Pandemic-COVID-19-Analysis-and-Visualization

This whole analysis and visualization has been done with Python. Libraries used plotly, matplotlib, numpy, pandas, calmap, seaborn.
To view the files properly: Go to: https://nbviewer.jupyter.org/
And copy-paste the .ipynb or .pdf links to view.

Data:
covid_19_clean_complete.csv - Country wise day to day cases dataset
usa_county_wise.csv - US county day to day cases dataset
full_grouped.csv - Day to day country wise no. of cases (Has County/State/Province level data)
country_wise_latest.csv - Latest country level no. of cases
day_wise.csv - Day wise no. of cases (Doesn't have country level data)
worldometer_data.csv - Data from https://www.worldometers.info/about/
time_series_covid19_confirmed_global.ipynb - Has day to day global confirmed cases data
time_series_covid19_deaths_global.ipynb - Has day to day global deaths data
time_series_covid19_recovered_global.ipynb - Has day to day global recovered data
time_series_covid19_confirmed_US.ipynb - Has day to day US confirmed cases data
time_series_covid19_deaths_US.ipynb - Has day to day US deaths data