analyses/filiafobia2/prepare_data.R
In joebrew/vilaweb: Reproducible data analysis for www.vilaweb.cat
# Libraries
library(vilaweb)
library(tidyverse)
library(lubridate)
library(databrew)
library(tidylog)
options(scipen = 999)
plot_twitter <- function(ca = TRUE){
pd <- fobia %>% filter(key == 'Hispanofòbia') %>%
group_by(date = as.Date(cut(date, 'month'))) %>%
summarise(n = n(),
rt = sum(retweets_count))
if(ca){
the_labs <- labs(x = 'Mes',
y = 'Piulets (escala logarítmica)',
title = "Piulets amb la paraula de 'hispanofòbia'",
subtitle = 'Dades de Twitter, incloent-hi repiulets',
caption = 'Gràfic de Joe Brew, @joethebrew')
} else {
the_labs <- labs(x = 'Month',
y = 'Piulets (log scale)',
title = "Tweets with the word 'Hispanophobia'",
subtitle = 'Data from Twitter, including retweets',
caption = 'Chart by Joe Brew, @joethebrew.')
}
ggplot(data = pd,
aes(x = date,
y = rt + n)) +
geom_line() +
# geom_path(color = 'darkorange', alpha = 0.6) +
theme_simple() +
scale_y_log10() +
the_labs
}
plot_google <- function(ca = TRUE){
# Read in google trends data (retrieved 23 jan 2020)
google <- read_csv('multiTimeline.csv', skip = 1)
google$date <- as.Date(paste0(google$Month, '-01'))
# google$date <- as.Date(cut(google$date, 'year'))
google$value <- google$`hispanofobia: (Spain)`
if(ca){
the_labs <- labs(x = 'Mes',
y = 'Percentatge (escala logarítmica)',
title = "Cerques de 'hispanofòbia'",
subtitle = 'Dades de Google Trends',
caption = 'Percentatge: cerques mensuals relatives al màxim. Gràfic de Joe Brew, @joethebrew')
} else {
the_labs <- labs(x = 'Month',
y = 'Percentage (log scale)',
title = "Searches for 'Hispanophobia'",
subtitle = 'Data from Google Trends',
caption = 'Percentage: monthly searches relative to the maximum. Chart by Joe Brew, @joethebrew.')
}
pd <- google %>%
group_by(date) %>%
summarise(value = mean(value))
ggplot(data = pd,
aes(x = date,
y = value)) +
geom_line() +
# geom_path(color = 'darkorange', alpha = 0.6) +
theme_simple() +
scale_y_log10(breaks = c(0:3, 5,10,25, 50, 100)) +
the_labs
}
# Read in the territorial survey data
pt <- vilaweb::ceo_percepcio_territorial
# Function for cleaning up the sympathy variable
simpatia_cleaner <- function(x){
x <- as.character(x)
x <- ifelse(x %in% c('No contesta', 'No ho sap'), NA,
ifelse(x == 'Us cauen molt bé 10', '10',
ifelse(x == 'No us cauen ni bé ni malament 5', 5,
ifelse(x == 'Us cauen molt malament 0', '0',
x))))
x <- as.numeric(x)
return(x)
}
pt <- pt %>%
mutate(visits = `I d’aquestes, en concret, em podria dir quantes vegades a viatjat a Catalunya?`,
simpatia = `Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`,
referendum = `Grau d'acord: S’hauria de fer un referèndum a Catalunya perquè els catalans i les catalanes decidissin quina relació volen que hi hagi entre Catalunya i l’Estat espanyol`) %>%
mutate(simpatia = simpatia_cleaner(simpatia)) %>%
mutate(ccaa = `Comunitat autònoma`)
# # Companeros de trabajo
# pt$`Amb independència que treballeu o no, quins són els tres que menys us agradaria tenir com a companys de feina o treball? Catalans`
#
# # Grau de simpatia
# pt$`Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`
# Define the label sets (for factor ordering)
label_df <- tibble(
ccaa = c('Andalusia',
'Aragó',
'Astúries',
'Balears',
'Canàries',
'Cantàbria',
'Castella la Manxa',
'Castella i Lleó',
'Catalunya',
'Extremadura',
'Galícia',
'Madrid',
'Múrcia',
'Navarra',
'Euskadi/País Basc',
'País Valencià',
'La Rioja', 'Ceuta', 'Melilla'),
key = c('Andalusos',
'Aragonesos',
'Asturians',
'Balears',
'Canaris',
'Càntabres',
'Castellanomanxecs',
'Castellanolleonesos',
'Catalans',
'Extremenys',
'Gallecs',
'Madrilenys',
'Murcians',
'Navarresos',
'Bascos',
'Valencians',
'Riojans',
'Ceutencs',
'Melillencs')
)
label_df$ccaa <- factor(label_df$ccaa, levels = label_df$ccaa)
label_df$key <- factor(label_df$key, levels = label_df$key)
fix_levels <- function(var, from_place = FALSE, to_place = TRUE){
if(from_place){
x <- tibble(ccaa = var)
} else {
x <- tibble(key = var)
}
# Join with the labels
joined <- left_join(x, label_df)
# Get the return val
if(to_place){
out <- joined$ccaa
out <- factor(out, levels = label_df$ccaa)
} else {
out <- joined$key
out <- factor(out, levels = label_df$key)
}
return(out)
}
plot_viatges_i_simpatia <- function(ca = TRUE){
# Viatges a Cat i favorabilitat e Cats
pd <- pt %>%
filter(ccaa != 'Catalunya') %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
group_by(visits) %>%
summarise(simpatia = mean(simpatia, na.rm = TRUE),
n = n())
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = 'Degree of sympathy (0-10) for\nthe residents of Catalonia',
title = "Times travelled to Catalonia and\nfeelings about Catalans",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
} else {
the_labs <- labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = 'Grau de simpatia (0-10) cap\nals habitants de Catalunya',
title = "Vegades que ha viatjat a Catalunya i\ngrau de simpatia cap als catalans",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
library(databrew)
ggplot(data = pd,
aes(x = visits,
y = simpatia)) +
# geom_bar(stat = 'identity') +
# geom_area(alpha = 0.5, color = NA, fill = 'darkorange', group = 1) +
geom_point(size = 10) +
geom_segment(aes(xend = visits,
yend = 5),
alpha = 0.8,
# size = 2,
lty = 3) +
geom_line(alpha = 0.2, group = 1) +
geom_text(aes(label = round(simpatia, digits = 1)),
# nudge_y = 0.2,
# alpha = 0.8,
color = 'white',
size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22)) +
ylim(5, 7.2)
}
plot_viatges_i_odi <- function(ca = TRUE){
# Viatges a Cat i favorabilitat e Cats
pd <- pt %>%
filter(ccaa != 'Catalunya') %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
group_by(visits) %>%
summarise(avg = mean(simpatia, na.rm = TRUE),
n = n(),
n_no_na = length(which(!is.na(simpatia))),
n0 = length(which(simpatia == 0))) %>%
mutate(p0 = n0 / n_no_na * 100)
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = "Percentage who say 'I don't like them at all'",
title = "Extreme dislike of Catalans among Spaniards\nand times travelled to Catalonia",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
} else {
the_labs <- labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = "Percentatge qui diu que els catalans\n'em cauen molt malament'",
title = "Aversió extrema dels catalans i\nvegades que ha viatjat a Catalunya",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
library(databrew)
ggplot(data = pd,
aes(x = visits,
y = p0)) +
# geom_bar(stat = 'identity') +
# geom_area(alpha = 0.5, color = NA, fill = 'darkorange', group = 1) +
geom_point(size = 10) +
geom_segment(aes(xend = visits,
yend = 5),
alpha = 0.8,
# size = 2,
lty = 3) +
geom_line(alpha = 0.2, group = 1) +
geom_text(aes(label = round(p0, digits = 1)),
# nudge_y = 0.2,
# alpha = 0.8,
color = 'white',
size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22)) +
ylim(3.5, 12)
}
plot_support_referendum <- function(ca = FALSE){
# Viatges a Cat i suport pel referendum
pd <- pt %>%
filter(`Comunitat autònoma` != 'Catalunya') %>%
mutate(visits = `I d’aquestes, en concret, em podria dir quantes vegades a viatjat a Catalunya?`) %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
mutate(referendum = as.character(referendum)) %>%
