DEPR: deprecate .select() in favor of .loc(axis=)[]

closes #12401

Author: jreback

doc/source/whatsnew/v0.21.0.txt

@@ -339,6 +339,30 @@ These now coerce to ``object`` dtype.
 - Inconsistent behavior in ``.where()`` with datetimelikes which would raise rather than coerce to ``object`` (:issue:`16402`)
 - Bug in assignment against ``int64`` data with ``np.ndarray`` with ``float64`` dtype may keep ``int64`` dtype (:issue:`14001`)
 
+.. _whatsnew_0210.api_breaking.select:
+
+Select method is deprecated
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The :meth:`Series.select` and :meth:`DataFrame.select` methods are deprecated in favor of using ``.loc[]`` (:issue:`12401`)
+
+.. ipython:: python
+
+   df = DataFrame({'A': [1, 2, 3]}, index=['foo', 'bar', 'baz'])
+
+.. code_block:: ipython
+
+   In [3]: df.select(lambda x: x in ['bar', 'baz'])
+   FutureWarning: select is deprecated and will be removed in a future release. You can use .loc[crit] as a replacement
+   Out[3]:
+        A
+   bar  2
+   baz  3
+
+.. ipython:: python
+
+   df.loc[lambda x: x in ['bar', 'baz']]
+
 .. _whatsnew_0210.api.na_changes:
 
 NA naming Changes

pandas/core/common.py

@@ -441,13 +441,43 @@ def _get_callable_name(obj):
     return None
 
 
-def _apply_if_callable(maybe_callable, obj, **kwargs):
+def _apply_if_callable(maybe_callable, obj, axis=None, **kwargs):
     """
     Evaluate possibly callable input using obj and kwargs if it is callable,
     otherwise return as it is
+
+    Parameters
+    ----------
+    maybe_callable : possibly a callable
+    obj : NDFrame
+    axis : int, optional
+    **kwargs
     """
+
     if callable(maybe_callable):
-        return maybe_callable(obj, **kwargs)
+
+        # act on object
+        try:
+            result = maybe_callable(obj, **kwargs)
+            result = getattr(result, 'values', result)
+
+            # if we have asked for a specific axis
+            # then we cannot be more than 1d
+            if axis is not None:
+                if getattr(result, 'ndim', 0) > 1:
+                    raise ValueError
+
+            return result
+        except (AttributeError, ValueError, KeyError):
+            pass
+
+        # act on the axis
+        try:
+            labels = obj._get_axis(axis or 0)
+            return labels.map(maybe_callable, **kwargs).values
+        except AttributeError:
+            pass
+
     return maybe_callable
 
 

pandas/core/generic.py

@@ -2281,6 +2281,8 @@ def select(self, crit, axis=0):
         """
         Return data corresponding to axis labels matching criteria
 
+        DEPRECATED: use .loc(axis=)[crit] to select via labels
+
         Parameters
         ----------
         crit : function
@@ -2291,6 +2293,11 @@ def select(self, crit, axis=0):
         -------
         selection : type of caller
         """
+        warnings.warn("select is deprecated and will be removed in a "
+                      "future release. You can use "
+                      ".loc[crit] as a replacement",
+                      FutureWarning, stacklevel=2)
+
         axis = self._get_axis_number(axis)
         axis_name = self._get_axis_name(axis)
         axis_values = self._get_axis(axis)
@@ -3043,7 +3050,7 @@ def filter(self, items=None, like=None, regex=None, axis=None):
 
         See Also
         --------
-        pandas.DataFrame.select
+        pandas.DataFrame.loc
 
         Notes
         -----
@@ -3062,20 +3069,23 @@ def filter(self, items=None, like=None, regex=None, axis=None):
 
         if axis is None:
             axis = self._info_axis_name
-        axis_name = self._get_axis_name(axis)
-        axis_values = self._get_axis(axis_name)
+        labels = self._get_axis(axis)
 
         if items is not None:
-            return self.reindex(**{axis_name:
-                                   [r for r in items if r in axis_values]})
+            name = self._get_axis_name(axis)
+            return self.reindex(
+                **{name: [r for r in items if r in labels]})
         elif like:
-            matchf = lambda x: (like in x if isinstance(x, string_types) else
-                                like in str(x))
-            return self.select(matchf, axis=axis_name)
+            def f(x):
+                if not isinstance(x, string_types):
+                    x = str(x)
+                return like in x
+            values = labels.map(f)
+            return self.loc(axis=axis)[values.values]
         elif regex:
             matcher = re.compile(regex)
-            return self.select(lambda x: matcher.search(str(x)) is not None,
-                               axis=axis_name)
+            values = labels.map(lambda x: matcher.search(str(x)) is not None)
+            return self.loc(axis=axis)[values.values]
         else:
             raise TypeError('Must pass either `items`, `like`, or `regex`')
 
@@ -5698,7 +5708,7 @@ def _where(self, cond, other=np.nan, inplace=False, axis=None, level=None,
         inplace = validate_bool_kwarg(inplace, 'inplace')
 
         # align the cond to same shape as myself
-        cond = com._apply_if_callable(cond, self)
+        cond = com._apply_if_callable(cond, self, axis=axis)
         if isinstance(cond, NDFrame):
             cond, _ = cond.align(self, join='right', broadcast_axis=1)
         else:
@@ -5939,7 +5949,7 @@ def _where(self, cond, other=np.nan, inplace=False, axis=None, level=None,
     def where(self, cond, other=np.nan, inplace=False, axis=None, level=None,
               try_cast=False, raise_on_error=True):
 
-        other = com._apply_if_callable(other, self)
+        other = com._apply_if_callable(other, self, axis=axis)
         return self._where(cond, other, inplace, axis, level, try_cast,
                            raise_on_error)
 
@@ -5950,7 +5960,7 @@ def mask(self, cond, other=np.nan, inplace=False, axis=None, level=None,
              try_cast=False, raise_on_error=True):
 
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        cond = com._apply_if_callable(cond, self)
+        cond = com._apply_if_callable(cond, self, axis=axis)
 
         return self.where(~cond, other=other, inplace=inplace, axis=axis,
                           level=level, try_cast=try_cast,