openml.study.list_studies¶
- openml.study.list_studies(offset: int | None = None, size: int | None = None, status: str | None = None, uploader: list[str] | None = None, benchmark_suite: int | None = None, output_format: typing_extensions.Literal[dict] = 'dict') dict¶
- openml.study.list_studies(offset: int | None = None, size: int | None = None, status: str | None = None, uploader: list[str] | None = None, benchmark_suite: int | None = None, output_format: typing_extensions.Literal[dataframe] = 'dataframe') DataFrame
Return a list of all studies which are on OpenML.
- Parameters:
- offsetint, optional
The number of studies to skip, starting from the first.
- sizeint, optional
The maximum number of studies to show.
- statusstr, optional
Should be {active, in_preparation, deactivated, all}. By default active studies are returned.
- uploaderlist (int), optional
Result filter. Will only return studies created by these users.
- benchmark_suiteint, optional
- output_format: str, optional (default=’dict’)
The parameter decides the format of the output. - If ‘dict’ the output is a dict of dict - If ‘dataframe’ the output is a pandas DataFrame
- Returns:
- datasetsdict of dicts, or dataframe
- If output_format=’dict’
Every dataset is represented by a dictionary containing the following information: - id - alias (optional) - name - benchmark_suite (optional) - status - creator - creation_date If qualities are calculated for the dataset, some of these are also returned.
- If output_format=’dataframe’
Every dataset is represented by a dictionary containing the following information: - id - alias (optional) - name - benchmark_suite (optional) - status - creator - creation_date If qualities are calculated for the dataset, some of these are also returned.