CODEWITHSUNDEEP
pythonarraysnumpy
wubbalubba
wubbalubba

Reputation: 764

Average of a numpy array returns NaN

I have an np.array with over 330,000 rows. I simply try to take the average of it and it returns NaN. Even if I try to filter out any potential NaN values in my array (there shouldn't be any anyways), average returns NaN. Am I doing something totally wacky?

My code is here: 

average(ngma_heat_daily)
Out[70]: nan

average(ngma_heat_daily[ngma_heat_daily != nan])
Out[71]: nan

Upvotes: 21

Views: 28403

Answers (2)

Saswata Mishra
Saswata Mishra

Reputation: 111

Also, there is a function named nanmedian which ignores NaN values. Signature of that function is: numpy.nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=<no value>)

Upvotes: 3

jakevdp
jakevdp

Reputation: 86463

try this:

>>> np.nanmean(ngma_heat_daily)

This function drops NaN values from your array before taking the mean.

Edit: the reason that average(ngma_heat_daily[ngma_heat_daily != nan]) doesn't work is because of this:

>>> np.nan == np.nan
False

according to the IEEE floating-point standard, NaN is not equal to itself! You could do this instead to implement the same idea:

>>> average(ngma_heat_daily[~np.isnan(ngma_heat_daily)])

np.isnan, np.isinf, and similar functions are very useful for this type of data masking.

Upvotes: 25

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