internlm/SWE-Fixer-Train-110K huggingface dataset:
Repository: modin-project/modin

Issue:
Series with categorical dtype doesn't match pandas
```python
import modin.pandas as pd
import pandas

ps = pandas.Series(["a", "b", "c", "a"], dtype="category")
print(ps)
0    a
1    b
2    c
3    a
dtype: category
Categories (3, object): ['a', 'b', 'c']

ms = pd.Series(["a", "b", "c", "a"], dtype="category")
print(ms)
0    a
1    b
2    c
3    a
Name: __reduced__, dtype: category
dtype: category
Categories (3, object): ['a', 'b', 'c']
```


Discussion:

Resolving patch:
diff --git a/modin/pandas/series.py b/modin/pandas/series.py
--- a/modin/pandas/series.py
+++ b/modin/pandas/series.py
@@ -420,7 +420,14 @@ def __repr__(self):
         )
         if len(self) == 0:
             return "Series([], {}{}{}".format(freq_str, name_str, dtype_str)
-        return temp_str.rsplit("\n", 1)[0] + "\n{}{}{}{}".format(
+        maxsplit = 1
+        if (
+            isinstance(temp_df, pandas.Series)
+            and temp_df.name is not None
+            and temp_df.dtype == "category"
+        ):
+            maxsplit = 2
+        return temp_str.rsplit("\n", maxsplit)[0] + "\n{}{}{}{}".format(
             freq_str, name_str, len_str, dtype_str
         )
 


Test patch:
diff --git a/modin/pandas/test/test_series.py b/modin/pandas/test/test_series.py
--- a/modin/pandas/test/test_series.py
+++ b/modin/pandas/test/test_series.py
@@ -529,6 +529,13 @@ def test___repr__(name, dt_index, data):
         assert repr(modin_series) == repr(pandas_series)
 
 
+def test___repr__4186():
+    modin_series, pandas_series = create_test_series(
+        ["a", "b", "c", "a"], dtype="category"
+    )
+    assert repr(modin_series) == repr(pandas_series)
+
+
 @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
 def test___round__(data):
     modin_series, pandas_series = create_test_series(data)
Repository: modin-project/modin

Issue:
CLN: remove `columnarize` method from pandas query complier
This method already defined in base query compiler.


Discussion:

Resolving patch:
diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
--- a/modin/core/storage_formats/pandas/query_compiler.py
+++ b/modin/core/storage_formats/pandas/query_compiler.py
@@ -686,13 +686,6 @@ def transpose(self, *args, **kwargs):
         # Switch the index and columns and transpose the data within the blocks.
         return self.__constructor__(self._modin_frame.transpose())
 
-    def columnarize(self):
-        if len(self.columns) != 1 or (
-            len(self.index) == 1 and self.index[0] == MODIN_UNNAMED_SERIES_LABEL
-        ):
-            return self.transpose()
-        return self
-
     def is_series_like(self):
         return len(self.columns) == 1 or len(self.index) == 1
 


Test patch:
Repository: modin-project/modin

Issue:
Disable empty-groupby handling logic in Experimental Mode
Recently merged #5442 broke CI on master in experimental mode. The following issue was raised: #5536 to resolve the root cause.

For now, we should disable this failing logic in the experimental mode in order to unblock CI.


Discussion:

Resolving patch:
diff --git a/modin/pandas/groupby.py b/modin/pandas/groupby.py
--- a/modin/pandas/groupby.py
+++ b/modin/pandas/groupby.py
@@ -150,19 +150,31 @@ def __getattr__(self, key):
                 return self.__getitem__(key)
             raise err
 
-    def __getattribute__(self, item):
-        attr = super().__getattribute__(item)
-        if item not in _DEFAULT_BEHAVIOUR and not self._query_compiler.lazy_execution:
-            # We default to pandas on empty DataFrames. This avoids a large amount of
-            # pain in underlying implementation and returns a result immediately rather
-            # than dealing with the edge cases that empty DataFrames have.
-            if callable(attr) and self._df.empty and hasattr(self._pandas_class, item):
-
-                def default_handler(*args, **kwargs):
-                    return self._default_to_pandas(item, *args, **kwargs)
-
-                return default_handler
-        return attr
+    # TODO: `.__getattribute__` overriding is broken in experimental mode. We should
+    # remove this branching one it's fixed:
+    # https://github.com/modin-project/modin/issues/5536
+    if not IsExperimental.get():
+
+        def __getattribute__(self, item):
+            attr = super().__getattribute__(item)
+            if (
+                item not in _DEFAULT_BEHAVIOUR
+                and not self._query_compiler.lazy_execution
+            ):
+                # We default to pandas on empty DataFrames. This avoids a large amount of
+                # pain in underlying implementation and returns a result immediately rather
+                # than dealing with the edge cases that empty DataFrames have.
+                if (
+                    callable(attr)
+                    and self._df.empty
+                    and hasattr(self._pandas_class, item)
+                ):
+
+                    def default_handler(*args, **kwargs):
+                        return self._default_to_pandas(item, *args, **kwargs)
+
+                    return default_handler
+            return attr
 
