DEPR: Deprecate convert parameter in take

xref gh-16948. The parameter is not respected, nor is it a parameter in many 'take' implementations.

Author: gfyoung

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 +4419,10 @@ 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)
+ # NEED TO INVESTIGATE
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
+ return self.data.take(self.sort_idx, axis=self.axis, convert=False)
 
  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 +2561,46 @@ 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 False
+ Whether to return a copy of the original object or not. This
+ implementation ignores this parameter.
 
  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/indexing/test_loc.py

@@ -581,11 +581,11 @@ def gen_test(l, l2):
 
  def gen_expected(df, mask):
  l = len(mask)
- return pd.concat([df.take([0], convert=False),
+ return pd.concat([df.take([0]),
  DataFrame(np.ones((l, len(columns))),
  index=[0] * l,
  columns=columns),
- df.take(mask[1:], convert=False)])
+ df.take(mask[1:])])
 
  df = gen_test(900, 100)
  assert not df.index.is_unique

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