Population Well-Being Database Tools

This repository provides tools for researchers working with population well-being data. It contains standardized data processing scripts for multiple well-being related datasets, helping researchers clean and prepare data for analysis in a consistent manner.

This project is developed by the Population Well-being Lab at the University of Toronto, under the direction of Professor Felix Cheung.

Currently Supported Datasets

1. Gallup World Poll Data Processing

A tool to generate customized data cleaning scripts for Gallup World Poll data.

Streamlined Workflow

1. Clone/download this repository to your local machine
2. Generate a cleaning script using the script generator 1_GallupWorldPoll_cleaningScript_generation.rmd
3. Copy the generated script to your own project repository
4. Run the cleaning script in your project to process your Gallup World Poll data

View detailed Gallup World Poll documentation

2. World Bank Data Processing

Tools to download and process World Bank indicators related to well-being and development.

Streamlined Workflow

1. Clone/download this repository to your local machine
2. Run or modify the download script 1_WorldBank_dataDownload.Rmd to customize which indicators you need
3. Use the processed data in your research projects

View detailed World Bank documentation

How Researchers Can Use This Repository

This repository is designed to:

1. Standardize data preparation across research projects
2. Save time by providing ready-to-use data processing scripts
3. Improve reproducibility by using consistent data cleaning approaches
4. Enable customization while maintaining core processing standards

Researchers can:

• Use the scripts as-is for standard processing
• Customize parameters to fit specific research needs
• Contribute improvements or extensions to the processing scripts
• Request support for additional data sources

License

This project is licensed under the GNU General Public License v3.0 (GPL-3.0). This means:

• You can freely use, modify, and distribute this software
• Any derivative work must also be distributed under the same license (GPL-3.0)
• You must include the original copyright notice and license text
• There is no warranty for this software

For more details, see the full license text on the GNU website.

Future Development

This is an ongoing project. We plan to add support for more well-being related datasets.

Want to contribute or request a new dataset? Please open an issue or submit a pull request.

---

Gallup World Poll Data Processing

Using the Cleaning Script Generator

Prerequisites

• R and RStudio installed
• Required R packages: dplyr, glue, rio
• Extracted metadata file (already provided, you don't need to run the extraction script yourself)

Steps to Generate a Cleaning Script

1. Open gallup_world_poll/scripts/1_GallupWorldPoll_cleaningScript_generation.rmd in RStudio/VSCode.

2. Configure the parameters in the "User Parameters" section, e.g.:

   • Set your project name
   • Specify your data file name
   • Select variables to extract
   • Choose whether to include affect calculations

3. Run the script to generate your custom cleaning code

4. Find the generated script in the gallup_world_poll/scripts/generated_scripts/ folder. The script will be named according to your project name and the data file name you specified.

5. Copy the generated script to your own project repository for further analysis.

For detailed instructions, parameter explanations, and troubleshooting information, please refer to the documentation within the RMD file.

Note: For an example of a generated cleaning script, see gallup_world_poll/scripts/generated_scripts/GWP_cleaningCode_Example_250414.Rmd

Folder Structure

The script expects the following folder structure:

gallup_world_poll/
  ├── data/
  │   ├── metadata/        # Contains variable metadata
  │   │   └── Gallup_World_Poll_XXXXXX_Attributes.rds
  │   └── raw/             # Place raw Gallup data files here if 0_GallupWorldPoll_attributes_extraction.rmd needs to be run
  └── scripts/
      ├── 0_GallupWorldPoll_attributes_extraction.rmd  # Script for extracting metadata (already executed, you don't need to run this)
      ├── 1_GallupWorldPoll_cleaningScript_generation.rmd  # The generator script
      ├── generated_scripts/  # Will contain generated cleaning scripts
      └── templates/          # Contains template files for script generation
          ├── affects_calculation_template.R
          ├── binary_conversion_template.R
          ├── cleaning_script_template.R
          └── na_conversion_template.R

Output

The generator produces an R markdown file with:

• Variable extraction code
• Non-substantive response conversion to NA
• Binary response recoding (Yes/No to 1/0)
• Optional affect indices calculation

World Bank Data Processing

Using the World Bank Data Download Script

Prerequisites

• R and RStudio installed
• Required R packages: WDI, tidyverse, countrycode

Steps to Download and Process World Bank Data

1. Open world_bank/scripts/1_WorldBank_dataDownload.Rmd in RStudio/VSCode.

2. Modify the indicators list if needed to include the specific World Bank indicators relevant to your research

3. Run the script to download and process the data

4. Find the processed data in the world_bank/data/processed/ folder

For detailed information on available indicators and customization options, please refer to the documentation within the RMD file.

Contact

For questions or support regarding this repository, please contact:

• Kenith Chan
• GitHub: ken1th