EXPLORATORY DATA ANALYSIS

Covid-19 Cases and Vaccinations

Introduction

This is an Exploratory Data Analysis project on Covid-19 Cases and Vaccination.

The Aim of the Project is to extract the characteristic results from the Data set and conduct comparative analysis of cases and vaccination among the countries.

The essential Questions formulated are related to Set of Vaccines are preferred by Countries, daily vaccinations, positive rate, total confirmed, active and death cases. There are several Visualizations regarding Leading Countries in highest number of total confirmed cases, serious critical cases and total Covid-19 deaths

The most powerful tools for data analysis used in this project are the packages Numpy and Pandas, and to visualize and explore the data: Matplotlib, Plotly and Seaborn. All of these tools were meaningfully and efficiently taught in the course "Data Analysis with Python: Zero to Pandas" given by Jovian in partnership with freeCodeCamp.

How to run the code

This is an executable Jupyter notebook hosted on Jovian.ml, a platform for sharing data science projects. You can run and experiment with the code in a couple of ways: using free online resources (recommended) or on your own computer.

Option 1: Running using free online resources (1-click, recommended)

The easiest way to start executing this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks. You can also select "Run on Colab" or "Run on Kaggle".

Option 2: Running on your computer locally

1. Install Conda by following these instructions. Add Conda binaries to your system PATH, so you can use the conda command on your terminal.

2. Create a Conda environment and install the required libraries by running these commands on the terminal:

conda create -n zerotopandas -y python=3.8 
conda activate zerotopandas
pip install jovian jupyter numpy pandas matplotlib seaborn opendatasets --upgrade

3. Press the "Clone" button above to copy the command for downloading the notebook, and run it on the terminal. This will create a new directory and download the notebook. The command will look something like this:

jovian clone notebook-owner/notebook-id

4. Enter the newly created directory using cd directory-name and start the Jupyter notebook.

jupyter notebook

You can now access Jupyter's web interface by clicking the link that shows up on the terminal or by visiting http://localhost:8888 on your browser. Click on the notebook file (it has a .ipynb extension) to open it.

Uploading this Jupyter notebook to Jovian.ai