thegreatfaizan / Investigating-Netflix-Movies-and-Guest-Stars-in-The-Office

In this guided project, we explore the world of Netflix movies and guest stars featured in the popular TV show, The Office. Using data analysis and visualization techniques, we gain insights into the most popular movies and guest stars on Netflix, as well as their ratings and viewership trends.

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Investigating Netflix Movies and Guest Stars in The Office

Introduction

This repository contains a data analysis project investigating the popularity of Netflix movies and guest stars in the hit TV show, The Office. The project utilizes two datasets: color_data.csv and netflix_data.csv, to uncover insights and trends in the data. The results are presented in a Jupyter Notebook file, notebook.ipynb.

Datasets

The datasets directory contains two csv files:

color_data.csv: This file contains information about various colors and their RGB values.

netflix_data.csv: This file contains information about Netflix movies and TV shows, as well as their ratings and viewership trends.

Notebook

The Jupyter Notebook file, notebook.ipynb, presents the data analysis and visualization results. The notebook contains all the code and explanations necessary to follow along with the project.

Requirements

To run this project, you will need the following packages installed:

"pandas"

"numpy"

"matplotlib"

Conclusion

This project provides a unique and entertaining way to explore the world of Netflix movies and guest stars in The Office. By utilizing data analysis and visualization techniques, we gain valuable insights and understanding about the popularity of these media offerings. The project serves as a great learning opportunity for anyone interested in data science.

About

In this guided project, we explore the world of Netflix movies and guest stars featured in the popular TV show, The Office. Using data analysis and visualization techniques, we gain insights into the most popular movies and guest stars on Netflix, as well as their ratings and viewership trends.


Languages

Language:Jupyter Notebook 100.0%