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task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: kuiper_fleet_data
configs:
- config_name: default
data_files:
- split: train
path: kuiper_fleet_data.tsfile
---
# kuiper_fleet_data (TsFile)
Apache TsFile version of [`juliensimon/kuiper-fleet-data`](https://huggingface.co/datasets/juliensimon/kuiper-fleet-data).
- **Data files:** `['kuiper_fleet_data.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("kuiper_fleet_data.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/juliensimon/kuiper-fleet-data
- License: not declared by the original dataset; please defer to the original.
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