Segmentacion Mercado K-meansClus SV
José Ramón A01625203
20-09-2022
Supermercado Ventas
Importar la base de datos
#file.choose()
bd <- read.csv("/Users/joseramonvazquezguzman/Documents/Tecnológico de Monterrey/Septimo semestre/Analítica de datos /M3/datos_clientes.csv") Herramienta “El generador de valor de Datos”
Paso 1. Definir el área del negocio que buscamos impactar y mejorar su KPI.
Se desea impactar el área de ventas y como KPI la retención del cliente e incremento en ventas.
Paso 2. Seleccionar plantilla (-s) para crear valor a partir de los datos de los clientes
Segmentación
Paso 3. Generar ideas o conceptos específicos
Estrategia para retener al cliente y aumentar la venta de productos dentro del supermercado
Paso 4. Reunir los datos requeridos
Base de datos limpia sobre tickets de compra del cliente
Paso 5. Plan de ejecución:
Limpiar base de datos para poderla analizar, segmentar a los clusters de los clientes, interpretar los resultados y generar estrategias para obtener un beneficio en las ventas del negocio.
Agregar el CustomerID como nombre de los renglones
bd2 <- bd
rownames(bd2) <- bd2$CustomerIDEliminar la columna de CustomerID
bd3 <- bd2
bd3 <- subset (bd3, select = -c(CustomerID))Revisar presencia de datos anormales
summary(bd3)## Total Visitas
## Min. : 3.45 Min. : 1.000
## 1st Qu.: 178.30 1st Qu.: 1.000
## Median : 292.00 Median : 2.000
## Mean : 415.62 Mean : 4.227
## 3rd Qu.: 426.63 3rd Qu.: 5.000
## Max. :84236.25 Max. :209.000plot(bd3$Total, bd3$Visitas)
Notas
#Los datos fuera de lo normal están fuera de los siguientes límites
#Límite Inferior = Q1 - 1.5*IQR
#Límite Superior = Q3 + 1.5*IQR
#Q1: Cuartil 1, Q3: Cuartil 3, IQR: Rango Intercuartil = Q3 - Q1Calcular el límite superior del Total
iqr_total <- IQR(bd3$Total)
limite_superior_total <- 426.63 + 1.5*iqr_total
limite_superior_total## [1] 799.1277Conservar sólo los tickets promedios menores a 800
bd4 <- bd3
bd4 <- bd4[bd4$Total < 800, ]
summary(bd4)## Total Visitas
## Min. : 3.45 Min. : 1.000
## 1st Qu.:172.96 1st Qu.: 1.000
## Median :272.23 Median : 2.000
## Mean :298.21 Mean : 4.125
## 3rd Qu.:390.24 3rd Qu.: 5.000
## Max. :799.62 Max. :209.000Calcular el límite superior de visites
iqr_Visitas <- IQR(bd3$Visitas)
limite_superior_visitas <- 5 + 1.5*iqr_Visitas
limite_superior_visitas## [1] 11Conservar sólo las visitas menores a 12
bd5 <- bd4
bd5 <- bd5[bd5$Visitas < 12, ]
summary(bd5)## Total Visitas
## Min. : 3.45 Min. : 1.000
## 1st Qu.:168.67 1st Qu.: 1.000
## Median :267.13 Median : 2.000
## Mean :293.99 Mean : 2.971
## 3rd Qu.:384.80 3rd Qu.: 4.000
## Max. :799.62 Max. :11.000plot(bd5$Total, bd5$Visitas)
k-means clustering
Normalizar variables
bd6 <- bd5
bd6 <- as.data.frame(scale(bd6))
plot(bd6$Total, bd6$Visitas)
Paso 2. k-means clustering
segmentos <- kmeans(bd6, 3)
segmentos## K-means clustering with 3 clusters of sizes 2093, 999, 677
##
## Cluster means:
## Total Visitas
## 1 -0.6143925 -0.4369737
## 2 1.2079890 -0.2822451
## 3 0.1169018 1.7674280
##
## Clustering vector:
## 12347 12350 12352 12353 12355 12358 12361 12362 12363 12364 12370 12373 12374
## 3 1 3 1 2 2 1 3 1 1 1 2 2
## 12379 12380 12381 12383 12384 12386 12388 12390 12393 12394 12399 12401 12402
## 2 2 3 3 1 1 3 2 2 2 1 1 1
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## 3 2 2 1 1 3 2 1 1 3 2 2 1
## 12429 12430 12434 12436 12441 12442 12445 12447 12448 12450 12452 12453 12455
## 2 1 2 2 1 1 1 2 2 1 1 2 1
## 12457 12458 12461 12462 12463 12464 12465 12468 12473 12475 12476 12478 12479
## 3 2 2 2 2 3 2 2 2 2 3 2 2
## 12481 12483 12484 12488 12489 12490 12491 12492 12493 12494 12498 12500 12502
## 3 3 2 2 1 3 2 1 1 3 1 3 2
## 12504 12506 12507 12508 12509 12510 12512 12513 12515 12516 12517 12518 12519
## 1 1 2 1 1 2 1 2 2 2 2 3 1
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## 2 2 1 3 3 2 1 3 2 1 2 2 2
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## 1 2 2 2 1 1 1 1 3 1 1 1 2
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## 1 3 2 1 2 1 2 1 1 3 1 2 2
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## 1 3 1 1 2 1 1 3 1 3 3 3 1
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## 1 2 1 2 3 2 2 1 2 2 2 1 3
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## 2 1 1 1 3 3 1 2 3 2 2 2 1
