Skip to content

Latest commit

 

History

History
62 lines (52 loc) · 3.09 KB

README.md

File metadata and controls

62 lines (52 loc) · 3.09 KB

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.