Abarrotes Limpia
Isaac Díaz A01540543
2022-09-06
Resumen
A la base de datos se le hicieron los siguientes cambios: Formato a fecha corta. “Se duplicaron los primeros 5 registros”Se cambió el formato a Hora (Español México) ” Se cambió el formato a código de barras (para que salga completo) Se guardó como CSV UTF-8 (Delimitado por comas).
Importar la base de datos
bd <- read.csv("/Users/isaacdiazruizdechavez/Downloads/abarrotes.csv")Entender las bases de datos
summary(bd)## vcClaveTienda DescGiro Codigo.Barras PLU
## Length:200625 Length:200625 Min. :8.347e+05 Min. : 1.00
## Class :character Class :character 1st Qu.:7.501e+12 1st Qu.: 1.00
## Mode :character Mode :character Median :7.501e+12 Median : 1.00
## Mean :5.950e+12 Mean : 2.11
## 3rd Qu.:7.501e+12 3rd Qu.: 1.00
## Max. :1.750e+13 Max. :30.00
## NA's :199188
## Fecha Hora Marca Fabricante
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Producto Precio Ult.Costo Unidades
## Length:200625 Min. :-147.00 Min. : 0.38 Min. : 0.200
## Class :character 1st Qu.: 11.00 1st Qu.: 8.46 1st Qu.: 1.000
## Mode :character Median : 16.00 Median : 12.31 Median : 1.000
## Mean : 19.42 Mean : 15.31 Mean : 1.262
## 3rd Qu.: 25.00 3rd Qu.: 19.23 3rd Qu.: 1.000
## Max. :1000.00 Max. :769.23 Max. :96.000
##
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## Min. : 1 Length:200625 Length:200625 Length:200625
## 1st Qu.: 33964 Class :character Class :character Class :character
## Median :105993 Mode :character Mode :character Mode :character
## Mean :193990
## 3rd Qu.:383005
## Max. :450040
##
## Estado Mts.2 Tipo.ubicación Giro
## Length:200625 Min. :47.0 Length:200625 Length:200625
## Class :character 1st Qu.:53.0 Class :character Class :character
## Mode :character Median :60.0 Mode :character Mode :character
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
##
## Hora.inicio Hora.cierre
## Length:200625 Length:200625
## Class :character Class :character
## Mode :character Mode :character
##
##
##
## #install.packages("dplyr")
library(dplyr)##
## 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#count(bd,vcClaveTienda, sort = TRUE)
#count(bd,DescGiro, sort = TRUE)
#count(bd,Marca, sort = TRUE)
#count(bd,Fabricante, sort = TRUE)
#count(bd,Producto, sort = TRUE)
#count(bd,NombreCategoria, sort = TRUE)
#count(bd,NombreFamilia, sort = TRUE)
#count(bd,Estado, sort = TRUE)
#count(bd,Mts.2, sort = TRUE)
#count(bd,Tipo.ubicación, sort = TRUE)
#count(bd,Giro, sort = TRUE)
#count(bd,Hora.inicio, sort = TRUE)
#count(bd,Hora.cierre, sort = TRUE)#install.packages("tidyverse")
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4
## ✔ tibble 3.1.8 ✔ stringr 1.4.1
## ✔ tidyr 1.2.0 ✔ forcats 0.5.2
## ✔ readr 2.1.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()tibble(bd)## # A tibble: 200,625 × 22
## vcClaveTienda DescGiro Codig…¹ PLU Fecha Hora Marca Fabri…² Produ…³ Precio
## <chr> <chr> <dbl> <int> <chr> <chr> <chr> <chr> <chr> <dbl>
## 1 MX001 Abarrot… 7.50e12 NA 19/0… 08:1… NUTR… MEXILAC Nutri … 16
## 2 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… DAN … DANONE… DANUP … 14
## 3 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… BIMBO GRUPO … Rebana… 5
## 4 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… PEPSI PEPSI-… Pepsi … 8
## 5 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… BLAN… FABRIC… Deterg… 19.5
## 6 MX001 Abarrot… 7.50e12 NA 19/0… 08:1… NUTR… MEXILAC Nutri … 16
## 7 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… DAN … DANONE… DANUP … 14
## 8 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… BIMBO GRUPO … Rebana… 5
## 9 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… PEPSI PEPSI-… Pepsi … 8
## 10 MX001 Abarrot… 7.50e12 NA 19/0… 08:2… BLAN… FABRIC… Deterg… 19.5
## # … with 200,615 more rows, 12 more variables: Ult.Costo <dbl>, Unidades <dbl>,
## # F.Ticket <int>, NombreDepartamento <chr>, NombreFamilia <chr>,
## # NombreCategoria <chr>, Estado <chr>, Mts.2 <int>, Tipo.ubicación <chr>,
## # Giro <chr>, Hora.inicio <chr>, Hora.cierre <chr>, and abbreviated variable
## # names ¹Codigo.Barras, ²Fabricante, ³Productostr(bd)## 'data.frame': 200625 obs. of 22 variables:
## $ vcClaveTienda : chr "MX001" "MX001" "MX001" "MX001" ...
## $ DescGiro : chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ Codigo.Barras : num 7.5e+12 7.5e+12 7.5e+12 7.5e+12 7.5e+12 ...
