Hugging Face's logo

Datasets:
AiresPucrs
/
movielens-movies

Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1K - 10K
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
2
movielens-movies / README.md
dieineb's picture
dieineb
Update README.md
3aec397 verified
preview code
|
raw
history blame contribute delete
No virus
2.46 kB
metadata
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: movieId
      dtype: int64
    - name: title
      dtype: string
    - name: genres
      dtype: string
  splits:
    - name: train
      num_bytes: 563045
      num_examples: 9742
  download_size: 300293
  dataset_size: 563045
language:
  - en
pretty_name: Movielens-movies
size_categories:
  - 1K<n<10K
license: other

Movielens-movies

This dataset contains a set of movies from the MovieLens website, a movie recommendation service.

Overview

MovieLens data sets were collected by the GroupLens Research Project at the University of Minnesota. The GroupLens Research has collected and made available rating data sets from the MovieLens website. MovieLens 100K movie ratings contain 100,000 ratings(1-5)from 943 users on 1682 movies. Released 1998.

Dataset Details

The dataset from Kaggle is named MovieLens100. Contains different CSV files for Movies, Ratings, Links, and Tags. We used only the file "movies.csv" in movielens-movies dataset.

  • Dataset Name: movielens-movies
  • Language: English
  • Total Size: 9,742 demonstrations

Citation:

@article{10.1145/2827872,
author = {Harper, F. Maxwell and Konstan, Joseph A.},
title = {The MovieLens Datasets: History and Context},
year = {2015},
issue_date = {January 2016},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {5},
number = {4},
issn = {2160-6455},
url = {https://doi.org/10.1145/2827872},
doi = {10.1145/2827872},
journal = {ACM Trans. Interact. Intell. Syst.},
month = dec,
articleno = {19},
numpages = {19},
keywords = {Datasets, recommendations, ratings, MovieLens}
}

Contents

The dataset consists of a data frame with the following columns:

  • movieID is a unique identifier of the rated movie.
  • title: the title of the rated movie with the release year in parentheses.
  • genres: a sequence of genres to which the rated movie belongs.
{
  movieID: 2,
  title: "Jumanji (1995)",
  genres: "Adventure|Children|Fantasy"
}

How to use 

from datasets import load_dataset

dataset = load_dataset("AiresPucrs/movielens-movies", split='train')

License

This dataset is licensed under the USAGE LICENSE - Other.