`scipy.stats._mstats_basic:describe`

source: /scipy/stats/_mstats_basic.py:3101

Signature

def describe(a, axis = 0, ddof = 0, bias = True)

Summary

Computes several descriptive statistics of the passed array.

Parameters

a : array_like: Data array
axis : int or None, optional: Axis along which to calculate statistics. Default 0. If None, compute over the whole array a.
ddof : int, optional: degree of freedom (default 0); note that default ddof is different from the same routine in stats.describe
bias : bool, optional: If False, then the skewness and kurtosis calculations are corrected for statistical bias.

Returns

nobs : int: (size of the data (discarding missing values)
minmax : (int, int): min, max
mean : float: arithmetic mean
variance : float: unbiased variance
skewness : float: biased skewness
kurtosis : float: biased kurtosis

Examples

import numpy as np
from scipy.stats.mstats import describe
ma = np.ma.array(range(6), mask=[0, 0, 0, 1, 1, 1])

✓

describe(ma)

✗

DescribeResult(nobs=np.int64(3), minmax=(masked_array(data=0,
             mask=False,
       fill_value=999999), masked_array(data=2,
             mask=False,
       fill_value=999999)), mean=np.float64(1.0), variance=np.float64(0.6666666666666666), skewness=masked_array(data=0.,
             mask=False,
       fill_value=1e+20), kurtosis=np.float64(-1.5))

Aliases

scipy.stats._mstats_basic.describe