DEPR: Deprecate convert parameter in take

xref pandas-devgh-16948. The parameter is not respected.

doc/source/whatsnew/v0.21.0.txt

@@ -300,7 +300,7 @@ Other API Changes
 Deprecations
 ~~~~~~~~~~~~
 - :func:`read_excel()` has deprecated ``sheetname`` in favor of ``sheet_name`` for consistency with ``.to_excel()`` (:issue:`10559`).
-
+- The ``convert`` parameter has been deprecated in the ``.take()`` method, as it was not being respected (:issue:`16948`)
 - ``pd.options.html.border`` has been deprecated in favor of ``pd.options.display.html.border`` (:issue:`15793`).
 
 .. _whatsnew_0210.prior_deprecations:

pandas/core/frame.py

@@ -2033,7 +2033,7 @@ def _ixs(self, i, axis=0):
                 return self.loc[:, lab_slice]
             else:
                 if isinstance(label, Index):
-                    return self.take(i, axis=1, convert=True)
+                    return self.take(i, axis=1)
 
                 index_len = len(self.index)
 
@@ -2115,10 +2115,10 @@ def _getitem_array(self, key):
             # be reindexed to match DataFrame rows
             key = check_bool_indexer(self.index, key)
             indexer = key.nonzero()[0]
-            return self.take(indexer, axis=0, convert=False)
+            return self.take(indexer, axis=0)
         else:
             indexer = self.loc._convert_to_indexer(key, axis=1)
-            return self.take(indexer, axis=1, convert=True)
+            return self.take(indexer, axis=1)
 
     def _getitem_multilevel(self, key):
         loc = self.columns.get_loc(key)
@@ -3354,7 +3354,7 @@ def dropna(self, axis=0, how='any', thresh=None, subset=None,
                 else:
                     raise TypeError('must specify how or thresh')
 
-            result = self.take(mask.nonzero()[0], axis=axis, convert=False)
+            result = self.take(mask.nonzero()[0], axis=axis)
 
         if inplace:
             self._update_inplace(result)
@@ -3490,7 +3490,7 @@ def trans(v):
 
         new_data = self._data.take(indexer,
                                    axis=self._get_block_manager_axis(axis),
-                                   convert=False, verify=False)
+                                   verify=False)
 
         if inplace:
             return self._update_inplace(new_data)
@@ -3551,7 +3551,7 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
         baxis = self._get_block_manager_axis(axis)
         new_data = self._data.take(indexer,
                                    axis=baxis,
-                                   convert=False, verify=False)
+                                   verify=False)
 
         # reconstruct axis if needed
         new_data.axes[baxis] = new_data.axes[baxis]._sort_levels_monotonic()

pandas/core/generic.py

@@ -1819,7 +1819,7 @@ def _iget_item_cache(self, item):
         if ax.is_unique:
             lower = self._get_item_cache(ax[item])
         else:
-            lower = self.take(item, axis=self._info_axis_number, convert=True)
+            lower = self.take(item, axis=self._info_axis_number)
         return lower
 
     def _box_item_values(self, key, values):
@@ -2074,9 +2074,9 @@ def take(self, indices, axis=0, convert=True, is_copy=True, **kwargs):
             The axis on which to select elements. "0" means that we are
             selecting rows, "1" means that we are selecting columns, etc.
         convert : bool, default True
-            Whether to convert negative indices to positive ones, just as with
-            indexing into Python lists. For example, if `-1` was passed in,
-            this index would be converted ``n - 1``.
+            .. deprecated:: 0.21.0
+
+            This parameter is not respected by the function.
         is_copy : bool, default True
             Whether to return a copy of the original object or not.
 
@@ -2134,9 +2134,15 @@ class  max_speed
         """
         nv.validate_take(tuple(), kwargs)
         self._consolidate_inplace()
+
+        if not convert:
+            msg = ("The 'convert' parameter is deprecated "
+                   "and will be removed in a future version.")
