BUG: replace of numeric by string fixed

Author: Carlos Souza

doc/source/whatsnew/v0.20.0.txt

@@ -989,3 +989,5 @@ Bug Fixes
 - Bug in ``pd.melt()`` where passing a tuple value for ``value_vars`` caused a ``TypeError`` (:issue:`15348`)
 - Bug in ``.eval()`` which caused multiline evals to fail with local variables not on the first line (:issue:`15342`)
 - Bug in ``pd.read_msgpack`` which did not allow to load dataframe with an index of type ``CategoricalIndex`` (:issue:`15487`)
+
+- Bug in ``Series.replace`` which replaced a numeric by string (:issue:`15743`)

pandas/core/missing.py

@@ -21,11 +21,16 @@ def mask_missing(arr, values_to_mask):
     Return a masking array of same size/shape as arr
     with entries equaling any member of values_to_mask set to True
     """
-    if not isinstance(values_to_mask, (list, np.ndarray)):
+    if isinstance(values_to_mask, np.ndarray):
+        mask_type = values_to_mask.dtype.type
+    elif isinstance(values_to_mask, list):
+        mask_type = type(values_to_mask[0])
+    else:
+        mask_type = type(values_to_mask)
         values_to_mask = [values_to_mask]
 
     try:
-        values_to_mask = np.array(values_to_mask, dtype=arr.dtype)
+        values_to_mask = np.array(values_to_mask, dtype=mask_type)
     except Exception:
         values_to_mask = np.array(values_to_mask, dtype=object)
 
@@ -409,7 +414,7 @@ def interpolate_2d(values, method='pad', axis=0, limit=None, fill_value=None,
         if axis != 0:  # pragma: no cover
             raise AssertionError("cannot interpolate on a ndim == 1 with "
                                  "axis != 0")
-        values = values.reshape(tuple((1, ) + values.shape))
+        values = values.reshape(tuple((1,) + values.shape))
 
     if fill_value is None:
         mask = None
@@ -447,7 +452,6 @@ def wrapper(arr, mask, limit=None):
 
 
 def pad_1d(values, limit=None, mask=None, dtype=None):
-
     if dtype is None:
         dtype = values.dtype
     _method = None
@@ -472,7 +476,6 @@ def pad_1d(values, limit=None, mask=None, dtype=None):
 
 
 def backfill_1d(values, limit=None, mask=None, dtype=None):
-
     if dtype is None:
         dtype = values.dtype
     _method = None
@@ -498,7 +501,6 @@ def backfill_1d(values, limit=None, mask=None, dtype=None):
 
 
 def pad_2d(values, limit=None, mask=None, dtype=None):
-
     if dtype is None:
         dtype = values.dtype
     _method = None
@@ -528,7 +530,6 @@ def pad_2d(values, limit=None, mask=None, dtype=None):
 
 
 def backfill_2d(values, limit=None, mask=None, dtype=None):
-
     if dtype is None:
         dtype = values.dtype
     _method = None

pandas/tests/series/test_replace.py

@@ -10,7 +10,6 @@
 
 
 class TestSeriesReplace(TestData, tm.TestCase):
-
     def test_replace(self):
         N = 100
         ser = pd.Series(np.random.randn(N))
@@ -101,7 +100,7 @@ def test_replace_gh5319(self):
         expected = ser.copy()
         expected.loc[2] = pd.Timestamp('20120101')
         result = ser.replace({pd.Timestamp('20130103'):
-                              pd.Timestamp('20120101')})
+                                  pd.Timestamp('20120101')})
         tm.assert_series_equal(result, expected)
         result = ser.replace(pd.Timestamp('20130103'),
                              pd.Timestamp('20120101'))
@@ -227,3 +226,10 @@ def test_replace_with_empty_dictlike(self):
         s = pd.Series(list('abcd'))
         tm.assert_series_equal(s, s.replace(dict()))
         tm.assert_series_equal(s, s.replace(pd.Series([])))
+
+    def test_replace_string_with_nan(self):
+        # GH 15743
+        s = pd.Series([1, 2, 3])
+        result = s.replace('2', np.nan)
+        expected = pd.Series([1, 2, 3])
+        tm.assert_series_equal(expected, result)