mutate(referendum = ifelse(referendum %in% c('Nc', 'Nhs'),
'NS/NC', referendum)) %>%
group_by(visits, referendum) %>%
tally %>%
group_by(visits) %>%
mutate(p = n / sum(n) * 100) %>%
ungroup
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
pd$referendum <- as.character(pd$referendum)
pd$referendum <- ifelse(pd$referendum %in% c('Nhs', 'Nc'),
'NS/NC', pd$referendum)
pd$referendum <- factor(pd$referendum,
levels = c("Molt d’acord",
"Més aviat d’acord",
"NS/NC",
"Ni d’acord ni en desacord",
"Més aviat en desacord",
"Molt en desacord"))
pd$referendum <- factor(pd$referendum,
levels = rev(levels(pd$referendum)))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
pd$referendum <- factor(pd$referendum,
labels = rev(c("Strongly agree",
"Agree",
"Don't know/No answer",
"Neither agree nor disagree",
"Disagree",
"Strongly disagree")))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = 'Percentage',
title = "Times travelled to Catalonia\nand support for referendum",
subtitle = "Agreement with phrase: 'A referendum should take place so Catalans\ncan decide the relationship they want between Catalonia and the Spanish State'",
caption = "Data source: survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
legend_title <- ''
} else {
the_labs <-
labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = 'Percentatge',
title = "Vegades que ha viatjat a Catalunya i\nsuport al referèndum",
subtitle = "Grau d'acord amb la frase: 'S'hauria de fer un referèndum a Catalunya perquè els catalans i les\ncatalanes decidissin quina relació volen que hi hagi entre Catalunya i l'Estat espanyol'",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya'. Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
legend_title <- ""
}
library(databrew)
library(RColorBrewer)
cols <- brewer.pal(n = 6, 'Spectral')
cols[3] <- grey(c(0.5))
ggplot(data = pd,
aes(x = visits,
y = p)) +
geom_bar(stat = 'identity',
aes(fill = referendum),
alpha = 0.9) +
# geom_text(aes(label = round(simpatia, digits = 1)),
# # nudge_y = 0.2,
# # alpha = 0.8,
# color = 'white',
# size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22),
plot.caption = element_text(hjust = 0),
axis.text.x = element_text(size = 8),
plot.subtitle = element_text(size = 10)) +
theme(legend.position = 'right') +
scale_fill_manual(name = legend_title,
values = cols) +
geom_hline(yintercept = 50, lty = 2, alpha = 0.7)
}
# Grau de simpatia i suport pel referendum
plot_simpatia_referendum <- function(ca = TRUE){
pd <- pt %>%
filter(`Comunitat autònoma` != 'Catalunya') %>%
mutate(simpatia = `Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`) %>%
mutate(simpatia = simpatia_cleaner(simpatia)) %>%
mutate(referendum = as.character(referendum)) %>%
mutate(referendum = ifelse(referendum %in% c('Nc', 'Nhs'),
'NS/NC', referendum)) %>%
group_by(referendum, simpatia) %>%
tally %>%
group_by(simpatia) %>%
mutate(p = n / sum(n) * 100) %>%
ungroup
pd$referendum <- as.character(pd$referendum)
pd$referendum <- ifelse(pd$referendum %in% c('Nhs', 'Nc'),
'NS/NC', pd$referendum)
pd$referendum <- factor(pd$referendum,
levels = c("Molt d’acord",
"Més aviat d’acord",
"NS/NC",
"Ni d’acord ni en desacord",
"Més aviat en desacord",
"Molt en desacord"))
pd$referendum <- factor(pd$referendum,
levels = rev(levels(pd$referendum)))
if(!ca){
pd$referendum <- factor(pd$referendum,
labels = c("Strongly agree",
"Agree",
"Don't know/No answer",
"Neither agree nor disagree",
"Disagree",
"Strongly disagree"))
the_labs <- labs(x = 'How much do you like Catalans (0-10)?',
y = 'Percentage',
title = "Sympathy/antipathy for Catalans\nand support for referendum",
subtitle = "Agreement with phrase: 'A referendum should take place so Catalans\ncan decide the relationship they want between Catalonia and the Spanish State'",
caption = "Data source: survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
legend_title <- ''
} else {
the_labs <- labs(x = 'Grau de simpatia (escala 0 a 10)',
y = 'Percentatge',
title = "Grau de simpatia pels catalans i\nsuport al referèndum",
subtitle = "Grau d'acord amb la frase: 'S'hauria de fer un referèndum a Catalunya perquè els catalans i les\ncatalanes decidissin quina relació volen que hi hagi entre Catalunya i l'Estat espanyol'",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya. Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
cols <- brewer.pal(n = 6, 'Spectral')
cols[3] <- grey(c(0.5))
ggplot(data = pd,
aes(x = simpatia,
y = p)) +
geom_bar(stat = 'identity',
aes(fill = referendum),
alpha = 0.9) +
# geom_text(aes(label = round(simpatia, digits = 1)),
# # nudge_y = 0.2,
# # alpha = 0.8,
# color = 'white',
# size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22),
plot.caption = element_text(hjust = 0),
axis.text.x = element_text(size = 8),
plot.subtitle = element_text(size = 10)) +
theme(legend.position = 'right') +
scale_fill_manual(name = '',
values = cols) +
geom_hline(yintercept = 50, lty = 2, alpha = 0.7) +
scale_x_continuous(breaks = 0:10)
}
# Grau de simpatia cap als habitants
plot_simpatia_matrix <- function(ca = FALSE, var = 'avg', roundy = 1, reverse_color = FALSE, text_size = 4, only_indepes = FALSE){
library(RColorBrewer)
pd <- pt
if(only_indepes){
pd <- pd %>%
mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
filter(keep)
}
pd <- pd %>%
mutate(weight = `Coeficients de ponderació`) %>%
mutate(ccaa = `Comunitat autònoma`) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
weight)
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
pda <- pd
# Now agg and get averages
pd <- pd %>%
filter(!ccaa %in% c('Ceuta', 'Melilla'),
!key %in% c('Ceutencs')) %>%
group_by(ccaa, key) %>%
summarise(n = n(),
n_no_na = length(which(!is.na(value))),
avg = mean(value, na.rm = TRUE),
avgx = weighted.mean(x = value, w = weight, na.rm = TRUE),
p75 = quantile(value, 0.75, na.rm = TRUE),
p25 = quantile(value, 0.25, na.rm = TRUE),
n_zero = length(which(value == 0)),
n1 = length(which(value <= 1)),
n2 = length(which(value <= 2)),
n3 = length(which(value <= 3)),
n4 = length(which(value <=4)),
n5 = length(which(value <= 5)),
n6 = length(which(value <= 6)),
n10 = length(which(value == 10))) %>%
mutate(p0 = n_zero / n_no_na * 100,
p1 = n1 / n_no_na * 100,
p2 = n2 / n_no_na * 100,
p3 = n3 / n_no_na * 100,
p4 = n4 / n_no_na * 100,
p5 = n5 / n_no_na * 100,
p10 = n10 / n_no_na * 100)
pd <- pd %>% ungroup %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE))
# Fix x-value if only indepes
if(only_indepes){
if(ca){
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Catalunya',
'Catalunya\n(només independentistes)',
ifelse(levels(pd$gent_de) == 'Euskadi/País Basc', 'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa', 'Castella - la Manxa', levels(pd$gent_de)))))
} else {
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Catalunya',
'Catalunya\n(only pro-indy)',
ifelse(levels(pd$gent_de) == 'Euskadi/País Basc', 'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa', 'Castella - la Manxa', levels(pd$gent_de)))))
}
} else {
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Euskadi/País Basc',
'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa',
'Castella - la Manxa',
levels(pd$gent_de))))
}
pd$cap_a <- factor(pd$cap_a,
levels = levels(pd$cap_a),
labels = ifelse(levels(pd$cap_a) == 'Euskadi/País Basc',
'País Basc',
