Improvements in the original Exploratory Data Analysis part (can be seen in Presentation Powerpoint page 6-14, which includes 10 pictures).Please run the code（Part1-Exploratory Data Analysis.ipynb, Part 1 R code.R） in the same folder as movie_data.csv.

Modelling the relationship between film features in our dataset and the IMDb rating (can be seen in Presentation Powerpoint page 25-33, which includes 7 pictures).Please run the code(Part2-Model Development.ipynb) in the same folder as movie_data.csv .

ARIMA in forecasting the number of new movies next year (can be seen in Presentation Powerpoint page 15-24, which includes 20 pictures). Please run the codes with the CSV files in the corresponding folders(four folders in total excluding the folder titled 'correlation test').

Data source:

For Netflix Dataset: https://www.kaggle.com/datasets/shivamb/netflix-shows

For Disney Dataset: https://www.kaggle.com/datasets/shivamb/disney-movies-and-tv-shows

For Hulu Dataset: https://www.kaggle.com/datasets/shivamb/hulu-movies-and-tv-shows

This directory contains the ipynb for the original case study that can be run without local data files.