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## 2 3 2 2 2 1 1 1 1 1 2 2 1
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## 1 3 1 2 1 1 2 3 1 1 3 3 1
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## 2 2 3 1 2 1 1 2 1 1 3 2 3
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## 2 2 2 2 1 1 3 1 1 1 2 3 3
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## 1 2 1 2 1 2 1 1 2 2 1 3 1
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## 1 2 1 3 3 3 2 3 1 1 1 1 1
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## 1 2 1 2 2 1 2 1 2 1 1 1 2
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## 1 1 1 1 2 3 2 3 1 3 1 1 1
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## 2 1 2 1 1 2 2 3 1 1 2 1 1
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## 2 1 2 1 1 2 1 1 2 2 1 2 1
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## 1 1 1 1 1 2 2 2 3 3 2 1 2
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## 2 3 1 2 1 1 2 3 1 1 1 3 1
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## 2 1 2 1 1 2 3 3 3 2 3 2 1
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## 3 1 3 1 3 2 1 1 1 1 2 1 1
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## 2 1 2 1 2 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 3 3 2 1 1 3 2
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## 3 1 2 2 2 1 1 2 1 1 1 2 2
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## 1 1 3 2 1 1 2 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 3 1 1 1
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## 1 1 3 1 1 1 3 1 2 2 2 3 2
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## 2 3 3 1 1 2 3 1 1 2 1 1 2
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## 2 3 3 2 1 2 1 1 1 1 1 2 2
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## 1 2 1 2 1 1 2 2 2 1 1 2 1
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## 1 1 2 1 3 1 3 3 1 2 1 1 1
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## 2 1 1 2 2 1 1 1 3 3 2 2 1
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## 3 1 1 1 1 2 1 1 1 2 1 3 1
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## 2 1 1 1 1 2 1 2 3 1 1 1 2
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## 1 1 1 2 2 1 3 3 2 1 1 1 1
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## 1 2 1 1 2 1 1 2 2 1 2 1 1
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## 2 2 1 2 1 1 1 3 1 2 3 2 1
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## 3 1 3 1 2 1 1 1 3 2 3 2 2
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## 2 2 2 2 2 2 1 1 1 2 2 2 2
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## 2 2 2 2 2 2 2 1 1 1 1 2 2
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## 2 2 1 2 1 3 2 1 1 2 1 3 1
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## 2 3 2 1 1 1 1 3 1 2 2 1 1
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## 1 2 3 1 1 1 1 2 1 3 1 3 1
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## 1 2 2 1 3 2 1 1 2 3 1 2 1
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## 2 1 2 1 2 1 1 2 2 3 1 3 1
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## 1 1 2 2 1 1 3 2 1 1 3 1 1
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## 3 2 1 1 1 1 2 1 3 2 1 1 1
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## 1 2 2 2 1 2 2 1 2 1 1 3 1
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## 1 1 1 3 3 1 1 1 1 3 1 1 1
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## 1 1 2 2 2 1 2 1 1 1 1 1 2
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## 1 1 2 1 2 3 1 3 2 1 3 2 2
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## 1 1 2 2 1 1 2 3 2 2 2 1 1
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## 1 1 1 3 3 3 3 3 3 3 1 1 2
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## 1 2 1 2 1 3 1 2 3 2 1 1 2
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## 2 1 1 1 1 1 2 1 1 1 1 1 1
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## 1 3 1 1 2 1 1 3 1 3 1 1 2
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## 1 1 1 1 3 1 3 1 3 1 2 2 1
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## 3 2 1 3 2 1 2 2 2 1 1 2 1
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## 3 2 1 1 3 3 1 3 2 1 3 3 1
