metadata
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 to Apache TsFile format.
Source Dataset
- Original dataset:
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:
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())