/Profit-Analyses-TMBD-Movies

Analyzing the profit and success of different movies within the TMDB movies dataset

Primary LanguageJupyter Notebook

Profit Analyses of TMBD Movies

Introduction

Have you ever wondered what makes a movie a block buster and preform well intenationally?, Does the sucess of movies depend on the skills of the cast or the director?, What is the most popular movie production company and why do these companies wrap up millions even billions of dollars every year in revenue?. In this project we would be analyzing different movies realeased from 1960 to 2015, and try to find the key features that makes these movies successful. This data set contains information of about 10,000 movies collected from The Movie Database (TMDb),including user ratings, release year, production companies, budget and revenue.

Installation

  • Pandas
  • Numpy
  • Matplotlib
  • Seaborn

Result

These were some of the results gained after the project was completed.

The Top 5 most profitable movies

  • Avatar
  • Star Wars: The Force Awakens
  • Titanic
  • Jurassic World
  • Furious 7

Most Popular Genre includes:

  • Drama
  • Comedy
  • Thriller
  • Action
  • Romance
  • Horror

Production Companies involved in High budget movies, High Revenue, and are popular are:

  • Universal Pictures
  • Warner Bros
  • Paramount Pictures
  • 20th Century Fox
  • Columbia Pictures
  • Walt Disney
  • Dream Works

Production Companies with high Profit Margin:

  • Warner Bros
  • Pixar Studios
  • Walt Disney
  • Marvel Studios
  • 20th Century Fox

All the production companies stated above having high budget, revenue, and are popular all had movies that failed. This shows that high budget does not neccesary influence the revenue of movies, but is a key factor to some successful movies.

Project Limitation

Columns like cast, tagline, homepage, overview, and vote_count where not explored in this project which might have improve the quality of the data analysis. The project did not make any predictions, but only use simple statistical analysis to make assumptions.