NCov2019 Analysis Save

Analysis of 2019-nCov coronavirus data

Project README

2019-nCov noval coronavirus Data analysis in Python

简体中文 | English

Introduction on Medium

https://towardsdatascience.com/understanding-the-coronavirus-epidemic-data-44d2fb356ecb

Data Sources

Chinese Data:

International Data:

Prerequisite

  • Pandas
  • If you need interactive analysis, and you cannot access Google Colab, then you need to install Python Notebook first.

Description

  • coronavirus_demo_colab.ipynb: A demo on Google Colab, showing how to extract / aggregate / slice data, and basic time series / cross-sectional plotting
  • demo.ipynb: Similar demo in a traditional Python Notebook, Chinese version
  • demo.en.ipynb: Similar demo in a traditional Python Notebook, English version
  • demo.html, demo.pdf: For those who doon't have Python Notebook, these two files serve as demo.ipynb for demonstration purpose (both are in Chinese)
  • death_rate.ipynb: An example analysis of the heterogeneity of death rate across different regions
  • utils.py: Utility functions

Some Examples:

data = utils.load_chinese_data()  # obtain CSV real time data
daily_frm = utils.aggDaily(data)  # aggregate to daily data
utils.tsplot_conf_dead_cured(daily_frm)  # Time Series plot of the Confirmed, dead, cured count of the whole country

Best Wishes

Open Source Agenda is not affiliated with "NCov2019 Analysis" Project. README Source: jianxu305/nCov2019_analysis
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