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## 1 2 1 2 3 2 2 1 1 1 1 3 3
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## 1 1 2 2 1 2 2 1 1 3 2 1 1
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## 3 2 1 1 2 2 1 1 2 1 1 2 3
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## 1 1 1 3 1 2 1 1 1 1 3 2 1
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## 1 2 2 1 1 1 3 3 1 1 1 2 2
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## 3 1 2 3 1 1 3 2 1 1 1 2 1
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## 2 3 1 1 2 1 1 1 1 2 1 2 3
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## 1 1 2 1 2 3 1 1 2 1 2 1 2
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## 1 1 2 1 1 1 1 1 1 1 3 1 1
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## 3 1 1 3 1 1 1 1 1 3 1 1 2
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## 3 2 1 1 2 3 1 2 2 1 3 1 3
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## 3 3 2 2 1 3 2 1 2 1 1 2 2
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## 1 1 2 1 1 1 1 3 3 1 3 2 1
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## 2 1 1 1 2 1 3 2 2 1 1 1 2
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## 1 3 1 1 1 3 1 1 1 1 3 2 1
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## 2 1 3 1 1 1 2 1 3 1 3 1 3
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## 1 1 1 3 2 1 3 1 2 2 1 1 1
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## 3 2 3 1 2 2 2 1 1 1 1 1 2
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## 1 1 2 1 1 2 3 2 1 2 1 1 2
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## 1 1 1 1 3 2 2 1 3 2 2 1 1
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## 1 3 1 1 1 1 3 3 3 3 3 2 1
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## 1 1 3 2 1 1 2 3 2 1 3 2 1
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## 2 1 1 1 3 2 1 1 3 2 1 1 2
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## 2 2 2 1 2 3 1 1 2 2 1 1 1
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## 2 1 1 2 1 2 3 2 3 3 1 1 1
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## 3 1 2 2 2 3 3 1 3 1 3 2 1
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## 3 1 1 1 2 1 1 2 3 1 2 1 1
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## 1 3 1 3 1 2 2 1 1 1 1 1 1
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## 1 2 1 1 2 1 3 1 1 1 1 1 1
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## 1 2 2 1 1 2 3 2 3 1 3 1 2
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## 2 3 1 3 3 3 3 2 1 3 1 2 3
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## 2 2 2 1 1 3 1 3 2 3 3 1 1
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## 1 2 2 2 1 3 1 1 1 1 1 1 3
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## 1 1 2 3 1 2 3 1 1 3 1 2 1
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## 1 1 1 1 1 3 1 1 1 3 2 1 2
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## 1 1 1 2 3 1 1 1 3 2 1 3 3
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## 3 1 3 1 1 2 3 1 1 1 1 1 3
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## 3 2 1 3 1 3 1 2 1 1 1 3 1
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## 2 3 1 1 2 1 1 3 2 1 2 2 2
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## 2 1 1 3 3 1 1 1 1 1 3 1 1
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## 1 3 1 2 1 1 1 3 2 1 2 1 2
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## 2 1 1 1 2 1 3 1 3 1 2 2 1
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## 2 1 1 1 1 2 3 3 1 1 2 2 1
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## 1 2 1 1 3 2 1 1 1 3 1 1 1
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## 1 3 1 2 1 2 3 2 3 1 1 3 2
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## 1 1 3 1 1 3 1 3 1 2 3 1 3
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## 1 2 1 3 1 3 1 1 1 3 1 1 3
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## 2 1 1 3 1 3 2 3 3 2 3 3 3
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## 1 3 2 2 1 3 2 2 2 2 1 1 1
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## 1 1 3 1 2 1 2 3 2 1 1 1 1
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## 1 1 1 1 1 1 3 1 1 1 1 1 2
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## 1 1 3 3 1 2 1 2 1 1 1 1 1
