### Setup
getwd()
## [1] "C:/Users/Jerome/Documents/0000_Work_Files/0000_Montgomery_College/Data_Science_101/Data_101_Fall_2022/Homework_10_Due_14Nov22"
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6 ✔ purrr 0.3.5
## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.1 ✔ stringr 1.4.1
## ✔ readr 2.1.3 ✔ forcats 0.5.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
library(dplyr)
library(readr)
library(infer)
library(ggplot2)
library(hablar)
##
## Attaching package: 'hablar'
##
## The following object is masked from 'package:forcats':
##
## fct
##
## The following object is masked from 'package:dplyr':
##
## na_if
##
## The following object is masked from 'package:tibble':
##
## num
### Question 1
### I wanted to find a file that had a good mix of continuous, discrete, and categorical variables, and from which I could tell some sort of story. I found this dataset on Kaggle: https://www.kaggle.com/datasets/whenamancodes/credit-card-customers-prediction The data set has data on one bank's credit card customers. The data were used to determine how many credit card customers "churned," or left the bank for other credit card vendors. I'm not interested in that aspect of the dataset, but I am interested in the demographics in relation to credit card limits and the extent to which people use their cards.
### There are 10,127 observations and 23 variables in the data set. Obviously I don't need all 23 variables. I selected 12 variables; again, far too many for this assignment, but I wanted a sufficient # of variables so I could play around w/ the data if I wanted to do so. The variables I chose are as follows:
#1 Customer Age
#2 Customer Gender - F, M
#3 # Dependents
#4 Customer Education - 7 Categories Ranging from Unknown, then Uneducated, high school, college, graduate, post-graduate, doctorate. No explanation was given, so I have no clue how to rank these from low to high. Note there is no way to distinguish between some high school and a high school graduate. Does graduate mean "this person graduated," or does it mean "some graduate school?" The documentation doesn't say.
#5 Customer Marital Status - S, M, D, U Note there is no code for widow or widower
#6 Credit Card Type - Blue, Silver, Gold, Platinum
#7 # of Months with Bank (Descriptives run for this variable "Months_on_book")
#8 # of Customer's Bank Products
#9 Customer Credit Limit (Descriptives run for this variable "Credit_Limit")
#10 Total Annual $ Value of the Customer's Transactions (Descriptives run for this Variable "Total_Trans_Amt")
#11 Total # of Customer's Annual Transactions
#12 Mean Card Utilization Ratio - Formula not given
###
# Question 2 - Descriptives for 2 - 3 key quantitative variables. 1st import the data into R.
bc <- read_csv("BankChurners.csv", show_col_types = FALSE)
# Question 2 (con't.) - Delete unwanted columns
bc1 <- bc[c(3,4,5,6,7,9,10,11,14,18,19,21)]
names(bc1)
## [1] "Customer_Age" "Gender"
## [3] "Dependent_count" "Education_Level"
## [5] "Marital_Status" "Card_Category"
## [7] "Months_on_book" "Total_Relationship_Count"
## [9] "Credit_Limit" "Total_Trans_Amt"
## [11] "Total_Trans_Ct" "Avg_Utilization_Ratio"
#Question 2 (con't) - Calculate descriptives for Months_on_book, Credit_Limit, and Total_Trans_Amt.I will do all descriptives for each variable sequentially, starting w/ Months_on_book. Note there are NAs in this data set (I lucked out).
mean(bc1$Months_on_book)
## [1] 35.92841
median(bc1$Months_on_book)
## [1] 36
which.max(table(bc1$Months_on_book)) %>% names
## [1] "36"
min(bc1$Months_on_book)
## [1] 13
max(bc1$Months_on_book)
## [1] 56
length(bc1$Months_on_book)
## [1] 10127
sd(bc1$Months_on_book)
## [1] 7.986416
# Question 2 (con't.) - Descriptives for Credit_Limit
mean(bc1$Credit_Limit)
## [1] 8631.954
median(bc1$Credit_Limit)
## [1] 4549
which.max(table(bc1$Credit_Limit)) %>% names
## [1] "34516"
min(bc1$Credit_Limit)
## [1] 1438.3
max(bc1$Credit_Limit)
## [1] 34516
length(bc1$Credit_Limit)
## [1] 10127
sd(bc1$Credit_Limit)
## [1] 9088.777
# Verify the Mode and Median are the same in Credit_Limit
unique(bc1$Credit_Limit)
## [1] 12691.0 8256.0 3418.0 3313.0 4716.0 4010.0 34516.0 29081.0 22352.0
## [10] 11656.0 6748.0 9095.0 11751.0 8547.0 2436.0 4234.0 30367.0 13535.0
## [19] 3193.0 14470.0 20979.0 1438.3 4470.0 2492.0 12217.0 7768.0 14784.0
## [28] 10215.0 10100.0 4785.0 2753.0 2451.0 8923.0 2650.0 12555.0 3520.0
## [37] 3035.0 15433.0 3672.0 7882.0 32426.0 6205.0 17304.0 3906.0 9830.0
## [46] 2283.0 2548.0 19458.0 4745.0 2622.0 3171.0 19763.0 15769.0 3298.0
## [55] 2802.0 4458.0 6273.0 3336.0 3436.0 5926.0 23957.0 14734.0 6584.0
## [64] 2084.0 1687.0 25300.0 2216.0 2910.0 22913.0 24312.0 5272.0 7000.0
## [73] 7038.0 2536.0 28904.0 8567.0 2158.0 10133.0 3085.0 19040.0 4026.0
## [82] 12756.0 5266.0 9930.0 31302.0 6576.0 2664.0 2535.0 1709.0 3454.0
## [91] 3789.0 9689.0 5449.0 23032.0 2940.0 3031.0 1862.0 8358.0 14450.0
## [100] 33791.0 8466.0 15088.0 3263.0 1494.0 13551.0 18886.0 11976.0 9964.0
## [109] 24159.0 5362.0 3174.0 12262.0 3788.0 2926.0 32090.0 11669.0 13532.0
## [118] 11888.0 2393.0 6111.0 19270.0 3710.0 3235.0 11749.0 7753.0 10408.0
## [127] 3967.0 8025.0 9036.0 14926.0 6335.0 14979.0 2732.0 2250.0 10916.0
## [136] 5349.0 9366.0 21617.0 13860.0 18386.0 2405.0 2154.0 2038.0 8135.0
## [145] 9364.0 32643.0 3195.0 2852.0 4224.0 20459.0 3482.0 3065.0 2185.0
## [154] 1611.0 2822.0 32975.0 15875.0 6703.0 3212.0 9797.0 10400.0 26792.0
## [163] 3006.0 19482.0 3356.0 5771.0 11106.0 2890.0 3380.0 21331.0 12860.0
## [172] 6278.0 9355.0 20758.0 14612.0 27259.0 6347.0 21592.0 3449.0 6028.0
## [181] 18214.0 16393.0 7871.0 5288.0 11376.0 12302.0 10514.0 2619.0 24407.0
## [190] 2377.0 11086.0 11432.0 13258.0 2571.0 5781.0 7872.0 11127.0 1857.0
## [199] 1913.0 3839.0 2115.0 27756.0 13878.0 3106.0 18871.0 5207.0 17965.0
## [208] 2733.0 8863.0 11107.0 21573.0 2859.0 5269.0 3387.0 1982.0 4645.0
## [217] 2189.0 2442.0 21304.0 7577.0 3234.0 4469.0 3616.0 3252.0 2358.0
## [226] 22322.0 3133.0 3540.0 6990.0 24396.0 2474.0 5214.0 9512.0 3187.0
## [235] 3353.0 2290.0 5279.0 23603.0 2601.0 6363.0 8029.0 2410.0 3401.0
## [244] 2260.0 17682.0 4206.0 23018.0 5556.0 6094.0 2939.0 27126.0 3342.0
## [253] 2532.0 1900.0 14546.0 2521.0 16427.0 13068.0 23218.0 3281.0 3096.0
## [262] 2052.0 9432.0 14938.0 2221.0 5731.0 6985.0 24221.0 15439.0 21637.0
## [271] 14543.0 9684.0 5007.0 1616.0 19116.0 2759.0 8249.0 14041.0 5264.0
## [280] 2420.0 2826.0 12518.0 5876.0 9648.0 3025.0 3265.0 6041.0 2293.0
## [289] 13399.0 4317.0 3378.0 5012.0 2569.0 3471.0 3312.0 2578.0 2902.0
## [298] 2742.0 2077.0 6265.0 7819.0 2731.0 16286.0 2609.0 7567.0 22770.0
## [307] 3791.0 2702.0 2555.0 2355.0 5332.0 1443.0 10741.0 7984.0 18584.0
## [316] 5585.0 2478.0 2339.0 2726.0 14881.0 1628.0 3156.0 19727.0 22720.0
## [325] 8129.0 3751.0 1594.0 18206.0 3104.0 2406.0 24571.0 15534.0 12301.0
## [334] 2846.0 9788.0 7231.0 2324.0 12208.0 5639.0 10021.0 2215.0 2027.0
## [343] 3920.0 9226.0 9376.0 1944.0 9599.0 28202.0 24850.0 3805.0 12781.0
## [352] 7477.0 29963.0 6509.0 13450.0 27000.0 13048.0 2453.0 16138.0 8077.0
## [361] 1929.0 3127.0 8645.0 24487.0 2567.0 4131.0 10790.0 6884.0 13961.0
## [370] 29801.0 13219.0 9478.0 3502.0 10509.0 1491.0 9734.0 2305.0 14241.0
## [379] 4789.0 23138.0 23008.0 3131.0 5798.0 6880.0 2075.0 4589.0 2317.0
## [388] 1981.0 6038.0 14910.0 29659.0 4320.0 11213.0 26181.0 5773.0 4503.0
## [397] 29770.0 5014.0 3445.0 23412.0 3044.0 14596.0 3864.0 17030.0 23090.0
## [406] 29205.0 14035.0 2962.0 18578.0 2201.0 2061.0 24602.0 15911.0 16867.0
## [415] 2783.0 2972.0 5124.0 2880.0 5579.0 12010.0 4394.0 18325.0 