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combinados-NOUSAR.R
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library(dplyr)
library(reshape2)
library(gridExtra)
library(grid)
library(ggplot2)
library(scales)
setwd("D:\\RCoursera\\r-s-l")
ripley.tv <- read.csv("D:\\RCoursera\\Ripley\\r-tvs-2016-03-04.csv", stringsAsFactors = F,
na.strings = "")
saga.tv <- read.csv("D:\\RCoursera\\Saga_falabella\\s-tv-2016-03-04.csv",
stringsAsFactors = F)
linio.tv <- read.csv("D:\\RCoursera\\Linio\\l-tv-2015-12-26.csv",
stringsAsFactors = F)
### Saga cleaning
saga.tv$categoria <- NULL
saga.tv$precio.normal <- NULL
saga.tv$recojo.tienda <- NULL
saga.tv$solo.online <- NULL
# Precio Internet tiene que llamarse "Precio Antes"
# Precio Unica tiene que llamarse "Precio Actual"
colnames(saga.tv)[4] <- "precio.antes"
colnames(saga.tv)[5] <- "precio.actual"
saga.tv$precio.antes <- gsub(",", "", saga.tv$precio.antes)
saga.tv$precio.actual <- gsub(",", "", saga.tv$precio.actual)
###
### Unión de los 3 dfs
tvs <- rbind(ripley.tv, saga.tv,
linio.tv)
### as numeric
tvs$marca <- trimws(tvs$marca, which = c("both"))
tvs$producto <- trimws(tvs$producto, which = c("both"))
tvs$precio.antes <- trimws(tvs$precio.antes, which = c("both"))
tvs$precio.actual <- trimws(tvs$precio.actual, which = c("both"))
tvs$pulgadas <- trimws(tvs$pulgadas, which = c("both"))
#Linio es el que tiene más variedad de productos
### En realidad Saga termina siendo el que ofrece menos
### productos. Será una estrategia para mostrar que cuentan con un
### mayor surtido de TVs. La teoría dice que entre menos elecciones tenga
### el consumidor, mejor decidirá.
#¿Por qué los ids son diferentes, si ya quitamos los duplicados?
tvs$precio.antes <- as.numeric(tvs$precio.antes)
tvs$precio.actual <- as.numeric(tvs$precio.actual)
tvs$pulgadas <- as.numeric(tvs$pulgadas)
### Linio no tiene mucha información en Precio Antes
### Rango de precios - basados en Ripley.com.pe
tvs <- tvs %>%
mutate(rangos = ifelse(precio.actual <= 500, "< S/.500",
ifelse(precio.actual > 500 & precio.actual <= 1500,
"S/.500 - S/.1500",
ifelse(precio.actual > 1500 & precio.actual <= 2500,"S/.1500 - S/.2500",
ifelse(precio.actual > 2500 & precio.actual <= 3500,"S/.2500 - S/.3500",
ifelse(precio.actual > 3500 & precio.actual <= 4500,"S/.3500 - S/.4500",
"> S/.4,500"))))))
tvs$rangos <- factor(tvs$rangos, levels = c("< S/.500",
"S/.500 - S/.1500",
"S/.1500 - S/.2500",
"S/.2500 - S/.3500",
"S/.3500 - S/.4500",
"> S/.4,500"),
ordered = T)
###
tvs$marca <- factor(tvs$marca, levels = c("hisense","nex", "continental",
"haier", "aoc",
"sharp", "imaco","panasonic","sony",
"lg", "samsung", "daewoo", "hyundai"),
ordered = T)
###
### Reemplazar nombres reales de Ecommerce por nombres clave
# Ripley <- A
# Saga <- B
# Linio <- C
tvs$ecommerce <- gsub("ripley", "a", tvs$ecommerce)
tvs$ecommerce <- gsub("falabella", "b", tvs$ecommerce)
tvs$ecommerce <- gsub("linio", "c", tvs$ecommerce)
tvs.cantidad <- tvs %>%
group_by(ecommerce) %>%
summarise(cantidad = length(marca))
tvs.cantidad$ecommerce <- factor(tvs.cantidad$ecommerce, levels = c("linio",
"ripley",
"falabella"),
ordered = T)
ggplot(tvs.cantidad, aes(x=ecommerce, y= cantidad)) +
geom_bar(stat = "identity", width = .7, fill= "lightblue") +
#facet_grid(~ ecommerce) +
labs(title = "Ecommerce con más TVs\n",
x = "", y = "") +
theme(axis.text.x = element_text(colour="grey10",size=22,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey10",size=20,,hjust=0,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey40",size=6,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey40",size=6,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(size = 24,vjust=2))
ggsave(file="tvs-cantidad.jpg", width = 12, height = 8,