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## 1 2 1 1 3 1 2 1 3 2 2 1 1
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## 1 3 1 3 1 2 2 2 1 1 2 1 1
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## 1 3 2 1 1 2 2 3 1 1 1 3 2
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## 2 2 1 1 1 2 2 1 2 3 3 1 2
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## 2 1 3 1 1 2 1 1 1 2 2 2 1
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## 1 1 1 3 2 1 3 1 1 1 1 1 1
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## 3 1 3 1 1 1 2 1 2 2 1 2 1
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## 1 3 3 1 1 1 1 1 1 1 1 2 2
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## 2 1 2 1 1 1 1 1 1 1 3 1 3
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## 3 2 1 1 1 1 1 3 3 1 1 3 1
## 15042 15043 15045 15047 15048 15049 15050 15051 15052 15053 15054 15057 15058
## 1 2 2 1 1 1 2 2 1 1 1 2 3
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## 3 1 1 2 2 2 1 1 2 2 2 2 1
## 15081 15083 15087 15088 15089 15090 15091 15092 15093 15095 15096 15097 15099
## 1 1 1 2 3 2 2 1 2 2 1 1 2
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## 1 1 2 2 3 3 3 2 1 2 3 1 2
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## 3 1 1 2 1 2 1 2 2 3 1 3 1
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## 3 1 1 1 3 2 1 1 2 2 1 2 3
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## 1 1 1 2 2 1 1 1 2 1 1 3 1
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## 1 1 2 1 1 1 1 1 1 2 2 2 1
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## 1 3 3 1 1 1 3 1 2 1 1 3 1
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## 1 3 1 3 2 2 2 1 2 1 3 1 1
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## 1 1 2 2 2 3 3 1 1 1 2 2 3
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## 1 1 1 1 3 1 1 1 2 2 1 3 2
## 15270 15272 15274 15275 15276 15277 15279 15280 15281 15286 15287 15288 15289
## 3 2 2 2 1 1 1 1 3 1 1 2 1
## 15292 15296 15297 15299 15300 15303 15304 15306 15307 15308 15312 15313 15314
## 1 2 1 3 2 2 3 2 1 1 1 1 1
## 15315 15316 15318 15319 15320 15322 15325 15326 15327 15329 15330 15332 15334
## 1 1 1 1 1 2 1 1 1 2 2 2 1
## 15335 15339 15342 15343 15344 15345 15346 15347 15348 15349 15350 15351 15353
## 1 1 2 2 1 2 1 1 1 1 1 3 2
## 15355 15356 15360 15361 15363 15364 15365 15366 15367 15368 15370 15374 15376
## 1 3 2 2 1 2 3 1 2 2 3 1 2
## 15379 15380 15381 15384 15385 15386 15389 15392 15393 15394 15395 15396 15397
## 3 3 1 1 1 2 2 2 1 2 1 1 1
## 15398 15399 15400 15402 15405 15406 15407 15408 15410 15411 15412 15414 15415
## 2 1 1 1 2 1 1 1 3 2 1 1 2
## 15417 15419 15421 15422 15423 15424 15426 15427 15428 15429 15432 15433 15434
## 2 1 1 1 1 1 3 2 1 1 1 1 3
## 15435 15436 15437 15438 15440 15442 15443 15444 15445 15447 15448 15449 15450
## 1 2 1 1 1 2 3 2 1 1 2 1 2
## 15452 15453 15454 15456 15457 15458 15460 15462 15463 15466 15467 15468 15469
## 1 3 1 1 1 1 1 1 1 1 1 1 1
## 15471 15472 15473 15475 15478 15483 15488 15489 15491 15492 15493 15494 15497
## 2 2 3 2 2 1 1 2 3 1 3 2 2
## 15500 15503 15504 15505 15506 15507 15508 15510 15511 15512 15514 15516 15517
## 1 1 1 2 1 2 3 1 3 1 3 1 1
## 15518 15520 15521 15522 15523 15524 15525 15526 15527 15528 15529 15530 15532
## 3 1 3 1 2 2 1 1 3 1 3 2 2
## 15533 15535 15537 15539 15540 15541 15543 15544 15545 15549 15550 15551 15552
## 1 1 1 2 1 1 1 3 1 2 1 2 1
## 15553 15554 15556 15557 15561 15562 15563 15565 15567 15568 15569 15571 15572
## 2 1 1 2 1 1 2 1 1 1 3 1 3
## 15573 15574 15577 15578 15579 15582 15584 15585 15587 15589 15592 15593 15594
## 1 1 1 1 1 1 1 2 1 1 2 1 3
## 15596 15597 15598 15599 15602 15603 15604 15605 15606 15607 15608 15609 15610
## 3 1 1 2 3 1 1 3 3 1 1 1 1
## 15612 15618 15619 15620 15621 15622 15623 15624 15625 15626 15628 15630 15632
## 1 1 1 2 1 3 1 1 2 1 3 2 3
## 15634 15636 15637 15639 15641 15643 15644 15645 15646 15648 15649 15651 15652
## 1 2 1 2 2 1 1 2 1 1 2 1 1
## 15653 15654 15655 15656 15657 15658 15659 15660 15661 15663 15664 15667 15668
## 2 2 2 1 1 3 1 3 1 1 2 1 1
## 15669 15670 15671 15673 15674 15675 15677 15678 15679 15680 15681 15683 15687
## 1 1 3 2 2 1 2 2 1 2 3 1 3
## 15689 15690 15691 15692 