https://github.com/itsrummmy/from-pixels-to-profit-eda

Exploratory data analysis on a TMDB dataset to evaluate movie performance across genres
https://github.com/itsrummmy/from-pixels-to-profit-eda

eda exploratory-data-analysis matplotlib pandas

Last synced: 2 months ago
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Exploratory data analysis on a TMDB dataset to evaluate movie performance across genres

• Host: GitHub
• URL: https://github.com/itsrummmy/from-pixels-to-profit-eda
• Owner: Itsrummmy
• Created: 2024-12-19T14:15:04.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2025-01-08T23:02:46.000Z (9 months ago)
• Last Synced: 2025-03-22T16:24:18.329Z (7 months ago)
• Topics: eda, exploratory-data-analysis, matplotlib, pandas
• Language: Jupyter Notebook
• Homepage:
• Size: 4.01 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          


# TMDB Exploratory Data Analysis Project

  Table of Contents

  


    


      Project Overview

    

    


      Tools Used

    

    


      Deliverables

    

    


      Outcomes

    

    


      Conclusion

    

    


      Requirements

  



## Project Overview

This project utilized Python and other python libraries to explore the TMDb dataset, focusing on analyzing movie performance across genres based on *revenue, popularity, and vote counts*.

## Tools Used

* **Python**

* **Libraries**:

  * `pandas`

  * `numpy`

  * `matplotlib`

  * `seaborn`

## Deliverables

A single notebook containing the full exploratory data analysis done.

## Outcomes

The analysis indicated that Animation emerged as the top-performing genre across revenue, popularity, and audience vote metrics. Although animation films generally require higher production budgets compared to other genres, they exhibit a significantly higher return on investment.

## Conclusion

This project offered an opportunity to develop my data analysis skills. I gained practical experience in data cleaning, handling missing values, identifying correlations, and effectively communicating findings through visualizations. Presenting my findings enhanced my ability to communicate data insights in an analytical and professional manner.

## Requirements

To run this project locally, you'll need: Python 3.x Jupyter Notebook Pandas and other relevant Python libraries.

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