pandas.api.extensions.ExtensionArray._reduce

ExtensionArray._reduce(name, *, skipna=True, keepdims=False, **kwargs)

Return a scalar result of performing the reduction operation.

Parameters:

namestr

Name of the function, supported values are: { any, all, min, max, sum, mean, median, prod, std, var, sem, kurt, skew }.

skipnabool, default True

If True, skip NaN values.

keepdimsbool, default False

If False, a scalar is returned. If True, the result has dimension with size one along the reduced axis.

**kwargs

Additional keyword arguments passed to the reduction function. Currently, ddof is the only supported kwarg.

Returns:

scalar or ndarray:

The result of the reduction operation. The type of the result depends on keepdims: - If keepdims is False, a scalar value is returned. - If keepdims is True, the result is wrapped in a numpy array with a single element.

Raises:

TypeErrorsubclass does not define operations

See also

Series.min

Return the minimum value.

Series.max

Return the maximum value.

Series.sum

Return the sum of values.

Series.mean

Return the mean of values.

Series.median

Return the median of values.

Series.std

Return the standard deviation.

Series.var

Return the variance.

Series.prod

Return the product of values.

Series.sem

Return the standard error of the mean.

Series.kurt

Return the kurtosis.

Series.skew

Return the skewness.

Examples

>>> pd.array([1, 2, 3])._reduce("min")
np.int64(1)
>>> pd.array([1, 2, 3])._reduce("max")
np.int64(3)
>>> pd.array([1, 2, 3])._reduce("sum")
np.int64(6)
>>> pd.array([1, 2, 3])._reduce("mean")
np.float64(2.0)
>>> pd.array([1, 2, 3])._reduce("median")
np.float64(2.0)