Name: IMDB Movies Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

IMDB Movies Dataset

Context

IMDB Dataset of top 1000 movies and tv shows.
You can find the EDA Process on - https://www.kaggle.com/harshitshankhdhar/eda-on-imdb-movies-dataset

Please consider UPVOTE if you found it useful.

Content

Data:-

Poster_Link - Link of the poster that imdb using
Series_Title = Name of the movie
Released_Year - Year at which that movie released
Certificate - Certificate earned by that movie
Runtime - Total runtime of the movie
Genre - Genre of the movie
IMDB_Rating - Rating of the movie at IMDB site
Overview - mini story/ summary
Meta_score - Score earned by the movie
Director - Name of the Director
Star1,Star2,Star3,Star4 - Name of the Stars
No_of_votes - Total number of votes
Gross - Money earned by that movie

Inspiration

Analysis of the gross of a movie vs directors.
Analysis of the gross of a movie vs different - different stars.
Analysis of the No_of_votes of a movie vs directors.
Analysis of the No_of_votes of a movie vs different - different stars.
Which actor prefer which Genre more?
Which combination of actors are getting good IMDB_Rating maximum time?
Which combination of actors are getting good gross?

Tables

Imdb Top 1000

@kaggle.harshitshankhdhar_imdb_dataset_of_top_1000_movies_and_tv_shows.imdb_top_1000

254.73 KB
1000 rows
16 columns


CREATE TABLE imdb_top_1000 (
  "poster_link" VARCHAR,
  "series_title" VARCHAR,
  "released_year" VARCHAR,
  "certificate" VARCHAR,
  "runtime" VARCHAR,
  "genre" VARCHAR,
  "imdb_rating" DOUBLE,
  "overview" VARCHAR,
  "meta_score" DOUBLE,
  "director" VARCHAR,
  "star1" VARCHAR,
  "star2" VARCHAR,
  "star3" VARCHAR,
  "star4" VARCHAR,
  "no_of_votes" BIGINT,
  "gross" DOUBLE
);