Beta Version 0.0.2
ClimActor is an R package created by the Data-Driven Envirolab team for the cleaning and preparation of subnational climate actors' names for further analysis.
As more non-state (i.e., cities, regions, and companies) actors commit to climate action, new initiatives and databases recording such commitments have also become more
commonplace. Many actors commit to multiple initiatives and appear in more than one database, yet appear across databases with slightly different names. This discrepancy
makes data cleaning and wrangling more difficult than it should be and can result in over-counting of actor’s climate commitments if not dealt with appropriately.
Update on December 16 2022 - all accented and non-ASCII characters have been removed from actors' preferred names as well as in names within the contextuals database. This change is to reduce the instances of encoding issues when trying to merge names across datasets, especially when working on Windows OS (where UTF-8 in and UTF-8 out is often difficult to enforce).
The ClimActor package can be installed from github using the install_github function from devtools.
# Install devtools as necessary
# install.packages("devtools")
devtools::install_github("datadrivenenvirolab/ClimActor", build_vignettes = T)
library(ClimActor)
It is recommended to build the package vignette during package installation.
The vignette presents a recommended workflow for using the ClimActor package, and covers the usage and explanation of the different key functions.
browseVignettes("ClimActor")
- I got an error while trying to install the package
It is likely that the error is due to a missing package which is required for ClimActor but which you have not installed (especially if you are trying to install the vignette as well). Try checking the DESCRIPTION file for a list of required packages.
- Do I have to follow the order of functions described in the vignette/flow diagram?
It is recommended that you follow of the order of the vignette/flow diagram as certain functions require outputs that would be created from previous functions.
- Do I have to run all the functions within the package to clean my dataset?
No - the functions are meant to be comprehensive and cover all key aspects of data cleaning while working with non-state climate actors. However, you may find that your dataset have existing data which requires no cleaning, and thus will not require certain functions.
Please file any bugs or requests for the package here.