15695 15696 15699 15700 15701 15703 15704 15705 15706
## 1 1 1 1 1 3 1 2 2 1 2 1 1
## 15707 15708 15709 15712 15713 15714 15716 15717 15720 15721 15722 15723 15724
## 1 3 1 3 1 1 1 1 2 2 2 1 1
## 15725 15727 15729 15730 15732 15733 15734 15737 15739 15740 15743 15744 15745
## 2 2 1 2 1 1 2 3 2 1 1 1 1
## 15746 15747 15748 15750 15752 15753 15754 15755 15756 15757 15758 15759 15762
## 1 1 1 3 3 1 1 3 1 2 1 1 1
## 15763 15764 15766 15768 15773 15774 15775 15776 15777 15780 15781 15783 15785
## 2 3 1 1 2 1 1 1 1 1 1 1 2
## 15787 15789 15790 15793 15795 15796 15797 15799 15800 15801 15802 15803 15806
## 1 2 1 1 2 3 2 1 2 2 2 2 1
## 15807 15809 15810 15811 15812 15813 15814 15815 15819 15820 15821 15822 15823
## 1 1 2 3 3 2 2 3 2 1 1 2 1
## 15825 15826 15829 15830 15831 15834 15835 15836 15837 15839 15840 15841 15843
## 2 2 1 2 1 2 1 1 2 2 1 1 1
## 15844 15845 15847 15850 15852 15853 15855 15857 15858 15860 15861 15862 15863
## 1 3 1 1 1 1 1 1 3 3 3 1 1
## 15864 15865 15866 15869 15870 15872 15874 15877 15880 15881 15882 15883 15885
## 3 1 1 1 2 1 3 1 1 1 1 1 1
## 15886 15888 15889 15891 15894 15895 15897 15898 15899 15900 15901 15903 15904
## 1 1 1 2 1 1 1 3 1 2 1 2 1
## 15906 15907 15909 15910 15912 15916 15917 15918 15919 15920 15921 15922 15923
## 3 1 1 3 1 3 1 1 1 1 1 2 1
## 15925 15930 15932 15933 15935 15937 15938 15940 15942 15944 15945 15948 15949
## 1 2 3 2 1 1 1 1 1 1 1 2 1
## 15950 15951 15952 15953 15957 15958 15963 15965 15967 15969 15970 15973 15974
## 2 2 1 3 2 1 1 1 1 1 1 1 3
## 15975 15976 15977 15980 15981 15983 15984 15985 15986 15987 15988 15990 15992
## 2 1 2 2 3 2 3 2 1 3 1 2 1
## 15993 15994 15996 15998 16003 16005 16006 16007 16008 16009 16010 16012 16014
## 3 2 3 2 2 1 1 2 1 1 1 2 1
## 16015 16016 16017 16018 16019 16020 16022 16023 16024 16025 16026 16027 16030
## 1 3 1 1 3 1 2 1 1 2 1 3 1
## 16031 16034 16036 16037 16038 16040 16042 16043 16045 16048 16049 16050 16052
## 1 1 2 1 1 2 3 1 2 1 2 1 2
## 16053 16054 16055 16056 16057 16059 16062 16063 16065 16066 16070 16071 16072
## 2 2 1 2 3 3 1 1 2 3 2 1 2
## 16073 16076 16078 16079 16080 16081 16083 16084 16085 16086 16091 16092 16093
## 1 3 1 2 1 2 2 2 3 3 1 1 1
## 16094 16096 16097 16098 16099 16102 16103 16104 16105 16106 16107 16109 16110
## 1 1 1 3 1 2 3 1 1 1 3 1 2
## 16112 16113 16114 16115 16116 16117 16119 16120 16121 16122 16123 16124 16125
## 1 1 1 3 2 1 1 1 2 1 1 1 1
## 16127 16128 16131 16134 16135 16136 16139 16140 16141 16142 16143 16144 16145
## 2 3 2 1 2 1 1 2 2 2 3 1 3
## 16146 16147 16148 16149 16150 16153 16156 16157 16159 16160 16162 16163 16164
## 1 2 1 1 3 3 3 1 1 2 1 2 1
## 16169 16170 16171 16172 16173 16174 16175 16177 16178 16179 16181 16183 16184
## 2 3 1 3 3 1 1 1 1 1 1 1 3
## 16185 16188 16189 16190 16193 16198 16200 16201 16202 16203 16204 16205 16206
## 1 1 1 1 1 2 2 2 2 1 2 1 1
## 16207 16208 16209 16211 16212 16213 16214 16215 16217 16218 16221 16224 16225
## 2 1 2 2 2 1 2 1 1 3 1 1 3
## 16226 16227 16229 16230 16232 16233 16235 16236 16239 16242 16243 16244 16245
## 1 1 2 1 1 1 3 2 1 3 1 2 2
## 16247 16248 16249 16250 16255 16256 16257 16261 16265 16266 16268 16271 16272
## 1 1 3 1 3 2 1 1 3 3 1 3 2
## 16274 16275 16278 16279 16282 16283 16284 16287 16292 16293 16295 16297 16298
## 2 2 2 2 1 3 2 1 1 3 2 1 1
## 16302 16305 16306 16308 16309 16311 16313 16315 16316 16317 16318 16319 16320
## 1 2 3 2 2 1 1 1 3 2 1 2 2
## 16321 16322 16323 16324 16325 16327 16330 16332 16337 16338 16339 16340 16341
## 1 1 1 1 1 2 1 3 1 1 1 2 2
## 16342 16343 16344 16345 16347 16348 16349 16350 16351 16352 16354 16356 16357
## 1 1 1 2 2 3 1 1 1 1 1 1 1
## 16358 16359 16360 16361 16362 16363 16364 16365 16366 16367 16368 16369 16370
## 2 3 2 1 1 1 2 3 1 2 1 2 1
## 16372 16374 16376 16377 16378 16379 16383 16384 16385 16386 16387 16389 16392
## 1 1 2 2 1 2 1 1 1 1 1 2 1
## 16394 16395 16399 16400 16402 16403 16404 16405 16406 16407 16409 16411 16412
## 3 3 1 1 1 1 2 1 1 3 3 1 1
## 16413 16414 16415 16416 16418 16419 16423 16424 16425 16426 16427 16429 16430
## 1 1 1 2 1 3 1 1 1 3 1 1 1
## 16431 16432 16433 16434 16438 16440 16441 16442 16444 16445 16447 16448 16449
## 1 1 1 3 1 2 1 1 1 1 1 1 2
## 16450 16451 16454 16455 16456 16457 16460 16461 16462 16463 16464 16466 16468
