---
task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: ego4d_manipulation_v1
size_categories:
- 10K<n<100K
---

# ego4d_manipulation_v1 (TsFile)

Apache TsFile version of [`mderry/ego4d-manipulation-v1`](https://huggingface.co/datasets/mderry/ego4d-manipulation-v1).

- **Records:** 25,415

## Schema (TsFile structure)

- **episode_index, task_index** (TAG) — device dimension(s).
- **episode_index** (FIELD).
- **task_index** (FIELD).
- **frame_index** (FIELD).
- **observation_images_ego** (FIELD).
- **observation_state_0** (FIELD).
- **observation_state_1** (FIELD).
- **observation_state_2** (FIELD).
- **observation_state_3** (FIELD).
- **observation_state_4** (FIELD).
- **observation_state_5** (FIELD).
- **observation_state_6** (FIELD).
- **observation_state_7** (FIELD).
- **observation_state_8** (FIELD).
- **observation_state_9** (FIELD).
- **observation_state_10** (FIELD).
- **observation_state_11** (FIELD).
- **observation_state_12** (FIELD).
- **observation_state_13** (FIELD).
- **action_0** (FIELD).
- **action_1** (FIELD).
- **action_2** (FIELD).
- **action_3** (FIELD).
- **action_4** (FIELD).
- **action_5** (FIELD).
- **action_6** (FIELD).
- **action_7** (FIELD).
- **action_8** (FIELD).
- **action_9** (FIELD).
- **action_10** (FIELD).
- **action_11** (FIELD).
- **action_12** (FIELD).
- **action_13** (FIELD).

## 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/ego4d_manipulation_v1.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/mderry/ego4d-manipulation-v1
- Author / publisher: mderry
- License: not declared by the original dataset; please defer to the original.