## $ PLU : int NA NA NA NA NA NA NA NA NA NA ...
## $ Fecha : chr "19/06/20" "19/06/20" "19/06/20" "19/06/20" ...
## $ Hora : chr "08:16:21 a. m." "08:23:33 a. m." "08:24:33 a. m." "08:24:33 a. m." ...
## $ Marca : chr "NUTRI LECHE" "DAN UP" "BIMBO" "PEPSI" ...
## $ Fabricante : chr "MEXILAC" "DANONE DE MEXICO" "GRUPO BIMBO" "PEPSI-COLA MEXICANA" ...
## $ Producto : chr "Nutri Leche 1 Litro" "DANUP STRAWBERRY P/BEBER 350GR NAL" "Rebanadas Bimbo 2Pz" "Pepsi N.R. 400Ml" ...
## $ Precio : num 16 14 5 8 19.5 16 14 5 8 19.5 ...
## $ Ult.Costo : num 12.3 14 5 8 15 ...
## $ Unidades : num 1 1 1 1 1 1 1 1 1 1 ...
## $ F.Ticket : int 1 2 3 3 4 1 2 3 3 4 ...
## $ NombreDepartamento: chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ NombreFamilia : chr "Lacteos y Refrigerados" "Lacteos y Refrigerados" "Pan y Tortilla" "Bebidas" ...
