REF/PERF: Use concat(..., ignore_index=True) when index doesn't matter

pandas/core/arrays/categorical.py

@@ -2622,7 +2622,7 @@ def describe(self) -> DataFrame:
         from pandas import Index
         from pandas.core.reshape.concat import concat
 
-        result = concat([counts, freqs], axis=1)
+        result = concat([counts, freqs], ignore_index=True, axis=1)
         result.columns = Index(["counts", "freqs"])
         result.index.name = "categories"
 

pandas/core/groupby/generic.py

@@ -574,7 +574,7 @@ def _transform_general(
         if results:
             from pandas.core.reshape.concat import concat
 
-            concatenated = concat(results)
+            concatenated = concat(results, ignore_index=True)
             result = self._set_result_index_ordered(concatenated)
         else:
             result = self.obj._constructor(dtype=np.float64)
@@ -1803,7 +1803,9 @@ def _transform_general(self, func, engine, engine_kwargs, *args, **kwargs):
             applied.append(res)
 
         concat_index = obj.columns
-        concatenated = concat(applied, axis=0, verify_integrity=False)
+        concatenated = concat(
+            applied, axis=0, verify_integrity=False, ignore_index=True
+        )
         concatenated = concatenated.reindex(concat_index, axis=1)
         return self._set_result_index_ordered(concatenated)
 
@@ -2797,7 +2799,7 @@ def _wrap_transform_general_frame(
         # other dimension; this will preserve dtypes
         # GH14457
         if res.index.is_(obj.index):
-            res_frame = concat([res] * len(group.columns), axis=1)
+            res_frame = concat([res] * len(group.columns), axis=1, ignore_index=True)
             res_frame.columns = group.columns
             res_frame.index = group.index
         else:

pandas/core/methods/describe.py

@@ -175,6 +175,7 @@ def describe(self, percentiles: Sequence[float] | np.ndarray) -> DataFrame:
         d = concat(
             [x.reindex(col_names) for x in ldesc],
             axis=1,
+            ignore_index=True,
             sort=False,
         )
         d.columns = data.columns.copy()

pandas/core/reshape/melt.py

@@ -243,7 +243,7 @@ def melt(
         not isinstance(dt, np.dtype) and dt._supports_2d for dt in frame.dtypes
     ):
         mdata[value_name] = concat(
-            [frame.iloc[:, i] for i in range(frame.shape[1])]
+            [frame.iloc[:, i] for i in range(frame.shape[1])], ignore_index=True
         ).values
     else:
         mdata[value_name] = frame._values.ravel("F")

pandas/core/reshape/pivot.py

@@ -835,7 +835,7 @@ def _normalize(
 
         elif normalize == "index":
             index_margin = index_margin / index_margin.sum()
-            table = table._append(index_margin)
+            table = table._append(index_margin, ignore_index=True)
             table = table.fillna(0)
             table.index = table_index
 
@@ -844,7 +844,7 @@ def _normalize(
             index_margin = index_margin / index_margin.sum()
             index_margin.loc[margins_name] = 1
             table = concat([table, column_margin], axis=1)
-            table = table._append(index_margin)
+            table = table._append(index_margin, ignore_index=True)
 
             table = table.fillna(0)
             table.index = table_index

pandas/core/reshape/reshape.py

@@ -953,7 +953,7 @@ def stack_v3(frame: DataFrame, level: list[int]) -> Series | DataFrame:
 
     result: Series | DataFrame
     if len(buf) > 0 and not frame.empty:
-        result = concat(buf)
+        result = concat(buf, ignore_index=True)
         ratio = len(result) // len(frame)
     else:
         # input is empty