Awesome

Taxation Inequality

This project is designed to visualise and explore correlations between taxation income arising from lower and upper income brackets.

DSG Basel

This is an open data project managed by Data Science for Good, Basel. Please join us if you would like to participate!

Repository structure

Data sources go in /data

Analysis code, etc goes in /code, should be placed under subdirectories when possible

Planning documents go in /planning

Analysis results, visualisations go in /results

Getting going with Python

In /code/python_gis_environment.yml is a YAML file, for use in configuring a conda environment. I strongly recommend you install conda and use this environment file to configure an environment. We can all maintain a consistent configuration in this way.

Configuring conda

• Use the command conda env create -f code/python_gis_environment.yml to create a new environment that includes Python 3.6, as well as all required libraries for analysing GIS data. You should be able to use this environment for Jupyter, as well as PyCharm.
  • If the environment doesn't show up in Jupyter, use the command conda install nb_conda (from the base environment), and restart Jupyter.
• Use the command source activate py36_gis to activate the environment in the terminal. You should do this if updating to exporting the environment (see below).
• If you require extra libraries, install them using conda install and then export a new environment file with the command conda env export > python_gis_environment.yml. Then commit the new environment, and let everyone in the Slack channel know.
• To update your existing conda environment, if someone else updates the python_gis_environment.yml definition, use the command conda update -f python_gis_environment.yml.