CODEWITHSUNDEEP
pythonnumpymean
user330860
user330860

Reputation:

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

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.

Upvotes: 33

Views: 51155

Answers (7)

Ishan Tomar
Ishan Tomar

Reputation: 1554

np.mean(Matrice[Matrice != None])

Upvotes: 0

tom10
tom10

Reputation: 69242

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

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

From the numpy docs linked above, "The numpy.ma module provides a nearly work-alike replacement for numpy that supports data arrays with masks."

Upvotes: 12

strangeloop
strangeloop

Reputation: 839

You can 'upcast' the array to numpy's float64 dtype and then use numpy's nanmean method as in the following example:

import numpy as np

arr = [1,2,3, None]
arr2 = np.array(arr, dtype=np.float64)
print(arr2) # [ 1.  2.  3. nan]
print(np.nanmean(arr2)) # 2.0

Upvotes: 4

Noam Peled
Noam Peled

Reputation: 4632

You can use scipy for that:

import scipy.stats.stats as st
m=st.nanmean(vec)

Upvotes: 6

endolith
endolith

Reputation: 26823

You might also be able to kludge with values like NaN or Inf.

In [1]: array([1, 2, None])
Out[1]: array([1, 2, None], dtype=object)

In [2]: array([1, 2, NaN])
Out[2]: array([  1.,   2.,  NaN])

Actually, it might not even be a kludge. Wikipedia says:

NaNs may be used to represent missing values in computations.

Actually, this doesn't work for the mean() function, though, so nevermind. :)

In [20]: mean([1, 2, NaN])
Out[20]: nan

Upvotes: 4

YOU
YOU

Reputation: 123881

You can also use filter, pass None to it, it will filter non True objects, also 0, :D So, use it when you dont need 0 too.

>>> filter(None,[1, 2, None])
[1, 2]

Upvotes: 3

cobbal
cobbal

Reputation: 70763

haven't used numpy, but in standard python you can filter out None using list comprehensions or the filter function

>>> [i for i in [1, 2, None] if i != None]
[1, 2]
>>> filter(lambda x: x != None, [1, 2, None])
[1, 2]

and then average the result to ignore the None

Upvotes: 7

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