https://github.com/netcodez/netflix-movies-analysis
"Netflix Movies Analysis" is a data analysis project that explores the trends in movie durations on the Netflix platform. The project utilizes Python and pandas to analyze and visualize the average movie durations over time, providing insights into the changing landscape of movie lengths.
https://github.com/netcodez/netflix-movies-analysis
Last synced: 12 months ago
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"Netflix Movies Analysis" is a data analysis project that explores the trends in movie durations on the Netflix platform. The project utilizes Python and pandas to analyze and visualize the average movie durations over time, providing insights into the changing landscape of movie lengths.
- Host: GitHub
- URL: https://github.com/netcodez/netflix-movies-analysis
- Owner: Netcodez
- Created: 2023-06-29T18:34:15.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-29T19:36:50.000Z (over 2 years ago)
- Last Synced: 2025-01-15T19:27:52.577Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 195 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Netflix Movies Analysis
"Netflix Movies Analysis" is a data analysis project that explores the trends in movie durations on the Netflix platform. The project utilizes Python and pandas to analyze and visualize the average movie durations over time, providing insights into the changing landscape of movie lengths.
Netflix Movies and Guest Stars in The Office Data Analysis
## Overview
This repository contains a software project aimed at analyzing Netflix movies and guest stars in the TV show "The Office." The project utilizes Python and popular data manipulation and visualization libraries such as pandas, matplotlib, and numpy. By leveraging these tools, we provide data-driven insights to assist decision-making in the entertainment industry.
## Features
- Data Loading and Preparation: Load the Netflix dataset in CSV format into a pandas DataFrame. Perform data cleaning and manipulation tasks to filter for movies and extract relevant columns required for analysis.
- Movie Duration Analysis: Calculate the average duration of movies on Netflix from 2011 to 2020 using the available data. Visualize the trend in movie durations over time using a line plot.
- Complete Netflix Data Exploration: Load and inspect the full Netflix dataset to gain a comprehensive understanding of the available data beyond the movie analysis.
- Movie Filtering: Filter the Netflix dataset to include only movies for further analysis. Extract essential movie details such as title, country, genre, release year, and duration.
- Movie Duration Visualization: Create a scatter plot to visually represent the relationship between movie duration and release year. Distinguish non-feature films such as children's movies, documentaries, and stand-up shows using different colors.
- Analysis of Short Movies: Identify and analyze movies with a duration of less than 60 minutes. Examine the genres of these short movies to investigate their influence on the overall average duration.
## Conclusion
This software project enables the analysis of Netflix movies and guest stars in "The Office" using Python programming and data manipulation techniques. By examining movie durations, trends, and genre correlations, it provides valuable insights for decision-making in the entertainment industry. Future enhancements could include statistical analysis, exploring additional factors affecting movie durations, analyzing guest stars' data in relation to Netflix movies, and incorporating machine learning techniques for predictive analysis. This project empowers entertainment professionals with data-driven insights to make informed decisions and drive success in the industry.
## Installation
To run the project locally, follow these steps:
- Clone the repository: git clone https://github.com/your-username/netflix-movies-analysis.git
- Install the required dependencies: pip install -r requirements.txt
- Run the main script: python notebook.py
Note: Ensure you have Python 3.x and pip installed on your system