Fixed STYLE #49656: concat.py and merge.py

pandas/core/internals/concat.py

@@ -69,7 +69,7 @@
 
 
 def _concatenate_array_managers(
-    mgrs_indexers, axes: list[Index], concat_axis: AxisInt, copy: bool
+    mgrs_indexers, axes: list[Index], concat_axis: AxisInt, is_copied: bool
 ) -> Manager:
     """
     Concatenate array managers into one.
@@ -95,7 +95,7 @@ def _concatenate_array_managers(
             )
             if ax == 1 and indexer is not None:
                 axis1_made_copy = True
-        if copy and concat_axis == 0 and not axis1_made_copy:
+        if is_copied and concat_axis == 0 and not axis1_made_copy:
             # for concat_axis 1 we will always get a copy through concat_arrays
             mgr = mgr.copy()
         mgrs.append(mgr)
@@ -151,7 +151,7 @@ def concat_arrays(to_concat: list) -> ArrayLike:
     to_concat = [
         arr.to_array(target_dtype)
         if isinstance(arr, NullArrayProxy)
-        else astype_array(arr, target_dtype, copy=False)
+        else astype_array(arr, target_dtype, is_copied=False)
         for arr in to_concat
     ]
 
@@ -173,7 +173,7 @@ def concat_arrays(to_concat: list) -> ArrayLike:
 
 
 def concatenate_managers(
-    mgrs_indexers, axes: list[Index], concat_axis: AxisInt, copy: bool
+    mgrs_indexers, axes: list[Index], concat_axis: AxisInt, is_copied: bool
 ) -> Manager:
     """
     Concatenate block managers into one.
@@ -191,7 +191,7 @@ def concatenate_managers(
     """
     # TODO(ArrayManager) this assumes that all managers are of the same type
     if isinstance(mgrs_indexers[0][0], ArrayManager):
-        return _concatenate_array_managers(mgrs_indexers, axes, concat_axis, copy)
+        return _concatenate_array_managers(mgrs_indexers, axes, concat_axis, is_copied)
 
     mgrs_indexers = _maybe_reindex_columns_na_proxy(axes, mgrs_indexers)
 
@@ -207,7 +207,7 @@ def concatenate_managers(
 
         if len(join_units) == 1 and not join_units[0].indexers:
             values = blk.values
-            if copy:
+            if is_copied:
                 values = values.copy()
             else:
                 values = values.view()
@@ -229,7 +229,7 @@ def concatenate_managers(
 
             fastpath = blk.values.dtype == values.dtype
         else:
-            values = _concatenate_join_units(join_units, concat_axis, copy=copy)
+            values = _concatenate_join_units(join_units, concat_axis, is_copied=is_copied)
             fastpath = False
 
         if fastpath:
@@ -260,7 +260,7 @@ def _maybe_reindex_columns_na_proxy(
                 axes[0],
                 indexers[0],
                 axis=0,
-                copy=False,
+                is_copied=False,
                 only_slice=True,
                 allow_dups=True,
                 use_na_proxy=True,
@@ -524,7 +524,7 @@ def get_reindexed_values(self, empty_dtype: DtypeObj, upcasted_na) -> ArrayLike:
 
 
 def _concatenate_join_units(
-    join_units: list[JoinUnit], concat_axis: AxisInt, copy: bool
+    join_units: list[JoinUnit], concat_axis: AxisInt, is_copied: bool
 ) -> ArrayLike:
     """
     Concatenate values from several join units along selected axis.
@@ -546,7 +546,7 @@ def _concatenate_join_units(
     if len(to_concat) == 1:
         # Only one block, nothing to concatenate.
         concat_values = to_concat[0]
-        if copy:
+        if is_copied:
             if isinstance(concat_values, np.ndarray):
                 # non-reindexed (=not yet copied) arrays are made into a view
                 # in JoinUnit.get_reindexed_values

pandas/core/reshape/merge.py

@@ -106,7 +106,7 @@ def merge(
     right_index: bool = False,
     sort: bool = False,
     suffixes: Suffixes = ("_x", "_y"),
-    copy: bool = True,
+    is_copied: bool = True,
     indicator: str | bool = False,
     validate: str | None = None,
 ) -> DataFrame:
@@ -124,7 +124,7 @@ def merge(
         indicator=indicator,
         validate=validate,
     )
-    return op.get_result(copy=copy)
+    return op.get_result(is_copied=is_copied)
 
 
 if __debug__:
@@ -183,7 +183,7 @@ def _groupby_and_merge(by, left: DataFrame, right: DataFrame, merge_pieces):
     from pandas.core.reshape.concat import concat
 
     result = concat(pieces, ignore_index=True)
-    result = result.reindex(columns=pieces[0].columns, copy=False)
+    result = result.reindex(columns=pieces[0].columns, is_copied=False)
     return result, lby
 