3773.0
## [424] 21684.0 1919.0 9995.0 11910.0 2279.0 3539.0 30579.0 24480.0 17561.0
## [433] 1638.0 2947.0 5738.0 33304.0 7251.0 2885.0 2641.0 2801.0 16794.0
## [442] 9336.0 2763.0 17391.0 3198.0 5100.0 3955.0 3140.0 4028.0 2264.0
## [451] 21620.0 6385.0 2375.0 1963.0 4256.0 5097.0 3228.0 20231.0 27512.0
## [460] 2585.0 12151.0 5504.0 3558.0 19853.0 4969.0 3117.0 21526.0 5512.0
## [469] 7262.0 7319.0 7712.0 2053.0 12804.0 26443.0 3125.0 4930.0 9476.0
## [478] 11722.0 13301.0 6705.0 22718.0 23981.0 2318.0 19324.0 5331.0 15700.0
## [487] 17625.0 17438.0 1962.0 3290.0 2402.0 9256.0 3674.0 6462.0 4335.0
## [496] 3233.0 11862.0 19802.0 24869.0 3624.0 6175.0 10953.0 11338.0 5544.0
## [505] 19665.0 2927.0 5146.0 1704.0 2974.0 5472.0 2736.0 5406.0 1976.0
## [514] 8714.0 8693.0 9247.0 7717.0 4908.0 7222.0 21740.0 2323.0 7788.0
## [523] 23700.0 11710.0 2278.0 4048.0 3663.0 3518.0 1717.0 16813.0 16434.0
## [532] 21872.0 15897.0 4271.0 7361.0 8628.0 18750.0 21242.0 2961.0 11327.0
## [541] 8308.0 3249.0 2981.0 8829.0 3714.0 7340.0 16952.0 20865.0 3083.0
## [550] 10584.0 2240.0 12240.0 5120.0 3124.0 11261.0 2468.0 22157.0 11477.0
## [559] 3933.0 8022.0 13771.0 30271.0 3244.0 2936.0 6242.0 11806.0 4734.0
## [568] 6244.0 23561.0 24742.0 27560.0 5923.0 8581.0 7151.0 1535.0 2122.0
## [577] 17131.0 5822.0 3537.0 16320.0 2407.0 3538.0 2684.0 15459.0 4307.0
## [586] 2081.0 2848.0 6361.0 15428.0 2544.0 9959.0 8796.0 3428.0 18001.0
## [595] 2680.0 4675.0 2448.0 4049.0 8154.0 4559.0 19354.0 2340.0 13848.0
## [604] 2490.0 32156.0 9050.0 8362.0 6514.0 4051.0 11959.0 2070.0 11840.0
## [613] 3636.0 11067.0 11262.0 5108.0 2072.0 4119.0 5903.0 7860.0 5918.0
## [622] 6741.0 3880.0 2494.0 22149.0 5450.0 2003.0 7723.0 18226.0 8128.0
## [631] 5851.0 10260.0 26945.0 2243.0 12248.0 19843.0 2163.0 33864.0 4531.0
## [640] 2950.0 7706.0 25657.0 17536.0 3770.0 10344.0 26437.0 2450.0 3136.0
## [649] 6976.0 21134.0 2019.0 20241.0 2421.0 30948.0 2642.0 8070.0 4085.0
## [658] 2187.0 3358.0 1888.0 14447.0 32349.0 12605.0 2964.0 3785.0 2727.0
## [667] 3343.0 9786.0 6407.0 4158.0 21697.0 31383.0 30883.0 12918.0 8520.0
## [676] 14310.0 14434.0 7793.0 8990.0 4343.0 2872.0 9697.0 2967.0 2148.0
## [685] 6116.0 18085.0 2524.0 33951.0 9956.0 3888.0 30655.0 2997.0 11042.0
## [694] 3386.0 15987.0 25188.0 4315.0 2592.0 5476.0 2464.0 2378.0 20056.0
## [703] 8013.0 7906.0 11501.0 13632.0 2229.0 5158.0 23271.0 10244.0 2588.0
## [712] 10747.0 7474.0 3555.0 22140.0 9457.0 6218.0 2580.0 6224.0 3093.0
## [721] 4076.0 4861.0 9851.0 7349.0 2853.0 17023.0 10060.0 1595.0 8475.0
## [730] 5559.0 2917.0 6692.0 8551.0 10569.0 7051.0 10117.0 8311.0 26442.0
## [739] 4920.0 26750.0 1869.0 14539.0 26977.0 5426.0 7623.0 4844.0 2683.0
## [748] 3214.0 5374.0 8004.0 2925.0 9235.0 8837.0 8801.0 3563.0 8138.0
## [757] 2458.0 4592.0 1868.0 20156.0 7410.0 12163.0 4250.0 12059.0 2799.0
## [766] 18037.0 5657.0 13770.0 4646.0 2514.0 14501.0 8663.0 2333.0 3038.0
## [775] 8851.0 2945.0 5267.0 8512.0 19063.0 5376.0 7772.0 9173.0 11975.0
## [784] 15405.0 2615.0 23991.0 3102.0 3170.0 17298.0 11915.0 16868.0 3266.0
## [793] 2770.0 3556.0 9149.0 14701.0 14825.0 10127.0 2929.0 3735.0 2930.0
## [802] 12716.0 22120.0 4546.0 1759.0 4829.0 7692.0 2156.0 9521.0 26714.0
## [811] 2092.0 11594.0 2834.0 4724.0 3049.0 20614.0 3250.0 3128.0 6414.0
## [820] 2506.0 7469.0 3460.0 4175.0 10264.0 4129.0 2658.0 2781.0 24880.0
## [829] 8504.0 8091.0 3417.0 9204.0 14302.0 6313.0 15904.0 11696.0 20371.0
## [838] 7552.0 5561.0 1441.0 19715.0 2486.0 4570.0 3870.0 12938.0 21178.0
## [847] 12182.0 3583.0 17018.0 16031.0 4203.0 4213.0 21548.0 18513.0 2483.0
## [856] 6511.0 2985.0 18797.0 2888.0 9172.0 14281.0 7353.0 5145.0 4753.0
## [865] 2171.0 4150.0 9106.0 2686.0 10239.0 15017.0 4426.0 2155.0 20620.0
## [874] 3238.0 14316.0 2607.0 6231.0 3730.0 3094.0 6630.0 1925.0 33406.0
## [883] 9452.0 2162.0 3947.0 15970.0 1830.0 20811.0 11789.0 3073.0 6725.0
## [892] 2978.0 24545.0 10074.0 2259.0 9519.0 3706.0 4438.0 2372.0 4214.0
## [901] 2613.0 4331.0 3665.0 4411.0 15871.0 12643.0 6088.0 13873.0 6158.0
## [910] 5638.0 2178.0 12588.0 11942.0 3914.0 18693.0 2943.0 2435.0 5756.0
## [919] 21065.0 9428.0 6065.0 5024.0 2174.0 3398.0 4319.0 3673.0 1815.0
## [928] 2495.0 3368.0 7225.0 5202.0 1923.0 6929.0 4364.0 2400.0 25878.0
## [937] 11876.0 4568.0 4740.0 4949.0 11189.0 6099.0 3575.0 3184.0 13363.0
## [946] 3452.0 4466.0 3030.0 2112.0 7583.0 11760.0 19762.0 2803.0 25666.0
## [955] 9297.0 2999.0 16435.0 5335.0 3506.0 3610.0 3172.0 8206.0 2416.0
## [964] 1677.0 11819.0 1459.0 1458.0 7758.0 10836.0 5062.0 3399.0 2212.0
## [973] 3186.0 5927.0 5176.0 3126.0 4670.0 10155.0 15242.0 16043.0 3181.0
## [982] 27088.0 5688.0 10462.0 5249.0 5155.0 10705.0 16494.0 6469.0 2800.0
## [991] 5159.0 5248.0 5881.0 1467.0 4999.0 4668.0 8638.0 9343.0 2256.0
## [1000] 8267.0 2235.0 2111.0 10604.0 21782.0 2133.0 16677.0 2717.0 3980.0
## [1009] 8411.0 2227.0 1860.0 2829.0 3764.0 4701.0 1631.0 8096.0 2304.0
## [1018] 5210.0 5452.0 7475.0 2359.0 4237.0 18582.0 7202.0 11221.0 18889.0
## [1027] 2066.0 20050.0 3046.0 6193.0 5634.0 4507.0 3040.0 21006.0 7326.0
## [1036] 3651.0 3416.0 3664.0 6085.0 22332.0 2063.0 4429.0 3991.0 9723.0
## [1045] 5325.0 7427.0 5619.0 5413.0 7646.0 4252.0 2031.0 6861.0 3327.0
## [1054] 7272.0 2515.0 2798.0 12609.0 19159.0 9642.0 8396.0 6978.0 2459.0
## [1063] 12956.0 7128.0 18749.0 2193.0 4522.0 2157.0 11927.0 11341.0 7345.0
## [1072] 6036.0 2096.0 1906.0 5039.0 6214.0 1512.0 3346.0 6660.0 2234.0
## [1081] 9671.0 6605.0 5456.0 4088.0 3930.0 4188.0 3637.0 11521.0 2253.0
## [1090] 30503.0 4596.0 5701.0 3221.0 3022.0 2699.0 2210.0 2041.0 1643.0
## [1099] 29543.0 3158.0 2899.0 5645.0 2463.0 2897.0 5391.0 2870.0 23959.0
## [1108] 14918.0 3590.0 2297.0 25058.0 7418.0 3012.0 4562.0 10723.0 1578.0
## [1117] 2094.0 4138.0 5417.0 9592.0 8881.0 3893.0 3242.0 6035.0 17642.0
## [1126] 4327.0 4852.0 7147.0 10320.0 3297.0 9981.0 3329.0 5991.0 6259.0
## [1135] 2541.0 21351.0 8998.0 10247.0 20311.0 33182.0 1686.0 4742.0 1726.0
## [1144] 8420.0 3352.0 6648.0 2335.0 12397.0 5330.0 1795.0 5741.0 2002.0
## [1153] 25662.0 22103.0 12355.0 2000.0 8713.0 9165.0 11583.0 8149.0 8434.0
## [1162] 9791.0 8444.0 2228.0 12211.0 1586.0 2247.0 2789.0 4241.0 8398.0
## [1171] 4112.0 15578.0 4008.0 12766.0 3438.0 16692.0 4066.0 13080.0 1934.0
## [1180] 3230.0 3615.0 1801.0 2665.0 28822.0 14632.0 6715.0 6658.0 3360.0
## [1189] 14853.0 4800.0 4610.0 8377.0 4147.0 2644.0 13355.0 3251.0 2100.0
## [1198] 3566.0 14915.0 13003.0 1758.0 5510.0 17196.0 5877.0 7667.0 5898.0
## [1207] 19995.0 2773.0 3323.0 16049.0 3601.0 2307.0 3742.0 2937.0 3209.0
## [1216] 12554.0 4702.0 14308.0 4882.0 33405.0 2700.0 2934.0 1548.0 5525.0
## [1225] 5750.0 27157.0 12830.0 5530.0 2437.0 3827.0 5940.0 13162.0 18713.0
## [1234] 3023.0 6103.0 10607.0 25197.0 2743.0 4111.0 3667.0 3178.0 5674.0
## [1243] 11444.0 6387.0 11827.0 2608.0 3203.0 2472.0 2147.0 8058.0 3410.0
## [1252] 19044.0 1606.0 24336.0 5030.0 24577.0 3517.0 7400.0 2956.0 3578.0
## [1261] 12778.0 1942.0 29961.0 17657.0 2821.0 1479.0 6859.0 3404.0 1890.0
## [1270] 3602.0 3766.0 3017.0 5478.0 13046.0 8687.0 6174.0 5655.0 5397.0
## [1279] 28465.0 3444.0 2104.0 15610.0 16912.0 5462.0 2868.0 2685.0 5238.0
## [1288] 4561.0 13091.0 10826.0 2600.0 2561.0 7087.0 10266.0 1553.0 6732.0
## [1297] 12181.0 7056.0 14365.0 11473.0 23996.0 2998.0 30011.0 21927.0 10029.0
## [1306] 4934.0 13882.0 2347.0 4116.0 13904.0 32558.0 12902.0 2509.0 2484.0
## [1315] 2780.0 5219.0 18102.0 4532.0 22399.0 4489.0 10329.0 2637.0 1864.0
## [1324] 13276.0 1935.0 6784.0 19127.0 32641.0 2417.0 19259.0 3796.0 4042.0
## [1333] 17603.0 2894.0 16730.0 