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This project is part of Udacity Data Analyst Nanodegree.

I had the option to choose from several datasets from here, And I chose this one.

Overview

The primary goal of the project is to go through the general data analysis process — using basic data analysis technique with NumPy, pandas, and Matplotlib. The movie dataset, which is originally from Kaggle, was cleaned and provided by Udacity. According Kaggle introduction page, the data contains information that are provided from The Movie Database (TMDb). It collects 5000+ movies basic move information and movie matrices, including user ratings, popularity and revenue data. These metrics can be seen as how successful these movies are. The movie basic information contained like cast, director, keywords, runtime, genres, etc.

Questions Asked.

1 General Questions:

  • Number of movie released year by year
  • Popularity Over Years.
  • Budget and Movie Trends over the years.

2 Properties associated with popular movies

  • Average duration, budget, revenue of movies based on popularity ?
  • Which director directed most films based on popularity?
  • Whcih cast has appeared the most based on popularity?
  • Which production companies are more successful based on popularity
  • Which genre are more successful based on popularity?

Requirements

  • Python 3.6 and up
  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn
  • Jupyter Notebook.

About

The Movie DataBase Analysis.

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