26.0000 On Time FTA 26-01-2020
## 2096 82.33669 26.0000 On Time FTA 11-09-2023
## 2097 75.45265 26.0000 On Time FTA 22-02-2024
## 2098 78.95024 26.0000 Delayed FTA 27-09-2019
## 2099 73.40481 26.0000 On Time FTA 15-07-2019
## 2100 74.91083 26.0000 Delayed FTA 20-10-2019
## 2101 83.28652 26.0000 On Time FTA 29-11-2018
## 2102 80.48986 26.0000 On Time Non-FTA 28-07-2020
## 2103 76.62075 26.0000 Delayed Non-FTA 05-05-2024
## 2104 72.25167 26.0000 On Time Non-FTA 17-01-2018
## 2105 78.70732 26.0000 On Time Non-FTA 14-07-2023
## 2106 72.88360 26.0000 Delayed FTA 18-11-2021
## 2107 80.91728 26.0000 Delayed FTA 14-10-2022
## 2108 74.06370 26.0000 On Time Non-FTA 24-05-2018
## 2109 71.25600 26.0000 Delayed FTA 14-10-2022
## 2110 83.35518 26.0000 On Time FTA 24-12-2024
## 2111 76.89779 26.0000 Delayed FTA 06-10-2022
## 2112 82.95777 26.0000 On Time FTA 03-02-2019
## 2113 78.24691 26.0000 On Time Non-FTA 17-07-2019
## 2114 84.69967 26.0000 Delayed Non-FTA 08-08-2019
## 2115 75.59431 26.0000 Delayed Non-FTA 03-11-2022
## 2116 83.16011 26.0000 On Time FTA 13-10-2023
## 2117 73.81031 26.0000 Delayed Non-FTA 03-06-2022
## 2118 70.50698 26.0000 Delayed FTA 23-02-2018
## 2119 82.32606 26.0000 On Time Non-FTA 07-03-2024
## 2120 74.45330 26.0000 Delayed Non-FTA 29-10-2024
## 2121 77.59279 26.0000 On Time FTA 18-12-2024
## 2122 71.26862 26.0000 Delayed FTA 01-08-2020
## 2123 76.34549 26.0000 On Time Non-FTA 10-11-2022
## 2124 76.21927 26.0000 On Time FTA 23-02-2023
## 2125 76.08060 26.0000 Delayed Non-FTA 29-06-2018
## 2126 71.58704 26.0000 Delayed Non-FTA 23-04-2024
## 2127 79.33632 26.0000 On Time FTA 28-09-2021
## 2128 72.86911 26.0000 On Time Non-FTA 11-11-2018
## 2129 81.33376 26.0000 On Time FTA 21-03-2021
## 2130 81.51296 26.0000 Delayed FTA 24-03-2023
## 2131 79.34299 26.0000 On Time Non-FTA 21-03-2022
## 2132 81.10269 26.0000 On Time FTA 16-12-2024
## 2133 75.80767 26.0000 On Time FTA 30-01-2020
## 2134 84.78703 26.0000 On Time Non-FTA 08-08-2024
## 2135 77.20961 26.0000 Delayed FTA 27-11-2021
## 2136 83.49543 26.0000 On Time FTA 07-12-2024
## 2137 74.67911 26.0000 On Time FTA 26-09-2024
## 2138 73.01033 26.0000 On Time Non-FTA 05-09-2018
## 2139 77.08814 26.0000 On Time FTA 06-04-2024
## 2140 75.22428 26.0000 Delayed Non-FTA 22-12-2023
## 2141 72.35688 26.0000 On Time Non-FTA 07-07-2022
## 2142 79.67511 26.0000 Delayed Non-FTA 23-04-2018
## 2143 77.36764 26.0000 On Time Non-FTA 20-05-2024
## 2144 80.38996 26.0000 On Time FTA 30-10-2024
## 2145 72.24083 26.0000 Delayed FTA 15-12-2021
## 2146 76.54000 26.0000 On Time Non-FTA 15-08-2018
## 2147 84.33844 26.0000 Delayed FTA 29-04-2024
## 2148 75.55548 26.0000 Delayed FTA 15-07-2024
## 2149 84.43940 26.0000 On Time Non-FTA 08-12-2022
## 2150 79.42431 26.0000 Delayed Non-FTA 09-12-2018
## 2151 74.05969 26.0000 On Time Non-FTA 16-08-2018
## 2152 83.32891 26.0000 Delayed Non-FTA 19-06-2022
## 2153 83.50003 26.0000 On Time FTA 15-04-2021
## 2154 73.98574 26.0000 Delayed FTA 03-05-2022
## 2155 83.02121 26.0000 On Time FTA 02-12-2018
## 2156 79.95610 26.0000 On Time FTA 27-09-2023
## 2157 80.09292 26.0000 Delayed FTA 19-10-2023
## 2158 76.63808 26.0000 On Time FTA 03-06-2022
## 2159 78.52563 26.0000 Delayed Non-FTA 02-07-2023
## 2160 81.69822 26.0000 On Time Non-FTA 24-01-2019
## 2161 80.83574 26.0000 On Time Non-FTA 12-03-2022
## 2162 77.11515 26.0000 On Time Non-FTA 05-01-2020
## 2163 78.70606 26.0000 On Time FTA 17-05-2019
## 2164 75.30388 26.0000 On Time Non-FTA 11-07-2019
## 2165 83.51897 26.0000 Delayed FTA 23-05-2019
## 2166 70.35042 26.0000 Delayed Non-FTA 03-07-2023
## 2167 79.16040 26.0000 Delayed FTA 05-07-2024
## 2168 80.16054 27.0000 Delayed FTA 15-10-2022
## 2169 75.74102 27.0000 On Time FTA 22-05-2018
## 2170 81.13934 27.0000 Delayed Non-FTA 12-01-2023
## 2171 78.39525 27.0000 Delayed FTA 02-01-2022
## 2172 76.73305 27.0000 On Time Non-FTA 11-02-2022
## 2173 77.27444 27.0000 On Time Non-FTA 24-10-2020
## 2174 75.76261 27.0000 Delayed FTA 12-05-2021
## 2175 70.32687 27.0000 On Time Non-FTA 16-06-2024
## 2176 84.95571 27.0000 Delayed Non-FTA 19-06-2023
## 2177 75.13894 27.0000 Delayed FTA 03-11-2021
## 2178 75.36728 27.0000 Delayed Non-FTA 23-04-2022
## 2179 81.44301 27.0000 Delayed FTA 11-05-2023
## 2180 82.09624 27.0000 Delayed FTA 16-04-2022
## 2181 81.72050 27.0000 Delayed FTA 02-02-2021
## 2182 74.97477 27.0000 Delayed FTA 14-08-2020
## 2183 79.55184 27.0000 On Time FTA 24-12-2022
## 2184 78.56085 27.0000 Delayed Non-FTA 19-09-2022
## 2185 82.86400 27.0000 Delayed FTA 05-04-2021
## 2186 75.45881 27.0000 On Time Non-FTA 09-06-2021
## 2187 83.11790 27.0000 On Time Non-FTA 11-02-2022
## 2188 72.14375 27.0000 Delayed FTA 16-12-2024
## 2189 76.17933 27.0000 Delayed Non-FTA 20-01-2021
## 2190 84.92990 27.0000 On Time Non-FTA 18-06-2024
## 2191 76.05765 27.0000 On Time Non-FTA 17-04-2024
## 2192 82.43443 27.0000 Delayed Non-FTA 04-11-2018
## 2193 75.45141 27.0000 On Time FTA 21-07-2018
## 2194 71.06139 27.0000 Delayed Non-FTA 09-12-2020
## 2195 76.26831 27.0000 Delayed Non-FTA 30-07-2020
## 2196 72.23262 27.0000 Delayed Non-FTA 23-12-2023
## 2197 71.79233 27.0000 On Time FTA 03-12-2021
## 2198 72.53717 27.0000 On Time Non-FTA 03-02-2021
## 2199 84.13403 27.0000 Delayed Non-FTA 30-04-2019
## 2200 72.42444 27.0000 Delayed Non-FTA 06-02-2019
## 2201 83.45255 27.0000 Delayed FTA 16-10-2024
## 2202 70.71247 27.0000 Delayed Non-FTA 17-01-2020
## 2203 76.87513 27.0000 On Time Non-FTA 24-11-2022
## 2204 76.07494 27.0000 On Time Non-FTA 29-03-2018
## 2205 71.71131 27.0000 On Time FTA 24-11-2020
## 2206 78.07959 27.0000 Delayed Non-FTA 04-08-2018
## 2207 71.97868 27.0000 Delayed FTA 09-09-2018
## 2208 70.42245 27.0000 Delayed Non-FTA 23-12-2024
## 2209 80.08767 27.0000 On Time Non-FTA 26-04-2024
## 2210 77.43314 27.0000 On Time Non-FTA 30-04-2018
## 2211 70.19613 27.0000 Delayed Non-FTA 20-12-2023
## 2212 70.58332 27.0000 Delayed FTA 16-09-2018
## 2213 74.50743 27.0000 On Time FTA 28-10-2021
## 2214 82.39807 27.0000 Delayed FTA 19-08-2021
## 2215 82.18644 27.0000 Delayed FTA 04-03-2021
## 2216 74.18137 27.0000 Delayed FTA 21-02-2022
## 2217 84.95263 27.0000 On Time Non-FTA 03-11-2019
## 2218 79.18767 27.0000 On Time FTA 13-09-2024
## 2219 84.58524 27.0000 On Time Non-FTA 18-05-2024
## 2220 81.08395 27.0000 Delayed Non-FTA 08-10-2021
## 2221 72.51681 27.0000 Delayed Non-FTA 19-06-2023
## 2222 71.33159 27.0000 Delayed Non-FTA 12-11-2020
## 2223 78.61765 27.0000 On Time FTA 03-10-2021
## 2224 78.94651 27.0000 Delayed Non-FTA 16-10-2021
## 2225 70.14958 27.0000 Delayed FTA 05-12-2021
## 2226 74.75058 27.0000 On Time Non-FTA 29-01-2024
## 2227 74.73334 27.0000 On Time Non-FTA 29-06-2024
## 2228 84.46305 27.0000 Delayed Non-FTA 24-02-2021
## 2229 72.72565 27.0000 Delayed Non-FTA 03-02-2018
## 2230 78.88478 27.0000 Delayed Non-FTA 03-10-2024
## 2231 73.53594 27.0000 Delayed FTA 23-07-2020
## 2232 81.18372 27.0000 Delayed Non-FTA 09-11-2019
## 2233 83.70865 27.0000 Delayed FTA 09-09-2018
## 2234 82.30615 27.0000 On Time Non-FTA 07-11-2024
## 2235 77.04744 27.0000 Delayed FTA 19-05-2024
## 2236 75.95484 27.0000 Delayed FTA 10-06-2024
## 2237 75.02642 27.0000 On Time Non-FTA 03-02-2023
## 2238 79.43122 27.0000 Delayed FTA 02-04-2020
## 2239 76.85477 27.0000 On Time Non-FTA 06-01-2021
## 2240 75.85431 27.0000 Delayed Non-FTA 10-10-2019
## 2241 74.79446 27.0000 Delayed Non-FTA 23-07-2023
## 2242 80.85907 27.0000 Delayed FTA 19-10-2018
## 2243 70.73374 27.0000 On Time FTA 03-09-2020
## 2244 79.39349 27.0000 On Time Non-FTA 03-05-2020
## 2245 81.02945 27.0000 On Time Non-FTA 10-03-2019
## 2246 74.63478 27.0000 On Time Non-FTA 17-01-2021
## 2247 83.50243 27.0000 On Time FTA 30-04-2023
## 2248 75.05032 28.0000 On Time Non-FTA 27-08-2022
## 2249 72.24915 28.0000 On Time FTA 07-11-2020
## 2250 80.99288 28.0000 On Time Non-FTA 13-03-2021
## 2251 75.13168 28.0000 Delayed Non-FTA 30-11-2018
## 2252 83.90405 28.0000 On Time Non-FTA 30-06-2020
## 2253 78.27269 28.0000 On Time Non-FTA 29-07-2020
## 2254 70.46752 28.0000 On Time FTA 14-03-2018
## 2255 70.61795 28.0000 Delayed Non-FTA 07-11-2024
## 2256 79.42871 28.0000 Delayed FTA 27-12-2024
## 2257 81.11521 28.0000 Delayed Non-FTA 19-01-2023
## 2258 76.89607 28.0000 On Time Non-FTA 26-08-2021
## 2259 81.04309 28.0000 On Time Non-FTA 10-01-2018
## 2260 78.44221 28.0000 Delayed FTA 15-08-2021
## 2261 72.15540 28.0000 Delayed FTA 12-01-2024
## 2262 84.21443 28.0000 Delayed FTA 01-02-2020
## 2263 78.76613 28.0000 On Time FTA 03-08-2024
## 2264 77.51352 28.0000 Delayed FTA 18-02-2018
## 2265 81.70831 28.0000 Delayed FTA 07-10-2023
## 2266 74.51127 28.0000 On Time FTA 05-08-2022
## 2267 71.01446 28.0000 On Time Non-FTA 14-06-2024
## 2268 78.32034 28.0000 On Time Non-FTA 31-08-2022
## 2269 77.88617 28.0000 Delayed FTA 23-01-2024
## 2270 84.12119 28.0000 On Time Non-FTA 29-08-2024
## 2271 74.17298 28.0000 On Time Non-FTA 05-11-2019
## 2272 74.58736 28.0000 On Time Non-FTA 19-01-2018
## 2273 75.35308 28.0000 Delayed FTA 13-11-2022
## 2274 75.45530 28.0000 On Time Non-FTA 30-11-2022
## 2275 70.42401 28.0000 On Time Non-FTA 14-12-2019
## 2276 70.29392 28.0000 Delayed FTA 28-02-2020
## 2277 77.06223 28.0000 Delayed Non-FTA 24-11-2019
## 2278 77.20257 28.0000 On Time FTA 29-07-2018
## 2279 75.15984 28.0000 On Time Non-FTA 11-10-2022
## 2280 74.62213 28.0000 On Time Non-FTA 03-10-2023
## 2281 83.37683 28.0000 Delayed FTA 03-02-2024
## 2282 77.59024 28.0000 Delayed Non-FTA 21-02-2020
## 2283 80.08957 28.0000 Delayed Non-FTA 02-06-2021
## 2284 77.73040 28.0000 Delayed FTA 20-03-2022
## 2285 79.67171 28.0000 On Time FTA 25-04-2024
## 2286 78.24729 28.0000 Delayed FTA 11-07-2020
## 2287 83.74795 28.0000 Delayed FTA 18-05-2018
## 2288 73.94450 28.0000 On Time Non-FTA 19-07-2021
## 2289 77.77673 28.0000 Delayed Non-FTA 02-07-2019
## 2290 73.56384 28.0000 On Time Non-FTA 25-02-2021
## 2291 71.61765 28.0000 On Time FTA 05-03-2020
## 2292 84.19157 28.0000 Delayed FTA 07-12-2023
## 2293 77.53441 28.0000 On Time FTA 15-09-2024
## 2294 73.59718 28.0000 Delayed Non-FTA 17-05-2018
## 2295 76.35090 28.0000 On Time Non-FTA 15-04-2022
## 2296 78.79019 28.0000 Delayed Non-FTA 18-01-2024
## 2297 80.81856 28.0000 On Time FTA 02-10-2023
## 2298 84.21669 28.0000 On Time FTA 27-01-2018
## 2299 71.24671 28.0000 On Time Non-FTA 08-09-2024
## 2300 71.70335 28.0000 On Time FTA 04-07-2023
## 2301 77.05886 28.0000 Delayed Non-FTA 20-10-2021
## 2302 72.87908 28.0000 On Time Non-FTA 20-10-2018
## 2303 79.85209 28.0000 Delayed FTA 15-04-2018
## 2304 72.73645 28.0000 On Time Non-FTA 20-02-2024
## 2305 74.77226 28.0000 On Time Non-FTA 29-03-2024
## 2306 82.92628 28.0000 Delayed Non-FTA 23-04-2023
## 2307 76.65435 28.0000 On Time Non-FTA 11-09-2021
## 2308 76.22758 28.0000 Delayed Non-FTA 13-09-2023
## 2309 84.15795 28.0000 Delayed FTA 01-10-2023
## 2310 80.83073 28.0000 On Time Non-FTA 03-01-2024
## 2311 79.75883 28.0000 Delayed FTA 06-09-2022
## 2312 72.01036 28.0000 On Time FTA 14-04-2020
## 2313 71.48419 28.0000 Delayed FTA 08-01-2020
## 2314 82.72342 28.0000 On Time Non-FTA 01-07-2024
## 2315 79.05290 28.0000 Delayed Non-FTA 09-05-2023
## 2316 74.41469 28.0000 Delayed Non-FTA 13-05-2020
## 2317 83.70592 28.0000 Delayed Non-FTA 01-05-2020
## 2318 76.68519 28.0000 On Time FTA 15-07-2021
## 2319 75.40244 28.0000 On Time FTA 06-06-2023
## 2320 81.32731 28.0000 On Time Non-FTA 09-01-2023
## 2321 80.85602 29.0000 On Time FTA 11-03-2018
## 2322 72.71368 29.0000 Delayed FTA 05-01-2018
## 2323 82.08302 29.0000 Delayed FTA 10-09-2018
## 2324 71.10222 29.0000 Delayed FTA 11-12-2023
## 2325 78.12685 29.0000 Delayed FTA 07-11-2020
## 2326 80.52174 29.0000 Delayed FTA 20-02-2018
## 2327 70.37011 29.0000 On Time Non-FTA 02-10-2022
## 2328 78.28753 29.0000 On Time Non-FTA 27-06-2018
## 2329 79.66087 29.0000 On Time Non-FTA 28-01-2022
## 2330 82.52124 29.0000 On Time Non-FTA 31-05-2019
## 2331 83.66867 29.0000 Delayed FTA 09-03-2023
## 2332 77.30831 29.0000 Delayed FTA 27-01-2019
## 2333 74.05696 29.0000 Delayed FTA 29-12-2022
## 2334 74.20617 29.0000 On Time FTA 24-01-2018
## 2335 81.59052 29.0000 Delayed Non-FTA 20-10-2022
## 2336 79.86091 29.0000 Delayed FTA 02-10-2021
## 2337 75.48638 29.0000 On Time FTA 29-06-2024
## 2338 72.23587 29.0000 Delayed Non-FTA 03-02-2022
## 2339 82.19465 29.0000 On Time Non-FTA 22-08-2021
## 2340 78.74101 29.0000 Delayed Non-FTA 03-08-2024
## 2341 76.47124 29.0000 On Time Non-FTA 23-08-2024
## 2342 80.35306 29.0000 Delayed Non-FTA 16-07-2021
## 2343 70.23260 29.0000 Delayed FTA 07-01-2022
## 2344 70.99119 29.0000 On Time Non-FTA 20-03-2022
## 2345 77.69367 29.0000 Delayed FTA 13-04-2018
## 2346 82.61191 29.0000 On Time Non-FTA 21-07-2023
## 2347 76.07867 29.0000 Delayed FTA 02-04-2019
## 2348 79.44055 29.0000 On Time Non-FTA 06-09-2023
## 2349 79.25539 29.0000 Delayed Non-FTA 08-05-2023
## 2350 74.73764 29.0000 On Time FTA 06-07-2022
## 2351 84.01930 29.0000 On Time Non-FTA 04-02-2020
## 2352 78.44822 29.0000 On Time Non-FTA 22-09-2019
## 2353 84.99039 29.0000 On Time Non-FTA 09-07-2021
## 2354 71.81609 29.0000 Delayed Non-FTA 14-02-2022
## 2355 72.12997 29.0000 Delayed FTA 15-06-2018
## 2356 84.07226 29.0000 On Time Non-FTA 22-08-2020
## 2357 70.39647 29.0000 On Time FTA 01-03-2022
## 2358 81.19321 29.0000 Delayed FTA 15-08-2024
## 2359 84.24283 29.0000 On Time Non-FTA 12-06-2020
## 2360 81.30570 29.0000 On Time FTA 08-12-2019
## 2361 70.77365 29.0000 Delayed Non-FTA 15-09-2020
## 2362 77.61691 29.0000 On Time Non-FTA 08-01-2018
## 2363 78.56505 29.0000 On Time FTA 03-05-2018
## 2364 74.18745 29.0000 On Time Non-FTA 07-07-2022
## 2365 83.24902 29.0000 Delayed FTA 10-04-2020
## 2366 74.51385 29.0000 On Time Non-FTA 14-09-2024
## 2367 77.22367 29.0000 Delayed Non-FTA 28-11-2019
## 2368 83.42159 29.0000 Delayed FTA 06-10-2020
## 2369 77.42696 29.0000 Delayed Non-FTA 13-11-2023
## 2370 79.50251 29.0000 On Time FTA 31-05-2021
## 2371 76.06945 29.0000 Delayed FTA 26-06-2019
## 2372 72.18479 29.0000 On Time Non-FTA 14-12-2018
## 2373 83.24390 29.0000 Delayed FTA 22-06-2021
## 2374 74.04593 29.0000 Delayed FTA 18-12-2024
## 2375 75.33589 29.0000 On Time FTA 22-02-2023
## 2376 84.18586 29.0000 Delayed FTA 20-02-2023
## 2377 78.14194 29.0000 Delayed FTA 12-05-2020
## 2378 75.38217 29.0000 Delayed Non-FTA 08-09-2019
## 2379 78.15360 29.0000 Delayed Non-FTA 20-02-2024
## 2380 84.93848 29.0000 On Time Non-FTA 24-04-2023
## 2381 74.40631 29.0000 On Time Non-FTA 08-01-2020
## 2382 80.13309 29.0000 On Time Non-FTA 14-09-2023
## 2383 71.31272 29.0000 Delayed FTA 08-07-2023
## 2384 84.13107 29.0000 On Time FTA 05-01-2023
## 2385 72.03908 29.0000 Delayed FTA 18-01-2024
## 2386 83.69293 29.0000 On Time FTA 22-05-2019
## 2387 77.30367 29.0000 On Time Non-FTA 02-09-2019
## 2388 84.58045 29.0000 Delayed FTA 14-05-2023
## 2389 72.87353 29.0000 Delayed FTA 24-01-2019
## 2390 70.08971 29.0000 On Time FTA 15-11-2024
## 2391 74.59777 29.0000 On Time FTA 18-02-2023
## 2392 70.82292 29.0000 On Time Non-FTA 03-05-2020
## 2393 71.76023 29.0000 On Time FTA 17-04-2022
## 2394 79.58308 29.0000 Delayed FTA 21-07-2019
## 2395 73.96724 29.0000 On Time Non-FTA 25-02-2022
## 2396 71.11336 29.0000 Delayed Non-FTA 19-01-2023
## 2397 81.71248 29.0000 On Time Non-FTA 29-05-2021
## 2398 72.40798 29.0000 On Time FTA 07-04-2019
## 2399 71.02180 29.0000 Delayed Non-FTA 03-05-2022
## 2400 72.09278 29.0000 On Time FTA 26-09-2019
## 2401 81.51356 29.0000 On Time Non-FTA 15-03-2024
## 2402 84.38272 29.0000 Delayed FTA 11-06-2023
## 2403 76.27645 29.0000 On Time Non-FTA 05-08-2022
## 2404 72.99096 29.0000 Delayed FTA 28-11-2024
## 2405 74.00722 29.0000 Delayed Non-FTA 21-01-2022
## 2406 81.18447 29.0000 On Time FTA 30-01-2023
## 2407 76.20439 29.0000 On Time FTA 28-05-2024
## 2408 73.09497 29.0000 On Time Non-FTA 03-04-2020
## 2409 83.04453 29.0000 On Time Non-FTA 16-06-2023
## 2410 77.66591 29.0000 Delayed FTA 13-01-2022
## 2411 83.07845 29.0000 On Time FTA 29-05-2023
## 2412 82.66164 29.0000 Delayed Non-FTA 02-09-2018
## 2413 72.43144 29.0000 On Time Non-FTA 26-10-2023
## 2414 82.75006 29.0000 Delayed Non-FTA 09-10-2020
## 2415 77.53012 29.0000 On Time Non-FTA 25-10-2020
## 2416 79.65512 29.0000 On Time FTA 20-01-2021
## 2417 74.75256 29.0000 On Time FTA 30-06-2022
## 2418 77.08860 29.0000 Delayed Non-FTA 09-11-2024
## 2419 76.26125 29.0000 Delayed FTA 13-11-2019
## 2420 79.48828 29.0000 Delayed FTA 11-07-2020
## 2421 76.79772 29.0000 Delayed FTA 15-06-2024
## 2422 80.20319 29.0000 Delayed FTA 19-07-2018
## 2423 84.59273 29.0000 Delayed Non-FTA 27-09-2024
## 2424 77.89322 29.0000 On Time Non-FTA 19-09-2022
## 2425 83.30403 29.0000 On Time FTA 06-12-2023
## 2426 84.09672 29.0000 On Time FTA 12-11-2024
## 2427 73.41378 30.0000 Delayed Non-FTA 13-02-2024
## 2428 81.45950 30.0000 On Time FTA 29-07-2020
## 2429 75.40469 30.0000 On Time Non-FTA 20-07-2022
## 2430 74.46662 30.0000 On Time FTA 24-10-2022
## 2431 73.19110 30.0000 On Time FTA 