ifelse(levels(pd$cap_a) == 'Castella la Manxa',
'Castella - la Manxa',
levels(pd$cap_a))))
if(ca){
the_labs <- labs(x = 'Grau de simpatia de les persones d\'aquí',
y = '...cap a les persones d\'aquí',
title = 'Grau de simpatia cap als habitants de les altres\ncomunitats autònomes, segons comunitat autònoma',
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
} else {
the_labs <- labs(x = 'How people from here feel...',
y = '...about people from here',
title = "How people from one area feel\nabout people from another area",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
}
# Define the variable
pd$y <- as.numeric(unlist(pd[,var] ))
# Colors
cols <- colorRampPalette(brewer.pal(n = 9, name = 'Spectral'))(10)
if(reverse_color){
cols <- rev(cols)
}
ggplot(data = pd,
aes(x = gent_de,
y = cap_a)) +
geom_point(size = 7.5,
aes(color = y)) +
# geom_point(size = 5,
# aes(#size = avg,
# # color = p2
# # color = avg
# )) +
# ggthemes::theme_fivethirtyeight() +
scale_color_gradientn(colours = cols) +
the_labs +
theme_simple() +
theme(axis.text.x = element_text(angle = 90,
hjust = 1,
vjust = 0.5),
plot.title = element_text(size = 13)) +
geom_text(aes(label = round(y, digits = roundy)), size = text_size) +
theme(legend.position = 'none')
}
# Get average
get_avg <- function(where_from = 'Catalunya',
var = 'avg',
where_to = label_df$ccaa[label_df$ccaa != 'Catalunya']){
pd <- pt %>%
# mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
# mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
# filter(keep) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
contains('weight'))
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
# Now agg and get averages
pd <- pd %>%
# filter(!ccaa %in% c('Ceuta', 'Melilla'),
# !key %in% c('Ceutencs')) %>%
group_by(ccaa, key) %>%
summarise(n = n(),
n_no_na = length(which(!is.na(value))),
avg = mean(value, na.rm = TRUE),
p75 = quantile(value, 0.75, na.rm = TRUE),
p25 = quantile(value, 0.25, na.rm = TRUE),
n_zero = length(which(value == 0)),
n1 = length(which(value <= 1)),
n2 = length(which(value <= 2)),
n3 = length(which(value <= 3)),
n4 = length(which(value <=4)),
n5 = length(which(value <= 5)),
n6 = length(which(value <= 6)),
n10 = length(which(value == 10))) %>%
mutate(p0 = n_zero / n_no_na * 100,
p1 = n1 / n_no_na * 100,
p2 = n2 / n_no_na * 100,
p3 = n3 / n_no_na * 100,
p4 = n4 / n_no_na * 100,
p5 = n5 / n_no_na * 100,
p10 = n10 / n_no_na * 100)
pd <- pd %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE))
pd$y <- as.numeric(unlist(pd[,var]))
pd %>% ungroup %>%
filter(gent_de %in% where_from,
cap_a %in% where_to) %>%
summarise(avg = mean(y, na.rm = T)) %>%
.$avg
}
# For each ccaa, what do the people there think of catalans compared to what catalans think of them
plot_compare <- function(ca = TRUE, only_indepes = FALSE){
pd <- pt
if(only_indepes){
pd <- pd %>%
mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
filter(keep)
}
pd <- pd %>%
mutate(weight = `Coeficients de ponderació`) %>%
mutate(ccaa = `Comunitat autònoma`) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
weight)
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
# Rename
pd <- pd %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE)) %>%
dplyr::select(gent_de,
cap_a, value, weight) %>%
group_by(gent_de, cap_a) %>%
summarise(avg = mean(value, na.rm = TRUE),
value_weighted = weighted.mean(value, w= weight, na.rm = TRUE)) %>%
mutate(value = avg)
pd$discrep <- pd$value - pd$value_weighted
# Keep only what people think about catalans or vice-versa
pd <- pd %>%
filter(gent_de == 'Catalunya' | cap_a == 'Catalunya')
# Define the ccaa
pd$cap_a <- as.character(pd$cap_a); pd$gent_de <- as.character(pd$gent_de)
pd$ccaa <- ifelse(pd$cap_a == 'Catalunya', pd$gent_de,
ifelse(pd$gent_de == 'Catalunya', pd$cap_a,
NA))
pd <- pd %>%
filter(!(cap_a == 'Catalunya' & gent_de == 'Catalunya')) %>%
filter(!ccaa %in% c('Ceuta', 'Melilla'))
# Make a new var
if(ca){
if(only_indepes){
levs <- c('Valoració mitjana dels habitants\nd\'aquesta comunitat cap als catalans',
'Valoració mitjana de catalans INDEPENDENTISTES\ncap als habitants d\'aquesta comunitat')
} else {
levs <- c('Valoració mitjana dels habitants d\'aquesta\ncomunitat cap als catalans',
'Valoració mitjana dels catalans cap\nals habitants d\'aquesta comunitat')
}
the_labs <- labs(x = '',
y = "Valoració mitjana (0-10)",
title = 'Grau de simpatia entre catalans i habitants\nde les altres comunitats autònomes',
caption = 'Escala de 0 a 10 on 0 significa: "Em cauen molt malament" i 10 significa: "Em cauen molt bé".\nDades de l\'enquesta "Percepció sobre el debat territorial a Espanya. 2019", Centre d\'Estudis d\'Opinió.\nEl text entre parèntesis és la xifra NO ponderada. La ponderació fa servir factors demogràfics per ajustar pel biaix de selecció/mostratge.\nMés detalls sobre la ponderació a http://upceo.ceo.gencat.cat/wsceop/7368/Press%20dossier%20-952.pdf\nGràfic de Joe Brew, @joethebrew. Codi a https://github.com/joebrew/vilaweb/tree/master/analyses/filiafobia')
} else {
if(only_indepes){
levs <- c('How people from this area\nfeel about Catalans',
'How PRO-INDY Catalans feel\nabout people from this area')
} else {
levs <- c('How people from this area\nfeel about Catalans',
'How Catalans feel about\npeople from this area')
}
the_labs <- labs(x = '',
y = "Degree to which they 'like' the other (0-10)",
title = 'Degree to which Catalans and inhabitants of\nother regions like one another',
caption = 'Scale from 0 to 10, where 0 means "I don\'t like them at all" and 10 means "I like them a lot".\nData from the survey "Percepció sobre el debat territorial a Espanya. 2019", Centre d\'Estudis d\'Opinió.\nText in parenthesis is the unadjusted/raw figure. Adjustment used demographic factors to generate weights to account for sampling bias.\nFull details on weighting at http://upceo.ceo.gencat.cat/wsceop/7368/Press%20dossier%20-952.pdf\nChart by Joe Brew, @joethebrew. Code at https://github.com/joebrew/vilaweb/tree/master/analyses/filiafobia')
}
pd$var <- ifelse(pd$cap_a == 'Catalunya', levs[1], levs[2])
pd$var <- factor(pd$var, levels = levs)
# Get the corrected levels order
pd$ccaa <- factor(pd$ccaa,
levels = c('Andalusia',
'Aragó',
'Astúries',
'Balears',
'Canàries',
'Cantàbria',
'Castella i Lleó',
'Castella la Manxa',
'Extremadura',
'Galícia',
'Madrid',
'Múrcia',
'Navarra',
'Euskadi/País Basc',
'País Valencià',
'La Rioja'))
fl <- levels(pd$ccaa)
pd$ccaa <- factor(pd$ccaa, levels = fl,
labels = gsub('Castella', 'Cas.', gsub('Euskadi/','', fl)))
ggplot(data = pd,
aes(x = var,
y = value_weighted)) +
geom_line(aes(group = ccaa), alpha = 0.7) +
geom_point(aes(color = var), size = 9) +
facet_wrap(~ccaa, nrow = 2) +
theme_simple() +
theme(axis.text.x = element_blank(),
strip.text = element_text(size = 8)) +
scale_color_manual(name = '',
values = c('darkorange', 'lightblue')) +
geom_text(aes(label = round(value_weighted, digits = 1))) +
the_labs +
ylim(min(pd$value_weighted) - 0.7,
max(pd$value_weighted) + 0.5) +
theme(legend.position = 'top',
plot.title = element_text(size = 16),
legend.text = element_text(size = 10),
plot.caption = element_text(size = 8)) +
geom_text(aes(label = paste0('(',
round(value, digits = 1),
')')),
nudge_y = -0.6,
size = 2.5, alpha = 0.8, color = 'black')
