notes/TODO.md

In brandonleekramer/tidyorgs: Standardize messy text data for organizational analysis

Package Development CSV

Academic

• UMETRICS Data

• IRIS Data

• AAUP Data

Goverment

• add in UK domains

• add in opendatasits91819.csv or this: https://www.data.gov/open-gov/

Countries

• Warnings for not being a dataframe, not being character or numeric, variable not being entered properly (see https://stackoverflow.com/questions/25640161/r-how-to-test-for-character0-in-if-statement)

• Add country_code parameter

• Subsidiaries of large tech companies (facebook, google, etc.)

• recode .com|.org|.net etc in business sector

[] Other tasks to complete:

• Build pkgdown website

• Validate tidy principles

Business

https://opencorporates.com/

• README

[] Resources that have been helpful so far:

• r-pkgs

• tidyr

• tidytable

• tidytext

Non-Profit

• Add in crypto foundations

• Manually edit to remove false positives

• Add in orgs below 99 employees in Kaggle data (see integrate nonprofit_cleaning_blk.R)

• Add in Stephanie's IRS data cleaning

• Add in this?: https://www.guidestar.org/NonprofitDirectory.aspx?cat=2&subcat=9&p=1

brandonleekramer/tidyorgs documentation built on Dec. 19, 2021, 11:42 a.m.