3282.0 15815.0 1672.0 8121.0 3182.0 5061.0
## [1342] 2735.0 3477.0 27858.0 14057.0 2461.0 7766.0 21308.0 4516.0 5424.0
## [1351] 1764.0 1493.0 17539.0 2149.0 6256.0 11922.0 4075.0 7290.0 5965.0
## [1360] 9007.0 6077.0 1808.0 12810.0 3421.0 3118.0 20013.0 4395.0 9661.0
## [1369] 1973.0 9926.0 4108.0 20741.0 16335.0 4588.0 5712.0 13184.0 8592.0
## [1378] 1910.0 6210.0 2220.0 20756.0 2895.0 9274.0 2334.0 3519.0 3088.0
## [1387] 11906.0 11098.0 2224.0 5723.0 9239.0 4061.0 4189.0 6373.0 3261.0
## [1396] 8014.0 10980.0 3092.0 14315.0 1648.0 1730.0 13768.0 1705.0 8673.0
## [1405] 6391.0 11102.0 24765.0 31864.0 5346.0 3148.0 2786.0 11894.0 7535.0
## [1414] 33180.0 2986.0 6729.0 2730.0 3324.0 5015.0 6905.0 5848.0 19136.0
## [1423] 3500.0 7453.0 6266.0 4945.0 27992.0 6162.0 3337.0 2205.0 4450.0
## [1432] 2172.0 4323.0 4145.0 2032.0 7010.0 3205.0 16547.0 5930.0 2047.0
## [1441] 2636.0 6425.0 4002.0 5175.0 4599.0 31258.0 11638.0 1829.0 8276.0
## [1450] 23539.0 2352.0 11371.0 2857.0 6690.0 4439.0 5344.0 27310.0 2531.0
## [1459] 9096.0 7169.0 5399.0 2280.0 6315.0 4402.0 27732.0 4947.0 3946.0
## [1468] 12291.0 3067.0 8633.0 2394.0 11374.0 6921.0 2564.0 2720.0 9843.0
## [1477] 21691.0 1826.0 5746.0 7061.0 5589.0 9620.0 2539.0 3642.0 3451.0
## [1486] 1841.0 5764.0 18278.0 16059.0 5887.0 3152.0 12464.0 4784.0 1950.0
## [1495] 7478.0 1707.0 4016.0 2370.0 3478.0 1539.0 3142.0 17236.0 13206.0
## [1504] 2480.0 2898.0 1570.0 4460.0 1544.0 3456.0 2751.0 4153.0 3685.0
## [1513] 8902.0 2944.0 2232.0 1569.0 23622.0 3326.0 11352.0 17531.0 8374.0
## [1522] 7049.0 3851.0 15936.0 10305.0 2987.0 6275.0 7185.0 3077.0 2042.0
## [1531] 2001.0 3625.0 7803.0 5951.0 15796.0 7558.0 5381.0 2661.0 8329.0
## [1540] 2774.0 4134.0 11329.0 9055.0 17393.0 5908.0 5825.0 3797.0 13734.0
## [1549] 3034.0 2973.0 24296.0 8969.0 2550.0 10357.0 1475.0 5154.0 3586.0
## [1558] 1640.0 2379.0 3422.0 4365.0 32938.0 6710.0 2507.0 6184.0 2029.0
## [1567] 16659.0 2203.0 5122.0 3074.0 2584.0 2037.0 2014.0 1818.0 2827.0
## [1576] 16033.0 3213.0 5924.0 14535.0 2833.0 1617.0 2237.0 2900.0 13126.0
## [1585] 8695.0 2159.0 2501.0 6338.0 2190.0 7578.0 2963.0 8260.0 8309.0
## [1594] 10230.0 22382.0 25790.0 2675.0 1652.0 5815.0 2595.0 6922.0 6979.0
## [1603] 2594.0 16915.0 2523.0 6235.0 1473.0 17116.0 4631.0 3047.0 32338.0
## [1612] 16611.0 22886.0 3544.0 3480.0 3549.0 6814.0 8500.0 28170.0 6610.0
## [1621] 15755.0 2711.0 10216.0 20420.0 13662.0 7050.0 1775.0 8960.0 6803.0
## [1630] 2145.0 3919.0 4500.0 2941.0 7102.0 6866.0 10378.0 13473.0 18178.0
## [1639] 8171.0 8082.0 24589.0 30310.0 1618.0 2498.0 10540.0 13384.0 16208.0
## [1648] 19214.0 3071.0 13395.0 17126.0 8083.0 8995.0 2404.0 2807.0 3097.0
## [1657] 10651.0 2175.0 28020.0 2640.0 31313.0 7304.0 3254.0 3161.0 7246.0
## [1666] 13719.0 4726.0 6100.0 19279.0 3792.0 6849.0 5802.0 2919.0 2462.0
## [1675] 1947.0 18563.0 3992.0 3568.0 7776.0 19636.0 7327.0 2033.0 5153.0
## [1684] 2062.0 2005.0 2479.0 2263.0 8184.0 9238.0 30210.0 6942.0 14551.0
## [1693] 11332.0 30967.0 7866.0 2718.0 3084.0 17302.0 12159.0 2797.0 2618.0
## [1702] 1442.0 9735.0 4310.0 11450.0 8906.0 4245.0 21953.0 1614.0 5140.0
## [1711] 31762.0 11692.0 15488.0 2503.0 6269.0 20337.0 3100.0 25008.0 1654.0
## [1720] 4608.0 3908.0 2551.0 8621.0 7451.0 2617.0 12634.0 2672.0 11948.0
## [1729] 2677.0 24703.0 6052.0 2562.0 15377.0 8654.0 16040.0 12423.0 9347.0
## [1738] 3143.0 5106.0 9871.0 1525.0 19630.0 12547.0 17686.0 3257.0 4824.0
## [1747] 8603.0 11498.0 3818.0 16594.0 5387.0 10023.0 9303.0 2218.0 7187.0
## [1756] 2590.0 4255.0 2778.0 10711.0 16163.0 2513.0 3291.0 8917.0 4955.0
## [1765] 2909.0 14015.0 2540.0 3497.0 3682.0 4430.0 3877.0 15124.0 19373.0
## [1774] 21590.0 3657.0 32444.0 5830.0 6463.0 2311.0 3585.0 9131.0 5471.0
## [1783] 8823.0 2173.0 5616.0 8571.0 3924.0 5663.0 7997.0 3652.0 12702.0
## [1792] 7189.0 12421.0 2818.0 2351.0 3119.0 13092.0 3702.0 2701.0 1813.0
## [1801] 2469.0 3091.0 5464.0 2942.0 15279.0 4328.0 5824.0 11281.0 7959.0
## [1810] 4459.0 17162.0 16254.0 3278.0 7173.0 3295.0 25033.0 4232.0 2703.0
## [1819] 2710.0 2322.0 5931.0 3300.0 8682.0 12616.0 9652.0 1651.0 2576.0
## [1828] 2575.0 8705.0 3838.0 10306.0 5366.0 2994.0 4247.0 1737.0 18431.0
## [1837] 5839.0 5137.0 11909.0 21390.0 9264.0 5484.0 4739.0 7970.0 7756.0
## [1846] 5605.0 2946.0 8886.0 19435.0 5246.0 2432.0 3103.0 30746.0 11962.0
## [1855] 14690.0 6629.0 5535.0 3305.0 9466.0 5297.0 4260.0 7291.0 6500.0
## [1864] 1626.0 6662.0 5846.0 8063.0 4597.0 7869.0 17884.0 2046.0 6370.0
## [1873] 2737.0 7266.0 2258.0 6510.0 2508.0 4006.0 16317.0 2109.0 7023.0
## [1882] 8302.0 5184.0 14575.0 3107.0 8322.0 10110.0 2707.0 4397.0 5795.0
## [1891] 9760.0 2246.0 3003.0 2638.0 2004.0 2414.0 2043.0 3111.0 8744.0
## [1900] 4185.0 4759.0 24457.0 14244.0 6572.0 23381.0 15965.0 9433.0 9180.0
## [1909] 8818.0 9031.0 9887.0 4161.0 2740.0 6152.0 8167.0 23742.0 16791.0
## [1918] 26783.0 25516.0 4815.0 23462.0 2252.0 2557.0 2300.0 22938.0 13129.0
## [1927] 3396.0 4712.0 7638.0 2624.0 17934.0 15198.0 3191.0 6053.0 12875.0
## [1936] 2602.0 4698.0 2222.0 8217.0 10091.0 19074.0 12852.0 12763.0 8242.0
## [1945] 1825.0 5497.0 6778.0 4267.0 3273.0 9371.0 8389.0 28410.0 6168.0
## [1954] 3141.0 8307.0 30753.0 5660.0 4230.0 9515.0 10962.0 23848.0 10144.0
## [1963] 2647.0 4580.0 24936.0 26101.0 14270.0 25618.0 11037.0 16763.0 2621.0
## [1972] 4939.0 4419.0 3055.0 19412.0 12786.0 4666.0 4894.0 27389.0 2132.0
## [1981] 6590.0 3176.0 4288.0 20130.0 5945.0 3350.0 5780.0 2497.0 10286.0
## [1990] 23125.0 7081.0 6824.0 12280.0 14607.0 2267.0 2556.0 12512.0 5323.0
## [1999] 9078.0 27029.0 9859.0 3552.0 4613.0 10386.0 2657.0 5031.0 1612.0
## [2008] 2423.0 7140.0 3377.0 2295.0 3150.0 2165.0 4249.0 2966.0 14593.0
## [2017] 8327.0 6479.0 18442.0 3032.0 2151.0 24073.0 25517.0 7709.0 4065.0
## [2026] 13169.0 11811.0 7440.0 12714.0 25882.0 3280.0 11023.0 6182.0 2186.0
## [2035] 17996.0 2306.0 26556.0 5779.0 5494.0 7571.0 4274.0 4980.0 15554.0
## [2044] 26570.0 22224.0 10606.0 5865.0 5369.0 5188.0 17742.0 2591.0 6543.0
## [2053] 26053.0 6316.0 4658.0 6476.0 8087.0 9033.0 3206.0 28751.0 2938.0
## [2062] 5715.0 2791.0 6551.0 4533.0 1854.0 6704.0 5489.0 10619.0 2481.0
## [2071] 5905.0 9293.0 5240.0 4182.0 9857.0 20117.0 6012.0 6369.0 13005.0
## [2080] 1575.0 6679.0 6458.0 20803.0 5540.0 2419.0 5156.0 14228.0 10257.0
## [2089] 32096.0 3014.0 5762.0 2140.0 4760.0 26372.0 8203.0 2655.0 13655.0
## [2098] 12169.0 2598.0 10566.0 8232.0 26365.0 4671.0 14869.0 2629.0 21875.0
## [2107] 3007.0 17404.0 2863.0 13919.0 18672.0 4204.0 16050.0 16766.0 20895.0
## [2116] 7881.0 13427.0 2281.0 10974.0 8925.0 5265.0 17156.0 13457.0 3890.0
## [2125] 17198.0 18951.0 1454.0 27499.0 32964.0 7411.0 7200.0 12007.0 3147.0
## [2134] 5110.0 5438.0 17450.0 18352.0 1585.0 2858.0 16443.0 3687.0 4840.0
## [2143] 15108.0 1909.0 15982.0 2549.0 5967.0 2182.0 2689.0 30622.0 6453.0
## [2152] 3318.0 22075.0 6746.0 4408.0 4838.0 3823.0 21670.0 7928.0 33996.0
## [2161] 2248.0 1901.0 31680.0 1872.0 2055.0 10991.0 3939.0 2127.0 34010.0
## [2170] 6971.0 1741.0 24904.0 11115.0 13241.0 14438.0 5228.0 5550.0 2064.0
## [2179] 3450.0 30030.0 7181.0 27745.0 6735.0 6128.0 23124.0 8874.0 3402.0
## [2188] 1556.0 7372.0 5713.0 2965.0 9819.0 8186.0 3846.0 13131.0 7554.0
## [2197] 25215.0 2606.0 8133.0 3101.0 24446.0 2361.0 2441.0 8532.0 16954.0
## [2206] 6827.0 4513.0 27347.0 1676.0 23870.0 4868.0 20437.0 2239.0 2428.0
## [2215] 15027.0 32056.0 2143.0 23507.0 4277.0 2771.0 2265.0 3075.0 15340.0
## [2224] 7118.0 11419.0 2403.0 2706.0 2226.0 3351.0 5570.0 10448.0 31501.0
## [2233] 21695.0 13650.0 16156.0 2413.0 5920.0 5841.0 8418.0 20640.0 9453.0
## [2242] 7949.0 