Market Basket Analysis
Instalar paquetes y llamar librerias
#install.packages("plyr")
library(plyr)
## Warning: package 'plyr' was built under R version 4.2.3
#install.packages("Matrix")
library(Matrix)
## Warning: package 'Matrix' was built under R version 4.2.3
#install.packages("arules")
library(arules)
## Warning: package 'arules' was built under R version 4.2.3
##
## Attaching package: 'arules'
## The following objects are masked from 'package:base':
##
## abbreviate, write
#install.packages("arulesViz")
library(arulesViz)
## Warning: package 'arulesViz' was built under R version 4.2.3
#install.packages("datasets")
library(datasets)
Importar la base de datos
#file.choose()
#bd_limpia <- read.csv("C:\\Users\\lesda\\OneDrive\\Documentos\\abarrotes_limpia.csv")
Ordenar de menor a mayor los tickets
#bd_limpia <- bd_limpia[order(bd_limpia$F.Ticket),]
#head(bd_limpia)
#tail(bd_limpia)
Eliminar numero de ticket
#basket$F.Ticket <- NULL
Renombrar el nombre de la columna marca
#colnames(basket) <- c("Marca")
# Exportar basket
#write.csv(basket,"basket.csv", quote = FALSE, row.names = FALSE)
# Importar transacciones
#file.choose()
#tr <- read.transactions("C:\\Users\\lesda\\OneDrive\\Documentos\\basket.csv", format = "basket", sep = ",")
Generar reglas de asociacion
#reglas_asociacion <- apriori(tr, parameter = list(supp=0.001, conf=0.2, maxlen=10))
#summary(reglas_asociacion)
#inspect(reglas_asociacion)
#reglas_asociacion <- sort(reglas_asociacion, by= "confidence", decreasing = TRUE)
#summary(reglas_asociacion)
#inspect(reglas_asociacion)
#top10reglas <- head(reglas_asociacion, n=10, by="confidence")
#plot(top10reglas, method="graph", engine="htmlwidget")
Estrategias de Negocio
# 1. Asignar marcas cercanas en el anaquel: Salvo y Fabuloso...
# 2. promocion en Reyma, Pinol, Queso/Jamon/Mayonesa, Zero/Light/Fanta.
# 3. Realizar Business Case para venta de sandwiches preparados.
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