https://github.com/arv-anshul/notebooks

My Jupyter notebooks in which I practice data science.
https://github.com/arv-anshul/notebooks

classification data-analysis data-science jupyter-notebook machine-learning matplotlib numpy pandas python3 regression seaborn visualization

Last synced: 4 days ago
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My Jupyter notebooks in which I practice data science.

• Host: GitHub
• URL: https://github.com/arv-anshul/notebooks
• Owner: arv-anshul
• License: apache-2.0
• Created: 2023-08-15T06:49:37.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-16T07:00:02.000Z (about 1 month ago)
• Last Synced: 2025-01-16T08:17:50.096Z (about 1 month ago)
• Topics: classification, data-analysis, data-science, jupyter-notebook, machine-learning, matplotlib, numpy, pandas, python3, regression, seaborn, visualization
• Language: Jupyter Notebook
• Homepage:
• Size: 28.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Notebooks

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

> \[!IMPORTANT\]

>

> See [`data/README.md`](data/README.md) to know about datasets I have used.

## Directory Info

### [`yt-watch-history`](yt-watch-history/)

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.

### [`spotify-analysis`](spotify-analysis/)

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.

### [`credit-modeling`](credit-modeling/)

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.

[Credit Risk Modeling project documentation]: credit-modeling/docs/DOCUMENTATION.pdf

[@sambhavm22]: https://github.com/sambhavm22

### [`election-2024`](election-2024/)

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.

Where is Notebooks?

There are no notebooks present in this project because I've converted those into `.py` scripts because I have to create

a dashboard using it and converted notebook's non-`async` codes into `async` code.

### [`marimo`](marimo/)

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

[website](https://marimo.io).

🏟️ Try Marimo playground at [marimo.app](https://marimo.app)

### [`extra`](extra/)

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

or fun purpose.