Welcome to my evolving journey through the world of Data Science! This repository serves as a central hub for my academic projects, self-learning modules, and experimental scripts.
"The goal is to turn data into information, and information into insight."
| Category | Description | Tech Stack |
|---|---|---|
| Academic Python | Core logic and college-level algorithms. | Python |
| Library Basics | Deep dives into data manipulation & viz. | NumPy, Pandas, Seaborn |
| Data Engineering | Data Engineering Principles | Python, SQL |
In the Academic-Python-Projects folder, I documented my transition from basic syntax to structured problem-solving. These represent my first steps into the logic that powers data science.
The Library-Basics folder focuses on the "Big Four" of the Python ecosystem. I used this space to master:
- Cleaning messy data with Pandas.
- Vectorizing math with NumPy.
- Telling Stories through Matplotlib and Seaborn charts.
To run any of these projects locally:
- Clone the repo:
git clone https://github.com/Deekshithaa-Y-M/data-science-playground.git - Navigate to a subfolder.
- Install requirements (if applicable):
pip install -r requirements.txt