A data science Python Notebook for exploration of BP energy data

Each year BP publishes a Statistical Review of World Energy, freely available at

https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html

The environment.yml file should list all Python libraries on which the notebooks depend, specified as though they were created using the following conda commands:

conda activate example-environment
conda install <pkg>=<version>
conda env export -f environment.yml

Note that the only libraries available to you will be the ones specified in the environment.yml, so be sure to include everything else that you need!

The xlsx report from 2020 has a missing blank char on the Wind Generation sheet name. In 2021 report that has been fixed and that's mostly the only difference in the two 'notebooks'. Current setup uses an older pandas version, mostly because newer versions don't yeld the right results on hashing the 'country' columns into an usable key for pandas DataFrame.