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https://github.com/milanowicz/covid-19-dataset
Corona COVID-19 Dataset
https://github.com/milanowicz/covid-19-dataset
coins-data corona coronavirus covid-19 covid-data data-science dataset finance-data jhu johns-hopkins-university rki robert-koch-institut
Last synced: 14 days ago
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Corona COVID-19 Dataset
- Host: GitHub
- URL: https://github.com/milanowicz/covid-19-dataset
- Owner: milanowicz
- Created: 2020-03-24T22:54:19.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2023-03-23T23:12:35.000Z (almost 2 years ago)
- Last Synced: 2024-11-23T15:43:47.517Z (3 months ago)
- Topics: coins-data, corona, coronavirus, covid-19, covid-data, data-science, dataset, finance-data, jhu, johns-hopkins-university, rki, robert-koch-institut
- Language: Python
- Homepage:
- Size: 167 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: ReadMe.md
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README
# COVID-19 Dataset
This COVID-19 Dataset should be used for Data Sciene.
Therefore the columns are the same for JHU and RKI data to load them with pandas.
## Case numbers Germany from Robert Koch-Institut (RKI) in Germany
Description of columns:
StateDateConfirmedDeaths
Name of federal state (German Bundesland)
Date in %Y-%m-%d format
Numbers of confirmed cases
Numbers of deaths
[COVID-19-RKI](https://github.com/Milanowicz/COVID-19-RKI)
## Case numbers from Johns Hopkins University (JHU) for the World
[COVID-19-JHU](https://github.com/CSSEGISandData/COVID-19)
### Data by day
Description of columns:
Data: data/jhu/time_series_covid19_confirmed_deaths_recovered.csv
CityStateCountryDateLatitudeLongitudeConfirmedDeathsRecoveredActiveWHO Region
Name from City
Name of federal state
Name from Country
Date in %Y-%m-%d format
Latitude
Longitude
Numbers of confirmed cases
Numbers of deaths
Numbers of recovered
Active = Confirmed - Deaths - Recovered
WHO Region
### Grouped by Day and Country
Data: data/jhu/time_series_covid19_grouped_day_country.csv
DateCountryConfirmedDeathsRecoveredActiveNew casesNew deathsNew recoveredWHO Region
Date in %Y-%m-%d format
Name from Country
Numbers of confirmed cases
Numbers of deaths
Numbers of recovered
Active = Confirmed - Deaths - Recovered
New cases / Day
New deaths / Day
New recovered / Day
WHO Region
### Grouped by all Countries together
Data: data/jhu/time_series_covid19_grouped_by_countries.csv
Columns:
Country
Confirmed
Deaths
Recovered
Active
New cases
New deaths
New recovered
Deaths / 100 Cases
Recovered / 100 Cases
Deaths / 100 Recovered
Confirmed last week
1 week change
1 week % increase
WHO Region
### Grouped by all Days together
Data: data/jhu/time_series_covid19_grouped_by_days.csv
Columns:
Date
Confirmed
Deaths
Recovered
Active
New cases
New deaths
New recovered
Deaths / 100 Cases
Recovered / 100 Cases
Deaths / 100 Recovered
Country Number
## Common data description
Population CSV files
The dataset contains population data of different countries/regions from 1960 to 2018.
There are condensed and region-wise data in the population dataset.
Origin: https://data.worldbank.org/indicator/SP.POP.TOTL
[Kaggle Competion](https://www.kaggle.com/imdevskp/world-population-19602018)
## Install Python environment
Create environment and install Python libs for a GNU/Linux operation system:
$ . env.sh
$ pip3 install pandas urllib shutil wget
## Update Dataset
Update data only
$ . update.sh
Update, commit and push data
$ . aupdate.sh
or manually
$ python get_data.py