path = "D:\\RCoursera\\r-s-l\\graficos")
###
tvs.rangos <- tvs %>%
group_by(ecommerce, rangos) %>%
summarise(cantidad = length(rangos))
tvs.rangos$ecommerce <- factor(tvs.rangos$ecommerce, levels = c("linio",
"ripley",
"falabella"),
ordered = T)
# To use for fills, add
###
ggplot(tvs.rangos, aes(x = rangos, y = cantidad, fill = ecommerce)) +
geom_bar(stat = "identity") +
scale_fill_manual("ecommerce",
values = c("linio" = "#FF5500","ripley" = "#802D69","falabella" = "#BED800")) +
labs(title = "Cantidad de TVs\nsegún rangos de precios\n",
x = "rangos de precios\n", y = "cantidad de tvs") +
facet_wrap(~ ecommerce, nrow = 3) +
coord_flip() +
theme(axis.text.x = element_text(colour="grey10",size=16,hjust=.5,vjust=.5,face="bold"),
axis.text.y = element_text(colour="grey10",size=18,,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey40",size=16,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey40",size=16,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(size = 18,vjust=4),
legend.title = element_text(colour="grey40", size=16, face="bold"),
legend.text = element_text(colour="grey10", size=16, face="bold"),
strip.text.x = element_text(size = 20, angle = 0),
legend.position = "none")
####
###
### Gráficos individuales por ecommerce ###
### ripley ###
tvs.ripley <- tvs[tvs$ecommerce == "ripley",]
tvs.ripley.porcentajes <- tvs.ripley %>%
group_by(rangos, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
mutate(porcentaje = cantidad.marca/sum(cantidad.marca))
ggplot(tvs.ripley.porcentajes, aes(x=rangos, y= porcentaje ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
scale_fill_brewer(palette="Set3") +
labs(title = "Ripley Perú \n % marca de tvs por rango de precios",
x = "rango de precios", y = "% cantidad de tvs") +
theme(axis.text.x = element_text(colour="grey20",size=14,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=14,,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=14,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=14,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2)) +
scale_y_continuous(labels=percent)
### falabella ###
tvs.falabella <- tvs[tvs$ecommerce == "falabella",]
tvs.falabella.porcentajes <- tvs.falabella %>%
group_by(rangos, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
mutate(porcentaje = cantidad.marca/sum(cantidad.marca))
ggplot(tvs.falabella.porcentajes, aes(x=rangos, y= porcentaje ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
scale_fill_brewer(palette="Set3") +
labs(title = "Falabella Perú \n % marca de tvs por rango de precios",
x = "rango de precios", y = "% cantidad de tvs") +
theme(axis.text.x = element_text(colour="grey20",size=14,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=14,,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=14,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=14,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2)) +
scale_y_continuous(labels=percent)
### linio ###
tvs.linio <- tvs[tvs$ecommerce == "linio",]
tvs.linio.porcentajes <- tvs.linio %>%
group_by(rangos, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
mutate(porcentaje = cantidad.marca/sum(cantidad.marca))
ggplot(tvs.linio.porcentajes, aes(x=rangos, y= porcentaje ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
scale_fill_brewer(palette="Set3") +
labs(title = "Linio Perú \n % marca de tvs por rango de precios",
x = "rango de precios", y = "% cantidad de tvs") +
theme(axis.text.x = element_text(colour="grey20",size=14,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=14,,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=14,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=14,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2)) +
scale_y_continuous(labels=percent)