}
# Autonomia
# Pel que fa a les relacions entre Catalunya i Espanya, creieu que Catalunya ha assolit...
# pt$`Pel que fa a les relacions entre Catalunya i la resta de l’Estat espanyol, què diríeu que és més necessari?`
# Libraries
library(vilaweb)
library(tidyverse)
library(lubridate)
# Line breaker function
line_breaker <- function(x,n = 10){
gsub(paste0('(.{1,',n,'})(\\s|$)'), '\\1\n', x)
}
df <- dff <- tibble(
partit = c('PP', 'PSC', 'Cs', 'JxCat', 'ERC', 'Comuns'),
`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c(40.9, 35.3, 33.3, 21.4, 19.1, 17.7),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c(6.8, 7.8, 7.5, 8.4, 8.5, 8.3),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c(7.6, 8.4, 8.4, 8.6, 8.9, 9),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c(50.5, 24.7, 42.4, 16.1, 13.4, 13.8),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c(62.2, 32.2, 50.5, 32.9, 25.8, 30.7),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c(9.3, 37.5, 13, 48.1, 47.3, 56.8)
)
fonts <- font <- tibble(`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% "agree" or "very much agree" that "immigrants should abandon their culture of origin and aopt the culture of the country where they have arrived"'),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "I like learning from other cultures"'),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "No specific culture is superior to others"'),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% that wants to "put strict limits on the number of foreigners that can come here" or "completely ban" their arrival'),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c("Aggregació d'enquestes CEO, 2015 i 2018. Mostra: 3.127 residents de Catalunya amb ciutadania espanyola. Preguntes P56i i P31.", 'Extent of agreement with the phrase "With so much immigration, one no longer feels at home"'),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c('http://upceo.ceo.gencat.cat/wsceop/7428/Dossier%20de%20premsa%20-955.pdf', '% that wants to spend more on welcoming immigrants'))
pd <- df %>%
gather(key, value, names(df)[2:length(names(df))])
pd$partit <- factor(pd$partit, levels = c('PP', 'Cs', 'PSC', 'Comuns', 'JxCat', 'ERC'))
keys <- unique(pd$key)
key_plot <- function(index = 1, ca = FALSE){
df <- dff <- tibble(
partit = c('PP', 'PSC', 'Cs', 'JxCat', 'ERC', 'Comuns'),
`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c(40.9, 35.3, 33.3, 21.4, 19.1, 17.7),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c(6.8, 7.8, 7.5, 8.4, 8.5, 8.3),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c(7.6, 8.4, 8.4, 8.6, 8.9, 9),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c(50.5, 24.7, 42.4, 16.1, 13.4, 13.8),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c(62.2, 32.2, 50.5, 32.9, 25.8, 30.7),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c(9.3, 37.5, 13, 48.1, 47.3, 56.8)
)
fonts <- font <- tibble(`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% "agree" or "very much agree" that "immigrants should abandon their culture of origin and aopt the culture of the country where they have arrived"'),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "I like learning from other cultures"'),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "No specific culture is superior to others"'),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% that wants to "put strict limits on the number of foreigners that can come here" or "completely ban" their arrival'),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c("Aggregació d'enquestes CEO, 2015 i 2018. Mostra: 3.127 residents de Catalunya amb ciutadania espanyola. Preguntes P56i i P31.", 'Extent of agreement with the phrase "With so much immigration, one no longer feels at home"'),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c('http://upceo.ceo.gencat.cat/wsceop/7428/Dossier%20de%20premsa%20-955.pdf', '% that wants to spend more on welcoming immigrants'))
pd <- df %>%
gather(key, value, names(df)[2:length(names(df))])
pd$partit <- factor(pd$partit, levels = c('PP', 'Cs', 'PSC', 'Comuns', 'JxCat', 'ERC'))
keys <- unique(pd$key)
this_key <- keys[index]
sub_pd <- pd %>% filter(key == this_key)
font1 <- unlist(fonts[,this_key][1,])
font2 <- unlist(fonts[,this_key][2,])
if(ca){
the_labs <- the_labs <- labs(x = '',
y = 'Percentatge/grau d\'acord',
title = line_breaker(this_key, n = 65),
caption = paste0("Font de dades: ", line_breaker(font[1, index], n = 100)))
} else {
the_labs <- labs(x = '',
y = 'Percentage/Extent of agreement',
title = line_breaker(fonts[2,index], n = 65),
caption = paste0("Source of data: ", line_breaker(font[1,index], n = 100)))
}
ggplot(data = sub_pd %>% mutate(key = line_breaker(key, 60)),
aes(x = partit,
y = value,
fill = partit,
color = partit)) +
geom_bar(stat = 'identity', alpha = 0.5,
# color = 'black',
lwd = 0.3) +
# facet_wrap(~key, scales = 'free') +
databrew::theme_simple() +
scale_fill_manual(name = '',
values = c('blue', 'darkorange', 'darkred', 'lightblue', 'purple', 'yellow')) +
scale_color_manual(name = '',
values = c('blue', 'darkorange', 'darkred', 'lightblue', 'purple', 'yellow')) +
theme(legend.position = 'none',
strip.text = element_text(size = 18),
axis.text.x = element_text(size = 18),
axis.text.y = element_text(size = 14),
plot.caption = element_text(size = 8)) +
geom_text(aes(label = paste0(round(value, digits = 1), ''),
y = (value * 0.9) - 1),
color = 'black',
size = 7,
alpha = 0.7) +
the_labs
}
# dir.create('~/Desktop/plots')
# for(i in 1:6){
# print(key_plot(i))
# ggsave(paste0('~/Desktop/plots/', i, '.png'))
# }
joebrew/vilaweb documentation built on Sept. 11, 2020, 3:42 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# Libraries
library(vilaweb)
library(tidyverse)
library(lubridate)
library(databrew)
library(tidylog)
options(scipen = 999)
plot_twitter <- function(ca = TRUE){
pd <- fobia %>% filter(key == 'Hispanofòbia') %>%
group_by(date = as.Date(cut(date, 'month'))) %>%
summarise(n = n(),
rt = sum(retweets_count))
if(ca){
the_labs <- labs(x = 'Mes',
y = 'Piulets (escala logarítmica)',
title = "Piulets amb la paraula de 'hispanofòbia'",
subtitle = 'Dades de Twitter, incloent-hi repiulets',
caption = 'Gràfic de Joe Brew, @joethebrew')
} else {
the_labs <- labs(x = 'Month',
y = 'Piulets (log scale)',
title = "Tweets with the word 'Hispanophobia'",
subtitle = 'Data from Twitter, including retweets',
caption = 'Chart by Joe Brew, @joethebrew.')