21-11-2020
## 2432 74.05047 30.0000 On Time FTA 16-06-2018
## 2433 79.68891 30.0000 On Time Non-FTA 08-09-2024
## 2434 76.61378 30.0000 On Time FTA 25-11-2019
## 2435 79.20856 30.0000 Delayed FTA 11-06-2018
## 2436 82.26677 30.0000 Delayed FTA 05-04-2019
## 2437 79.15206 30.0000 Delayed FTA 01-12-2024
## 2438 75.96541 30.0000 Delayed Non-FTA 26-06-2020
## 2439 74.68904 30.0000 On Time Non-FTA 12-01-2021
## 2440 74.19994 30.0000 On Time Non-FTA 29-01-2024
## 2441 84.82885 30.0000 On Time Non-FTA 10-08-2024
## 2442 79.58191 30.0000 Delayed Non-FTA 12-07-2020
## 2443 75.72353 30.0000 On Time FTA 16-06-2019
## 2444 81.01300 30.0000 Delayed Non-FTA 23-09-2024
## 2445 70.56158 30.0000 On Time FTA 12-02-2023
## 2446 73.85718 30.0000 On Time Non-FTA 22-10-2018
## 2447 79.11473 30.0000 On Time Non-FTA 27-09-2022
## 2448 71.78603 30.0000 On Time Non-FTA 05-03-2024
## 2449 81.50512 30.0000 Delayed Non-FTA 24-06-2018
## 2450 80.45831 30.0000 On Time Non-FTA 15-10-2022
## 2451 75.34939 30.0000 On Time Non-FTA 19-07-2024
## 2452 80.68161 30.0000 Delayed Non-FTA 29-09-2023
## 2453 78.96197 30.0000 Delayed Non-FTA 07-10-2019
## 2454 80.35912 30.0000 On Time Non-FTA 29-05-2023
## 2455 74.61994 30.0000 Delayed FTA 08-06-2022
## 2456 83.88828 30.0000 Delayed Non-FTA 13-06-2021
## 2457 77.78056 30.0000 On Time Non-FTA 12-03-2021
## 2458 82.56004 30.0000 Delayed FTA 10-07-2019
## 2459 81.35710 30.0000 On Time FTA 21-03-2019
## 2460 81.88737 30.0000 Delayed Non-FTA 18-06-2024
## 2461 77.56159 30.0000 On Time FTA 30-08-2024
## 2462 73.53875 30.0000 On Time FTA 15-02-2021
## 2463 81.13351 30.0000 Delayed FTA 06-09-2018
## 2464 74.63967 30.0000 On Time Non-FTA 12-12-2023
## 2465 79.10488 30.0000 Delayed FTA 25-04-2023
## 2466 82.71575 30.0000 Delayed Non-FTA 28-03-2018
## 2467 80.22641 30.0000 Delayed FTA 04-05-2022
## 2468 77.52127 30.0000 On Time FTA 01-06-2021
## 2469 83.42157 30.0000 On Time Non-FTA 07-01-2018
## 2470 80.45694 30.0000 Delayed FTA 22-01-2020
## 2471 71.93680 30.0000 On Time Non-FTA 18-11-2018
## 2472 72.44630 30.0000 Delayed FTA 25-03-2019
## 2473 79.63395 30.0000 Delayed FTA 25-07-2020
## 2474 70.61733 30.0000 On Time FTA 16-11-2020
## 2475 71.20147 30.0000 Delayed Non-FTA 30-04-2021
## 2476 83.43051 30.0000 Delayed FTA 24-08-2023
## 2477 76.05539 30.0000 Delayed FTA 10-07-2020
## 2478 79.71120 30.0000 On Time FTA 06-10-2018
## 2479 74.80859 30.0000 On Time Non-FTA 18-09-2022
## 2480 76.67086 30.0000 Delayed FTA 21-07-2022
## 2481 77.26586 30.0000 Delayed FTA 24-12-2019
## 2482 82.36984 30.0000 On Time Non-FTA 12-11-2018
## 2483 72.59064 30.0000 Delayed FTA 31-03-2018
## 2484 83.54902 30.0000 On Time Non-FTA 01-12-2018
## 2485 79.32819 30.0000 Delayed Non-FTA 14-03-2022
## 2486 72.40767 30.0000 On Time Non-FTA 21-07-2024
## 2487 84.20406 30.0000 On Time FTA 04-02-2024
## 2488 80.88199 30.0000 Delayed FTA 07-04-2023
## 2489 77.82466 30.0000 Delayed Non-FTA 09-03-2022
## 2490 84.30248 30.0000 Delayed Non-FTA 07-02-2019
## 2491 74.41198 30.0000 Delayed Non-FTA 14-06-2023
## 2492 81.35901 30.0000 On Time FTA 16-09-2020
## 2493 82.92018 30.0000 On Time FTA 29-12-2018
## 2494 78.72675 30.0000 Delayed Non-FTA 29-05-2022
## 2495 73.62860 30.0000 On Time FTA 24-09-2019
## 2496 72.77787 30.0000 Delayed Non-FTA 08-12-2021
## 2497 72.44885 30.0000 Delayed Non-FTA 08-12-2023
## 2498 72.38847 30.0000 On Time FTA 26-01-2021
## 2499 71.60248 103.1988 On Time Non-FTA 04-09-2021
## Value_INR Profit Loss Is_Delayed Profit_Margin
## 1 1057937.34 88818.184 105134.671 FALSE 0.08395411
## 2 4252342.27 444612.443 86123.560 FALSE 0.10455707
## 3 7105021.98 1117474.996 515452.562 FALSE 0.15727960
## 4 2422846.52 251141.533 77273.348 FALSE 0.10365557
## 5 5896746.33 1139178.500 253968.764 TRUE 0.19318764
## 6 5638420.34 347625.800 317637.605 TRUE 0.06165305
## 7 4875511.86 641783.565 118318.852 FALSE 0.13163409
## 8 3679771.44 436140.812 244824.195 TRUE 0.11852389
## 9 6975929.84 1281387.105 280263.852 TRUE 0.18368693
## 10 5207407.95 631794.547 251432.670 TRUE 0.12132611
## 11 7254971.32 1306134.152 426569.089 TRUE 0.18003299
## 12 5623459.96 314502.900 437146.548 TRUE 0.05592694
## 13 3963734.49 418627.471 240850.918 FALSE 0.10561441
## 14 425089.51 21548.573 36823.762 FALSE 0.05069185
## 15 1598696.90 272920.220 152652.869 TRUE 0.17071417
## 16 75028.24 13022.511 4001.122 FALSE 0.17356811
## 17 4367898.95 612136.076 235163.935 TRUE 0.14014429
## 18 4197107.42 337539.557 210392.871 FALSE 0.08042195
## 19 1534495.97 178242.199 34310.599 FALSE 0.11615684
## 20 3442664.37 374048.494 334730.340 TRUE 0.10865087
## 21 4859777.63 712713.594 428145.077 FALSE 0.14665560
## 22 188136.95 21541.615 17075.465 TRUE 0.11449965
## 23 364098.19 66978.771 8409.874 TRUE 0.18395799
## 24 4157118.43 572293.806 177661.786 TRUE 0.13766599
## 25 312992.81 60731.120 21757.042 TRUE 0.19403360
## 26 6033564.25 515140.066 125292.178 TRUE 0.08537906
## 27 159863.30 11272.899 2191.136 TRUE 0.07051586
## 28 3966231.24 426914.614 207785.021 FALSE 0.10763735
## 29 2416979.98 172882.596 50268.659 TRUE 0.07152835
## 30 4041981.96 254035.929 162561.508 TRUE 0.06284935
## 31 4710977.22 499068.634 231791.205 FALSE 0.10593739
## 32 4509913.23 274523.456 415954.171 FALSE 0.06087112
## 33 4378660.99 648165.741 97212.657 FALSE 0.14802830
## 34 1480462.93 106366.852 68757.903 FALSE 0.07184702
## 35 3907337.98 305542.085 360745.922 FALSE 0.07819699
## 36 1042925.71 74829.443 90064.897 TRUE 0.07174954
## 37 5917311.26 456387.010 92982.243 TRUE 0.07712743
## 38 2183238.53 256294.683 211490.360 TRUE 0.11739198
## 39 7017903.74 401124.707 330946.452 FALSE 0.05715734
## 40 114034.41 15025.186 3499.334 TRUE 0.13176011
## 41 5366309.74 976160.627 213265.743 TRUE 0.18190538
## 42 2281391.31 187823.482 54265.512 TRUE 0.08232848
## 43 5634521.31 903026.921 198377.521 TRUE 0.16026684
## 44 5231755.27 581073.685 187449.366 FALSE 0.11106668
## 45 1960523.44 284244.413 39291.503 FALSE 0.14498394
## 46 3218612.39 476599.881 234957.171 FALSE 0.14807620
## 47 1790871.35 102051.524 63149.176 FALSE 0.05698429
## 48 5212945.60 989723.078 251599.048 TRUE 0.18985870
## 49 4563743.64 477050.035 116696.315 TRUE 0.10453042
## 50 2671160.27 224610.193 97445.286 TRUE 0.08408713
## 51 6849344.24 980880.931 212799.765 FALSE 0.14320801
## 52 5745660.26 501162.678 547814.489 FALSE 0.08722456
## 53 2799394.09 410630.865 61221.900 TRUE 0.14668562
## 54 5971221.90 507473.210 318318.389 FALSE 0.08498649
## 55 3767200.20 751188.619 169635.721 TRUE 0.19940236
## 56 4901587.39 682341.241 251762.765 TRUE 0.13920822
## 57 3323208.13 649231.654 315372.802 TRUE 0.19536292
## 58 7120284.23 597070.230 555651.512 FALSE 0.08385483
## 59 410409.82 57940.766 11359.040 FALSE 0.14117782
## 60 4995446.30 967644.168 219625.219 FALSE 0.19370525
## 61 8087043.66 1598195.408 440334.629 TRUE 0.19762418
## 62 1822834.22 231667.571 176608.225 FALSE 0.12709196
## 63 5131975.02 877337.193 358662.560 TRUE 0.17095508
## 64 1161641.89 225890.530 18498.876 TRUE 0.19445797
## 65 6522053.53 505618.853 316772.304 TRUE 0.07752449
## 66 827266.14 99974.779 21881.748 TRUE 0.12084960
## 67 5759178.82 782503.419 66456.137 TRUE 0.13587066
## 68 771886.38 72989.459 58158.683 FALSE 0.09455985
## 69 3416606.79 190911.025 291205.975 FALSE 0.05587738
## 70 4002044.81 465136.581 65875.329 TRUE 0.11622473
## 71 152240.19 30124.763 8079.560 TRUE 0.19787654
## 72 2544244.32 483251.261 149866.458 TRUE 0.18993902
## 73 2280588.25 373661.896 143852.389 FALSE 0.16384452
## 74 1725331.93 94140.775 105456.037 FALSE 0.05456386
## 75 5215456.99 761538.497 452086.789 FALSE 0.14601568
## 76 1261658.27 70195.027 65115.251 FALSE 0.05563712
## 77 3022613.48 259062.638 173602.791 TRUE 0.08570816
## 78 6802176.04 494518.085 273527.684 FALSE 0.07269998
## 79 4534633.76 669014.448 168693.039 TRUE 0.14753439
## 80 733234.30 102594.755 59296.717 TRUE 0.13992083
## 81 1443353.75 110502.677 111903.152 FALSE 0.07655966
## 82 4481234.48 660124.278 300530.299 TRUE 0.14730858
## 83 657519.81 56476.628 60188.766 TRUE 0.08589342
## 84 6058594.98 1144349.693 295612.383 TRUE 0.18888038
## 85 5208088.19 644461.011 186115.232 TRUE 0.12374234
## 86 6315555.28 1177714.157 380262.238 FALSE 0.18647832
## 87 3942300.06 730507.450 385634.129 TRUE 0.18529981
## 88 5243723.94 515898.902 77349.819 FALSE 0.09838407
## 89 3755977.66 473244.394 221286.639 TRUE 0.12599766
## 90 5528254.04 1012008.194 374336.642 FALSE 0.18306109
## 91 2866193.29 229945.755 194520.389 FALSE 0.08022688
## 92 1113910.75 66291.317 74835.210 FALSE 0.05951223
## 93 2915779.86 504264.489 181027.506 FALSE 0.17294326
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## 746 3731386.67 442496.064 65624.676 TRUE 0.11858757
## 747 4738740.50 277345.460 105490.920 TRUE 0.05852725
## 748 3549207.29 486624.212 319432.897 TRUE 0.13710786
## 749 4718687.95 922997.860 282675.468 TRUE 0.19560477
## 750 2730707.76 160657.059 239649.057 FALSE 0.05883349
## 751 3464681.94 453302.452 340359.310 FALSE 0.13083523
## 752 7077957.85 1111902.866 226140.905 FALSE 0.15709374
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## 754 168037.01 27027.423 11591.057 TRUE 0.16084209
## 755 2837151.59 448387.490 269419.736 FALSE 0.15804143
## 756 1845788.25 136519.030 75806.218 TRUE 0.07396245
## 757 6802667.32 917801.312 373085.672 TRUE 0.13491786
## 758 8097934.14 1259031.993 273662.813 TRUE 0.15547570
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## 761 5872497.51 665045.610 361103.991 TRUE 0.11324749
## 762 5866382.45 478441.610 330626.091 FALSE 0.08155650
## 763 3048968.18 247000.151 161837.241 TRUE 0.08101106
## 764 6548001.69 1202858.660 606207.389 FALSE 0.18369859
## 765 1496848.33 255774.507 35449.848 TRUE 0.17087537
## 766 243074.18 21061.997 23068.223 FALSE 0.08664844
## 767 3625388.38 682990.629 116757.517 TRUE 0.18839102
## 768 4849401.74 334815.707 326771.045 FALSE 0.06904268
## 769 5021846.09 1002115.249 222097.970 TRUE 0.19955117
## 770 144023.03 26656.799 10446.931 FALSE 0.18508706
## 771 843418.29 49264.833 10090.043 TRUE 0.05841091
## 772 6801804.77 1096856.309 429887.340 TRUE 0.16125960
## 773 526578.90 97948.475 40622.896 FALSE 0.18600912
## 774 7549657.34 1302551.113 126598.374 FALSE 0.17253116
## 775 480665.58 53384.881 45954.140 TRUE 0.11106450
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## 777 6628310.51 1273696.520 644944.559 FALSE 0.19216006
## 778 7588656.55 746418.337 316229.445 TRUE 0.09835975
## 779 7865145.01 679681.314 542870.249 FALSE 0.08641688
## 780 382769.28 75715.337 6524.926 TRUE 0.19780934
## 781 6105547.58 473134.882 197757.347 TRUE 0.07749262
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## 786 3757831.17 277923.348 79981.222 FALSE 0.07395844
## 787 5054021.29 898969.027 438628.480 FALSE 0.17787203
## 788 1151375.93 117978.961 50042.258 FALSE 0.10246780
## 789 2656058.21 407992.147 147521.024 FALSE 0.15360813
## 790 5604803.56 365212.773 414839.343 FALSE 0.06516067
## 791 3544868.75 439007.167 46038.006 TRUE 0.12384300
## 792 6823040.12 1320634.259 289128.862 TRUE 0.19355511
## 793 225129.38 14321.794 3524.707 TRUE 0.06361584
## 794 7855039.83 1441453.559 625823.841 TRUE 0.18350684
## 795 7042143.90 667712.114 236109.654 TRUE 0.09481660
## 796 3383326.16 609743.934 323784.628 TRUE 0.18022026
## 797 1371545.29 152866.990 119249.307 TRUE 0.11145603
## 798 5693989.87 833215.806 62240.755 TRUE 0.14633251
## 799 5415553.95 507216.286 243683.565 FALSE 0.09365917
## 800 3053403.90 172333.059 265420.281 FALSE 0.05643965
## 801 954807.27 140862.157 27835.067 TRUE 0.14752941
## 802 1728215.29 216149.429 121559.392 FALSE 0.12507089
## 803 3339634.86 560461.421 212437.769 TRUE 0.16782117
## 804 2131458.08 267700.877 140177.568 FALSE 0.12559519
## 805 6986337.72 718636.461 626616.601 FALSE 0.10286312
## 806 4611132.89 613356.901 251015.828 FALSE 0.13301653
## 807 3314223.34 520153.845 214433.141 TRUE 0.15694592
## 808 246805.94 19057.010 5715.457 TRUE 0.07721455
## 809 1629158.63 300141.315 45957.233 FALSE 0.18423087
## 810 4148876.26 599549.669 114469.221 FALSE 0.14450893
## 811 408410.51 55543.625 19026.869 TRUE 0.13599950
## 812 1055506.73 137752.957 19450.982 TRUE 0.13050884
## 813 5586956.91 643217.024 366055.412 FALSE 0.11512833
## 814 2501922.67 185346.738 71120.932 FALSE 0.07408172
## 815 5379244.19 962931.129 432569.796 FALSE 0.17900863
## 816 443487.71 30130.557 37374.536 FALSE 0.06794001
## 817 1758132.08 140722.891 140051.220 TRUE 0.08004114
## 818 5649316.23 541657.006 175853.698 FALSE 0.09588010
## 819 3245085.50 411221.481 92530.489 FALSE 0.12672131
## 820 2087792.93 199024.725 185931.528 FALSE 0.09532781
## 821 2547199.45 323419.470 97319.840 FALSE 0.12697061
## 822 5567123.88 466526.258 288425.777 FALSE 0.08380023
## 823 4693179.61 920750.254 140064.463 FALSE 0.19618901
## 824 6912536.53 1037662.884 218911.988 FALSE 0.15011319
## 825 4712373.66 519686.024 286153.330 FALSE 0.11028116
## 826 5124405.77 979605.229 427467.355 TRUE 0.19116465
## 827 3385722.72 400046.066 318570.900 FALSE 0.11815677
## 828 1598585.44 163677.160 63523.717 TRUE 0.10238875
## 829 3387646.15 481734.761 318293.493 FALSE 0.14220339
## 830 5761463.44 663550.456 388762.518 TRUE 0.11517047
## 831 6992937.24 717542.802 691263.352 TRUE 0.10260964
## 832 5245355.85 369853.239 78141.247 FALSE 0.07051061
## 833 3195629.07 171221.884 280213.247 FALSE 0.05358002
## 834 2557805.57 360093.759 33095.513 TRUE 0.14078230
## 835 235448.61 15718.091 2567.970 TRUE 0.06675805
## 836 4244268.80 676342.420 131534.222 FALSE 0.15935428
## 837 2957951.11 166535.719 113681.924 TRUE 0.05630104
## 838 1881082.10 102649.293 42698.324 TRUE 0.05456928
## 839 2096995.57 121640.860 77180.155 FALSE 0.05800721
## 840 4460116.17 232770.224 276451.523 TRUE 0.05218927
## 841 4584543.26 583532.258 304034.044 TRUE 0.12728253
## 842 6762235.12 870770.117 668703.394 TRUE 0.12876957
## 843 1316908.53 197491.750 49857.112 FALSE 0.14996619
## 844 832732.74 63239.042 82572.124 TRUE 0.07594158
## 845 2494884.29 236688.393 154508.055 FALSE 0.09486949
## 846 5461820.17 281870.993 174022.205 FALSE 0.05160752
## 847 4505328.79 674271.650 417800.893 FALSE 0.14966092
## 848 4501000.18 486969.454 379938.416 FALSE 0.10819139
## 849 7767843.62 1016049.609 408311.507 TRUE 0.13080202
## 850 670649.08 90818.652 31031.686 FALSE 0.13541904
## 851 4763863.31 486794.780 95645.660 TRUE 0.10218488
## 852 4630981.24 643430.657 73163.811 TRUE 0.13894046
## 853 6674630.57 1173660.000 458279.623 FALSE 0.17583895
## 854 5981614.60 1166590.595 111749.481 TRUE 0.19502938
## 855 4019707.76 415245.093 247250.092 TRUE 0.10330231
## 856 7844510.59 916355.917 99165.334 TRUE 0.11681493
## 857 7560944.63 780152.307 463542.409 FALSE 0.10318186
## 858 2630211.47 243669.028 45453.572 FALSE 0.09264237
## 859 206617.87 33837.457 11110.372 FALSE 0.16376829
## 860 7431622.16 1383666.273 138689.558 TRUE 0.18618631
## 861 1807606.73 305280.545 62571.505 TRUE 0.16888659
## 862 7613958.73 411397.317 224648.365 TRUE 0.05403199
## 863 3508410.70 244590.763 339335.461 TRUE 0.06971554
## 864 395146.79 64913.086 18002.115 TRUE 0.16427588
## 865 1406821.10 138028.087 68371.831 TRUE 0.09811346
## 866 4891720.11 400653.933 405512.300 TRUE 0.08190451
## 867 4389316.89 794866.384 310593.680 FALSE 0.18109114
## 868 685073.76 78614.756 22644.726 FALSE 0.11475371
## 869 1968741.71 200588.297 81081.364 TRUE 0.10188655
## 870 1778953.68 203784.881 140798.621 TRUE 0.11455322
## 871 5441980.98 479229.557 465539.627 TRUE 0.08806160
## 872 3932112.55 363337.414 298065.800 FALSE 0.09240260
## 873 3912973.11 649280.840 287545.657 TRUE 0.16593031
## 874 2524881.89 205898.979 107272.218 TRUE 0.08154796
## 875 2312322.43 151317.428 144827.927 FALSE 0.06543959
## 876 3274240.79 535710.653 230714.468 FALSE 0.16361370
## 877 6731639.11 733639.468 274183.492 TRUE 0.10898378
## 878 5866208.39 350351.479 180847.786 FALSE 0.05972367
## 879 3134873.98 291210.188 133870.698 TRUE 0.09289375
## 880 8056301.95 1288153.856 704564.897 FALSE 0.15989394
## 881 7759248.99 1516761.370 150278.149 TRUE 0.19547786
## 882 6250779.78 969250.800 527765.586 FALSE 0.15506078
## 883 8195897.72 693509.576 800542.957 FALSE 0.08461667
## 884 6646861.61 1000419.475 569591.347 FALSE 0.15051005
## 885 5658761.04 485633.528 342991.292 TRUE 0.08581976
## 886 5855822.04 1102962.979 577325.880 FALSE 0.18835323
## 887 5206319.87 647675.526 188245.733 TRUE 0.12440179
## 888 6922292.59 539854.660 407087.280 FALSE 0.07798784
## 889 3219001.31 598529.787 153934.388 FALSE 0.18593648
## 890 4032978.58 461423.923 365569.082 FALSE 0.11441269
## 891 630014.40 90283.198 21282.075 FALSE 0.14330339
## 892 6072571.18 1194326.269 260763.449 FALSE 0.19667555
## 893 2608763.36 213861.040 181501.374 FALSE 0.08197794
## 894 5675873.46 332699.269 384918.975 FALSE 0.05861640
## 895 4857396.26 457843.141 142072.828 FALSE 0.09425691
## 896 5364828.50 894823.594 239409.301 FALSE 0.16679445
