User inputs:
the user can filter the data based on the movement type, e.g in the google data you can look at park visits / pharmacy visits / residential activity / shopping activity etc.
there could also be some sort of time filtering as the data is available at the daily level
choropleth at country
dataset is accessed as CSV from https://www.google.com/covid19/mobility/
use a geoJSON file with country boundaries join the data using the names of the countries (ISO2 and ISO3 country codes)
this requires some cleanup / matching of the semantic country names between the geoJSON and google datasets
map the geoJSON polygons and use the google movement metrics as data for the colormapping using folium's choropleth method https://github.com/python-visualization/folium/blob/master/examples/GeoJSON_and_choropleth.ipynb
there could also be some sort of time filtering as the data is available at the daily level