DOI: 10.7910/dvn/zqmjal
title: IRS 990-N e-Postcard Filers

description: Most small tax-exempt organizations whose annual gross receipts are normally $50,000 or less can satisfy their annual IRS reporting requirement by electronically submitting Form 990-N if they choose not to file Form 990 or Form 990-EZ instead. This dataset contains all of the 990-N Postcard e-Filers as of August 2016.
description: 990-N Postcard Filers
Info including data dictionary can be found at: https://apps.irs.gov/app/eos/forwardToEpostDownload.do
Internal Revenue Service United States Department of the Treasury Form 990-N (e-Postcard) Data Download Layout
The Form 990-N (e-Postcard) filing information will be listed in rows, with each field of data separated by a pipe (‘|’) symbol. The following table describes the format and order of each field in a row, representing one Form 990-N (e-Postcard) filing.



DATA DICTIONARY


https://github.com/lecy/Open-Data-for-Nonprofit-Research/blob/master/Build_Datasets/postcard%20990N%20filers.RMD





BUILD THE DATASET
<pre class="r"><code>

# create subdirectory for the data

getwd()

dir.create( "IRS Nonprofit Data" )

setwd( "./IRS Nonprofit Data" )



# download and unzip

file.url &lt;- "https://apps.irs.gov/pub/epostcard/data-download-epostcard.zip"

download.file( url=file.url, "epostcard.zip" )

unzip( "epostcard.zip" )

file.remove( "epostcard.zip" )

dat.990n &lt;- read.delim( file="data-download-epostcard.txt", 
 header = FALSE, 
 sep = "|", 
 quote = "",
 dec = ".", 
 fill = TRUE, 
 colClasses="character"
 )


# add header information - variable names

var.names &lt;- c("EIN", "Tax.Year", "Organization.Name", "Gross.Receipts.Under.$25,000", 
"Terminated", "Tax.Period.Begin.Date", "Tax.Period.End.Date", 
"Website.URL", "Officer.Name", "Officer.Address.Line.1", "Officer.Address.Line.2", 
"Officer.Address.City", "Officer.Address.Province", "Officer.Address.State", 
"Officer.Address.Postal.Code", "Officer.Address.Country", "Organization.Address.Line.1", 
"Organization.Address.Line.2", "Organization.Address.City", "Organization.Address.Province", 
"Organization.Address.State", "Organization.Address.Postal.Code", 
"Organization.Address.Country", "Doing.Business.As.Name.1", "Doing.Business.As.Name.2", 
"Doing.Business.As.Name.3")

names( dat.990n ) &lt;- var.names

rm( var.names )


# change Tax.Year from YYYY-MM to YYYY

dat.990n$FileYear &lt; substr( dat.990n$Tax.Year, 1, 4 )
</code></pre>


EXPORT THE DATASET
<pre class="r"><code>
# AS R DATA SET

saveRDS( dat.990n, file="PostcardFilers.rds" )


# AS CSV

write.csv( dat.990n, "PostcardFilers.csv", row.names=F )


# IN STATA

install.packages( "haven" )
library( haven )
write_dta( dat.990n, "PostcardFilers.dta" )


# IN SPSS - creates a text file and a script for reading it into SPSS

library( foreign )
write.foreign( df=dat.990n, datafile="PostcardFilers.txt", codefile="CodeToLoadDataInSPSS.txt", package="SPSS" )

# if package 'foreign' is not installed first try: install.packages("foreign")
</code></pre>
description: The source code used to generate this data and the data dictionary can be found on GitHub at: https://github.com/lecy/Open-Data-for-Nonprofit-Research/blob/master/Build_Datasets/postcard%20990N%20filers.RMD