2758.0 20148.0 26566.0 13477.0 9706.0 7457.0 19081.0 2447.0
## [2251] 28830.0 2563.0 3397.0 1842.0 2383.0 20791.0 19900.0 32024.0 3701.0
## [2260] 4199.0 4353.0 4913.0 5454.0 2845.0 18570.0 25907.0 2206.0 12050.0
## [2269] 2107.0 27175.0 17905.0 4940.0 1835.0 1993.0 7130.0 12539.0 8208.0
## [2278] 26222.0 34173.0 5882.0 7158.0 5833.0 4152.0 11699.0 4505.0 5257.0
## [2287] 10331.0 17557.0 4366.0 8037.0 8740.0 8514.0 3132.0 2010.0 2381.0
## [2296] 16411.0 22127.0 5685.0 7348.0 11188.0 3650.0 5076.0 32658.0 28634.0
## [2305] 3414.0 12315.0 2690.0 12165.0 1792.0 19300.0 8120.0 2292.0 21434.0
## [2314] 3424.0 2787.0 8696.0 32446.0 9133.0 5116.0 18974.0 12101.0 5379.0
## [2323] 32676.0 15202.0 5858.0 2692.0 7165.0 26988.0 2517.0 11091.0 10745.0
## [2332] 2722.0 8228.0 11777.0 14821.0 6131.0 22380.0 12893.0 5093.0 1927.0
## [2341] 22125.0 5260.0 4333.0 6637.0 4396.0 6853.0 2570.0 2166.0 3647.0
## [2350] 11684.0 4475.0 16604.0 5446.0 28700.0 9451.0 13933.0 6130.0 15008.0
## [2359] 4583.0 5268.0 14976.0 2282.0 5130.0 5702.0 14480.0 7570.0 12878.0
## [2368] 26218.0 2804.0 5801.0 2271.0 4465.0 3264.0 26856.0 21756.0 5596.0
## [2377] 15326.0 11373.0 2673.0 16227.0 19110.0 2993.0 11176.0 21416.0 14265.0
## [2386] 16985.0 4341.0 27710.0 13431.0 2645.0 14028.0 5699.0 16284.0 3226.0
## [2395] 2192.0 8318.0 4736.0 9944.0 4717.0 16920.0 3240.0 4704.0 14987.0
## [2404] 3554.0 9227.0 7522.0 2319.0 18531.0 4683.0 7133.0 10253.0 4210.0
## [2413] 12630.0 21084.0 3639.0 31945.0 5894.0 2209.0 23447.0 4180.0 12685.0
## [2422] 21374.0 1911.0 8666.0 5984.0 23000.0 2976.0 16099.0 19595.0 13193.0
## [2431] 5758.0 25873.0 2695.0 20860.0 1892.0 27751.0 24580.0 29893.0 21165.0
## [2440] 9148.0 10979.0 6519.0 14999.0 10332.0 10226.0 26124.0 9816.0 15942.0
## [2449] 12222.0 10227.0 4265.0 13867.0 11239.0 22558.0 23510.0 4549.0 7176.0
## [2458] 18293.0 18332.0 6383.0 13441.0 20114.0 8017.0 8519.0 9474.0 6587.0
## [2467] 7154.0 4039.0 5516.0 5577.0 30137.0 9778.0 20912.0 14699.0 10350.0
## [2476] 11346.0 19711.0 8650.0 9748.0 2454.0 3271.0 13306.0 13637.0 6733.0
## [2485] 2728.0 6250.0 3653.0 22919.0 4198.0 7532.0 4587.0 12250.0 17753.0
## [2494] 12535.0 3541.0 14622.0 23973.0 29200.0 10077.0 8667.0 12871.0 2346.0
## [2503] 9919.0 17087.0 5505.0 1902.0 4254.0 9854.0 7711.0 9977.0 5659.0
## [2512] 17161.0 5018.0 11474.0 7925.0 12793.0 4834.0 12948.0 5662.0 6030.0
## [2521] 6779.0 15248.0 15583.0 25270.0 8717.0 33755.0 7282.0 7260.0 12952.0
## [2530] 5353.0 11741.0 11167.0 20882.0 6617.0 3276.0 10097.0 5776.0 7207.0
## [2539] 2106.0 21158.0 22906.0 2648.0 30702.0 17054.0 3761.0 15845.0 8061.0
## [2548] 19430.0 2708.0 23566.0 9829.0 7226.0 4072.0 21646.0 14046.0 25620.0
## [2557] 21358.0 1856.0 2586.0 7115.0 13220.0 5996.0 9080.0 7563.0 8749.0
## [2566] 14973.0 7108.0 23007.0 24248.0 11617.0 30428.0 6805.0 14257.0 5719.0
## [2575] 9517.0 5317.0 2526.0 2971.0 6834.0 3002.0 16727.0 4573.0 15410.0
## [2584] 3299.0 13453.0 6362.0 2679.0 4369.0 1721.0 2196.0 21144.0 3952.0
## [2593] 17343.0 3498.0 9121.0 20230.0 15422.0 9132.0 8054.0 8739.0 24949.0
## [2602] 3115.0 29695.0 7261.0 1621.0 33472.0 11512.0 12463.0 8511.0 4821.0
## [2611] 8596.0 7223.0 1629.0 7216.0 28397.0 13720.0 7553.0 2952.0 11229.0
## [2620] 7109.0 4511.0 2533.0 2016.0 11068.0 5546.0 7277.0 9426.0 3490.0
## [2629] 2364.0 15704.0 18253.0 3696.0 8748.0 5608.0 3236.0 5195.0 6327.0
## [2638] 4728.0 6276.0 13430.0 2796.0 2457.0 7075.0 12386.0 32210.0 2136.0
## [2647] 10851.0 10698.0 6772.0 10696.0 11851.0 11558.0 9551.0 29923.0 3675.0
## [2656] 9183.0 7924.0 5383.0 21425.0 32866.0 10467.0 12856.0 9721.0 3981.0
## [2665] 7587.0 8012.0 3812.0 21378.0 12873.0 20229.0 16546.0 11191.0 17576.0
## [2674] 10271.0 1647.0 1560.0 1659.0 22487.0 5403.0 5180.0 4915.0 12154.0
## [2683] 3258.0 13349.0 31458.0 10961.0 8904.0 16105.0 16815.0 11538.0 9569.0
## [2692] 3340.0 3654.0 10541.0 1613.0 1922.0 14521.0 1931.0 8513.0 1478.0
## [2701] 2466.0 13602.0 2485.0 14817.0 13824.0 6189.0 22956.0 3943.0 5569.0
## [2710] 2418.0 7966.0 7742.0 2074.0 4948.0 4988.0 28701.0 6607.0 16034.0
## [2719] 24149.0 16903.0 24657.0 5026.0 9352.0 9502.0 22855.0 6602.0 3728.0
## [2728] 2021.0 2255.0 8436.0 8340.0 15104.0 2009.0 31668.0 5735.0 7633.0
## [2737] 23642.0 6698.0 17814.0 7738.0 13114.0 17345.0 8706.0 19272.0 4798.0
## [2746] 12254.0 9549.0 11568.0 6197.0 1791.0 7238.0 4514.0 29812.0 9559.0
## [2755] 8353.0 5455.0 9899.0 15641.0 3504.0 18432.0 2369.0 10882.0 3509.0
## [2764] 14335.0 4005.0 3734.0 6033.0 6245.0 11880.0 9344.0 24126.0 5496.0
## [2773] 12342.0 1928.0 12814.0 5242.0 8808.0 8031.0 9728.0 4748.0 19999.0
## [2782] 6331.0 9662.0 1693.0 5483.0 15186.0 33408.0 9810.0 7084.0 8896.0
## [2791] 30733.0 10177.0 6848.0 17165.0 20274.0 19939.0 9773.0 3668.0 3196.0
## [2800] 7030.0 9410.0 4096.0 7210.0 8026.0 18064.0 6897.0 13991.0 11366.0
## [2809] 23692.0 3476.0 27781.0 10534.0 2721.0 10458.0 12544.0 11464.0 11770.0
## [2818] 10998.0 2757.0 19709.0 6967.0 23424.0 21718.0 1470.0 7936.0 14366.0
## [2827] 9231.0 18679.0 20356.0 6663.0 2424.0 15677.0 1816.0 4950.0 24172.0
## [2836] 9037.0 7616.0 11209.0 9908.0 18737.0 19032.0 5916.0 16277.0 9442.0
## [2845] 2990.0 1527.0 6022.0 26729.0 6102.0 8101.0 4632.0 1996.0 11600.0
## [2854] 8464.0 29003.0 5000.0 14963.0 3855.0 28200.0 2310.0 1960.0 9771.0
## [2863] 6417.0 16037.0 14839.0 8769.0 20968.0 2188.0 30314.0 18799.0 2546.0
## [2872] 10775.0 5816.0 20533.0 9890.0 30820.0 6091.0 9690.0 6797.0 4985.0
## [2881] 2125.0 4012.0 23858.0 6728.0 2527.0 5644.0 2837.0 5941.0 9576.0
## [2890] 15412.0 2663.0 18873.0 5341.0 9904.0 7498.0 32719.0 12590.0 25133.0
## [2899] 17818.0 6006.0 3269.0 28262.0 2169.0 3767.0 8989.0 2838.0 7199.0
## [2908] 8495.0 14164.0 3604.0 1752.0 6649.0 6813.0 18004.0 11242.0 10693.0
## [2917] 3026.0 12836.0 11277.0 12815.0 24016.0 26516.0 2285.0 9617.0 2354.0
## [2926] 11533.0 5042.0 1809.0 8624.0 22917.0 18410.0 10130.0 3099.0 19849.0
## [2935] 3469.0 4092.0 3458.0 3028.0 11884.0 26058.0 2808.0 1874.0 11236.0
## [2944] 6380.0 1645.0 5797.0 21721.0 31756.0 8333.0 2067.0 2214.0 3775.0
## [2953] 4388.0 4100.0 5157.0 15939.0 9216.0 3413.0 20348.0 2440.0 11328.0
## [2962] 3183.0 12945.0 24528.0 15898.0 8516.0 10062.0 9589.0 5826.0 3521.0
## [2971] 8386.0 15449.0 7323.0 8924.0 18965.0 7976.0 3054.0 10620.0 3984.0
## [2980] 7599.0 31954.0 19666.0 6628.0 13049.0 3036.0 16575.0 23391.0 23898.0
## [2989] 4944.0 18026.0 5216.0 7699.0 7232.0 8476.0 25837.0 1536.0 4453.0
## [2998] 4389.0 13429.0 1840.0 17846.0 9013.0 18862.0 7958.0 4854.0 3807.0
## [3007] 2529.0 4097.0 3057.0 1957.0 11252.0 24534.0 33384.0 7582.0 13884.0
## [3016] 6167.0 11545.0 5666.0 4417.0 2991.0 13109.0 5443.0 2628.0 16054.0
## [3025] 3216.0 12295.0 5794.0 1858.0 2593.0 12420.0 2775.0 2886.0 7037.0
## [3034] 7065.0 1896.0 11634.0 13735.0 6899.0 6508.0 5090.0 7015.0 30560.0
## [3043] 4384.0 1511.0 4946.0 32182.0 9595.0 21952.0 5667.0 6366.0 14320.0
## [3052] 5972.0 8771.0 7112.0 7333.0 4207.0 1555.0 6846.0 2071.0 11336.0
## [3061] 15221.0 21359.0 19366.0 2923.0 7853.0 16386.0 11164.0 2960.0 10816.0
## [3070] 2568.0 4539.0 4806.0 2025.0 6249.0 4284.0 1738.0 4527.0 3532.0
## [3079] 4846.0 11392.0 22036.0 2772.0 11117.0 10714.0 5420.0 2652.0 6492.0
## [3088] 3167.0 2431.0 3050.0 2191.0 5677.0 4176.0 2577.0 9261.0 1564.0
## [3097] 12740.0 3778.0 12698.0 26229.0 8346.0 5395.0 1490.0 18274.0 4409.0
## [3106] 7560.0 20783.0 6188.0 27876.0 1924.0 29149.0 3160.0 2331.0 8156.0
## [3115] 8109.0 5853.0 5997.0 10824.0 9300.0 5351.0 2097.0 2266.0 13598.0
## [3124] 1803.0 6292.0 1765.0 4964.0 3741.0 31631.0 7636.0 11096.0 25027.0
## [3133] 27391.0 2704.0 11721.0 15142.0 1936.0 3828.0 