}
ggplot(data = pd,
aes(x = date,
y = rt + n)) +
geom_line() +
# geom_path(color = 'darkorange', alpha = 0.6) +
theme_simple() +
scale_y_log10() +
the_labs
}
plot_google <- function(ca = TRUE){
# Read in google trends data (retrieved 23 jan 2020)
google <- read_csv('multiTimeline.csv', skip = 1)
google$date <- as.Date(paste0(google$Month, '-01'))
# google$date <- as.Date(cut(google$date, 'year'))
google$value <- google$`hispanofobia: (Spain)`
if(ca){
the_labs <- labs(x = 'Mes',
y = 'Percentatge (escala logarítmica)',
title = "Cerques de 'hispanofòbia'",
subtitle = 'Dades de Google Trends',
caption = 'Percentatge: cerques mensuals relatives al màxim. Gràfic de Joe Brew, @joethebrew')
} else {
the_labs <- labs(x = 'Month',
y = 'Percentage (log scale)',
title = "Searches for 'Hispanophobia'",
subtitle = 'Data from Google Trends',
caption = 'Percentage: monthly searches relative to the maximum. Chart by Joe Brew, @joethebrew.')
}
pd <- google %>%
group_by(date) %>%
summarise(value = mean(value))
ggplot(data = pd,
aes(x = date,
y = value)) +
geom_line() +
# geom_path(color = 'darkorange', alpha = 0.6) +
theme_simple() +
scale_y_log10(breaks = c(0:3, 5,10,25, 50, 100)) +
the_labs
}
# Read in the territorial survey data
pt <- vilaweb::ceo_percepcio_territorial
# Function for cleaning up the sympathy variable
simpatia_cleaner <- function(x){
x <- as.character(x)
x <- ifelse(x %in% c('No contesta', 'No ho sap'), NA,
ifelse(x == 'Us cauen molt bé 10', '10',
ifelse(x == 'No us cauen ni bé ni malament 5', 5,
ifelse(x == 'Us cauen molt malament 0', '0',
x))))
x <- as.numeric(x)
return(x)
}
pt <- pt %>%
mutate(visits = `I d’aquestes, en concret, em podria dir quantes vegades a viatjat a Catalunya?`,
simpatia = `Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`,
referendum = `Grau d'acord: S’hauria de fer un referèndum a Catalunya perquè els catalans i les catalanes decidissin quina relació volen que hi hagi entre Catalunya i l’Estat espanyol`) %>%
mutate(simpatia = simpatia_cleaner(simpatia)) %>%
mutate(ccaa = `Comunitat autònoma`)
# # Companeros de trabajo
# pt$`Amb independència que treballeu o no, quins són els tres que menys us agradaria tenir com a companys de feina o treball? Catalans`
#
# # Grau de simpatia
# pt$`Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`
# Define the label sets (for factor ordering)
label_df <- tibble(
ccaa = c('Andalusia',
'Aragó',
'Astúries',
'Balears',
'Canàries',
'Cantàbria',
'Castella la Manxa',
'Castella i Lleó',
'Catalunya',
'Extremadura',
'Galícia',
'Madrid',
'Múrcia',
'Navarra',
'Euskadi/País Basc',
'País Valencià',
'La Rioja', 'Ceuta', 'Melilla'),
key = c('Andalusos',
'Aragonesos',
'Asturians',
'Balears',
'Canaris',
'Càntabres',
'Castellanomanxecs',
'Castellanolleonesos',
'Catalans',
'Extremenys',
'Gallecs',
'Madrilenys',
'Murcians',
'Navarresos',
'Bascos',
'Valencians',
'Riojans',
'Ceutencs',
'Melillencs')
)
label_df$ccaa <- factor(label_df$ccaa, levels = label_df$ccaa)
label_df$key <- factor(label_df$key, levels = label_df$key)
fix_levels <- function(var, from_place = FALSE, to_place = TRUE){
if(from_place){
x <- tibble(ccaa = var)
} else {
x <- tibble(key = var)
}
# Join with the labels
joined <- left_join(x, label_df)
# Get the return val
if(to_place){
out <- joined$ccaa
out <- factor(out, levels = label_df$ccaa)
} else {
out <- joined$key
out <- factor(out, levels = label_df$key)
}
return(out)
}
plot_viatges_i_simpatia <- function(ca = TRUE){
# Viatges a Cat i favorabilitat e Cats
pd <- pt %>%
filter(ccaa != 'Catalunya') %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
group_by(visits) %>%
summarise(simpatia = mean(simpatia, na.rm = TRUE),
n = n())
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = 'Degree of sympathy (0-10) for\nthe residents of Catalonia',
title = "Times travelled to Catalonia and\nfeelings about Catalans",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
} else {
the_labs <- labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = 'Grau de simpatia (0-10) cap\nals habitants de Catalunya',
title = "Vegades que ha viatjat a Catalunya i\ngrau de simpatia cap als catalans",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
library(databrew)
ggplot(data = pd,
aes(x = visits,
y = simpatia)) +
# geom_bar(stat = 'identity') +
# geom_area(alpha = 0.5, color = NA, fill = 'darkorange', group = 1) +
geom_point(size = 10) +
geom_segment(aes(xend = visits,
yend = 5),
alpha = 0.8,
# size = 2,
lty = 3) +
geom_line(alpha = 0.2, group = 1) +
geom_text(aes(label = round(simpatia, digits = 1)),
# nudge_y = 0.2,
# alpha = 0.8,
color = 'white',
size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22)) +
ylim(5, 7.2)
}
plot_viatges_i_odi <- function(ca = TRUE){
# Viatges a Cat i favorabilitat e Cats
pd <- pt %>%
filter(ccaa != 'Catalunya') %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
group_by(visits) %>%
summarise(avg = mean(simpatia, na.rm = TRUE),
n = n(),
n_no_na = length(which(!is.na(simpatia))),
n0 = length(which(simpatia == 0))) %>%
mutate(p0 = n0 / n_no_na * 100)
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = "Percentage who say 'I don't like them at all'",
title = "Extreme dislike of Catalans among Spaniards\nand times travelled to Catalonia",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
} else {
the_labs <- labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = "Percentatge qui diu que els catalans\n'em cauen molt malament'",
title = "Aversió extrema dels catalans i\nvegades que ha viatjat a Catalunya",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
library(databrew)
ggplot(data = pd,
aes(x = visits,
y = p0)) +
# geom_bar(stat = 'identity') +
# geom_area(alpha = 0.5, color = NA, fill = 'darkorange', group = 1) +
geom_point(size = 10) +
geom_segment(aes(xend = visits,
yend = 5),
alpha = 0.8,
# size = 2,
lty = 3) +
geom_line(alpha = 0.2, group = 1) +
geom_text(aes(label = round(p0, digits = 1)),
# nudge_y = 0.2,
# alpha = 0.8,
color = 'white',
size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22)) +
ylim(3.5, 12)
}
plot_support_referendum <- function(ca = FALSE){
# Viatges a Cat i suport pel referendum
pd <- pt %>%
filter(`Comunitat autònoma` != 'Catalunya') %>%
mutate(visits = `I d’aquestes, en concret, em podria dir quantes vegades a viatjat a Catalunya?`) %>%
filter(!is.na(visits)) %>%
filter(!visits %in% c('No ho sap', 'No contesta')) %>%
mutate(referendum = as.character(referendum)) %>%
mutate(referendum = ifelse(referendum %in% c('Nc', 'Nhs'),
'NS/NC', referendum)) %>%
group_by(visits, referendum) %>%
tally %>%
group_by(visits) %>%
mutate(p = n / sum(n) * 100) %>%
ungroup
pd$visits <- factor(pd$visits,
levels = unique(c('No, mai',
levels(pd$visits))))
pd$visits <- factor(pd$visits,
levels = levels(pd$visits),
labels = gsub(' vegad', '\nvegad', c('Mai', levels(pd$visits)[2:length(levels(pd$visits))])))
pd$referendum <- as.character(pd$referendum)
pd$referendum <- ifelse(pd$referendum %in% c('Nhs', 'Nc'),
'NS/NC', pd$referendum)
pd$referendum <- factor(pd$referendum,
levels = c("Molt d’acord",
"Més aviat d’acord",
"NS/NC",
"Ni d’acord ni en desacord",
"Més aviat en desacord",
"Molt en desacord"))
pd$referendum <- factor(pd$referendum,
levels = rev(levels(pd$referendum)))
if(!ca){
pd$visits <- factor(pd$visits,
labels = c('Never', 'Just\nonce',
'2-5 times',
