Package: campfin 1.0.11

Kiernan Nicholls

campfin: Wrangle Campaign Finance Data

Explore and normalize American campaign finance data. Created by the Investigative Reporting Workshop to facilitate work on The Accountability Project, an effort to collect public data into a central, standard database that is more easily searched: <https://publicaccountability.org/>.

Authors:Kiernan Nicholls [aut, cre, cph], Investigative Reporting Workshop [cph], Yanqi Xu [aut], Schuyler Erle [cph]

campfin_1.0.11.tar.gz
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campfin_1.0.11.tgz(r-4.6-any)campfin_1.0.11.tgz(r-4.5-any)
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campfin_1.0.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
campfin/json (API)

# Install 'campfin' in R:

install.packages('campfin', repos = c('https://irworkshop.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/irworkshop/campfin/issues

Pkgdown/docs site:https://irworkshop.github.io

Datasets:

dark2 - Dark Color Palette
extra_city - Additional US City Names
invalid_city - Invalid City Names
rx_phone - Phone number regex
rx_state - State regex
rx_url - URL regex
rx_zip - ZIP code regex
usps_city - USPS City Abbreviations
usps_state - USPS State Abbreviations
usps_street - USPS Street Abbreviations
valid_abb - US State Abbreviations
valid_city - US City Names
valid_name - US State Names
valid_state - US State Abbreviations
valid_zip - Almost all of the valid USA ZIP Codes
zipcodes - US City, state, and ZIP

On CRAN:

campaign-finance data-journalism

5.67 score 17 stars 55 scripts 360 downloads 59 exports 49 dependencies

Last updated from:a146c16a21. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	162
source / vignettes	OK	208
linux-release-x86_64	OK	159
macos-release-arm64	OK	189
macos-oldrel-arm64	OK	235
windows-devel	OK	115
windows-release	OK	143
windows-oldrel	OK	115
wasm-release	OK	106

Exports:%>%%out%abbrev_full abbrev_state add_prop all_files_new check_city col_date_mdy col_date_usa col_stats count_diff count_in count_na count_out expand_abbrev expand_state explore_plot fetch_city file_age file_encoding flag_dupes flag_na flush_memory glimpse_fun guess_delim invert_named is_abbrev is_binary is_even keypad_convert most_common na_in na_out na_rep non_ascii normal_address normal_city normal_phone normal_state normal_zip path.abbrev progress_table prop_distinct prop_in prop_na prop_out read_names rename_prefix rx_break scale_x_truncate scale_x_wrap str_dist str_normal this_file_new url_file_size url2path use_diary what_in what_out

Dependencies:askpass bit bit64 cli clipr cpp11 crayon curl dplyr farver fs generics ggplot2 glue gtable hms httr isoband jsonlite labeling lifecycle lubridate magrittr mime openssl pillar pkgconfig prettyunits progress purrr R6 RColorBrewer readr rlang S7 scales stringdist stringi stringr sys tibble tidyselect timechange tzdb utf8 vctrs viridisLite vroom withr

Normalize Geographic Variables

Background | Messy Data | Read | Cities | Conclude

Rendered fromnormalize-geography.Rmdusingknitr::rmarkdown

Last update: 2023-10-10
Started: 2020-03-23

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Inverted match	%out%
Abbreviate full strings	abbrev_full
Abbreviate US state names	abbrev_state
Add proportions	add_prop
Check if all files in a directory are new	all_files_new
Check whether an input is a valid place with Google Maps API	check_city
Parse USA date columns in readr functions	col_date_mdy col_date_usa
Apply a statistic function to all column vectors	col_stats glimpse_fun
Count set difference	count_diff
Count in	count_in
Count missing	count_na
Count out	count_out
Dark Color Palette	dark2
Expand Abbreviations	expand_abbrev
Expand US state names	expand_state
Create Basic Barplots	explore_plot
Additional US City Names	extra_city
Return Closest Match Result of Cities from Google Maps API	fetch_city
File modification date age	file_age
File Encoding	file_encoding
Flag Duplicate Rows With New Column	flag_dupes
Flag Missing Values With New Column	flag_na
Flush Garbage Memory	flush_memory
Guess the delimiter of a text file	guess_delim
Invalid City Names	invalid_city
Invert a named vector	invert_named
Check if abbreviation	is_abbrev
Check if Binary	is_binary
Check if even	is_even
Convert letters or numbers to their keypad counterpart	keypad_convert
Find most common values	most_common
Remove in	na_in
Remove out	na_out
Remove repeated character elements	na_rep
Show non-ASCII lines of file	non_ascii
Normalize street addresses	normal_address
Normalize city names	normal_city
Normalize phone number	normal_phone
Normalize US State Abbreviations	normal_state
Normalize ZIP codes	normal_zip
Abbreviate a file path	path.abbrev
Create a progress table	progress_table
Proportion missing	prop_distinct
Proportion in	prop_in
Proportion missing	prop_na
Proportion out	prop_out
Read column names	read_names
Convert data frame name suffixes to prefixes	rename_prefix
Form a word break regex pattern	rx_break
Phone number regex	rx_phone
State regex	rx_state
URL regex	rx_url
ZIP code regex	rx_zip
Truncate and wrap x-axis labels	scale_x_truncate scale_x_wrap
Calculate string distance	str_dist
Normalize a character string	str_normal
Check if a single file is new	this_file_new
Check a URL file size	url_file_size
Make a File Path from a URL	url2path
Create a new template data diary	use_diary
USPS City Abbreviations	usps_city
USPS State Abbreviations	usps_state
USPS Street Abbreviations	usps_street
US State Abbreviations	valid_abb
US City Names	valid_city
US State Names	valid_name
US State Abbreviations	valid_state
Almost all of the valid USA ZIP Codes	valid_zip
Which in	what_in
Which out	what_out
US City, state, and ZIP	zipcodes