I process the COVID-19 data provided by Johns Hopkins CSSE. For World Data, first I split original data by countries. Then I tag the day as day 1 when there are at least 20 confirmed cases in that country. Finally I drop previous days before day 1. For US data, I split original data by states and do the same with threshold 10.
For example:
-
- country: US
- date: from 3/2/20 to 4/17/20
- confirmed: cumulative confirmed cases in US
- deaths: cumulative death cases in US
- new_confirmed: new confirmed cases in some day
- new_deaths: new death cases in some day
- tagged_day: how many days since "day 1", when there are at least 20 confirmed cases in US
-
- state: California
- date: from 3/2/20 to 4/17/20
- confirmed: cumulative confirmed cases in California
- deaths: cumulative death cases in California
- new_confirmed: new confirmed cases in some day
- new_deaths: new death cases in some day
- tagged_day: how many days since "day 1", when there are at least 10 confirmed cases in California
This idea comes from the blog. The author points out that setting the first day when there exist at least 20 confirmed cases can help people compare the situations in different regions by almost the same initial condition.
I will update the repository each day after Johns Hopkins CSSE updates their data until the end of COVID-19. So the dataset in today's folder may contain data upto today or yesterday. Feel free to use the data to do further analysis.
git clone https://github.com/secregister01/2020-04-13_COVID19-N20.git
cd DataProcessing
./core.sh
You can modify the code in core.sh to disable "github_share.py", that is, delete the last two lines of core.sh. This script is to update this repo for myself.
If you want to tag the day as day 1 when there are at least N confirmed cases in some country, say 50, you can modify DataProcessing/core.sh, changing COUNTRY_THRESHOLD's value
COUNTRY_THRESHOLD=50
For us state, change STATE_THRESHOLD to M, for example
STATE_THRESHOLD=30
After modifying the script,
cd DataProcessing
./core.sh
MIT License
Copyright (c) [2020] [Sicheng Zhou]
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