Contains all my 📓 Notebooks where I have performed Data Analysis on unique datasets.

Perform analysis on YouTube Watch History data (exported via Google Takeout).

• Previously using Pandas but switched to Polars as I started exploring it.

• Used polars's amazing syntax to handle data, preprocess the text data and handle datetime data.
• Plot many graphs to show some amazing insights present in data.
• Build ML model to predict videos "Content Type" from its title.
• Build a Channel Recommender System which recommends similar channels from channel's videos' title and tags.

Perform analysis on Spotify Streaming History data (exported via Spotify website).

• Analysed data from the perspective of Track, Artist, Album, Playlist and Time.
• Used polars builtin plot namespace (which uses hvplot library internally) to plot analysis graphs.

A project from CampusX's free course on Credit Risk Modeling by Rohan Azad.

• Collaborated with @sambhavm22.
• Perform data analysis, build ML model using diffrent ML algorithms.
• Contains notebooks of mine and @sambhavm22 both.
• Got many insights about banking sector.
• Created diagrams to explain the project workflows.
• Credit Risk Modeling project documentation in PDF format.

Created a dashboard using Streamlit which fetches data from ECI official website.

• Used httpx to fetch data asynchronously.
• Used polars.LazyFrame to manipulate data efficiently.
• Used streamlit to create dashboard.

Instead of Jupyter Notebook uses Marimo a new project as an alternative to Jupyter Notebooks. See marimo website.

🏟️ Try Marimo playground at marimo.app

This directory contains extra notebooks which are independent of each others. Created these notebooks just for learning or fun purpose.