Datasets:
File size: 1,548 Bytes
e13a865 8f70a4b e13a865 8f70a4b e13a865 8f70a4b e13a865 8f70a4b e13a865 8f70a4b e13a865 8f70a4b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
license: mit
task_categories:
- robotics
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: insert_mujoco
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/insert_mujoco.tsfile
---
# insert_mujoco (TsFile)
Apache TsFile version of [`autobio-bench/insert-mujoco`](https://huggingface.co/datasets/autobio-bench/insert-mujoco).
- **Converted rows:** 55,127
- **Data files:** `['data/insert_mujoco.tsfile']`
## 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/insert_mujoco.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/autobio-bench/insert-mujoco
- Author / publisher: autobio-bench
- License: mit
|