## $ NombreCategoria : chr "Leche" "Yogurt" "Pan Dulce Empaquetado" "Refrescos Plástico (N.R.)" ...
## $ Estado : chr "Nuevo León" "Nuevo León" "Nuevo León" "Nuevo León" ...
## $ Mts.2 : int 60 60 60 60 60 60 60 60 60 60 ...
## $ Tipo.ubicación : chr "Esquina" "Esquina" "Esquina" "Esquina" ...
## $ Giro : chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ Hora.inicio : chr "8:00" "8:00" "8:00" "8:00" ...
## $ Hora.cierre : chr "22:00" "22:00" "22:00" "22:00" ...head(bd)## vcClaveTienda DescGiro Codigo.Barras PLU Fecha Hora
## 1 MX001 Abarrotes 7.501021e+12 NA 19/06/20 08:16:21 a. m.
## 2 MX001 Abarrotes 7.501032e+12 NA 19/06/20 08:23:33 a. m.
## 3 MX001 Abarrotes 7.501000e+12 NA 19/06/20 08:24:33 a. m.
## 4 MX001 Abarrotes 7.501031e+12 NA 19/06/20 08:24:33 a. m.
## 5 MX001 Abarrotes 7.501026e+12 NA 19/06/20 08:26:28 a. m.
## 6 MX001 Abarrotes 7.501021e+12 NA 19/06/20 08:16:21 a. m.
## Marca Fabricante
## 1 NUTRI LECHE MEXILAC
## 2 DAN UP DANONE DE MEXICO
## 3 BIMBO GRUPO BIMBO
## 4 PEPSI PEPSI-COLA MEXICANA
## 5 BLANCA NIEVES (DETERGENTE) FABRICA DE JABON LA CORONA
## 6 NUTRI LECHE MEXILAC
## Producto Precio Ult.Costo Unidades F.Ticket
## 1 Nutri Leche 1 Litro 16.0 12.31 1 1
## 2 DANUP STRAWBERRY P/BEBER 350GR NAL 14.0 14.00 1 2
## 3 Rebanadas Bimbo 2Pz 5.0 5.00 1 3
## 4 Pepsi N.R. 400Ml 8.0 8.00 1 3
## 5 Detergente Blanca Nieves 500G 19.5 15.00 1 4
## 6 Nutri Leche 1 Litro 16.0 12.31 1 1
## NombreDepartamento NombreFamilia NombreCategoria
## 1 Abarrotes Lacteos y Refrigerados Leche
## 2 Abarrotes Lacteos y Refrigerados Yogurt
## 3 Abarrotes Pan y Tortilla Pan Dulce Empaquetado
## 4 Abarrotes Bebidas Refrescos Plástico (N.R.)
## 5 Abarrotes Limpieza del Hogar Lavandería
## 6 Abarrotes Lacteos y Refrigerados Leche
## Estado Mts.2 Tipo.ubicación Giro Hora.inicio Hora.cierre
## 1 Nuevo León 60 Esquina Abarrotes 8:00 22:00
## 2 Nuevo León 60 Esquina Abarrotes 8:00 22:00
## 3 Nuevo León 60 Esquina Abarrotes 8:00 22:00
## 4 Nuevo León 60 Esquina Abarrotes 8:00 22:00
## 5 Nuevo León 60 Esquina Abarrotes 8:00 22:00
## 6 Nuevo León 60 Esquina Abarrotes 8:00 22:00tail(bd)## vcClaveTienda DescGiro Codigo.Barras PLU Fecha Hora
## 200620 MX005 Depósito 7.62221e+12 NA 12/07/20 01:08:25 a. m.
## 200621 MX005 Depósito 7.62221e+12 NA 23/10/20 10:17:37 p. m.
## 200622 MX005 Depósito 7.62221e+12 NA 10/10/20 08:30:20 p. m.
## 200623 MX005 Depósito 7.62221e+12 NA 10/10/20 10:40:43 p. m.
## 200624 MX005 Depósito 7.62221e+12 NA 27/06/20 10:30:19 p. m.
## 200625 MX005 Depósito 7.62221e+12 NA 26/06/20 11:43:34 p. m.
## Marca Fabricante Producto Precio
## 200620 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## 200621 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## 200622 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## 200623 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## 200624 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## 200625 TRIDENT XTRA CARE CADBURY ADAMS Trident Xtracare Freshmint 16.32G 9
## Ult.Costo Unidades F.Ticket NombreDepartamento NombreFamilia
## 200620 6.92 1 103100 Abarrotes Dulcería
## 200621 6.92 1 116598 Abarrotes Dulcería
## 200622 6.92 1 114886 Abarrotes Dulcería
## 200623 6.92 1 114955 Abarrotes Dulcería
## 200624 6.92 1 101121 Abarrotes Dulcería
## 200625 6.92 1 100879 Abarrotes Dulcería
## NombreCategoria Estado Mts.2 Tipo.ubicación Giro Hora.inicio
## 200620 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## 200621 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## 200622 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## 200623 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## 200624 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## 200625 Gomas de Mazcar Quintana Roo 58 Esquina Mini súper 8:00
## Hora.cierre
## 200620 21:00
## 200621 21:00
## 200622 21:00
## 200623 21:00
## 200624 21:00
## 200625 21:00#install.packages("janitor")
library(janitor)##
## Attaching package: 'janitor'
##
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.testtabyl(bd, vcClaveTienda, NombreDepartamento)## vcClaveTienda Abarrotes Bebes e Infantiles Carnes Farmacia Ferretería Mercería
## MX001 95415 515 1 147 245 28
## MX002 6590 21 0 4 10 0
## MX003 4026 15 0 2 8 0
## MX004 82234 932 0 102 114 16
## MX005 10014 0 0 0 0 0
## Papelería Productos a Eliminar Vinos y Licores
## 35 3 80
## 0 0 4
## 0 0 0
## 32 5 20
## 7 0 0observaciones
- Casi ningun registro cuenta con PLU.
- Cambiar formato de fecha
- Cambiar formato de Hora
- Hay precios negativos
- Hay unidades menores a 1
Técnicas para limpieza de datos
Técnica 1. Remover valores irrelevantes
#Eliminar columnas
bd1 <- bd
bd1<- subset(bd1, select = -c (PLU, Codigo.Barras))
#Eliminar renglones
bd2 <- bd1
bd2 <- bd2[bd2$Precio > 0, ]
summary(bd1)## vcClaveTienda DescGiro Fecha Hora
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Marca Fabricante Producto Precio
## Length:200625 Length:200625 Length:200625 Min. :-147.00
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.42
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 0.200 Min. : 1 Length:200625
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33964 Class :character
## Median : 12.31 Median : 1.000 Median :105993 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193990
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383005
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200625 Length:200625 Length:200625 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
## summary(bd2)## vcClaveTienda DescGiro Fecha Hora
## Length:200478 Length:200478 Length:200478 Length:200478
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Marca Fabricante Producto Precio
## Length:200478 Length:200478 Length:200478 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 0.200 Min. : 1 Length:200478
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33977 Class :character
## Median : 12.31 Median : 1.000 Median :106034 Mode :character
## Mean : 15.31 Mean : 1.261 Mean :194096
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383062
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200478 Length:200478 Length:200478 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200478 Length:200478 Length:200478 Length:200478
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
## Técnica 2. Remover valores duplicados
Cuantos renglones duplicados tenemos?
