More from this project:
Organizations by IRS Subsection
501(c)(23) - Veterans Associations Founded Prior to 1880
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 == "23"))
#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 = TRUE) %>%
select(NAME, INCOME, ASSETS)
colnames(random20) <- c("Organization", "Gross Receipts", "Total Assets")
Number of organizations reporting assets or income = 2. Total Gross Receipts = $617,482,891. Total Assets = $4,002,873,747.
Largest 501(c)(23)s by Gross Receipts
#display tables
kable(LargestGrossReceipts, format.args = list(decimal.mark = '.', big.mark = ","), caption = "Largest Organizations (By Gross Receipts)")
Organization | Gross Receipts | Total Assets |
---|---|---|
NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
Largest 501(c)(23)s by Total Assets
#display tables
kable(LargestAssets, format.args = list(decimal.mark = '.', big.mark = ","), caption ="Largest Organizations (By Total Assets)")
Organization | Gross Receipts | Total Assets |
---|---|---|
NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
Random Sample of 501(c)(23)s
#display tables
kable(random20, format.args = list(decimal.mark = '.', big.mark = ","), caption = "Random Sample" )
Organization | Gross Receipts | Total Assets | |
---|---|---|---|
2 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
2.1 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1.1 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
1.2 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
2.2 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
2.3 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
2.4 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
2.5 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1.3 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
1.4 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
1.5 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
2.6 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1.6 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
2.7 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
2.8 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1.7 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
1.8 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
2.9 | AMERICAN ARMED FORCES MUTUAL AID ASSOCIATION | 141,912,261 | 1,154,555,615 |
1.9 | NAVY MUTUAL AID ASSOCIATION | 475,570,630 | 2,848,318,132 |
Source: NCCS IRS Business Master File August 2016