https://github.com/walterthesmart/tmdb-project

https://github.com/walterthesmart/tmdb-project

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• Host: GitHub
• URL: https://github.com/walterthesmart/tmdb-project
• Owner: walterthesmart
• Created: 2022-07-01T07:54:44.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-01T08:48:49.000Z (over 2 years ago)
• Last Synced: 2023-03-31T05:24:45.002Z (over 1 year ago)
• Language: HTML
• Size: 502 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# TMDb-project

# TMDb-Project: Investigate The Dataset 

## Table of Contents 

Introduction 

Data Wrangling 

Exploratory Data Analysis 

Conclusions 

## Introduction 

In this project, I will be analyzing data from The Movie Database (TMDb). This data set contains 10,866 rows and the following column attributes:

movie_id - A unique identifier for each movie. 

imdb_id - A unique identifier for each movie on IMDB. 

cast - The name of lead and supporting actors. 

director - the director of the movie. 

budget - The budget in which the movie was made. 

genre - The genre of the movie, Action, Comedy ,Thriller etc. 

homepage - A link to the homepage of the movie. 

id - This is infact the movie_id as in the first dataset. 

keywords - The keywords or tags related to the movie. 

original_title - The title of the movie before translation or adaptation. 

overview - A brief description of the movie. 

popularity - A numeric quantity specifying the movie popularity. 

production_companies - The production house of the movie. 

production_countries - The country in which it was produced. 

release_date - The date on which it was released. 

revenue - The worldwide revenue generated by the movie. 

runtime - The running time of the movie in minutes. 

tagline - Movie's tagline. 

vote_average - average ratings the movie recieved. 

budget_adj - shows the budget associated movie in terms of 2010 dollars. 

revenue_adj - shows the revenue associated movie in terms of 2010 dollars.

The project process is divided into three parts: Data Wrangling, Exploratory Data Analysis, and Conclusion.

## Questions 

This analysis will answer the following questions:

How did the amount of produced films changed over time?

Which Month Released Highest Number Of Movies In all Of The Years?

What is the most and what is the least popular movie?

What are the 10 most and least profitable movies?

What are the correlations between popularity, revenue, budget and profit?