4786.0 22143.0 7150.0
## [3142] 25502.0 20178.0 5258.0 1561.0 11550.0 28618.0 6623.0 8136.0 19156.0
## [3151] 7982.0 3120.0 4606.0 9949.0 2892.0 7093.0 3569.0 4663.0 2553.0
## [3160] 2873.0 7840.0 1971.0 6230.0 22243.0 2855.0 8440.0 4186.0 22074.0
## [3169] 17667.0 26548.0 8795.0 3491.0 6060.0 25190.0 13911.0 5652.0 2777.0
## [3178] 2223.0 2916.0 16476.0 9598.0 13626.0 2298.0 9191.0 4181.0 7540.0
## [3187] 1477.0 8916.0 1481.0 8580.0 21163.0 30540.0 7357.0 11879.0 21877.0
## [3196] 7255.0 6394.0 5597.0 32535.0 4391.0 8738.0 1592.0 24593.0 7613.0
## [3205] 26107.0 4287.0 10733.0 5536.0 1469.0 5693.0 4098.0 18358.0 2337.0
## [3214] 2124.0 3968.0 2793.0 13513.0 16351.0 9619.0 19030.0 3179.0 5065.0
## [3223] 10885.0 10817.0 13666.0 7191.0 3222.0 1610.0 3809.0 2388.0 2473.0
## [3232] 13103.0 2465.0 6081.0 21815.0 8264.0 1697.0 3069.0 10309.0 4983.0
## [3241] 1663.0 14782.0 2488.0 1785.0 7897.0 4772.0 12064.0 9065.0 10290.0
## [3250] 3433.0 1773.0 4555.0 30666.0 1891.0 16634.0 7985.0 3304.0 6247.0
## [3259] 3645.0 21329.0 7234.0 2262.0 4187.0 16362.0 2748.0 21585.0 9966.0
## [3268] 27804.0 15626.0 18800.0 4579.0 25824.0 3429.0 15809.0 2493.0 6593.0
## [3277] 1625.0 2121.0 4757.0 8668.0 21869.0 8190.0 1850.0 7066.0 3640.0
## [3286] 5527.0 31625.0 32409.0 9827.0 2623.0 12944.0 6401.0 5506.0 17673.0
## [3295] 2656.0 6118.0 17437.0 1461.0 1965.0 30899.0 8876.0 15535.0 13354.0
## [3304] 26723.0 3949.0 5937.0 18806.0 3512.0 1975.0 9375.0 2806.0 6836.0
## [3313] 8757.0 10529.0 2883.0 5225.0 2582.0 11524.0 13039.0 1456.0 5612.0
## [3322] 4205.0 3515.0 26174.0 1602.0 29939.0 5298.0 2433.0 9758.0 24931.0
## [3331] 8854.0 2230.0 28327.0 2500.0 9246.0 11155.0 11926.0 5501.0 2110.0
## [3340] 12994.0 29551.0 5054.0 6109.0 3989.0 3315.0 1794.0 5993.0 8320.0
## [3349] 1930.0 2329.0 18128.0 10642.0 6946.0 9716.0 4377.0 2516.0 1844.0
## [3358] 13233.0 1593.0 8589.0 1714.0 21148.0 7487.0 7608.0 2184.0 3495.0
## [3367] 8018.0 20543.0 18819.0 17811.0 14418.0 3936.0 1513.0 18075.0 5989.0
## [3376] 2659.0 13490.0 1664.0 16026.0 2705.0 2884.0 24299.0 20755.0 21096.0
## [3385] 6457.0 1603.0 9051.0 10057.0 2348.0 2017.0 13613.0 5553.0 6346.0
## [3394] 15133.0 2502.0 2589.0 2049.0 3560.0 25937.0 2387.0 2912.0 7062.0
## [3403] 12186.0 3570.0 3072.0 5928.0 8482.0 23911.0 33913.0 1637.0 5448.0
## [3412] 5152.0 15195.0 1817.0 3443.0 4281.0 28186.0 11494.0 28142.0 2316.0
## [3421] 10533.0 14322.0 6798.0 2445.0 1781.0 2270.0 3292.0 10797.0 30501.0
## [3430] 5371.0 9137.0 10614.0 4035.0 21114.0 2522.0 11309.0 13883.0 13448.0
## [3439] 25991.0 2537.0 13019.0 3339.0 28390.0 23665.0 1624.0 8900.0 5239.0
## [3448] 9351.0 3173.0 6243.0 6730.0 1746.0 4141.0 2363.0 28829.0 1994.0
## [3457] 9727.0 33771.0 10452.0 4707.0 8258.0 8892.0 3841.0 1920.0 7802.0
## [3466] 1822.0 9294.0 15069.0 4650.0 10007.0 3095.0 3607.0 1954.0 21317.0
## [3475] 19402.0 1845.0 4710.0 24287.0 1694.0 1457.0 25045.0 10859.0 16928.0
## [3484] 4297.0 2734.0 27374.0 9110.0 2667.0 3062.0 3114.0 14948.0 1749.0
## [3493] 2534.0 13284.0 4830.0 5911.0 11012.0 19188.0 18056.0 3201.0 3144.0
## [3502] 9782.0 4738.0 1938.0 3781.0 2211.0 20631.0 1507.0 11097.0 8162.0
## [3511] 18721.0 1736.0 6611.0 7942.0 13382.0 18550.0 1696.0 3056.0 3331.0
## [3520] 4123.0 2238.0 3875.0 2760.0 9086.0 21142.0 1713.0 6548.0 1953.0
## [3529] 3051.0 25256.0 1630.0 10800.0 1876.0 4963.0 16739.0 4743.0 9382.0
## [3538] 2059.0 20410.0 6472.0 2766.0 3283.0 2470.0 20695.0 4228.0 31743.0
## [3547] 5884.0 1724.0 1912.0 18927.0 1986.0 2877.0 2312.0 3510.0 15026.0
## [3556] 27186.0 29535.0 8148.0 2646.0 2054.0 1879.0 15913.0 8685.0 2676.0
## [3565] 1711.0 2572.0 4535.0 5950.0 2088.0 10466.0 4761.0 1488.0 19114.0
## [3574] 7536.0 13189.0 1914.0 1679.0 7119.0 7459.0 2294.0 5129.0 1722.0
## [3583] 8708.0 8869.0 10543.0 17764.0 6371.0 3076.0 4139.0 4121.0 3394.0
## [3592] 17628.0 4480.0 3370.0 3112.0 1551.0 1682.0 6743.0 32838.0 2510.0
## [3601] 3199.0 1918.0 18660.0 7591.0 18038.0 1853.0 4951.0 1757.0 24033.0
## [3610] 3614.0 1943.0 3795.0 3001.0 5726.0 14914.0 1580.0 15483.0 1916.0
## [3619] 1667.0 2231.0 6465.0 8599.0 5444.0 25293.0 1748.0 4034.0 26129.0
## [3628] 14902.0 12228.0 16665.0 20974.0 3139.0 19865.0 2069.0 33371.0 5370.0
## [3637] 22437.0 3573.0 1959.0 1661.0 5363.0 3009.0 18535.0 2376.0 2882.0
## [3646] 3277.0 3301.0 12391.0 2168.0 7762.0 12587.0 14785.0 2425.0 11619.0
## [3655] 2035.0 8842.0 13921.0 2761.0 3232.0 19075.0 31978.0 6225.0 10360.0
## [3664] 3135.0 3189.0 8963.0 1723.0 2161.0 3901.0 1895.0 26496.0 1583.0
## [3673] 13608.0 10273.0 8431.0 5852.0 12914.0 8694.0 1735.0 2286.0 3589.0
## [3682] 9437.0 11557.0 14831.0 1495.0 9703.0 3889.0 14140.0 2694.0 19629.0
## [3691] 6507.0 10195.0 11314.0 1837.0 7821.0 1984.0 1970.0 4476.0 1699.0
## [3700] 3698.0 2712.0 5486.0 18096.0 16741.0 6936.0 11099.0 4406.0 5104.0
## [3709] 7195.0 1956.0 3317.0 5095.0 10111.0 5987.0 5630.0 6622.0 18733.0
## [3718] 2907.0 8791.0 2302.0 2670.0 21382.0 2254.0 4433.0 2520.0 3961.0
## [3727] 2476.0 11606.0 8459.0 9554.0 19826.0 2545.0 3164.0 1804.0 22664.0
## [3736] 3547.0 29715.0 2179.0 4906.0 1880.0 12155.0 6160.0 28422.0 1671.0
## [3745] 11422.0 5139.0 4783.0 4502.0 33521.0 4361.0 7026.0 16388.0 2905.0
## [3754] 5649.0 14345.0 6524.0 2633.0 7693.0 10262.0 11320.0 2482.0 26308.0
## [3763] 6721.0 5842.0 8777.0 15060.0 2126.0 4907.0 3553.0 4428.0 6723.0
## [3772] 2756.0 34198.0 2817.0 2573.0 5869.0 4586.0 1790.0 5862.0 15594.0
## [3781] 11410.0 1584.0 13298.0 2114.0 1762.0 2245.0 8168.0 3881.0 20485.0
## [3790] 9856.0 32244.0 5624.0 1656.0 15699.0 6608.0 1547.0 11060.0 3670.0
## [3799] 1538.0 2330.0 2120.0 5583.0 7764.0 25670.0 5791.0 2865.0 6467.0
## [3808] 1468.0 5386.0 5402.0 2983.0 4871.0 2313.0 2434.0 14544.0 24621.0
## [3817] 33122.0 2709.0 4499.0 4697.0 3110.0 1734.0 3562.0 19198.0 4540.0
## [3826] 1990.0 5096.0 3015.0 3786.0 12078.0 6448.0 5398.0 2620.0 13435.0
## [3835] 7098.0 3086.0 1520.0 4043.0 16541.0 7486.0 8365.0 7789.0 6626.0
## [3844] 5547.0 14527.0 8185.0 6340.0 5711.0 2086.0 3256.0 14854.0 7184.0
## [3853] 6541.0 12663.0 5056.0 30928.0 1669.0 9725.0 21696.0 2992.0 9673.0
## [3862] 3609.0 6423.0 14899.0 3224.0 4135.0 8376.0 25944.0 8701.0 5600.0
## [3871] 2687.0 4464.0 1529.0 6274.0 2134.0 17158.0 3359.0 11997.0 3302.0
## [3880] 2860.0 13387.0 10873.0 7596.0 2921.0 10136.0 30997.0 2611.0 3328.0
## [3889] 26142.0 12405.0 17655.0 4941.0 1644.0 13906.0 10588.0 4045.0 5845.0
## [3898] 15341.0 4602.0 9383.0 2847.0 15638.0 10700.0 7939.0 2850.0 8973.0
## [3907] 6960.0 4167.0 5099.0 2782.0 1480.0 5070.0 5774.0 6054.0 19090.0
## [3916] 4473.0 3245.0 14728.0 11272.0 12270.0 7901.0 5983.0 7362.0 12972.0
## [3925] 17785.0 3029.0 9097.0 3802.0 2954.0 11882.0 5632.0 11025.0 30357.0
## [3934] 5182.0 3783.0 1515.0 2341.0 13287.0 1639.0 5668.0 24542.0 1838.0
## [3943] 3927.0 4345.0 2422.0 1440.0 26108.0 3646.0 8729.0 4073.0 9916.0
## [3952] 6452.0 1952.0 2610.0 2415.0 2918.0 3666.0 2809.0 26303.0 25060.0
## [3961] 1545.0 1451.0 16424.0 1926.0 1848.0 1634.0 5481.0 2129.0 9026.0
## [3970] 1761.0 3316.0 13364.0 28292.0 2933.0 21630.0 4173.0 12229.0 2272.0
## [3979] 6953.0 2765.0 6904.0 7531.0 8644.0 1531.0 10241.0 4542.0 3372.0
## [3988] 5299.0 2138.0 29100.0 13509.0 2396.0 18964.0 1623.0 2579.0 5045.0
## [3997] 2089.0 2866.0 9738.0 4370.0 3355.0 2325.0 3871.0 3983.0 15490.0
## [4006] 2314.0 4212.0 6248.0 2430.0 5543.0 3255.0 1691.0 18229.0 4202.0
## [4015] 5245.0 2583.0 7464.0 4928.0 9863.0 1452.0 1546.0 2013.0 2819.0
## [4024] 1702.0 3272.0 6145.0 1657.0 4554.0 5119.0 10600.0 20769.0 7116.0
## [4033] 2082.0 5626.0 2920.0 6526.0 1793.0 2427.0 3011.0 7492.0 3632.0
## [4042] 1744.0 9654.0 1605.0 