fixes

Signed-off-by: Anatoly Myachev <[email protected]>

modin/core/storage_formats/pandas/query_compiler.py

@@ -943,9 +943,8 @@ def compute_dtypes_fn(dtypes, axis, **kwargs):
                 and any(is_bool_dtype(t) for t in dtypes)
                 and any(is_numeric_dtype(t) for t in dtypes)
             ):
-                return np.object_
-            # how to take into account backend here?
-            return np.float64
+                return "object"
+            return "float64"
 
         return TreeReduce.register(
             map_fn,

modin/tests/pandas/utils.py

@@ -1087,14 +1087,25 @@ def eval_io_from_str(csv_str: str, unique_filename: str, **kwargs):
     )
 
 
-def create_test_dfs(*args, **kwargs) -> tuple[pd.DataFrame, pandas.DataFrame]:
-    post_fn = kwargs.pop("post_fn", lambda df: df)
+def create_test_dfs(
+    *args, post_fn=None, backend=None, **kwargs
+) -> tuple[pd.DataFrame, pandas.DataFrame]:
+    if post_fn is None:
+        post_fn = lambda df: (  # noqa: E731
+            df.convert_dtypes(dtype_backend=backend) if backend is not None else df
+        )
+    elif backend is not None:
+        post_fn = lambda df: post_fn(df).convert_dtypes(  # noqa: E731
+            dtype_backend=backend
+        )
     return tuple(
         map(post_fn, [pd.DataFrame(*args, **kwargs), pandas.DataFrame(*args, **kwargs)])
     )
 
 
-def create_test_series(vals, sort=False, **kwargs) -> tuple[pd.Series, pandas.Series]:
+def create_test_series(
+    vals, sort=False, backend=None, **kwargs
+) -> tuple[pd.Series, pandas.Series]:
     if isinstance(vals, dict):
         modin_series = pd.Series(vals[next(iter(vals.keys()))], **kwargs)
         pandas_series = pandas.Series(vals[next(iter(vals.keys()))], **kwargs)
@@ -1104,6 +1115,10 @@ def create_test_series(vals, sort=False, **kwargs) -> tuple[pd.Series, pandas.Se
     if sort:
         modin_series = modin_series.sort_values().reset_index(drop=True)
         pandas_series = pandas_series.sort_values().reset_index(drop=True)
+
+    if backend is not None:
+        modin_series = modin_series.convert_dtypes(dtype_backend=backend)
+        pandas_series = pandas_series.convert_dtypes(dtype_backend=backend)
     return modin_series, pandas_series