## 897 3138097.02 174865.210 170584.732 TRUE 0.05572333
## 898 913168.63 64317.030 69477.817 FALSE 0.07043281
## 899 4122117.95 227136.819 205102.509 FALSE 0.05510197
## 900 1461491.57 255540.120 133847.191 TRUE 0.17484885
## 901 4904748.30 826674.036 247584.986 TRUE 0.16854566
## 902 7750614.25 920507.705 283667.383 FALSE 0.11876577
## 903 3453763.85 327825.830 182789.249 TRUE 0.09491843
## 904 7645330.29 838246.976 557185.282 TRUE 0.10964170
## 905 5858057.00 1139580.548 454314.578 FALSE 0.19453217
## 906 5474581.96 816409.826 453249.085 FALSE 0.14912734
## 907 5111408.99 335242.623 81701.637 TRUE 0.06558713
## 908 329517.53 42588.345 7247.532 TRUE 0.12924455
## 909 3432074.50 519139.041 220290.336 FALSE 0.15126101
## 910 2132332.46 238573.618 165093.394 TRUE 0.11188387
## 911 4684204.24 465281.244 238305.613 FALSE 0.09932984
## 912 6664497.49 458412.073 503670.057 FALSE 0.06878419
## 913 321613.16 63614.806 25260.717 TRUE 0.19779914
## 914 4444967.13 324465.572 407638.530 FALSE 0.07299617
## 915 2209705.43 309425.090 52709.976 TRUE 0.14003002
## 916 1464411.60 87666.753 71691.657 TRUE 0.05986483
## 917 1947109.90 114158.804 179750.073 FALSE 0.05862987
## 918 4457767.11 645955.160 301922.819 FALSE 0.14490554
## 919 3226820.92 512984.742 37369.583 FALSE 0.15897527
## 920 4695583.03 512987.608 93610.611 FALSE 0.10924897
## 921 6602059.68 561129.599 451282.885 TRUE 0.08499311
## 922 3808636.06 620578.922 230091.422 TRUE 0.16293994
## 923 5367045.00 616242.892 133652.449 TRUE 0.11481977
## 924 143053.31 19860.180 12482.336 FALSE 0.13883062
## 925 5376500.37 504735.583 348355.395 TRUE 0.09387809
## 926 7020409.36 511356.411 250150.258 FALSE 0.07283855
## 927 1159098.98 177258.173 32824.268 FALSE 0.15292756
## 928 4892951.80 736326.811 474536.596 FALSE 0.15048724
## 929 5404382.77 373603.730 339074.667 TRUE 0.06912977
## 930 2367907.50 145832.211 178600.317 TRUE 0.06158695
## 931 3669929.50 364689.090 220932.865 TRUE 0.09937223
## 932 6462899.44 813355.336 475295.594 TRUE 0.12584991
## 933 6278957.18 504199.491 576030.687 TRUE 0.08029988
## 934 1160724.11 155612.017 98995.240 TRUE 0.13406460
## 935 3891649.82 474954.508 59556.723 FALSE 0.12204451
## 936 1332711.58 90747.112 60085.022 FALSE 0.06809209
## 937 3399972.59 623922.010 195878.672 FALSE 0.18350795
## 938 4902710.94 432812.630 480120.845 TRUE 0.08828027
## 939 3890372.08 772804.146 111916.264 FALSE 0.19864530
## 940 7465737.14 820081.689 541867.051 TRUE 0.10984604
## 941 518369.62 58037.557 17113.762 FALSE 0.11196173
## 942 4969903.64 594018.124 54740.090 FALSE 0.11952307
## 943 4814709.55 304287.942 345210.824 FALSE 0.06319965
## 944 4196760.08 558679.398 221385.548 FALSE 0.13312160
## 945 4733524.14 375916.143 66608.910 FALSE 0.07941570
## 946 4139918.08 569100.117 103291.365 FALSE 0.13746652
## 947 1802344.57 317161.735 137943.586 FALSE 0.17597175
## 948 2444989.38 161946.158 212918.161 TRUE 0.06623594
## 949 772191.13 119241.446 48293.539 TRUE 0.15441960
## 950 5151098.02 436999.752 264966.012 FALSE 0.08483623
## 951 275114.66 45189.893 8575.491 TRUE 0.16425840
## 952 1270612.71 203120.830 32945.146 TRUE 0.15986054
## 953 3843499.58 271291.149 262821.160 TRUE 0.07058441
## 954 2199771.31 328508.437 86126.292 TRUE 0.14933754
## 955 1224185.18 243213.359 103651.775 TRUE 0.19867367
## 956 4055135.18 219332.663 259988.460 FALSE 0.05408763
## 957 4758278.77 374154.722 100269.932 TRUE 0.07863237
## 958 1192320.24 80830.595 15478.711 FALSE 0.06779269
## 959 3228508.31 373033.273 232046.226 FALSE 0.11554354
## 960 5467978.84 571606.584 91246.321 FALSE 0.10453709
## 961 1136548.68 188019.832 13465.323 TRUE 0.16543051
## 962 4366243.73 246702.525 224619.028 TRUE 0.05650223
## 963 4505442.54 517617.095 252889.915 TRUE 0.11488707
## 964 3040745.03 326922.306 171400.777 FALSE 0.10751388
## 965 2025946.19 295020.203 151728.997 FALSE 0.14562095
## 966 330981.62 52761.366 23666.528 TRUE 0.15940875
## 967 6240825.75 792234.542 161578.696 TRUE 0.12694387
## 968 4731013.87 371435.348 251334.222 TRUE 0.07851073
## 969 6213863.22 430143.683 501919.004 FALSE 0.06922323
## 970 953884.49 128680.046 84959.089 FALSE 0.13490108
## 971 4279320.78 573291.011 72587.568 TRUE 0.13396776
## 972 2360019.78 193624.864 55190.710 FALSE 0.08204375
## 973 3093006.26 239910.587 201889.339 FALSE 0.07756550
## 974 2901523.72 507026.639 188614.564 TRUE 0.17474496
## 975 2986708.27 443066.852 288911.398 FALSE 0.14834621
## 976 5431964.05 468407.280 83395.003 FALSE 0.08623166
## 977 2729962.38 235891.740 232302.302 FALSE 0.08640842
## 978 6336212.81 569954.544 170262.851 FALSE 0.08995193
## 979 7859641.41 1279422.382 555391.535 FALSE 0.16278381
## 980 5656841.76 703892.533 343281.983 FALSE 0.12443207
## 981 4413521.90 601204.305 366895.788 FALSE 0.13621872
## 982 2379561.57 333765.893 93933.428 TRUE 0.14026361
## 983 1680339.11 173250.355 25525.938 TRUE 0.10310440
## 984 3579401.97 617732.628 77216.386 TRUE 0.17257984
## 985 765415.40 148231.816 57717.137 FALSE 0.19366192
## 986 6908162.12 1328036.355 389541.247 TRUE 0.19224163
## 987 2009150.74 119396.857 101655.122 FALSE 0.05942653
## 988 6652757.85 964050.752 279835.030 FALSE 0.14490994
## 989 3419508.59 232659.535 250761.150 TRUE 0.06803888
## 990 4907896.85 695185.911 364472.328 FALSE 0.14164640
## 991 3944953.84 426666.562 375198.413 TRUE 0.10815502
## 992 5058457.05 785977.670 270745.979 TRUE 0.15537894
## 993 3403866.67 220734.058 297059.548 FALSE 0.06484803
## 994 6299949.94 836582.897 156209.187 FALSE 0.13279199
## 995 2298437.83 205844.970 81524.960 FALSE 0.08955864
## 996 2818137.00 343621.599 47125.376 FALSE 0.12193218
## 997 398728.02 68010.306 20203.027 FALSE 0.17056816
## 998 4761268.38 560676.319 157860.133 TRUE 0.11775776
## 999 144148.81 26109.541 1783.772 FALSE 0.18112908
## 1000 1381235.06 108385.775 46686.928 TRUE 0.07847019
## 1001 3023200.71 222165.695 247457.547 TRUE 0.07348692
## 1002 822790.59 143613.622 40583.203 FALSE 0.17454456
## 1003 7105399.55 1181906.476 708237.827 FALSE 0.16633920
## 1004 4017476.49 684450.076 47380.228 TRUE 0.17036816
## 1005 5117328.43 396129.192 431511.048 FALSE 0.07740937
## 1006 6002390.33 358689.853 269207.184 FALSE 0.05975784
## 1007 944916.21 155318.662 20952.648 FALSE 0.16437295
## 1008 6578319.98 421058.925 222682.647 FALSE 0.06400706
## 1009 469211.30 43266.563 20164.914 FALSE 0.09221126
## 1010 712096.69 102251.737 12487.354 FALSE 0.14359249
## 1011 98899.82 7240.970 5583.698 FALSE 0.07321520
## 1012 6831219.68 554940.694 545594.104 FALSE 0.08123596
## 1013 982225.70 95801.247 58008.702 TRUE 0.09753486
## 1014 6219801.71 335983.037 407568.911 FALSE 0.05401829
## 1015 2622306.78 345733.412 214443.823 TRUE 0.13184324
## 1016 3616824.88 265813.403 233119.899 FALSE 0.07349358
## 1017 7082055.14 409444.930 595551.535 FALSE 0.05781442
## 1018 2139823.25 379247.029 175161.214 TRUE 0.17723288
## 1019 3213865.35 172398.499 60572.135 FALSE 0.05364210
## 1020 5248925.95 1039805.192 73048.258 FALSE 0.19809866
## 1021 4988193.84 845837.635 490439.821 FALSE 0.16956792
## 1022 975630.93 112274.662 10551.487 FALSE 0.11507903
## 1023 3462360.12 430486.966 174074.904 TRUE 0.12433339
## 1024 4321372.67 354015.729 357885.662 TRUE 0.08192205
## 1025 5307815.77 1028909.289 282980.810 TRUE 0.19384797
## 1026 6949686.81 920553.201 178114.688 TRUE 0.13245967
## 1027 4172799.10 701981.752 119143.704 FALSE 0.16822803
## 1028 2338507.20 333638.933 92252.532 TRUE 0.14267176
## 1029 5016664.50 714924.734 187263.126 FALSE 0.14250998
## 1030 4532402.38 323919.884 74621.508 TRUE 0.07146759
## 1031 1158665.59 119166.493 16589.434 TRUE 0.10284805
## 1032 3293841.05 621550.744 293415.952 FALSE 0.18870089
## 1033 4950199.73 609853.662 131879.971 TRUE 0.12319779
## 1034 4455665.46 867284.013 79523.032 FALSE 0.19464747
## 1035 100427.60 10315.979 9723.019 TRUE 0.10272055
## 1036 7187958.61 594469.113 277631.987 FALSE 0.08270347
## 1037 2646560.32 376404.628 200247.011 FALSE 0.14222409
## 1038 3549776.50 216917.853 303533.816 TRUE 0.06110747
## 1039 1332315.02 91810.642 26341.006 TRUE 0.06891061
## 1040 7679511.48 1489036.808 246837.208 TRUE 0.19389733
## 1041 3114719.57 571182.129 74728.803 TRUE 0.18338156
## 1042 3898358.82 273131.220 247092.366 FALSE 0.07006313
## 1043 5073724.26 793653.125 413295.438 FALSE 0.15642417
## 1044 5468165.23 488683.590 327847.307 TRUE 0.08936884
## 1045 835771.14 87596.573 11629.544 FALSE 0.10480928
## 1046 6955849.33 591834.169 504512.318 FALSE 0.08508439
## 1047 433196.85 36769.493 36681.368 TRUE 0.08487941
## 1048 3715695.00 433125.134 130519.042 FALSE 0.11656638
## 1049 3048289.98 248150.425 75664.829 TRUE 0.08140644
## 1050 192253.60 31407.764 14090.741 TRUE 0.16336632
## 1051 916100.62 153116.942 75856.110 FALSE 0.16713987
## 1052 187456.12 21843.367 16436.189 TRUE 0.11652523
## 1053 2136847.69 353199.328 36429.821 TRUE 0.16528989
## 1054 574498.85 39170.200 23348.167 FALSE 0.06818151
## 1055 3150729.64 292218.685 245291.753 FALSE 0.09274635
## 1056 2265325.30 166888.680 113289.866 FALSE 0.07367096
## 1057 4680090.62 827328.622 183420.928 TRUE 0.17677620
## 1058 1956239.39 337937.269 95389.806 TRUE 0.17274842
## 1059 2794103.29 554994.272 279362.702 TRUE 0.19863055
## 1060 4594984.34 452770.640 261405.316 TRUE 0.09853584
## 1061 7570731.06 883561.184 612381.541 TRUE 0.11670751
## 1062 73939.28 13218.502 3802.282 FALSE 0.17877511
## 1063 5384941.33 278765.273 134423.570 TRUE 0.05176756
## 1064 940334.15 135398.593 19370.418 FALSE 0.14398987
## 1065 1511380.69 210207.410 20108.062 TRUE 0.13908303
## 1066 2714008.62 166526.558 256227.564 TRUE 0.06135815
## 1067 2995752.47 181685.323 276650.770 TRUE 0.06064764
## 1068 1329089.83 264400.710 102206.323 FALSE 0.19893366
## 1069 1203689.16 127766.246 65771.787 TRUE 0.10614555
## 1070 4068885.61 651821.691 228934.878 TRUE 0.16019661
## 1071 4476227.71 273407.608 302108.626 FALSE 0.06107991
## 1072 3121048.19 416427.308 55627.511 FALSE 0.13342547
## 1073 1154327.43 179704.434 109782.989 FALSE 0.15567891
## 1074 5389076.03 561384.584 276482.884 TRUE 0.10417084
## 1075 6543581.21 726788.519 609354.615 FALSE 0.11106892
## 1076 3484506.39 196269.870 216903.535 FALSE 0.05632645
## 1077 785370.89 53591.179 74791.718 FALSE 0.06823678
## 1078 7097705.06 509036.701 318230.483 TRUE 0.07171849
## 1079 3663317.40 410866.154 39154.340 FALSE 0.11215685
## 1080 5775931.07 1001527.322 574834.806 TRUE 0.17339669
## 1081 3066087.06 401601.686 231306.756 TRUE 0.13098183
## 1082 7633141.24 1337988.836 585222.212 TRUE 0.17528679
## 1083 2025680.85 240627.689 164977.770 TRUE 0.11878855
## 1084 5236367.41 460322.113 327100.908 FALSE 0.08790867
## 1085 4359615.82 584325.411 185077.637 TRUE 0.13403140
## 1086 1696008.53 240044.753 129751.985 TRUE 0.14153511
## 1087 4293279.95 254756.553 220764.011 FALSE 0.05933844
## 1088 5937015.40 853525.986 199141.980 FALSE 0.14376348
## 1089 1324418.54 200778.540 41069.985 TRUE 0.15159750
## 1090 6311918.54 1070032.002 447213.780 FALSE 0.16952564
## 1091 6757458.10 726501.882 587873.057 FALSE 0.10751112
## 1092 7209016.63 466708.079 236105.497 TRUE 0.06473949
## 1093 5046712.24 851753.593 363622.748 FALSE 0.16877396
## 1094 7352062.37 887323.399 114710.658 TRUE 0.12069041
## 1095 285888.83 54636.436 20025.589 TRUE 0.19111077
## 1096 176912.51 16116.138 14314.848 FALSE 0.09109665
## 1097 3171328.69 503479.763 247559.845 FALSE 0.15875988
## 1098 6198178.99 1032583.030 120772.766 FALSE 0.16659458
## 1099 3342521.83 600536.037 262299.216 TRUE 0.17966555
## 1100 5948678.23 774809.751 395592.872 FALSE 0.13024906
## 1101 2348518.21 193832.089 170763.761 FALSE 0.08253378
## 1102 340696.62 50083.582 7946.487 FALSE 0.14700346
## 1103 6361539.49 511802.786 302890.315 TRUE 0.08045266
## 1104 5021046.87 573921.239 78252.026 TRUE 0.11430310
## 1105 6353301.40 1180273.224 288572.674 TRUE 0.18577321
## 1106 7113058.61 665973.370 490149.770 FALSE 0.09362686
## 1107 5463583.34 631037.469 513019.579 TRUE 0.11549883
## 1108 5964023.72 586449.555 213378.906 TRUE 0.09833119
## 1109 4230688.80 331297.151 217195.540 FALSE 0.07830809
## 1110 1855010.41 140144.191 89968.182 TRUE 0.07554901
## 1111 1278984.31 153977.406 83411.859 FALSE 0.12039038
## 1112 6729471.19 1185866.160 151581.287 FALSE 0.17621981
## 1113 7988732.43 427389.262 82097.061 FALSE 0.05349901
## 1114 7033987.85 449960.480 280003.810 TRUE 0.06396947
## 1115 1988934.95 245644.250 188918.596 FALSE 0.12350542
## 1116 2057455.84 385913.784 116787.419 TRUE 0.18756844
## 1117 3714465.24 355210.204 165381.391 FALSE 0.09562889
## 1118 2652442.12 435036.280 34203.101 FALSE 0.16401349
## 1119 4058160.21 803786.120 276459.082 TRUE 0.19806663
## 1120 3472598.10 561896.857 262950.722 FALSE 0.16180878
## 1121 1737597.38 158842.919 173636.076 FALSE 0.09141526
## 1122 5574813.47 680036.813 150973.505 FALSE 0.12198378
## 1123 7374002.55 612176.654 648881.640 FALSE 0.08301823
## 1124 6378000.12 789311.553 187149.689 FALSE 0.12375534
## 1125 3266405.63 354377.413 313854.665 FALSE 0.10849155
## 1126 6052964.71 854980.170 382786.369 FALSE 0.14124982
## 1127 6505725.67 1295200.356 404115.402 FALSE 0.19908622
## 1128 5124540.64 651569.298 104857.575 FALSE 0.12714687
## 1129 6817586.65 973198.633 458032.365 FALSE 0.14274826
## 1130 1181886.64 159833.978 45410.857 TRUE 0.13523630
## 1131 5038729.22 770795.403 176882.205 FALSE 0.15297417
## 1132 4423974.04 310275.318 279911.967 TRUE 0.07013498
## 1133 5933946.00 1014276.052 225345.089 TRUE 0.17092775
## 1134 4450997.12 799772.519 336559.790 TRUE 0.17968390
## 1135 1522649.63 178082.755 85602.239 FALSE 0.11695583
## 1136 165965.31 12272.592 12241.497 FALSE 0.07394673
## 1137 6987541.32 846871.042 165277.419 TRUE 0.12119729
## 1138 5605701.74 667058.847 249698.255 TRUE 0.11899649
## 1139 6863931.63 599378.699 631496.967 TRUE 0.08732294
## 1140 5277640.65 646606.850 331227.010 FALSE 0.12251817
## 1141 4304349.36 696768.294 217799.934 TRUE 0.16187540
## 1142 5806196.50 991943.142 298726.568 FALSE 0.17084216
## 1143 1084846.38 94162.245 67885.871 FALSE 0.08679777
## 1144 2825282.23 164285.042 195737.157 TRUE 0.05814819
## 1145 3435010.12 525015.025 292715.468 TRUE 0.15284235
## 1146 4375086.81 588641.270 72106.484 TRUE 0.13454391
## 1147 2028561.38 204717.715 23617.878 FALSE 0.10091768
## 1148 3191582.74 301677.046 205881.336 TRUE 0.09452271
## 1149 7025155.69 568830.208 433492.293 FALSE 0.08097048
## 1150 3507202.62 574532.254 59706.118 TRUE 0.16381496
## 1151 6817659.28 909879.990 362154.208 TRUE 0.13345929
## 1152 4181963.41 784111.100 316352.688 FALSE 0.18749832
## 1153 2012971.27 124488.076 105636.645 FALSE 0.06184295
## 1154 5027894.93 272172.403 466868.685 TRUE 0.05413248
## 1155 2429161.51 480926.384 216376.494 TRUE 0.19798041
## 1156 6220491.61 823290.288 289318.061 TRUE 0.13235132
## 1157 5564786.13 508032.136 198395.495 TRUE 0.09129410
## 1158 2810689.97 448539.479 234703.988 TRUE 0.15958341
## 1159 3888635.84 417699.195 379381.040 TRUE 0.10741535
## 1160 2844354.55 549381.235 218125.977 TRUE 0.19314794
## 1161 6445214.13 674073.344 509803.376 FALSE 0.10458510
## 1162 1123527.98 87010.329 108983.978 TRUE 0.07744385
## 1163 1843805.76 105735.887 39651.128 TRUE 0.05734654
## 1164 3592335.02 217250.588 153231.650 TRUE 0.06047615
## 1165 6863118.73 1082303.992 498777.012 FALSE 0.15769857
## 1166 2638884.15 210258.089 221043.807 FALSE 0.07967689
## 1167 555729.95 99251.637 19448.704 FALSE 0.17859688
## 1168 6072796.76 609493.116 451879.577 FALSE 0.10036448
## 1169 3730610.18 301409.877 66825.008 TRUE 0.08079372
## 1170 1381413.34 149047.284 37391.331 TRUE 0.10789478
## 1171 1373984.21 252999.654 66161.095 FALSE 0.18413578
## 1172 113062.65 9988.410 10987.449 TRUE 0.08834403
## 1173 7845326.33 411143.985 204150.171 TRUE 0.05240623
## 1174 2177552.90 205207.354 55170.554 FALSE 0.09423760
## 1175 2083310.73 271835.133 126159.273 FALSE 0.13048228
## 1176 3126775.07 534172.740 215629.272 TRUE 0.17083824
## 1177 914138.65 116030.512 18530.014 FALSE 0.12692879
## 1178 1214804.65 155895.010 38597.493 FALSE 0.12832928
## 1179 1901590.85 134780.906 50329.872 FALSE 0.07087797
## 1180 7073010.73 1031348.733 88330.498 FALSE 0.14581467
## 1181 106285.48 15392.038 9897.124 FALSE 0.14481788
## 1182 1010232.08 89002.140 41972.871 FALSE 0.08810069
## 1183 3533146.23 225382.692 168441.507 FALSE 0.06379093
## 1184 6794646.31 578638.218 543361.056 TRUE 0.08516090
## 1185 5930263.48 900083.634 399520.657 FALSE 0.15177802
## 1186 793499.04 136952.127 33802.272 TRUE 0.17259268
## 1187 4501857.25 508757.682 431550.121 FALSE 0.11301062
## 1188 4473522.25 659436.984 130242.840 FALSE 0.14740890
## 1189 5761449.72 1035732.805 97050.790 FALSE 0.17976948
## 1190 2850833.10 403148.796 88689.002 FALSE 0.14141438
## 1191 1711130.59 174810.482 52434.021 TRUE 0.10216081
## 1192 2731284.69 426733.619 272129.498 TRUE 0.15623916
## 1193 1467802.40 73921.677 86458.342 TRUE 0.05036214
## 1194 7861517.08 1505836.728 