bd1[duplicated(bd1),]## vcClaveTienda DescGiro Fecha Hora Marca
## 6 MX001 Abarrotes 19/06/20 08:16:21 a. m. NUTRI LECHE
## 7 MX001 Abarrotes 19/06/20 08:23:33 a. m. DAN UP
## 8 MX001 Abarrotes 19/06/20 08:24:33 a. m. BIMBO
## 9 MX001 Abarrotes 19/06/20 08:24:33 a. m. PEPSI
## 10 MX001 Abarrotes 19/06/20 08:26:28 a. m. BLANCA NIEVES (DETERGENTE)
## Fabricante Producto Precio
## 6 MEXILAC Nutri Leche 1 Litro 16.0
## 7 DANONE DE MEXICO DANUP STRAWBERRY P/BEBER 350GR NAL 14.0
## 8 GRUPO BIMBO Rebanadas Bimbo 2Pz 5.0
## 9 PEPSI-COLA MEXICANA Pepsi N.R. 400Ml 8.0
## 10 FABRICA DE JABON LA CORONA Detergente Blanca Nieves 500G 19.5
## Ult.Costo Unidades F.Ticket NombreDepartamento NombreFamilia
## 6 12.31 1 1 Abarrotes Lacteos y Refrigerados
## 7 14.00 1 2 Abarrotes Lacteos y Refrigerados
## 8 5.00 1 3 Abarrotes Pan y Tortilla
## 9 8.00 1 3 Abarrotes Bebidas
## 10 15.00 1 4 Abarrotes Limpieza del Hogar
## NombreCategoria Estado Mts.2 Tipo.ubicación Giro
## 6 Leche Nuevo León 60 Esquina Abarrotes
## 7 Yogurt Nuevo León 60 Esquina Abarrotes
## 8 Pan Dulce Empaquetado Nuevo León 60 Esquina Abarrotes
## 9 Refrescos Plástico (N.R.) Nuevo León 60 Esquina Abarrotes
## 10 Lavandería Nuevo León 60 Esquina Abarrotes
## Hora.inicio Hora.cierre
## 6 8:00 22:00
## 7 8:00 22:00
## 8 8:00 22:00
## 9 8:00 22:00
## 10 8:00 22:00sum(duplicated(bd1))## [1] 5Eliminar renglones duplicados
bd3<-bd1
library(dplyr)
bd3 <- distinct(bd3)Técnica 3. Errores tipográficos y errores similares
Precios en absoluto
bd4<-bd3
bd4$Precio <- abs(bd4$Precio)
summary(bd4)## vcClaveTienda DescGiro Fecha Hora
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Marca Fabricante Producto Precio
## Length:200620 Length:200620 Length:200620 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 0.200 Min. : 1 Length:200620
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33967 Class :character
## Median : 12.31 Median : 1.000 Median :105996 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193994
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383008
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200620 Length:200620 Length:200620 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
## Cantidades en enteros
bd5 <- bd4
bd5$Unidades <- ceiling(bd5$Unidades)
summary(bd5)## vcClaveTienda DescGiro Fecha Hora
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Marca Fabricante Producto Precio
## Length:200620 Length:200620 Length:200620 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 1.000 Min. : 1 Length:200620
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33967 Class :character
## Median : 12.31 Median : 1.000 Median :105996 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193994
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383008
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200620 Length:200620 Length:200620 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
## Técnica 4. Convertir tipos de datos
Convertir de caracter a fecha
bd6<- bd5
bd6$Fecha <- as.Date(bd6$Fecha, format="%d/%m/%y")
tibble(bd6)## # A tibble: 200,620 × 20
## vcCla…¹ DescG…² Fecha Hora Marca Fabri…³ Produ…⁴ Precio Ult.C…⁵ Unida…⁶
## <chr> <chr> <date> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 MX001 Abarro… 2020-06-19 08:1… NUTR… MEXILAC Nutri … 16 12.3 1
## 2 MX001 Abarro… 2020-06-19 08:2… DAN … DANONE… DANUP … 14 14 1
## 3 MX001 Abarro… 2020-06-19 08:2… BIMBO GRUPO … Rebana… 5 5 1
## 4 MX001 Abarro… 2020-06-19 08:2… PEPSI PEPSI-… Pepsi … 8 8 1
## 5 MX001 Abarro… 2020-06-19 08:2… BLAN… FABRIC… Deterg… 19.5 15 1
## 6 MX001 Abarro… 2020-06-19 08:2… FLASH ALEN Flash … 9.5 7.31 1
## 7 MX001 Abarro… 2020-06-19 08:2… VARI… DANONE… Danone… 11 11 1
## 8 MX001 Abarro… 2020-06-19 08:2… ZOTE FABRIC… Jabon … 9.5 7.31 1
## 9 MX001 Abarro… 2020-06-19 08:2… ALWA… PROCTE… T Feme… 23.5 18.1 1
## 10 MX001 Abarro… 2020-06-19 03:2… JUMEX JUMEX Jugo D… 12 12 1
## # … with 200,610 more rows, 10 more variables: F.Ticket <int>,
## # NombreDepartamento <chr>, NombreFamilia <chr>, NombreCategoria <chr>,
## # Estado <chr>, Mts.2 <int>, Tipo.ubicación <chr>, Giro <chr>,
## # Hora.inicio <chr>, Hora.cierre <chr>, and abbreviated variable names
## # ¹vcClaveTienda, ²DescGiro, ³Fabricante, ⁴Producto, ⁵Ult.Costo, ⁶UnidadesConvertir de caracter a entero
bd7 <- bd6
bd7$Hora <- substr(bd7$Hora, start = 1, stop = 2)
tibble(bd7)## # A tibble: 200,620 × 20
## vcCla…¹ DescG…² Fecha Hora Marca Fabri…³ Produ…⁴ Precio Ult.C…⁵ Unida…⁶
## <chr> <chr> <date> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 MX001 Abarro… 2020-06-19 08 NUTR… MEXILAC Nutri … 16 12.3 1
## 2 MX001 Abarro… 2020-06-19 08 DAN … DANONE… DANUP … 14 14 1
## 3 MX001 Abarro… 2020-06-19 08 BIMBO GRUPO … Rebana… 5 5 1
## 4 MX001 Abarro… 2020-06-19 08 PEPSI PEPSI-… Pepsi … 8 8 1
## 5 MX001 Abarro… 2020-06-19 08 BLAN… FABRIC… Deterg… 19.5 15 1
## 6 MX001 Abarro… 2020-06-19 08 FLASH ALEN Flash … 9.5 7.31 1
## 7 MX001 Abarro… 2020-06-19 08 VARI… DANONE… Danone… 11 11 1
## 8 MX001 Abarro… 2020-06-19 08 ZOTE FABRIC… Jabon … 9.5 7.31 1
## 9 MX001 Abarro… 2020-06-19 08 ALWA… PROCTE… T Feme… 23.5 18.1 1
## 10 MX001 Abarro… 2020-06-19 03 JUMEX JUMEX Jugo D… 12 12 1
## # … with 200,610 more rows, 10 more variables: F.Ticket <int>,
## # NombreDepartamento <chr>, NombreFamilia <chr>, NombreCategoria <chr>,
## # Estado <chr>, Mts.2 <int>, Tipo.ubicación <chr>, Giro <chr>,
## # Hora.inicio <chr>, Hora.cierre <chr>, and abbreviated variable names
## # ¹vcClaveTienda, ²DescGiro, ³Fabricante, ⁴Producto, ⁵Ult.Costo, ⁶Unidadesbd7$Hora <- as.integer(bd7$Hora)
str(bd7)## 'data.frame': 200620 obs. of 20 variables:
