##Market basket analisis
library(Matrix)## Warning: package 'Matrix' was built under R version 4.1.3library(arules)## Warning: package 'arules' was built under R version 4.1.3##
## Attaching package: 'arules'## The following objects are masked from 'package:base':
##
## abbreviate, writelibrary(arulesViz)## Warning: package 'arulesViz' was built under R version 4.1.3library(datasets)##importar base de datos
bd_limpia <- read.csv("abarrotes_bd_limpia.csv")##Ordena de menor a mayor de los tickets
bd_limpia <- bd_limpia[order(bd_limpia$F.Ticket),]
head(bd_limpia)## ï..vcClaveTienda DescGiro Fecha Hora Marca
## 1 MX001 Abarrotes 2020-06-19 8 NUTRI LECHE
## 2 MX001 Abarrotes 2020-06-19 8 DAN UP
## 3 MX001 Abarrotes 2020-06-19 8 BIMBO
## 4 MX001 Abarrotes 2020-06-19 8 PEPSI
## 5 MX001 Abarrotes 2020-06-19 8 BLANCA NIEVES (DETERGENTE)
## 6 MX001 Abarrotes 2020-06-19 8 FLASH
## Fabricante Producto Precio
## 1 MEXILAC Nutri Leche 1 Litro 16.0
## 2 DANONE DE MEXICO DANUP STRAWBERRY P/BEBER 350GR NAL 14.0
## 3 GRUPO BIMBO Rebanadas Bimbo 2Pz 5.0
## 4 PEPSI-COLA MEXICANA Pepsi N.R. 400Ml 8.0
## 5 FABRICA DE JABON LA CORONA Detergente Blanca Nieves 500G 19.5
## 6 ALEN Flash Xtra Brisa Marina 500Ml 9.5
## Ult.Costo Unidades F.Ticket NombreDepartamento NombreFamilia
## 1 12.31 1 1 Abarrotes Lacteos y Refrigerados
## 2 14.00 1 2 Abarrotes Lacteos y Refrigerados
## 3 5.00 1 3 Abarrotes Pan y Tortilla
## 4 8.00 1 3 Abarrotes Bebidas
## 5 15.00 1 4 Abarrotes Limpieza del Hogar
## 6 7.31 1 4 Abarrotes Limpieza del Hogar
## NombreCategoria Estado Mts.2 Tipo.ubicación Giro
## 1 Leche Nuevo León 60 Esquina Abarrotes
## 2 Yogurt Nuevo León 60 Esquina Abarrotes
## 3 Pan Dulce Empaquetado Nuevo León 60 Esquina Abarrotes
## 4 Refrescos Plástico (N.R.) Nuevo León 60 Esquina Abarrotes
## 5 LavanderÃa Nuevo León 60 Esquina Abarrotes
## 6 Limpiadores LÃquidos Nuevo León 60 Esquina Abarrotes
## Hora.inicio Hora.cierre Dia_de_la_semana Subtotal Utilidad
## 1 08:00 22:00 6 16.0 3.69
## 2 08:00 22:00 6 14.0 0.00
## 3 08:00 22:00 6 5.0 0.00
## 4 08:00 22:00 6 8.0 0.00
## 5 08:00 22:00 6 19.5 4.50
## 6 08:00 22:00 6 9.5 2.19tail(bd_limpia)## ï..vcClaveTienda DescGiro Fecha Hora Marca
## 107394 MX004 CarnicerÃa 2020-10-15 11 YEMINA
## 167771 MX004 CarnicerÃa 2020-10-15 11 DEL FUERTE
## 149429 MX004 CarnicerÃa 2020-10-15 11 COCA COLA ZERO
## 168750 MX004 CarnicerÃa 2020-10-15 11 DIAMANTE
## 161193 MX004 CarnicerÃa 2020-10-15 12 PEPSI
## 112970 MX004 CarnicerÃa 2020-10-15 12 COCA COLA
## Fabricante Producto Precio Ult.Costo
## 107394 HERDEZ PASTA SPAGHETTI YEMINA 200G 7 5.38
## 167771 ALIMENTOS DEL FUERTE PURE DE TOMATE DEL FUERTE 345G 12 9.23
## 149429 COCA COLA COCA COLA ZERO 600ML 15 11.54
## 168750 EMPACADOS ARROZ DIAMANTE225G 11 8.46
## 161193 PEPSI-COLA MEXICANA PEPSI N. R. 500ML 10 7.69
## 112970 COCA COLA COCA COLA RETORNABLE 500ML 10 7.69
## Unidades F.Ticket NombreDepartamento NombreFamilia
## 107394 2 450032 Abarrotes Sopas y Pastas
## 167771 1 450032 Abarrotes Salsas y Sazonadores
## 149429 2 450034 Abarrotes Bebidas
## 168750 1 450037 Abarrotes Granos y Semillas
## 161193 1 450039 Abarrotes Bebidas
## 112970 8 450040 Abarrotes Bebidas
## NombreCategoria Estado Mts.2 Tipo.ubicación Giro
## 107394 Fideos, Spaguetti, Tallarines Sinaloa 53 Esquina Abarrotes
## 167771 Salsa para Spaguetti Sinaloa 53 Esquina Abarrotes
## 149429 Refrescos Retornables Sinaloa 53 Esquina Abarrotes
## 168750 Arroz Sinaloa 53 Esquina Abarrotes
## 161193 Refrescos Plástico (N.R.) Sinaloa 53 Esquina Abarrotes
## 112970 Refrescos Retornables Sinaloa 53 Esquina Abarrotes
## Hora.inicio Hora.cierre Dia_de_la_semana Subtotal Utilidad
## 107394 07:00 23:00 5 14 1.62
## 167771 07:00 23:00 5 12 2.77
## 149429 07:00 23:00 5 30 3.46
## 168750 07:00 23:00 5 11 2.54
## 161193 07:00 23:00 5 10 2.31
## 112970 07:00 23:00 5 80 2.31##Generar basket
library(plyr)## Warning: package 'plyr' was built under R version 4.1.3basket <- ddply(bd_limpia, c("F.Ticket"), function(bd_limpia)paste(bd_limpia$Marca, collapse = "."))##Eliminar numero de tickets
