Enhanced Movie Ratings Dashboard

A Python-based tool for analyzing movie metadata and user ratings from Kaggle datasets. Features a command-line interface (CLI) for filtering, statistics, and visualizations, plus a Streamlit web dashboard for interactive exploration. Built as part of a 6-month self-taught Python career transition plan.

Features

• Data Loading: Imports movie metadata (titles, genres, vote averages) and user ratings from CSV into SQLite for persistent storage.
• Filtering: SQL-based filters for genres (multi-genre OR matching), rating ranges, or both.
• Statistics: Genre-based counts and average ratings using SQL aggregations (json_each for multi-genres).
• Ratings Query: Fetch user ratings for a specific movie via SQL joins, with average calculation.
• Visualizations: Bar plots for genre counts, saved as PNG (Matplotlib).
• Save/Load: Export/import filtered data to/from CSV/JSON.
• Web Dashboard: Streamlit UI for dynamic filtering, data display, stats computation, and plotting.
• Error Handling: Robust checks for file existence, invalid inputs, NaN values, and parsing errors.

Installation

1. Clone the repository:

   git clone https://github.com/HuntedCode/python-movie-analyzer.git
   cd python-movie-analyzer

2. Install dependencies (Python 3.8+ required):

   pip install pandas matplotlib streamlit

   (SQLite is built-in; no additional install needed.)
3. Download the datasets: Get movies_metadata.csv and ratings.csv from Kaggle’s The Movies Dataset. Place them in the project folder.

Usage

CLI Mode

Run the CLI for console-based interaction:

python main.py

• Commands: view (display data), filter (genre/rating), stats (genre averages/counts), plot (genre bar chart), ratings (user ratings per movie), save/load (CSV/JSON), refresh (reload data), help, exit.
• Example: Filter for "Drama" movies rated 7-9, compute stats, plot genres.

Web Dashboard Mode

Run the Streamlit dashboard for browser-based use:

streamlit run app.py

• Opens at http://localhost:8501.
• Sidebar: Input genres (space-separated), slider for min/max rating.
• Main page: Displays filtered data table, buttons for stats (dataframe) and plot (bar chart).
• Example: Enter "Comedy Action", set ratings 8-10, click "Compute Stats" and "Generate Plot".

Note: For educational use. Respects Kaggle terms—use datasets responsibly.

Project Structure

• main.py: CLI entry point.
• app.py: Streamlit dashboard entry point.
• cli.py: CLI commands and logic (filters, stats, plots).
• db.py: SQLite database management (loading, queries, joins, aggregations).
• movies_metadata.csv / ratings.csv: Kaggle input data (not in repo—download separately).

Contributing

Feedback welcome! Fork the repo, make changes, and submit a pull request. Report issues on GitHub.

License

MIT License—free to use and modify.

Built by Jeffrey Lowe as part of a 6-month Python learning plan for remote coding jobs. Last updated: August 5, 2025.