CLN: removed unused "convert" parameter to _take (pandas-dev#20934)

Author: toobaz

pandas/core/frame.py

@@ -2641,7 +2641,7 @@ 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)
 
@@ -2720,10 +2720,10 @@ 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)
@@ -4292,7 +4292,7 @@ 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)

pandas/core/generic.py

@@ -37,7 +37,6 @@
 from pandas.core.index import (Index, MultiIndex, _ensure_index,
  InvalidIndexError, RangeIndex)
 import pandas.core.indexing as indexing
-from pandas.core.indexing import maybe_convert_indices
 from pandas.core.indexes.datetimes import DatetimeIndex
 from pandas.core.indexes.period import PeriodIndex, Period
 from pandas.core.internals import BlockManager
@@ -2510,8 +2509,7 @@ 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):
@@ -2765,11 +2763,6 @@ def __delitem__(self, key):
  axis : int, default 0
  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 into positive ones.
- For example, ``-1`` would map to the ``len(axis) - 1``.
- The conversions are similar to the behavior of indexing a
- regular Python list.
  is_copy : bool, default True
  Whether to return a copy of the original object or not.
 
@@ -2785,12 +2778,9 @@ def __delitem__(self, key):
  """
 
  @Appender(_shared_docs['_take'])
- def _take(self, indices, axis=0, convert=True, is_copy=True):
+ def _take(self, indices, axis=0, is_copy=True):
  self._consolidate_inplace()
 
- if convert:
- indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
-
  new_data = self._data.take(indices,
  axis=self._get_block_manager_axis(axis),
  verify=True)
@@ -2893,11 +2883,9 @@ def take(self, indices, axis=0, convert=None, is_copy=True, **kwargs):
  msg = ("The 'convert' parameter is deprecated "
  "and will be removed in a future version.")
  warnings.warn(msg, FutureWarning, stacklevel=2)
- else:
- convert = True
 
- convert = nv.validate_take(tuple(), kwargs)
- return self._take(indices, axis=axis, convert=convert, is_copy=is_copy)
+ nv.validate_take(tuple(), kwargs)
+ return self._take(indices, axis=axis, is_copy=is_copy)
 
  def xs(self, key, axis=0, level=None, drop_level=True):
  """
@@ -2998,9 +2986,9 @@ 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]
@@ -6784,7 +6772,7 @@ 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')
 
@@ -6808,7 +6796,7 @@ 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/groupby.py

@@ -508,8 +508,7 @@ def _set_grouper(self, obj, sort=False):
  # use stable sort to support first, last, nth
  indexer = self.indexer = ax.argsort(kind='mergesort')
  ax = ax.take(indexer)
- obj = obj._take(indexer, axis=self.axis,
- convert=False, is_copy=False)
+ obj = obj._take(indexer, axis=self.axis, is_copy=False)
 
  self.obj = obj
  self.grouper = ax
@@ -860,7 +859,7 @@ 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):
  """
@@ -1437,9 +1436,9 @@ def last(x):
  cls.min = groupby_function('min', 'min', np.min, numeric_only=False)
  cls.max = groupby_function('max', 'max', np.max, numeric_only=False)
  cls.first = groupby_function('first', 'first', first_compat,
- numeric_only=False, _convert=True)
+ numeric_only=False)
  cls.last = groupby_function('last', 'last', last_compat,
- numeric_only=False, _convert=True)
+ numeric_only=False)
 
  @Substitution(name='groupby')
  @Appender(_doc_template)
@@ -2653,7 +2652,7 @@ 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 = reduction.SeriesGrouper(obj, func, group_index, ngroups,
@@ -5032,7 +5031,7 @@ 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

@@ -1126,7 +1126,7 @@ def _getitem_iterable(self, key, axis=None):
  if com.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
@@ -1158,8 +1158,7 @@ def _getitem_iterable(self, key, axis=None):
  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)
 
  self._validate_read_indexer(key, new_indexer, axis)
  result = result._reindex_with_indexers(
@@ -1356,7 +1355,7 @@ def _get_slice_axis(self, slice_obj, axis=None):
  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):
@@ -1494,7 +1493,7 @@ def _getbool_axis(self, key, axis=None):
  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)
 
@@ -1514,7 +1513,7 @@ def _get_slice_axis(self, slice_obj, axis=None):
  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):
@@ -2050,7 +2049,7 @@ def _get_slice_axis(self, slice_obj, axis=None):
  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=None):
  """
@@ -2068,7 +2067,7 @@ def _get_list_axis(self, key, axis=None):
  if axis is None:
  axis = self.axis or 0
  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

@@ -3503,16 +3503,15 @@ def memory_usage(self, index=True, deep=False):
  return v
 
  @Appender(generic._shared_docs['_take'])
- def _take(self, indices, axis=0, convert=True, is_copy=False):
- if convert:
- indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
+ def _take(self, indices, axis=0, is_copy=False):
 
  indices = _ensure_platform_int(indices)
  new_index = self.index.take(indices)
 
  if is_categorical_dtype(self):
  # https://github.com/pandas-dev/pandas/issues/20664
  # TODO: remove when the default Categorical.take behavior changes
+ indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
  kwargs = {'allow_fill': False}
  else:
  kwargs = {}