Visualizing Ground Support

JOUR 377

Overview 💡

All data I will be using came from the Federal Election Commission. To look into ground support by candidate, we filtered to donations that are between $0-$100 and from 09/01/2022 to 11/15/2022.

Graphic 📈

Code

# returns quartile rank
# Returns quartile rank
quartile_rank <- function(x = 0:99) {
  # Set quartile
  quart_breaks <- c(
    -Inf,
    quantile(x,
      probs = c(.25, .5, .75),
      na.rm = TRUE
    ),
    Inf
  )
  cut(x = x, breaks = quart_breaks, labels = FALSE)
}

# for warnock 
quart_warnock <- warnock %>% 
  select(committee_name_2, contribution_receipt_amount) %>% 
  mutate(cont_quart = quartile_rank(contribution_receipt_amount)) %>% 
  group_by(cont_quart) 

# for walker
quart_walker <- walker %>% 
  select(committee_name_2, contribution_receipt_amount) %>% 
  mutate(cont_quart = quartile_rank(contribution_receipt_amount)) %>% 
  group_by(cont_quart)

# combining data 
walker_warnock <- merge(quart_walker, quart_warnock)


# barplot 
ggplot() + 
  geom_col(data = quart_warnock, aes(x = committee_name_2, 
                                     y = contribution_receipt_amount,
                                     fill = cont_quart)) +
  geom_col(data = quart_walker, aes(x = committee_name_2,
                                    y = contribution_receipt_amount,
                                    fill = cont_quart))