CLN: removed unused "convert" parameter to _take

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 = {}