Do not mask infinite values in nanops.nanargmin, argmax (pandas-dev#1…

…3595)

The implementations of `nanargmin` and `nanargmax` in `nanops` were
forcing the `_get_values` utility function to always mask out infinite
values. For example, in `nanargmax`,

    >>> nanops._get_values(np.array([1, np.nan, np.inf]), True,
    isfinite=True, fill_value_typ='-inf')

    (array([  1., -inf, -inf]),
     array([False,  True,  True], dtype=bool),
     dtype('float64'),
     numpy.float64)

The first element of the result tuple (the masked version of the
values array) is used for actually finding the max or min argument. As
a result, infinite values could never be correctly recognized as the
maximum or minimum values in an array.

pandas/core/nanops.py

@@ -474,8 +474,7 @@ def nanargmax(values, axis=None, skipna=True):
     """
     Returns -1 in the NA case
     """
-    values, mask, dtype, _ = _get_values(values, skipna, fill_value_typ='-inf',
-                                         isfinite=True)
+    values, mask, dtype, _ = _get_values(values, skipna, fill_value_typ='-inf')
     result = values.argmax(axis)
     result = _maybe_arg_null_out(result, axis, mask, skipna)
     return result
@@ -485,8 +484,7 @@ def nanargmin(values, axis=None, skipna=True):
     """
     Returns -1 in the NA case
     """
-    values, mask, dtype, _ = _get_values(values, skipna, fill_value_typ='+inf',
-                                         isfinite=True)
+    values, mask, dtype, _ = _get_values(values, skipna, fill_value_typ='+inf')
     result = values.argmin(axis)
     result = _maybe_arg_null_out(result, axis, mask, skipna)
     return result