在python中删除了NaN值的列表的中位数 [英] Median of a list with NaN values removed, in python

问题描述

是否可以在不显式删除NaN的情况下计算列表的中位数，而是忽略它们?

Is it possible to calculate the median of a list without explicitly removing the NaN's, but rather, ignoring them?

我希望median([1,2,3,NaN,NaN,NaN,NaN,NaN,NaN])为2，而不是NaN.

I want median([1,2,3,NaN,NaN,NaN,NaN,NaN,NaN]) to be 2, not NaN.

推荐答案

numpy 1.9.0具有功能nanmedian:

numpy 1.9.0 has the function nanmedian:

nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=False)
    Compute the median along the specified axis, while ignoring NaNs.

    Returns the median of the array elements.

    .. versionadded:: 1.9.0

例如

>>> from numpy import nanmedian, NaN
>>> nanmedian([1,2,3,NaN,NaN,NaN,NaN,NaN,NaN])
2.0

如果您不能使用numpy的1.9.0版本，则类似@Parker的答案将起作用；例如

If you can't use version 1.9.0 of numpy, something like @Parker's answer will work; e.g.

>>> import numpy as np
>>> x = np.array([1,2,3,NaN,NaN,NaN,NaN,NaN,NaN])
>>> np.median(x[~np.isnan(x)])
2.0

或

>>> np.median(x[np.isfinite(x)])
2.0

(应用于布尔数组时，~是not的一元运算符.)

(When applied to a boolean array, ~ is the unary operator notation for not.)

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