In joebrew/vilaweb: Reproducible data analysis for www.vilaweb.cat

# Basic knitr options
library(knitr)
opts_chunk$set(comment = NA, 
               echo = FALSE, 
               warning = FALSE, 
               message = FALSE, 
               error = TRUE, 
               cache = FALSE,
               fig.width = 8.64,
               fig.height = 4.86,
               fig.path = 'figures/')

# Libraries
library(vilaweb)
library(tidyverse)
require(readr)
library(ggrepel)
source('prepare_ceo_data.R')

make_b <- function(ca = TRUE){

  pd <- vilaweb::ceo %>%
  dplyr::select(contains('P21'))
for(j in 1:ncol(pd)){
  message(j)
  col_name <- names(pd)[j]
  this_name <- attr(eval(parse(text = paste0('pd$`', col_name, '`'))), 'label')
  names(pd)[j] <- this_name
}
names(pd) <- unlist(lapply(strsplit(names(pd), '. ', fixed = TRUE), function(x){x[2]}))
for(j in 1:ncol(pd)){
  pd[,j] <- make_number(unlist(pd[,j]))
}



out <- apply(pd, 2, mean, na.rm = TRUE)
people <- apply(pd, 2, function(x){length(which(!is.na(x)))})
people <- range(people)
people <- numberfy(people)
people <- paste0(people, collapse = ' - ')
  if(ca){
    the_labs <- labs(x = '',
                     y = 'Valoració',
                     title = 'Grau de confiança dels catalans en les institucions',
                     subtitle = 'Escala de 0 a 10',
                     caption = paste0('Mostra: ', people,
                                       ' residents de Catalunya amb ciutadania espanyola.\nDades: agregació de dades del 2015-2018 del Baròmetre d\'Opinió Pública del Centre d\'Estudis d\'Opinió.\nGràfic de Joe Brew | @joethebrew | www.vilaweb.cat.'))
  } else {
    the_labs <- labs(x = '',
                     y = 'Rating',
                     title = 'Catalans\' degree of confidence in institutions',
                     subtitle = 'Scale from 0 to 10',
                     caption = paste0('Sample: ', people,
                                       ' residents of Catalonia with Spanish citizenship.\nData. Aggregation of 2015-2018 data from the Baròmetre d\'Opinió Pública of the Centre d\'Estudis d\'Opinió.\nChart by Joe Brew | @joethebrew | www.vilaweb.cat.'))
  }


pd <- tibble(key = names(out),
             value = as.numeric(out)) %>%
  arrange(value) %>%
  # mutate(key = gsub('la i', 'la\ni', key)) %>%
  mutate(key = gsub(' (0-10)', '', key, fixed = TRUE))
pd$key <- factor(pd$key, levels = pd$key)
pd$yend <- 0
ggplot(data = pd,
       aes(x = key,
           y = value)) +
  geom_point() +
  theme_vilaweb() +
    theme(axis.text.x = element_text(angle = 90,
                                   vjust = 0.5,
                                   hjust = 1,
                                   size = 2),
          plot.title = element_text(hjust = 1)) +
  geom_text(aes(label = round(value, digits = 2)),
            nudge_y = 0.5,
            alpha = 0.6,
            size = 3) +
  geom_segment(aes(xend = key,
                   yend = yend)) +
  the_labs +
  coord_flip()
}

make_chart <- function(ca = TRUE,
                       df,
                       skipper = 0.25){

  pd <- df %>%
  filter(!is.na(var)) %>%
  group_by(date) %>%
  summarise(p = mean(var, na.rm = TRUE),
            people = n()) %>%
  mutate(date = date + 20)

  if(ca){
    the_labs <- labs(x = 'Data',
                     y = 'Valoració',
                     subtitle = 'Escala de 0 a 10',
                     caption = paste0('Mostra: ', numberfy(sum(pd$people)),
                                       ' residents de Catalunya amb ciutadania espanyola.\nDades del Baròmetre d\'Opinió Pública del Centre d\'Estudis d\'Opinió.'))
  } else {
    the_labs <- labs(x = 'Date',
                     y = 'Rating',

                     subtitle = 'Scale from 0 to 10',
                     caption = paste0('Sample: ', numberfy(sum(pd$people)),
                                       ' residents of Catalonia with Spanish citizenship.\nData from the Baròmetre d\'Opinió Pública of the Centre d\'Estudis d\'Opinió.\nChart by Joe Brew | @joethebrew | www.vilaweb.cat.'))
  }

ggplot(data = pd,
       aes(x = date,
           y = p)) +
  geom_point() +
  geom_area(alpha = 0.2) +
  geom_line(alpha = 0.4) +
  theme_vilaweb() +
  scale_y_continuous(breaks = seq(0, 10, by = skipper)) +
  geom_text_repel(aes(label = round(p, digits = 1)),
            alpha = 0.6,
            nudge_y = 0.1) +
  # geom_vline(aes(xintercept = as.Date('2017-09-20')),
  #            alpha = 0.8,
  #            lty = 2) +
  # geom_label(data = data.frame(date = as.Date('2017-09-20'),
  #                              p = 1.25,
  #                              label = 'Oct 2017'),
  #            aes(x = date, y = p, label = label)) +
  the_labs +
  ylim(0,7)
}
make_chart(ca = TRUE,
           df = df %>% mutate(var = monarquia),
          skipper = 1) +
  labs(title = 'Grau de confiança dels catalans en\nla Monarquia Espanyola')
# make_b(ca = TRUE)



 P26B = P21B, # partits politics
                       P26C = P21C, # el seu ajuntament
                       P26D = P21D, # govern espanyol
                       P26E = P21E, # els sindicats
                       P26F = P21F, # govern de la generalitat
                       P26G = P21G, # congres dels diputats
                       P26H = P21H, # parlament de catalunya
                       P26I = P21I, # la UE
                       P26K = P21K, # l'exercit
                       P26L = P21L, # PN i GC
                       P26M = P21M, # mossos d'esquadra
                       P26N = P21N, # esglesia catolica
                       P26O = P21O, # l ONU
                       P26P = P21P, # la banca
                       P26Q = P21Q, # mitjans de comunicacio
                       P26R = P21R, # tribunal constitucional
                       P26S = P21S, # universitats
                       P26T = P21T, # parlament europe