import dascore as dc
from dascore.utils.downloader import fetch
file_path = fetch("prodml_2.1.h5")
df = dc.scan_to_df(file_path)scan_to_df
scan_to_df(
path: Path | str | Patch | BaseSpool | IOResourceManager ,
file_format: str | None[str, None] = None,
file_version: str | None[str, None] = None,
ext: str | None[str, None] = None,
timestamp: float | None[float, None] = None,
progress: Literal[‘standard’, ‘basic’, None] = standard,
exclude = (‘history’,),
)-> ‘pd.DataFrame’
Scan a path, return a dataframe of contents.
The columns of the dataframe depend on the attributes and coordinates found in the data files.
Parameters
| Parameter | Description |
|---|---|
| path | The path the to file to scan |
| file_format | Format of the file. If not provided DASCore will try to determine it. |
| file_version | The version string of the file. |
| exclude | A sequence of column names to exclude in the final dataframe. |