In databrew/covid19: COVID-19 App

# Basic knitr options
library(knitr)
opts_chunk$set(comment = NA, 
               # echo = FALSE, 
               warning = FALSE, 
               message = FALSE, 
               error = TRUE, 
               cache = FALSE,
               fig.width = 9.64,
               fig.height = 5.9,
               fig.path = 'figures/')

## Load libraries
library(covid19)
library(ggplot2)
library(lubridate)
library(dplyr)
library(ggplot2)
library(sp)
library(raster)
library(viridis)
library(ggthemes)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)
library(RColorBrewer)
library(readr)
library(zoo)
options(scipen = '999')

# Read in names data from:
# https://github.com/marcboquet/spanish-names
if(!'mujeres.csv' %in% dir()){
  download.file(url = 'https://github.com/marcboquet/spanish-names/raw/master/mujeres.csv',
                destfile = 'mujeres.csv')
}
if(!'hombres.csv' %in% dir()){
  download.file(url = 'https://github.com/marcboquet/spanish-names/raw/master/hombres.csv',
                destfile = 'hombres.csv')
}
if(!'apellidos.csv' %in% dir()){
  download.file(url = 'https://github.com/marcboquet/spanish-names/raw/master/apellidos.csv',
                destfile = 'apellidos.csv')
}
hombres <- read_csv('hombres.csv')
mujeres <- read_csv('mujeres.csv')
apellidos <- read_csv('apellidos.csv')
nombres <- bind_rows(hombres, mujeres)
# Get number of dead
n_dead <- df_country %>% filter(country == 'Spain',
                                date == max(date)) %>%
  summarise(n = sum(deaths)) %>% .$n

# Generate names
first_names <- sample(nombres$nombre, size = n_dead, replace = TRUE, prob = nombres$frec)
last_names1 <- sample(apellidos$apellido, size = n_dead, replace = TRUE, prob = apellidos$frec_pri)
last_names2 <- sample(apellidos$apellido, size = n_dead, replace = TRUE, prob = apellidos$frec_seg)

# Combine
combined <- paste0(first_names, ' ', 
                   last_names1, ' ',
                   last_names2)

# Paste into chunks of 4 names per line
n_columns <- 6
chunk_starts <- seq(1, n_dead, by = n_columns)
chunk_ends <- chunk_starts + (n_columns -1)
out_list <- list()
for(i in 1:length(chunk_starts)){
  message(i)
  the_end <- chunk_ends[i]
  if(the_end > length(combined)){
    the_end <- length(combined)
  }
  these <- combined[chunk_starts[i]:the_end]  
  these <- these[!is.na(these)]
  these <- paste0(these, collapse = ', ')
  these <- paste0(these, '\n', collapse = '')
  out_list[[i]] <- these
}

# Define number of lines per plot
n_rows <- 100
chunk_starts <- seq(1, n_dead, by = n_rows)
chunk_ends <- chunk_starts + (n_rows -1)
rows_list <- list()
for(i in 1:length(chunk_starts)){
  message(i)
  the_end <- chunk_ends[i]
  if(the_end > length(out_list)){
    the_end <- length(out_list)
  }
  these <- unlist(out_list[chunk_starts[i]:the_end])  
  these <- these[!is.na(these)]
  these <- paste0(these, collapse = '')
  rows_list[[i]] <- these
}

add_zero <- function(x, n){
    x <- as.character(x)
    adders <- n - nchar(x)
    adders <- ifelse(adders < 0, 0, adders)
    for (i in 1:length(x)){
      if(!is.na(x[i])){
        x[i] <- paste0(
          paste0(rep('0', adders[i]), collapse = ''),
          x[i],
          collapse = '')  
      } 
    }
    return(x)
  }

# Render plots
if(!dir.exists('plots')){
  dir.create('plots')
}
par(mar = c(0,0,0,0) + 0.1)
for(i in 1:length(rows_list)){
  file_name <- add_zero(i, 5)
  file_name <- paste0('plots/', file_name, '.png')
  png(filename = file_name,
      width = 1200,
      height = 1300)
  plot(c(0, 1), c(0, 1), ann = F, bty = 'n', type = 'n', xaxt = 'n', yaxt = 'n')
  text(x = 0.5, y = 0.5, rows_list[[i]], 
     cex = 0.8, col = "black")
  dev.off()
}
par(mar = c(5, 4, 4, 2) + 0.1)