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tvs-graficos.R
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library(dplyr)
library(ggplot2)
library(ggforce)
library(hrbrthemes)
library(scales)
library(tibble)
library(plotly)
library(repmis)
setwd("D:\\RCoursera\\r-s-l")
tvs <- source_data("https://www.dropbox.com/s/6arewitgenhwwba/2017-03-15-total-tvs.csv?raw=1")
############################################
### Total TVS 2017 vs 2016 por Ecommerce ###
############################################
### Remover de Linio lo que no son TVs #####
tvs <- tvs %>%
filter(pulgadas < 90, !is.na(marca))
tvs.cantidad <- tvs %>%
group_by(periodo, ecommerce) %>%
summarise(cantidad = length(marca))
tvs.cantidad$ecommerce <- factor(tvs.cantidad$ecommerce, levels = c("linio",
"ripley",
"falabella"),
ordered = T)
tvs.cantidad$periodo <- factor(tvs.cantidad$periodo, levels = c(2017,2016),
ordered = T)
tt1 <- "Ecommerce con más TVs"
stt1 <- "Linio, Ripley y Falabella son los 3 principales ecommerce del Perú.\n"
cptn <- "\nogonzales.com | Data Analyst"
ggplot(tvs.cantidad, aes(x=ecommerce, y= cantidad, fill = ecommerce)) +
geom_bar(stat = "identity", width = .7) +
facet_grid(~ periodo) +
theme_bw() +
scale_fill_manual("ecommerce",
values = c("linio" = "#FF5500","ripley" = "#802D69","falabella" = "#BED800")) +
labs(title = "Ecommerce con más TVs\n",
x = "", y = "") +
#theme_ipsum_rc(grid = "Y") +
theme(axis.text.x = element_text(colour="grey10",size=12,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey10",size=8,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,face="bold"),
plot.subtitle = element_text(vjust=2, size = 16),
plot.caption = element_text(vjust=2, size = 8),
panel.border = element_rect(colour = "white"),
legend.position = "none",
strip.text = element_text(size = 18, hjust = 0.08, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()) +
geom_text(aes(label=cantidad), vjust=-0.6, size = 4) +
ylim(0, 600) +
labs(title = tt1, subtitle = stt1, caption = cptn,
x = "", y = "")
############################################
### TVS 2017 vs 2016 por Rango de Precio ###
############################################
tvs.rango <- tvs %>%
group_by(periodo, ecommerce, rango) %>%
summarise(cantidad = length(rango))
tvs.rango$periodo <- factor(tvs.rango$periodo, levels = c(2017,2016),
ordered = T)
tvs.rango$ecommerce <- factor(tvs.rango$ecommerce, levels = c("linio",
"ripley",
"falabella"),
ordered = T)
tvs.rango$rango <- factor(tvs.rango$rango, levels = c("< S/.500",
"S/.500 -\r\n S/.1500",
"S/.1500 -\r\n S/.2500",
"S/.2500 -\r\n S/.3500",
"S/.3500 -\r\n S/.4500",
"> S/.4,500"),
ordered = T)
