In this notebook we want to show mobility dynamics in different countries in 2020, and how much it correlates with COVID-19.
According to Apple, data show the relative volume of direction requests per country compared to the baseline volume on January 13, 2020. "Day" is defined as midnight to midnight, Pacific time. In many countries, relative volume has increased since January 13, consistent with normal, seasonal usage of Apple Maps. In addition, we need to consider the-day-of-the-week effects.
In most dataframes I normalize mobility so that the volume on January 13 is 1. So, for example, mobility equals 2 if it has increased twice since the start time.
from itertools import product import numpy as np import pandas as pd import geopandas as gpd from lets_plot import * LetsPlot.setup_html()