# Load R packages

library(tidyusafec)
library(tidyverse)

# Get Data

candidates <- search_candidates(
  office = 'H',
  election_year = '2018',
  district = '09',
  state = 'TN',
  unnest_committees = FALSE
)

candidate_totals <- candidates %>% 
    get_candidate_totals() 

# Wrangle Data

chart_data <- candidate_totals %>%
    filter(type_of_funds %in% tidyusafec_filters$candidate_totals$type_of_funds$top_level,
           last_report_year == '2018') %>%
    mutate(type_of_funds = type_of_funds %>% str_replace_all('_',' ') %>% str_to_title(),
           name = fct_reorder(name, -desc(amount)))

# Visualize Data

ggplot(data = chart_data) +
    geom_bar(aes(x = name, y = amount, fill = party), stat = 'identity') +
    coord_flip() +
    facet_wrap(~type_of_funds, labeller = label_wrap_gen(width = 10)) +
    scale_fill_manual(values = c('DEM' = '#2c4d82', 'REP' = '#8e1b1b', 'IND' = '#a3a3a3', 'GRE' = '#1c561d', 'LIB' = '#afac3d','NNE' = '#0A0A0A')) +
    scale_y_continuous(labels = scales::dollar) +
    theme_bw() +
    theme(axis.text.x = element_text(angle = -90, hjust = 0, vjust = .5)) +
    labs(
      title = 'Tennessee Congressional District 09 Race - 2018',
      subtitle = 'Financial Summary',
      x = '',
      y = '',
      fill = 'Party',
      caption = paste0('Source: FEC. Data retreived on ', Sys.Date(), ', created by @StephenHolz')
    )