10573.0 1789.0 7595.0 2382.0 22294.0 2574.0
## [4051] 5441.0 4467.0 5033.0 8604.0 9705.0 1554.0 1786.0 2477.0 7336.0
## [4060] 9396.0 4020.0 25856.0 7398.0 4058.0 3042.0 2688.0 3388.0 4902.0
## [4069] 3241.0 5069.0 13625.0 8766.0 9005.0 2713.0 18284.0 7215.0 21800.0
## [4078] 1485.0 2505.0 2631.0 3307.0 29638.0 1859.0 13362.0 6034.0 2194.0
## [4087] 2922.0 6943.0 4248.0 2392.0 3474.0 8737.0 13397.0 6352.0 1787.0
## [4096] 18734.0 3525.0 2051.0 27378.0 7862.0 21805.0 1698.0 15631.0 15011.0
## [4105] 10721.0 6125.0 3200.0 12286.0 21543.0 6355.0 2836.0 14951.0 1591.0
## [4114] 8930.0 4685.0 3390.0 17412.0 11186.0 2716.0 2874.0 18776.0 19793.0
## [4123] 12362.0 4143.0 2197.0 9314.0 3719.0 6996.0 7306.0 13199.0 2491.0
## [4132] 1977.0 1806.0 3188.0 2288.0 1780.0 2373.0 23250.0 12882.0 6348.0
## [4141] 1843.0 2303.0 29195.0 28253.0 1882.0 2395.0 3845.0 1506.0 11778.0
## [4150] 2747.0 3068.0 3426.0 12906.0 7904.0 11502.0 16199.0 13590.0 1695.0
## [4159] 1522.0 16509.0 7316.0 7627.0 9465.0 12283.0 2715.0 19897.0 24250.0
## [4168] 1964.0 1904.0 18202.0 2291.0 3375.0 8856.0 2980.0 17656.0 2475.0
## [4177] 3942.0 1771.0 17678.0 20958.0 4117.0 18524.0 4090.0 14958.0 21961.0
## [4186] 11629.0 4142.0 2202.0 3591.0 4781.0 3832.0 9025.0 11627.0 5686.0
## [4195] 4976.0 13951.0 14370.0 21681.0 2634.0 2204.0 1502.0 4478.0 7359.0
## [4204] 13090.0 5678.0 3964.0 4692.0 5821.0 2357.0 8294.0 1852.0 3503.0
## [4213] 17835.0 3383.0 3815.0 2144.0 16612.0 2560.0 2057.0 1972.0 6223.0
## [4222] 7632.0 1836.0 9397.0 1601.0 2543.0 3462.0 13095.0 5396.0 1899.0
## [4231] 7564.0 13116.0 3716.0 2006.0 2948.0 4669.0 13994.0 8760.0 1688.0
## [4240] 9881.0 4534.0 3545.0 3334.0 2496.0 9357.0 1783.0 10580.0 3279.0
## [4249] 4068.0 2128.0 1878.0 9909.0 1665.0 14111.0 2012.0 5714.0 5071.0
## [4258] 24028.0 9124.0 8051.0 3635.0 2028.0 4304.0 6644.0 7607.0 2060.0
## [4267] 6885.0 1871.0 1867.0 4640.0 3853.0 14409.0 2639.0 2338.0 4283.0
## [4276] 6263.0 2225.0 1519.0 5495.0 2141.0 2616.0 6606.0 13812.0 12310.0
## [4285] 1622.0 12559.0 7927.0 1720.0 6143.0 3899.0 11964.0 3862.0 33142.0
## [4294] 3523.0 4462.0 3976.0 2719.0 3369.0 1690.0 8583.0 2996.0 6966.0
## [4303] 11316.0 11362.0 7790.0 2023.0 9117.0 8787.0 27436.0 2195.0 4575.0
## [4312] 4860.0 24512.0 21430.0 2558.0 10061.0 2815.0 6185.0 9234.0 2749.0
## [4321] 1980.0 6931.0 4235.0 6501.0 6376.0 5576.0 12917.0 13324.0 11154.0
## [4330] 9535.0 2904.0 1770.0 1534.0 2170.0 10001.0 4169.0 2566.0 6812.0
## [4339] 4332.0 11761.0 4776.0 2697.0 3542.0 3492.0 2977.0 30976.0 2810.0
## [4348] 8997.0 4998.0 3892.0 2345.0 2135.0 2528.0 19719.0 15292.0 31733.0
## [4357] 2547.0 5708.0 19838.0 2284.0 11535.0 3524.0 30186.0 1620.0 4038.0
## [4366] 2078.0 1571.0 4604.0 4312.0 1462.0 4163.0 7201.0 1883.0 3308.0
## [4375] 2022.0 8597.0 4693.0 3400.0 8241.0 2901.0 9759.0 2525.0 19262.0
## [4384] 7077.0 8169.0 1966.0 13439.0 1636.0 1449.0 4120.0 2289.0 3511.0
## [4393] 2426.0 12230.0 7328.0 16207.0 15468.0 4009.0 3411.0 15525.0 2118.0
## [4402] 2275.0 4642.0 3743.0 4130.0 10960.0 3900.0 6236.0 1615.0 8332.0
## [4411] 11536.0 11905.0 3052.0 1978.0 2876.0 9505.0 1576.0 5647.0 1766.0
## [4420] 2896.0 13840.0 4862.0 22651.0 12935.0 1516.0 1820.0 10190.0 1833.0
## [4429] 4490.0 11062.0 1574.0 2368.0 1937.0 7135.0 5190.0 6059.0 1572.0
## [4438] 28600.0 3455.0 18123.0 1518.0 2723.0 1776.0 1968.0 2180.0 12114.0
## [4447] 4959.0 10374.0 1486.0 2542.0 4943.0 1760.0 1670.0 6018.0 2755.0
## [4456] 8783.0 1861.0 13709.0 17285.0 3210.0 1755.0 14485.0 6043.0 17239.0
## [4465] 7951.0 14201.0 1849.0 4972.0 13565.0 6332.0 6062.0 13407.0 2030.0
## [4474] 3146.0 5302.0 3185.0 9090.0 2792.0 12890.0 6854.0 5293.0 14670.0
## [4483] 4375.0 3448.0 3123.0 15713.0 4115.0 6925.0 1898.0 22639.0 2452.0
## [4492] 9924.0 2308.0 1655.0 2768.0 25658.0 4410.0 3468.0 6968.0 32733.0
## [4501] 8315.0 2020.0 5261.0 3680.0 4311.0 8438.0 3595.0 2315.0 3427.0
## [4510] 5573.0 18008.0 13483.0 4349.0 11698.0 1503.0 9094.0 15100.0 9030.0
## [4519] 1543.0 1877.0 9577.0 5427.0 5913.0 2867.0 3137.0 3913.0 4953.0
## [4528] 5724.0 1886.0 2024.0 2299.0 2137.0 12219.0 2343.0 19724.0 4386.0
## [4537] 2411.0 6397.0 23958.0 10033.0 1641.0 11596.0 5162.0 16312.0 25276.0
## [4546] 1939.0 2788.0 10317.0 2397.0 6169.0 2811.0 7501.0 2856.0 29898.0
## [4555] 2812.0 10031.0 2669.0 1951.0 1528.0 8406.0 2242.0 6538.0 13032.0
## [4564] 5013.0 3466.0 1689.0 2429.0 17523.0 9257.0 1731.0 16929.0 3606.0
## [4573] 23512.0 1855.0 13546.0 2552.0 18379.0 3499.0 18295.0 1568.0 2177.0
## [4582] 2296.0 9220.0 23128.0 14897.0 1798.0 14304.0 15370.0 6318.0 9852.0
## [4591] 1579.0 4541.0 1674.0 32611.0 3027.0 10931.0 1573.0 2626.0 13376.0
## [4600] 31636.0 3453.0 11434.0 2790.0 14314.0 1889.0 2875.0 1763.0 3288.0
## [4609] 4382.0 3159.0 5393.0 12618.0 6049.0 13816.0 6400.0 3347.0 1514.0
## [4618] 2504.0 1633.0 5466.0 21328.0 3534.0 11238.0 1460.0 4225.0 2344.0
## [4627] 7270.0 2835.0 1540.0 5084.0 23925.0 6720.0 15569.0 1565.0 5947.0
## [4636] 18821.0 2153.0 1684.0 12398.0 4461.0 2597.0 9733.0 2261.0 8793.0
## [4645] 5843.0 3322.0 2036.0 1884.0 3747.0 16002.0 5222.0 1533.0 5763.0
## [4654] 2814.0 2903.0 4543.0 17506.0 5956.0 4177.0 3059.0 3208.0 7534.0
## [4663] 14044.0 5005.0 3033.0 5204.0 2213.0 3546.0 2989.0 13587.0 32431.0
## [4672] 2207.0 6475.0 2142.0 3382.0 8961.0 4223.0 1666.0 4565.0 9817.0
## [4681] 4970.0 4373.0 12073.0 6451.0 1897.0 3231.0 1577.0 3061.0 3024.0
## [4690] 1998.0 11881.0 2968.0 13984.0 5856.0 7182.0 5844.0 3940.0 5784.0
## [4699] 8632.0 9874.0 1873.0 2754.0 3979.0 28229.0 12084.0 2762.0 3934.0
## [4708] 9139.0 10351.0 6811.0 2040.0 8404.0 4354.0 9974.0 4316.0 3116.0
## [4717] 24868.0 17706.0 1819.0 19350.0 12045.0 10587.0 2596.0 3008.0 5528.0
## [4726] 7381.0 11354.0 23034.0 4752.0 6114.0 18232.0 3868.0 3808.0 1750.0
## [4735] 2385.0 1811.0 34058.0 16290.0 3745.0 26690.0 14566.0 2353.0 23542.0
## [4744] 9272.0 1967.0 5068.0 7499.0 8700.0 14266.0 2957.0 9918.0 8159.0
## [4753] 18551.0 10886.0 10457.0 4960.0 4601.0 2741.0 23209.0 12610.0 2090.0
## [4762] 2269.0 4036.0 5342.0 5640.0 3349.0 1504.0 2018.0 2105.0 20080.0
## [4771] 1530.0 2915.0 11742.0 1814.0 1446.0 4244.0 2984.0 2471.0 27437.0
## [4780] 4166.0 13100.0 4432.0 4975.0 3489.0 14858.0 2241.0 2581.0 14713.0
## [4789] 2366.0 1681.0 4696.0 4682.0 11670.0 1596.0 1590.0 4994.0 16406.0
## [4798] 9109.0 2632.0 2776.0 8529.0 1604.0 4263.0 1521.0 5284.0 5590.0
## [4807] 7645.0 1745.0 3376.0 7298.0 8383.0 3600.0 4595.0 2795.0 1768.0
## [4816] 2887.0 10879.0 1562.0 5295.0 4708.0 2384.0 11249.0 2932.0 1484.0
## [4825] 1678.0 12373.0 20789.0 3911.0 4848.0 19099.0 22981.0 22067.0 8958.0
## [4834] 25219.0 3361.0 2725.0 10039.0 2467.0 2045.0 4170.0 5422.0 2015.0
## [4843] 2048.0 2152.0 3858.0 11651.0 9449.0 3423.0 11486.0 1653.0 1824.0
## [4852] 9248.0 17627.0 5357.0 1706.0 19360.0 3844.0 2851.0 2951.0 22863.0
## [4861] 1784.0 8919.0 2164.0 4788.0 1532.0 3659.0 3811.0 7106.0 2784.0
## [4870] 1866.0 7514.0 4938.0 19940.0 12366.0 1708.0 2123.0 5633.0 4556.0
## [4879] 1537.0 2080.0 7565.0 8446.0 13908.0 19220.0 9186.0 6673.0 1662.0
## [4888] 3879.0 11794.0 7603.0 2654.0 3611.0 7421.0 12268.0 9873.0 2160.0
## [4897] 1834.0 13001.0 2146.0 4269.0 4195.0 1832.0 4847.0 7507.0 5232.0
## [4906] 1828.0 10834.0 2099.0 11438.0 4703.0 5254.0 1788.0 7508.0 3333.0
## [4915] 13745.0 5021.0 9641.0 12621.0 6074.0 4995.0 4617.0 8220.0 5716.0
## [4924] 1635.0 4259.0 10762.0 4651.0 4576.0 2911.0 2257.0 18457.0 7382.0
## [4933] 3861.0 10009.0 8243.0 11946.0 4025.0 3649.0 5562.0 13733.0 2374.0
## [4942] 3319.0 3021.0 29219.0 4431.0 6384.0 24462.0 1474.0 9880.0 21839.0
## [4951] 1991.0 29795.0 2131.0 2605.0 5169.0 4694.0 6039.0 