CLN: move com.mask_missing to missing

Author: jreback

pandas/core/common.py

@@ -378,53 +378,6 @@ def flatten(l):
             yield el
 
 
-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)):
-        values_to_mask = [values_to_mask]
-
-    try:
-        values_to_mask = np.array(values_to_mask, dtype=arr.dtype)
-    except Exception:
-        values_to_mask = np.array(values_to_mask, dtype=object)
-
-    na_mask = isnull(values_to_mask)
-    nonna = values_to_mask[~na_mask]
-
-    mask = None
-    for x in nonna:
-        if mask is None:
-
-            # numpy elementwise comparison warning
-            if is_numeric_v_string_like(arr, x):
-                mask = False
-            else:
-                mask = arr == x
-
-            # if x is a string and arr is not, then we get False and we must
-            # expand the mask to size arr.shape
-            if lib.isscalar(mask):
-                mask = np.zeros(arr.shape, dtype=bool)
-        else:
-
-            # numpy elementwise comparison warning
-            if is_numeric_v_string_like(arr, x):
-                mask |= False
-            else:
-                mask |= arr == x
-
-    if na_mask.any():
-        if mask is None:
-            mask = isnull(arr)
-        else:
-            mask |= isnull(arr)
-
-    return mask
-
-
 def _pickle_array(arr):
     arr = arr.view(np.ndarray)
 

pandas/core/generic.py

@@ -54,7 +54,7 @@ def _single_replace(self, to_replace, method, inplace, limit):
     result = self if inplace else self.copy()
     fill_f = missing.get_fill_func(method)
 
-    mask = com.mask_missing(result.values, to_replace)
+    mask = missing.mask_missing(result.values, to_replace)
     values = fill_f(result.values, limit=limit, mask=mask)
 
     if values.dtype == orig_dtype and inplace:

pandas/core/internals.py

@@ -597,7 +597,7 @@ def replace(self, to_replace, value, inplace=False, filter=None,
         try:
             values, _, to_replace, _ = self._try_coerce_args(self.values,
                                                              to_replace)
-            mask = com.mask_missing(values, to_replace)
+            mask = missing.mask_missing(values, to_replace)
             if filter is not None:
                 filtered_out = ~self.mgr_locs.isin(filter)
                 mask[filtered_out.nonzero()[0]] = False

pandas/core/missing.py

@@ -10,6 +10,53 @@
 from pandas.compat import range
 
 
+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)):
+        values_to_mask = [values_to_mask]
+
+    try:
+        values_to_mask = np.array(values_to_mask, dtype=arr.dtype)
+    except Exception:
+        values_to_mask = np.array(values_to_mask, dtype=object)
+
+    na_mask = com.isnull(values_to_mask)
+    nonna = values_to_mask[~na_mask]
+
+    mask = None
+    for x in nonna:
+        if mask is None:
+
+            # numpy elementwise comparison warning
+            if com.is_numeric_v_string_like(arr, x):
+                mask = False
+            else:
+                mask = arr == x
+
+            # if x is a string and arr is not, then we get False and we must
+            # expand the mask to size arr.shape
+            if lib.isscalar(mask):
+                mask = np.zeros(arr.shape, dtype=bool)
+        else:
+
+            # numpy elementwise comparison warning
+            if com.is_numeric_v_string_like(arr, x):
+                mask |= False
+            else:
+                mask |= arr == x
+
+    if na_mask.any():
+        if mask is None:
+            mask = com.isnull(arr)
+        else:
+            mask |= com.isnull(arr)
+
+    return mask
+
+
 def clean_fill_method(method, allow_nearest=False):
     if method is None:
         return None
@@ -239,7 +286,7 @@ def interpolate_2d(values, method='pad', axis=0, limit=None, fill_value=None,
     if fill_value is None:
         mask = None
     else:  # todo create faster fill func without masking
-        mask = com.mask_missing(transf(values), fill_value)
+        mask = mask_missing(transf(values), fill_value)
 
     method = clean_fill_method(method)
     if method == 'pad':

pandas/tseries/period.py

@@ -24,6 +24,7 @@
 from pandas.lib import Timedelta
 import pandas.lib as lib
 import pandas.tslib as tslib
+import pandas.core.missing as missing
 from pandas.compat import zip, u
 
 
@@ -77,8 +78,8 @@ def wrapper(self, other):
 
             result = getattr(self.values, opname)(other.values)
 
-            mask = (com.mask_missing(self.values, tslib.iNaT) |
-                    com.mask_missing(other.values, tslib.iNaT))
+            mask = (missing.mask_missing(self.values, tslib.iNaT) |
+                    missing.mask_missing(other.values, tslib.iNaT))
             if mask.any():
                 result[mask] = nat_result