Commit cc931abc authored by numeroteca's avatar numeroteca
Browse files

posibilita crear img de plots en directorios de cada caso

parent b7622128
......@@ -3,53 +3,65 @@
# ---- Load libraries -----
library(tidyverse)
# Load data
data <- read.delim("data/verba/180320_180430_cifuentes-y-palabras-relacionadas_clasificado.csv",sep = ",")
data <- read.delim("data/verba/140104_140228_barcenas-palabras-relacionadas_01.csv",sep = ",")
data <- read.delim("data/verba/140104_140228_messi_01.csv",sep = ",")
# Settings ------
# subtitle_text <- "Telediarios de TVE. 20 marzo - 29 abril 2018"
# subtitle_text <- "Telediarios de TVE. 4 enero - 28 febrero 2017"
subtitle_text <- "Telediarios de TVE. 1 marzo - 30 junio 2017"
# el_caso <- "caso Máster (Cristina Cifuentes)"
el_caso <- "caso Lezo y caso Púnica"
caso_path <- "lezo-punica"
# el_caso <- "Messi"
caption_text <- "Datos: Verba (Civio). Gráfico: numeroteca.org"
# Load data ---------------
# data <- read.delim("data/verba/180320_180430_cifuentes-y-palabras-relacionadas_clasificado.csv",sep = ",")
# data <- read.delim("data/verba/140104_140228_barcenas-palabras-relacionadas_01.csv",sep = ",")
# data <- read.delim("data/verba/140104_140228_messi_01.csv",sep = ",")
data <- read.delim("data/verba/170301_170630_lezo-punica.csv",sep = ",")
# Preprocess data -------
# preprocessed data (cifuentes)i
# preprocessed data (cifuentes)
# data$date <- as.Date(data$date)
# data$date2 <- as.POSIXct(data$date)
# raw vera data
# Transform raw verba data into date format
data$date <- as.Date(data$programme_date)
# Transforms in to date-time format. TODO: loses hour!
data$date2 <- as.POSIXct(data$date)
# create variable Telediario based on programme_date
data$telediario_fino <- substr(data$programme_date, 11, 13)
table(data$telediario_fino)
# simplifies times
# simplifies times when times are not the standard T15 and T21.
# Transforms T22 and T20 to T21, and T14 to T15.
# T15 is 15:00h program and T21 is 21:00h program
data[data$telediario_fino == "T22",]$telediario_fino <- "T21"
data[data$telediario_fino == "T20",]$telediario_fino <- "T21"
data[data$telediario_fino == "T14",]$telediario_fino <- "T15"
table(data$telediario_fino)
# test borrable
# data$id <- as.character(data$id)
# data[data$id == "GxCr-W0BCKkHyZ2v_0lo",]$id <- "wer"
# levels(data$telediario_fino) <- c("15:00h","21.00h")
data$date2[1] + 3600
# Settings
subtitle_text <- "Telediarios de TVE. 20 marzo - 29 abril 2018"
subtitle_text <- "Telediarios de TVE. 4 enero - 28 febrero 2017"
el_caso <- "caso Máster (Cristina Cifuentes)"
el_caso <- "caso Lezo y caso Púnica"
el_caso <- "Messi"
caption_text <- "Datos: Verba. Gráfico: numeroteca.org"
# data$date2[1] + 3600
# Plots ----------------------
# Número de frases por telediario
png(filename=paste("img/apariciones-n-telediarios-caso-master_01.png", sep = ""),width = 1200,height = 900)
png(filename=paste("img/",caso_path ,"/apariciones-n-telediarios-",caso_path,"_01.png", sep = ""),width = 1200,height = 700)
ggplot(data = data ) +
geom_bar(aes( x=date2 )) + # si hay clasificación por caso: fill=caso
theme_minimal(base_family = "Roboto Condensed", base_size = 22) +
scale_x_datetime(date_breaks = "1 day", date_labels = "%d") +
# scale_x_datetime(date_breaks = "1 day", date_labels = "%d") +
scale_x_datetime(date_breaks = "5 day",
date_labels = "%d",
#secondary axis to add months
sec.axis = sec_axis(~ .,
labels = scales::time_format("%b"))
) +
labs(title = paste("Número de frases sobre ",el_caso,sep = ""),
subtitle = subtitle_text,
x = NULL,
......@@ -58,14 +70,15 @@ ggplot(data = data ) +
theme(
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
# panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank()
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
axis.ticks.x = element_line()
) +
facet_wrap( ~telediario_fino, ncol=1)
dev.off()
# Cuando hablan del caso dentro del Telediario
png(filename=paste("img/apariciones-cuando-telediarios-caso-master_01.png", sep = ""),width = 1200,height = 900)
png(filename=paste("img/",caso_path ,"/apariciones-cuando-telediarios_",caso_path,"_01.png", sep = ""),width = 1200,height = 900)
ggplot(data = data ) + #%>% filter( date> "2018-04-01" & date < "2018-04-05" )
geom_rect(aes( xmin=min(data$date2+ 41000) , xmax=max(data$date2+ 82800+ 40000), ymin=0,ymax=90/60), alpha = 0.02, fill = "lightgrey" ) +
geom_segment( aes(x = date2 + 82800, xend = date2 + 82800, y = start_time/60, yend = (start_time+30)/60), alpha = 0.8, size=4) + #, color=caso
......@@ -75,8 +88,8 @@ ggplot(data = data ) + #%>% filter( date> "2018-04-01" & date < "2018-04-05" )
# color="#999999", data =data, curvature = -0.2, size = 0.1) +
# annotate(geom = "text", x = as.POSIXct("2018-03-26"), y = 7, label = "Portada (1:30 minutos)",
# family = "Roboto Condensed", hjust = 0,size=6,size=0.6) +
theme_minimal(base_family = "Roboto Condensed", base_size = 22) +
scale_x_datetime(date_breaks = "3 day", date_labels = "%d", expand= c(0.01,0.05)) +
theme_minimal(base_family = "Roboto Condensed", base_size = 18) +
scale_x_datetime(date_breaks = "1 day", date_labels = "%d", expand= c(0.01,0.05)) +
labs(title = paste("Cuándo hablan del ",el_caso, " en los telediarios",sep = ""),
subtitle = paste(subtitle_text),
x = NULL,
......@@ -85,12 +98,11 @@ ggplot(data = data ) + #%>% filter( date> "2018-04-01" & date < "2018-04-05" )
theme(
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
# panel.grid.major.x = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank()
) +
facet_wrap( ~telediario_fino, ncol=1)
dev.off()
dev.off()
png(filename=paste("img/apariciones-cuando-telediarios-caso-master_01_v.png", sep = ""),width = 900,height = 1200)
ggplot(data = data ) + #%>% filter( date> "2018-04-01" & date < "2018-04-05" )
......
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