---
license: cc0-1.0
task_categories:
- sentence-similarity
language:
- en
pretty_name: '"Movie descriptors for Semantic Search"'
size_categories:
- 10K<n<100K
tags:
- movies
- embeddings
- semantic search
- films
- hpi
- workshop
---
# Dataset Card

This dataset is a subset from Kaggle's The Movie Dataset that contains only name, release year and overview for every film in the original dataset that has that information complete.
It is intended as a toy dataset for learning about embeddings in a workshop from the AI Service Center Berlin-Brandenburg at the Hasso Plattner Institute.

This dataset has a smaller version [here](https://huggingface.co/datasets/mt0rm0/movie_descriptors_small).

## Dataset Details

### Dataset Description

The dataset has 44435 rows and 3 columns:

- 'name': includes the title of the movies
- 'release_year': indicates the year of release
- 'overview': provides a brief description of each movie, used for advertisement.

**Curated by:** [Mario Tormo Romero](https://huggingface.co/mt0rm0)

**Language(s) (NLP):** English

**License:** cc0-1.0

### Dataset Sources

This Dataset is a subset of Kaggle's [The Movie Dataset](https://www.kaggle.com/datasets/rounakbanik/the-movies-dataset). 
We have only used the <kbd>movies_metadata.csv</kbd> file and extracted some features (see Dataset Description) and dropped the rows that didn't were complete.

The original Dataset has a cc0-1.0 License and we have maintained it.

## Uses

This is a toy dataset created for pegagogical purposes, and is used in the **Working with embeddings** Workshop created and organized by the [AI Service Center Berlin-Brandenburg](https://hpi.de/kisz/) at the [Hasso Plattner Institute](https://hpi.de/). 

## Dataset Creation

### Curation Rationale

We want to provide with this dataset a fast way of obtaining the required data for our workshops without having to download huge datasets that contain just way too much information.  

### Source Data

Our source is Kaggle's The Movie Dataset., so the information comes from the MovieLens Dataset. The dataset consists of movies released on or before July 2017. 

#### Data Collection and Processing

The data was downloaded from [Kaggle](https://www.kaggle.com/datasets/rounakbanik/the-movies-dataset) as a zip file. The file <kbd>movies_metadata.csv</kbd> was then extracted.

The data was processed with the following code:

```python
import pandas as pd

# load the csv file
df = pd.read_csv("movies_metadata.csv", low_memory=False)

# select the required columns, drop rows with missing values and
# reset the index
df = df.loc[:, ['title', 'release_date', 'overview']]
df = df.dropna(axis=0).reset_index(drop=True)

# make a new column with the release year
df.loc[:, 'release_year'] = pd.to_datetime(df.release_date).dt.year

# select the columns in the desired order
df = df.loc[:, ['title', 'release_year', 'overview']]

# save the data to parquet
df.to_parquet('descriptors_data.parquet')
```

#### Who are the source data producers?

This dataset is an ensemble of data collected by [Rounak Banik](https://www.kaggle.com/rounakbanik) from TMDB and GroupLens.
In particular, the movies metadata has been collected from the TMDB Open API, but the source dataset is not endorsed or certified by TMDb.