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nccsdata

Overview

nccsdata provides tools to read, filter and append metadata to publicly available NCCS Core and BMF data sets.

Installation

You can install the development version of nccsdata from GitHub with:

install.packages("devtools")
devtools::install_github("UrbanInstitute/nccsdata")
library(nccsdata)

Usage

Data Pulls

The nccsdata package can be used to download legacy core data from 1989 to 2019 for charities, nonprofits, or private foundations that file their respective required IRS forms such as Form 990, 990EZs, or both.

This data can be filtered based on NTEE codes and geography.

core_2005_nonprofit_pz <- nccsdata::get_data(dsname = "core",
                                             time = "2005",
                                             scope.orgtype = "NONPROFIT",
                                             scope.formtype = "PZ")
#> Requested files have a total size of 82.6 MB. Proceed
#>                       with download? Enter Y/N (Yes/no/cancel)


tibble::as_tibble(core_2005_nonprofit_pz)
#> # A tibble: 157,211 × 150
#>    NTEECC new.code   type.org broad.category major.group univ  hosp  two.digit
#>    <chr>  <chr>      <chr>    <chr>          <chr>       <lgl> <lgl> <chr>    
#>  1 J40    RG-HMS-J40 RG       HMS            J           FALSE FALSE 40       
#>  2 W30    RG-PSB-W30 RG       PSB            W           FALSE FALSE 30       
#>  3 W30    RG-PSB-W30 RG       PSB            W           FALSE FALSE 30       
#>  4 W30    RG-PSB-W30 RG       PSB            W           FALSE FALSE 30       
#>  5 W30    RG-PSB-W30 RG       PSB            W           FALSE FALSE 30       
#>  6 Y42    RG-MMB-Y42 RG       MMB            Y           FALSE FALSE 42       
#>  7 S41    RG-PSB-S41 RG       PSB            S           FALSE FALSE 41       
#>  8 N60    RG-HMS-N60 RG       HMS            N           FALSE FALSE 60       
#>  9 S41    RG-PSB-S41 RG       PSB            S           FALSE FALSE 41       
#> 10 S41    RG-PSB-S41 RG       PSB            S           FALSE FALSE 41       
#> # ℹ 157,201 more rows
#> # ℹ 142 more variables: further.category <int>, division.subdivision <chr>,
#> #   broad.category.description <chr>, major.group.description <chr>,
#> #   code.name <chr>, division.subdivision.description <chr>, keywords <chr>,
#> #   further.category.desciption <chr>, ntee2.code <chr>, EIN <chr>,
#> #   TAXPER <int>, STYEAR <int>, CONT <int>, DUES <int>, SECUR <int64>,
#> #   SALESEXP <int64>, INVINC <int>, SOLICIT <int>, GOODS <int>, GRPROF <int>, …
core_2005_artnonprofits_newyork <- nccsdata::get_data(dsname = "core",
                                                      time = "2016",
                                                      scope.orgtype = "NONPROFIT",
                                                      scope.formtype = "PZ",
                                                      ntee = "ART",
                                                      geo.state = "NY")
#> Requested files have a total size of 113.6 MB. Proceed
#>                       with download? Enter Y/N (Yes/no/cancel)
tibble::as_tibble(core_2005_artnonprofits_newyork)
#> # A tibble: 346 × 168
#>    NTEECC new.code   type.org broad.category major.group univ  hosp  two.digit
#>    <chr>  <chr>      <chr>    <chr>          <chr>       <lgl> <lgl> <chr>    
#>  1 A01    AA-ART-A00 AA       ART            A           FALSE FALSE 1        
#>  2 A01    AA-ART-A00 AA       ART            A           FALSE FALSE 1        
#>  3 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  4 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  5 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  6 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  7 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  8 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#>  9 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#> 10 A03    PA-ART-A00 PA       ART            A           FALSE FALSE 3        
#> # ℹ 336 more rows
#> # ℹ 160 more variables: further.category <int>, division.subdivision <chr>,
#> #   broad.category.description <chr>, major.group.description <chr>,
#> #   code.name <chr>, division.subdivision.description <chr>, keywords <chr>,
#> #   further.category.desciption <chr>, ntee2.code <chr>, EIN <int>,
#> #   ACCPER <int>, ACTIV1 <dbl>, ACTIV2 <dbl>, ACTIV3 <dbl>, ADDRESS <chr>,
#> #   AFCD <dbl>, ASS_BOY <dbl>, ASS_EOY <dbl>, BOND_BOY <dbl>, BOND_EOY <dbl>, …

Summarising Data

After processing the desired data, nccsdata can also be used to generate summary tables.

nccsdata::preview_sample(data = core_2005_artnonprofits_newyork,
                         group_by = c("NTEECC", "STATE"),
                         var = c("TOTREV"),
                         stats = c("count", "mean", "max"))
#> # A tibble: 29 × 5
#> # Groups:   NTEECC [29]
#>    NTEECC STATE count    mean     max
#>    <chr>  <chr> <int> <int64> <int64>
#>  1 A01    NY        2   77734  151889
#>  2 A03    NY       14  924422 9222403
#>  3 A11    NY        2  762752 1485739
#>  4 A19    NY        1   50300   50300
#>  5 A20    NY        5  236863  711793
#>  6 A23    NY      112   64597  758835
#>  7 A30    NY       26  810942 4974965
#>  8 A31    NY        3 1389737 2142396
#>  9 A32    NY        7  759395 3154923
#> 10 A33    NY       15  329638  828684
#> # ℹ 19 more rows

NTEE Codes

nccsdata also offers several supplementary functions for documenting and retrieving NTEE codes.

Getting Help

Raise an issue on the issues page or contact Thiyaghessan at tpoongundranar@urban.org.