make much simpler

Author: jreback

pandas/core/common.py

@@ -455,43 +455,7 @@ def _apply_if_callable(maybe_callable, obj, axis=None, **kwargs):
     """
 
     if callable(maybe_callable):
-
-        # we are allowing a user callable, which can return
-        # a result based on the object itself, e.g. a scalar / list
-        # of labels, or a boolean result from evaluating the labels
-        # on the specified axis
-
-        def try_on_axis():
-            labels = obj._get_axis(axis or 0)
-            return labels.map(maybe_callable, **kwargs).values
-
-        # act on object
-        try:
-            result = maybe_callable(obj, **kwargs)
-
-            # if we have asked for a specific axis
-            # then we must be 1d
-            if axis is not None:
-                if getattr(result, 'ndim', 1) != 1:
-                    raise ValueError
-
-            return result
-        except KeyError as e:
-            # this is potentially a legitimate error
-            # if we cannot work on the labels
-            # we want to preserve the original KeyError
-            try:
-                return try_on_axis()
-            except:  # no pragma
-                raise e
-        except:  # no pragma
-            pass
-
-        # act on the axis
-        try:
-            return try_on_axis()
-        except AttributeError:
-            pass
+        return maybe_callable(obj, **kwargs)
 
     return maybe_callable
 

pandas/core/generic.py

@@ -2339,7 +2339,7 @@ def select(self, crit, axis=0):
         """
         Return data corresponding to axis labels matching criteria
 
-        DEPRECATED: use .loc(axis=)[crit] to select via labels
+        DEPRECATED: use df.loc[labels.map(crit).values] to select via labels
 
         Parameters
         ----------
@@ -2353,7 +2353,7 @@ def select(self, crit, axis=0):
         """
         warnings.warn("select is deprecated and will be removed in a "
                       "future release. You can use "
-                      ".loc[crit] as a replacement",
+                      ".loc[labels.map(crit).values] as a replacement",
                       FutureWarning, stacklevel=2)
 
         axis = self._get_axis_number(axis)

pandas/tests/frame/test_alter_axes.py

@@ -146,11 +146,7 @@ def test_set_index_bug(self):
         xp = DataFrame({'val': [1, 2]},
                        Index(['b', 'c'], name='key'))
 
-        df2 = df.loc(axis=0)[lambda indx: indx >= 1]
-        rs = df2.set_index('key')
-        assert_frame_equal(rs, xp)
-
-        df2 = df.loc[lambda indx: indx >= 1]
+        df2 = df.loc[df.index.map(lambda indx: indx >= 1).values]
         rs = df2.set_index('key')
         assert_frame_equal(rs, xp)
 

pandas/tests/frame/test_axis_select_reindex.py

@@ -812,27 +812,23 @@ def test_select(self):
             assert_frame_equal(result, expected, check_names=False)
 
         # replacement
-        result = self.tsframe.loc(axis=0)[f]
+        f = lambda x: x.weekday == 2
+        result = self.tsframe.loc(axis=0)[f(self.tsframe.index)]
         assert_frame_equal(result, expected_weekdays)
 
-        result = self.tsframe.loc[f]
-        assert_frame_equal(result, expected_weekdays)
-
-        result = self.frame.loc(axis=1)[lambda x: x in ('B', 'D')]
+        crit = lambda x: x in ['B', 'D']
+        result = self.frame.loc(axis=1)[(self.frame.columns.map(crit)).values]
         expected = self.frame.reindex(columns=['B', 'D'])
         assert_frame_equal(result, expected, check_names=False)
 
         # doc example
         df = DataFrame({'A': [1, 2, 3]}, index=['foo', 'bar', 'baz'])
 
+        crit = lambda x: x in ['bar', 'baz']
         with tm.assert_produces_warning(FutureWarning,
                                         check_stacklevel=False):
-
-            expected = df.select(lambda x: x in ['bar', 'baz'])
-        result = df.loc[lambda x: x in ['bar', 'baz']]
-        assert_frame_equal(result, expected, check_names=False)
-
-        result = df.loc(axis=0)[lambda x: x in ['bar', 'baz']]
+            expected = df.select(crit)
+        result = df.loc[df.index.map(crit).values]
         assert_frame_equal(result, expected, check_names=False)
 
     def test_take(self):

pandas/tests/groupby/test_groupby.py

@@ -3103,7 +3103,8 @@ def agg_before(hour, func, fix=False):
             """
 
             def _func(data):
-                d = data.loc(axis=0)[lambda x: x.hour < 11].dropna()
+                d = data.loc[data.index.map(
+                    lambda x: x.hour < 11).values].dropna()
                 if fix:
                     data[data.index[0]]
                 if len(d) == 0:

pandas/tests/test_multilevel.py

@@ -1239,7 +1239,8 @@ def test_groupby_level_no_obs(self):
             'f2', 's1'), ('f2', 's2'), ('f3', 's1'), ('f3', 's2')])
         df = DataFrame(
             [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], columns=midx)
-        df1 = df.loc(axis=1)[lambda u: u[0] in ['f2', 'f3']]
+        df1 = df.loc(axis=1)[df.columns.map(
+            lambda u: u[0] in ['f2', 'f3']).values]
 
         grouped = df1.groupby(axis=1, level=0)
         result = grouped.sum()