'6-10 times',
'More than\n10 times'))
pd$referendum <- factor(pd$referendum,
labels = rev(c("Strongly agree",
"Agree",
"Don't know/No answer",
"Neither agree nor disagree",
"Disagree",
"Strongly disagree")))
the_labs <- labs(x = 'How many times have you travelled to Catalonia?',
y = 'Percentage',
title = "Times travelled to Catalonia\nand support for referendum",
subtitle = "Agreement with phrase: 'A referendum should take place so Catalans\ncan decide the relationship they want between Catalonia and the Spanish State'",
caption = "Data source: survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
legend_title <- ''
} else {
the_labs <-
labs(x = 'Quantes vegades ha viatjat a Catalunya?',
y = 'Percentatge',
title = "Vegades que ha viatjat a Catalunya i\nsuport al referèndum",
subtitle = "Grau d'acord amb la frase: 'S'hauria de fer un referèndum a Catalunya perquè els catalans i les\ncatalanes decidissin quina relació volen que hi hagi entre Catalunya i l'Estat espanyol'",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya'. Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
legend_title <- ""
}
library(databrew)
library(RColorBrewer)
cols <- brewer.pal(n = 6, 'Spectral')
cols[3] <- grey(c(0.5))
ggplot(data = pd,
aes(x = visits,
y = p)) +
geom_bar(stat = 'identity',
aes(fill = referendum),
alpha = 0.9) +
# geom_text(aes(label = round(simpatia, digits = 1)),
# # nudge_y = 0.2,
# # alpha = 0.8,
# color = 'white',
# size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22),
plot.caption = element_text(hjust = 0),
axis.text.x = element_text(size = 8),
plot.subtitle = element_text(size = 10)) +
theme(legend.position = 'right') +
scale_fill_manual(name = legend_title,
values = cols) +
geom_hline(yintercept = 50, lty = 2, alpha = 0.7)
}
# Grau de simpatia i suport pel referendum
plot_simpatia_referendum <- function(ca = TRUE){
pd <- pt %>%
filter(`Comunitat autònoma` != 'Catalunya') %>%
mutate(simpatia = `Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: Catalans`) %>%
mutate(simpatia = simpatia_cleaner(simpatia)) %>%
mutate(referendum = as.character(referendum)) %>%
mutate(referendum = ifelse(referendum %in% c('Nc', 'Nhs'),
'NS/NC', referendum)) %>%
group_by(referendum, simpatia) %>%
tally %>%
group_by(simpatia) %>%
mutate(p = n / sum(n) * 100) %>%
ungroup
pd$referendum <- as.character(pd$referendum)
pd$referendum <- ifelse(pd$referendum %in% c('Nhs', 'Nc'),
'NS/NC', pd$referendum)
pd$referendum <- factor(pd$referendum,
levels = c("Molt d’acord",
"Més aviat d’acord",
"NS/NC",
"Ni d’acord ni en desacord",
"Més aviat en desacord",
"Molt en desacord"))
pd$referendum <- factor(pd$referendum,
levels = rev(levels(pd$referendum)))
if(!ca){
pd$referendum <- factor(pd$referendum,
labels = c("Strongly agree",
"Agree",
"Don't know/No answer",
"Neither agree nor disagree",
"Disagree",
"Strongly disagree"))
the_labs <- labs(x = 'How much do you like Catalans (0-10)?',
y = 'Percentage',
title = "Sympathy/antipathy for Catalans\nand support for referendum",
subtitle = "Agreement with phrase: 'A referendum should take place so Catalans\ncan decide the relationship they want between Catalonia and the Spanish State'",
caption = "Data source: survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
legend_title <- ''
} else {
the_labs <- labs(x = 'Grau de simpatia (escala 0 a 10)',
y = 'Percentatge',
title = "Grau de simpatia pels catalans i\nsuport al referèndum",
subtitle = "Grau d'acord amb la frase: 'S'hauria de fer un referèndum a Catalunya perquè els catalans i les\ncatalanes decidissin quina relació volen que hi hagi entre Catalunya i l'Estat espanyol'",
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya. Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
}
cols <- brewer.pal(n = 6, 'Spectral')
cols[3] <- grey(c(0.5))
ggplot(data = pd,
aes(x = simpatia,
y = p)) +
geom_bar(stat = 'identity',
aes(fill = referendum),
alpha = 0.9) +
# geom_text(aes(label = round(simpatia, digits = 1)),
# # nudge_y = 0.2,
# # alpha = 0.8,
# color = 'white',
# size = 3.6) +
the_labs +
theme_simple(black = T, base_size = 16) +
theme(plot.title = element_text(size = 22),
plot.caption = element_text(hjust = 0),
axis.text.x = element_text(size = 8),
plot.subtitle = element_text(size = 10)) +
theme(legend.position = 'right') +
scale_fill_manual(name = '',
values = cols) +
geom_hline(yintercept = 50, lty = 2, alpha = 0.7) +
scale_x_continuous(breaks = 0:10)
}
# Grau de simpatia cap als habitants
plot_simpatia_matrix <- function(ca = FALSE, var = 'avg', roundy = 1, reverse_color = FALSE, text_size = 4, only_indepes = FALSE){
library(RColorBrewer)
pd <- pt
if(only_indepes){
pd <- pd %>%
mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
filter(keep)
}
pd <- pd %>%
mutate(weight = `Coeficients de ponderació`) %>%
mutate(ccaa = `Comunitat autònoma`) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
weight)
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
pda <- pd
# Now agg and get averages
pd <- pd %>%
filter(!ccaa %in% c('Ceuta', 'Melilla'),
!key %in% c('Ceutencs')) %>%
group_by(ccaa, key) %>%
summarise(n = n(),
n_no_na = length(which(!is.na(value))),
avg = mean(value, na.rm = TRUE),
avgx = weighted.mean(x = value, w = weight, na.rm = TRUE),
p75 = quantile(value, 0.75, na.rm = TRUE),
p25 = quantile(value, 0.25, na.rm = TRUE),
n_zero = length(which(value == 0)),
n1 = length(which(value <= 1)),
n2 = length(which(value <= 2)),
n3 = length(which(value <= 3)),
n4 = length(which(value <=4)),
n5 = length(which(value <= 5)),
n6 = length(which(value <= 6)),
n10 = length(which(value == 10))) %>%
mutate(p0 = n_zero / n_no_na * 100,
p1 = n1 / n_no_na * 100,
p2 = n2 / n_no_na * 100,
p3 = n3 / n_no_na * 100,
p4 = n4 / n_no_na * 100,
p5 = n5 / n_no_na * 100,
p10 = n10 / n_no_na * 100)
pd <- pd %>% ungroup %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE))
# Fix x-value if only indepes
if(only_indepes){
if(ca){
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Catalunya',
'Catalunya\n(només independentistes)',
ifelse(levels(pd$gent_de) == 'Euskadi/País Basc', 'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa', 'Castella - la Manxa', levels(pd$gent_de)))))
} else {
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Catalunya',
'Catalunya\n(only pro-indy)',
ifelse(levels(pd$gent_de) == 'Euskadi/País Basc', 'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa', 'Castella - la Manxa', levels(pd$gent_de)))))
}
} else {
pd$gent_de <- factor(pd$gent_de,
levels = levels(pd$gent_de),
labels = ifelse(levels(pd$gent_de) == 'Euskadi/País Basc',
'País Basc',
ifelse(levels(pd$gent_de) == 'Castella la Manxa',
'Castella - la Manxa',
levels(pd$gent_de))))
}
pd$cap_a <- factor(pd$cap_a,
levels = levels(pd$cap_a),
labels = ifelse(levels(pd$cap_a) == 'Euskadi/País Basc',
'País Basc',
ifelse(levels(pd$cap_a) == 'Castella la Manxa',
'Castella - la Manxa',
levels(pd$cap_a))))
if(ca){
the_labs <- labs(x = 'Grau de simpatia de les persones d\'aquí',
y = '...cap a les persones d\'aquí',
title = 'Grau de simpatia cap als habitants de les altres\ncomunitats autònomes, segons comunitat autònoma',
caption = "Font de dades: Enquesta 'Percepció sobre el debat territorial a Espanya' del Centre d'Estudis d'Opinió.\nGràfic: @joethebrew")
} else {
the_labs <- labs(x = 'How people from here feel...',
