Raise MixedTypeError when a column of mixed-dtype is being construc…

…ted (#14050)

Fixes #14038 

This PR introduces changes that raise an error when a column of `object` dtype is being constructed when the data is not string or bools.

Authors:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Matthew Roeschke (https://github.com/mroeschke)

URL: #14050

python/cudf/cudf/core/column/column.py

@@ -2062,10 +2062,15 @@ def as_column(
             )
         else:
             pyarrow_array = pa.array(arbitrary, from_pandas=nan_as_null)
-            if arbitrary.dtype == cudf.dtype("object") and isinstance(
-                pyarrow_array, (pa.DurationArray, pa.TimestampArray)
+            if (
+                arbitrary.dtype == cudf.dtype("object")
+                and cudf.dtype(pyarrow_array.type.to_pandas_dtype())
+                != cudf.dtype(arbitrary.dtype)
+                and not is_bool_dtype(
+                    cudf.dtype(pyarrow_array.type.to_pandas_dtype())
+                )
             ):
-                raise TypeError("Cannot create column with mixed types")
+                raise MixedTypeError("Cannot create column with mixed types")
             if isinstance(pyarrow_array.type, pa.Decimal128Type):
                 pyarrow_type = cudf.Decimal128Dtype.from_arrow(
                     pyarrow_array.type
@@ -2436,8 +2441,12 @@ def as_column(
                 if (
                     isinstance(arbitrary, pd.Index)
                     and arbitrary.dtype == cudf.dtype("object")
-                    and isinstance(
-                        pyarrow_array, (pa.DurationArray, pa.TimestampArray)
+                    and (
+                        cudf.dtype(pyarrow_array.type.to_pandas_dtype())
+                        != cudf.dtype(arbitrary.dtype)
+                        and not is_bool_dtype(
+                            cudf.dtype(pyarrow_array.type.to_pandas_dtype())
+                        )
                     )
                 ):
                     raise MixedTypeError(

python/cudf/cudf/tests/test_index.py

@@ -2676,10 +2676,11 @@ def test_scalar_getitem(self, index_values, i):
             12,
             20,
         ],
+        [1, 2, 3, 4],
     ],
 )
 def test_index_mixed_dtype_error(data):
-    pi = pd.Index(data)
+    pi = pd.Index(data, dtype="object")
     with pytest.raises(TypeError):
         cudf.Index(pi)
 

python/cudf/cudf/tests/test_parquet.py

@@ -2374,11 +2374,11 @@ def test_parquet_writer_list_statistics(tmpdir):
         for i, col in enumerate(pd_slice):
             stats = pq_file.metadata.row_group(rg).column(i).statistics
 
-            actual_min = cudf.Series(pd_slice[col].explode().explode()).min()
+            actual_min = pd_slice[col].explode().explode().dropna().min()
             stats_min = stats.min
             assert normalized_equals(actual_min, stats_min)
 
-            actual_max = cudf.Series(pd_slice[col].explode().explode()).max()
+            actual_max = pd_slice[col].explode().explode().dropna().max()
             stats_max = stats.max
             assert normalized_equals(actual_max, stats_max)
 

python/cudf/cudf/tests/test_series.py

@@ -2187,11 +2187,15 @@ def test_series_init_error():
     )
 
 
-@pytest.mark.parametrize("dtype", ["datetime64[ns]", "timedelta64[ns]"])
+@pytest.mark.parametrize(
+    "dtype", ["datetime64[ns]", "timedelta64[ns]", "object", "str"]
+)
 def test_series_mixed_dtype_error(dtype):
     ps = pd.concat([pd.Series([1, 2, 3], dtype=dtype), pd.Series([10, 11])])
     with pytest.raises(TypeError):
         cudf.Series(ps)
+    with pytest.raises(TypeError):
+        cudf.Series(ps.array)
 
 
 @pytest.mark.parametrize("data", [[True, False, None], [10, 200, 300]])