## $ vcClaveTienda : chr "MX001" "MX001" "MX001" "MX001" ...
## $ DescGiro : chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ Fecha : Date, format: "2020-06-19" "2020-06-19" ...
## $ Hora : int 8 8 8 8 8 8 8 8 8 3 ...
## $ Marca : chr "NUTRI LECHE" "DAN UP" "BIMBO" "PEPSI" ...
## $ Fabricante : chr "MEXILAC" "DANONE DE MEXICO" "GRUPO BIMBO" "PEPSI-COLA MEXICANA" ...
## $ Producto : chr "Nutri Leche 1 Litro" "DANUP STRAWBERRY P/BEBER 350GR NAL" "Rebanadas Bimbo 2Pz" "Pepsi N.R. 400Ml" ...
## $ Precio : num 16 14 5 8 19.5 9.5 11 9.5 23.5 12 ...
## $ Ult.Costo : num 12.3 14 5 8 15 ...
## $ Unidades : num 1 1 1 1 1 1 1 1 1 1 ...
## $ F.Ticket : int 1 2 3 3 4 4 4 4 4 5 ...
## $ NombreDepartamento: chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ NombreFamilia : chr "Lacteos y Refrigerados" "Lacteos y Refrigerados" "Pan y Tortilla" "Bebidas" ...
## $ NombreCategoria : chr "Leche" "Yogurt" "Pan Dulce Empaquetado" "Refrescos Plástico (N.R.)" ...
## $ Estado : chr "Nuevo León" "Nuevo León" "Nuevo León" "Nuevo León" ...
## $ Mts.2 : int 60 60 60 60 60 60 60 60 60 60 ...
## $ Tipo.ubicación : chr "Esquina" "Esquina" "Esquina" "Esquina" ...
## $ Giro : chr "Abarrotes" "Abarrotes" "Abarrotes" "Abarrotes" ...
## $ Hora.inicio : chr "8:00" "8:00" "8:00" "8:00" ...
## $ Hora.cierre : chr "22:00" "22:00" "22:00" "22:00" ...Tecnica 5. Valores faltantes
Cuantas NA tengo en la base de datos?
sum(is.na(bd7))## [1] 0sum(is.na(bd))## [1] 199188Cuantos NA tengo por variable?
sapply(bd7, function(x) sum(is.na(x)))## vcClaveTienda DescGiro Fecha Hora
## 0 0 0 0
## Marca Fabricante Producto Precio
## 0 0 0 0
## Ult.Costo Unidades F.Ticket NombreDepartamento
## 0 0 0 0
## NombreFamilia NombreCategoria Estado Mts.2
## 0 0 0 0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## 0 0 0 0sapply(bd, function(x) sum(is.na(x)))## vcClaveTienda DescGiro Codigo.Barras PLU
## 0 0 0 199188
## Fecha Hora Marca Fabricante
## 0 0 0 0
## Producto Precio Ult.Costo Unidades
## 0 0 0 0
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## 0 0 0 0
## Estado Mts.2 Tipo.ubicación Giro
## 0 0 0 0
## Hora.inicio Hora.cierre
## 0 0Borrar todos los registros NA de una tabla
bd8<- bd
bd8<- na.omit(bd8)
summary(bd8)## vcClaveTienda DescGiro Codigo.Barras PLU
## Length:1437 Length:1437 Min. :6.750e+08 Min. : 1.000
## Class :character Class :character 1st Qu.:6.750e+08 1st Qu.: 1.000
## Mode :character Mode :character Median :6.750e+08 Median : 1.000
## Mean :2.616e+11 Mean : 2.112
## 3rd Qu.:6.750e+08 3rd Qu.: 1.000
## Max. :7.501e+12 Max. :30.000
## Fecha Hora Marca Fabricante
## Length:1437 Length:1437 Length:1437 Length:1437
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Producto Precio Ult.Costo Unidades
## Length:1437 Min. :30.00 Min. : 1.00 Min. :1.000
## Class :character 1st Qu.:90.00 1st Qu.:64.62 1st Qu.:1.000
## Mode :character Median :90.00 Median :64.62 Median :1.000
## Mean :87.94 Mean :56.65 Mean :1.124
## 3rd Qu.:90.00 3rd Qu.:64.62 3rd Qu.:1.000
## Max. :90.00 Max. :64.62 Max. :7.000
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## Min. : 772 Length:1437 Length:1437 Length:1437
## 1st Qu.: 99955 Class :character Class :character Class :character
## Median :102493 Mode :character Mode :character Mode :character
## Mean :100595
## 3rd Qu.:106546
## Max. :118356
## Estado Mts.2 Tipo.ubicación Giro
## Length:1437 Min. :58.00 Length:1437 Length:1437
## Class :character 1st Qu.:58.00 Class :character Class :character
## Mode :character Median :58.00 Mode :character Mode :character
## Mean :58.07
## 3rd Qu.:58.00
## Max. :60.00
## Hora.inicio Hora.cierre
## Length:1437 Length:1437
## Class :character Class :character
## Mode :character Mode :character
##
##
## Reemplazar NA con CEROS
bd9 <- bd
bd9[is.na(bd9)] <- 0
summary(bd9)## vcClaveTienda DescGiro Codigo.Barras PLU
