Data-Analysis-Top-Movie-Streaming

Netflix, Hulu, Prime Video, Disney+ Data Analysis & Data Visualization

Executive Summary

Throughout the analysis, I was able to pull out several interesting insights:

• 18+ ages group has most no. of movies
• Prime Video has more well-rated movies from Rotten Tomato Ratings
• Top 10 languages in Streaming Services is 'English', 'Hindi', 'English,Spanish', 'Spanish', 'English,French', 'Italian', 'French', 'Japanese', 'Mandarin', 'Tamil'
• Prime Video has more well-rated movies from IMDb
• Top 3 Directors Directed most movies- 1. Jay Chapman 2. Joseph Kane 3. Cheh Chang
• Drama is the most produced genre across most countries and over time
• Comedy,Adventure and Action are the most well-rated genres on average
• Top Movies From Each Platform

Exploratory Data Analysis (EDA)

In this project, my goal was to exploit the data in all possible ways. After performing some data cleaning (handling null values, etc.), I answered to these questions:

• What is the number of movies for each age group?
• Top 10 languages in Streaming Services?
• Number of movies in specific age group in All services?
• Rotten Tomato Ratings For Overall Services?
• Rotten Tomato Ratings For Each Services?
• IMDB Ratings?
• Count Of Runtimes Of Movies?
• Directors and their Count Of Movies they have Directed?
• Exploring Genres?
• What are the top Movies On Each Platform?

Prerequisites

• Python

Installation

Install libraries

  pip install pandas
  pip install numpy
  pip install seaborn
  pip install matplotlib
  pip install plotly

Run

  # Running Scraper File..
  Data_Analysis_Top_Movie_Streaming.ipynb  #File inside the folder