Best Data Visualisation Hack at Dataday Grind III by MLH

Check out the project video here - YouTube

Inspiration💡

Air pollution, one of the most major problems in today's world.

• How the air quality been pre and post-Covid.
• How Air Quality varies across different cities.
• Cities that have severe conditions in terms of air quality

What it does 🧭

The ipynb notebook consists of data mining, wrangling and visualisation techniques to understand how the air pollution is varied across various cities in India. We aim to analyze -

• the air quality pre and post covid for a given city.

How we built it 🔧

Our solution, was built using Jupyter notebook and Python along with it's numerous libraries

Tech Stack 🔨

1. Data Science
2. Python
3. Jupyter Notebook
4. Anaconda
5. Git
6. GitHub
7. DaVinci Resolve 16

Challenges we ran into 🏃‍♂️

1. We could not implement the part where we could take in the name of the city as an input to showcase predicted air quality over the next months due to the time constraints.

Accomplishments that we're proud of 🏅

1. We made the analysis for pre and post covid
2. Understood how burning crackers or fireworks during festivals affects our environment

What we learned 🧠

1. Learnt Data visualisation techniques
2. Exploring the dataset

What's next ⏭

1. For future additions we aim to take in city name as an input and predict how the air quality can be in the future

Collaborators 🤖

Only developers.

Name	GitHub Profile
Gyanesh Samanta	GitHub
Praveen Kumar K	GitHub