y = '...about people from here',
title = "How people from one area feel\nabout people from another area",
caption = "Data source: Survey 'Percepció sobre el debat territorial a Espanya' from the Centre d'Estudis d'Opinió.\nChart: @joethebrew")
}
# Define the variable
pd$y <- as.numeric(unlist(pd[,var] ))
# Colors
cols <- colorRampPalette(brewer.pal(n = 9, name = 'Spectral'))(10)
if(reverse_color){
cols <- rev(cols)
}
ggplot(data = pd,
aes(x = gent_de,
y = cap_a)) +
geom_point(size = 7.5,
aes(color = y)) +
# geom_point(size = 5,
# aes(#size = avg,
# # color = p2
# # color = avg
# )) +
# ggthemes::theme_fivethirtyeight() +
scale_color_gradientn(colours = cols) +
the_labs +
theme_simple() +
theme(axis.text.x = element_text(angle = 90,
hjust = 1,
vjust = 0.5),
plot.title = element_text(size = 13)) +
geom_text(aes(label = round(y, digits = roundy)), size = text_size) +
theme(legend.position = 'none')
}
# Get average
get_avg <- function(where_from = 'Catalunya',
var = 'avg',
where_to = label_df$ccaa[label_df$ccaa != 'Catalunya']){
pd <- pt %>%
# mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
# mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
# filter(keep) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
contains('weight'))
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
# Now agg and get averages
pd <- pd %>%
# filter(!ccaa %in% c('Ceuta', 'Melilla'),
# !key %in% c('Ceutencs')) %>%
group_by(ccaa, key) %>%
summarise(n = n(),
n_no_na = length(which(!is.na(value))),
avg = mean(value, na.rm = TRUE),
p75 = quantile(value, 0.75, na.rm = TRUE),
p25 = quantile(value, 0.25, na.rm = TRUE),
n_zero = length(which(value == 0)),
n1 = length(which(value <= 1)),
n2 = length(which(value <= 2)),
n3 = length(which(value <= 3)),
n4 = length(which(value <=4)),
n5 = length(which(value <= 5)),
n6 = length(which(value <= 6)),
n10 = length(which(value == 10))) %>%
mutate(p0 = n_zero / n_no_na * 100,
p1 = n1 / n_no_na * 100,
p2 = n2 / n_no_na * 100,
p3 = n3 / n_no_na * 100,
p4 = n4 / n_no_na * 100,
p5 = n5 / n_no_na * 100,
p10 = n10 / n_no_na * 100)
pd <- pd %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE))
pd$y <- as.numeric(unlist(pd[,var]))
pd %>% ungroup %>%
filter(gent_de %in% where_from,
cap_a %in% where_to) %>%
summarise(avg = mean(y, na.rm = T)) %>%
.$avg
}
# For each ccaa, what do the people there think of catalans compared to what catalans think of them
plot_compare <- function(ca = TRUE, only_indepes = FALSE){
pd <- pt
if(only_indepes){
pd <- pd %>%
mutate(indepe = `I, personalment, estaríeu a favor o en contra que Catalunya fos independent?`) %>%
mutate(keep = ccaa != 'Catalunya' | indepe == 'Hi estaria a favor') %>%
filter(keep)
}
pd <- pd %>%
mutate(weight = `Coeficients de ponderació`) %>%
mutate(ccaa = `Comunitat autònoma`) %>%
dplyr::select(contains('Grau de simpatia cap als habitants'),
contains('ccaa'),
weight)
names(pd) <- gsub("Grau de simpatia cap als habitants de cadascuna de les diferents comunitats autònomes: ", '', names(pd))
# Make long
pd <- pd %>% gather(key, value, Andalusos:Ceutencs)
pd$value <- simpatia_cleaner(pd$value)
# Rename
pd <- pd %>%
mutate(gent_de = fix_levels(ccaa, from_place = TRUE, to_place = TRUE),
cap_a = fix_levels(key, from_place = FALSE, to_place = TRUE)) %>%
dplyr::select(gent_de,
cap_a, value, weight) %>%
group_by(gent_de, cap_a) %>%
summarise(avg = mean(value, na.rm = TRUE),
value_weighted = weighted.mean(value, w= weight, na.rm = TRUE)) %>%
mutate(value = avg)
pd$discrep <- pd$value - pd$value_weighted
# Keep only what people think about catalans or vice-versa
pd <- pd %>%
filter(gent_de == 'Catalunya' | cap_a == 'Catalunya')
# Define the ccaa
pd$cap_a <- as.character(pd$cap_a); pd$gent_de <- as.character(pd$gent_de)
pd$ccaa <- ifelse(pd$cap_a == 'Catalunya', pd$gent_de,
ifelse(pd$gent_de == 'Catalunya', pd$cap_a,
NA))
pd <- pd %>%
filter(!(cap_a == 'Catalunya' & gent_de == 'Catalunya')) %>%
filter(!ccaa %in% c('Ceuta', 'Melilla'))
# Make a new var
if(ca){
if(only_indepes){
levs <- c('Valoració mitjana dels habitants\nd\'aquesta comunitat cap als catalans',
'Valoració mitjana de catalans INDEPENDENTISTES\ncap als habitants d\'aquesta comunitat')
} else {
levs <- c('Valoració mitjana dels habitants d\'aquesta\ncomunitat cap als catalans',
'Valoració mitjana dels catalans cap\nals habitants d\'aquesta comunitat')
}
the_labs <- labs(x = '',
y = "Valoració mitjana (0-10)",
title = 'Grau de simpatia entre catalans i habitants\nde les altres comunitats autònomes',
caption = 'Escala de 0 a 10 on 0 significa: "Em cauen molt malament" i 10 significa: "Em cauen molt bé".\nDades de l\'enquesta "Percepció sobre el debat territorial a Espanya. 2019", Centre d\'Estudis d\'Opinió.\nEl text entre parèntesis és la xifra NO ponderada. La ponderació fa servir factors demogràfics per ajustar pel biaix de selecció/mostratge.\nMés detalls sobre la ponderació a http://upceo.ceo.gencat.cat/wsceop/7368/Press%20dossier%20-952.pdf\nGràfic de Joe Brew, @joethebrew. Codi a https://github.com/joebrew/vilaweb/tree/master/analyses/filiafobia')
} else {
if(only_indepes){
levs <- c('How people from this area\nfeel about Catalans',
'How PRO-INDY Catalans feel\nabout people from this area')
} else {
levs <- c('How people from this area\nfeel about Catalans',
'How Catalans feel about\npeople from this area')
}
the_labs <- labs(x = '',
y = "Degree to which they 'like' the other (0-10)",
title = 'Degree to which Catalans and inhabitants of\nother regions like one another',
caption = 'Scale from 0 to 10, where 0 means "I don\'t like them at all" and 10 means "I like them a lot".\nData from the survey "Percepció sobre el debat territorial a Espanya. 2019", Centre d\'Estudis d\'Opinió.\nText in parenthesis is the unadjusted/raw figure. Adjustment used demographic factors to generate weights to account for sampling bias.\nFull details on weighting at http://upceo.ceo.gencat.cat/wsceop/7368/Press%20dossier%20-952.pdf\nChart by Joe Brew, @joethebrew. Code at https://github.com/joebrew/vilaweb/tree/master/analyses/filiafobia')
}
pd$var <- ifelse(pd$cap_a == 'Catalunya', levs[1], levs[2])
pd$var <- factor(pd$var, levels = levs)
# Get the corrected levels order
pd$ccaa <- factor(pd$ccaa,
levels = c('Andalusia',
'Aragó',
'Astúries',
'Balears',
'Canàries',
'Cantàbria',
'Castella i Lleó',
'Castella la Manxa',
'Extremadura',
'Galícia',
'Madrid',
'Múrcia',
'Navarra',
'Euskadi/País Basc',
'País Valencià',
'La Rioja'))
fl <- levels(pd$ccaa)
pd$ccaa <- factor(pd$ccaa, levels = fl,
labels = gsub('Castella', 'Cas.', gsub('Euskadi/','', fl)))
ggplot(data = pd,
aes(x = var,
y = value_weighted)) +
geom_line(aes(group = ccaa), alpha = 0.7) +
geom_point(aes(color = var), size = 9) +
facet_wrap(~ccaa, nrow = 2) +
theme_simple() +
theme(axis.text.x = element_blank(),
strip.text = element_text(size = 8)) +
scale_color_manual(name = '',
values = c('darkorange', 'lightblue')) +
geom_text(aes(label = round(value_weighted, digits = 1))) +
the_labs +
ylim(min(pd$value_weighted) - 0.7,
max(pd$value_weighted) + 0.5) +
theme(legend.position = 'top',
plot.title = element_text(size = 16),
legend.text = element_text(size = 10),
plot.caption = element_text(size = 8)) +
geom_text(aes(label = paste0('(',
round(value, digits = 1),
')')),
nudge_y = -0.6,
size = 2.5, alpha = 0.8, color = 'black')
