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

Create a Dataset from a list of cases

  • names (sequence of str) – Names for the variables.

  • cases (sequence of sequence of { str | scalar | 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 (str | sequence of 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, the intersection is used instead.


See Dataset basics