eelbrain.table.stats(y, row, col=None, match=None, sub=None, fmt='%.4g', funcs=(<function mean>, ), ds=None, title=None, caption=None)

Make a table with statistics

  • y (Var) – Dependent variable.

  • row (Union[Factor, Interaction, NestedEffect, str]) – Model specifying rows

  • col (Union[Factor, Interaction, NestedEffect, str, None]) – Model specifying columns.

  • match (Union[Factor, Interaction, NestedEffect, str, None]) – Identifier for repeated measures data; aggregate within subject before computing statistics.

  • sub (Union[Var, ndarray, str, None]) – Only use part of the data.

  • fmt (str) – How to format values.

  • funcs (Sequence[Callable]) – A list of statistics functions to show (all functions must take an array argument and return a scalar).

  • ds (Optional[Dataset]) – If a Dataset is provided, y, row, and col can be strings specifying members.

  • title (Union[str, List[str], FMTextElement, FMTextConstant, None]) – Table title.

  • caption (str | FMText) – Table caption.


table – Table with statistics.

Return type



>>> ds = datasets.get_uts()
>>> table.stats('Y', 'A', 'B', ds=ds)
     b0        b1
a0   0.1668    -0.3646
a1   -0.4897   0.8746
>>> table.stats('Y', 'A', ds=ds, funcs=[np.mean, np.std])
Condition   Mean     Std
a0          0.6691   1.37
a1          0.8596   1.192