https://github.com/guibacellar/covid-19

covid-19 covid-data covid19 datascience pandas python python3 scipy sklearn

Last synced: 2 months ago
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COVID-19 Data Analysis

Host: GitHub
URL: https://github.com/guibacellar/covid-19
Owner: guibacellar
License: gpl-3.0
Created: 2020-03-19T22:04:48.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2022-06-22T01:29:02.000Z (about 4 years ago)
Last Synced: 2023-08-06T14:21:19.275Z (almost 3 years ago)
Topics: covid-19, covid-data, covid19, datascience, pandas, python, python3, scipy, sklearn
Language: Jupyter Notebook
Homepage: https://www.theobservator.net/covid-19-data-source-and-download/
Size: 833 KB
Stars: 1
Watchers: 1
Forks: 0
Open Issues: 2
Metadata Files:
- Readme: README.md
- License: LICENSE

README

# COVID-19
COVID-19 Data Analysis

> **This project uses Python 3.7**

## Data Explanation
Location: */data*

* all_timeline.json > Raw Data Downloaded from https://thevirustracker.com/timeline/map-data.json

* all_timeline.csv > Just the *all_timeline.json* file sanitized and in *csv* format.

* all_timeline_with_features.csv > *all_timeline.csv* file processed with some features that I consider helpful

## Files Explanation

* cv19_constants.py > Just constants for code organization

* cv19_downloader.py > Responsible to download the Raw Timeline Data from https://thevirustracker.com

* cv19_parser.py > *all_timeline.json* to *all_timeline.csv* converter and sanitizer

* main.py > Application Entrypoint

## Jypiter Notebooks
* exploration.ipynb > One Country Only Data Exploration, Insights and Graph Generation

* exploration_compare_countries.ipynb > Many Countries Data Exploration, Insights and Graph Generation

* feature_generation.ipynb > Feature Generation for *all_timeline.csv* file

* logistic_regression.ipynb > WIP: Predictions using Logistic Regression