https://github.com/hms75/movie_rating_analysis

A movie rating analysis which identifies trends amongst a dataset of 5000 movies.
https://github.com/hms75/movie_rating_analysis

data-analysis data-visualization matplotlib-pyplot numpy pandas python

Last synced: 7 months ago
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A movie rating analysis which identifies trends amongst a dataset of 5000 movies.

• Host: GitHub
• URL: https://github.com/hms75/movie_rating_analysis
• Owner: HMS75
• Created: 2025-04-05T06:41:09.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2025-04-05T09:43:48.000Z (8 months ago)
• Last Synced: 2025-04-09T19:16:49.076Z (7 months ago)
• Topics: data-analysis, data-visualization, matplotlib-pyplot, numpy, pandas, python
• Language: Python
• Homepage:
• Size: 8.69 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
## Movie_Rating_Analysis

A data analysis project that explores and visualizes trends in movie ratings using a dataset of 5000+ movies. 

This project leverages Python libraries to analyze metrics such as average ratings, popularity, genres, etc.

## Objective

To gain insights from a large movie dataset and create visual representations that help identify patterns in movie performance based on ratings, genres, and other factors.

## Dataset

- Source: [Kaggle Movie Dataset](https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata/data) 

- Size: ~5000 movies

- Format: CSV

## Technologies Used

- **Python**

- **NumPy** – For numerical computations

- **Pandas** – For data manipulation and cleaning

- **Matplotlib** – For creating visualizations

- **Seaborn** - For heatmap 

## Key Analysis Performed

- Count and distribution of movies by genres.

- Top-rated movies and their statistics.

- Relationship between popularity and average ratings.

- Visualization of:

  - Rating distribution

  - Top genres

## How to run

- pip install pandas matplotlib numpy

- python movie_rating_analysis.py

## Charts obtained for various trends

![image](https://github.com/user-attachments/assets/171144b1-65c3-4023-ab5b-4d967f23e184)

![image](https://github.com/user-attachments/assets/2a4c8208-21b8-42d7-b280-08570eca7e01)

![image](https://github.com/user-attachments/assets/133139ab-18b4-47d3-8135-d1fe4c11325e)

![image](https://github.com/user-attachments/assets/0097f1b5-a352-48e7-9510-7802546b6a75)

![image](https://github.com/user-attachments/assets/147ce776-ce9a-4367-ae31-7f5580dad003)

![image](https://github.com/user-attachments/assets/8b2b3ae8-6c19-42f1-baed-8f071effcf7f)

![image](https://github.com/user-attachments/assets/538af9c3-dd12-4fb4-afc7-b3cc4d5e6845)

![image](https://github.com/user-attachments/assets/fb45a262-e3d6-4613-bea2-327f2a777773)

## Author 

HMS