rm(list=ls())
library(mice)
##
## Attaching package: 'mice'
## The following object is masked from 'package:stats':
##
## filter
## The following objects are masked from 'package:base':
##
## cbind, rbind
##
## Attaching package: 'janitor'
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.test
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(Rcpp)
library(Amelia)
## ##
## ## Amelia II: Multiple Imputation
## ## (Version 1.8.3, built: 2024-11-07)
## ## Copyright (C) 2005-2026 James Honaker, Gary King and Matthew Blackwell
## ## Refer to http://gking.harvard.edu/amelia/ for more information
## ##
Cviko 3
rm(list=ls())
data <- read.csv("smart_logistics_dataset.csv")
head(data)
## Timestamp Asset_ID Latitude Longitude Inventory_Level
## 1 2024-03-20 00:11:14 Truck_7 -65.7383 11.2497 390
## 2 2024-10-30 07:53:51 Truck_6 22.2748 -131.7086 491
## 3 2024-07-29 18:42:48 Truck_10 54.9232 79.5455 190
## 4 2024-10-28 00:50:54 Truck_9 42.3900 -1.4788 330
## 5 2024-09-27 15:52:58 Truck_7 -65.8477 47.9468 480
## 6 2024-09-17 06:02:15 Truck_7 73.3312 46.5831 118
## Shipment_Status Temperature Humidity Traffic_Status Waiting_Time
## 1 Delayed 27.0 67.8 Detour 38
## 2 In Transit 22.5 54.3 Heavy 16
## 3 In Transit 25.2 62.2 Detour 34
## 4 Delivered 25.4 52.3 Heavy 37
## 5 Delayed 20.5 57.2 Clear 56
## 6 In Transit 24.3 61.8 Clear 56
## User_Transaction_Amount User_Purchase_Frequency Logistics_Delay_Reason
## 1 320 4 None
## 2 439 7 Weather
## 3 355 3 None
## 4 227 5 Traffic
## 5 197 6 None
## 6 258 10 None
## Asset_Utilization Demand_Forecast Logistics_Delay
## 1 60.1 285 1
## 2 80.9 174 1
## 3 99.2 260 0
## 4 97.4 160 1
## 5 71.6 270 1
## 6 66.8 189 0
library(janitor)
# Clean up the column names - skratenie a uprava nazvov
data <- data %>%
clean_names()
head(data)
## timestamp asset_id latitude longitude inventory_level
## 1 2024-03-20 00:11:14 Truck_7 -65.7383 11.2497 390
## 2 2024-10-30 07:53:51 Truck_6 22.2748 -131.7086 491
## 3 2024-07-29 18:42:48 Truck_10 54.9232 79.5455 190
## 4 2024-10-28 00:50:54 Truck_9 42.3900 -1.4788 330
## 5 2024-09-27 15:52:58 Truck_7 -65.8477 47.9468 480
## 6 2024-09-17 06:02:15 Truck_7 73.3312 46.5831 118
## shipment_status temperature humidity traffic_status waiting_time
## 1 Delayed 27.0 67.8 Detour 38
## 2 In Transit 22.5 54.3 Heavy 16
## 3 In Transit 25.2 62.2 Detour 34
## 4 Delivered 25.4 52.3 Heavy 37
## 5 Delayed 20.5 57.2 Clear 56
## 6 In Transit 24.3 61.8 Clear 56
## user_transaction_amount user_purchase_frequency logistics_delay_reason
## 1 320 4 None
## 2 439 7 Weather
## 3 355 3 None
## 4 227 5 Traffic
## 5 197 6 None
## 6 258 10 None
## asset_utilization demand_forecast logistics_delay
## 1 60.1 285 1
## 2 80.9 174 1
## 3 99.2 260 0
## 4 97.4 160 1
## 5 71.6 270 1
## 6 66.8 189 0
## [1] "timestamp" "asset_id"
## [3] "latitude" "longitude"
## [5] "inventory_level" "shipment_status"
## [7] "temperature" "humidity"
## [9] "traffic_status" "waiting_time"
## [11] "user_transaction_amount" "user_purchase_frequency"
## [13] "logistics_delay_reason" "asset_utilization"
## [15] "demand_forecast" "logistics_delay"