+            warnings.warn(msg, FutureWarning, stacklevel=2)
+
         new_data = self._data.take(indices,
                                    axis=self._get_block_manager_axis(axis),
-                                   convert=True, verify=True)
+                                   verify=True)
         result = self._constructor(new_data).__finalize__(self)
 
         # maybe set copy if we didn't actually change the index
@@ -2245,9 +2251,9 @@ def xs(self, key, axis=0, level=None, drop_level=True):
             if isinstance(loc, np.ndarray):
                 if loc.dtype == np.bool_:
                     inds, = loc.nonzero()
-                    return self.take(inds, axis=axis, convert=False)
+                    return self.take(inds, axis=axis)
                 else:
-                    return self.take(loc, axis=axis, convert=True)
+                    return self.take(loc, axis=axis)
 
             if not is_scalar(loc):
                 new_index = self.index[loc]
@@ -5066,7 +5072,7 @@ def at_time(self, time, asof=False):
         """
         try:
             indexer = self.index.indexer_at_time(time, asof=asof)
-            return self.take(indexer, convert=False)
+            return self.take(indexer)
         except AttributeError:
             raise TypeError('Index must be DatetimeIndex')
 
@@ -5090,7 +5096,7 @@ def between_time(self, start_time, end_time, include_start=True,
             indexer = self.index.indexer_between_time(
                 start_time, end_time, include_start=include_start,
                 include_end=include_end)
-            return self.take(indexer, convert=False)
+            return self.take(indexer)
         except AttributeError:
             raise TypeError('Index must be DatetimeIndex')
 

pandas/core/groupby.py

@@ -317,7 +317,7 @@ def _set_grouper(self, obj, sort=False):
             indexer = self.indexer = ax.argsort(kind='mergesort')
             ax = ax.take(indexer)
             obj = obj.take(indexer, axis=self.axis,
-                           convert=False, is_copy=False)
+                           is_copy=False)
 
         self.obj = obj
         self.grouper = ax
@@ -640,7 +640,7 @@ def get_group(self, name, obj=None):
         if not len(inds):
             raise KeyError(name)
 
-        return obj.take(inds, axis=self.axis, convert=False)
+        return obj.take(inds, axis=self.axis)
 
     def __iter__(self):
         """
@@ -2190,7 +2190,7 @@ def _aggregate_series_fast(self, obj, func):
         # avoids object / Series creation overhead
         dummy = obj._get_values(slice(None, 0)).to_dense()
         indexer = get_group_index_sorter(group_index, ngroups)
-        obj = obj.take(indexer, convert=False).to_dense()
+        obj = obj.take(indexer).to_dense()
         group_index = algorithms.take_nd(
             group_index, indexer, allow_fill=False)
         grouper = lib.SeriesGrouper(obj, func, group_index, ngroups,
@@ -4419,7 +4419,7 @@ def __iter__(self):
             yield i, self._chop(sdata, slice(start, end))
 
     def _get_sorted_data(self):
-        return self.data.take(self.sort_idx, axis=self.axis, convert=False)
+        return self.data.take(self.sort_idx, axis=self.axis)
 
     def _chop(self, sdata, slice_obj):
         return sdata.iloc[slice_obj]

pandas/core/indexing.py

@@ -1092,7 +1092,7 @@ def _getitem_iterable(self, key, axis=0):
         if is_bool_indexer(key):
             key = check_bool_indexer(labels, key)
             inds, = key.nonzero()
-            return self.obj.take(inds, axis=axis, convert=False)
+            return self.obj.take(inds, axis=axis)
         else:
             # Have the index compute an indexer or return None
             # if it cannot handle; we only act on all found values
@@ -1125,15 +1125,14 @@ def _getitem_iterable(self, key, axis=0):
                     keyarr)
 
                 if new_indexer is not None:
-                    result = self.obj.take(indexer[indexer != -1], axis=axis,
-                                           convert=False)
+                    result = self.obj.take(indexer[indexer != -1], axis=axis)
 
                     result = result._reindex_with_indexers(
                         {axis: [new_target, new_indexer]},
                         copy=True, allow_dups=True)
 
                 else:
-                    result = self.obj.take(indexer, axis=axis, convert=False)
+                    result = self.obj.take(indexer, axis=axis)
 
                 return result
 
@@ -1263,7 +1262,7 @@ def _get_slice_axis(self, slice_obj, axis=0):
         if isinstance(indexer, slice):
             return self._slice(indexer, axis=axis, kind='iloc')
         else:
-            return self.obj.take(indexer, axis=axis, convert=False)
+            return self.obj.take(indexer, axis=axis)
 
 
 class _IXIndexer(_NDFrameIndexer):
@@ -1348,7 +1347,7 @@ def _getbool_axis(self, key, axis=0):
         key = check_bool_indexer(labels, key)
         inds, = key.nonzero()
         try:
-            return self.obj.take(inds, axis=axis, convert=False)
+            return self.obj.take(inds, axis=axis)
         except Exception as detail:
             raise self._exception(detail)
 
@@ -1365,7 +1364,7 @@ def _get_slice_axis(self, slice_obj, axis=0):
         if isinstance(indexer, slice):
             return self._slice(indexer, axis=axis, kind='iloc')
         else:
-            return self.obj.take(indexer, axis=axis, convert=False)
+            return self.obj.take(indexer, axis=axis)
 
 
 class _LocIndexer(_LocationIndexer):
@@ -1703,7 +1702,7 @@ def _get_slice_axis(self, slice_obj, axis=0):
         if isinstance(slice_obj, slice):
             return self._slice(slice_obj, axis=axis, kind='iloc')
         else:
-            return self.obj.take(slice_obj, axis=axis, convert=False)
+            return self.obj.take(slice_obj, axis=axis)
 
     def _get_list_axis(self, key, axis=0):
         """
@@ -1719,7 +1718,7 @@ def _get_list_axis(self, key, axis=0):
         Series object
         """
         try:
-            return self.obj.take(key, axis=axis, convert=False)
+            return self.obj.take(key, axis=axis)
         except IndexError:
             # re-raise with different error message
             raise IndexError("positional indexers are out-of-bounds")

pandas/core/series.py

@@ -2561,27 +2561,45 @@ def memory_usage(self, index=True, deep=False):
 
     def take(self, indices, axis=0, convert=True, is_copy=False, **kwargs):
         """
-        return Series corresponding to requested indices
+        Return a Series corresponding to requested indices.
