The campfin package was created to facilitate the work being done on the The Accountability Project, a tool created by The Investigative Reporting Workshop in Washington, DC. The Accountability Project curates, cleans, and indexes public data to give journalists, researchers and others a simple way to search across otherwise siloed records.
The data focuses on people, organizations and locations. This package was created specifically to help with state-level campaign finance data, although the tools included are useful in general database exploration and normalization.
You can install the released version of campfin from CRAN with:
The development version can be installed from GitHub with:
# install.packages("remotes") remotes::install_github("irworkshop/campfin")
The package was originally built to normalize geographic data using the
normal_*() functions, which take the messy self-reported geographic
data of a contributor, vendor, candidate, or committee and return
normalized text that
is more searchable. They are largely wrappers around the
stringr package, and can call
other sub-functions to streamline normalization.
normal_address()takes a street address and reduces inconsistencies.
normal_zip()takes ZIP Codes and aims to return a valid 5-digit code.
normal_state()takes US states and returns a 2 digit abbreviation.
normal_city()takes cities and reduces inconsistencies.
normal_phone()consistently formats US telephone numbers.
Please see the vignette on normalization for an example of how these functions are used to fix a wide variety of string inconsistencies and make campaign finance data more consistent. In general, these functions fix the following inconsistencies:
The campfin package contains a number of built in data frames and strings used to help wrangle campaign finance data.
#>  "dark2" "extra_city" "invalid_city" "rx_phone" "rx_state" "rx_url" #>  "rx_zip" "usps_city" "usps_state" "usps_street" "valid_abb" "valid_city" #>  "valid_name" "valid_state" "valid_zip" "zipcodes"
/data-raw directory contains the code used to create the objects.
zipcodes (plural) table is a new version of the
(singular) table from the archived
This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources.
valid_zip vectors are sorted, unique
columns from the
zipcodes data frame.
sample_frac(zipcodes) #> # A tibble: 44,336 x 3 #> city state zip #> <chr> <chr> <chr> #> 1 KANSAS CITY MO 64155 #> 2 HOLT FL 32564 #> 3 WOODBRIDGE VA 22194 #> 4 MERRITT ISLAND FL 32954 #> 5 WOODSIDE NY 11377 #> 6 CLAY KY 42404 #> 7 ACRA NY 12405 #> 8 COLUMBUS OH 43271 #> 9 STATE COLLEGE PA 16801 #> 10 COAMO PR 00640 #> # … with 44,326 more rows
usps_* data frames were scraped from the official United States
Postal Service (USPS) Postal Addressing
Standards. These data
frames are designed to work with the abbreviation functionality of
normal_city() to replace common abbreviations
with their full equivalent.
usps_city is a curated subset of
usps_state, whose full version
appear at least once in the
valid_city vector from
valid_name vectors contain the columns from
usps_state and include territories not found in R’s build in
sample_n(usps_street, 3) #> # A tibble: 3 x 2 #> full abb #> <chr> <chr> #> 1 GTWAY GTWY #> 2 NORTH N #> 3 LIGHT LGT sample_n(usps_state, 3) #> # A tibble: 3 x 2 #> full abb #> <chr> <chr> #> 1 OREGON OR #> 2 MISSOURI MO #> 3 WYOMING WY setdiff(valid_state, state.abb) #>  "AS" "AA" "AE" "AP" "DC" "FM" "GU" "MH" "MP" "PW" "PR" "VI"
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