}
# Autonomia
# Pel que fa a les relacions entre Catalunya i Espanya, creieu que Catalunya ha assolit...
# pt$`Pel que fa a les relacions entre Catalunya i la resta de l’Estat espanyol, què diríeu que és més necessari?`
# Libraries
library(vilaweb)
library(tidyverse)
library(lubridate)
# Line breaker function
line_breaker <- function(x,n = 10){
gsub(paste0('(.{1,',n,'})(\\s|$)'), '\\1\n', x)
}
df <- dff <- tibble(
partit = c('PP', 'PSC', 'Cs', 'JxCat', 'ERC', 'Comuns'),
`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c(40.9, 35.3, 33.3, 21.4, 19.1, 17.7),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c(6.8, 7.8, 7.5, 8.4, 8.5, 8.3),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c(7.6, 8.4, 8.4, 8.6, 8.9, 9),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c(50.5, 24.7, 42.4, 16.1, 13.4, 13.8),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c(62.2, 32.2, 50.5, 32.9, 25.8, 30.7),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c(9.3, 37.5, 13, 48.1, 47.3, 56.8)
)
fonts <- font <- tibble(`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% "agree" or "very much agree" that "immigrants should abandon their culture of origin and aopt the culture of the country where they have arrived"'),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "I like learning from other cultures"'),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "No specific culture is superior to others"'),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% that wants to "put strict limits on the number of foreigners that can come here" or "completely ban" their arrival'),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c("Aggregació d'enquestes CEO, 2015 i 2018. Mostra: 3.127 residents de Catalunya amb ciutadania espanyola. Preguntes P56i i P31.", 'Extent of agreement with the phrase "With so much immigration, one no longer feels at home"'),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c('http://upceo.ceo.gencat.cat/wsceop/7428/Dossier%20de%20premsa%20-955.pdf', '% that wants to spend more on welcoming immigrants'))
pd <- df %>%
gather(key, value, names(df)[2:length(names(df))])
pd$partit <- factor(pd$partit, levels = c('PP', 'Cs', 'PSC', 'Comuns', 'JxCat', 'ERC'))
keys <- unique(pd$key)
key_plot <- function(index = 1, ca = FALSE){
df <- dff <- tibble(
partit = c('PP', 'PSC', 'Cs', 'JxCat', 'ERC', 'Comuns'),
`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c(40.9, 35.3, 33.3, 21.4, 19.1, 17.7),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c(6.8, 7.8, 7.5, 8.4, 8.5, 8.3),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c(7.6, 8.4, 8.4, 8.6, 8.9, 9),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c(50.5, 24.7, 42.4, 16.1, 13.4, 13.8),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c(62.2, 32.2, 50.5, 32.9, 25.8, 30.7),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c(9.3, 37.5, 13, 48.1, 47.3, 56.8)
)
fonts <- font <- tibble(`% "d'acord" o "molt d'acord" amb la frase "Els immigrants haurien d'abandonar la seva cultura d'origen i adoptar la cultura del país al quan han arribat"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% "agree" or "very much agree" that "immigrants should abandon their culture of origin and aopt the culture of the country where they have arrived"'),
`Grau d'acord amb la frase "M'agrada aprendre de les altres cultures"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "I like learning from other cultures"'),
`Grau d'acord amb la frase "Cap cultura en concret no és superior a les altres"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", 'Extent of agreement with the phrase "No specific culture is superior to others"'),
`% que vol "posar límits estrictes al nombre d'estrangers que poden venir aquí" o "prohibir-ne l'arribada completament"` = c("http://upceo.ceo.gencat.cat/wsceop/7348/Dossier%20de%20premsa%20-951.pdf", '% that wants to "put strict limits on the number of foreigners that can come here" or "completely ban" their arrival'),
`% d'acord amb la frase "Amb tanta immigració, un ja no se sent com a casa"` = c("Aggregació d'enquestes CEO, 2015 i 2018. Mostra: 3.127 residents de Catalunya amb ciutadania espanyola. Preguntes P56i i P31.", 'Extent of agreement with the phrase "With so much immigration, one no longer feels at home"'),
`% que vol gastar més o molt més en l'acolliment de la immigració` = c('http://upceo.ceo.gencat.cat/wsceop/7428/Dossier%20de%20premsa%20-955.pdf', '% that wants to spend more on welcoming immigrants'))
pd <- df %>%
gather(key, value, names(df)[2:length(names(df))])
pd$partit <- factor(pd$partit, levels = c('PP', 'Cs', 'PSC', 'Comuns', 'JxCat', 'ERC'))
keys <- unique(pd$key)
this_key <- keys[index]
sub_pd <- pd %>% filter(key == this_key)
font1 <- unlist(fonts[,this_key][1,])
font2 <- unlist(fonts[,this_key][2,])
if(ca){
the_labs <- the_labs <- labs(x = '',
y = 'Percentatge/grau d\'acord',
title = line_breaker(this_key, n = 65),
caption = paste0("Font de dades: ", line_breaker(font[1, index], n = 100)))
} else {
the_labs <- labs(x = '',
y = 'Percentage/Extent of agreement',
title = line_breaker(fonts[2,index], n = 65),
caption = paste0("Source of data: ", line_breaker(font[1,index], n = 100)))
}
ggplot(data = sub_pd %>% mutate(key = line_breaker(key, 60)),
aes(x = partit,
y = value,
fill = partit,
color = partit)) +
geom_bar(stat = 'identity', alpha = 0.5,
# color = 'black',
lwd = 0.3) +
# facet_wrap(~key, scales = 'free') +
databrew::theme_simple() +
scale_fill_manual(name = '',
values = c('blue', 'darkorange', 'darkred', 'lightblue', 'purple', 'yellow')) +
scale_color_manual(name = '',
values = c('blue', 'darkorange', 'darkred', 'lightblue', 'purple', 'yellow')) +
theme(legend.position = 'none',
strip.text = element_text(size = 18),
axis.text.x = element_text(size = 18),
axis.text.y = element_text(size = 14),
plot.caption = element_text(size = 8)) +
geom_text(aes(label = paste0(round(value, digits = 1), ''),
y = (value * 0.9) - 1),
color = 'black',
size = 7,
alpha = 0.7) +
the_labs
}
# dir.create('~/Desktop/plots')
# for(i in 1:6){
# print(key_plot(i))
# ggsave(paste0('~/Desktop/plots/', i, '.png'))
# }
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