618615.314 FALSE 0.19154531
## 1195 2553243.08 186349.569 187975.386 FALSE 0.07298544
## 1196 7547733.25 1333857.184 707926.776 FALSE 0.17672288
## 1197 628746.70 97437.929 17812.408 TRUE 0.15497168
## 1198 7253333.61 660919.905 119420.129 FALSE 0.09111947
## 1199 574645.38 58553.556 6027.023 TRUE 0.10189511
## 1200 4579990.88 324477.287 78264.062 FALSE 0.07084671
## 1201 7138524.17 1426029.468 187795.524 TRUE 0.19976531
## 1202 4684303.99 868862.008 346827.365 FALSE 0.18548369
## 1203 6942417.13 1161281.629 607653.691 FALSE 0.16727339
## 1204 5555157.36 366117.614 451785.720 FALSE 0.06590589
## 1205 1795741.63 343447.408 114433.705 FALSE 0.19125658
## 1206 5796583.16 832653.738 429638.226 TRUE 0.14364561
## 1207 2817512.91 413513.594 103924.071 TRUE 0.14676547
## 1208 5527219.58 465327.309 158853.967 TRUE 0.08418832
## 1209 5108423.08 497678.132 364160.503 FALSE 0.09742305
## 1210 4257235.03 445902.345 123053.541 FALSE 0.10473989
## 1211 7334767.05 411158.211 489795.754 FALSE 0.05605607
## 1212 638568.71 95587.214 60941.851 FALSE 0.14968979
## 1213 7125225.29 976595.062 468330.629 FALSE 0.13706164
## 1214 3123519.38 365973.733 278360.303 FALSE 0.11716711
## 1215 7310740.18 999427.012 457105.630 TRUE 0.13670668
## 1216 4006949.10 587421.122 90824.735 TRUE 0.14660059
## 1217 7250239.71 898517.419 443245.504 FALSE 0.12392934
## 1218 5381042.41 285823.775 453673.099 FALSE 0.05311680
## 1219 1183063.16 212203.759 17982.051 TRUE 0.17936807
## 1220 1900869.57 330212.641 173502.182 TRUE 0.17371662
## 1221 4949161.96 707189.061 367407.135 FALSE 0.14289067
## 1222 7016773.52 1018881.682 441241.226 TRUE 0.14520658
## 1223 3278817.06 419520.888 322297.024 FALSE 0.12794885
## 1224 1627872.83 105645.296 77236.612 FALSE 0.06489776
## 1225 1204138.88 78882.182 23147.903 FALSE 0.06550921
## 1226 3263657.87 317187.239 40060.682 FALSE 0.09718765
## 1227 2252938.34 354581.423 65266.192 FALSE 0.15738621
## 1228 6406425.35 423741.736 318898.953 TRUE 0.06614324
## 1229 4173022.07 581714.351 345041.742 FALSE 0.13939882
## 1230 1998544.12 394296.773 40071.507 FALSE 0.19729200
## 1231 2053477.36 406507.780 111934.596 FALSE 0.19796068
## 1232 7053410.87 949215.183 455719.499 TRUE 0.13457534
## 1233 2139753.92 115118.003 49304.890 TRUE 0.05379965
## 1234 2854487.77 278150.205 157011.213 FALSE 0.09744312
## 1235 2232133.13 358976.137 188029.788 TRUE 0.16082201
## 1236 3078998.53 610513.738 177028.154 TRUE 0.19828322
## 1237 6493942.20 505597.105 148520.381 FALSE 0.07785673
## 1238 2211614.65 289874.495 54346.876 TRUE 0.13106917
## 1239 6878554.21 1248721.199 665877.263 FALSE 0.18153832
## 1240 4230328.49 640056.805 402728.140 FALSE 0.15130192
## 1241 1236095.84 159462.567 105873.722 FALSE 0.12900502
## 1242 2010057.50 320677.106 142599.468 TRUE 0.15953628
## 1243 5302132.08 711897.671 299368.807 TRUE 0.13426630
## 1244 7926432.18 1220127.528 685535.434 FALSE 0.15393149
## 1245 871761.64 116378.728 49563.220 TRUE 0.13349834
## 1246 4925052.32 275617.327 488778.983 FALSE 0.05596231
## 1247 974532.39 99681.351 53252.612 TRUE 0.10228634
## 1248 294147.12 16806.348 5239.034 FALSE 0.05713586
## 1249 2664358.56 284941.041 31869.269 FALSE 0.10694546
## 1250 5286869.23 441157.080 199421.105 TRUE 0.08344392
## 1251 5367410.18 339578.075 479236.143 FALSE 0.06326665
## 1252 94873.87 10836.281 4494.710 TRUE 0.11421776
## 1253 4274773.13 835287.110 56664.918 FALSE 0.19539917
## 1254 6281717.41 1222475.464 397315.343 FALSE 0.19460848
## 1255 2601952.79 431643.788 224098.904 TRUE 0.16589224
## 1256 2633416.03 229343.934 42955.117 FALSE 0.08708990
## 1257 4712468.48 798007.125 163205.030 FALSE 0.16933951
## 1258 126684.54 10402.916 2629.755 TRUE 0.08211670
## 1259 3599504.55 689501.385 192064.029 FALSE 0.19155453
## 1260 2384780.21 476321.384 143092.165 TRUE 0.19973387
## 1261 6315060.11 316909.658 296376.144 FALSE 0.05018316
## 1262 3230309.86 595543.643 162110.989 FALSE 0.18436115
## 1263 946297.61 142136.333 58616.848 FALSE 0.15020257
## 1264 4211364.46 443460.729 397254.611 FALSE 0.10530096
## 1265 4792768.80 264931.818 206397.479 TRUE 0.05527740
## 1266 3646084.97 204579.047 262574.786 FALSE 0.05610924
## 1267 5560817.20 997023.616 59847.530 TRUE 0.17929444
## 1268 5845184.12 768494.633 452329.739 FALSE 0.13147484
## 1269 3681437.10 611019.637 137236.885 FALSE 0.16597313
## 1270 4434921.48 841268.016 408796.137 TRUE 0.18969175
## 1271 2692865.76 477266.010 135729.304 FALSE 0.17723349
## 1272 622558.14 121935.123 33743.512 FALSE 0.19586142
## 1273 6441861.65 1273226.227 351431.508 FALSE 0.19764880
## 1274 2358456.79 248671.367 229891.603 FALSE 0.10543817
## 1275 1692411.15 95242.302 36451.936 TRUE 0.05627610
## 1276 7971792.51 1565476.607 254654.014 FALSE 0.19637699
## 1277 1445497.90 188308.550 101611.051 FALSE 0.13027245
## 1278 781716.15 127133.575 53122.520 TRUE 0.16263394
## 1279 2981577.81 228677.247 136137.655 FALSE 0.07669672
## 1280 1281751.67 93477.042 37497.381 TRUE 0.07292914
## 1281 3008082.87 428982.893 50868.284 FALSE 0.14261006
## 1282 424246.75 27698.904 28184.104 FALSE 0.06528961
## 1283 592795.35 31775.703 16754.936 FALSE 0.05360316
## 1284 3797992.04 251418.680 294613.765 TRUE 0.06619779
## 1285 2791182.78 338368.502 95797.023 FALSE 0.12122764
## 1286 2984831.15 487268.769 186969.563 TRUE 0.16324835
## 1287 4219105.67 418942.063 334720.540 TRUE 0.09929641
## 1288 4326374.04 525040.131 217314.873 FALSE 0.12135801
## 1289 552641.94 58242.345 40710.945 TRUE 0.10538893
## 1290 3220416.10 346931.905 69591.925 FALSE 0.10772891
## 1291 4598948.07 575495.468 398399.126 TRUE 0.12513633
## 1292 1034871.02 115571.775 12403.277 TRUE 0.11167747
## 1293 4886537.94 805259.316 187036.819 FALSE 0.16479138
## 1294 6011315.70 453690.539 99810.495 FALSE 0.07547275
## 1295 5985907.71 693653.318 370134.329 FALSE 0.11588106
## 1296 4157603.05 554937.829 130802.032 FALSE 0.13347542
## 1297 6826471.01 1231626.258 284328.554 FALSE 0.18041917
## 1298 6979202.89 1005561.000 652089.300 FALSE 0.14407963
## 1299 2033524.10 311735.161 26596.501 TRUE 0.15329799
## 1300 2551580.46 292619.022 153599.104 FALSE 0.11468148
## 1301 397394.69 71796.369 5591.727 FALSE 0.18066766
## 1302 356243.06 30844.219 30519.799 FALSE 0.08658195
## 1303 1345106.73 252852.243 26807.343 TRUE 0.18797932
## 1304 4143934.56 492352.613 77528.442 TRUE 0.11881284
## 1305 5302682.14 338208.865 479259.198 FALSE 0.06378072
## 1306 5793273.70 679653.795 238800.727 TRUE 0.11731774
## 1307 983491.28 92572.132 11815.981 FALSE 0.09412603
## 1308 795193.81 134609.456 11180.892 TRUE 0.16927880
## 1309 6431142.09 367783.898 535816.792 TRUE 0.05718796
## 1310 3270801.31 434444.439 254144.166 FALSE 0.13282508
## 1311 2235236.31 255027.266 193701.146 FALSE 0.11409410
## 1312 892909.82 154106.913 11975.347 FALSE 0.17258956
## 1313 6637176.71 857023.444 574290.382 FALSE 0.12912470
## 1314 2896052.24 481218.111 38205.666 FALSE 0.16616348
## 1315 6887939.20 1369095.597 87827.049 TRUE 0.19876709
## 1316 1406391.64 194456.208 109751.725 TRUE 0.13826604
## 1317 6935462.47 424274.121 548839.000 TRUE 0.06117460
## 1318 303259.21 17939.199 11701.407 FALSE 0.05915467
## 1319 3622762.83 437062.856 47648.853 FALSE 0.12064352
## 1320 5153408.06 914855.883 184379.576 FALSE 0.17752444
## 1321 1520622.75 298278.752 63180.327 TRUE 0.19615566
## 1322 4106695.46 474313.099 377669.653 FALSE 0.11549751
## 1323 6745140.13 1193063.556 634467.309 TRUE 0.17687750
## 1324 7450595.00 1191564.354 283072.844 TRUE 0.15992875
## 1325 5267956.91 551267.568 267564.711 TRUE 0.10464542
## 1326 5011901.84 885786.313 473540.626 FALSE 0.17673656
## 1327 5678954.28 803068.035 461864.716 TRUE 0.14141125
## 1328 2182395.40 394333.059 85597.067 TRUE 0.18068818
## 1329 3801640.93 609044.359 363605.512 FALSE 0.16020565
## 1330 651299.36 118603.304 24672.533 TRUE 0.18210260
## 1331 5363809.18 1035816.571 133620.061 FALSE 0.19311212
## 1332 5650814.59 485348.138 466760.599 TRUE 0.08588994
## 1333 233730.60 46555.523 4723.624 TRUE 0.19918454
## 1334 4059167.33 775369.904 92451.085 FALSE 0.19101698
## 1335 396964.78 51704.222 36702.780 TRUE 0.13024889
## 1336 908382.48 89392.232 17546.189 FALSE 0.09840814
## 1337 2010399.96 164395.190 111405.012 TRUE 0.08177238
## 1338 450371.83 42694.146 24625.902 TRUE 0.09479755
## 1339 4535680.71 841208.257 300706.767 FALSE 0.18546461
## 1340 2424927.51 293052.413 41088.126 TRUE 0.12084997
## 1341 4299383.18 729341.167 196369.873 FALSE 0.16963856
## 1342 1578952.81 252978.058 71777.771 FALSE 0.16021888
## 1343 6127088.47 345547.827 122927.389 FALSE 0.05639674
## 1344 295569.15 37651.185 22266.169 TRUE 0.12738537
## 1345 4695349.09 832733.069 211893.193 FALSE 0.17735275
## 1346 7234183.11 764134.121 689204.989 FALSE 0.10562825
## 1347 5541099.17 581829.377 183723.523 FALSE 0.10500252
## 1348 7813286.80 802544.676 656759.066 TRUE 0.10271537
## 1349 3387591.83 174977.313 137616.901 TRUE 0.05165242
## 1350 910247.72 144541.643 66630.823 TRUE 0.15879374
## 1351 6414178.28 747175.051 279098.954 FALSE 0.11648804
## 1352 3539431.19 610522.431 178967.875 FALSE 0.17249168
## 1353 2032986.13 332985.956 78290.000 FALSE 0.16379155
## 1354 6142690.99 591393.504 94919.640 FALSE 0.09627597
## 1355 7123514.44 889958.973 646537.606 TRUE 0.12493257
## 1356 4774973.55 923970.538 473359.057 TRUE 0.19350276
## 1357 6042293.49 765638.698 574091.213 TRUE 0.12671326
## 1358 5329657.47 944079.654 238527.047 FALSE 0.17713702
## 1359 5634467.91 979234.090 297276.959 FALSE 0.17379353
## 1360 1161239.25 175866.202 100457.226 FALSE 0.15144700
## 1361 6872503.87 360379.640 517639.647 FALSE 0.05243790
## 1362 2651819.39 240388.504 202837.965 TRUE 0.09065041
## 1363 4723295.44 521162.989 425927.879 FALSE 0.11033885
## 1364 1935191.06 169974.496 78107.727 FALSE 0.08783344
## 1365 3117826.80 509045.575 263620.924 FALSE 0.16326936
## 1366 5286919.66 521013.554 93081.959 TRUE 0.09854766
## 1367 5437160.47 1085905.834 527145.238 TRUE 0.19971929
## 1368 242204.52 45530.663 22802.256 FALSE 0.18798437
## 1369 5791891.29 1008634.221 574206.152 FALSE 0.17414592
## 1370 2146272.97 405206.930 92321.319 FALSE 0.18879562
## 1371 3468770.76 312992.112 126177.006 FALSE 0.09023142
## 1372 1947551.15 340459.920 47192.690 FALSE 0.17481437
## 1373 3747194.34 527988.635 366572.830 TRUE 0.14090239
## 1374 2253914.13 151525.511 168976.927 FALSE 0.06722772
## 1375 5658404.68 1035939.319 369269.842 TRUE 0.18307975
## 1376 666525.97 119083.517 62276.878 FALSE 0.17866298
## 1377 4015314.19 580273.348 375893.969 TRUE 0.14451505
## 1378 1550111.08 144588.035 44555.727 FALSE 0.09327592
## 1379 903864.55 63917.432 75378.077 TRUE 0.07071572
## 1380 883087.53 169466.986 60486.255 TRUE 0.19190282
## 1381 6573850.92 865942.875 83670.469 TRUE 0.13172536
## 1382 7339546.02 786341.858 465111.422 FALSE 0.10713767
## 1383 1797772.45 113314.545 159228.573 TRUE 0.06303053
## 1384 2863790.87 173254.538 163563.319 TRUE 0.06049832
## 1385 1349022.81 168088.533 112717.381 FALSE 0.12460022
## 1386 2153872.01 274619.949 52196.519 FALSE 0.12750059
## 1387 5128210.09 272773.343 428891.675 TRUE 0.05319075
## 1388 4557103.86 546162.473 407864.562 TRUE 0.11984859
## 1389 6051255.12 410262.759 414643.585 TRUE 0.06779796
## 1390 5349052.41 662085.571 382253.914 TRUE 0.12377624
## 1391 1300313.65 107490.314 66542.175 TRUE 0.08266491
## 1392 4850635.00 406987.716 75438.933 TRUE 0.08390401
## 1393 4273528.92 324526.398 403424.152 FALSE 0.07593874
## 1394 1360395.80 182685.442 132089.786 FALSE 0.13428845
## 1395 2240339.51 149125.282 171822.675 FALSE 0.06656370
## 1396 1024793.91 193119.993 37003.137 FALSE 0.18844764
## 1397 3161524.00 627084.172 190388.997 FALSE 0.19834870
## 1398 4762353.64 620596.481 111597.550 TRUE 0.13031298
## 1399 923764.24 75228.631 68883.297 FALSE 0.08143705
## 1400 3524789.15 696751.200 241358.282 FALSE 0.19767174
## 1401 777560.71 111132.697 64380.653 TRUE 0.14292479
## 1402 3811678.31 506469.944 89609.221 FALSE 0.13287321
## 1403 1074127.57 82034.128 44937.341 TRUE 0.07637280
## 1404 2023491.09 393206.543 147679.024 FALSE 0.19432087
## 1405 5467922.50 588212.450 229675.597 TRUE 0.10757513
## 1406 3714037.61 431096.499 341391.230 TRUE 0.11607220
## 1407 5009039.84 605696.364 313843.872 FALSE 0.12092065
## 1408 4002885.90 410502.696 131517.732 FALSE 0.10255169
## 1409 3579954.46 423473.457 325906.424 TRUE 0.11829018
## 1410 4034259.86 338795.978 246222.818 TRUE 0.08397971
## 1411 669994.25 36209.059 20796.006 TRUE 0.05404384
## 1412 5721513.53 1143755.010 400221.539 TRUE 0.19990427
## 1413 5209132.92 913886.267 491607.398 TRUE 0.17543923
## 1414 495934.27 54980.130 7304.435 FALSE 0.11086173
## 1415 1207177.49 94684.969 119606.495 TRUE 0.07843500
## 1416 627821.86 46646.662 39093.015 TRUE 0.07429920
## 1417 2801885.35 435656.823 58900.952 FALSE 0.15548703
## 1418 2618945.61 297130.699 147629.683 FALSE 0.11345432
## 1419 1220471.36 105748.980 103649.559 TRUE 0.08664601
## 1420 4370189.13 819254.094 43919.180 FALSE 0.18746422
## 1421 2885403.98 368836.825 288446.786 TRUE 0.12782849
## 1422 5083044.05 694868.274 392413.397 TRUE 0.13670318
## 1423 3548502.76 326544.552 149903.659 FALSE 0.09202319
## 1424 3585528.82 667197.828 180329.447 FALSE 0.18608073
## 1425 6967064.06 1000402.494 229399.177 FALSE 0.14359025
## 1426 1361640.29 241671.406 54088.634 FALSE 0.17748550
## 1427 1304954.36 175709.067 112899.649 FALSE 0.13464767
## 1428 7270426.10 453463.605 685459.540 FALSE 0.06237098
## 1429 6752575.25 959383.607 172582.566 FALSE 0.14207670
## 1430 180320.40 27441.024 4285.307 TRUE 0.15217925
## 1431 6363912.62 538964.131 586606.910 TRUE 0.08469069
## 1432 4624863.71 758601.882 434463.947 TRUE 0.16402686
## 1433 1975752.40 354606.633 94271.410 TRUE 0.17947929
## 1434 4851573.33 421601.935 82613.828 FALSE 0.08690004
## 1435 6728011.61 623142.134 309700.082 FALSE 0.09261906
## 1436 4370836.89 282687.426 159084.999 TRUE 0.06467581
## 1437 3327703.47 491777.228 227351.445 FALSE 0.14778277
## 1438 4164673.55 735039.412 264904.600 FALSE 0.17649388
## 1439 7305767.85 670899.958 618299.701 TRUE 0.09183155
## 1440 5569962.69 297074.540 276080.960 TRUE 0.05333510
## 1441 6975610.23 1204547.431 290985.006 FALSE 0.17267986
## 1442 794217.65 66053.185 25159.832 TRUE 0.08316761
## 1443 5408012.59 887553.936 491064.312 TRUE 0.16411832
## 1444 4386809.78 338668.079 420023.360 FALSE 0.07720145
## 1445 5412146.13 769291.581 322978.536 FALSE 0.14214169
## 1446 4001985.51 339831.231 173621.610 FALSE 0.08491566
## 1447 3371087.26 402467.176 310321.235 FALSE 0.11938794
## 1448 398818.73 34316.359 24922.885 TRUE 0.08604500
## 1449 6822119.61 730111.153 523590.455 TRUE 0.10702116
## 1450 2105279.67 266287.969 188238.634 FALSE 0.12648579
## 1451 375912.30 53481.104 10101.711 TRUE 0.14227016
## 1452 2563490.16 197837.564 229067.183 TRUE 0.07717508
## 1453 7490769.24 1199554.126 144234.763 FALSE 0.16013764
## 1454 2805017.97 523845.579 112925.038 TRUE 0.18675302
## 1455 3703109.73 619600.386 67041.784 TRUE 0.16731894
## 1456 4332080.67 577673.377 238165.396 TRUE 0.13334779
## 1457 1647752.59 125101.554 153140.580 FALSE 0.07592254
## 1458 6917110.92 751580.027 610592.158 TRUE 0.10865519
## 1459 443648.19 52800.582 26745.119 FALSE 0.11901453
## 1460 593901.40 49604.721 52598.186 TRUE 0.08352350
## 1461 4088479.18 218760.850 110457.310 FALSE 0.05350666
## 1462 4638387.03 816317.349 158473.034 FALSE 0.17599164
## 1463 6010317.38 1199755.154 230012.362 FALSE 0.19961594
## 1464 2583008.30 189593.329 140143.868 FALSE 0.07340020
## 1465 1372567.99 107583.000 90129.584 FALSE 0.07838082
## 1466 5016800.42 702380.796 151298.820 FALSE 0.14000573
## 1467 974935.55 144088.800 88549.436 TRUE 0.14779315
## 1468 462367.03 37243.419 5086.626 FALSE 0.08054947
## 1469 3781198.38 728383.992 111808.136 FALSE 0.19263311
## 1470 7089774.25 1001168.756 534296.849 FALSE 0.14121307
## 1471 6726396.96 593625.696 180030.700 FALSE 0.08825315
## 1472 5968891.43 665506.534 497556.191 TRUE 0.11149583
## 1473 2643914.74 507409.154 127838.818 FALSE 0.19191585
## 1474 2481658.09 158881.643 33919.623 TRUE 0.06402237
## 1475 3143321.11 224237.315 155029.715 FALSE 0.07133771
## 1476 4317535.92 466213.545 213873.727 FALSE 0.10798139
## 1477 7245735.41 1422619.953 441498.100 FALSE 0.19633893
## 1478 7535381.44 619851.912 347129.608 FALSE 0.08225886
## 1479 3742602.73 292502.672 173610.556 FALSE 0.07815488
## 1480 2484822.38 372676.869 164497.863 TRUE 0.14998129
## 1481 6225554.58 594345.201 436450.796 FALSE 0.09546864
## 1482 2529279.40 351474.357 189819.252 FALSE 0.13896225
## 1483 430599.02 66993.316 14360.748 FALSE 0.15558168
## 1484 5607959.05 967107.522 203803.131 TRUE 0.17245267
## 1485 2049686.99 155228.822 114550.747 FALSE 0.07573294
## 1486 5140527.19 637097.334 487478.595 FALSE 0.12393619
## 1487 2354965.09 426088.514 117310.356 FALSE 0.18093199
## 1488 2275487.39 339180.129 106619.946 FALSE 0.14905823
## 1489 8302766.60 1348056.657 607842.674 TRUE 