     @property
     def ngroups(self):


Test patch:
Repository: modin-project/modin

Issue:
Avoid computation of dtypes after `__invert__` op
This should help if the mask is of bool type: `df[~mask]`.


Discussion:

Resolving patch:
diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
--- a/modin/core/storage_formats/pandas/query_compiler.py
+++ b/modin/core/storage_formats/pandas/query_compiler.py
@@ -1336,7 +1336,7 @@ def stack(self, level, dropna):
     applymap = Map.register(pandas.DataFrame.applymap)
     conj = Map.register(lambda df, *args, **kwargs: pandas.DataFrame(np.conj(df)))
     convert_dtypes = Map.register(pandas.DataFrame.convert_dtypes)
-    invert = Map.register(pandas.DataFrame.__invert__)
+    invert = Map.register(pandas.DataFrame.__invert__, dtypes="copy")
     isin = Map.register(pandas.DataFrame.isin, dtypes=np.bool_)
     isna = Map.register(pandas.DataFrame.isna, dtypes=np.bool_)
     _isfinite = Map.register(


Test patch:
Repository: modin-project/modin

Issue:
don't trigger axes computation in `to_pandas` function 
In the case when the indexes are not materialized, we get them from internal partitions. However, then they are compared with the indexes of the dataframe obtained from the internal partitions. In this case, we know in advance that they will be the same. 
Looks like extra work that can be avoided.


Discussion:

Resolving patch:
diff --git a/modin/core/dataframe/pandas/dataframe/dataframe.py b/modin/core/dataframe/pandas/dataframe/dataframe.py
--- a/modin/core/dataframe/pandas/dataframe/dataframe.py
+++ b/modin/core/dataframe/pandas/dataframe/dataframe.py
@@ -3230,13 +3230,22 @@ def to_pandas(self):
         if df.empty:
             df = pandas.DataFrame(columns=self.columns, index=self.index)
         else:
-            for axis in [0, 1]:
-                ErrorMessage.catch_bugs_and_request_email(
-                    not df.axes[axis].equals(self.axes[axis]),
-                    f"Internal and external indices on axis {axis} do not match.",
-                )
-            df.index = self.index
-            df.columns = self.columns
+            for axis, external_index in enumerate(
+                [self._index_cache, self._columns_cache]
+            ):
+                # no need to check external and internal axes since in that case
+                # external axes will be computed from internal partitions
+                if external_index is not None:
+                    ErrorMessage.catch_bugs_and_request_email(
+                        not df.axes[axis].equals(external_index),
+                        f"Internal and external indices on axis {axis} do not match.",
+                    )
+                    # have to do this in order to assign some potentially missing metadata,
+                    # the ones that were set to the external index but were never propagated
+                    # into the internal ones
+                    df.set_axis(
+                        axis=axis, labels=external_index, inplace=True, copy=False
+                    )
 
         return df
 


Test patch:
Repository: modin-project/modin

Issue:
Upgrade pandas to 1.5.3



Discussion:

Resolving patch:
diff --git a/modin/pandas/__init__.py b/modin/pandas/__init__.py
--- a/modin/pandas/__init__.py
+++ b/modin/pandas/__init__.py
@@ -14,7 +14,7 @@
 import pandas
 import warnings
 
-__pandas_version__ = "1.5.2"
+__pandas_version__ = "1.5.3"
 
 if pandas.__version__ != __pandas_version__:
     warnings.warn(
diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -47,7 +47,7 @@ def make_distribution(self):
     long_description=long_description,
     long_description_content_type="text/markdown",
     install_requires=[
-        "pandas==1.5.2",
+        "pandas==1.5.3",
         "packaging",
         "numpy>=1.18.5",
         "fsspec",


Test patch:
Repository: modin-project/modin

Issue:
don't use deprecated `inplace` parameter for `set_axis` function
When used internally in Modin, this generates a warning that can confuse users.


