psychopy_ext.stats.accuracy

psychopy_ext.stats.accuracy(df, values=None, correct='correct', incorrect='incorrect', **kwargs)[source]

Computes accuracy given correct and incorrect data labels.

Args:
df (pandas.DataFrame)

Your data

Kwargs:
  • values (str or list of str, default: None)

    Name(s) of the column(s) that is aggregated

  • correct (str or a number or list of str or numbers, default: None)

    Labels that are treated as correct responses.

  • incorrect (str or a number or list of str or numbers, default: None)

    Labels that are treated as incorrect responses.

  • kwargs

    Anything else you want to pass to aggregate(). Note that aggfunc is set to np.size and you cannot change that.

Returns:

A pandas.DataFrame in the format of accuracy() where the reported values are a fraction correct / (correct+incorrect).

See also:

accuracy()