The short-term COVID-19 prediction model project involves fetching and organizing the daily COVID-19 cases data
for India using the Pandas library. The project fetches the data from the CSSEGISandData repository and stores it
in a tidy format in a CSV file named "India.csv". The loadData function is used to convert the raw
data into a tidy format for confirmed cases, deaths, and recovered cases. The refreshData function
merges the three dataframes, keeps only the data for India, and adds a new column named "Day" representing the
number of days since the first case was reported in India.
The organized data can be used to develop a short-term prediction model using linear regression. By using the "Day" column as the independent variable and the "CumConfirmed" column as the dependent variable, the model can predict the number of COVID-19 cases for upcoming days. However, it's important to keep in mind that the accuracy of the model may be impacted by changes in testing protocols, vaccination rates, and government policies. Overall, this project offers a useful tool for analyzing COVID-19 cases data and developing predictive models for India.
A Fully Automated Django Based covid-india Prediction App Which Fetch The Database Then Performs Necessary Calculations On The Data Using The Skit-learn Library Then Push Everything To The Frontend UI
Built Using the CSSEGISandData COVID Database
Use This Link To See The app In action