# To use for fills, add
###
### No usar título porque no entra en los límites del
### formato de la página web.
#tt2 <- "Cantidad de TVs según rango de precio"
tt2 <- ""
stt2 <- "\n"
ggplotly(ggplot(tvs.rango, aes(x = rango, y = cantidad, fill = ecommerce)) +
geom_bar(stat = "identity") +
scale_fill_manual("ecommerce",
values = c("linio" = "#FF5500","ripley" = "#802D69","falabella" = "#BED800")) +
facet_grid(~ periodo) +
theme_bw() +
coord_flip() +
#theme_ipsum_rc(grid = "X") +
theme(axis.text.x = element_text(colour="grey10",size=10,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey10",size=10,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 = 24,vjust=4, face="bold"),
plot.subtitle = element_text(vjust=2, size = 16),
plot.caption = element_text(vjust=2, size = 16),
panel.border = element_rect(colour = "white"),
legend.position = "none",
strip.text = element_text(size = 18, hjust = 0.01, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank()) +
#geom_text(aes(label=cantidad), hjust=-0.25, size = 4) +
ylim(0, 300) +
labs(title = tt2, subtitle = stt2, caption = cptn,
x = "", y = ""))
###################################################
# BOXPLOTS TVS 2017 vs 2016 todos los Ecommerce ###
###################################################
tvs.precios <- tvs
tvs.precios$periodo <- factor(tvs.precios$periodo, levels = c(2017,2016),
ordered = T)
tvs.precios$ecommerce <- factor(tvs.precios$ecommerce, levels = c("linio",
"ripley",
"falabella"),
ordered = T)
### Distribución de los precios de TVs por Ecommerce
p <- plot_ly(tvs.precios, x = ~periodo, y = ~precio.actual, color = ~ecommerce, type = "box") %>%
layout(boxmode = "group")
p
#############################################
### Gráficos individuales por ecommerce ###
#############################################
### ripley ###
tvs.ripley <- tvs[tvs$ecommerce == "ripley",]
### falabella ###
tvs.falabella <- tvs[tvs$ecommerce == "falabella",]
### linio ###
tvs.linio <- tvs[tvs$ecommerce == "linio",]
tvs.linio.parte1 <- tvs.linio %>%
filter(marca %in% c("lg", "aoc","imaco",
"royal","panasonic",
"samsung", "sony", "olitec",
"haier", "nex"))
tvs.linio.parte2 <- tvs.linio %>%
filter(marca %in% c("daywoo","altron","blackline",
"miray","hisense", "king master",
"xenon", "hyundai", "jvc"))
#########################################################
### MARCAS DE TV POR RANGO DE PRECIO - EN PORCENTAJES ###
#########################################################
### Ripley
tvs.ripley.tvs.por.rango <- tvs.ripley %>%
group_by(periodo, rango, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
#mutate(porcentaje = paste0(round(cantidad.marca/sum(cantidad.marca)*100,2),'%'))
mutate(porcentaje_tvs = round(cantidad.marca/sum(cantidad.marca),4))
tvs.ripley.tvs.por.rango$periodo <- factor(tvs.ripley.tvs.por.rango$periodo, levels = c(2017,2016),
ordered = T)
tvs.ripley.tvs.por.rango$rango <- factor(tvs.ripley.tvs.por.rango$rango, levels = c("< S/.500",
"S/.500 -\r\n S/.1500",
"S/.1500 -\r\n S/.2500",
"S/.2500 -\r\n S/.3500",
"S/.3500 -\r\n S/.4500",
"> S/.4,500"),
ordered = T)
tt3 <- "Ripley.com.pe \nmarcas de tvs por rango de precio en porcentajes %"
stt3 <- "\n"
ggplot(tvs.ripley.tvs.por.rango, aes(x=rango, y= porcentaje_tvs ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
facet_grid(~ periodo) +
theme_bw() +
theme(axis.text.x = element_text(colour="grey20",size=8,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=8,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=18,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=16,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2, size = 24,face="bold"),
plot.subtitle = element_text(vjust=2, size = 16),
plot.caption = element_text(vjust=2, size = 16),
legend.position = "bottom",
panel.border = element_rect(colour = "white"),
strip.text = element_text(size = 18, hjust = 0.05, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()) +
scale_y_continuous(labels=percent) +
# scale_fill_manual(
# values = c("hisense" = "#F39EF7","sony" = "#003366","panasonic" = "#FCB462",
# "samsung" = "#7ec0ee", "lg" = "#A21420",
# "aoc" = "#9DCC27", "sharp" = "#BEBBDA", "hyundai" = "#FCB442")) +
# labs(title = tt5, subtitle = stt5, caption = cptn,
# x = "", y = "") +
labs(title = tt3, subtitle = stt3, caption = "",
