openml.tasks.list_tasks

openml.tasks.list_tasks(task_type: Optional[openml.tasks.task.TaskType] = None, offset: Optional[int] = None, size: Optional[int] = None, tag: Optional[str] = None, output_format: str = 'dict', **kwargs) Union[Dict, pandas.core.frame.DataFrame]

Return a number of tasks having the given tag and task_type

Parameters
Filter task_type is separated from the other filters because
it is used as task_type in the task description, but it is named
type when used as a filter in list tasks call.
task_typeTaskType, optional

ID of the task type as detailed here. - Supervised classification: 1 - Supervised regression: 2 - Learning curve: 3 - Supervised data stream classification: 4 - Clustering: 5 - Machine Learning Challenge: 6 - Survival Analysis: 7 - Subgroup Discovery: 8

offsetint, optional

the number of tasks to skip, starting from the first

sizeint, optional

the maximum number of tasks to show

tagstr, optional

the tag to include

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

kwargs: dict, optional

Legal filter operators: data_tag, status, data_id, data_name, number_instances, number_features, number_classes, number_missing_values.

Returns
dict

All tasks having the given task_type and the give tag. Every task is represented by a dictionary containing the following information: task id, dataset id, task_type and status. If qualities are calculated for the associated dataset, some of these are also returned.

dataframe

All tasks having the given task_type and the give tag. Every task is represented by a row in the data frame containing the following information as columns: task id, dataset id, task_type and status. If qualities are calculated for the associated dataset, some of these are also returned.