How to use numpy with 'None' value in Python?

python numpy mean
user330860 picture user330860 · Jun 7, 2009 · Viewed 30.8k times · Source

I'd like to calculate the mean of an array in Python in this form:

Matrice = [1, 2, None]

I'd just like to have my None value ignored by the numpy.mean calculation but I can't figure out how to do it.

Answer

tom10 picture tom10 · Jun 7, 2009

You are looking for masked arrays. Here's an example.

import MA
a = MA.array([1, 2, None], mask = [0, 0, 1])
print "average =", MA.average(a)

Unfortunately, masked arrays aren't thoroughly supported in numpy, so you've got to look around to see what can and can't be done with them.

Related questions

Mean Squared Error in Numpy?

Is there a method in numpy for calculating the Mean Squared Error between two matrices? I've tried searching but found none. Is it under a different name? If there isn't, how do you overcome this? Do you write it yourself …

Read More
np.mean() vs np.average() in Python NumPy?

I notice that In [30]: np.mean([1, 2, 3]) Out[30]: 2.0 In [31]: np.average([1, 2, 3]) Out[31]: 2.0 However, there should be some differences, since after all they are two different functions. What are the differences between them?

Read More
Calculate mean across dimension in a 2D array

I have an array a like this: a = [[40, 10], [50, 11]] I need to calculate the mean for each dimension separately, the result should be this: [45, 10.5] 45 being the mean of a[*][0] and 10.5 the mean of a[*][1]. What is the most elegant way of …

Read More