Dataset: Netflixmovies

About this Dataset

Netflixmovies

I extracted this data to find the unpopular movies on Netflix. The dataset I used here comes directly from Netflix movies data, which consists of 4 text data files, each file contains over 20M rows, over 4K movies, and 400K, customers. Altogether over are 17K movies and 500K+ customers!

I made some modifications and I extracted the e df_avgRating_with_usersCount.csv from the original data after applying some mathematical operations to get the average ratings and the count of users who made the ratings for each movie in movie_id below. Feel free to browse and use the data within your notebooks.

Here you could find my previous notebook on Kaggle to extract the dataset

Tables

Df Avgrating With Userscount

@kaggle.kefahaied_netflixmovies.df_avgrating_with_userscount

85.2 KB
4499 rows
3 columns


CREATE TABLE df_avgrating_with_userscount (
  "movie_id" BIGINT,
  "rating" DOUBLE,
  "user_id" BIGINT
);

Movie Titles

@kaggle.kefahaied_netflixmovies.movie_titles

551.75 KB
17770 rows
4 columns


CREATE TABLE movie_titles (
  "unnamed_0" BIGINT,
  "movie_id" BIGINT,
  "year" DOUBLE,
  "name" VARCHAR
);