Discussion:

Resolving patch:
diff --git a/modin/core/dataframe/pandas/dataframe/dataframe.py b/modin/core/dataframe/pandas/dataframe/dataframe.py
--- a/modin/core/dataframe/pandas/dataframe/dataframe.py
+++ b/modin/core/dataframe/pandas/dataframe/dataframe.py
@@ -3279,9 +3279,7 @@ def to_pandas(self):
                     # have to do this in order to assign some potentially missing metadata,
                     # the ones that were set to the external index but were never propagated
                     # into the internal ones
-                    df.set_axis(
-                        axis=axis, labels=external_index, inplace=True, copy=False
-                    )
+                    df = df.set_axis(axis=axis, labels=external_index, copy=False)
 
         return df
 
diff --git a/modin/pandas/base.py b/modin/pandas/base.py
--- a/modin/pandas/base.py
+++ b/modin/pandas/base.py
@@ -3429,7 +3429,7 @@ def tz_convert(self, tz, axis=0, level=None, copy=True):  # noqa: PR01, RT01, D2
         else:
             new_labels = self.axes[axis].tz_convert(tz)
         obj = self.copy() if copy else self
-        return obj.set_axis(new_labels, axis, inplace=False, copy=copy)
+        return obj.set_axis(new_labels, axis, copy=copy)
 
     def tz_localize(
         self, tz, axis=0, level=None, copy=True, ambiguous="raise", nonexistent="raise"
@@ -3450,7 +3450,7 @@ def tz_localize(
             )
             .index
         )
-        return self.set_axis(new_labels, axis, inplace=False, copy=copy)
+        return self.set_axis(new_labels, axis, copy=copy)
 
     # TODO: uncomment the following lines when #3331 issue will be closed
     # @prepend_to_notes(


Test patch:
Repository: modin-project/modin

Issue:
Do not materialize metadata in `PandasDataframe.filter`
It currently may trigger `self.axes[axis]` materialization, we can avoid it by using a cache here
https://github.com/modin-project/modin/blob/e56a80c32f8854edd877529597d101bf18c58d2a/modin/core/dataframe/pandas/dataframe/dataframe.py#L2116-L2118


Discussion:

Resolving patch:
diff --git a/modin/core/dataframe/pandas/dataframe/dataframe.py b/modin/core/dataframe/pandas/dataframe/dataframe.py
--- a/modin/core/dataframe/pandas/dataframe/dataframe.py
+++ b/modin/core/dataframe/pandas/dataframe/dataframe.py
@@ -2113,8 +2113,12 @@ def filter(self, axis: Union[Axis, int], condition: Callable) -> "PandasDatafram
 
         new_axes, new_lengths = [0, 0], [0, 0]
 
-        new_axes[axis.value] = self.axes[axis.value]
-        new_lengths[axis.value] = self._axes_lengths[axis.value]
+        new_axes[axis.value] = (
+            self._index_cache if axis.value == 0 else self._columns_cache
+        )
+        new_lengths[axis.value] = (
+            self._row_lengths_cache if axis.value == 0 else self._column_widths_cache
+        )
         new_axes[axis.value ^ 1], new_lengths[axis.value ^ 1] = None, None
 
         return self.__constructor__(


Test patch:
Repository: modin-project/modin

Issue:
`PyArrowDataset.files` uses `ParquetDataset.files` method that exists only for `pyarrow>=8.0.0`
We should update the minimum version of this dependency.

https://github.com/modin-project/modin/blob/5d1fe8b1bb789e30292bb39da45f99f71f48bfc6/modin/core/io/column_stores/parquet_dispatcher.py#L218


Discussion:

Resolving patch:
diff --git a/modin/core/io/column_stores/parquet_dispatcher.py b/modin/core/io/column_stores/parquet_dispatcher.py
--- a/modin/core/io/column_stores/parquet_dispatcher.py
+++ b/modin/core/io/column_stores/parquet_dispatcher.py
@@ -216,7 +216,12 @@ def row_groups_per_file(self):
     @property
     def files(self):
         if self._files is None:
-            self._files = self._get_files(self.dataset.files)
+            try:
+                files = self.dataset.files
+            except AttributeError:
+                # compatibility at least with 3.0.0 <= pyarrow < 8.0.0
+                files = self.dataset._dataset.files
+            self._files = self._get_files(files)
         return self._files
 
     def to_pandas_dataframe(


Test patch:
Repository: modin-project/modin

Issue:
Do not materialize metadata in `PandasDataframe.filter`
It currently may trigger `self.axes[axis]` materialization, we can avoid it by using a cache here
https://github.com/modin-project/modin/blob/e56a80c32f8854edd877529597d101bf18c58d2a/modin/core/dataframe/pandas/dataframe/dataframe.py#L2116-L2118


