SETUP.md

⚙️ Setup Guide — Data Cleanser

Get the notebook running in under 2 minutes.

---

Option 1 — Google Colab (Recommended — Zero Setup)

1. Open Data_Cleanser_ParthShah.ipynb on GitHub
2. Click the Open in Colab button at the top of the file
3. In Colab: Runtime → Run all
4. Done. The dataset is generated inside the notebook — no external file needed.

---

Option 2 — Local Jupyter Notebook

Step 1 — Clone the repository

git clone https://github.com/ParthShah7099/Data-Cleanser.git
cd Data-Cleanser

Step 2 — Create a virtual environment (optional but recommended)

python3 -m venv venv
source venv/bin/activate        # Mac / Linux
venv\Scripts\activate           # Windows

Step 3 — Install dependencies

pip install -r requirements.txt

Step 4 — Launch Jupyter

jupyter notebook

Step 5 — Open and run

Open Data_Cleanser_ParthShah.ipynb → Kernel → Restart & Run All

---

Requirements

Requirement	Version
Python	3.9 or above
pandas	2.0.0 or above
numpy	1.24.0 or above
matplotlib	3.7.0 or above
seaborn	0.12.0 or above
scikit-learn	1.3.0 or above
scipy	1.11.0 or above

All installable in one command via pip install -r requirements.txt.

---

No Dataset File Needed

The dataset is synthetically generated inside the notebook using numpy.random.seed(42).
Every run produces the exact same 200-row patient health records dataset — fully reproducible.

---

Made with discipline by THE PARTH SHAH