## 1 1 1 3 3 1 1 1 1 2 2 3 1
## 16469 16470 16471 16473 16474 16475 16477 16478 16479 16480 16482 16483 16484
## 1 1 1 1 3 1 3 1 1 2 1 1 1
## 16485 16488 16491 16493 16495 16496 16497 16498 16499 16500 16503 16504 16505
## 2 1 2 2 1 2 3 1 1 3 2 2 2
## 16506 16509 16510 16511 16513 16515 16516 16517 16518 16519 16520 16526 16527
## 1 2 1 1 1 3 1 1 1 1 2 1 1
## 16528 16529 16531 16533 16535 16536 16539 16542 16545 16546 16549 16550 16551
## 1 2 3 2 2 2 2 1 1 2 3 2 1
## 16552 16554 16555 16556 16557 16560 16561 16565 16566 16567 16569 16570 16571
## 1 1 1 3 1 2 1 1 1 2 1 3 2
## 16572 16573 16574 16581 16582 16583 16584 16586 16587 16589 16591 16593 16594
## 1 1 2 1 1 1 2 2 1 1 1 1 1
## 16595 16596 16597 16598 16600 16601 16602 16603 16609 16610 16611 16612 16613
## 2 1 1 1 3 1 2 1 2 1 1 1 2
## 16614 16616 16617 16618 16619 16620 16621 16623 16624 16625 16627 16628 16629
## 2 1 1 2 1 1 1 1 2 1 1 2 1
## 16633 16634 16637 16638 16639 16641 16642 16643 16644 16647 16648 16650 16653
## 3 1 1 3 2 1 2 2 2 1 1 2 2
## 16654 16655 16657 16658 16659 16660 16665 16666 16667 16668 16669 16670 16671
## 1 2 1 1 1 1 1 1 1 3 2 3 2
## 16674 16676 16679 16680 16681 16682 16685 16686 16688 16689 16690 16692 16693
## 1 2 1 1 3 3 1 3 1 1 1 2 1
## 16696 16697 16706 16708 16709 16710 16711 16712 16714 16715 16716 16717 16718
## 1 1 1 2 2 3 3 3 2 1 2 2 2
## 16719 16720 16721 16723 16725 16726 16727 16728 16730 16732 16734 16735 16737
## 3 1 1 1 3 3 1 1 1 2 1 2 2
## 16738 16739 16742 16743 16744 16747 16748 16750 16752 16753 16755 16756 16757
## 1 1 2 3 3 2 3 1 1 1 2 1 1
## 16758 16759 16761 16762 16763 16765 16766 16767 16768 16769 16770 16771 16773
## 2 1 1 2 2 1 2 3 1 2 1 2 1
## 16774 16775 16776 16777 16778 16780 16781 16784 16788 16789 16790 16791 16792
## 1 3 2 1 1 1 1 1 1 1 3 3 1
## 16793 16794 16795 16796 16801 16803 16804 16805 16806 16807 16808 16809 16810
## 1 3 2 1 2 1 1 1 1 2 1 3 1
## 16811 16812 16813 16816 16817 16818 16820 16823 16824 16825 16826 16828 16829
## 1 2 3 1 3 3 2 2 1 2 1 1 1
## 16830 16832 16833 16834 16835 16836 16837 16838 16841 16842 16846 16847 16848
## 1 1 1 2 1 1 3 1 3 2 1 1 1
## 16849 16850 16851 16852 16855 16856 16858 16859 16861 16863 16866 16869 16871
## 1 1 1 1 1 1 2 2 1 1 1 1 3
## 16872 16875 16877 16878 16880 16881 16882 16883 16884 16885 16887 16889 16891
## 1 3 3 1 3 2 1 1 1 1 1 2 1
## 16892 16893 16895 16897 16898 16899 16900 16903 16905 16906 16907 16909 16910
## 1 1 1 1 1 3 1 2 3 1 3 2 3
## 16912 16913 16914 16915 16916 16917 16918 16919 16921 16924 16926 16927 16929
## 3 1 1 3 1 2 3 3 1 1 1 1 3
## 16930 16932 16933 16934 16936 16938 16942 16943 16947 16948 16949 16950 16951
## 1 1 1 2 1 2 3 1 2 1 3 2 2
## 16952 16953 16954 16955 16956 16957 16959 16960 16961 16963 16965 16966 16967
## 1 1 3 1 1 1 1 1 1 1 1 3 1
## 16968 16969 16971 16976 16978 16979 16980 16982 16983 16985 16987 16988 16989
## 1 1 2 1 1 3 2 2 3 3 3 1 3
## 16990 16992 16996 16997 16998 16999 17001 17002 17004 17006 17007 17010 17011
## 1 3 3 1 1 1 3 2 2 1 3 1 1
## 17014 17015 17018 17019 17022 17024 17025 17026 17027 17029 17030 17031 17033
## 1 2 2 1 1 1 1 1 3 2 1 1 2
## 17034 17035 17038 17040 17041 17042 17043 17045 17046 17047 17048 17049 17050
## 1 1 1 2 2 3 2 1 2 2 1 3 3
## 17051 17052 17053 17054 17058 17059 17060 17061 17062 17063 17064 17069 17070
## 1 2 2 3 2 2 1 3 1 3 1 3 1
## 17071 17073 17075 17076 17078 17079 17080 17081 17083 17085 17086 17088 17090
## 3 2 1 1 1 1 1 1 2 3 3 2 3
## 17091 17092 17094 17095 17096 17097 17100 17101 17102 17105 17109 17110 17111
## 3 2 1 2 1 3 2 2 1 1 3 1 1
## 17114 17115 17117 17118 17119 17120 17122 17123 17124 17125 17126 17128 17131
## 3 1 1 1 1 1 1 1 1 1 3 1 2
## 17133 17134 17135 17138 17140 17142 17144 17146 17147 17148 17152 17153 17154
## 2 1 3 2 2 2 2 1 2 1 2 1 1
## 17155 17157 17158 17159 17160 17162 17163 17164 17165 17166 17169 17171 17172
## 1 1 2 2 2 3 1 3 1 1 2 1 1
## 17173 17174 17175 17176 17179 17180 17181 17183 17186 17187 17188 17189 17190
## 3 1 2 1 1 1 1 3 1 1 3 1 1
## 17191 17193 17194 17198 17201 17203 17204 17205 17206 17211 17212 17213 17214
## 3 3 1 1 1 2 2 2 1 3 1 3 3
## 17217 17218 17219 17221 17222 17223 17226 17227 17228 17229 17230 17231 17232
## 1 3 1 1 2 1 2 3 3 1 3 3 1
## 17233 17234 