min and max gives arbitrary result (instead of nan) when there is nan #87
Description
In [1]: import riptable as rt
In [2]: rt.version
'1.0.38'
In [3]: import numpy as np
In [4]: ar = np.array([1.0, np.nan, 3.0])
In [5]: np.min(ar)
nan
In [6]: tmp = rt.Dataset({'f': ar})
In [7]: np.min(tmp['f'])
3.0
In [8]: tmp['f'].min()
3.0