## Length:200625 Length:200625 Min. :8.347e+05 Min. : 0.00000
## Class :character Class :character 1st Qu.:7.501e+12 1st Qu.: 0.00000
## Mode :character Mode :character Median :7.501e+12 Median : 0.00000
## Mean :5.950e+12 Mean : 0.01513
## 3rd Qu.:7.501e+12 3rd Qu.: 0.00000
## Max. :1.750e+13 Max. :30.00000
## Fecha Hora Marca Fabricante
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Producto Precio Ult.Costo Unidades
## Length:200625 Min. :-147.00 Min. : 0.38 Min. : 0.200
## Class :character 1st Qu.: 11.00 1st Qu.: 8.46 1st Qu.: 1.000
## Mode :character Median : 16.00 Median : 12.31 Median : 1.000
## Mean : 19.42 Mean : 15.31 Mean : 1.262
## 3rd Qu.: 25.00 3rd Qu.: 19.23 3rd Qu.: 1.000
## Max. :1000.00 Max. :769.23 Max. :96.000
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## Min. : 1 Length:200625 Length:200625 Length:200625
## 1st Qu.: 33964 Class :character Class :character Class :character
## Median :105993 Mode :character Mode :character Mode :character
## Mean :193990
## 3rd Qu.:383005
## Max. :450040
## Estado Mts.2 Tipo.ubicación Giro
## Length:200625 Min. :47.0 Length:200625 Length:200625
## Class :character 1st Qu.:53.0 Class :character Class :character
## Mode :character Median :60.0 Mode :character Mode :character
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Hora.inicio Hora.cierre
## Length:200625 Length:200625
## Class :character Class :character
## Mode :character Mode :character
##
##
## Reemplazar NA con el promedio
bd10 <- bd
bd10$PLU[is.na(bd10$PLU)]<-mean(bd10$PLU, na.rm = TRUE)
summary(bd10)## vcClaveTienda DescGiro Codigo.Barras PLU
## Length:200625 Length:200625 Min. :8.347e+05 Min. : 1.000
## Class :character Class :character 1st Qu.:7.501e+12 1st Qu.: 2.112
## Mode :character Mode :character Median :7.501e+12 Median : 2.112
## Mean :5.950e+12 Mean : 2.112
## 3rd Qu.:7.501e+12 3rd Qu.: 2.112
## Max. :1.750e+13 Max. :30.000
## Fecha Hora Marca Fabricante
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Producto Precio Ult.Costo Unidades
## Length:200625 Min. :-147.00 Min. : 0.38 Min. : 0.200
## Class :character 1st Qu.: 11.00 1st Qu.: 8.46 1st Qu.: 1.000
## Mode :character Median : 16.00 Median : 12.31 Median : 1.000
## Mean : 19.42 Mean : 15.31 Mean : 1.262
## 3rd Qu.: 25.00 3rd Qu.: 19.23 3rd Qu.: 1.000
## Max. :1000.00 Max. :769.23 Max. :96.000
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## Min. : 1 Length:200625 Length:200625 Length:200625
## 1st Qu.: 33964 Class :character Class :character Class :character
## Median :105993 Mode :character Mode :character Mode :character
## Mean :193990
## 3rd Qu.:383005
## Max. :450040
## Estado Mts.2 Tipo.ubicación Giro
## Length:200625 Min. :47.0 Length:200625 Length:200625
## Class :character 1st Qu.:53.0 Class :character Class :character
## Mode :character Median :60.0 Mode :character Mode :character
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Hora.inicio Hora.cierre
## Length:200625 Length:200625
## Class :character Class :character
## Mode :character Mode :character
##
##
## Reemplazar negativos con cero
bd11<-bd
bd11[bd11<0]<-0
summary(bd11)## vcClaveTienda DescGiro Codigo.Barras PLU
## Length:200625 Length:200625 Min. :8.347e+05 Min. : 1.00
## Class :character Class :character 1st Qu.:7.501e+12 1st Qu.: 1.00
## Mode :character Mode :character Median :7.501e+12 Median : 1.00
## Mean :5.950e+12 Mean : 2.11
## 3rd Qu.:7.501e+12 3rd Qu.: 1.00
## Max. :1.750e+13 Max. :30.00
## NA's :199188
## Fecha Hora Marca Fabricante
## Length:200625 Length:200625 Length:200625 Length:200625
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Producto Precio Ult.Costo Unidades
