IMDb Top Movie Characteristics And Reviews
Exploring Cinematic and Consumer Trends
@kaggle.thedevastator_imdb_top_250_movie_characteristics_and_reviews
Exploring Cinematic and Consumer Trends
@kaggle.thedevastator_imdb_top_250_movie_characteristics_and_reviews
By [source]
This Kaggle dataset contains data related to the top movies according to IMDb, providing a unique insight into the trends and consumer reactions in the world of cinema over the years. With detailed columns listing out film names, scores, duration, release dates, countries of origin and language used as well as details on budgeted costs, gross revenue figures and collected reviews – both positive and negative – this is an exceptional resource for exploring the cinema world. To gain a deeper understanding of popular movie trends we can look into various genres featured in these movies or explore how particular countries have become renowned for certain film styles or sound types. Additionally, we can analyse user sentiments towards different movies reflected through their reviews - giving us a comprehensive overview of how each film has been received. With this dataset at our fingertips we now have access to information that will let us unlock intriguing discoveries about past cinema experiences as well as make better informed predictions about future ones!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
This dataset contains information about the top 250 movies according to IMDB. It includes columns such as name, score, genre(s), duration, release year, country of origin, language, sound format, color format in which the movie was filmed or presented onscreen or released and budget. Along with technical attributes the data also offers insight into user reviews on a six-point scale assigning positive ratings (good reviews) and negative ones (bad reviews).
- Predict the success of movie releases by analyzing features such as genre, budget, duration, and language for historical trends.
- Visualize changes in consumer preferences for different genres of movies over time by comparing user reviews, budgets and ratings from year to year.
- Utilize sentiment analysis on user reviews to understand what kinds of stories/themes cause certain reactions from viewers as well as create predictions on how a movie will be received upon release based on user feedback gathered before the movie has even come out
If you use this dataset in your research, please credit the original authors.
Data Source
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: movies.csv
Column name | Description |
---|---|
name | The title of the movie. (String) |
score | The IMDb score of the movie. (Float) |
genre1 | The primary genre of the movie. (String) |
genre2 | The secondary genre of the movie. (String) |
genre3 | The tertiary genre of the movie. (String) |
duration | The length of the movie in minutes. (Integer) |
release | The year the movie was released. (Integer) |
rating | The MPAA rating of the movie. (String) |
country | The country of origin of the movie. (String) |
language | The language of the movie. (String) |
sound | The sound format of the movie. (String) |
color | The color format of the movie. (String) |
budget | The budget of the movie in USD. (Integer) |
gross | The total gross of the movie in USD. (Integer) |
badReviews | The number of bad reviews for the movie. (Integer) |
neutralReviews | The number of neutral reviews for the movie. (Integer) |
goodReviews | The number of good reviews for the movie. (Integer) |
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .
CREATE TABLE movies (
"name" VARCHAR,
"score" DOUBLE,
"genre1" VARCHAR,
"genre2" VARCHAR,
"genre3" VARCHAR,
"duration" BIGINT,
"release" VARCHAR,
"rating" VARCHAR,
"country" VARCHAR,
"language" VARCHAR,
"sound" VARCHAR,
"color" VARCHAR,
"ratio" VARCHAR,
"budget" VARCHAR,
"gross" VARCHAR,
"badreviews" BIGINT,
"neutralreviews" BIGINT,
"goodreviews" BIGINT
);
Anyone who has the link will be able to view this.