---
license: cc-by-nc-4.0
task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: hc01_t2d_sample
configs:
- config_name: default
  data_files:
  - split: train
    path: complications.tsfile
  - split: train
    path: encounters.tsfile
  - split: train
    path: labs.tsfile
  - split: train
    path: medications.tsfile
  - split: train
    path: patient_master.tsfile
  - split: train
    path: population_summary.tsfile
---

# hc01_t2d_sample (TsFile)

Apache TsFile version of [`xpertsystems/hc01-t2d-sample`](https://huggingface.co/datasets/xpertsystems/hc01-t2d-sample).

- **Data files:** `['complications.tsfile', 'encounters.tsfile', 'labs.tsfile', 'medications.tsfile', 'patient_master.tsfile', 'population_summary.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("complications.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/xpertsystems/hc01-t2d-sample
- License: cc-by-nc-4.0