x = "", y = "")
### Falabella
tvs.falabella.tvs.por.rango <- tvs.falabella %>%
group_by(periodo, rango, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
#mutate(porcentaje = paste0(round(cantidad.marca/sum(cantidad.marca)*100,2),'%'))
mutate(porcentaje_tvs = round(cantidad.marca/sum(cantidad.marca),4))
tvs.falabella.tvs.por.rango$periodo <- factor(tvs.falabella.tvs.por.rango$periodo, levels = c(2017,2016),
ordered = T)
tvs.falabella.tvs.por.rango$rango <- factor(tvs.falabella.tvs.por.rango$rango, levels = c("< S/.500",
"S/.500 -\r\n S/.1500",
"S/.1500 -\r\n S/.2500",
"S/.2500 -\r\n S/.3500",
"S/.3500 -\r\n S/.4500",
"> S/.4,500"),
ordered = T)
tt5 <- "Sagafalabella \n % marcas de tvs por rango de precios"
stt5 <- "\n"
ggplot(tvs.falabella.tvs.por.rango, aes(x=rango, y= porcentaje_tvs ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
facet_grid(~ periodo) +
theme_bw() +
#theme_ipsum_rc(grid = "Y") +
theme(axis.text.x = element_text(colour="grey20",size=8,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=8,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=18,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=16,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2, size = 24,face="bold"),
plot.subtitle = element_text(vjust=2, size = 16),
plot.caption = element_text(vjust=2, size = 16),
legend.position = "top",
panel.border = element_rect(colour = "white"),
strip.text = element_text(size = 18, hjust = 0.05, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()) +
scale_y_continuous(labels=percent) +
# scale_fill_manual(
# values = c("hisense" = "#F39EF7","sony" = "#003366","panasonic" = "#FCB462",
# "samsung" = "#7ec0ee", "lg" = "#A21420",
# "aoc" = "#9DCC27", "sharp" = "#BEBBDA", "hyundai" = "#FCB442")) +
# labs(title = tt5, subtitle = stt5, caption = cptn,
# x = "", y = "") +
labs(title = tt5, subtitle = stt5, caption = "",
x = "", y = "")
### Linio
tvs.linio.tvs.por.rango <- tvs.linio %>%
group_by(periodo, rango, marca) %>%
summarise(cantidad.marca = length(marca)) %>%
#mutate(porcentaje = paste0(round(cantidad.marca/sum(cantidad.marca)*100,2),'%'))
mutate(porcentaje_tvs = round(cantidad.marca/sum(cantidad.marca),4))
tvs.linio.tvs.por.rango$periodo <- factor(tvs.linio.tvs.por.rango$periodo, levels = c(2017,2016),
ordered = T)
tvs.linio.tvs.por.rango$rango <- factor(tvs.linio.tvs.por.rango$rango, levels = c("< S/.500",
"S/.500 -\r\n S/.1500",
"S/.1500 -\r\n S/.2500",
"S/.2500 -\r\n S/.3500",
"S/.3500 -\r\n S/.4500",
"> S/.4,500"),
ordered = T)
tt5 <- "Linio \n % marcas de tvs por rango de precios"
stt5 <- "\n"
ggplot(tvs.linio.tvs.por.rango, aes(x=rango, y= porcentaje_tvs ,fill=marca)) +
geom_bar(stat = "identity", width = .7) +
facet_grid(~ periodo) +
theme_bw() +
#theme_ipsum_rc(grid = "Y") +
theme(axis.text.x = element_text(colour="grey20",size=8,hjust=.5,vjust=.5,face="plain"),
axis.text.y = element_text(colour="grey20",size=8,hjust=1,vjust=0,face="plain"),
axis.title.x = element_text(colour="grey20",size=18,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey20",size=16,angle=90,hjust=.5,vjust=.5,face="plain"),
plot.title = element_text(vjust=2, size = 24,face="bold"),
plot.subtitle = element_text(vjust=2, size = 16),
plot.caption = element_text(vjust=2, size = 16),
legend.position = "top",
panel.border = element_rect(colour = "white"),
strip.text = element_text(size = 18, hjust = 0.05, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()) +
scale_y_continuous(labels=percent) +
# scale_fill_manual(
# values = c("hisense" = "#F39EF7","sony" = "#003366","panasonic" = "#FCB462",
# "samsung" = "#7ec0ee", "lg" = "#A21420",
# "aoc" = "#9DCC27", "sharp" = "#BEBBDA", "hyundai" = "#FCB442")) +
# labs(title = tt5, subtitle = stt5, caption = cptn,
# x = "", y = "") +
labs(title = tt5, subtitle = stt5, caption = "",
x = "", y = "")
#
# solo.linio <- plot_ly(tvs.linio.porcentajes, x = ~marca, y = ~dif.porcentual, color = ~marca, type = "box") %>%
# layout(boxmode = "group")
#
# solo.linio
############################################################################
