---
license: apache-2.0
task_categories:
- robotics
tags:
- tsfile
- timeseries
- time-series
- LeRobot
- robotics
- format:tsfile
pretty_name: so100_basketball
size_categories:
- 10K<n<100K
---

# so100_basketball (TsFile)

Apache TsFile version of [`hoon-shin/so100_basketball`](https://huggingface.co/datasets/hoon-shin/so100_basketball).

## Overview

A LeRobot robot dataset recorded on a so100 arm. Task(s): Grasp basketball and place into cup.. Each frame holds the commanded `action` and observed `observation.state` joint positions, plus camera views stored as videos in the original dataset.

- **Episodes:** 50
- **Frames:** 37,289
- **Sampling rate:** 30 fps
- **Tasks:** 1 — "Grasp basketball and place into cup."

## Schema (TsFile structure)

All episodes share one TsFile with `episode_index` and `task_index` as TAG columns; query a single episode with `WHERE episode_index = N`.

- **Time** (INT64, milliseconds) — `round(timestamp * 1000)`; the source
  `timestamp` column is dropped (it equals Time / 1000).
- **episode_index** (TAG) — device dimension.
- **task_index** (TAG) — device dimension.
- **episode_index** (INT64) — measurement.
- **task_index** (INT64) — measurement.
- **frame_index** (INT64) — measurement.
- **sample_index** (INT64) — measurement.
- **action_0** (FLOAT) — measurement.
- **action_1** (FLOAT) — measurement.
- **action_2** (FLOAT) — measurement.
- **action_3** (FLOAT) — measurement.
- **action_4** (FLOAT) — measurement.
- **action_5** (FLOAT) — measurement.
- **observation_state_0** (FLOAT) — measurement.
- **observation_state_1** (FLOAT) — measurement.
- **observation_state_2** (FLOAT) — measurement.
- **observation_state_3** (FLOAT) — measurement.
- **observation_state_4** (FLOAT) — measurement.
- **observation_state_5** (FLOAT) — measurement.

The vector columns are flattened per joint:
- `action_*` — commanded joints: main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, main_gripper.
- `observation_state_*` — observed joints: main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, main_gripper.

## Usage

Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file:

```python
from pathlib import Path
from tsfile import TsFileReader

path = Path("data/so100_basketball.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())
```

## Source & license

- Original dataset: https://huggingface.co/datasets/hoon-shin/so100_basketball
- Author / publisher: hoon-shin
- License: apache-2.0
- Note: camera videos are NOT included; see the original dataset.