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Impact-of-COVID-19 - data visualisation using Plotly

Derive interesting data insights on covid-19 and visualize the outbreak of coronavirus compared to SARS

Note:

All the data, codes and data sources have been provided for reproducing. Please modify the code as per application requirement.

Introduction

The aim here is to understand how visualization helps to derive informative insights from data sources. For the visualization part, I am using Plotly.

Data set:

The data-set sources are accumulated, processed and latest updates are made available by “Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)” in their github page

Terms of use: As stated by JHU CSSE.

Important notes:

Data as of 3rd March has been used for the below analysis. Please refrain from using the data or insights derived from the analysis for medical guidance or use of the same in commerce. It is solely for learning purpose. The same code template can be leveraged for various other data sources. I would encourage readers to try other charts as well in Plotly and to customize the codes according to application requirements. Another important aspect of showing your key findings is to use only a set of charts that infer key insight from the data rather than showing too much charts with redundant information.

Results

Impact

Spread

Infected Cases

Deaths

Recoveries

COVID19 vs SARS

COVID19 vs SARS