Update README.md

README.md

@@ -1,75 +1,10 @@
-# MovieLens Movie Data Analysis
-
-This project provides a reproducible pipeline for preprocessing and exploratory data analysis (EDA) on the MovieLens movie dataset.
-
-## Project Structure
-
-```
-.
-├── app/
-│   └── Practical.py         # Main entry point for running the pipeline
-├── src/
-│   ├── preprocessing.py     # Data loading, cleaning, merging
-│   └── eda.py               # EDA and visualization (plots saved to /report/images)
-├── notebooks/
-│   └── Practical.ipynb      # Step-by-step notebook for exploration and prototyping
-├── report/
-│   └── images/              # Output directory for all generated plots and images
-├── data/
-│   ├── raw/                 # Raw input data (CSV files)
-│   ├── interim/             # Cleaned/intermediate CSVs
-│   └── processed/           # (Optional) Final processed data
-├── requirements.txt         # Python dependencies
-└── README.md                # This file
-```
-
-## How to Run
-
-1. **Install dependencies**  
-   Make sure you have Python 3.8+ and run:
-   ```
-   pip install -r requirements.txt
-   ```
-
-2. **Prepare data**  
-   Place the raw MovieLens CSV files in `data/raw/` as:
-   - `movies_metadata.csv`
-   - `credits.csv`
-   - `keywords.csv`
-   - `links.csv`
-   - `ratings.csv`
-
-3. **Run the pipeline**
-   ```
-   python app/Practical.py
-   ```
-   This will:
-   - Clean and merge the data
-   - Save interim cleaned CSVs to `data/interim/`
-   - Generate all EDA plots and wordclouds, saving them to `report/images/`
-   - Save interactive Plotly plots as PNG (requires [kaleido](https://github.com/plotly/Kaleido)) or HTML fallback
-
-## Features
-
-- **Modular Preprocessing**: All data cleaning, merging, and type handling in `src/preprocessing.py`
-- **Automated EDA**: All plots and wordclouds generated and saved by `src/eda.py`
-- **Reproducibility**: One-command run for the entire workflow
-- **Notebook**: `notebooks/Practical.ipynb` for step-by-step exploration
-
-## Requirements
-
-- pandas
-- numpy
-- matplotlib
-- seaborn
-- missingno
-- wordcloud
-- plotly
-- pycountry
-- kaleido (for static plotly image export)
-
-## Notes
-
-- If static Plotly image export fails, HTML versions of the plots are saved as a fallback.
-- All output images are saved in `report/images/`.
-- Adjust paths in `src/eda.py` and `src/preprocessing.py` if your
+---
+title: Movie Recommender System
+emoji: 🎬
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: "4.41.0"   # you can also leave this out and HF picks latest
+app_file: app.py
+pinned: false
+---