pyinterp.core.DescriptiveStatisticsFloat32

class pyinterp.core.DescriptiveStatisticsFloat32(self, values: numpy.ndarray[tuple[int, ...], numpy.dtype[numpy.float64]], weights: [numpy.ndarray[tuple[int, ...], numpy.dtype[numpy.float64]] | None = None, axis: list[int] | None = None)

Bases: pybind11_object

Compute univariate descriptive statistics.

Parameters:

• values – Array containing numbers whose statistics are desired.

• weights – An array of weights associated with the values. If not provided, all values are assumed to have equal weight.

• axes – Axis or axes along which to compute the statistics. If not provided, the statistics are computed over the flattened array.

Public Methods

count(self)	Return the count of samples.
kurtosis(self)	Return the kurtosis of samples.
max(self)	Return the maximum of samples.
mean(self)	Return the mean of samples.
min(self)	Return the minimum of samples.
skewness(self)	Return the skewness of samples.
sum(self)	Return the sum of samples.
sum_of_weights(self)	Return the sum of weights.
variance(self[, ddof])	Return the variance of samples.

Special Methods

__add__(self, other)	Override the default behavior of the + operator.
__copy__(self)	Implement the shallow copy operation.
__getstate__(self, /)
__iadd__(self, other)	Override the default behavior of the += operator.
__setstate__(self, arg0)