5256.0 20401.0
## [4960] 3296.0 8956.0 2671.0 2208.0 4196.0 12581.0 17890.0 3192.0 3293.0
## [4969] 7268.0 12725.0 2371.0 7751.0 2401.0 4661.0 8494.0 3926.0 2864.0
## [4978] 4607.0 1476.0 4778.0 16239.0 11726.0 17827.0 1701.0 3998.0 33211.0
## [4987] 1863.0 2691.0 15471.0 4222.0 6614.0 4836.0 12675.0 2813.0 3223.0
## [4996] 2653.0 2745.0 1870.0 8064.0 10016.0 4523.0 6083.0 5813.0 1588.0
## [5005] 3749.0 1796.0 1489.0 8953.0 5999.0 3617.0 3219.0 19782.0 11561.0
## [5014] 8477.0 8671.0 7773.0 8075.0 7932.0 1753.0 5814.0 1989.0 9560.0
## [5023] 5275.0 3758.0 10946.0 3108.0 3202.0 1472.0 10024.0 8840.0 4468.0
## [5032] 17268.0 1649.0 1609.0 6973.0 17228.0 2321.0 3157.0 5523.0 7317.0
## [5041] 5218.0 11114.0 10648.0 10761.0 3897.0 4721.0 2831.0 1508.0 21350.0
## [5050] 10431.0 9430.0 11671.0 11367.0 4416.0 1715.0 2604.0 4978.0 4047.0
## [5059] 5384.0 5141.0 3977.0 1751.0 7434.0 6959.0 2979.0 2391.0 7264.0
## [5068] 4348.0 4162.0 9749.0 4916.0 8279.0 7562.0 4662.0 10503.0 5557.0
## [5077] 1728.0 11750.0 10486.0 13679.0 1921.0 1732.0 5037.0 8314.0 20929.0
## [5086] 1754.0 4209.0 2449.0 4618.0 3618.0 3437.0 3481.0 3019.0 4688.0
## [5095] 1812.0 13623.0 3731.0 2446.0 1821.0 1517.0 19138.0 16835.0 5549.0
## [5104] 4654.0 9114.0 3043.0 4621.0 1740.0 7744.0 9389.0 9317.0 7452.0
## [5113] 1946.0 1471.0 3709.0 10214.0 8111.0 10730.0 1567.0 7278.0 3190.0
## [5122] 3081.0 3793.0 1779.0 21680.0 3918.0 12764.0 3287.0 3891.0 3559.0
## [5131] 2843.0 4325.0 2881.0 4095.0 10417.0 1483.0 5087.0 3819.0 8074.0
## [5140] 8688.0 15109.0 22304.0 1893.0 3790.0 6392.0 9989.0 2559.0 4022.0
## [5149] 1632.0 2085.0 3803.0 3165.0 4628.0 3306.0 8480.0 4637.0 3420.0
## [5158] 4445.0 5721.0 2328.0 3883.0 3229.0 3080.0 4517.0 4762.0 4802.0
## [5167] 2268.0 8204.0 1827.0 8086.0 11287.0 3430.0 6314.0 2181.0 4754.0
## [5176] 11247.0 16258.0 9091.0 1552.0 3472.0 10973.0 25645.0 4257.0 4977.0
## [5185] 7114.0 10972.0 3439.0 3005.0 5051.0 10254.0 28673.0 25410.0 8566.0
## [5194] 2816.0 2350.0 2625.0 3959.0 6941.0 1466.0 17999.0 4553.0 2953.0
## [5203] 4363.0 1894.0 1983.0 7879.0 1915.0 4878.0 4718.0 3683.0 13478.0
## [5212] 2841.0 2360.0 3717.0 5338.0 2276.0 4091.0 3798.0 1778.0 10880.0
## [5221] 20749.0 7600.0 5578.0 1933.0 27169.0 2367.0 5642.0 3239.0 8103.0
## [5230] 5492.0 2444.0 9017.0 32777.0 23486.0 1997.0 3379.0 16553.0 2830.0
## [5239] 24987.0 3705.0 1675.0 1439.0 4440.0 6618.0 4436.0 13138.0 6272.0
## [5248] 9906.0 9525.0 3168.0 2724.0 4629.0 1558.0 13093.0 4451.0 6426.0
## [5257] 3367.0 4154.0 1774.0 1492.0 1550.0 3311.0 2233.0 32106.0 4057.0
## [5266] 17096.0 6568.0 7884.0 4146.0 7293.0 3829.0 16747.0 4790.0 13670.0
## [5275] 12287.0 24431.0 6615.0 1979.0 4262.0 5431.0 7299.0 7551.0 9076.0
## [5284] 10699.0 7212.0 3089.0 11250.0 2456.0 11773.0 4060.0 12967.0 2326.0
## [5293] 4376.0 12745.0 2969.0 5400.0 1719.0 4883.0 3626.0 3335.0 1727.0
## [5302] 19349.0 13409.0 6330.0 3391.0 14324.0 1839.0 1685.0 4850.0 2840.0
## [5311] 1961.0 2832.0 11409.0 8827.0 24256.0 5594.0 3505.0 1905.0 6146.0
## [5320] 13426.0 9104.0 30300.0 7088.0 6763.0 24379.0 13172.0 5027.0 7584.0
## [5329] 28930.0 3485.0 23459.0 18177.0 7839.0 6078.0 21322.0 15618.0 34496.0
## [5338] 4765.0 16583.0 6153.0 11000.0 14344.0 20304.0 8283.0 11318.0 11919.0
## [5347] 12294.0 7253.0 21922.0 13452.0 24735.0 4942.0 29690.0 6751.0 9484.0
## [5356] 25178.0 18224.0 4813.0 24965.0 12569.0 8259.0 13804.0 5700.0 5479.0
## [5365] 5807.0 3605.0 17077.0 5380.0 27720.0 18341.0 27712.0 8285.0 19704.0
## [5374] 21325.0 7045.0 14388.0 3874.0 7484.0 18336.0 10682.0 8587.0 6228.0
## [5383] 7537.0 13609.0 7350.0 18956.0 13445.0 8979.0 6674.0 13165.0 9243.0
## [5392] 4737.0 8798.0 24670.0 23453.0 6139.0 14800.0 9815.0 12265.0 19000.0
## [5401] 13197.0 22599.0 23457.0 31560.0 29572.0 2844.0 9678.0 26882.0 15034.0
## [5410] 12214.0 23070.0 2167.0 6895.0 25894.0 3138.0 12055.0 16592.0 33184.0
## [5419] 10753.0 20001.0 8786.0 7142.0 4477.0 23402.0 6565.0 6982.0 5128.0
## [5428] 9405.0 14646.0 12578.0 6058.0 8561.0 5625.0 2274.0 9422.0 3849.0
## [5437] 5168.0 21046.0 6540.0 8141.0 33441.0 3794.0 5785.0 19387.0 4086.0
## [5446] 31987.0 9043.0 11128.0 22054.0 2199.0 7566.0 11343.0 15155.0 10795.0
## [5455] 6633.0 8572.0 14895.0 9511.0 10896.0 8401.0 12406.0 6769.0 32292.0
## [5464] 4557.0 10949.0 10398.0 22361.0 10877.0 11552.0 11901.0 2273.0 3082.0
## [5473] 9298.0 4136.0 12399.0 15030.0 6441.0 4174.0 23223.0 6954.0 7136.0
## [5482] 6636.0 31497.0 7801.0 6455.0 2879.0 6713.0 10984.0 23058.0 17606.0
## [5491] 18000.0 5800.0 10874.0 13769.0 17894.0 15016.0 12813.0 4660.0 13174.0
## [5500] 11210.0 31639.0 26438.0 7504.0 15048.0 11548.0 8767.0 5306.0 3608.0
## [5509] 31782.0 19107.0 21751.0 7926.0 27984.0 24499.0 27318.0 9766.0 26692.0
## [5518] 33256.0 17698.0 6482.0 18975.0 8230.0 22226.0 28852.0 6893.0 7653.0
## [5527] 26840.0 16828.0 6530.0 11642.0 5390.0 8390.0 3442.0 6680.0 7244.0
## [5536] 8758.0 13432.0 10830.0 20633.0 9070.0 11954.0 4479.0 2599.0 10901.0
## [5545] 8325.0 7196.0 32926.0 18072.0 24533.0 4874.0 12889.0 30117.0 5131.0
## [5554] 24262.0 7385.0 20708.0 17072.0 25737.0 16950.0 15043.0 29338.0 25808.0
## [5563] 8861.0 15365.0 2913.0 11508.0 18991.0 10908.0 14627.0 2219.0 25736.0
## [5572] 2849.0 29227.0 12458.0 7547.0 10677.0 6329.0 28307.0 7650.0 6443.0
## [5581] 13356.0 30172.0 11814.0 28687.0 25653.0 4705.0 19150.0 11765.0 16627.0
## [5590] 13553.0 11476.0 23026.0 18477.0 29890.0 8290.0 3723.0 12695.0 30379.0
## [5599] 9875.0 12218.0 21754.0 12094.0 17812.0 13743.0 15785.0 11714.0 11135.0
## [5608] 13259.0 23355.0 20734.0 14630.0 6080.0 28605.0 10850.0 24244.0 17218.0
## [5617] 14746.0 34458.0 9369.0 22741.0 17277.0 33565.0 20176.0 2519.0 13067.0
## [5626] 11529.0 6616.0 11467.0 15821.0 15795.0 3109.0 8110.0 2236.0 3711.0
## [5635] 18980.0 15472.0 21498.0 4291.0 12773.0 9594.0 19281.0 14806.0 7473.0
## [5644] 27742.0 14563.0 7791.0 3733.0 14416.0 12033.0 3243.0 9761.0 9947.0
## [5653] 3599.0 12648.0 4572.0 4021.0 25601.0 25428.0 4216.0 21161.0 9074.0
## [5662] 24927.0 6157.0 33889.0 33552.0 19594.0 14803.0 3536.0 19333.0 11605.0
## [5671] 5975.0 19141.0 3461.0 29394.0 16191.0 4023.0 33711.0 31699.0 8858.0
## [5680] 7064.0 15487.0 33870.0 23760.0 29239.0 4598.0 3435.0 17540.0 31346.0
## [5689] 4342.0 3842.0 9682.0 7664.0 30498.0 19962.0 21398.0 4746.0 20434.0
## [5698] 29531.0 10688.0 22725.0 8155.0 18266.0 10492.0 19055.0 3973.0 4318.0
## [5707] 7660.0 13313.0 8284.0 3768.0 14382.0 10798.0 22729.0 27670.0 33874.0
## [5716] 3175.0 7979.0 14767.0 3592.0 4819.0 16433.0 12174.0 9230.0 6867.0
## [5725] 18046.0 7680.0 7825.0 5002.0 4755.0 22104.0 29038.0 4620.0 11463.0
## [5734] 19252.0 4822.0 12100.0 20466.0 17887.0 23399.0 13026.0 15698.0 17575.0
## [5743] 29528.0 12494.0 13411.0 17646.0 11121.0 4109.0 6176.0 4512.0 32791.0
## [5752] 10602.0 7953.0 9092.0 5541.0 7204.0 4548.0 3860.0 14581.0 12375.0
## [5761] 19534.0 22993.0 15164.0 9215.0 25438.0 3759.0 12207.0 32089.0 7139.0
## [5770] 3669.0 5859.0 32417.0 27945.0 12338.0 16703.0 16667.0 18512.0 14131.0
## [5779] 3629.0 13312.0 15223.0 5287.0 9060.0 4731.0 29738.0 3944.0 6577.0
## [5788] 8670.0 32554.0 8331.0 15524.0 3275.0 18349.0 4015.0 9719.0 4178.0
## [5797] 29856.0 11522.0 14774.0 5118.0 14682.0 28612.0 24134.0 27929.0 8257.0
## [5806] 23051.0 3755.0 7539.0 11808.0 15504.0 12091.0 13818.0 4442.0 5282.0
## [5815] 10353.0 6280.0 13694.0 8940.0 6546.0 32587.0 9463.0 12552.0 21679.0
## [5824] 10531.0 4905.0 10017.0 31832.0 34427.0 4779.0 3882.0 6121.0 3535.0
## [5833] 9178.0 9634.0 19033.0 5508.0 5871.0 15219.0 8147.0 9711.0 11358.0
## [5842] 6765.0 4725.0 3699.0 8506.0 21714.0 3371.0 9546.0 3848.0 9199.0