0.16236235
## 1490 3912760.02 650896.880 110596.707 FALSE 0.16635236
## 1491 2874045.78 507920.806 56991.898 TRUE 0.17672676
## 1492 6830982.37 1104798.759 558510.003 TRUE 0.16173351
## 1493 3970652.58 653762.675 280956.596 TRUE 0.16464867
## 1494 6970675.44 446740.229 166880.619 TRUE 0.06408851
## 1495 5503612.73 1014870.646 300824.961 FALSE 0.18440081
## 1496 1502514.69 75175.955 148249.910 FALSE 0.05003342
## 1497 4451460.79 828213.435 313117.464 TRUE 0.18605430
## 1498 5562739.98 867958.255 257445.500 TRUE 0.15603071
## 1499 2109636.95 205189.743 126685.750 FALSE 0.09726306
## 1500 2508841.43 434019.500 221017.299 FALSE 0.17299599
## 1501 3757662.88 641230.618 123569.540 FALSE 0.17064613
## 1502 4892529.56 426705.998 56555.417 FALSE 0.08721582
## 1503 6924129.92 365442.776 342872.190 FALSE 0.05277815
## 1504 2444282.13 470042.799 127581.648 TRUE 0.19230301
## 1505 1943486.11 218450.892 38666.042 TRUE 0.11240157
## 1506 5256502.30 293196.295 91311.841 FALSE 0.05577783
## 1507 3719628.86 637827.155 142793.160 FALSE 0.17147602
## 1508 4081444.19 803126.264 339258.067 TRUE 0.19677502
## 1509 5877249.49 540939.757 382758.454 FALSE 0.09203961
## 1510 3488376.67 670683.487 245805.267 TRUE 0.19226235
## 1511 1358649.13 156446.278 45953.282 FALSE 0.11514840
## 1512 1689819.62 303021.155 62682.356 TRUE 0.17932160
## 1513 3779636.36 289532.747 216675.277 TRUE 0.07660333
## 1514 6194029.69 1125873.949 464099.631 FALSE 0.18176761
## 1515 3389485.93 265865.393 314732.423 TRUE 0.07843826
## 1516 2624634.21 302637.564 31764.260 TRUE 0.11530657
## 1517 261474.79 45049.032 14183.656 FALSE 0.17228824
## 1518 7019603.07 1272459.026 511323.793 FALSE 0.18127222
## 1519 3991336.38 328897.273 380115.746 TRUE 0.08240279
## 1520 8322758.55 1566511.158 140446.549 TRUE 0.18822019
## 1521 1248714.65 124836.764 62774.531 FALSE 0.09997221
## 1522 4048378.23 233201.277 186414.546 TRUE 0.05760363
## 1523 1321474.96 119404.129 16480.912 TRUE 0.09035671
## 1524 5332643.65 1026265.997 168078.067 TRUE 0.19244976
## 1525 3909655.07 422560.573 55538.449 TRUE 0.10808129
## 1526 2795083.69 456807.254 170119.511 FALSE 0.16343241
## 1527 195807.77 36973.612 17626.052 FALSE 0.18882607
## 1528 2157763.94 361235.496 47498.330 FALSE 0.16741196
## 1529 1179758.85 122048.413 99835.951 FALSE 0.10345200
## 1530 4017176.25 686390.351 272017.587 TRUE 0.17086389
## 1531 1263899.65 96386.062 45893.321 FALSE 0.07626085
## 1532 2662209.52 455316.938 259250.768 TRUE 0.17102972
## 1533 360271.84 18870.818 5746.379 FALSE 0.05237939
## 1534 1564335.47 143552.587 125049.601 FALSE 0.09176586
## 1535 7545641.66 1276654.362 379187.568 TRUE 0.16919096
## 1536 4850656.31 414640.400 470217.790 FALSE 0.08548130
## 1537 860560.82 43209.451 16907.856 FALSE 0.05021080
## 1538 1482917.14 263327.115 44638.622 TRUE 0.17757372
## 1539 1368436.59 155294.503 48348.327 FALSE 0.11348316
## 1540 3617345.62 454018.300 221107.702 TRUE 0.12551145
## 1541 4267043.95 687151.880 92719.561 FALSE 0.16103698
## 1542 1422419.09 77242.294 26704.027 FALSE 0.05430347
## 1543 5220670.95 814639.740 281613.793 FALSE 0.15604120
## 1544 5186850.61 922936.900 54262.109 FALSE 0.17793782
## 1545 5174807.04 276756.295 55058.462 FALSE 0.05348147
## 1546 986569.31 138360.746 66794.809 TRUE 0.14024432
## 1547 475855.35 64381.643 15826.167 FALSE 0.13529667
## 1548 1853932.43 161148.826 124102.025 TRUE 0.08692271
## 1549 6709440.34 673687.084 471204.162 TRUE 0.10040883
## 1550 5381975.63 623498.094 66259.792 TRUE 0.11584930
## 1551 6996528.93 817365.634 135724.477 FALSE 0.11682445
## 1552 3108699.79 316135.802 279595.260 FALSE 0.10169390
## 1553 5681505.64 557322.107 337799.661 FALSE 0.09809409
## 1554 1693094.12 126960.004 74487.081 TRUE 0.07498697
## 1555 4090638.63 567369.994 121916.924 TRUE 0.13869961
## 1556 271024.93 21221.962 7631.942 TRUE 0.07830262
## 1557 5839513.20 399169.264 450505.041 FALSE 0.06835660
## 1558 5317250.21 305088.966 135287.074 TRUE 0.05737721
## 1559 4688956.13 546055.258 248620.128 TRUE 0.11645561
## 1560 5182162.73 446925.423 393626.101 FALSE 0.08624303
## 1561 4957401.79 963118.473 117846.829 TRUE 0.19427888
## 1562 3912998.98 573666.590 130648.845 TRUE 0.14660535
## 1563 4143260.14 354291.145 348793.505 TRUE 0.08551023
## 1564 851372.19 133753.948 12138.427 TRUE 0.15710397
## 1565 3417575.01 509723.318 281257.015 FALSE 0.14914766
## 1566 4562573.83 663436.917 308423.579 FALSE 0.14540848
## 1567 4961887.23 554877.426 351364.931 TRUE 0.11182790
## 1568 4334672.18 781094.043 432923.519 FALSE 0.18019680
## 1569 5508722.81 725976.903 402789.432 TRUE 0.13178679
## 1570 1392865.08 176530.073 24096.073 FALSE 0.12673882
## 1571 4278384.05 395134.182 43898.806 FALSE 0.09235594
## 1572 197438.67 19705.679 15775.915 FALSE 0.09980659
## 1573 4465127.18 353249.158 407623.354 FALSE 0.07911290
## 1574 6987878.09 671432.455 358148.938 TRUE 0.09608531
## 1575 6285517.94 683180.955 78088.530 FALSE 0.10869127
## 1576 5005827.06 267905.272 473508.456 TRUE 0.05351868
## 1577 540595.93 90694.498 16428.866 TRUE 0.16776763
## 1578 6941500.41 660750.899 257856.485 FALSE 0.09518848
## 1579 4937807.46 805591.957 423717.856 TRUE 0.16314771
## 1580 2773087.42 339371.600 211566.340 FALSE 0.12238042
## 1581 3180682.62 345752.776 190145.952 TRUE 0.10870395
## 1582 5346971.83 418621.921 315543.088 FALSE 0.07829140
## 1583 1941909.13 146037.692 152753.996 FALSE 0.07520315
## 1584 6671563.71 779038.877 649928.657 TRUE 0.11677006
## 1585 953658.64 114675.978 74119.941 TRUE 0.12024845
## 1586 3352755.00 320137.301 188647.525 TRUE 0.09548485
## 1587 1212195.00 124822.468 92268.258 FALSE 0.10297227
## 1588 6217023.92 367358.978 496875.967 FALSE 0.05908920
## 1589 2395840.31 220225.604 58181.884 TRUE 0.09191998
## 1590 1607753.98 211448.971 126764.239 FALSE 0.13151824
## 1591 6502376.98 1033739.370 311045.411 TRUE 0.15897869
## 1592 4346212.70 849210.101 407836.927 FALSE 0.19539083
## 1593 6786657.82 564932.451 289224.904 TRUE 0.08324163
## 1594 2942573.70 314765.989 115273.342 TRUE 0.10696962
## 1595 5441005.06 1055928.910 342689.446 FALSE 0.19406872
## 1596 4037311.79 256511.790 193534.744 TRUE 0.06353529
## 1597 6191827.39 618063.044 360110.933 TRUE 0.09981917
## 1598 4162955.58 570044.711 212393.856 TRUE 0.13693269
## 1599 6292715.60 1170283.879 180204.971 FALSE 0.18597438
## 1600 5712886.36 1061066.756 162651.558 TRUE 0.18573217
## 1601 5490417.13 472304.204 434119.664 FALSE 0.08602337
## 1602 6180498.11 835280.025 473604.857 FALSE 0.13514769
## 1603 5749323.55 869130.791 475363.172 FALSE 0.15117097
## 1604 215722.30 29905.851 18592.814 FALSE 0.13863125
## 1605 6464793.01 755551.752 526018.439 FALSE 0.11687176
## 1606 353322.12 58644.545 31006.525 FALSE 0.16598040
## 1607 3115956.06 451271.273 256674.353 TRUE 0.14482594
## 1608 600077.20 42339.325 53534.320 FALSE 0.07055646
## 1609 4398082.53 320419.715 409194.617 FALSE 0.07285441
## 1610 2311970.57 347811.057 26865.705 TRUE 0.15043922
## 1611 6614000.02 913584.367 337412.467 FALSE 0.13812887
## 1612 2581332.98 234693.738 257282.545 TRUE 0.09091959
## 1613 3324356.79 653950.520 256885.476 TRUE 0.19671490
## 1614 482610.77 51857.003 44906.778 TRUE 0.10745099
## 1615 6571929.00 1074365.157 250789.889 TRUE 0.16347790
## 1616 6810110.38 648375.248 269072.867 TRUE 0.09520774
## 1617 1545004.41 287548.510 94736.116 FALSE 0.18611501
## 1618 4396576.70 560905.938 344080.624 FALSE 0.12757788
## 1619 1614684.49 87612.300 127297.422 FALSE 0.05425970
## 1620 2160893.42 301210.321 174429.800 TRUE 0.13939157
## 1621 4382164.76 269540.377 142109.958 TRUE 0.06150850
## 1622 818613.69 149483.084 74225.478 FALSE 0.18260516
## 1623 1101799.61 57842.374 69467.158 TRUE 0.05249809
## 1624 6538035.85 1037026.522 586270.807 TRUE 0.15861438
## 1625 1339599.23 149384.067 78717.497 FALSE 0.11151400
## 1626 3895195.86 439447.019 42487.258 FALSE 0.11281770
## 1627 7591231.76 501460.795 252475.713 TRUE 0.06605790
## 1628 2958735.98 382739.359 136090.371 TRUE 0.12935908
## 1629 2785516.21 350390.055 272160.856 TRUE 0.12578999
## 1630 1318373.63 134476.294 87631.579 TRUE 0.10200166
## 1631 3953322.24 531026.687 130406.594 TRUE 0.13432416
## 1632 7352540.36 448180.285 369681.231 FALSE 0.06095584
## 1633 7661600.48 1198694.059 550282.786 TRUE 0.15645479
## 1634 714106.20 70903.023 67623.359 TRUE 0.09928918
## 1635 892051.83 98834.164 9819.688 TRUE 0.11079419
## 1636 623722.43 57973.072 9802.862 TRUE 0.09294691
## 1637 3028054.31 167557.515 206034.436 TRUE 0.05533504
## 1638 2776461.00 188203.680 198311.073 FALSE 0.06778546
## 1639 1789403.87 244183.071 136226.099 FALSE 0.13646057
## 1640 3571340.37 515613.871 157400.226 TRUE 0.14437545
## 1641 7641968.74 599645.735 462658.462 FALSE 0.07846744
## 1642 7669217.61 1390098.735 279143.137 TRUE 0.18125692
## 1643 6471646.17 1104062.876 466829.218 FALSE 0.17060001
## 1644 6988867.25 1154555.342 102431.788 TRUE 0.16519921
## 1645 1970246.39 383402.813 52769.295 TRUE 0.19459638
## 1646 5209497.34 692534.553 131463.949 TRUE 0.13293692
## 1647 2419341.23 368690.531 201016.158 TRUE 0.15239294
## 1648 2095295.00 215594.590 197454.421 FALSE 0.10289462
## 1649 4201289.74 542720.562 334943.390 FALSE 0.12917951
## 1650 2784528.93 374005.312 224386.797 TRUE 0.13431547
## 1651 6130480.96 1104663.099 211496.984 FALSE 0.18019191
## 1652 2991287.63 487219.230 40710.339 FALSE 0.16287943
## 1653 1470498.45 147837.410 83724.599 TRUE 0.10053558
## 1654 5352108.62 654608.588 157924.399 FALSE 0.12230854
## 1655 6084498.18 613380.568 359685.230 TRUE 0.10081038
## 1656 4808477.63 574928.584 441785.497 TRUE 0.11956561
## 1657 5353430.41 715454.309 527434.540 TRUE 0.13364408
## 1658 1976638.67 280571.291 121367.915 FALSE 0.14194364
## 1659 7790980.39 876319.236 450939.905 FALSE 0.11247869
## 1660 779805.13 61800.823 76724.477 FALSE 0.07925162
## 1661 1688548.70 107781.686 71237.419 FALSE 0.06383096
## 1662 4165247.40 457710.927 169085.825 TRUE 0.10988805
## 1663 8102373.70 990204.950 549528.823 FALSE 0.12221171
## 1664 1333159.98 208454.255 44390.344 TRUE 0.15636102
## 1665 753045.75 132974.660 13986.866 TRUE 0.17658245
## 1666 6460874.29 1212240.557 97893.048 FALSE 0.18762794
## 1667 8144055.78 470957.212 537980.058 TRUE 0.05782834
## 1668 813589.97 88758.005 12996.665 TRUE 0.10909427
## 1669 7198665.63 1079911.965 485558.108 FALSE 0.15001558
## 1670 7647719.87 890158.677 539685.957 TRUE 0.11639530
## 1671 6277621.82 815703.162 129188.655 FALSE 0.12993825
## 1672 3264093.62 640982.020 187908.645 FALSE 0.19637366
## 1673 3895194.25 551138.667 216820.345 TRUE 0.14149196
## 1674 1723089.79 229729.286 44994.731 TRUE 0.13332404
## 1675 1023753.26 70582.596 64813.684 TRUE 0.06894493
## 1676 2272823.06 438128.484 80806.696 TRUE 0.19276841
## 1677 4556034.54 779477.842 82444.631 TRUE 0.17108690
## 1678 6464230.52 528597.471 397437.138 TRUE 0.08177268
## 1679 3116658.99 336374.940 157874.118 TRUE 0.10792805
## 1680 1408495.98 274390.139 60919.326 FALSE 0.19481074
## 1681 914120.79 62559.022 43933.267 TRUE 0.06843627
## 1682 8056340.92 1432012.396 140470.148 TRUE 0.17774973
## 1683 5789561.37 511166.034 199660.133 TRUE 0.08829098
## 1684 6615272.45 642028.066 454158.803 FALSE 0.09705240
## 1685 4105187.88 418878.721 300120.643 TRUE 0.10203643
## 1686 1093701.75 66631.716 34180.082 FALSE 0.06092311
## 1687 3041725.41 494178.809 279153.703 TRUE 0.16246661
## 1688 3535982.43 451821.145 84430.035 FALSE 0.12777811
## 1689 4599813.23 646336.730 128783.535 TRUE 0.14051369
## 1690 4264292.42 733667.605 192007.371 FALSE 0.17204908
## 1691 3308835.80 248981.455 161169.338 TRUE 0.07524745
## 1692 6427824.05 533976.986 594607.141 TRUE 0.08307274
## 1693 455692.71 30329.333 39966.708 FALSE 0.06655655
## 1694 3636130.51 419478.861 50457.167 FALSE 0.11536408
## 1695 318055.33 43293.975 23982.368 FALSE 0.13612089
## 1696 5089508.41 315598.763 477585.513 TRUE 0.06200968
## 1697 5424261.84 1029079.812 78492.944 TRUE 0.18971795
## 1698 3846477.87 436468.699 171561.650 FALSE 0.11347230
## 1699 5120847.62 574132.888 141380.320 TRUE 0.11211677
## 1700 1286220.31 145523.034 106210.950 TRUE 0.11314005
## 1701 5413633.03 601727.349 232862.972 TRUE 0.11115038
## 1702 4562607.78 510650.502 114152.897 FALSE 0.11192075
## 1703 2017117.28 391512.577 70285.455 FALSE 0.19409510
## 1704 6574943.56 935655.119 571162.206 TRUE 0.14230618
## 1705 6655669.00 1230142.954 141682.620 FALSE 0.18482634
## 1706 7165032.72 614175.335 373348.734 FALSE 0.08571843
## 1707 2810999.42 325014.047 265272.028 TRUE 0.11562224
## 1708 3850433.64 635311.054 337764.549 FALSE 0.16499727
## 1709 3786741.06 366776.224 162436.771 TRUE 0.09685802
## 1710 6054441.39 853517.360 598483.636 TRUE 0.14097376
## 1711 3593781.20 488570.752 38176.946 FALSE 0.13594894
## 1712 7251862.41 798028.864 642140.367 TRUE 0.11004468
## 1713 4592929.20 363876.401 321302.618 TRUE 0.07922535
## 1714 2456476.95 403923.107 39263.141 FALSE 0.16443187
## 1715 5784445.45 1042857.600 94351.574 TRUE 0.18028653
## 1716 3941442.30 486875.294 72916.979 FALSE 0.12352719
## 1717 3023815.29 569744.999 99605.557 FALSE 0.18841925
## 1718 3988525.48 768549.720 260521.515 TRUE 0.19269019
## 1719 5802057.30 797480.438 157682.816 TRUE 0.13744787
## 1720 1593489.49 312103.587 47029.114 FALSE 0.19586172
## 1721 6244477.27 746804.936 406167.724 FALSE 0.11959447
## 1722 2434421.00 470863.037 66793.078 TRUE 0.19341890
## 1723 4172700.28 795209.436 224515.768 TRUE 0.19057430
## 1724 2795036.32 436385.372 159087.307 TRUE 0.15612869
## 1725 3682734.45 252671.601 166301.358 FALSE 0.06860978
## 1726 6812531.16 628895.145 339232.946 FALSE 0.09231446
## 1727 159057.87 24475.365 7532.419 FALSE 0.15387711
## 1728 6954567.48 804912.407 668138.401 FALSE 0.11573867
## 1729 157374.17 28283.393 2485.483 TRUE 0.17972068
## 1730 6384166.25 336050.365 396586.635 TRUE 0.05263810
## 1731 515124.91 52963.320 49308.412 FALSE 0.10281646
## 1732 5430943.96 607990.444 273363.757 FALSE 0.11194931
## 1733 5579020.90 684771.300 199206.125 FALSE 0.12274041
## 1734 161008.40 32159.584 5463.604 TRUE 0.19973855
## 1735 5693042.63 457316.253 394734.988 FALSE 0.08032897
## 1736 326164.63 63756.672 32610.883 FALSE 0.19547390
## 1737 4819333.52 499945.175 481548.901 TRUE 0.10373741
## 1738 6756820.02 718217.832 131990.258 TRUE 0.10629524
## 1739 7976309.59 1416268.724 363631.703 FALSE 0.17755940
## 1740 5042348.22 270755.144 232025.373 FALSE 0.05369624
## 1741 4124029.08 428695.157 85290.547 FALSE 0.10395057
## 1742 3078947.76 421055.211 250611.098 TRUE 0.13675296
## 1743 3897472.89 741073.581 216114.725 FALSE 0.19014207
## 1744 5922806.32 549324.385 423077.651 FALSE 0.09274732
## 1745 1472043.90 262024.434 26363.543 FALSE 0.17800042
## 1746 1981053.02 311576.321 117308.417 TRUE 0.15727813
## 1747 5528161.58 821852.003 93292.804 FALSE 0.14866642
## 1748 1810416.82 249761.564 79125.188 FALSE 0.13795804
## 1749 5199563.12 1035962.817 125074.610 TRUE 0.19924036
## 1750 2121994.33 164784.221 152405.755 FALSE 0.07765535
## 1751 692001.46 99497.800 50528.005 TRUE 0.14378264
## 1752 1557698.77 259212.757 124924.331 FALSE 0.16640750
## 1753 4468594.28 855589.037 388354.782 FALSE 0.19146716
## 1754 2684227.96 387152.222 233126.888 FALSE 0.14423224
## 1755 1251408.52 91031.693 61675.470 TRUE 0.07274339
## 1756 1742661.70 88336.155 157171.097 FALSE 0.05069036
## 1757 4301567.75 217847.755 330007.804 FALSE 0.05064380
## 1758 1392782.33 178216.385 73560.076 FALSE 0.12795710
## 1759 4445210.64 438665.086 197763.525 TRUE 0.09868263
## 1760 140432.75 13536.837 8498.348 TRUE 0.09639373
## 1761 3495338.11 573058.983 190481.298 FALSE 0.16394951
## 1762 5598825.65 728364.226 559391.943 FALSE 0.13009232
## 1763 5179954.47 565247.281 149473.742 TRUE 0.10912206
## 1764 3582790.11 498572.279 103138.123 TRUE 0.13915755
## 1765 383063.64 58215.499 36682.627 TRUE 0.15197344
## 1766 4209790.48 660969.416 309612.633 FALSE 0.15700768
## 1767 1977730.38 250849.943 58238.231 TRUE 0.12683728
## 1768 1592666.77 244389.094 127007.006 TRUE 0.15344647
## 1769 5658985.32 909475.584 255107.459 TRUE 0.16071354
## 1770 2235680.69 142804.336 211924.425 FALSE 0.06387510
## 1771 4391705.13 714139.853 275325.448 TRUE 0.16261107
## 1772 2216729.41 236419.389 116708.726 TRUE 0.10665234
## 1773 6289071.41 849595.622 596407.102 TRUE 0.13509079
## 1774 3616406.33 526658.251 40627.037 FALSE 0.14563028
## 1775 513042.33 87783.953 25640.139 FALSE 0.17110470
## 1776 4083932.91 368559.233 91733.888 FALSE 0.09024615
## 1777 2230354.73 162495.404 206241.607 FALSE 0.07285630
## 1778 7689811.58 896897.381 608638.146 TRUE 0.11663451
## 1779 6344306.65 611220.967 502219.982 TRUE 0.09634165
## 1780 5292557.32 423707.852 293993.217 FALSE 0.08005730
## 1781 3987900.67 686282.215 116423.645 TRUE 0.17209110
## 1782 4667445.39 438682.250 151091.187 TRUE 0.09398766
## 1783 90175.86 13528.018 7893.780 FALSE 0.15001817
## 1784 6984931.65 546389.359 602463.551 TRUE 0.07822401
## 1785 1521280.17 261631.692 