Discussion:
It still unnecessary triggers `dtypes` computation, so reopening the issue
https://github.com/modin-project/modin/blob/4f78260d91042497b5d40305c3647bb00c482b14/modin/core/dataframe/pandas/dataframe/dataframe.py#L2128

Resolving patch:
diff --git a/modin/core/dataframe/pandas/dataframe/dataframe.py b/modin/core/dataframe/pandas/dataframe/dataframe.py
--- a/modin/core/dataframe/pandas/dataframe/dataframe.py
+++ b/modin/core/dataframe/pandas/dataframe/dataframe.py
@@ -2125,7 +2125,7 @@ def filter(self, axis: Union[Axis, int], condition: Callable) -> "PandasDatafram
             new_partitions,
             *new_axes,
             *new_lengths,
-            self.dtypes if axis == Axis.COL_WISE else None,
+            self._dtypes if axis == Axis.COL_WISE else None,
         )
 
     def filter_by_types(self, types: List[Hashable]) -> "PandasDataframe":


Test patch:
Repository: modin-project/modin

Issue:
BUG: read_sql syntax not compatible with snowflake
### Modin version checks

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the latest released version of Modin.

- [X] I have confirmed this bug exists on the main branch of Modin. (In order to do this you can follow [this guide](https://modin.readthedocs.io/en/stable/getting_started/installation.html#installing-from-the-github-master-branch).)


### Reproducible Example

```python
import modin.pandas as pd

df = pd.DataFrame([[1, 2]])
conn_str = "some_snowflake_connection_string"
df.to_sql("TABLE", conn_str)
```


### Issue Description

Getting a snowflake compilation error

### Expected Behavior

should be able to `to_sql`

### Error Logs

<details>

```python-traceback

ProgrammingError: (snowflake.connector.errors.ProgrammingError) 001003 (42000): SQL compilation error:
syntax error line 1 at position 205 unexpected '_'.
[SQL: SELECT COUNT(*) FROM (select * from forecast_platform.ml_daily_forecast_production_submarket_weekly_normalized_dagster where run_date='2023-01-23' and target_date between '2023-01-23' and '2023-01-30') AS _]
(Background on this error at: https://sqlalche.me/e/14/f405)

```

</details>


### Installed Versions

N/A


Discussion:
temporary Fix is on this branch :https://github.com/RehanSD/modin/tree/rehan/fix_snowflake_db_conn

Resolving patch:
diff --git a/modin/db_conn.py b/modin/db_conn.py
--- a/modin/db_conn.py
+++ b/modin/db_conn.py
@@ -136,7 +136,7 @@ def column_names_query(self, query: str) -> str:
         """
         # This query looks odd, but it works in both PostgreSQL and Microsoft
         # SQL, which doesn't let you use a "limit" clause to select 0 rows.
-        return f"SELECT * FROM ({query}) AS _ WHERE 1 = 0"
+        return f"SELECT * FROM ({query}) AS _MODIN_COUNT_QUERY WHERE 1 = 0"
 
     def row_count_query(self, query: str) -> str:
         """
@@ -151,7 +151,7 @@ def row_count_query(self, query: str) -> str:
         -------
         str
         """
-        return f"SELECT COUNT(*) FROM ({query}) AS _"
+        return f"SELECT COUNT(*) FROM ({query}) AS _MODIN_COUNT_QUERY"
 
     def partition_query(self, query: str, limit: int, offset: int) -> str:
         """
@@ -172,9 +172,10 @@ def partition_query(self, query: str, limit: int, offset: int) -> str:
         """
         return (
             (
-                f"SELECT * FROM ({query}) AS _ ORDER BY(SELECT NULL)"
+                f"SELECT * FROM ({query}) AS _MODIN_COUNT_QUERY ORDER BY(SELECT NULL)"
                 + f" OFFSET {offset} ROWS FETCH NEXT {limit} ROWS ONLY"
             )
             if self._dialect_is_microsoft_sql()
-            else f"SELECT * FROM ({query}) AS _ LIMIT {limit} OFFSET {offset}"
+            else f"SELECT * FROM ({query}) AS _MODIN_COUNT_QUERY LIMIT "
+            + f"{limit} OFFSET {offset}"
         )


Test patch:
Repository: modin-project/modin

Issue:
Don't trigger axes computation when accessing cat.codes
When we call cat.codes and return a Series object, we don't need to trigger axes computation in columnarize.


