eelbrain.Dataset.from_caselist

classmethod Dataset.from_caselist(names, cases, name=None, caption=None, info=None, random=None, check_dims=True, dim_intersection=False, to_list=False)

Create a Dataset from a list of cases

Parameters

  • names (Sequence[str]) – Names for the variables.

  • cases (Sequence[Sequence[str, Number, NDVar]]) – A sequence of cases, whereby each case is itself represented as a sequence of values (str or scalar). Variable type (Factor or Var) is inferred from whether values are str or not.

  • name (str) – Name for the Dataset.

  • caption (str) – Caption for the table.

  • info (dict) – Info dictionary, can contain arbitrary entries and can be accessed as .info attribute after initialization. The Dataset makes a shallow copy.

  • random (Union[str, Collection[str]]) – Names of the columns that should be assigned as random factor.

  • check_dims (bool) – For NDVar columns, check dimensions for consistency between cases (e.g., channel locations in a Sensor). Default is True. Set to False to ignore mismatches.

  • dim_intersection (bool) – Only applies to combining NDVar: normally, when NDVar have mismatching dimensions, a DimensionMismatchError is raised. With dim_intersection=True, the intersection is used instead.

  • to_list (bool) – Only applies to combining NDVar: normally, when NDVar have mismatching dimensions, a DimensionMismatchError is raised. With to_list=True, the NDVar are added as list of NDVar instead.

Examples

See Dataset basics