Welcome to covid_daily’s documentation!

Introduction

Coronavirus (COVID-19) Daily Data from Worldometers with Python

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 and generated using sphinx with the theme sphinx_rtd_theme which is the standard Read the Docs theme for sphinx.

Usage

Retrieve the World overview

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

    Country,Other TotalCases NewCases TotalDeaths NewDeaths  ... Serious,Critical TotCases/1M pop Deaths/1M pop TotalTests Tests/1M pop
0           World  4,125,046  +26,758     280,957      +733  ...           47,637             529          36.0        NaN          NaN
1             USA  1,347,325      +16      80,041        +4  ...           16,816           4,070           242  8,918,345       26,943
2           Spain    264,663   +1,880      26,621      +143  ...            1,741           5,661           569  2,467,761       52,781
3           Italy    218,268      NaN      30,395       NaN  ...            1,034           3,610           503  2,514,234       41,584
4              UK    215,260      NaN      31,587       NaN  ...            1,559           3,171           465  1,728,443       25,461

Retrieve chart’s data from every country

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.

            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 and all the available chart types at AVAILABLE_CHARTS.

Retrieve & Plot all the available charts

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.

API Reference

covid_daily.covid

covid_daily.covid.data(country, chart, as_json=False)

This function will retrieve the coronavirus data overview from all the available countries from worldometers.info/coronavirus/, which contains real time data and statistics from multiple features realted to the virus. For more information, please visit: https://www.worldometers.info/coronavirus/

Parameters:
  • chart (str) – name of the country to retrieve the COVID data from (available values at: covid_daily.constants.AVAILABLE_COUNTRIES)
  • chart – name of the chart to retrieve the COVID data from (available values at: covid_daily.constants.AVAILABLE_CHARTS)
  • as_json (bool) – set to True if overview wants to be retrieved as json, if not, leave default value (False).
Returns:

pandas.DataFrame - data

This function returns a pandas.DataFrame by default (if as_json parameter is set to False, if True a json is returned), containing the COVID data of the introduced chart from the introduced country.
Raises:
  • ValueError – raised if any of the introduced parameters is not valid
  • ConnectionError – raised if connection with Worldometers failed
covid_daily.covid.overview(as_json=False)

This function retrieves the coronavirus data overview from all the available countries from worldometers.info/coronavirus/, which contains real time data and statistics from multiple features realted to the virus. For more information, please visit: https://www.worldometers.info/coronavirus/

Parameters:

as_json (bool) – set to True if overview wants to be retrieved as json, if not, leave default value (False).
Returns:

pandas.DataFrame - overview

This function returns a pandas.DataFrame by default (if as_json parameter is set to False, if True a json is returned), containing the world overview coronavirus data.
Raises:
  • ValueError – raised if any of the introduced parameters is not valid
  • ConnectionError – raised if connection with Worldometers failed

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 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 - Coronavirus (COVID-19) Daily Data from Worldometers with Python },
    year = { 2020 },
    publisher = {GitHub},
    journal = {GitHub Repository},
    howpublished = {\url{https://github.com/alvarobartt/covid-daily}}
}

Credits

This repository has been generated using pypackage-cookie

Indices and tables