From 3cc2fae24b6f117e9ed7daccf72ef478608c5f74 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Fri, 2 Nov 2018 16:34:34 +0100
Subject: [PATCH] API: fix corner case of lib.infer_dtype (#23422)

---
 pandas/_libs/lib.pyx                  |  5 ++++-
 pandas/_libs/missing.pxd              |  6 ++++++
 pandas/_libs/missing.pyx              |  2 +-
 pandas/tests/dtypes/test_inference.py | 16 ++++++++++++++++
 4 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index 6ec9a7e93bc55b..3a02a4ac33192a 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -57,7 +57,7 @@ from tslibs.conversion cimport convert_to_tsobject
 from tslibs.timedeltas cimport convert_to_timedelta64
 from tslibs.timezones cimport get_timezone, tz_compare
 
-from missing cimport (checknull,
+from missing cimport (checknull, isnaobj,
                       is_null_datetime64, is_null_timedelta64, is_null_period)
 
 
@@ -1177,6 +1177,9 @@ def infer_dtype(object value, bint skipna=False):
         values = construct_1d_object_array_from_listlike(value)
 
     values = getattr(values, 'values', values)
+    if skipna:
+        values = values[~isnaobj(values)]
+
     val = _try_infer_map(values)
     if val is not None:
         return val
diff --git a/pandas/_libs/missing.pxd b/pandas/_libs/missing.pxd
index 9f660cc6785c8c..e171dc5f2c9624 100644
--- a/pandas/_libs/missing.pxd
+++ b/pandas/_libs/missing.pxd
@@ -1,8 +1,14 @@
 # -*- coding: utf-8 -*-
 
+from numpy cimport ndarray, uint8_t
+
+from tslibs.nattype cimport is_null_datetimelike
+
 cpdef bint checknull(object val)
 cpdef bint checknull_old(object val)
 
+cpdef ndarray[uint8_t] isnaobj(ndarray arr)
+
 cdef bint is_null_datetime64(v)
 cdef bint is_null_timedelta64(v)
 cdef bint is_null_period(v)
diff --git a/pandas/_libs/missing.pyx b/pandas/_libs/missing.pyx
index 2590a30c57f33d..6776a4b6d7f7e7 100644
--- a/pandas/_libs/missing.pyx
+++ b/pandas/_libs/missing.pyx
@@ -124,7 +124,7 @@ cdef inline bint _check_none_nan_inf_neginf(object val):
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def isnaobj(ndarray arr):
+cpdef ndarray[uint8_t] isnaobj(ndarray arr):
     """
     Return boolean mask denoting which elements of a 1-D array are na-like,
     according to the criteria defined in `_check_all_nulls`:
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index d0dd03d6eb8df8..c5911da1666d25 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -591,6 +591,22 @@ def test_unicode(self):
         expected = 'unicode' if PY2 else 'string'
         assert result == expected
 
+    @pytest.mark.parametrize('dtype, missing, skipna, expected', [
+        (float, np.nan, False, 'floating'),
+        (float, np.nan, True, 'floating'),
+        (object, np.nan, False, 'floating'),
+        (object, np.nan, True, 'empty'),
+        (object, None, False, 'mixed'),
+        (object, None, True, 'empty')
+    ])
+    @pytest.mark.parametrize('box', [pd.Series, np.array])
+    def test_object_empty(self, box, missing, dtype, skipna, expected):
+        # GH 23421
+        arr = box([missing, missing], dtype=dtype)
+
+        result = lib.infer_dtype(arr, skipna=skipna)
+        assert result == expected
+
     def test_datetime(self):
 
         dates = [datetime(2012, 1, x) for x in range(1, 20)]