17235 17236 17237 17239 17242 17245 17247 17248 17250 17251 17252
## 1 1 1 3 1 2 2 1 1 1 1 1 1
## 17253 17254 17255 17256 17259 17262 17263 17265 17266 17267 17268 17272 17274
## 1 1 1 1 1 3 1 1 1 1 1 2 1
## 17277 17278 17279 17282 17284 17286 17287 17288 17289 17290 17291 17293 17295
## 2 1 1 2 3 1 3 3 1 1 2 3 1
## 17297 17298 17299 17301 17302 17303 17309 17311 17312 17314 17320 17321 17323
## 1 1 1 1 3 1 1 2 1 3 2 2 3
## 17324 17325 17329 17330 17331 17333 17334 17337 17339 17341 17343 17344 17345
## 1 1 1 1 1 2 1 2 1 1 1 1 1
## 17347 17348 17349 17350 17351 17356 17357 17358 17359 17360 17361 17362 17364
## 1 3 1 1 1 1 1 1 1 1 1 1 3
## 17365 17367 17368 17370 17371 17372 17373 17374 17375 17376 17379 17382 17383
## 3 1 3 1 1 3 1 1 1 1 2 1 1
## 17384 17385 17386 17387 17388 17391 17392 17394 17397 17398 17400 17403 17405
## 1 1 3 2 1 1 1 1 2 1 3 1 2
## 17406 17408 17409 17410 17411 17412 17414 17415 17418 17420 17422 17423 17425
## 2 1 2 3 1 3 2 2 1 1 3 2 2
## 17427 17429 17430 17431 17432 17433 17434 17436 17438 17440 17442 17446 17447
## 1 1 1 2 1 1 3 1 2 1 3 1 1
## 17449 17451 17453 17454 17455 17456 17457 17458 17459 17460 17461 17462 17463
## 3 3 1 1 1 1 3 1 1 3 1 1 3
## 17464 17466 17468 17469 17470 17472 17475 17480 17481 17483 17486 17489 17490
## 1 2 1 3 3 1 1 2 1 1 2 1 3
## 17491 17492 17495 17496 17498 17499 17500 17501 17502 17503 17504 17505 17506
## 3 2 1 1 1 2 2 1 1 1 3 2 1
## 17507 17508 17509 17510 17512 17513 17514 17515 17516 17517 17519 17520 17521
## 1 2 3 1 3 2 1 1 1 1 3 2 1
## 17522 17523 17524 17525 17526 17527 17528 17530 17531 17534 17535 17536 17537
## 3 1 1 2 1 1 3 3 1 1 1 1 2
## 17538 17540 17542 17545 17548 17549 17550 17551 17552 17554 17555 17556 17557
## 1 1 1 1 1 1 1 1 1 3 1 1 1
## 17560 17561 17562 17564 17566 17567 17569 17571 17572 17573 17574 17578 17579
## 1 1 3 1 2 3 1 2 1 1 1 1 1
## 17580 17582 17584 17585 17588 17589 17590 17591 17593 17594 17595 17596 17600
## 1 1 2 1 2 2 2 3 2 2 1 3 1
## 17601 17603 17604 17608 17609 17612 17614 17615 17616 17618 17619 17620 17621
## 1 2 1 1 3 3 2 1 1 1 1 1 2
## 17623 17624 17625 17628 17629 17630 17631 17633 17634 17636 17637 17639 17640
## 2 2 2 1 3 1 1 2 3 1 1 1 2
## 17642 17643 17644 17646 17647 17648 17650 17651 17653 17654 17655 17656 17658
## 2 1 3 1 1 2 1 3 1 1 3 3 1
## 17660 17663 17664 17666 17667 17668 17669 17670 17671 17673 17674 17676 17678
## 1 3 1 2 3 1 3 1 2 3 1 3 1
## 17680 17682 17684 17685 17691 17692 17693 17694 17695 17696 17697 17698 17700
## 1 3 1 3 1 1 1 1 2 3 1 1 2
## 17701 17702 17703 17704 17705 17707 17708 17709 17711 17712 17714 17715 17716
## 2 2 1 2 3 1 1 1 1 2 1 1 3
## 17718 17720 17722 17723 17724 17725 17731 17732 17733 17734 17736 17737 17738
## 1 1 2 3 2 3 1 1 2 1 1 1 2
## 17739 17742 17744 17746 17747 17749 17750 17752 17754 17758 17759 17760 17761
## 3 1 3 1 1 1 3 1 3 3 1 1 2
## 17763 17764 17765 17767 17768 17769 17770 17771 17772 17774 17775 17777 17779
## 1 2 1 1 2 3 3 1 1 1 1 1 1
## 17781 17783 17785 17786 17787 17788 17789 17791 17793 17795 17796 17797 17799
## 1 1 1 1 2 2 1 1 1 1 1 1 3
## 17800 17802 17805 17806 17812 17813 17816 17817 17819 17824 17827 17828 17830
## 3 2 2 2 1 3 1 1 3 1 3 2 1
## 17831 17832 17835 17836 17837 17838 17839 17843 17848 17849 17852 17854 17855
## 1 1 1 1 3 2 1 1 3 1 1 1 1
## 17856 17859 17860 17861 17862 17863 17864 17866 17867 17869 17871 17873 17874
## 2 1 1 3 1 3 1 1 3 1 1 3 3
## 17877 17878 17879 17880 17881 17883 17884 17885 17886 17887 17888 17889 17890
## 1 2 1 2 1 1 1 1 1 1 3 1 1
## 17891 17892 17893 17894 17895 17896 17897 17898 17899 17900 17901 17904 17905
## 1 1 1 3 1 1 1 1 1 1 1 1 1
## 17906 17908 17911 17912 17913 17914 17917 17921 17923 17924 17925 17926 17928
## 1 1 2 1 1 1 1 1 1 3 1 1 1
## 17929 17930 17931 17932 17934 17935 17936 17937 17939 17940 17941 17942 17946
## 1 3 1 2 2 1 2 3 1 3 1 1 1
## 17947 17948 17950 17951 17955 17956 17957 17958 17960 17962 17964 17966 17967
## 1 2 1 1 1 1 1 2 1 1 1 3 1
## 17968 17969 17970 17972 17973 17974 17976 17977 17978 17979 17980 17984 17985
## 1 1 2 1 1 1 2 1 1 1 1 1 2
## 17986 17987 17988 17990 17991 17994 17995 17997 17999 18001 18004 18005 18006
## 1 1 3 1 1 1 1 3 1 1 1 1 2
## 18008 18009 18010 18011 18013 18014 18015 18016 18017 18018 18019 