File size: 1,597 Bytes
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license: apache-2.0
tags:
- tsfile
- timeseries
- format:tsfile
- time-series
configs:
- config_name: default
data_files:
- split: train
path: data/upload_test.tsfile
---
# upload_test
Converted from the Hugging Face dataset [`Dongkkka/upload_test`](https://huggingface.co/datasets/Dongkkka/upload_test) to Apache TsFile format.
## Source Dataset
- **Original dataset:** [`Dongkkka/upload_test`](https://huggingface.co/datasets/Dongkkka/upload_test)
- **Authors:** Dongkkka
- **License:** apache-2.0
## Conversion Notes
- Conversion mode: `script`
- Time precision: `ms`
- TsFile data files: `['data/upload_test.tsfile']`
- Converter: `scripts/converters/lerobot_listfix.py`
## 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/upload_test.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())
``` |