How to Make The Best Movies

TMDB Movie Dashboard Tableau Link

Business Problem

Analyze IMDB's extensive publicly available dataset, extract the financial datfrom TMDB's API and extract insights and recommendations on how to make the best movies.

This project uses a combination of machine learning model based insights and hypothesis testing to answer stakeholder questions. A Tableau Dashboard was created to supplement visually the stakeholder questions.

Stakeholder's Requirements.

• Stackholders did not want to include movies released before 2000.
• Stackholders are only interested in movies released in the United States

Part 1 - IMDB Data Processing

• Download movie metadata from IMDB's public datasets.
  • The datasets can be obtained here .
  • Data dictionary for extracted datasets can be obtained here .
• Filter the necessary information that meets the stakeholder's requirements
• Files extracted include:
  • title.basics.tsv.gz
  • title.ratings.tsv.gz
  • title.akas.tsv.gz
  • title.crew.tsv.gz
  • title.principals.tsv.gz
  • name.basics.tsv.gz

Part 2 - Extracting TMDB Data

• Extract financial data and MPAA rating for the movies using TMDB's API.

Exploratory Data Analysis

Movies with Financial Data

Movies in each Category

Average Revenue per Certification

Average Budget per Certification

Part 3 - MySQL Database

• Normalize all extracted IMDB movie data into proper MySQL database
  • See notebook for more details on this process

Part 4 - Hypothesis Testing

(to be updated)