Overview of 501(c)(4)s

library(tidyverse)

library(knitr)

library(stringr)

library(scales)

library(httr)

source('https://raw.githubusercontent.com/UrbanInstitute/urban_R_theme/master/urban_theme_windows.R')

#Import IRS BMF

bmffile <- read.csv(file = "Data/bm1608.csv")

#Filter out of scope organizations 

bmffile <- bmffile %>%

  filter((OUTNCCS != "OUT")) %>%

  filter((FNDNCD != "02" & FNDNCD!= "03" & FNDNCD != "04")) %>%

  filter((SUBSECCD == "4"))

#Sort the bmf in descending order by gross receipts

#Limit the list to 10

#Select the appropriate columns, drop the rest

LargestGrossReceipts <- bmffile %>%

  arrange(desc(INCOME)) %>%

  slice(1:10) %>%

  select(NAME, INCOME, ASSETS)

#Rename columns appropriately

colnames(LargestGrossReceipts) <- c("Organization", "Gross Receipts", "Total Assets")

LargestAssets <- bmffile %>%

  arrange(desc(ASSETS)) %>%

  slice(1:10) %>%

  select(NAME, INCOME, ASSETS)

#Rename columns appropriately

colnames(LargestAssets) <- c("Organization", "Gross Receipts", "Total Assets")

#Generate random sample

set.seed(143)

random20 <- bmffile %>% 

  filter(bmffile$INCOME != 0 | bmffile$ASSETS != 0) 

random20 <-sample_n(random20, 20, replace = FALSE) %>%

  select(NAME, INCOME, ASSETS)

colnames(random20) <- c("Organization", "Gross Receipts", "Total Assets")

#display tables

kable(LargestGrossReceipts, format.args = list(decimal.mark = '.', big.mark = ","), caption = "Largest Organizations (By Gross Receipts)")

#display tables

kable(LargestAssets, format.args = list(decimal.mark = '.', big.mark = ","), caption ="Largest Organizations (By Total Assets)")

#display tables

kable(random20, format.args = list(decimal.mark = '.', big.mark = ","), caption = "Random Sample" )