basket$F.Tickert <- NULL##Renombrar
colnames(basket) <- c("Marca")##Exportar
write.csv(basket,"basket.csv", quote = FALSE, row.names = FALSE)##Importar transacciones
tr <- read.transactions("basket.csv", format = "basket", sep = ".")## Warning in scan(text = l, what = "character", sep = sep, quote = quote, : EOF
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## within quoted string## Warning in asMethod(object): removing duplicated items in transactionsreglas.asociacion <- apriori(tr, parameter = list(supp=0.001, conf=0.2, maxlen= 10))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.2 0.1 1 none FALSE TRUE 5 0.001 1
## maxlen target ext
## 10 rules TRUE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 115
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[115648 item(s), 115111 transaction(s)] done [0.19s].
## sorting and recoding items ... [133 item(s)] done [0.02s].
## creating transaction tree ... done [0.02s].
## checking subsets of size 1 2 3 done [0.00s].
## writing ... [1 rule(s)] done [0.00s].
## creating S4 object ... done [0.01s].summary(reglas.asociacion)## set of 1 rules
##
## rule length distribution (lhs + rhs):sizes
## 2
## 1
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2 2 2 2 2 2
##
## summary of quality measures:
## support confidence coverage lift
## Min. :0.001129 Min. :0.2044 Min. :0.005525 Min. :27.04
## 1st Qu.:0.001129 1st Qu.:0.2044 1st Qu.:0.005525 1st Qu.:27.04
## Median :0.001129 Median :0.2044 Median :0.005525 Median :27.04
## Mean :0.001129 Mean :0.2044 Mean :0.005525 Mean :27.04
## 3rd Qu.:0.001129 3rd Qu.:0.2044 3rd Qu.:0.005525 3rd Qu.:27.04
## Max. :0.001129 Max. :0.2044 Max. :0.005525 Max. :27.04
## count
## Min. :130
## 1st Qu.:130
## Median :130
## Mean :130
## 3rd Qu.:130
## Max. :130
##
## mining info:
## data ntransactions support confidence
## tr 115111 0.001 0.2
## call
## apriori(data = tr, parameter = list(supp = 0.001, conf = 0.2, maxlen = 10))inspect(reglas.asociacion)## lhs rhs support confidence coverage lift count
## [1] {REYMA} => {CONVERMEX} 0.001129345 0.2044025 0.005525102 27.0448 130reglas.asociacion <- sort(reglas.asociacion, by="confidence" , decreasing = TRUE)
summary(reglas.asociacion)## set of 1 rules
##
## rule length distribution (lhs + rhs):sizes
## 2
## 1
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2 2 2 2 2 2
##
## summary of quality measures:
## support confidence coverage lift
## Min. :0.001129 Min. :0.2044 Min. :0.005525 Min. :27.04
## 1st Qu.:0.001129 1st Qu.:0.2044 1st Qu.:0.005525 1st Qu.:27.04
## Median :0.001129 Median :0.2044 Median :0.005525 Median :27.04
## Mean :0.001129 Mean :0.2044 Mean :0.005525 Mean :27.04
## 3rd Qu.:0.001129 3rd Qu.:0.2044 3rd Qu.:0.005525 3rd Qu.:27.04
## Max. :0.001129 Max. :0.2044 Max. :0.005525 Max. :27.04
## count
## Min. :130
## 1st Qu.:130
## Median :130
## Mean :130
## 3rd Qu.:130
## Max. :130
##
## mining info:
## data ntransactions support confidence
## tr 115111 0.001 0.2
## call
## apriori(data = tr, parameter = list(supp = 0.001, conf = 0.2, maxlen = 10))inspect(reglas.asociacion)## lhs rhs support confidence coverage lift count
## [1] {REYMA} => {CONVERMEX} 0.001129345 0.2044025 0.005525102 27.0448 130top10reglas <- head(reglas.asociacion, n=10, by= "confidence")
plot(top10reglas, method= "graph", engine= "htmlwidget")