REFACTOR-#6293: Corrected 'missmatch' to 'mismatch' in ErrorMessage.m…

…issmatch_with_pandas method (#6901)

Signed-off-by: Vedant <2711vedant@gmail.com>

modin/core/dataframe/algebra/groupby.py

@@ -379,7 +379,7 @@ def caller(
         if not groupby_kwargs.get("sort", True) and isinstance(
             by, type(query_compiler)
         ):
-            ErrorMessage.missmatch_with_pandas(
+            ErrorMessage.mismatch_with_pandas(
                 operation="df.groupby(categorical_by, sort=False)",
                 message=(
                     "the groupby keys will be sorted anyway, although the 'sort=False' was passed. "

modin/core/storage_formats/pandas/parsers.py

@@ -254,7 +254,7 @@ def get_dtypes(cls, dtypes_ids, columns):
         frame_dtypes.name = None
 
         if not combined_part_dtypes.eq(frame_dtypes, axis=0).all(axis=None):
-            ErrorMessage.missmatch_with_pandas(
+            ErrorMessage.mismatch_with_pandas(
                 operation="read_*",
                 message="Data types of partitions are different! "
                 + "Please refer to the troubleshooting section of the Modin documentation "

modin/core/storage_formats/pandas/query_compiler.py

@@ -2706,7 +2706,7 @@ def melt(
         col_level=None,
         ignore_index=True,
     ):
-        ErrorMessage.missmatch_with_pandas(
+        ErrorMessage.mismatch_with_pandas(
             operation="melt", message="Order of rows could be different from pandas"
         )
 
@@ -3785,7 +3785,7 @@ def _groupby_shuffle(
 
         if is_transform:
             # https://github.com/modin-project/modin/issues/5924
-            ErrorMessage.missmatch_with_pandas(
+            ErrorMessage.mismatch_with_pandas(
                 operation="range-partitioning groupby",
                 message="the order of rows may be shuffled for the result",
             )
@@ -4344,7 +4344,7 @@ def pivot_table(
         observed,
         sort,
     ):
-        ErrorMessage.missmatch_with_pandas(
+        ErrorMessage.mismatch_with_pandas(
             operation="pivot_table",
             message="Order of columns could be different from pandas",
         )

modin/error_message.py

@@ -101,7 +101,7 @@ def bad_type_for_numpy_op(cls, function_name: str, operand_type: type) -> None:
         )
 
     @classmethod
-    def missmatch_with_pandas(cls, operation: str, message: str) -> None:
+    def mismatch_with_pandas(cls, operation: str, message: str) -> None:
         get_logger().debug(
             f"Modin Warning: {operation} mismatch with pandas: {message}"
         )

modin/pandas/groupby.py

@@ -778,7 +778,7 @@ def __getitem__(self, key):
         if make_dataframe:
             internal_by = frozenset(self._internal_by)
             if len(internal_by.intersection(key)) != 0:
-                ErrorMessage.missmatch_with_pandas(
+                ErrorMessage.mismatch_with_pandas(
                     operation="GroupBy.__getitem__",
                     message=(
                         "intersection of the selection and 'by' columns is not yet supported, "
@@ -933,7 +933,7 @@ def do_relabel(obj_to_relabel):  # noqa: F811
                 and not self._as_index
                 and any(col in func_dict for col in self._internal_by)
             ):
-                ErrorMessage.missmatch_with_pandas(
+                ErrorMessage.mismatch_with_pandas(
                     operation="GroupBy.aggregate(**dictionary_renaming_aggregation)",
                     message=(
                         "intersection of the columns to aggregate and 'by' is not yet supported when 'as_index=False', "

modin/pandas/test/utils.py

@@ -951,7 +951,7 @@ def eval_io(
     comparator: obj
         Function to perform comparison.
     cast_to_str: bool
-        There could be some missmatches in dtypes, so we're
+        There could be some mismatches in dtypes, so we're
         casting the whole frame to `str` before comparison.
         See issue #1931 for details.
     check_exception_type: bool

modin/pandas/window.py

@@ -272,7 +272,7 @@ def __init__(self, groupby_obj, *args, **kwargs):
         super().__init__(self._groupby_obj._df, *args, **kwargs)
 
     def sem(self, *args, **kwargs):
-        ErrorMessage.missmatch_with_pandas(
+        ErrorMessage.mismatch_with_pandas(
             operation="RollingGroupby.sem() when 'as_index=False'",
             message=(
                 "The group columns won't be involved in the aggregation.\n"

modin/test/storage_formats/pandas/test_internals.py

@@ -772,7 +772,7 @@ def test_groupby_with_empty_partition():
     )
     md_res = md_df.query("a > 1", engine="python")
     grp_obj = md_res.groupby("a")
-    # check index error due to partitioning missmatching
+    # check index error due to partitioning mismatching
     grp_obj.count()
 
     md_df = construct_modin_df_by_scheme(