planning.txt

Tooling
pycharm
python 3.9
shared github repository
pycountry

JFx Sun 18h zoom

Week 1 (13.-20.12.)
Get data and explore data separately as follows
- Engergy production and consumption (Josef) 
- economical (GDP, growth, ...)  (Frank)
- ecological data (CO2 emission, pollution, ...) (Felix)
- political data (climate agreements, government, ...) (Johannes)
- define country code / conversion (Johannes)
Granularity: country (world-wide), year (approx 1945-2019)
Review interim results together and refine questions 20.12.

Common data structure:
0: year
1: country code
2..: features

Week 2 (21.-28.12.)
Explore, clean datasets (unifiy country codes, handle missing values and outliers)
Columns: [0]: year, [1]: country, [2:]: features (most relevant, simplified names)
Upload cleaned up python script to GitHub --> scripts, upload raw data --> data (with references).
Review interim results together 28.12. 18:00.
Refine planning

Week 3 (29.-3.1.)
Finalize exploration
Time-range is set to 1980-2018.
Merge individual dataframes into a single dataframe "load_data.py".
Finalize main questions
Refine planning

Week 4 (4.-10.1.)
Model data and find answers
Refine planning

Week 5 (11-17.1.)
Report and visualize (coropleth map with time slider, time series, ...)
Refine planning

Week 6 (18.-24.1.)
Create final deliveries
Jupyter notebook (Josef)
2-page pdf summary (tex document) (Frank)
presentation (Felix, Johannes)