18022 18024
## 3 1 1 1 1 1 1 3 1 1 1 2 1
## 18027 18030 18032 18033 18034 18035 18036 18037 18040 18042 18043 18044 18045
## 1 1 1 1 1 1 1 3 1 1 1 3 1
## 18048 18050 18053 18055 18056 18058 18059 18061 18062 18064 18066 18067 18068
## 1 1 1 3 2 1 1 3 1 2 1 2 1
## 18069 18071 18072 18074 18075 18077 18078 18080 18081 18082 18084 18085 18086
## 3 1 1 2 3 3 1 2 1 2 1 2 1
## 18088 18093 18094 18095 18096 18097 18099 18101 18104 18105 18106 18108 18110
## 1 2 3 1 1 3 1 1 2 1 2 1 1
## 18112 18113 18114 18116 18117 18119 18120 18121 18122 18123 18125 18126 18127
## 1 1 1 3 1 1 1 1 3 1 1 1 1
## 18129 18130 18135 18136 18138 18142 18143 18145 18146 18147 18149 18150 18151
## 1 2 1 1 1 2 2 2 1 1 1 1 1
## 18154 18155 18156 18158 18159 18160 18161 18164 18165 18167 18168 18169 18170
## 1 1 2 1 2 1 3 2 1 2 3 1 1
## 18171 18173 18174 18176 18177 18178 18179 18180 18181 18183 18184 18185 18188
## 3 2 1 2 3 2 3 3 2 1 1 1 2
## 18189 18190 18191 18193 18196 18200 18202 18203 18204 18205 18209 18210 18211
## 2 1 1 1 2 1 2 1 2 1 1 3 1
## 18212 18213 18215 18216 18217 18218 18219 18220 18221 18222 18224 18226 18227
## 1 1 1 2 1 1 3 1 3 2 1 3 1
## 18228 18230 18231 18232 18233 18235 18236 18237 18239 18240 18242 18245 18246
## 2 3 3 1 2 2 3 3 3 2 2 3 1
## 18248 18249 18250 18252 18255 18257 18259 18260 18261 18262 18263 18265 18268
## 2 1 2 1 1 3 2 3 1 1 2 2 1
## 18269 18270 18272 18273 18274 18276 18277 18278 18280 18281 18282 18287
## 1 1 3 1 1 1 1 1 1 1 1 2
##
## Within cluster sum of squares by cluster:
## [1] 957.5353 884.2098 843.1167
## (between_SS / total_SS = 64.4 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"asignacion <- cbind(bd5, cluster = segmentos$cluster)
head(asignacion,10)## Total Visitas cluster
## 12347 615.7143 7 3
## 12350 334.4000 1 1
## 12352 313.2550 8 3
## 12353 89.0000 1 1
## 12355 459.4000 1 2
## 12358 584.0300 2 2
## 12361 189.9000 1 1
## 12362 522.6230 10 3
## 12363 276.0000 2 1
## 12364 328.2750 4 1Exportar csv
write.csv(asignacion,"act_clientes_segmentados_a01177017")Visualizar segmentos
#install.packages("factoextra")
library(factoextra)## Loading required package: ggplot2## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBafviz_cluster(segmentos, data = bd6,
palette = c("red", "blue", "black", "darkgreen"),
ellipse.type = "euclid",
star.plot = T,
repel = T,
ggtheme = theme())## Warning: ggrepel: 3734 unlabeled data points (too many overlaps). Consider
## increasing max.overlaps
Optimizar k
#install.packages("cluster")
library(cluster)
set.seed(123)
optimizacion <- clusGap(bd6, FUN = kmeans, nstart = 25, K.max = 10, B = 50)## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterations
## Warning: did not converge in 10 iterationsplot(optimizacion, xlab = "Numero de clusters k")
Conclusiones
Se logran ver 3 clusters, el primero de color negro que esta en el tercer cuadrante, nos indica cuales son los clientes que visitan pocas veces el supermercado y consumen poco al ir; para este cluster se propone integrar un sistema de cupones que incentive que estas personas se sientan más atraídas por ir a este supermercado, y que cuando vayan se puedan enganchar con más cosas que se pongan en zonas estratégicas para incentivar la compra de más productos.
En el cuadrante cuatro, se tiene el color azul, que nos indica los clientes que van pocas veces pero que cuando van compran un ticket elevado, aquí lo que se propone es tener generar un sistema de puntos en tarjeta para que estos clientes que van pocas veces pero consumen mucho cuando van, sientan la necesidad de ir con ´más frecuencia al tener puntos acumulados, lo que les genere algún tipo de presión.
Finalmente en el cuadrante uno, tenemos el color rojo, donde están los clientes que compran mucho y van constantemente al supermercado, la estrategia que se recomienda implementar aquí para que estos sigan consumiendo con esa frecuencia es mantener promociones visibles en toda la tienda, que logren llamar la atención de estos clientes, bajar estratégicamente los precios de los productos más vendidos y subirlos en otros que quizá no sean tan frecuentes pero que si sean vendidos a cierto sector económico para mantener a dichos clientes.
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