87431.195 FALSE 0.17198127
## 1786 4822349.42 604351.775 76766.765 FALSE 0.12532310
## 1787 175615.82 16003.517 3111.921 TRUE 0.09112799
## 1788 2758779.14 159528.445 162776.031 TRUE 0.05782574
## 1789 6176841.34 735199.633 470328.546 FALSE 0.11902518
## 1790 4369312.39 454688.856 209457.416 TRUE 0.10406417
## 1791 4126982.76 599761.260 190738.461 TRUE 0.14532681
## 1792 6666691.50 1307106.358 100587.613 TRUE 0.19606522
## 1793 6914964.80 1251113.706 494157.804 TRUE 0.18092843
## 1794 6456359.35 1043041.442 341757.300 TRUE 0.16155257
## 1795 2832831.17 399098.969 220892.793 FALSE 0.14088343
## 1796 2938790.44 211156.925 117620.910 FALSE 0.07185164
## 1797 3480445.05 350989.440 110184.344 FALSE 0.10084614
## 1798 196751.53 25941.101 19121.043 FALSE 0.13184701
## 1799 6281541.09 1013653.735 445885.485 TRUE 0.16137023
## 1800 2972580.63 461441.591 110429.929 FALSE 0.15523266
## 1801 1041863.95 112248.629 88085.097 TRUE 0.10773828
## 1802 3817418.91 635863.398 354458.203 TRUE 0.16656893
## 1803 6386862.73 1046729.230 537018.845 FALSE 0.16388785
## 1804 817015.39 122820.754 49984.341 FALSE 0.15032857
## 1805 6869144.54 390574.589 125872.717 TRUE 0.05685928
## 1806 6921053.16 991728.511 665384.234 FALSE 0.14329156
## 1807 350982.88 46858.780 13513.867 TRUE 0.13350731
## 1808 3898386.15 607914.686 119690.642 FALSE 0.15594009
## 1809 1955387.41 234902.718 170185.672 FALSE 0.12013104
## 1810 5945363.77 622495.683 114963.380 TRUE 0.10470271
## 1811 603761.69 52927.965 48082.218 TRUE 0.08766367
## 1812 6814248.07 773175.973 203086.824 FALSE 0.11346461
## 1813 4969085.97 561507.901 307003.688 FALSE 0.11300024
## 1814 716649.24 92576.705 16317.225 FALSE 0.12917994
## 1815 1405248.67 206815.676 24964.547 FALSE 0.14717372
## 1816 5174793.53 1010535.531 109734.195 TRUE 0.19528036
## 1817 455027.64 74660.008 32813.589 TRUE 0.16407796
## 1818 1834671.66 140183.197 36675.288 FALSE 0.07640778
## 1819 81319.80 14355.985 3042.898 TRUE 0.17653739
## 1820 4108778.51 465106.057 173877.585 FALSE 0.11319813
## 1821 1670673.24 278993.673 34355.936 TRUE 0.16699476
## 1822 5460115.72 552776.790 249750.830 FALSE 0.10123902
## 1823 2716578.27 297564.719 208507.826 FALSE 0.10953659
## 1824 4878978.72 244975.183 249571.210 TRUE 0.05021034
## 1825 1857199.35 98377.843 98289.544 TRUE 0.05297107
## 1826 1646488.56 110302.946 88143.510 FALSE 0.06699284
## 1827 431744.56 79088.635 8482.454 TRUE 0.18318386
## 1828 2968366.54 304727.335 258676.244 TRUE 0.10265826
## 1829 6672739.79 1035325.549 98413.733 FALSE 0.15515749
## 1830 7785331.65 873120.133 318716.016 FALSE 0.11214938
## 1831 4245328.32 584585.321 363163.659 FALSE 0.13770085
## 1832 4597772.63 436478.896 64906.464 FALSE 0.09493268
## 1833 4580537.31 694917.960 238236.267 FALSE 0.15171101
## 1834 3223298.20 376538.833 120690.006 TRUE 0.11681787
## 1835 4599586.66 831656.606 188800.018 TRUE 0.18081116
## 1836 7261235.94 1312217.001 428431.578 TRUE 0.18071538
## 1837 5723910.21 1142306.127 378293.784 TRUE 0.19956744
## 1838 7336587.43 1113908.244 116385.131 FALSE 0.15182921
## 1839 6413940.77 623361.084 460549.465 TRUE 0.09718847
## 1840 5583663.46 949802.400 248539.592 TRUE 0.17010380
## 1841 185999.01 21651.540 9061.367 FALSE 0.11640675
## 1842 3038154.03 194144.503 40278.424 TRUE 0.06390213
## 1843 4383974.31 301331.754 251116.133 TRUE 0.06873484
## 1844 1550936.26 192365.456 145128.866 TRUE 0.12403183
## 1845 2648206.82 190044.915 124883.042 FALSE 0.07176362
## 1846 4109827.73 619004.228 250123.884 FALSE 0.15061561
## 1847 2359382.47 129784.942 190401.780 FALSE 0.05500801
## 1848 7317677.79 704509.343 687676.753 TRUE 0.09627499
## 1849 5961717.76 685505.552 425747.405 FALSE 0.11498457
## 1850 3661915.09 543914.517 47344.074 FALSE 0.14853280
## 1851 1583420.04 232290.897 108750.404 FALSE 0.14670201
## 1852 7185648.45 385364.859 292721.617 FALSE 0.05362980
## 1853 5441272.04 324103.411 376009.945 TRUE 0.05956390
## 1854 2260231.50 322435.234 81406.602 TRUE 0.14265584
## 1855 3822274.72 731741.425 107581.125 TRUE 0.19144135
## 1856 2181732.71 127379.382 192485.824 FALSE 0.05838450
## 1857 814272.73 124591.438 34372.268 FALSE 0.15300947
## 1858 1382656.74 227779.465 15807.765 FALSE 0.16474043
## 1859 5931571.23 705092.849 179824.353 FALSE 0.11887118
## 1860 6690744.66 558451.279 493278.516 TRUE 0.08346624
## 1861 4321656.69 518600.809 401881.002 TRUE 0.12000046
## 1862 5461187.39 662625.210 274350.218 FALSE 0.12133354
## 1863 6319301.47 665235.819 369166.004 TRUE 0.10527047
## 1864 6387276.01 877375.233 539080.611 TRUE 0.13736297
## 1865 4781750.24 458753.893 442419.134 TRUE 0.09593849
## 1866 1749328.52 331497.151 86362.725 TRUE 0.18949966
## 1867 4834195.61 806084.535 482526.894 TRUE 0.16674636
## 1868 5397417.95 528680.342 155066.408 FALSE 0.09795060
## 1869 410110.44 52643.410 4751.275 FALSE 0.12836398
## 1870 3606851.51 474270.828 245536.595 FALSE 0.13149164
## 1871 3981130.32 328553.246 393227.240 FALSE 0.08252763
## 1872 4657956.78 643032.831 211171.746 TRUE 0.13805041
## 1873 7540096.81 661148.338 280876.872 TRUE 0.08768433
## 1874 4217229.45 691788.316 339527.959 FALSE 0.16403858
## 1875 6020372.81 966498.393 329142.715 FALSE 0.16053796
## 1876 6053009.52 498533.536 356144.238 TRUE 0.08236127
## 1877 4489343.84 306340.617 195585.358 FALSE 0.06823728
## 1878 274130.47 41910.494 27219.479 TRUE 0.15288520
## 1879 7436237.19 982239.184 333672.760 FALSE 0.13208820
## 1880 1781744.28 192341.945 19243.211 TRUE 0.10795149
## 1881 2941784.27 394397.055 140354.424 TRUE 0.13406729
## 1882 5399608.26 540708.546 91141.998 TRUE 0.10013848
## 1883 3259006.40 512190.854 150828.993 FALSE 0.15716166
## 1884 3750400.29 439287.631 82964.513 TRUE 0.11713087
## 1885 862768.51 103911.219 32213.009 FALSE 0.12043928
## 1886 1015977.52 182632.457 17295.336 FALSE 0.17976033
## 1887 2782492.01 526742.396 204952.256 FALSE 0.18930599
## 1888 900234.96 116972.514 74364.115 FALSE 0.12993554
## 1889 3263449.55 494503.529 81890.896 FALSE 0.15152786
## 1890 7473670.82 840097.011 206246.188 FALSE 0.11240755
## 1891 732315.83 74833.739 16702.854 FALSE 0.10218779
## 1892 3416778.99 427948.130 288572.637 TRUE 0.12524899
## 1893 1977794.85 359940.078 139587.740 FALSE 0.18199060
## 1894 7254500.82 383152.230 508347.200 TRUE 0.05281580
## 1895 5072593.35 317142.160 270898.470 TRUE 0.06252071
## 1896 1664248.77 290916.704 23655.593 FALSE 0.17480362
## 1897 5090534.04 526282.015 473724.061 TRUE 0.10338444
## 1898 5447862.40 699460.192 246342.223 TRUE 0.12839168
## 1899 1454783.35 146526.882 23554.027 TRUE 0.10072076
## 1900 1700618.60 246767.675 18953.205 FALSE 0.14510466
## 1901 3791039.06 431346.462 278539.158 FALSE 0.11378054
## 1902 2274600.21 124873.087 213800.275 TRUE 0.05489892
## 1903 2467291.59 267010.505 114055.870 TRUE 0.10822008
## 1904 5499724.93 587037.801 117750.444 FALSE 0.10673948
## 1905 3240095.84 365658.153 323368.444 FALSE 0.11285412
## 1906 5487251.05 631147.449 130119.248 FALSE 0.11502070
## 1907 2981478.64 328342.259 174420.448 TRUE 0.11012732
## 1908 2051750.47 407271.349 51315.124 TRUE 0.19849945
## 1909 3706402.66 204031.470 43506.767 TRUE 0.05504838
## 1910 4918096.81 305833.466 189539.923 FALSE 0.06218533
## 1911 4492340.57 598784.420 61577.157 FALSE 0.13329008
## 1912 3504453.70 538684.051 115050.489 FALSE 0.15371413
## 1913 7431460.31 1081729.221 180894.379 FALSE 0.14556079
## 1914 7670871.62 1214897.418 352931.616 FALSE 0.15837801
## 1915 2368540.57 332664.599 90241.433 FALSE 0.14045130
## 1916 6293781.98 512116.345 386458.285 TRUE 0.08136862
## 1917 4661275.96 699405.645 207323.834 TRUE 0.15004596
## 1918 6377618.17 943282.901 316372.880 FALSE 0.14790520
## 1919 4407213.67 833889.019 150900.622 TRUE 0.18921003
## 1920 2750551.00 399530.662 127325.659 TRUE 0.14525477
## 1921 6838661.03 668753.826 243440.200 TRUE 0.09779017
## 1922 1901024.10 156743.039 87365.751 TRUE 0.08245189
## 1923 3358520.80 307121.110 130532.291 FALSE 0.09144535
## 1924 4718243.72 477984.133 455336.920 FALSE 0.10130552
## 1925 5383327.96 711721.822 228851.211 TRUE 0.13220852
## 1926 6978187.46 419798.538 275238.115 FALSE 0.06015868
## 1927 5100021.25 584728.290 277428.542 FALSE 0.11465213
## 1928 2055766.75 179499.951 124950.636 TRUE 0.08731533
## 1929 5325565.66 627448.326 516101.297 FALSE 0.11781816
## 1930 5804609.08 932623.861 432873.811 TRUE 0.16066954
## 1931 1850009.64 320018.976 44972.826 TRUE 0.17298233
## 1932 5971464.75 447988.153 204113.148 TRUE 0.07502149
## 1933 7736035.39 1002036.106 475053.843 FALSE 0.12952838
## 1934 5702814.91 602428.107 123034.274 TRUE 0.10563697
## 1935 444000.77 29794.865 43498.420 TRUE 0.06710544
## 1936 2503301.81 156143.255 153589.582 FALSE 0.06237492
## 1937 6082027.33 700930.424 365593.110 FALSE 0.11524618
## 1938 3383984.52 506210.538 99628.683 TRUE 0.14959009
## 1939 6571339.97 456415.626 444841.628 FALSE 0.06945549
## 1940 6650050.75 361882.105 649903.560 FALSE 0.05441795
## 1941 258434.44 39356.907 12165.855 FALSE 0.15228972
## 1942 4862162.86 299635.683 454425.116 TRUE 0.06162601
## 1943 4280426.00 435306.193 279821.827 FALSE 0.10169693
## 1944 8095159.59 971452.792 559555.906 FALSE 0.12000416
## 1945 4061003.36 773747.771 150590.173 FALSE 0.19053118
## 1946 5263698.91 774276.935 201908.704 TRUE 0.14709750
## 1947 4648998.83 591544.738 146812.429 TRUE 0.12724132
## 1948 4085139.44 540550.278 317245.781 FALSE 0.13232113
## 1949 7966935.22 818075.066 600238.097 FALSE 0.10268379
## 1950 3889741.42 575911.667 321670.109 TRUE 0.14805911
## 1951 1742812.93 99294.028 132092.423 TRUE 0.05697343
## 1952 6781085.83 1155545.525 228763.394 FALSE 0.17040715
## 1953 326845.17 41176.456 29823.648 FALSE 0.12598153
## 1954 5791652.39 1135059.905 314447.290 TRUE 0.19598205
## 1955 8033242.46 1307505.238 722117.613 FALSE 0.16276183
## 1956 5467109.94 811182.570 448975.079 FALSE 0.14837502
## 1957 4370966.10 288148.250 87385.360 FALSE 0.06592324
## 1958 6231043.90 887034.674 505015.201 TRUE 0.14235731
## 1959 2127672.79 302904.574 208323.053 FALSE 0.14236427
## 1960 4331027.37 774100.481 165511.508 FALSE 0.17873368
## 1961 5501175.60 518512.454 248224.505 TRUE 0.09425485
## 1962 8000998.67 883486.735 517486.633 FALSE 0.11042206
## 1963 3574549.54 426887.653 286344.281 TRUE 0.11942418
## 1964 2959194.79 471376.947 95720.373 TRUE 0.15929230
## 1965 6339408.82 938379.441 141569.123 TRUE 0.14802318
## 1966 2171729.29 338547.408 27150.444 FALSE 0.15588840
## 1967 2119825.49 373623.748 67986.386 FALSE 0.17625213
## 1968 7083959.93 659093.333 345191.729 TRUE 0.09304024
## 1969 4753636.03 586866.671 442953.070 TRUE 0.12345637
## 1970 1676660.92 162019.157 108857.563 TRUE 0.09663204
## 1971 254410.50 48007.069 19405.118 TRUE 0.18869925
## 1972 7876495.07 1320899.716 536925.967 FALSE 0.16770146
## 1973 1449695.89 216139.956 71466.778 FALSE 0.14909331
## 1974 5782175.72 678305.495 410476.129 TRUE 0.11730973
## 1975 2436423.60 221614.732 106495.614 TRUE 0.09095903
## 1976 3418502.88 301335.235 324025.983 TRUE 0.08814831
## 1977 6399059.67 739291.904 570827.881 TRUE 0.11553133
## 1978 5109638.11 982888.688 497798.952 FALSE 0.19235975
## 1979 2323132.84 306236.191 42918.588 FALSE 0.13182035
## 1980 8211033.25 1318388.410 480604.269 FALSE 0.16056303
## 1981 979734.73 138674.194 30428.181 FALSE 0.14154259
## 1982 5399893.22 836910.772 501779.273 FALSE 0.15498654
## 1983 1588304.28 238435.600 97140.663 TRUE 0.15011960
## 1984 2857090.23 445555.453 217659.554 TRUE 0.15594728
## 1985 3819557.97 293189.801 135851.943 TRUE 0.07676014
## 1986 3158000.40 308344.287 192606.819 FALSE 0.09763909
## 1987 5277851.52 780383.724 284633.157 FALSE 0.14786011
## 1988 1994279.72 143884.270 183683.498 FALSE 0.07214849
## 1989 4297882.31 387062.380 80937.452 TRUE 0.09005886
## 1990 4485190.88 493081.503 286734.525 FALSE 0.10993546
## 1991 4971091.38 681687.665 78507.375 FALSE 0.13713038
## 1992 7415078.90 1284100.217 350620.610 TRUE 0.17317418
## 1993 4748133.85 616740.015 452457.662 TRUE 0.12989103
## 1994 4638465.65 358712.471 149519.874 TRUE 0.07733429
## 1995 2868844.13 170840.731 191895.502 FALSE 0.05955037
## 1996 749123.33 125905.592 43803.480 TRUE 0.16807058
## 1997 2077536.01 400560.865 48633.165 FALSE 0.19280574
## 1998 7419979.43 1076260.268 511557.923 TRUE 0.14504896
## 1999 459458.15 46214.021 6849.318 FALSE 0.10058375
## 2000 6821224.54 529340.577 620681.365 FALSE 0.07760199
## 2001 5703336.09 295061.166 170668.105 FALSE 0.05173484
## 2002 5330837.01 351105.088 426481.108 TRUE 0.06586303
## 2003 6131783.33 1049436.875 243446.831 FALSE 0.17114709
## 2004 6196492.52 927774.134 461792.443 TRUE 0.14972569
## 2005 6928525.13 919151.869 380209.527 TRUE 0.13266198
## 2006 5090713.84 724430.959 193600.084 FALSE 0.14230440
## 2007 797196.61 133354.682 27433.125 TRUE 0.16727954
## 2008 4352329.54 284289.331 184705.892 FALSE 0.06531889
## 2009 3049671.95 357202.442 115509.541 TRUE 0.11712815
## 2010 5301314.08 666729.031 195359.609 FALSE 0.12576675
## 2011 5157253.34 668127.041 453685.732 FALSE 0.12955094
## 2012 176342.30 18296.096 3759.794 FALSE 0.10375330
## 2013 5751403.90 596168.077 558314.648 FALSE 0.10365610
## 2014 6503465.41 344096.199 475903.070 FALSE 0.05290967
## 2015 2720645.96 408604.953 107324.657 TRUE 0.15018674
## 2016 5515047.37 652439.306 267061.704 FALSE 0.11830167
## 2017 7976411.34 917007.002 234977.389 TRUE 0.11496486
## 2018 3437619.57 538942.551 338515.100 TRUE 0.15677783
## 2019 2400830.99 406481.444 153679.516 TRUE 0.16930865
## 2020 1872816.01 98088.732 46814.974 FALSE 0.05237500
## 2021 4531191.78 562754.380 349103.500 TRUE 0.12419567
## 2022 1234835.82 152162.520 95683.508 TRUE 0.12322490
## 2023 6895990.04 375161.632 623506.599 FALSE 0.05440287
## 2024 3881142.32 639384.467 375773.361 FALSE 0.16474131
## 2025 2222287.16 252450.102 92436.863 FALSE 0.11359923
## 2026 3201837.18 514675.448 53960.351 TRUE 0.16074379
## 2027 5220961.59 364896.581 180085.118 FALSE 0.06989068
## 2028 4968507.59 495795.979 382455.703 FALSE 0.09978771
## 2029 5615855.41 709532.035 122277.893 FALSE 0.12634443
## 2030 5703323.42 317217.899 424609.784 TRUE 0.05561983
## 2031 5303579.35 700205.659 234337.815 TRUE 0.13202511
## 2032 6048155.75 814353.229 451654.677 FALSE 0.13464488
## 2033 5174770.11 883453.362 325189.879 TRUE 0.17072321
## 2034 3653074.87 230204.957 36684.537 FALSE 0.06301676
## 2035 2200631.21 149898.623 188369.952 FALSE 0.06811619
## 2036 6051124.67 305214.264 449699.293 FALSE 0.05043926
## 2037 7303791.79 379509.744 159767.467 FALSE 0.05196065
## 2038 3214677.11 510189.578 115266.292 FALSE 0.15870632
## 2039 6920877.30 766040.725 648500.248 TRUE 0.11068549
## 2040 4429397.09 601441.703 259840.765 FALSE 0.13578410
## 2041 3984527.25 254697.471 289882.395 FALSE 0.06392163
## 2042 488860.96 49366.287 27903.926 FALSE 0.10098226
## 2043 2511654.06 491945.140 67849.516 FALSE 0.19586501
## 2044 4753049.09 244840.908 251580.235 FALSE 0.05151239
## 2045 6597998.29 441414.959 512452.550 TRUE 0.06690134
## 2046 1210709.93 136870.148 34719.145 TRUE 0.11304950
## 2047 6157388.77 752215.772 514843.859 FALSE 0.12216474
## 2048 6738016.65 1341577.554 615568.541 TRUE 0.19910570
## 2049 7101193.03 814093.248 197421.972 FALSE 0.11464176
## 2050 5414050.81 627868.797 206844.633 FALSE 0.11597024
## 2051 3005549.94 599738.144 224981.558 FALSE 0.19954356
## 2052 1805094.23 95098.904 82393.111 FALSE 0.05268362
## 2053 4656261.63 328098.498 264269.585 FALSE 0.07046393
## 2054 173108.50 34481.918 15862.253 FALSE 0.19919252
## 2055 5232310.01 373664.726 282196.754 FALSE 0.07141487
## 2056 2734681.94 159054.656 67950.411 FALSE 0.05816203
## 2057 3796567.42 731109.028 282442.138 FALSE 0.19257106
## 2058 2612486.04 469380.879 157847.732 FALSE 0.17966828
## 2059 6421523.39 1209591.770 308706.505 TRUE 0.18836524
## 2060 908199.70 177579.762 16334.212 TRUE 0.19552942
## 2061 4734991.77 417402.347 170275.744 TRUE 0.08815271
## 2062 2728851.68 406982.362 209438.984 TRUE 0.14914052
## 2063 6578698.92 517527.293 648778.113 FALSE 0.07866712
## 2064 6178351.48 813819.029 364610.273 TRUE 0.13172106
## 2065 4236937.49 776780.527 266335.567 FALSE 0.18333538
## 2066 5790878.68 1042505.564 248961.384 FALSE 0.18002545
## 2067 360612.92 59085.451 8626.204 FALSE 0.16384730
## 2068 6088930.46 618916.344 479903.980 TRUE 0.10164615
## 2069 6394291.06 810948.752 447632.168 TRUE 0.12682387
## 2070 7232119.99 666844.338 222009.198 TRUE 0.09220593
## 2071 4474017.63 396834.967 197135.604 TRUE 0.08869768
## 2072 827327.75 90860.197 10806.933 FALSE 0.10982370
## 2073 2363941.60 144775.162 115548.567 FALSE 0.06124312
## 2074 5502150.26 801441.946 233300.517 FALSE 0.14565977
## 2075 2440942.13 157418.339 161083.859 TRUE 0.06449081
## 2076 5094737.73 723798.373 196861.963 FALSE 0.14206784
## 2077 5348211.63 971897.160 149647.777 FALSE 0.18172377
## 2078 1692232.26 225665.875 95865.695 TRUE 0.13335396
## 2079 2580844.67 365107.436 87149.795 FALSE 0.14146819
## 2080 2808223.75 