 
@@ -624,7 +624,7 @@ class _MergeOperation:
     bm_axis: AxisInt
     sort: bool
     suffixes: Suffixes
-    copy: bool
+    is_copied: bool
     indicator: str | bool
     validate: str | None
     join_names: list[Hashable]
@@ -721,7 +721,7 @@ def _reindex_and_concat(
         join_index: Index,
         left_indexer: npt.NDArray[np.intp] | None,
         right_indexer: npt.NDArray[np.intp] | None,
-        copy: bool,
+        is_copied: bool,
     ) -> DataFrame:
         """
         reindex along index and concat along columns.
@@ -742,7 +742,7 @@ def _reindex_and_concat(
                 join_index,
                 left_indexer,
                 axis=1,
-                copy=False,
+                is_copied=False,
                 only_slice=True,
                 allow_dups=True,
                 use_na_proxy=True,
@@ -755,7 +755,7 @@ def _reindex_and_concat(
                 join_index,
                 right_indexer,
                 axis=1,
-                copy=False,
+                is_copied=False,
                 only_slice=True,
                 allow_dups=True,
                 use_na_proxy=True,
@@ -767,17 +767,17 @@ def _reindex_and_concat(
 
         left.columns = llabels
         right.columns = rlabels
-        result = concat([left, right], axis=1, copy=copy)
+        result = concat([left, right], axis=1, is_copied=is_copied)
         return result
 
-    def get_result(self, copy: bool = True) -> DataFrame:
+    def get_result(self, is_copied: bool = True) -> DataFrame:
         if self.indicator:
             self.left, self.right = self._indicator_pre_merge(self.left, self.right)
 
         join_index, left_indexer, right_indexer = self._get_join_info()
 
         result = self._reindex_and_concat(
-            join_index, left_indexer, right_indexer, copy=copy
+            join_index, left_indexer, right_indexer, is_copied=is_copied
         )
         result = result.__finalize__(self, method=self._merge_type)
 
@@ -1776,7 +1776,7 @@ def __init__(
             sort=True,  # factorize sorts
         )
 
-    def get_result(self, copy: bool = True) -> DataFrame:
+    def get_result(self, is_copied: bool = True) -> DataFrame:
         join_index, left_indexer, right_indexer = self._get_join_info()
 
         llabels, rlabels = _items_overlap_with_suffix(
@@ -1799,7 +1799,7 @@ def get_result(self, copy: bool = True) -> DataFrame:
             right_join_indexer = right_indexer
 
         result = self._reindex_and_concat(
-            join_index, left_join_indexer, right_join_indexer, copy=copy
+            join_index, left_join_indexer, right_join_indexer, is_copied=is_copied
         )
         self._maybe_add_join_keys(result, left_indexer, right_indexer)
 
@@ -1845,7 +1845,7 @@ def __init__(
         right_by=None,
         axis: AxisInt = 1,
         suffixes: Suffixes = ("_x", "_y"),
-        copy: bool = True,
+        is_copied: bool = True,
         fill_method: str | None = None,
         how: str = "asof",
         tolerance=None,
@@ -2156,7 +2156,7 @@ def _get_multiindex_indexer(
     if sort:
         rcodes = list(map(np.take, rcodes, index.codes))
     else:
-        i8copy = lambda a: a.astype("i8", subok=False, copy=True)
+        i8copy = lambda a: a.astype("i8", subok=False, is_copied=True)
         rcodes = list(map(i8copy, index.codes))
 
     # fix right labels if there were any nulls
@@ -2420,8 +2420,8 @@ def _get_join_keys(
 
     # get keys for the first `nlev` levels
     stride = np.prod(shape[1:nlev], dtype="i8")
-    lkey = stride * llab[0].astype("i8", subok=False, copy=False)
-    rkey = stride * rlab[0].astype("i8", subok=False, copy=False)
+    lkey = stride * llab[0].astype("i8", subok=False, is_copied=False)
+    rkey = stride * rlab[0].astype("i8", subok=False, is_copied=False)
 
     for i in range(1, nlev):
         with np.errstate(divide="ignore"):