This repository contains the scripts and data necessary to reproduce the climate analysis for the Climate Data Dive page.
Maintainers:
- Our World in Data
- World Bank, World Development Indicators (WDI)
- IMF, World Economic Outlook (WEO)
- Met Office Hadley Centre/Climatic Research Unit (HADCRUT5)
- Centre for Research on the Epidemiology of Disasters (CRED)
- Notre Dame Global Adaptation Initiative (ND-GAIN)
- UN World Population Prospects
- World Mining Data
In order to reproduce this analysis, Python (>= 3.10) is needed. Other packages are listed in requirements.txt. The repository includes the following sub-folders:
output: contains clean and formatted csv files that are used to create the
visualizations.
raw_data: contains raw data used for the analysis including manually downloaded data
glossaries: contains metadata and other useful lookup files.
scripts: scripts for creating the analysis.
download_data.py contains functions to extract and clean data from sources.
charts.py contains functions to produce flourish charts.
utils.py contains utility functions and
config.py manages file paths to different folders and source urls.
Data from the International Disaster Database (EM-DAT) from
CRED needs to be manually downloaded from the
data portal. In the Query tool
select all options and download. Place the file in
raw_data as emdat.xlsx.