README.md

---
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 movie ratings 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](https://movielens.org). 
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](https://www.kaggle.com/datasets/abhikjha/movielens-100k). 
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:**
```latex
@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:  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.

```bash
{
  movieID: 2,
  title: "Jumanji (1995)",
  genres: "Adventure|Children|Fantasy"
}
```

## How to use

```python
from datasets import load_dataset

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

```

## License

This dataset is licensed under the USAGE LICENSE [Other](https://files.grouplens.org/datasets/movielens/ml-100k-README.txt).