Yet another dataset about movies. This dataset consists of more than 100K movies/TV shows items. Data are scraped from criticker.com and for each item meta-data fields like title, description, and publish date are provided. Below you will find an extensive description for each field.
What makes this dataset different:
- Then is comes to deep learning, size does matter. My goal is to create a huge dataset with almost every movie/tv show item from criticker.
- Ratings and Reviews.
great_expectations tool is used for Data Quality purposes, check here the datadocs
movies.csv contains almost every movie/tv show from criticker. For each item the following fields are available (wherever is applicable):
| field name | description | field type |
|---|---|---|
| actors | Comma-separated actors' names | str |
| akas | Comma-separated AKA (As Known as) names | str |
| avg_percentile | Ratings average percentile | float |
| counties | Comma-separated countries | str |
| creators | Comma-separated creators' names | str |
| date_published | [For films only] Year of publish | int |
| description | Description | str |
| directors | Comma-separated directors' names | str |
| end_date | [For TV Shows only] End year | int |
| franchises | Comma-separated franchises | str |
| genres | Comma-separated genres | str |
| n_ratings | Total number of ratings | int |
| name | Name | str |
| poster_url | Poster's url | str |
| rss_feed_url | RSS Feed url | str |
| start_date | [For TV Shows only] Start year | int |
| trailer_url | Youtube trailer url | str |
| type | Type like Short Film, TV Show and others. Empty type means that item is probably a regular film | str |
| uid | md5 Unique ID | str |
| url | URL | str |
| writers | Comma-separated writers' names | str |
- Add ratings and reviews