## [5851] 13381.0 15101.0 3603.0 4132.0 6882.0 17978.0 3821.0 3787.0 4623.0
## [5860] 17328.0 23889.0 3999.0 11782.0 3220.0 9742.0 26819.0 9580.0 7940.0
## [5869] 14072.0 15928.0 20798.0 9752.0 24844.0 3090.0 9943.0 3384.0 10186.0
## [5878] 16983.0 4268.0 10748.0 31718.0 11898.0 13056.0 14002.0 5500.0 8549.0
## [5887] 4390.0 24884.0 4841.0 4246.0 29974.0 20724.0 21079.0 3720.0 11077.0
## [5896] 12024.0 4446.0 11511.0 19192.0 17542.0 32949.0 32250.0 4251.0 23714.0
## [5905] 3744.0 8449.0 4192.0 14217.0 17350.0 13784.0 5073.0 4074.0 10284.0
## [5914] 11900.0 9701.0 6075.0 13035.0 17306.0 5319.0 15894.0 5855.0 13062.0
## [5923] 7428.0 8848.0 4380.0 12510.0 23712.0 3784.0 9680.0 8065.0 20501.0
## [5932] 23260.0 9073.0 20101.0 6911.0 10729.0 28570.0 12495.0 13344.0 32563.0
## [5941] 12299.0 10858.0 5465.0 12633.0 3876.0 6903.0 13731.0 4826.0 16998.0
## [5950] 29295.0 26423.0 4935.0 12933.0 29937.0 27514.0 32275.0 4107.0 5023.0
## [5959] 6071.0 27494.0 17230.0 30885.0 17970.0 10343.0 9267.0 14386.0 3581.0
## [5968] 3079.0 3594.0 10488.0 24001.0 10301.0 23939.0 21615.0 8712.0 12203.0
## [5977] 3548.0 30543.0 5230.0 3246.0 10018.0 10272.0 19846.0 20701.0 8426.0
## [5986] 16722.0 4413.0 8455.0 7659.0 11059.0 4093.0 24239.0 6024.0 32222.0
## [5995] 31091.0 7769.0 3533.0 27229.0 6261.0 5189.0 14458.0 16909.0 6739.0
## [6004] 4982.0 12359.0 8507.0 15355.0 23731.0 17909.0 3995.0 8297.0 5520.0
## [6013] 3736.0 9664.0 28043.0 16453.0 23502.0 7685.0 17374.0 20030.0 8656.0
## [6022] 5988.0 4917.0 18591.0 10982.0 20144.0 16349.0 10610.0 7386.0 4720.0
## [6031] 3660.0 12932.0 6089.0 23103.0 11280.0 16565.0 14305.0 6104.0 4063.0
## [6040] 11791.0 17744.0 21032.0 18571.0 10948.0 29076.0 20237.0 14828.0 3727.0
## [6049] 14290.0 7594.0 8416.0 34140.0 13753.0 15315.0 12086.0 5016.0 10325.0
## [6058] 18418.0 9633.0 8698.0 4041.0 19713.0 15261.0 33779.0 15648.0 9283.0
## [6067] 3970.0 6159.0 15633.0 3895.0 5611.0 22722.0 12978.0 9129.0 7500.0
## [6076] 14804.0 9683.0 19671.0 25217.0 21067.0 25187.0 18142.0 29865.0 9431.0
## [6085] 30770.0 3638.0 27124.0 13747.0 28174.0 11109.0 4014.0 21226.0 3681.0
## [6094] 26710.0 9550.0 16127.0 18022.0 16748.0 14143.0 7684.0 26021.0 3843.0
## [6103] 14840.0 3929.0 11427.0 3771.0 23362.0 13669.0 9764.0 10585.0 33905.0
## [6112] 33004.0 20891.0 22715.0 3526.0 6991.0 16268.0 5768.0 9491.0 4155.0
## [6121] 13894.0 6828.0 5542.0 15733.0 30082.0 3676.0 17721.0 4404.0 4423.0
## [6130] 4184.0 26923.0 15977.0 26812.0 22355.0 23240.0 16081.0 14135.0 31546.0
## [6139] 3310.0 10292.0 15944.0 34162.0 7832.0 13704.0 4133.0 5270.0 3782.0
## [6148] 5173.0 21551.0 9805.0 7530.0 8983.0 4855.0 9524.0 5181.0 28831.0
## [6157] 7020.0 12833.0 3804.0 21794.0 3850.0 4626.0 13651.0 26794.0 17190.0
## [6166] 6933.0 13589.0 4552.0 3750.0 8224.0 5654.0 28564.0 6172.0 5435.0
## [6175] 16496.0 8348.0 7935.0 9611.0 12958.0 4103.0 6888.0 21906.0 7288.0
## [6184] 12540.0 4493.0 29808.0 22754.0 29663.0 5043.0 4299.0 11859.0 17504.0
## [6193] 4165.0 6481.0 13303.0 4700.0 13187.0 17925.0 14657.0 13940.0 3688.0
## [6202] 4003.0 5409.0 5281.0 10388.0
# Question 2 (con't.) - Descriptives for Total_Trans_Amt
mean(bc1$Total_Trans_Amt)
## [1] 4404.086
median(bc1$Total_Trans_Amt)
## [1] 3899
which.max(table(bc1$Total_Trans_Amt)) %>% names
## [1] "4253"
min(bc1$Total_Trans_Amt)
## [1] 510
max(bc1$Total_Trans_Amt)
## [1] 18484
length(bc1$Total_Trans_Amt)
## [1] 10127
sd(bc1$Total_Trans_Amt)
## [1] 3397.129
# Question 3 - Frequency Distribution and a Relative Frequency Distribution for a categorical variable
# First, the Frequency Distribution of Card Category
table(bc1$Card_Category)
##
## Blue Gold Platinum Silver
## 9436 116 20 555
# Then the Relative Frequency Distribution of Card Category
table(bc1$Card_Category) / length(bc1$Card_Category)
##
## Blue Gold Platinum Silver
## 0.931766565 0.011454528 0.001974919 0.054803989
# Question 4 - Contingency Table for 2 categorical Variables
table(bc1$Marital_Status, bc1$Education_Level)
##
## College Doctorate Graduate High School Post-Graduate Uneducated
## Divorced 86 36 225 128 41 136
## Married 467 205 1479 949 243 656
## Single 386 182 1197 782 189 586
## Unknown 74 28 227 154 43 109
##
## Unknown
## Divorced 96
## Married 688
## Single 621
## Unknown 114
# Question 5 - Bar Chart & Pie Chart for categorical variables
# First the bar chart of Educaion Levels
p1 <- bc1 %>%
ggplot(aes(x = Education_Level))+
geom_bar()+
ggtitle("Education Level of the Bank's Card Holders")+
xlab("Education Levels")
p1
# Question 5 (con't.) Now the Pie Chart
card_type <- c("Blue", "Silver", "Gold", "Platinum")
number <- c(9436, 555, 116, 20 )
cards <- data.frame(card_type, number)
cards
## card_type number
## 1 Blue 9436
## 2 Silver 555
## 3 Gold 116
## 4 Platinum 20
#col = rainbow(length(cards$number)) I tried a # of ways to get color; finally got this. Not happy w/ it, but it worked.
pie(cards$number,
col = rainbow(length(cards$number)),
labels = card_type,
main = "The Bank's Card Holders by Card Type" )
# Question 6 - 2 Histograms & 2 Boxplots - 1 each for 2 quantitative variables
# The first histogram I will create is of the Total Transaction Amount, differentiated by Gender
p2 <- bc1 %>%
ggplot( aes(x=Total_Trans_Amt, colour = Gender)) +
geom_histogram( binwidth=100) +
ggtitle("Histogram of Total Transaction Amount by Gender")
# theme_ipsum() +
#theme(
# plot.title = "Histogram of Total Transaction Amount by Gender"
#)
p2
# Question 6 (con't.) Boxplot of Total Transaction Amount by Gender
boxplot(bc1$Total_Trans_Amt ~ (bc1$Gender), ylab = "Total Transaction Amount", xlab = "Gender", main = "Boxplot of Total Transaction Amount by Gender")
# Question 6 - 2 Histograms & 2 Boxplots - 1 each for 2 quantitative variables
# The second histogram I will create is of the Credit Limit
p3 <- bc1 %>%
ggplot( aes(x=Credit_Limit)) +
geom_histogram(binwidth = 500) +
ggtitle("Histogram of Credit Limit")
p3
# Question 6 (con't.) Boxplot of Credit Limit by Marital Status
boxplot(bc1$Credit_Limit ~ (bc1$Marital_Status), ylab = "Credit Limit", xlab = "Marital Status", main = "Boxplot of Credit Limit by Marital Status")
#Question 7 - Analyze the results
### One interesting result, and to me unexpected, was the 6,205 unique credit limits. Almost everyone in the data set had his or her own credit limit - 6,205 of 10,127 observations. The statistics that led me to investigate this was the congruence of the mode and maximum of the credit limit. It was not intuituve, to me at least, why the highest credit limit was the mode. I thought there must be an error. But many, if not most, of the credit limit values had only 1 or 2 occurrences. I thought credit limits would be in even dollar amounts - 500, 1000, 1500, etc. This is not the case, at least w/ this bank.
### Another interesting finding is the total transaction amount compared by gender. The histogram seems to show females have more transactions at any given total transaction amount. Yet when I ran the boxplot, the males were highter. What happened? Then I studied the histogram in more detail. At the very highest transaction amount, the number of females is either negligible or none. Males thus underspend females, except at the very highest level. This seems to confirm the adage: "The difference between men and boys is the price of their toys."
### Finally, it seems odd that married individuals have overall lower credit limits than divorced or single persons. While the outliers for all groups seem to be about the same, the IQC and median for marrieds is the lowest of all 4 marital status groups.
### All in all, a very interesting and fun assignment.