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 arra
A great substitute for np.isnan() and pd.isnull() is
for i in range(0,a.shape[0]): if(a[i]!=a[i]): //do something here //a[i] is nan
since only nan is not equal to itself.