 
         Parameters
         ----------
-        indices : list / array of ints
-        convert : translate negative to positive indices (default)
+        indices : array-like
+            An array of ints indicating which positions to take.
+        axis : int, default 0
+            The axis on which to select elements. This implementation
+            ignores this parameter because there is only one axis.
+        convert : bool, default True
+            .. deprecated:: 0.21.0
+
+            Whether to translate negative to positive indices. In the future,
+            this function will always translate negative to positive indices.
+
+        is_copy : bool, default True
+            Whether to return a copy of the original object or not.
 
         Returns
         -------
         taken : Series
+            An array-like containing the elements taken from the object.
 
-        See also
+        See Also
         --------
         numpy.ndarray.take
+        numpy.take
         """
+
         if kwargs:
             nv.validate_take(tuple(), kwargs)
 
-        # check/convert indicies here
+        # Check / convert indices here.
         if convert:
             indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
+        else:
+            msg = ("The 'convert' parameter is deprecated "
+                   "and will be removed in a future version.")
+            warnings.warn(msg, FutureWarning, stacklevel=2)
 
         indices = _ensure_platform_int(indices)
         new_index = self.index.take(indices)

pandas/core/sparse/series.py

@@ -604,14 +604,38 @@ def sparse_reindex(self, new_index):
 
     def take(self, indices, axis=0, convert=True, *args, **kwargs):
         """
-        Sparse-compatible version of ndarray.take
+        Sparse-compatible version of ndarray.take.
+
+        Parameters
+        ----------
+        indices : array-like
+            An array of ints indicating which positions to take.
+        axis : int, default 0
+            The axis on which to select elements. This implementation
+            ignores this parameter because there is only one axis.
+        convert : bool, default True
+            .. deprecated:: 0.21.0
+
+            This parameter is not respected by the function.
 
         Returns
         -------
-        taken : ndarray
+        taken : numpy.ndarray
+            An array-like containing the elements taken from the object.
+
+        See Also
+        --------
+        numpy.ndarray.take
+        numpy.take
         """
 
         convert = nv.validate_take_with_convert(convert, args, kwargs)
+
+        if not convert:
+            msg = ("The 'convert' parameter is deprecated "
+                   "and will be removed in a future version.")
+            warnings.warn(msg, FutureWarning, stacklevel=2)
+
         new_values = SparseArray.take(self.values, indices)
         new_index = self.index.take(indices)
         return self._constructor(new_values,

pandas/tests/frame/test_axis_select_reindex.py

@@ -787,14 +787,18 @@ def test_take(self):
             expected = df.loc[:, ['D', 'B', 'C', 'A']]
             assert_frame_equal(result, expected, check_names=False)
 
-        # neg indicies
+        # negative indices
         order = [2, 1, -1]
         for df in [self.frame]:
 
             result = df.take(order, axis=0)
             expected = df.reindex(df.index.take(order))
             assert_frame_equal(result, expected)
 
+            with tm.assert_produces_warning(FutureWarning):
+                result = df.take(order, convert=False, axis=0)
+                assert_frame_equal(result, expected)
+
             # axis = 1
             result = df.take(order, axis=1)
             expected = df.loc[:, ['C', 'B', 'D']]
@@ -819,7 +823,7 @@ def test_take(self):
             expected = df.loc[:, ['foo', 'B', 'C', 'A', 'D']]
             assert_frame_equal(result, expected)
 
-        # neg indicies
+        # negative indices
         order = [4, 1, -2]
         for df in [self.mixed_frame]:
 

pandas/tests/series/test_indexing.py

@@ -1066,6 +1066,23 @@ def test_setitem_with_tz_dst(self):
         s.iloc[[1, 2]] = vals
         tm.assert_series_equal(s, exp)
 
+    def test_take(self):
+        s = Series([-1, 5, 6, 2, 4])
+
+        actual = s.take([1, 3, 4])
+        expected = Series([5, 2, 4], index=[1, 3, 4])
+        tm.assert_series_equal(actual, expected)
+
+        actual = s.take([-1, 3, 4])
+        expected = Series([4, 2, 4], index=[4, 3, 4])
+        tm.assert_series_equal(actual, expected)
+
+        pytest.raises(IndexError, s.take, [1, 10])
+        pytest.raises(IndexError, s.take, [2, 5])
+
+        with tm.assert_produces_warning(FutureWarning):
+            s.take([-1, 3, 4], convert=False)
+
     def test_where(self):
         s = Series(np.random.randn(5))
         cond = s > 0

pandas/tests/sparse/test_series.py

@@ -520,6 +520,9 @@ def _compare(idx):
         exp = pd.Series(np.repeat(nan, 5))
         tm.assert_series_equal(sp.take([0, 1, 2, 3, 4]), exp)
 
+        with tm.assert_produces_warning(FutureWarning):
+            sp.take([1, 5], convert=False)
+
     def test_numpy_take(self):
         sp = SparseSeries([1.0, 2.0, 3.0])
         indices = [1, 2]