dat<-readRDS("/Users/cjcurry/Downloads/FairTraders_Receipts_and_StorageBins.rds")
str(dat)
## 'data.frame': 6275201 obs. of 15 variables:
## $ ItemNo : num 1101010 1101010 1101010 1101010 1101010 ...
## $ Date.x : POSIXct, format: "2011-01-12" "2011-01-12" ...
## $ SourceType : chr "Supplier Order" "Supplier Order" "Supplier Order" "Supplier Order" ...
## $ SourceNo : chr "236169" "236169" "236169" "236169" ...
## $ Quantity.x : num 1 1 1 1 1 1 1 1 1 1 ...
## $ MerchVol.x : num 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 ...
## $ CustGroup : chr "FESTIVAL" "FESTIVAL" "FESTIVAL" "FESTIVAL" ...
## $ Date.y : POSIXct, format: "2010-05-01" "2010-12-01" ...
## $ BinCode : chr "3B16A2" "1H36E1" "1Z03B1" "1G21D1" ...
## $ BinSize : chr "CHICKENBOX" "PALLET" "PALLET" "PALLET" ...
## $ BinVol : num 2.29 60 60 60 60 ...
## $ Quantity.y : num 37 804 700 339 278 550 804 3 800 30 ...
## $ ItemBoxType: chr "Skid" "Skid" "Skid" "Skid" ...
## $ MerchVol.y : num 44.4 964.8 840 406.8 333.6 ...
## $ PercentFull: num 19.37 16.08 14 6.78 5.56 ...
There are entries in the data file.
nrow(dat)
## [1] 6275201
the percentage of product by each group
dat$CustGroup<-as.factor(dat$CustGroup)
str(dat$CustGroup)
## Factor w/ 3 levels "ECOMMERCE","FESTIVAL",..: 2 2 2 2 2 2 2 2 2 2 ...
table(dat$CustGroup)
##
## ECOMMERCE FESTIVAL WHOLESALE
## 961299 5163906 149996
prop.table(table(dat$CustGroup))
##
## ECOMMERCE FESTIVAL WHOLESALE
## 0.15319015 0.82290687 0.02390298
The percentage of orders that were Purchase Orders
dat$SourceType<-as.factor(dat$SourceType)
table(dat$SourceType)
##
## Purchase Order Supplier Order
## 961299 5313902
prop.table(table(dat$SourceType))
##
## Purchase Order Supplier Order
## 0.1531902 0.8468098
The percantage of orders that were recieved by the eCommerce business unit
prop.table(table(dat$CustGroup, dat$SourceType))
##
## Purchase Order Supplier Order
## ECOMMERCE 0.15319015 0.00000000
## FESTIVAL 0.00000000 0.82290687
## WHOLESALE 0.00000000 0.02390298
The percentage of orders that were recieved by the eCommerce is 15%.
The percantage of order recieved by the Wholesale business unit
prop.table(table(dat$CustGroup, dat$SourceType))
##
## Purchase Order Supplier Order
## ECOMMERCE 0.15319015 0.00000000
## FESTIVAL 0.00000000 0.82290687
## WHOLESALE 0.00000000 0.02390298
The percentage of orders that were recieved by the Wholesale business unit is 0.
table(dat$BinSize)
##
## BASKET CHICKENBOX HALFPALLET ODDSIZE3A PALLET TALLPALLET
## 12752 2911658 158661 3644 3119723 68763
prop.table(table(dat$BinSize))
##
## BASKET CHICKENBOX HALFPALLET ODDSIZE3A PALLET TALLPALLET
## 0.0020321261 0.4639943804 0.0252838116 0.0005806985 0.4971510873 0.0109578960
The percantage of orders stored as a pallet is 49.7%
prop.table(table(dat$BinSize, dat$SourceType))
##
## Purchase Order Supplier Order
## BASKET 0.0002200726 0.0018120535
## CHICKENBOX 0.0717017670 0.3922926134
## HALFPALLET 0.0018459966 0.0234378150
## ODDSIZE3A 0.0001958503 0.0003848482
## PALLET 0.0754847534 0.4216663339
## TALLPALLET 0.0037417128 0.0072161832
The percentage of orders that were recieved as a Purchase Order and stored in a Chicken Box is 7.1%
We added the percentage of Purchase orders and the percentage of orders stored in a Chicken Box and subtracted the percentage of orders that were purchase orders and stored in a chicken box. 15.32% + 46.4% - 7.17% = 54.55%