Behavior of sum and infinity

[craustin]

import numpy as np
from pandas import Series
a = [np.nan, 1]
b = [np.inf, 1]
print Series(a).sum() #1
print Series(b).sum() #2
print np.sum(a) #3
print np.sum(b) #4

I understand that pandas has made the design decision that sums with nans will drop nans (#1), but why is infinity dropped in the same way? I don't see why np.inf + 5 could reasonably be 5. numpy returns np.inf in this case.

[wesm]

This arose entirely out of practicality--the unfortunate alternative is that you need to add a LOT of infinity checks in your code (and replace infinity with NA in many cases). I agree it's probably a good idea to replace all usages of np.isfinite(x) with -np.isnan(x) .

[wesm]

Initially it seemed like treating infs as NAs as the way to go but now
not so sure

On Mon, Mar 26, 2012 at 1:36 PM, Chang She
reply@reply.github.com
wrote:

The logic is the same in both cases that Series.sum should only sum over
valid numerical values. Series([inf, 3, 4]).sum() is not inf + 3 +4, but
instead it is 3 + 4.

On Mon, Mar 26, 2012 at 10:48 AM, Craig Austin <
reply@reply.github.com

wrote:

import numpy as np
from pandas import Series
a = [np.nan, 1]
b = [np.inf, 1]
print Series(a).sum() #1
print Series(b).sum() #2
print np.sum(a) #3
print np.sum(b) #4

I understand that pandas has made the design decision that sums with nans
will drop nans (#1), but why is infinity dropped in the same way?  I don't
see why np.inf + 5 could reasonably be 5.  numpy returns np.inf in this
case.

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