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---
license: cc0-1.0
pretty_name: Lichess Standard Rated Games
dataset_info:
features:
- name: Event
dtype: string
- name: Site
dtype: string
- name: White
dtype: string
- name: Black
dtype: string
- name: Result
dtype: string
- name: WhiteTitle
dtype: string
- name: BlackTitle
dtype: string
- name: WhiteElo
dtype: int16
- name: BlackElo
dtype: int16
- name: WhiteRatingDiff
dtype: int16
- name: BlackRatingDiff
dtype: int16
- name: UTCDate
dtype: date32
- name: UTCTime
dtype: time32[s]
- name: ECO
dtype: string
- name: Opening
dtype: string
- name: Termination
dtype: string
- name: TimeControl
dtype: string
- name: movetext
dtype: string
configs:
- config_name: default
data_files:
- split: train
path: data/**/train-*
tags:
- chess
- games
- game
- lichess
size_categories:
- 1B<n<10B
---
> [!CAUTION]
> This dataset is still a work in progress and some breaking changes might occur. In the meantime, please use https://database.lichess.org/#standard_games
>
# Dataset Card for the Lichess Rated Standard Chess Games Dataset
## Dataset Description
**6,111,210,071** standard rated games, played on [lichess.org], updated monthly from the [database dumps](https://database.lichess.org/#standard_games).
This version of the data is meant for data analysis. If you need PGN files you can find those [here](https://database.lichess.org/#standard_games). That said, once you have a subset of interest, it is trivial to convert it back to PGN as shown in the [Dataset Usage](#dataset-usage) section.
This dataset is hive-partitioned into multiple parquet files on two keys: `year` and `month`:
```bash
.
├── data
│ └── year=2015
│ ├── month=01
│ │ ├── train-00000-of-00003.parquet
│ │ ├── train-00001-of-00003.parquet
│ │ └── train-00002-of-00003.parquet
│ ├── month=02
│ │ ├── train-00000-of-00003.parquet
│ │ ├── train-00001-of-00003.parquet
│ │ └── train-00002-of-00003.parquet
│ ├── ...
```
### Dataset Creation
```python
```
### Dataset Usage
Using the `datasets` library:
```python
from datasets import load_dataset
dset = load_dataset("Lichess/chess-evaluations", split="train")
```
Using the `polars` library:
Using DuckDB:
Using `python-chess`:
## Dataset Details
### Dataset Sample
One row of the dataset looks like this:
```python
{
"Event":,
"Site":,
}
```
### Dataset Fields
Every row of the dataset contains the following fields:
- **`Event`**: `string`,
- **`Site`**: `string`,
### Notes
- About 6% of the games include Stockfish analysis evaluations: [%eval 2.35] (235 centipawn advantage), [%eval #-4] (getting mated in 4), always from White's point of view.
- The WhiteElo and BlackElo tags contain Glicko2 ratings.
- Games contain clock information as PGN %clk comments since April 2017. |