Fix

Signed-off-by: Iaroslav Igoshev <iaroslav.igoshev@intel.com>

modin/core/dataframe/pandas/dataframe/dataframe.py

@@ -3436,10 +3436,12 @@ def broadcast_apply_full_axis(
                         )
                     )
 
+        is_index_materialized = ModinIndex.is_materialized_index(new_index)
+        is_columns_materialized = ModinIndex.is_materialized_index(new_columns)
+        is_one_row_shaped = new_partitions.shape[0] == 1
+        is_one_column_shaped = new_partitions.shape[1] == 1
         if not keep_partitioning:
-            if kw["row_lengths"] is None and ModinIndex.is_materialized_index(
-                new_index
-            ):
+            if kw["row_lengths"] is None and is_index_materialized:
                 if axis == 0:
                     kw["row_lengths"] = get_length_list(
                         axis_len=len(new_index), num_splits=new_partitions.shape[0]
@@ -3449,11 +3451,9 @@ def broadcast_apply_full_axis(
                         self._row_lengths_cache
                     ):
                         kw["row_lengths"] = self._row_lengths_cache
-                    elif len(new_index) == 1 and new_partitions.shape[0] == 1:
-                        kw["row_lengths"] = [1]
-            if kw["column_widths"] is None and ModinIndex.is_materialized_index(
-                new_columns
-            ):
+                    elif is_one_row_shaped:
+                        kw["row_lengths"] = [len(new_index)]
+            if kw["column_widths"] is None and is_columns_materialized:
                 if axis == 1:
                     kw["column_widths"] = get_length_list(
                         axis_len=len(new_columns),
@@ -3464,29 +3464,33 @@ def broadcast_apply_full_axis(
                         new_columns
                     ) == sum(self._column_widths_cache):
                         kw["column_widths"] = self._column_widths_cache
-                    elif len(new_columns) == 1 and new_partitions.shape[1] == 1:
-                        kw["column_widths"] = [1]
+                    elif is_one_column_shaped:
+                        kw["column_widths"] = [len(new_columns)]
         else:
             if (
                 axis == 0
                 and kw["row_lengths"] is None
                 and self._row_lengths_cache is not None
-                and ModinIndex.is_materialized_index(new_index)
+                and is_index_materialized
                 and len(new_index) == sum(self._row_lengths_cache)
                 # to avoid problems that may arise when filtering empty dataframes
                 and all(r != 0 for r in self._row_lengths_cache)
             ):
                 kw["row_lengths"] = self._row_lengths_cache
+                if is_columns_materialized and is_one_column_shaped:
+                    kw["column_widths"] = [len(new_columns)]
             if (
                 axis == 1
                 and kw["column_widths"] is None
                 and self._column_widths_cache is not None
-                and ModinIndex.is_materialized_index(new_columns)
+                and is_columns_materialized
                 and len(new_columns) == sum(self._column_widths_cache)
                 # to avoid problems that may arise when filtering empty dataframes
                 and all(w != 0 for w in self._column_widths_cache)
             ):
                 kw["column_widths"] = self._column_widths_cache
+                if is_index_materialized and is_one_row_shaped:
+                    kw["row_lengths"] = [len(new_index)]
 
         result = self.__constructor__(
             new_partitions, index=new_index, columns=new_columns, **kw