cptools

A package for processing Indian elections and Consumer Pyramids data. It currently uses tidyverse functions and will soon be updated to take advantage of the ultra-fast yet user-friendly tidytable rendering

Why use it

cptools provides a few simple convenience functions for operating on dataframes containing Indian administrative divisions:

• include_states() and exclude_states() automatically find the column storing Indian states and Union Territories and subset the dataframe accordingly
• rename_states() ensures States and Union Territories have modern spellings and homogenises the various names of "Delhi" and of "Jammu and Kashmir".
• duplicheck() and find_acno_incomplete() respectively help check for duplicates and for missing Assembly Constituency numbers. They have more generic equivalents. Duplicheck is very similar to janitor::get_dupes(), although I only discovered that later!
• odd_val_col() summarises 'odd values' from large dataframes. The default definition of 'odd values' is taken from missing value markers in Consumer Pyramids but can be altered.

This package also contains a few add-ins to facilitate workflow, most notably an improved View() function that prevents Rstudio from crashing or slowing down as it sometimes happens when viewing large sf dataframes.

cptools is necessary to run the replication materials in its sister repository:

Martínez Arranz, A., R. Thomson et al., 2021, "The Uneven Expansion of Electricity Supply in India", Energy Research and Social Science, Volume 78, August 2021, 102126. DOI: https://doi.org/10.1016/j.erss.2021.102126

You may use any code in this repository subject to the MIT license. Please acknowledge it in any written material with a citation to the above article.

How to use it

Install with: devtools::install_github("https://github.com/AltfunsMA/cptools")