scipy.stats.skew¶
- scipy.stats.skew(a, axis=0, bias=True, nan_policy='propagate')[source]¶
Computes the skewness of a data set.
For normally distributed data, the skewness should be about 0. A skewness value > 0 means that there is more weight in the left tail of the distribution. The function skewtest can be used to determine if the skewness value is close enough to 0, statistically speaking.
Parameters: a : ndarray
data
axis : int or None, optional
Axis along which skewness is calculated. Default is 0. If None, compute over the whole array a.
bias : bool, optional
If False, then the calculations are corrected for statistical bias.
nan_policy : {‘propagate’, ‘raise’, ‘omit’}, optional
Defines how to handle when input contains nan. ‘propagate’ returns nan, ‘raise’ throws an error, ‘omit’ performs the calculations ignoring nan values. Default is ‘propagate’.
Returns: skewness : ndarray
The skewness of values along an axis, returning 0 where all values are equal.
References
[R635] Zwillinger, D. and Kokoska, S. (2000). CRC Standard Probability and Statistics Tables and Formulae. Chapman & Hall: New York. 2000. Section 2.2.24.1