We built a website that allowed people to view real-time district wise +ve reported cases, help people in need of emergencies and see the trend of COVID-19 spread. We now try to observe the environmental factors that may influence the spread of Covid-19. Our initial suspect is the weather and climate factors and believe that they play some role in this.

What it does

If successful, the features that affect the spread could be used to lower them by machine or deep learning algorithms.

How I built it

We collect data from our website,, and weather data from onpoint API. We then use python libraries and dataiku to clean any noise and refine the data. We graph to look for any pattern.

Challenges I ran into

A lot of noise and too many parameters (e.g. lockdown and tests done in different districts) that affect  the number of reported cases.

Accomplishments that I'm proud of

We have enough observations, data and resources to publish it on blogs.

What I learned

Data cleaning's a bitch. Noise is a headache.

What's next for The Covindia Project

Try It out



covindiaapi, dataiku, onpointapi, python

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