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https://github.com/alvarobartt/covid-daily
🦠COVID-19 Daily Data from Worldometers with Python
https://github.com/alvarobartt/covid-daily
coronavirus coronavirus-daily-report coronavirus-data covid-19 covid19-data worldometers
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🦠COVID-19 Daily Data from Worldometers with Python
- Host: GitHub
- URL: https://github.com/alvarobartt/covid-daily
- Owner: alvarobartt
- License: mit
- Created: 2020-04-26T15:42:47.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-02-28T11:50:52.000Z (over 3 years ago)
- Last Synced: 2024-09-18T10:33:47.624Z (2 months ago)
- Topics: coronavirus, coronavirus-daily-report, coronavirus-data, covid-19, covid19-data, worldometers
- Language: Jupyter Notebook
- Homepage: https://covid_daily.readthedocs.io
- Size: 5.74 MB
- Stars: 13
- Watchers: 1
- Forks: 6
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🦠COVID-19 Daily Data ðŸ¦
[](https://pypi.org/project/covid_daily/)
[](https://pypi.org/project/covid_daily/)
[](https://pypi.org/project/covid_daily/)
[](https://github.com/alvarobartt/covid-daily)
[](https://covid_daily.readthedocs.io/)
This repository allows any user to easily download COVID-19 daily data from [Worldometers](https://www.worldometers.info/coronavirus/). Data is disaggregated per country, so you can retrieve COVID real time daily data from your own country and analyze it.
## Contents
* `scraper/`: contains the Jupyter Notebooks where the Web Scraper was developed and the "scripts" so as to download all the data by yourself.
* `covid_daily/`: this is the Python Package directory, which contains the previously developed functions integrated into a simple Python package so that any user can easily access the data by themselves.
* `data/`: contains a folder per country with all the available data as provided by Worldometers.
* `tests/`: contains the tests using pytest to ensure that after each commit the package is still working properly.
* `docs/`: contains the generated sphinx documentation, but you can see it at https://covid_daily.readthedocs.io
## Features
- Detailed data from every country available at worldometers.info/coronavirus, which is indeed every country affected by the pandemic.
- Data is updated daily so you can track its evolution day by day.
- A general overview on how the pandemic is affecting every country (real-time).
## Installation
In order to get this package working you will need to **install it via pip** (with a Python3.5 version or higher) on the terminal by typing:
``$ pip install covid_daily``
## Documentation
You can find the **complete developer documentation** at: https://covid_daily.readthedocs.io/, hosted on [Read the Docs](https://readthedocs.org/) and generated using [sphinx](https://www.sphinx-doc.org/en/master/) with the theme [sphinx_rtd_theme](https://github.com/readthedocs/sphinx_rtd_theme) which is the standard Read the Docs theme for sphinx.
## Kaggle
You can find a Kaggle Notebook explaining all the features on detail and providing some useful plots at: https://www.kaggle.com/alvarob96/covid-daily-data-retrieval-plot. Make sure to upvote the Kaggle Notebook and follow me at Kaggle so as to stay tuned for all the updates: https://www.kaggle.com/alvarob96
## Usage
### Retrieve the World's overview
```python
import covid_daily
overview = covid_daily.overview(as_json=False)
print(overview.head())
```
As already mentioned, this function retrieves an overview of the COVID-19 from all the available countries as indexed in Worldometers.info/coronavirus
```{r, engine='python', count_lines}
Country,Other TotalCases NewCases TotalDeaths NewDeaths TotalRecovered \
0 World 6282377 23127 374232 535 2854425
1 USA 1837170 0 106195 0 599867
2 Brazil 514992 143 29341 27 206555
3 Russia 414878 9035 4855 162 175877
4 Spain 286509 0 27127 0 196958
ActiveCases Serious,Critical TotCases/1M pop Deaths/1M pop TotalTests \
0 3053720 53397 806 48 0
1 1131108 17075 5553 321 17672567
2 279096 8318 2424 138 930013
3 234146 2300 2843 33 10923108
4 62424 617 6128 580 4063843
Tests/1M pop Population
0 0 0
1 53417 330843477
2 4378 212434518
3 74852 145929507
4 86921 46753345
```
### Retrieve chart's data from every country
```python
import covid_daily
data = covid_daily.data(country='spain', chart='total-currently-infected-linear', as_json=False)
print(data.head())
```
Which returns a `pandas.DataFrame` containing all the information provided by Worldometers related to the total amoun of infected people because of the COVID-19 in Spain, in this case.
```{r, engine='python', count_lines}
Currently Infected
Date
2020-05-09 63148
2020-05-10 61603
2020-05-11 63553
2020-05-12 62130
2020-05-13 60764
```
Note that this functions lets the user change the country and the chart type from which data will be retrieved, containing different statistics. All the available countries can be found at [AVAILABLE_COUNTRIES](https://github.com/alvarobartt/covid-daily/blob/7400dce5157e562858a9eff9dffea6694d198d32/covid_daily/constants.py#L1) and all the available chart types at [AVAILABLE_CHARTS](https://github.com/alvarobartt/covid-daily/blob/7400dce5157e562858a9eff9dffea6694d198d32/covid_daily/constants.py#L41).
### Retrieve & Plot all the available charts for any country
```python
import covid_daily
from covid_daily.constants import AVAILABLE_CHARTS
import matplotplib.pyplot as plt
fig, axs = plt.subplots(3, 3, figsize=(20,15))
from itertools import product
pairs = list(product((range(3)), (range(3))))
for idx, available_chart in enumerate(AVAILABLE_CHARTS):
data = covid_daily.data(country='spain', chart=available_chart, as_json=False)
data.plot(ax=axs[pairs[idx]], title=available_chart)
fig.tight_layout()
fig.show()
```
The resulting figure containing all the data (charts) from Spain, as previously retrieved, is shown below, generated after the previous code block.
## Contribute
As this is an open source project it is **open to contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas**. There is an open tab of [issues](https://github.com/alvarobartt/covid-daily/issues) where anyone can open new issues if needed or navigate through them in order to solve them or contribute to its solving. Remember that **issues are not threads to describe multiple problems**, this does not mean that issues can't be discussed, but so to keep a structured project management, the same issue should not describe different problems, just the main one and some nested/related errors that may be found.
## Citation
When citing this repository on your publications please use the following **BibTeX** citation:
```
@misc{
covid_daily,
author = { Alvaro Bartolome del Canto },
title = { covid_daily - COVID-19 Daily Data from Worldometers with Python },
year = { 2020 },
publisher = {GitHub},
journal = {GitHub Repository},
howpublished = {\url{https://github.com/alvarobartt/covid-daily}}
}
```