CineMatch - Your Personal Movie Matchmaker 🎥

Welcome to CineMatch, a personalized movie recommendation system that helps you find the perfect movie based on your favorite genres and era preferences. Powered by IMDb data, CineMatch allows users to explore a variety of genres and choose movies from different time periods, providing top-rated suggestions along the way!

Table of Contents

• Features
• Installation
• Usage
• Requirements
• Data Source
• License

Features

• Interactive Interface: Simple prompts to select your favorite movie genres and era (before or after 2000).
• Top 10 Movies: Option to view top 10 movies by vote average within your selected genres.
• Detailed Movie Information: Provides detailed movie information such as title, overview, cast, director, release date, and more.
• Customizable Options: Filter movies by genre and era, and choose to see additional movie details on demand.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/cinematch.git

2. Navigate to the project directory:

   cd cinematch

3. Install the required Python packages: Make sure you have Python installed. You can install the necessary dependencies using:

   pip install pandas

4. Download the IMDb dataset: The system uses an IMDb dataset in CSV format. You can download the IMDb data from IMDb datasets and place it in the appropriate folder. Ensure that the file path in the script points to the location of the CSV file.

Usage

1. Run the CineMatch system:

   python cinematch.py

2. Follow the prompts:

   • Enter your name.
   • Choose your preferred genres from the available list.
   • Select whether you'd like movies from the "old" era (before 2000) or the "new" era (from 2000 onwards).
   • Optionally, you can view the top 10 movies sorted by vote average.

3. Explore movie recommendations:

   • Choose a movie from the generated list, and view detailed information such as overview, cast, director, runtime, and more.

Requirements

• Python 3.x
• pandas library

Data Source

This project uses IMDb data, which can be obtained from the official IMDb datasets here. The script assumes the dataset is in CSV format with fields such as:

• genres
• release_year
• vote_average
• original_title
• overview
• cast
• director
• release_date
• runtime
• budget
• revenue
• popularity
• vote_count
• keywords
• homepage