| --- |
| 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()) |
| ``` |
