covidify

Features • How To Use • Install • Visualizations • Data Source • Credits • To-Do List

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Features

Covidify downloads the latest covid-19 data for confirmed cases, deaths and recoveries.

• Creates a time series dataset
• Creates a daily stats dataset
• Forecast global and country confirmed cases
• Generate visualizations
• Filter by country
• List all countries affected
• Shows number of people currently infected
• Generates an excel report including all of the above

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Install

• pip install covidify

How to use

$ covidify
Usage: covidify [OPTIONS] COMMAND [ARGS]...

  ☣  COVIDIFY ☣

   - use the most up-to-date data to generate reports of 
     confirmed cases, fatalities and recoveries.

Options:
  --help  Show this message and exit.

Commands:
  list  List all the countries that have confirmed cases.
  run   Generate reports for global cases or refine by country.

$ covidify run --help
Usage: covidify run [OPTIONS]

Options:
  --output TEXT    Folder to output data and reports [Default:
                   /Users/award40/Desktop/covidify-output/]
  --source TEXT    There are two datasources to choose from, Johns Hopkins
                   github repo or wikipedia -- options are JHU or wiki
                   respectively [Default: JHU]
  --country TEXT   Filter reports by a country
  --top TEXT       Top N infected countries for log plot. [Default: 10]
  --forecast TEXT  Number of days to forecast cumulative cases in the future.
                   [Default: 15]
  --help           Show this message and exit.

Example Commands:

# List all countries affected 
covidify list --countries

# Will default to desktop folder for output and github for datasource
covidify run 

# Specify output folder and source
covidify run --output=<PATH TO DESIRED OUTPUT FOLDER>

# Filter reports by country
covidify run --country="South Korea"

# Show top 20 infected countries on a logarithmic scale
covidify run --top=20

# Forecast cumulative cases in America for 14 days into the future
covidify run --country=America --forecast=14

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Visualizations

An excel spreadsheet is generated with a number of visualizations and statistics.

Logarithmic Plot

This plot shows the top N infected countries on a logarithmic scale.

Forecasting

An ARIMA model is trained and used to forecast the cumulative cases for N number of days into the future (DISCLAIMER: the forecast is a ballpark figure, and should not be taken as gospel)

Accumulative Trend

This is an accumulative sum trendline for all the confirmed cases, deaths and recoveries.

Daily Trendline

This is a daily sum trendline for all the confirmed cases, deaths and recoveries.

Stacked Daily Confirmed Cases

This stacked bar chart shows a daily sum of people who are already confirmed (red) and the people who have been confirmed on that date (blue)

Daily Confirmed Cases

A count for new cases on a given date, does not take past confirmations into account.

Daily Deaths

A count for deaths on a given date, does not take past deaths into account.

Daily Recoveries

A count for new recoveries on a given date, does not take past recoveries into account.

Currently Infected

A count for all the people who are currently infected for a given date.

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Credits

• Written by me (Aaron Ward - https://www.linkedin.com/in/aaronjward/)
• A special thank you to the JHU CSSE team for maintaining the data
• Also a special thank you to @ajaymaity for bug fixes 🎉

Fork

Forked this project by Steven Chen for York EECS 3311 class