## Length:200625 Min. : 0.00 Min. : 0.38 Min. : 0.200
## Class :character 1st Qu.: 11.00 1st Qu.: 8.46 1st Qu.: 1.000
## Mode :character Median : 16.00 Median : 12.31 Median : 1.000
## Mean : 19.44 Mean : 15.31 Mean : 1.262
## 3rd Qu.: 25.00 3rd Qu.: 19.23 3rd Qu.: 1.000
## Max. :1000.00 Max. :769.23 Max. :96.000
##
## F.Ticket NombreDepartamento NombreFamilia NombreCategoria
## Min. : 1 Length:200625 Length:200625 Length:200625
## 1st Qu.: 33964 Class :character Class :character Class :character
## Median :105993 Mode :character Mode :character Mode :character
## Mean :193990
## 3rd Qu.:383005
## Max. :450040
##
## Estado Mts.2 Tipo.ubicación Giro
## Length:200625 Min. :47.0 Length:200625 Length:200625
## Class :character 1st Qu.:53.0 Class :character Class :character
## Mode :character Median :60.0 Mode :character Mode :character
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
##
## Hora.inicio Hora.cierre
## Length:200625 Length:200625
## Class :character Class :character
## Mode :character Mode :character
##
##
##
## Técnica 6. Método estadístico
bd12<-bd7
boxplot(bd12$Precio, horizontal = TRUE)
boxplot(bd12$Unidades, horizontal = TRUE)
Agregar columnas
#install.packages("lubridate")
library(lubridate)##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, unionbd12$Dia_de_la_Semana <- wday(bd12$Fecha)
summary(bd12)## vcClaveTienda DescGiro Fecha Hora
## Length:200620 Length:200620 Min. :2020-05-01 Min. : 1.000
## Class :character Class :character 1st Qu.:2020-06-06 1st Qu.: 5.000
## Mode :character Mode :character Median :2020-07-11 Median : 8.000
## Mean :2020-07-18 Mean : 7.299
## 3rd Qu.:2020-08-29 3rd Qu.:10.000
## Max. :2020-11-11 Max. :12.000
## Marca Fabricante Producto Precio
## Length:200620 Length:200620 Length:200620 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 1.000 Min. : 1 Length:200620
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33967 Class :character
## Median : 12.31 Median : 1.000 Median :105996 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193994
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383008
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200620 Length:200620 Length:200620 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Dia_de_la_Semana
## Min. :1.000
## 1st Qu.:2.000
## Median :4.000
## Mean :3.912
## 3rd Qu.:6.000
## Max. :7.000bd12$Subtotal <- bd12$Precio * bd12$Unidades
summary(bd12)## vcClaveTienda DescGiro Fecha Hora
## Length:200620 Length:200620 Min. :2020-05-01 Min. : 1.000
## Class :character Class :character 1st Qu.:2020-06-06 1st Qu.: 5.000
## Mode :character Mode :character Median :2020-07-11 Median : 8.000
## Mean :2020-07-18 Mean : 7.299
## 3rd Qu.:2020-08-29 3rd Qu.:10.000
## Max. :2020-11-11 Max. :12.000
## Marca Fabricante Producto Precio
## Length:200620 Length:200620 Length:200620 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 1.000 Min. : 1 Length:200620
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33967 Class :character
## Median : 12.31 Median : 1.000 Median :105996 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193994
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383008
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200620 Length:200620 Length:200620 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Dia_de_la_Semana Subtotal
## Min. :1.000 Min. : 1.00
## 1st Qu.:2.000 1st Qu.: 12.00
## Median :4.000 Median : 18.00
## Mean :3.912 Mean : 24.33
## 3rd Qu.:6.000 3rd Qu.: 27.00
## Max. :7.000 Max. :2496.00bd12$Utilidad <- bd12$Precio - bd12$Ult.Costo
summary(bd12)## vcClaveTienda DescGiro Fecha Hora
## Length:200620 Length:200620 Min. :2020-05-01 Min. : 1.000
## Class :character Class :character 1st Qu.:2020-06-06 1st Qu.: 5.000
## Mode :character Mode :character Median :2020-07-11 Median : 8.000
## Mean :2020-07-18 Mean : 7.299
## 3rd Qu.:2020-08-29 3rd Qu.:10.000
## Max. :2020-11-11 Max. :12.000
## Marca Fabricante Producto Precio
## Length:200620 Length:200620 Length:200620 Min. : 0.50
## Class :character Class :character Class :character 1st Qu.: 11.00
## Mode :character Mode :character Mode :character Median : 16.00
## Mean : 19.45
## 3rd Qu.: 25.00
## Max. :1000.00
## Ult.Costo Unidades F.Ticket NombreDepartamento
## Min. : 0.38 Min. : 1.000 Min. : 1 Length:200620
## 1st Qu.: 8.46 1st Qu.: 1.000 1st Qu.: 33967 Class :character
## Median : 12.31 