Numpy isnan() fails on an array of floats (from pandas dataframe apply)

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I have an array of floats (some normal numbers, some nans) that is coming out of an apply on a pandas dataframe.

For some reason, numpy.isnan is failing on this array, however as shown below, each element is a float, numpy.isnan runs correctly on each element, the type of the variable is definitely a numpy array.

What"s going on?!

set([type(x) for x in tester])
Out[59]: {float}

tester
Out[60]: 
array([-0.7000000000000001, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan], dtype=object)

set([type(x) for x in tester])
Out[61]: {float}

np.isnan(tester)
Traceback (most recent call last):

File "<ipython-input-62-e3638605b43c>", line 1, in <module>
np.isnan(tester)

TypeError: ufunc "isnan" not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ""safe""

set([np.isnan(x) for x in tester])
Out[65]: {False, True}

type(tester)
Out[66]: numpy.ndarray

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