Discussion:

Resolving patch:
diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
--- a/modin/core/storage_formats/pandas/query_compiler.py
+++ b/modin/core/storage_formats/pandas/query_compiler.py
@@ -3394,10 +3394,12 @@ def func(df) -> np.ndarray:
             ser = df.iloc[:, 0]
             if ser.dtype != "category":
                 ser = ser.astype("category", copy=False)
-            return ser.cat.codes
+            return ser.cat.codes.to_frame(name=MODIN_UNNAMED_SERIES_LABEL)
 
-        res = self._modin_frame.apply_full_axis(axis=0, func=func)
-        return self.__constructor__(res)
+        res = self._modin_frame.apply_full_axis(
+            axis=0, func=func, new_columns=[MODIN_UNNAMED_SERIES_LABEL]
+        )
+        return self.__constructor__(res, shape_hint="column")
 
     # END Cat operations
 


Test patch:
Repository: modin-project/modin

Issue:
Avoid re-putting a distributed Series to the engine's object store at `.map()`



Discussion:

Resolving patch:
diff --git a/modin/pandas/series.py b/modin/pandas/series.py
--- a/modin/pandas/series.py
+++ b/modin/pandas/series.py
@@ -1266,6 +1266,14 @@ def map(self, arg, na_action=None):  # noqa: PR01, RT01, D200
         """
         Map values of Series according to input correspondence.
         """
+        if isinstance(arg, type(self)):
+            # HACK: if we don't cast to pandas, then the execution engine will try to
+            # propagate the distributed Series to workers and most likely would have
+            # some performance problems.
+            # TODO: A better way of doing so could be passing this `arg` as a query compiler
+            # and broadcast accordingly.
+            arg = arg._to_pandas()
+
         if not callable(arg) and hasattr(arg, "get"):
             mapper = arg
 


Test patch:
Repository: modin-project/modin

Issue:
Preserve metadata when applying `Series.cat.codes`
We can preserve index, row_lengths, column_widths in addition to columns.


Discussion:

Resolving patch:
diff --git a/modin/core/dataframe/pandas/dataframe/dataframe.py b/modin/core/dataframe/pandas/dataframe/dataframe.py
--- a/modin/core/dataframe/pandas/dataframe/dataframe.py
+++ b/modin/core/dataframe/pandas/dataframe/dataframe.py
@@ -1793,7 +1793,7 @@ def window(
         pass
 
     @lazy_metadata_decorator(apply_axis="both")
-    def fold(self, axis, func):
+    def fold(self, axis, func, new_columns=None):
         """
         Perform a function across an entire axis.
 
@@ -1803,6 +1803,11 @@ def fold(self, axis, func):
             The axis to apply over.
         func : callable
             The function to apply.
+        new_columns : list-like, optional
+            The columns of the result.
+            Must be the same length as the columns' length of `self`.
+            The column labels of `self` may change during an operation so
+            we may want to pass the new column labels in (e.g., see `cat.codes`).
 
         Returns
         -------
@@ -1813,6 +1818,13 @@ def fold(self, axis, func):
         -----
         The data shape is not changed (length and width of the table).
         """
+        if new_columns is not None:
+            if self._columns_cache is not None:
+                assert len(self._columns_cache) == len(
+                    new_columns
+                ), "The length of `new_columns` doesn't match the columns' length of `self`"
+            self._columns_cache = new_columns
+
         new_partitions = self._partition_mgr_cls.map_axis_partitions(
             axis, self._partitions, func, keep_partitioning=True
         )
diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
--- a/modin/core/storage_formats/pandas/query_compiler.py
+++ b/modin/core/storage_formats/pandas/query_compiler.py
@@ -3427,7 +3427,7 @@ def func(df) -> np.ndarray:
                 ser = ser.astype("category", copy=False)
             return ser.cat.codes.to_frame(name=MODIN_UNNAMED_SERIES_LABEL)
 
-        res = self._modin_frame.apply_full_axis(
+        res = self._modin_frame.fold(
             axis=0, func=func, new_columns=[MODIN_UNNAMED_SERIES_LABEL]
         )
         return self.__constructor__(res, shape_hint="column")


Test patch:
Repository: modin-project/modin

Issue:
Do not convert numpy arrays to a python list at `df.__setitem__`
It's absolutely unnecessary and hits performance a lot:
https://github.com/modin-project/modin/blob/f4ed1c803c1d0139c5f731f6d723252025645134/modin/pandas/dataframe.py#L2769-L2770


Discussion:

Resolving patch:
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -2766,7 +2766,7 @@ def setitem_unhashable_key(df, value):
                 value = value.T.reshape(-1)
                 if len(self) > 0:
                     value = value[: len(self)]
-            if not isinstance(value, (Series, Categorical)):
+            if not isinstance(value, (Series, Categorical, np.ndarray)):
                 value = list(value)
 
         if not self._query_compiler.lazy_execution and len(self.index) == 0:


Test patch: