REST API for Covid-19 in India

Data-cleansing/Transformation process on the Dataset

• Formatted dates (YYYY-MM-DD format).
• Formatted time (from 12-hour to 24-hour format).
• Missing values for the no. of hospitals and beds have been replaced by the mean values.
• Missing age values have been replaced by mode.
• Age ranges have been replaced by the mean of the lower bound and upper bound.
• After decimal part has been ignored for ages (some ages were in decimal).
• In StatewiseTestingDetails.csv, positive_cases + negative_cases = total_samples, so if one of the two values is missing (i.e. pos. or neg.) it is substituted by performing substraction from total samples but if both are missing then 0 is assigned.
• Finally there are columns in dataset where more than 80-90% of the values is missing, these columns have been simply ignored.

Loading of Dataset into Database

• Load csv file into dataframe using pandas.
• Reload the database by hitting the required endpoint (check urls.py).
• Perform transformations.
• It will create each object (row by row) and then save it in the database.
• Databse used is SQLite (because of small application).

Technology Stack

Languages :-

Python

Frameworks, Libraries and Tools:-

Django, Django-REST-Framework, Pandas, Numpy, Git

Databases:-

SQLite, Postgresql

Environment:-

Windows(my PC)