317120.621 274700.367 FALSE 0.11292570
## 2081 2893781.38 199949.073 234863.159 TRUE 0.06909612
## 2082 6421441.89 928235.401 531534.297 FALSE 0.14455249
## 2083 6674431.27 651773.142 524633.724 FALSE 0.09765224
## 2084 6788624.50 1244944.605 367741.531 FALSE 0.18338687
## 2085 6479420.64 1240976.358 569641.029 FALSE 0.19152582
## 2086 2051995.67 320071.517 57346.389 FALSE 0.15598060
## 2087 6512911.55 622313.985 166418.240 TRUE 0.09555081
## 2088 1173012.37 98905.554 52264.581 TRUE 0.08431757
## 2089 2476762.87 413077.869 87133.177 FALSE 0.16678136
## 2090 1838662.53 232503.260 166172.586 FALSE 0.12645238
## 2091 1421557.01 205161.872 128573.089 FALSE 0.14432194
## 2092 2296810.45 354712.011 107049.228 TRUE 0.15443678
## 2093 2404641.01 162114.437 235928.986 TRUE 0.06741731
## 2094 7458862.96 378158.113 124007.780 TRUE 0.05069916
## 2095 3344042.78 400654.108 164549.683 FALSE 0.11981130
## 2096 5364006.49 681193.364 158212.785 FALSE 0.12699339
## 2097 1761630.27 233961.430 88326.743 FALSE 0.13280961
## 2098 4559335.84 470507.270 106921.809 TRUE 0.10319645
## 2099 5412392.21 394091.755 417927.990 FALSE 0.07281286
## 2100 6002227.56 734018.904 376594.878 TRUE 0.12229108
## 2101 5282878.31 808369.312 151954.788 FALSE 0.15301683
## 2102 1068900.07 148051.727 102303.527 FALSE 0.13850848
## 2103 6641712.23 499000.919 205905.132 TRUE 0.07513137
## 2104 6705999.05 1091444.634 592938.755 FALSE 0.16275646
## 2105 672770.47 117719.450 16462.543 FALSE 0.17497714
## 2106 4101743.65 381390.865 349643.381 TRUE 0.09298262
## 2107 3706014.00 265714.028 130118.189 TRUE 0.07169806
## 2108 2574872.22 299440.312 108030.026 FALSE 0.11629327
## 2109 6372499.99 920857.187 543619.553 TRUE 0.14450485
## 2110 2994068.68 181958.191 156738.760 FALSE 0.06077288
## 2111 2274857.36 341987.037 28618.915 TRUE 0.15033340
## 2112 4962219.89 618536.641 109629.158 FALSE 0.12464918
## 2113 7817338.74 1385766.126 660945.727 FALSE 0.17726827
## 2114 5585381.66 642824.377 142057.859 TRUE 0.11509050
## 2115 451477.43 55014.084 41154.813 TRUE 0.12185345
## 2116 641601.70 90012.855 33989.197 FALSE 0.14029398
## 2117 6588321.15 623894.820 569071.133 TRUE 0.09469709
## 2118 5282450.97 747876.931 176308.361 TRUE 0.14157764
## 2119 2603991.30 342528.443 223235.052 FALSE 0.13153978
## 2120 5449302.25 1009063.230 532038.142 TRUE 0.18517292
## 2121 2861591.21 460370.204 176792.930 FALSE 0.16087909
## 2122 1961671.63 118325.030 45338.305 TRUE 0.06031847
## 2123 2843221.00 273483.505 179627.895 FALSE 0.09618792
## 2124 6569219.08 830309.029 187072.119 FALSE 0.12639387
## 2125 410915.72 42271.448 26386.387 TRUE 0.10287133
## 2126 2715668.83 414368.964 28637.943 TRUE 0.15258450
## 2127 1176502.71 205570.405 52883.271 FALSE 0.17473007
## 2128 5406841.54 946162.146 236662.777 FALSE 0.17499350
## 2129 3234435.80 283481.691 58915.092 FALSE 0.08764487
## 2130 2512635.38 322070.889 48114.272 TRUE 0.12818051
## 2131 2575561.11 495228.624 240265.503 FALSE 0.19227990
## 2132 2811400.32 509549.078 85980.826 FALSE 0.18124387
## 2133 5369303.90 406085.034 435378.753 FALSE 0.07563085
## 2134 2867481.44 486605.913 226893.208 FALSE 0.16969802
## 2135 6003557.49 636323.868 121339.765 TRUE 0.10599113
## 2136 7701793.69 1429919.944 466381.231 FALSE 0.18566064
## 2137 5475127.20 763289.815 389871.919 FALSE 0.13941043
## 2138 4726508.91 556947.213 247474.020 FALSE 0.11783480
## 2139 1954810.72 342105.812 19971.117 FALSE 0.17500713
## 2140 1209653.30 76642.123 79386.500 TRUE 0.06335875
## 2141 5471157.04 299176.464 220125.150 FALSE 0.05468249
## 2142 3264384.21 523447.638 263157.235 TRUE 0.16035111
## 2143 2260747.69 244034.525 99014.783 FALSE 0.10794417
## 2144 5097949.48 650049.717 66937.037 FALSE 0.12751200
## 2145 462625.50 37995.799 32348.741 TRUE 0.08213079
## 2146 6161218.24 1153227.780 338275.453 FALSE 0.18717529
## 2147 4340223.12 632650.629 247189.831 TRUE 0.14576454
## 2148 1941505.70 317651.401 25422.938 TRUE 0.16361085
## 2149 5015936.86 472583.350 221822.881 FALSE 0.09421637
## 2150 6358127.39 984188.267 455204.986 TRUE 0.15479216
## 2151 1252210.90 202156.541 44451.736 FALSE 0.16143969
## 2152 3458610.97 547834.083 268600.651 TRUE 0.15839714
## 2153 7606860.81 989163.323 272442.754 FALSE 0.13003568
## 2154 7254100.13 632882.021 329450.099 TRUE 0.08724473
## 2155 3818452.27 649048.632 82759.172 FALSE 0.16997689
## 2156 7390174.59 1471668.035 713543.262 FALSE 0.19913847
## 2157 3696837.19 436845.662 255026.580 TRUE 0.11816741
## 2158 3705330.09 621301.588 206815.256 FALSE 0.16767780
## 2159 3197165.62 234569.519 144382.875 TRUE 0.07336796
## 2160 1917265.69 298294.868 64327.787 FALSE 0.15558348
## 2161 5858638.46 388209.482 83371.411 FALSE 0.06626275
## 2162 1107246.58 189879.490 35674.040 FALSE 0.17148799
## 2163 2126964.18 334814.629 69207.584 FALSE 0.15741432
## 2164 3614188.02 498169.975 284564.582 FALSE 0.13783732
## 2165 1716875.24 325501.206 108509.323 TRUE 0.18958932
## 2166 3716633.44 235110.842 174188.917 TRUE 0.06325909
## 2167 2517744.07 162183.969 227008.645 TRUE 0.06441638
## 2168 2724735.39 411124.479 58675.139 TRUE 0.15088602
## 2169 6741612.70 957824.743 390272.689 FALSE 0.14207650
## 2170 6776787.67 628482.811 654718.725 TRUE 0.09274052
## 2171 6203906.45 1003319.861 580144.795 TRUE 0.16172389
## 2172 3724006.35 403441.075 238415.301 FALSE 0.10833523
## 2173 2643841.45 279393.292 107428.659 FALSE 0.10567702
## 2174 7024899.44 1122819.413 364182.252 TRUE 0.15983423
## 2175 6505554.93 952248.993 193803.260 FALSE 0.14637475
## 2176 3008724.26 324087.006 264379.935 TRUE 0.10771576
## 2177 7066339.83 408292.601 606849.694 TRUE 0.05777993
## 2178 5724221.67 426556.236 481050.842 TRUE 0.07451777
## 2179 4592453.94 695545.392 143754.607 TRUE 0.15145397
## 2180 3517990.57 395594.554 165245.335 TRUE 0.11244901
## 2181 930219.54 138665.073 46301.842 TRUE 0.14906704
## 2182 1940912.13 310855.954 84972.695 TRUE 0.16015973
## 2183 4725086.28 494973.641 99060.118 FALSE 0.10475441
## 2184 7665693.86 584206.254 104723.829 TRUE 0.07621049
## 2185 7366949.13 953020.827 654569.376 TRUE 0.12936438
## 2186 6317026.48 682014.131 510265.363 FALSE 0.10796442
## 2187 7554278.34 1375031.005 210117.834 FALSE 0.18202017
## 2188 6625953.47 783647.676 320515.482 TRUE 0.11826942
## 2189 3215548.77 412822.160 122120.138 TRUE 0.12838311
## 2190 7359966.89 397354.585 269537.586 FALSE 0.05398864
## 2191 635392.16 35100.509 41238.385 FALSE 0.05524228
## 2192 7702864.72 1167587.163 709986.429 TRUE 0.15157830
## 2193 4654750.22 534943.753 134176.856 FALSE 0.11492427
## 2194 3408192.79 370075.155 167413.257 TRUE 0.10858399
## 2195 5841218.22 847901.837 184605.733 TRUE 0.14515839
## 2196 5522787.37 716464.718 93657.465 TRUE 0.12972883
## 2197 6043871.28 803370.787 281100.073 FALSE 0.13292321
## 2198 1097082.68 202585.284 97125.487 FALSE 0.18465817
## 2199 6963104.79 627901.241 514661.355 TRUE 0.09017547
## 2200 2847374.73 454678.143 202257.484 TRUE 0.15968328
## 2201 8268606.25 667116.143 668617.397 TRUE 0.08068060
## 2202 6869936.97 1203358.520 295371.481 TRUE 0.17516296
## 2203 4254572.40 584275.823 356508.135 FALSE 0.13732892
## 2204 1061303.15 92088.011 30113.221 FALSE 0.08676881
## 2205 3583004.30 369705.258 90254.250 FALSE 0.10318303
## 2206 2158581.56 367243.491 147500.750 TRUE 0.17013186
## 2207 2216413.72 329572.179 47729.904 TRUE 0.14869615
## 2208 3078153.44 411933.616 109312.634 TRUE 0.13382491
## 2209 3983229.12 496220.150 213495.899 FALSE 0.12457736
## 2210 182726.44 29647.686 3425.027 FALSE 0.16225175
## 2211 4888014.39 624944.810 429953.204 TRUE 0.12785249
## 2212 5981776.54 924911.845 341659.347 TRUE 0.15462160
## 2213 3107842.58 213270.061 276109.608 FALSE 0.06862319
## 2214 5942016.07 774618.720 367297.987 TRUE 0.13036295
## 2215 2140665.88 356365.672 96262.579 TRUE 0.16647422
## 2216 200930.74 31091.145 11688.317 TRUE 0.15473563
## 2217 7918942.40 1380155.705 737610.415 FALSE 0.17428536
## 2218 3301594.36 379537.210 99306.449 FALSE 0.11495574
## 2219 5158411.79 855671.014 277214.340 FALSE 0.16587877
## 2220 497448.15 43726.517 48532.884 TRUE 0.08790166
## 2221 236731.54 35700.564 15915.101 TRUE 0.15080611
## 2222 1563112.88 277683.187 125900.037 TRUE 0.17764756
## 2223 7269625.16 608421.439 136811.236 FALSE 0.08369365
## 2224 5312197.98 319170.501 382575.156 TRUE 0.06008257
## 2225 3463981.57 588795.296 82046.934 TRUE 0.16997645
## 2226 214015.97 22416.295 4662.187 FALSE 0.10474122
## 2227 4709799.16 570326.586 353820.244 FALSE 0.12109361
## 2228 2961463.24 571821.378 129950.488 TRUE 0.19308745
## 2229 2969899.55 326833.336 115259.753 TRUE 0.11004862
## 2230 7704320.91 1195080.030 123701.608 TRUE 0.15511815
## 2231 1739293.40 277400.502 173236.455 TRUE 0.15949034
## 2232 3834166.24 594250.193 146923.631 TRUE 0.15498811
## 2233 6122103.09 1210834.200 272721.272 TRUE 0.19778076
## 2234 1111180.36 139094.819 62625.985 FALSE 0.12517754
## 2235 5454941.18 379024.214 391143.181 TRUE 0.06948273
## 2236 4051947.18 706503.331 220288.334 TRUE 0.17436144
## 2237 5222665.45 450330.913 187234.540 FALSE 0.08622626
## 2238 7680528.18 1314500.481 156503.689 TRUE 0.17114715
## 2239 5432420.13 582585.529 495587.401 FALSE 0.10724235
## 2240 7123979.80 985143.404 100597.112 TRUE 0.13828554
## 2241 2606281.15 179261.041 155180.563 TRUE 0.06878039
## 2242 7396887.75 397032.077 89803.323 TRUE 0.05367556
## 2243 2046132.80 273468.806 143696.283 FALSE 0.13365154
## 2244 3849516.23 273021.071 149201.856 FALSE 0.07092348
## 2245 4763244.16 654320.256 428959.474 FALSE 0.13736862
## 2246 3197925.42 173249.095 34038.060 FALSE 0.05417546
## 2247 6716738.78 889087.976 247602.964 FALSE 0.13236900
## 2248 7432947.92 1181633.874 642167.481 FALSE 0.15897244
## 2249 874564.04 118334.993 81794.448 FALSE 0.13530741
## 2250 6789193.05 1296193.847 641295.315 FALSE 0.19092016
## 2251 159816.21 9882.339 3390.222 TRUE 0.06183565
## 2252 7882697.57 643918.007 557535.406 FALSE 0.08168752
## 2253 3599985.42 706699.228 316855.221 FALSE 0.19630614
## 2254 1852835.09 333948.429 116944.661 FALSE 0.18023646
## 2255 4496600.19 370905.467 319046.521 TRUE 0.08248576
## 2256 4786953.23 399556.942 104882.222 TRUE 0.08346790
## 2257 4387912.20 372075.792 169278.724 TRUE 0.08479563
## 2258 849025.15 51808.354 66068.527 FALSE 0.06102099
## 2259 2638051.18 321625.147 222742.125 FALSE 0.12191771
## 2260 6721414.34 527137.470 549813.932 TRUE 0.07842657
## 2261 3480633.33 480412.085 249940.177 TRUE 0.13802433
## 2262 5455279.43 843050.794 509141.277 TRUE 0.15453852
## 2263 4202282.63 301794.316 100143.298 FALSE 0.07181676
## 2264 2536083.48 264390.509 167243.139 TRUE 0.10425150
## 2265 917662.68 84036.640 27117.392 TRUE 0.09157683
## 2266 4031384.58 445971.386 113700.960 FALSE 0.11062487
## 2267 1557702.27 159189.553 120317.973 FALSE 0.10219511
## 2268 6136374.90 443783.804 287691.373 FALSE 0.07232019
## 2269 6372264.26 1142498.759 326737.048 TRUE 0.17929243
## 2270 5645491.03 809325.974 231137.984 FALSE 0.14335794
## 2271 3861274.35 471487.157 93592.204 FALSE 0.12210662
## 2272 6720885.23 1146143.911 429371.340 FALSE 0.17053467
## 2273 4847861.66 590616.815 210818.778 TRUE 0.12183038
## 2274 581257.74 83352.009 36622.733 FALSE 0.14339940
## 2275 5307410.40 875046.105 278342.901 FALSE 0.16487252
## 2276 4951978.03 438025.297 242612.028 TRUE 0.08845461
## 2277 6431538.35 515132.352 440491.020 TRUE 0.08009473
## 2278 4069644.96 375197.747 326572.092 FALSE 0.09219422
## 2279 1776466.24 315436.264 171171.953 FALSE 0.17756389
## 2280 3416728.41 365738.988 227646.353 FALSE 0.10704362
## 2281 1867283.56 359193.938 174021.088 TRUE 0.19236175
## 2282 3797521.72 375388.486 52647.291 TRUE 0.09885091
## 2283 5234778.96 597546.699 120971.931 TRUE 0.11414937
## 2284 3559088.36 528620.912 320322.855 TRUE 0.14852705
## 2285 6149973.32 991905.795 209491.916 FALSE 0.16128619
## 2286 5412612.79 940178.911 223443.665 TRUE 0.17370149
## 2287 938469.52 53879.756 77778.985 TRUE 0.05741237
## 2288 2992112.92 509650.610 187806.308 FALSE 0.17033134
## 2289 2346926.38 160163.004 224435.161 TRUE 0.06824373
## 2290 6533189.37 583910.559 419444.522 FALSE 0.08937603
## 2291 4583992.28 253968.035 319848.268 FALSE 0.05540324
## 2292 4937594.04 973366.780 457750.159 TRUE 0.19713382
## 2293 7429571.91 1419409.002 296843.206 FALSE 0.19104856
## 2294 4035780.69 563286.103 227419.944 TRUE 0.13957302
## 2295 426449.45 69873.652 41254.676 FALSE 0.16384979
## 2296 114141.76 17455.030 2969.683 TRUE 0.15292413
## 2297 1593131.02 97846.031 72149.461 FALSE 0.06141744
## 2298 5513204.55 619509.455 246788.111 FALSE 0.11236831
## 2299 3508322.06 658951.985 248885.038 FALSE 0.18782540
## 2300 1864955.23 237370.485 133790.762 FALSE 0.12727945
## 2301 2101192.65 301143.745 116108.853 TRUE 0.14332039
## 2302 6531757.95 908035.595 577663.271 FALSE 0.13901856
## 2303 3815088.17 475097.320 61964.513 TRUE 0.12453115
## 2304 404332.71 49953.180 34309.081 FALSE 0.12354474
## 2305 5358195.19 655001.269 432698.510 FALSE 0.12224289
## 2306 5776131.67 629106.134 558930.002 TRUE 0.10891478
## 2307 618986.48 118508.837 32435.555 FALSE 0.19145626
## 2308 1825594.89 312591.186 49247.569 TRUE 0.17122703
## 2309 3727384.17 560174.696 40001.873 TRUE 0.15028628
## 2310 2967727.67 239942.156 289472.400 FALSE 0.08085046
## 2311 1395097.92 182128.507 111632.743 TRUE 0.13054891
## 2312 5079061.02 460611.006 318335.079 FALSE 0.09068822
## 2313 3048483.40 575124.122 206026.964 TRUE 0.18865910
## 2314 7939263.98 1299861.290 113303.351 FALSE 0.16372567
## 2315 5530586.57 597398.550 499366.820 TRUE 0.10801721
## 2316 3081603.32 201143.719 108313.146 TRUE 0.06527242
## 2317 7754969.12 1267918.237 519006.510 TRUE 0.16349752
## 2318 4015099.87 369896.754 257510.921 FALSE 0.09212641
## 2319 1701576.80 112479.332 22315.298 FALSE 0.06610300
## 2320 4772983.68 258373.393 373306.835 FALSE 0.05413247
## 2321 609043.91 94639.131 31589.868 FALSE 0.15538967
## 2322 3787491.64 500073.236 45939.416 TRUE 0.13203283
## 2323 3942176.78 608869.477 333102.382 TRUE 0.15445007
## 2324 6452109.96 489115.135 467643.142 TRUE 0.07580701
## 2325 1150416.18 116077.971 60363.629 TRUE 0.10090085
## 2326 1280342.26 117659.340 40884.942 TRUE 0.09189679
## 2327 5900015.10 988649.687 427121.935 FALSE 0.16756731
## 2328 1911278.51 135983.682 28717.291 FALSE 0.07114802
## 2329 4511870.87 737516.473 336113.662 FALSE 0.16346134
## 2330 1603331.89 245313.686 141649.053 FALSE 0.15300244
## 2331 3714642.73 320291.085 103179.343 TRUE 0.08622393
## 2332 4536028.91 658669.193 343646.742 TRUE 0.14520833
## 2333 6096674.77 865359.080 565624.937 TRUE 0.14193952
## 2334 2391366.71 444840.820 28430.365 FALSE 0.18601949
## 2335 1947715.54 144703.128 153051.786 TRUE 0.07429377
## 2336 4032300.14 667738.708 299316.109 TRUE 0.16559747
## 2337 3173223.23 238243.731 72076.471 FALSE 0.07507941
## 2338 6144784.11 1216060.029 215705.248 TRUE 0.19790118
## 2339 179047.86 11415.654 11737.293 FALSE 0.06375756
## 2340 5191454.18 557018.558 473319.656 TRUE 0.10729529
## 2341 4067333.50 506034.689 233057.466 FALSE 0.12441436
## 2342 242127.62 21555.285 16548.334 TRUE 0.08902448
## 2343 5059475.15 834893.050 121327.762 TRUE 0.16501574
## 2344 4838883.21 958406.940 134374.796 FALSE 0.19806366
## 2345 5970167.11 615959.130 127429.661 TRUE 0.10317285
## 2346 717567.32 119535.077 19849.240 FALSE 0.16658378
## 2347 5435439.74 405918.720 175972.092 TRUE 0.07468001
## 2348 2589221.39 392733.238 130410.904 FALSE 0.15168005
## 2349 966147.26 121849.665 44658.229 TRUE 0.12611914
## 2350 1471653.64 252854.852 117318.639 FALSE 0.17181682
## 2351 3486053.41 340855.268 228782.621 FALSE 0.09777683
## 2352 7825730.14 699544.600 224309.723 FALSE 0.08939033
## 2353 7188115.28 1160372.890 684357.650 FALSE 0.16142937
## 2354 6949819.56 1221383.387 391214.165 TRUE 0.17574318
## 2355 6054127.50 758335.795 285888.741 TRUE 0.12525930
## 2356 1328778.96 95800.642 24327.734 FALSE 0.07209675
## 2357 5209812.19 265256.832 226282.857 FALSE 0.05091486
## 2358 6991045.79 1391521.105 584793.313 TRUE 0.19904334
## 2359 6247759.46 1024451.185 475898.944 FALSE 0.16397097
## 2360 2706572.89 356835.306 117106.716 FALSE 0.13184027
## 2361 262506.20 14425.500 10417.846 TRUE 0.05495299
## 2362 6008458.17 672190.921 554743.465 FALSE 0.11187411
## 2363 2941240.18 393604.780 234993.847 FALSE 0.13382273
## 2364 3746270.12 587950.733 57557.116 FALSE 0.15694296
## 2365 1589101.46 300918.818 109522.470 TRUE 0.18936413
## 2366 4560273.29 881118.291 158673.294 FALSE 0.19321612
## 2367 6423142.71 832927.059 571255.085 TRUE 0.12967594
## 2368 1934812.22 309573.788 35160.015 TRUE 0.16000198
## 2369 6114415.29 687762.887 266415.369 TRUE 0.11248220
## 2370 4153050.87 752165.799 75721.726 FALSE 0.18111163
## 2371 3500307.27 516052.254 271247.356 TRUE 0.14743056
## 2372 1081884.18 69865.071 70242.323 FALSE 0.06457722
## 2373 773046.17 128062.539 71321.508 TRUE 0.16565963
## 2374 5619609.84 790744.157 119443.537 TRUE 0.14071158
## 2375 