Project

Data Science Project - COVID-19 Data analysis

This repository is open for contributions from everyone at college, as a part of the annual Kalanjali events. Make your commits count!

Project Aim :

Analyzing prevalent COVID-19 datasets to generate insights on the spread of COVID-19 over time using charts, graphs, time series and other tools.

Authors:

• Thanya Ramanathan (2nd Year, MEE)
• Anirudh Balan (2nd Year, EEE)

Tools used

• Anaconda
• Jupyter Notebook

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Language and Libraries used

• Python
• Pandas
• Matplotlib
• Numpy
• Seaborn

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Kaggle and Our World in Data were the main sources for our datasets.
Different datasets pertaining to response measures taken, cases confirmed in India and around the World, vaccines prefferred by some countries and number of vaccines administered in India and around the world were chosen.

Graphs shown

• Response measures taken (bar graph)
• Number of cases registered in Indian states and union territories (line graph)
• Variation on number of COVID cases with time (time series)
• Top 10 most affected countriies (line graph)
• Variation of number of cases worldwide with respect to time (time series)
• Variation of number of cases worldwide with respect to time (jointplot)
• Subplots comparing the spread of H1N1, SARS and COVID with respect to time (line graph)
• Vaccines administered worldwide (bar graph)
• Vaccines administered worldwide over time (time series)
• Moderna (pie chart)
• Oxford/Astra Zenaca (pie chart)
• Pfizer/BioNtech (piechart)
• Sinovac (pie chart)
• Propotion of different vaccines used in countries (stack plot)
• Vaccinations in India (time series)
• Vaccinations per capita (time series)
• Daily vaccinations per million (joint plot)

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