# Diferencia porcentual por marca en LINIO. No se puede hacer interactiva.#
########################### Usar GGPLOT2 ###################################
############################################################################
###############################################
######### Precio Actual por Marca #############
###############################################
tvs.ripley$periodo <- factor(tvs.ripley$periodo, levels = c(2017,2016),
ordered = T)
tvs.falabella$periodo <- factor(tvs.falabella$periodo, levels = c(2017,2016),
ordered = T)
tvs.linio$periodo <- factor(tvs.linio$periodo, levels = c(2017,2016),
ordered = T)
tvs.linio.parte1$periodo <- factor(tvs.linio.parte1$periodo, levels = c(2017,2016),
ordered = T)
tvs.linio.parte2$periodo <- factor(tvs.linio.parte2$periodo, levels = c(2017,2016),
ordered = T)
### Ripley: distribución de los precios de TVs por marca
precio.actual.ripley <- plot_ly(tvs.ripley, x = ~periodo, y = ~precio.actual, color = ~marca, type = "box") %>%
layout(boxmode = "group")
precio.actual.ripley
### Falabella: distribución de los precios de TVs por marca
precio.actual.falabella <- plot_ly(tvs.falabella, x = ~periodo, y = ~precio.actual, color = ~marca, type = "box") %>%
layout(boxmode = "group")
precio.actual.falabella
### Linio - Precio Actual - Parte 1 y 2
precio.actual.linio.parte1 <- plot_ly(tvs.linio.parte1, x = ~periodo, y = ~precio.actual, color = ~marca, type = "box") %>%
layout(boxmode = "group")
precio.actual.linio.parte1
precio.actual.linio.parte2 <- plot_ly(tvs.linio.parte2, x = ~periodo, y = ~precio.actual, color = ~marca, type = "box") %>%
layout(boxmode = "group")
precio.actual.linio.parte2
##################################################
######## BoxPlot - Dif Porcentual precios ########
##################################################
### Ripley
tvs.ripley.dif.porcentual <- tvs.ripley %>%
group_by(periodo,marca, precio.antes, precio.actual) %>%
mutate(dif.precios = precio.antes - precio.actual,
dif.porcentual = round(100*dif.precios/precio.antes,2))
tt4 <- "Ripley - variación % descuentos según rango de precios"
stt4 <- "\n"
dif.porcentual.ripley <- plot_ly(tvs.ripley.dif.porcentual, x = ~periodo, y = ~dif.porcentual, color = ~marca, type = "box") %>%
layout(boxmode = "group")
dif.porcentual.ripley
################################################
####### Scaterplot Pulgadas vs Precios #########
################################################
tv.pulgadas.vs.pulgadas <- tvs %>%
group_by(periodo, ecommerce, marca, pulgadas) %>%
filter(pulgadas <= 90, marca != "xenon")
tv.pulgadas.vs.pulgadas$periodo <- factor(tv.pulgadas.vs.pulgadas$periodo, levels = c(2017,2016), ordered = T)
tv.pulgadas.vs.pulgadas$marca <- as.factor(tv.pulgadas.vs.pulgadas$marca)
pulgadas_precio <- ggplot(tv.pulgadas.vs.pulgadas, aes(x = pulgadas, y = precio.actual)) +
geom_point(aes(color=marca),size = 2,alpha = 0.4) +
facet_grid(ecommerce ~ periodo, switch = "y") +
theme_bw() +
theme(axis.text.x = element_text(colour="grey10",size=10,hjust=.5,vjust=.5,face="plain"),
axis.text.y=element_blank(),axis.ticks=element_blank(),
axis.title.x = element_text(colour="grey40",size=12,angle=0,hjust=.5,vjust=0,face="plain"),
axis.title.y = element_text(colour="grey40",size=12,angle=90,hjust=.5,vjust=.5,face="plain"),
legend.position = "none",
plot.title = element_text(size = 24,vjust=4, face="bold"),
plot.subtitle = element_text(vjust=2, size = 8),
plot.caption = element_text(vjust=2, size = 8),
legend.title = element_text(colour="grey40",size=14,hjust=.5,vjust=.5,face="bold"),
legend.text = element_text(colour="grey10", size=18, face="plain"),
panel.border = element_rect(colour = "white"),
strip.text = element_text(size = 12, hjust = 0.05, vjust = -0.5),
strip.background = element_rect(colour = "white", fill = "white"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()) +
scale_y_continuous(label=comma, limits = c(0,36000)) +
#scale_x_continuous(label=comma, limits = c(0,100)) +
labs(title = "", subtitle = "", caption = "",
x = "pulgadas \n", y = "Precio en S/.")
ggplotly(pulgadas_precio)