3129613.46 412728.257 106269.617 FALSE 0.13187835
## 2376 1090212.16 62144.335 42451.863 TRUE 0.05700206
## 2377 5669711.17 1059890.905 88426.808 TRUE 0.18693914
## 2378 3350929.76 375884.034 315193.788 TRUE 0.11217306
## 2379 5686967.03 338733.868 203926.451 TRUE 0.05956318
## 2380 2217380.44 216761.065 219728.732 FALSE 0.09775547
## 2381 1194007.74 117725.243 21521.680 FALSE 0.09859672
## 2382 845699.66 44591.903 38461.739 FALSE 0.05272782
## 2383 117432.16 8206.131 4162.336 TRUE 0.06987976
## 2384 6110726.51 634651.607 249462.899 FALSE 0.10385862
## 2385 5388796.21 898183.036 505516.455 TRUE 0.16667601
## 2386 8156383.71 1000770.659 564227.434 FALSE 0.12269784
## 2387 6602345.25 366618.815 614987.004 FALSE 0.05552857
## 2388 4749509.95 428803.429 245736.320 TRUE 0.09028372
## 2389 2601846.65 480167.126 223264.448 TRUE 0.18454859
## 2390 6376392.88 1248260.327 365111.270 FALSE 0.19576277
## 2391 6725385.92 419544.782 485009.006 FALSE 0.06238226
## 2392 6156696.12 781113.845 267713.717 FALSE 0.12687224
## 2393 3931166.87 375286.948 305035.410 FALSE 0.09546452
## 2394 7230835.87 934936.141 236506.488 TRUE 0.12929849
## 2395 2936048.03 388594.734 197661.230 FALSE 0.13235299
## 2396 3409848.61 547508.245 66603.382 TRUE 0.16056673
## 2397 5515887.02 664852.265 531925.706 FALSE 0.12053406
## 2398 2676465.25 357682.894 109417.485 FALSE 0.13364003
## 2399 3823077.39 544140.374 100927.381 TRUE 0.14233046
## 2400 5361647.65 1010200.563 69240.778 FALSE 0.18841234
## 2401 3929428.87 629987.152 276883.552 FALSE 0.16032537
## 2402 807183.14 108955.404 68294.210 TRUE 0.13498226
## 2403 6580655.48 505213.904 125888.976 FALSE 0.07677258
## 2404 2932926.07 363393.315 38430.379 TRUE 0.12390129
## 2405 6164277.57 607716.384 120380.423 TRUE 0.09858680
## 2406 1639748.95 225625.373 95906.872 FALSE 0.13759751
## 2407 1989160.48 279768.488 40452.751 FALSE 0.14064651
## 2408 6681756.17 521097.127 647767.414 FALSE 0.07798805
## 2409 4307031.27 264073.096 288873.007 FALSE 0.06131209
## 2410 7118979.90 370113.224 479294.510 TRUE 0.05198964
## 2411 7850481.27 670748.857 509849.031 FALSE 0.08544048
## 2412 739799.89 118455.336 31804.041 TRUE 0.16011808
## 2413 1593125.69 261821.606 38605.525 FALSE 0.16434460
## 2414 8007527.32 411765.508 629571.074 TRUE 0.05142230
## 2415 6472991.28 357678.517 295703.027 FALSE 0.05525707
## 2416 886330.24 46062.158 53087.861 FALSE 0.05196952
## 2417 5654334.93 793438.505 213839.244 FALSE 0.14032393
## 2418 4310554.34 601219.969 84289.380 TRUE 0.13947625
## 2419 5206835.58 797416.147 96170.256 TRUE 0.15314794
## 2420 6193287.97 1027102.412 502917.570 TRUE 0.16584122
## 2421 6114647.78 879223.525 445533.349 TRUE 0.14378973
## 2422 5086077.09 415583.980 142408.543 TRUE 0.08171012
## 2423 6752850.21 510588.661 204591.006 TRUE 0.07561084
## 2424 7161555.77 1174736.553 347282.424 FALSE 0.16403371
## 2425 8249483.28 1490473.422 686439.825 FALSE 0.18067476
## 2426 8138280.08 441052.300 453476.376 FALSE 0.05419478
## 2427 5364118.34 884828.594 266392.675 TRUE 0.16495322
## 2428 415716.19 67807.150 6654.038 FALSE 0.16310923
## 2429 3829104.97 622181.418 300857.474 FALSE 0.16248743
## 2430 2749822.01 365532.937 89624.877 FALSE 0.13292967
## 2431 2939235.81 462991.882 288207.109 FALSE 0.15752118
## 2432 1080853.50 120487.028 69626.722 FALSE 0.11147397
## 2433 2632785.78 442477.529 107188.708 FALSE 0.16806439
## 2434 7508674.15 1349816.823 177720.240 FALSE 0.17976767
## 2435 1319762.99 233478.710 92419.719 TRUE 0.17690958
## 2436 4267722.47 263646.184 356388.849 TRUE 0.06177679
## 2437 432803.53 81559.867 5893.901 TRUE 0.18844548
## 2438 5709600.05 913157.638 158149.036 TRUE 0.15993373
## 2439 2636422.88 395015.930 53888.218 FALSE 0.14983026
## 2440 2587385.34 285359.823 151316.153 FALSE 0.11028888
## 2441 7215883.17 1099900.689 681980.980 FALSE 0.15242773
## 2442 3383694.67 583730.407 183714.538 TRUE 0.17251273
## 2443 1478900.79 160310.549 69757.024 FALSE 0.10839845
## 2444 1373080.18 100057.022 65098.250 TRUE 0.07287049
## 2445 2904528.60 483633.334 53304.322 FALSE 0.16651010
## 2446 2026994.59 366556.081 123412.786 FALSE 0.18083723
## 2447 498947.92 92621.707 27565.009 FALSE 0.18563402
## 2448 6206605.80 494700.420 381826.919 FALSE 0.07970547
## 2449 3861205.94 388794.230 125178.010 TRUE 0.10069244
## 2450 3926432.12 241835.782 66130.790 FALSE 0.06159174
## 2451 6542534.72 384318.375 573164.029 FALSE 0.05874151
## 2452 6108932.83 627507.835 320293.778 TRUE 0.10271971
## 2453 1922566.18 100453.540 118646.074 TRUE 0.05224972
## 2454 3576398.94 435011.282 244981.782 FALSE 0.12163388
## 2455 1885591.54 219187.378 119643.955 TRUE 0.11624330
## 2456 4975068.63 756074.915 71907.704 TRUE 0.15197276
## 2457 1648663.09 148916.774 126194.917 FALSE 0.09032578
## 2458 4798729.62 726098.111 267176.732 TRUE 0.15131049
## 2459 5603937.16 687003.640 515215.623 FALSE 0.12259303
## 2460 5744883.96 333325.799 399948.990 TRUE 0.05802133
## 2461 1098327.35 191643.991 53933.707 FALSE 0.17448713
## 2462 2602735.27 241879.231 86709.204 FALSE 0.09293271
## 2463 5644123.78 1021283.921 443469.623 TRUE 0.18094641
## 2464 5320983.05 340419.029 315409.638 FALSE 0.06397672
## 2465 3110649.83 165467.305 200159.557 TRUE 0.05319381
## 2466 1128186.77 203188.675 41883.143 TRUE 0.18010198
## 2467 5681181.18 631332.555 105629.547 TRUE 0.11112699
## 2468 4590854.90 293102.964 366299.951 FALSE 0.06384496
## 2469 4851098.35 585759.004 89340.958 FALSE 0.12074771
## 2470 1458207.96 132385.615 125427.579 TRUE 0.09078651
## 2471 6872260.29 1089829.836 517627.452 FALSE 0.15858390
## 2472 73727.01 12096.230 4971.915 TRUE 0.16406783
## 2473 1229185.44 240274.944 67607.879 TRUE 0.19547493
## 2474 1315318.00 94421.760 100820.198 FALSE 0.07178626
## 2475 6249776.39 1144650.406 504648.440 TRUE 0.18315062
## 2476 1921644.44 103973.096 175907.107 TRUE 0.05410631
## 2477 6926757.55 1374933.890 483799.246 TRUE 0.19849603
## 2478 1083276.15 115658.052 43373.984 FALSE 0.10676691
## 2479 3428017.17 680662.650 335207.023 FALSE 0.19855871
## 2480 4472291.31 551180.992 166293.882 TRUE 0.12324354
## 2481 5965428.43 579024.702 409709.265 TRUE 0.09706339
## 2482 5426218.22 786609.826 500165.218 FALSE 0.14496465
## 2483 5446593.29 927302.629 162970.028 TRUE 0.17025369
## 2484 2500020.65 364901.161 154092.646 FALSE 0.14595926
## 2485 1170741.60 199858.099 16534.304 TRUE 0.17071068
## 2486 5266149.45 496507.034 506917.470 FALSE 0.09428275
## 2487 4374314.70 718158.041 99506.132 FALSE 0.16417613
## 2488 7322903.50 1359987.979 91964.225 TRUE 0.18571704
## 2489 5707332.90 1006399.035 231081.661 TRUE 0.17633438
## 2490 5707837.99 452503.779 58741.269 TRUE 0.07927761
## 2491 5331261.13 597681.857 496268.604 TRUE 0.11210891
## 2492 7499408.26 1112337.576 573684.740 FALSE 0.14832338
## 2493 1085602.50 182081.997 64593.999 FALSE 0.16772437
## 2494 1030344.56 170436.695 35612.450 TRUE 0.16541718
## 2495 1575045.50 79181.526 55614.364 FALSE 0.05027253
## 2496 5379834.32 469325.497 287536.509 TRUE 0.08723791
## 2497 6876322.93 423368.437 399678.888 TRUE 0.06156902
## 2498 647803.63 117775.647 44848.677 FALSE 0.18180764
## 2499 4709250.24 546074.494 140136.513 FALSE 0.115957844 Level : Data Visualization
4.1 Question: Visualize total import vs export value
data %>%
group_by(Import_Export) %>%
summarise(Total = sum(Value_INR)) %>%
ggplot(aes(x = Import_Export, y = Total, fill = Import_Export)) +
geom_bar(stat = "identity") +
scale_y_continuous(labels=comma) +
ggtitle("Import vs Export Trade Value")
Explanation: This bar chart compares total import and
export values.
4.2 Question: Show country-wise trade distribution
# Get top 10 countries
top_countries <- data %>%
group_by(Country) %>%
summarise(Total = sum(Value_INR, na.rm = TRUE)) %>%
arrange(desc(Total)) %>%
head(10)
# Plot Import vs Export for top countries
data %>%
filter(Country %in% top_countries$Country) %>%
ggplot(aes(x = Country, y = Value_INR, fill = Import_Export)) +
geom_bar(stat = "summary", fun = "sum", position = "dodge") +
scale_fill_manual(values = c("Import" = "steelblue", "Export" = "orange")) +
scale_y_continuous(labels=comma) +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Explanation: Shows which countries contribute most to
trade.
4.3 Question: Analyze product category trade value
data %>%
group_by(Product_Category) %>%
summarise(Total = sum(Value_INR)) %>%
ggplot(aes(x = Product_Category, y = Total, fill = Product_Category)) +
geom_bar(stat = "identity") +
scale_fill_brewer(palette = "Pastel1") +
scale_y_continuous(labels=comma) +
ggtitle("Trade by Product Category") +
theme_minimal()
Explanation: Displays trade distribution across product
categories.
4.4 Question: Relationship between Quantity and Trade Value
ggplot(data, aes(x = Quantity, y = Value_INR, color = Import_Export)) +
geom_point(size = 2) +
scale_color_manual(values = c("Import" = "red", "Export" = "darkgreen")) +
scale_y_continuous(labels=comma) +
ggtitle("Quantity vs Trade Value") +
theme_minimal()
Explanation: Shows relationship between quantity and
trade value.
4.5 Question: Distribution of Profit using histogram
ggplot(data, aes(x = Profit)) +
geom_histogram(fill = "purple", bins = 25, color = "black") +
ggtitle("Distribution of Profit") +
theme_minimal()
Explanation: Displays distribution of profit
values.
4.6 Question: Compare profit between import and export using boxplot
ggplot(data, aes(x = Import_Export, y = Profit, fill = Import_Export)) +
geom_boxplot() +
scale_fill_manual(values = c("Import" = "cyan", "Export" = "pink")) +
ggtitle("Profit Comparison: Import vs Export") +
theme_minimal()
Explanation:
Boxplot shows median, quartiles, and outliers Helps compare profit variation
4.7 Question: Line Plot (Monthly Trend)
data %>%
group_by(Month) %>%
summarise(Total = sum(Value_INR)) %>%
ggplot(aes(x = Month, y = Total, group = 1)) +
geom_line(color = "blue", size = 1) +
scale_y_continuous(labels=comma) +
geom_point(color = "red") +
ggtitle("Monthly Trade Trend") +
theme_minimal()## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Explanation Monthly trade trend
5 Level : Exploratory Data Analysis (EDA)
5.1 Question: Calculate Mean, Median, Standard Deviation of Trade Value
mean(data$Value_INR, na.rm = TRUE)## [1] 3913429median(data$Value_INR, na.rm = TRUE)## [1] 3989931sd(data$Value_INR, na.rm = TRUE)## [1] 2185819Explanation: Mean gives average trade value, median shows middle value, and standard deviation shows variability in trade.
5.2 Question: Calculate Quartiles and IQR
quantile(data$Value_INR, probs = c(0.25, 0.5, 0.75), na.rm = TRUE)## 25% 50% 75%
## 2019441 3989931 5650065IQR(data$Value_INR, na.rm = TRUE)## [1] 3630624Explanation: Quartiles divide data into parts and IQR helps understand spread of middle 50%
5.3 Question: Density Plot
ggplot(data, aes(x = Value_INR)) +
geom_density(fill = "blue") +
scale_y_continuous(labels=comma) +
theme_minimal()
Explanation: Smooth curve representing data
distribution shape.
5.4 Question: Boxplot for Outlier Detection
ggplot(data, aes(y = Value_INR)) +
geom_boxplot(fill = "orange") +
scale_y_continuous(labels=comma) +
theme_minimal()
Explanation: Outliers appear as points outside
whiskers
5.5 Question: Group-wise Summary
data %>%
group_by(Product_Category) %>%
summarise(mean_value = mean(Value_INR, na.rm = TRUE))## # A tibble: 5 × 2
## Product_Category mean_value
## <fct> <dbl>
## 1 Agriculture 3910976.
## 2 Automobile 4008188.
## 3 Electronics 3873842.
## 4 Pharma 3925927.
## 5 Textile 3844378.Explanation: Compares average trade value across categories.
6 Level: Correlation Analysis
6.1 Question: Compute Correlation between Quantity and Value
cor(data$Quantity, data$Value_INR, use = "complete.obs")## [1] -0.03386827Explanation Shows strength and direction of relationship.
6.2 Question: Correlation Matrix
numeric_data <- data %>% select_if(is.numeric)
cor(numeric_data, use = "complete.obs")## Year Quantity Value_USD Tariff
## Year 1.000000000 0.0161030111 -0.025092511 -0.0103024691
## Quantity 0.016103011 1.0000000000 -0.039329509 -0.0027596824
## Value_USD -0.025092511 -0.0393295092 1.000000000 -0.0041065640
## Tariff -0.010302469 -0.0027596824 -0.004106564 1.0000000000
## GST 0.049261965 -0.0068695965 -0.026283757 -0.0227755818
## Exchange_Rate 0.009181148 0.0057305000 0.010871942 0.0115424653
## Shipment_Days 0.001427761 -0.0107827285 0.027842990 0.0189737978
## Value_INR -0.017378650 -0.0338682718 0.962019051 0.0004222747
## Profit -0.006989967 -0.0266887378 0.780593400 -0.0163097473
## Loss -0.014888712 -0.0692412830 0.688611934 -0.0214187557
## Profit_Margin 0.017390244 -0.0004879952 -0.020474883 -0.0180827251
## GST Exchange_Rate Shipment_Days Value_INR
## Year 0.0492619649 0.009181148 0.0014277605 -0.0173786505
## Quantity -0.0068695965 0.005730500 -0.0107827285 -0.0338682718
## Value_USD -0.0262837569 0.010871942 0.0278429902 0.9620190507
## Tariff -0.0227755818 0.011542465 0.0189737978 0.0004222747
## GST 1.0000000000 -0.007138023 -0.0001991214 -0.0313732239
## Exchange_Rate -0.0071380228 1.000000000 0.0044045595 0.1064546517
## Shipment_Days -0.0001991214 0.004404560 1.0000000000 0.0324612039
## Value_INR -0.0313732239 0.106454652 0.0324612039 1.0000000000
## Profit -0.0164102752 0.081987313 0.0322617629 0.8161955333
## Loss -0.0300993851 0.094260786 0.0095081903 0.7230017381
## Profit_Margin 0.0187139214 -0.013248795 0.0167840538 -0.0158131350
## Profit Loss Profit_Margin
## Year -0.006989967 -0.01488871 0.0173902445
## Quantity -0.026688738 -0.06924128 -0.0004879952
## Value_USD 0.780593400 0.68861193 -0.0204748830
## Tariff -0.016309747 -0.02141876 -0.0180827251
## GST -0.016410275 -0.03009939 0.0187139214
## Exchange_Rate 0.081987313 0.09426079 -0.0132487946
## Shipment_Days 0.032261763 0.00950819 0.0167840538
## Value_INR 0.816195533 0.72300174 -0.0158131350
## Profit 1.000000000 0.58138789 0.4888629573
## Loss 0.581387891 1.00000000 -0.0252525421
## Profit_Margin 0.488862957 -0.02525254 1.0000000000Explanation Displays correlation among all numeric variables.
6.3 Question: Correlation Heatmap
library(corrplot)## Warning: package 'corrplot' was built under R version 4.5.3## corrplot 0.95 loadedcorr_matrix <- cor(numeric_data, use = "complete.obs")
corrplot(corr_matrix, method = "color")
Explanation Visual representation of correlation
strength.
6.4 Question: Correlation Test
pairs(numeric_data)
Explanation
Provides significance of correlation.
7 Level : Regression Analysis
7.1 Question: Simple Linear Regression
model1 <- lm(Value_INR ~ Exchange_Rate, data = data)
summary(model1)##
## Call:
## lm(formula = Value_INR ~ Exchange_Rate, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4159867 -1846639 77105 1741970 4045319
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -261249 781533 -0.334 0.738
## Exchange_Rate 53953 10085 5.350 9.6e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2174000 on 2497 degrees of freedom
## Multiple R-squared: 0.01133, Adjusted R-squared: 0.01094
## F-statistic: 28.62 on 1 and 2497 DF, p-value: 9.598e-08Explanation Shows how quantity affects trade value.
7.2 Question: Multiple Linear Regression
model_correct <- lm(Value_INR ~ Quantity + Shipment_Days + Exchange_Rate, data = data)
summary(model_correct)##
## Call:
## lm(formula = Value_INR ~ Quantity + Shipment_Days + Exchange_Rate,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4248177 -1854641 81336 1736276 4210855
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -253196.41 787573.80 -0.321 0.7479
## Quantity -25.94 15.11 -1.717 0.0862 .
## Shipment_Days 7727.53 4859.18 1.590 0.1119
## Exchange_Rate 53981.87 10077.98 5.356 9.27e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2172000 on 2495 degrees of freedom
## Multiple R-squared: 0.01352, Adjusted R-squared: 0.01234
## F-statistic: 11.4 on 3 and 2495 DF, p-value: 2.008e-07EXPLANATION Analyzes multiple factors affecting value.
7.3 Question: Regression Plot
ggplot(data, aes(x = Quantity, y = Value_INR)) +
geom_point() +
geom_smooth(method = "lm", color = "blue") +
scale_y_continuous(labels=comma) +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'
EXPLANTION Displays regression line.
7.4 Question: Polynomial Regression
model3 <- lm(Value_INR ~ poly(Quantity, 2), data = data)
summary(model3)##
## Call:
## lm(formula = Value_INR ~ poly(Quantity, 2), data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3902702 -1892705 66727 1734194 4528043
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3913429 43715 89.521 <2e-16 ***
## poly(Quantity, 2)1 -3700014 2185328 -1.693 0.0906 .
## poly(Quantity, 2)2 -1106363 2185328 -0.506 0.6127
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2185000 on 2496 degrees of freedom
## Multiple R-squared: 0.00125, Adjusted R-squared: 0.0004493
## F-statistic: 1.561 on 2 and 2496 DF, p-value: 0.21Explation Captures non-linear relationship.
7.5 Question: Residual Analysis
plot(model1$residuals)