Gets the subreddits that made it to the front page the most often

front_page.R

library(tidyverse)
library(jsonlite)
library(plotly)

# Figure out which columns are lists
drop_lists <- function(df) {
  for(column in names(df)) {
    if(typeof(df[[column]])=="list") {
      # Remove column
      df[[column]] <- NULL
    }
  }
  return(df)
}

# Get posts from front page
posts <- list() # empty list
after <- "" # empty character string
for(i in 1:40) {
  url <- paste0("https://www.reddit.com/.json?after=",after)
  result <- fromJSON(url)
  # Column 'edited' was throwing an error
  # Error: Column `edited` can't be converted from numeric to logical
  # Might as well just drop that column too
  posts[[i]] <- result$data$children$data %>% 
    drop_lists %>% select(-edited)
  after <- posts[[i]]$name %>% tail(1)
  print(url)
}
df <- posts %>% bind_rows
# Clean up workspace
rm(list=c("after","result","url","i"))

# Top 10 subreddits to make it to the front page
# Possible targets
top_10 <- table(Subreddit = df$subreddit) %>% 
  data.frame %>% top_n(n = 10, wt = Freq)
# Note: top_10 may return more than the results...
# ...if Freq of nth subreddit is the same across multiple subs
print(top_10)
# Get character length of titles

p1 <- ggplot(df %>% filter(subreddit %in% top_10$Subreddit), 
       aes(x = score, color = subreddit)) + 
  geom_density() + scale_x_log10() + scale_color_tableau()
p1

# Lots of colors are hard to differentiate
# This makes it easier because you can hover
ggplotly(p1)