Datasets:

azithromycin
/

ReubenLim_so101_ball_in_cup

license: apache-2.0
authors:
  - Reuben Lim Yaw Hui
task_categories:
  - robotics
tags:
  - tsfile
  - timeseries
  - tabular
modality:
  - timeseries
  - tabular
pretty_name: SO101 Ball in Cup TsFile
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/reubenlim_so101_ball_in_cup.tsfile
size_categories:
  - 10K<n<100K

SO101 Ball in Cup TsFile

This is an Apache TsFile conversion of ReubenLim/so101_ball_in_cup, a LeRobot v2.1 SO101 dataset for picking up a ball and placing it in a cup.

Source and provenance

Original dataset: ReubenLim/so101_ball_in_cup
Pinned source revision: 811ff35e5d324f666941ad289c06de4d13980538
Repository owner, uploader, and commit author: Reuben Lim Yaw Hui (ReubenLim)
License: Apache-2.0
Paper/citation: not provided by the source repository
Robot: so101; LeRobot codebase: v2.1
Split: train; sampling frequency: 30 fps
Task 0: Pick up the ball and place it in the cup.
Scale: 61 episodes, 57,839 rows, one task, 61 source Parquet shards
Source data path: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet

The source README still embeds an obsolete 23-episode info.json example. The counts above come from the pinned repository meta/info.json, all source Parquet footers, and the complete repository tree.

Converted artifact

TsFile: data/reubenlim_so101_ball_in_cup.tsfile
Table: reubenlim_so101_ball_in_cup
Rows/devices: 57,839 / 61
Time precision: milliseconds
Source Parquet size: 2,754,715 bytes
TsFile size: 780,173 bytes
TsFile/source size ratio: 0.283214
meta/ is preserved, with meta/info.json updated for this TsFile artifact.

Schema

Column or group	TsFile role	Type	Notes
`Time`	TIME	INT64	`round(timestamp * 1000)` ms; restarts at zero per episode
`episode_index`	TAG	STRING	Original integer value stored as a TsFile device/TAG segment
`task_index`	TAG	STRING	Original integer value stored as a TsFile device/TAG segment
`frame_index`	FIELD	INT64	Original per-episode frame index
`sample_index`	FIELD	INT64	Renamed from source `index`
`action_0` ... `action_5`	FIELD	FLOAT	Flattened source `action[6]`
`observation_state_0` ... `observation_state_5`	FIELD	FLOAT	Flattened source `observation.state[6]`

Vector prefixes preserve their source names, with . replaced by _.

Conversion details

Time: TS_2DIFF + LZ4
FLOAT/DOUBLE: GORILLA + LZ4
INT32/INT64: TS_2DIFF + LZ4
BOOLEAN: RLE + LZ4 when present; this source has no BOOLEAN field
TAG values use the TsFile table-model device/tag mechanism.
All train episodes are merged into one table and sorted by TAG columns and Time.
Source timestamp is dropped because it is represented by Time / 1000 seconds.
No numeric rows, action/state dimensions, frame indexes, episode indexes, or task indexes are dropped.
Camera pixels are video assets rather than Parquet columns and are not embedded in TsFile.

Videos

Videos are not included in this TsFile dataset. The original repository stores 183 frame-aligned AV1 MP4 files: 61 episodes for each of the front, overhead, and side streams under videos/chunk-000/. The exact template is videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. The source videos total 1,585,929,900 bytes and are 640x480 at 30 fps without audio. Stream sizes are 573,779,857 bytes (front), 483,143,898 bytes (overhead), and 529,006,145 bytes (side). Use episode_index and frame_index to align TsFile rows with all three views.

Validation

Local validation read all 57,839 rows with the Apache TsFile Java reader, checked the physical codecs, TAG schema, per-episode Time ordering, vector widths, duplicate TAG+Time keys, and the source/staged/TsFile row counts. The conversion script and validation reports stay local and are not part of the upload-ready dataset directory.

Minimal read example

from tsfile import TsFileReader

reader = TsFileReader("data/reubenlim_so101_ball_in_cup.tsfile")
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
]
with reader.query_table("reubenlim_so101_ball_in_cup", columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()

Citation

The source repository provides no formal citation. Cite the original Hugging Face dataset and its repository author Reuben Lim Yaw Hui (ReubenLim) when using this conversion.