Median : 1.000 Median :105996 Mode :character
## Mean : 15.31 Mean : 1.262 Mean :193994
## 3rd Qu.: 19.23 3rd Qu.: 1.000 3rd Qu.:383008
## Max. :769.23 Max. :96.000 Max. :450040
## NombreFamilia NombreCategoria Estado Mts.2
## Length:200620 Length:200620 Length:200620 Min. :47.0
## Class :character Class :character Class :character 1st Qu.:53.0
## Mode :character Mode :character Mode :character Median :60.0
## Mean :56.6
## 3rd Qu.:60.0
## Max. :62.0
## Tipo.ubicación Giro Hora.inicio Hora.cierre
## Length:200620 Length:200620 Length:200620 Length:200620
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Dia_de_la_Semana Subtotal Utilidad
## Min. :1.000 Min. : 1.00 Min. : 0.000
## 1st Qu.:2.000 1st Qu.: 12.00 1st Qu.: 2.310
## Median :4.000 Median : 18.00 Median : 3.230
## Mean :3.912 Mean : 24.33 Mean : 4.142
## 3rd Qu.:6.000 3rd Qu.: 27.00 3rd Qu.: 5.420
## Max. :7.000 Max. :2496.00 Max. :230.770Exportar base de datos limpia
bd_limpia <- bd12
write.csv(bd_limpia, file="abarrotes_bd_limpia.csv", row.names= FALSE)Market basket Analysis
#install.packages("plyr")
library(Matrix)##
## Attaching package: 'Matrix'## The following objects are masked from 'package:tidyr':
##
## expand, pack, unpacklibrary(arules)##
## Attaching package: 'arules'## The following object is masked from 'package:dplyr':
##
## recode## The following objects are masked from 'package:base':
##
## abbreviate, write#install.packages("arules")
#install.packages("arulesViz")
library(arules)
library(datasets)
library(arulesViz)Ordenar de menor a mayor los Tickets
bd_limpia <- bd_limpia[order(bd_limpia$F.Ticket),]
head(bd_limpia)## 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 Lavandería Nuevo León 60 Esquina Abarrotes
## 6 Limpiadores Líquidos Nuevo León 60 Esquina Abarrotes
## Hora.inicio Hora.cierre Dia_de_la_Semana Subtotal Utilidad
## 1 8:00 22:00 6 16.0 3.69
## 2 8:00 22:00 6 14.0 0.00
## 3 8:00 22:00 6 5.0 0.00
## 4 8:00 22:00 6 8.0 0.00
## 5 8:00 22:00 6 19.5 4.50
## 6 8:00 22:00 6 9.5 2.19tail(bd_limpia)## vcClaveTienda DescGiro Fecha Hora Marca
## 107394 MX004 Carnicería 2020-10-15 11 YEMINA
## 167771 MX004 Carnicería 2020-10-15 11 DEL FUERTE
## 149429 MX004 Carnicería 2020-10-15 11 COCA COLA ZERO
## 168750 MX004 Carnicería 2020-10-15 11 DIAMANTE
## 161193 MX004 Carnicería 2020-10-15 12 PEPSI
## 112970 MX004 Carnicería 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 7:00 23:00 5 14 1.62
## 167771 7:00 23:00 5 12 2.77
## 149429 7:00 23:00 5 30 3.46
## 168750 7:00 23:00 5 11 2.54
## 161193 7:00 23:00 5 10 2.31
## 112970 7:00 23:00 5 80 2.31Generar basket
#install.packages("plyr")
library(plyr)## ------------------------------------------------------------------------------## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)## ------------------------------------------------------------------------------##
## Attaching package: 'plyr'## The following object is masked from 'package:purrr':
##
## compact## The following objects are masked from 'package:dplyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarizebasket <- ddply(bd_limpia,c("F.Ticket"), function(bd_limpia)paste(bd_limpia$Marca, collapse = ","))Eliminar el número de ticket
basket$F.Ticket<-NULLRenombramos el nombre de la columna
colnames(basket)<- c ("Marca")Exportar basket
write.csv(basket,"basket.csv", quote = FALSE, row.names = FALSE)Importar transacciones
#file.choose()
tr<- read.transactions("/Users/isaacdiazruizdechavez/basket.csv", format="basket", sep = ,)## 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 ...[27312 item(s), 115111 transaction(s)] done [0.17s].
## sorting and recoding items ... [191 item(s)] done [0.01s].
## creating transaction tree ... done [0.05s].
## checking subsets of size 1 2 3 4 done [0.00s].
## writing ... [139 rule(s)] done [0.00s].
## creating S4 object ... done [0.04s].#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")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