TL;DR. I've built a web application that reveals the impact of the COVID-19 pandemic on people's lives and habits. Also, I tell how I built it.
Here's how this application looks like:
Surely, you can select any country β definitely try your own. You will explore how COVID-19 affected social mobility or how "stay at home" requirements were followed (or not).
Insights
Let's take Israel. You can clearly see three waves and the positive effect of "stay at home" requirements β after they are introduced, every wave spreads with lesser speed.
Let's take Germany. You can see how Germans interact with the rules: after the first "stay at home" requirements are lifted, park activity grows, and after the second "stay at home" requirements are introduced, parks instantly become deserted.
Let's take Singapore. Obviously enough, you can see Singapore doing a great job containing the virus. The third wave is nearly unexistent.
Tutorial
You can build this application from scratch using BigQuery public datasets, JavaScript, React, and Cube.js. Read on:
Also, don't hesitate to share your insights in the comments π
Top comments (5)
Why everything is 0 or 0%?
Oops! I've fixed it. Could you check again, please? π
Everything was 0 or 0% because some zero values were appended to the public datasets. It doesn't make much sense since the number of confirmed cases cannot drop down instantly. I worked around that by skipping a few days on the rightmost part of the timeline.
You forgot to smooth the curve.
I think it matters a lot when the graph isn't interactive.
Could you please elaborate on smoothing? The ups and downs that you see on the charts are not some glitches, they are actual changes due to people's weekly activity patterns. Anyway, thank you for the feedback :)
An idea is last 7 days' average.