silenced warnings in pandas/tests/series

Author: SaturnFromTitan

pandas/core/construction.py

@@ -625,6 +625,50 @@ def create_series_with_explicit_dtype(
 
     if is_empty_data(data) and dtype is None:
         dtype = dtype_if_empty
+    return create_series_with_explicit_index_type(
+        data=data, index=index, dtype=dtype, name=name, copy=copy, fastpath=fastpath
+    )
+
+
+def create_series_with_explicit_index_type(
+    data: Any = None,
+    index: Optional[Union[ArrayLike, "Index"]] = None,
+    dtype: Optional[Dtype] = None,
+    name: Optional[str] = None,
+    copy: bool = False,
+    fastpath: bool = False,
+    index_if_empty: Optional["Index"] = None,
+) -> "Series":
+    """
+    Helper to pass an explicit index type when instantiating an Series where
+    data is list-like and empty.
+
+    This silences a DeprecationWarning described in GitHub-16737.
+
+    Parameters
+    ----------
+    data : Mirrored from Series.__init__
+    index : Mirrored from Series.__init__
+    dtype : Mirrored from Series.__init__
+    name : Mirrored from Series.__init__
+    copy : Mirrored from Series.__init__
+    fastpath : Mirrored from Series.__init__
+    index_if_empty : instance of (Index, RangeIndex)
+        This index type will be passed explicitly when Series is initialised
+        with `data` being list-like and empty.
+
+    Returns
+    -------
+    Series
+    """
+    from pandas import Series
+    from pandas import Index
+
+    if index_if_empty is None:
+        index_if_empty = Index([])
+
+    if is_list_like(data) and len(data) == 0:
+        index = index_if_empty
     return Series(
         data=data, index=index, dtype=dtype, name=name, copy=copy, fastpath=fastpath
     )

pandas/tests/series/indexing/test_boolean.py

@@ -3,6 +3,7 @@
 
 from pandas import Index, Series
 import pandas._testing as tm
+from pandas.core.construction import create_series_with_explicit_index_type
 from pandas.core.indexing import IndexingError
 
 from pandas.tseries.offsets import BDay
@@ -20,7 +21,7 @@ def test_getitem_boolean(string_series):
 
 
 def test_getitem_boolean_empty():
-    s = Series([], dtype=np.int64)
+    s = create_series_with_explicit_index_type([], dtype=np.int64)
     s.index.name = "index_name"
     s = s[s.isna()]
     assert s.index.name == "index_name"
@@ -30,7 +31,7 @@ def test_getitem_boolean_empty():
     # indexing with empty series
     s = Series(["A", "B"])
     expected = Series(dtype=object, index=Index([], dtype="int64"))
-    result = s[Series([], dtype=object)]
+    result = s[create_series_with_explicit_index_type([], dtype=object)]
     tm.assert_series_equal(result, expected)
 
     # invalid because of the boolean indexer
@@ -40,7 +41,7 @@ def test_getitem_boolean_empty():
         r"the boolean Series and of the indexed object do not match"
     )
     with pytest.raises(IndexingError, match=msg):
-        s[Series([], dtype=bool)]
+        s[create_series_with_explicit_index_type([], dtype=bool)]
 
     with pytest.raises(IndexingError, match=msg):
         s[Series([True], dtype=bool)]

pandas/tests/series/indexing/test_indexing.py

@@ -5,6 +5,7 @@
 import numpy as np
 import pytest
 
+from pandas.core.construction import create_series_with_explicit_index_type
 from pandas.core.dtypes.common import is_scalar
 
 import pandas as pd
@@ -160,7 +161,7 @@ def test_getitem_out_of_bounds(datetime_series):
 
     # GH #917
     # With a RangeIndex, an int key gives a KeyError
-    s = Series([], dtype=object)
+    s = Series([], index=pd.RangeIndex(0), dtype=object)
     with pytest.raises(KeyError, match="-1"):
         s[-1]
 
@@ -617,7 +618,7 @@ def test_setitem_na():
 
 def test_timedelta_assignment():
     # GH 8209
-    s = Series([], dtype=object)
+    s = create_series_with_explicit_index_type([], dtype=object)
     s.loc["B"] = timedelta(1)
     tm.assert_series_equal(s, Series(Timedelta("1 days"), index=["B"]))
 

pandas/tests/series/methods/test_drop_duplicates.py

@@ -3,6 +3,7 @@
 
 from pandas import Categorical, Series
 import pandas._testing as tm
+from pandas.core.construction import create_series_with_explicit_index_type
 
 
 @pytest.mark.parametrize(
@@ -46,8 +47,8 @@ def test_drop_duplicates_bool(keep, expected):
 
 @pytest.mark.parametrize("values", [[], list(range(5))])
 def test_drop_duplicates_no_duplicates(any_numpy_dtype, keep, values):
-    tc = Series(values, dtype=np.dtype(any_numpy_dtype))
-    expected = Series([False] * len(tc), dtype="bool")
+    tc = create_series_with_explicit_index_type(values, dtype=np.dtype(any_numpy_dtype))
+    expected = create_series_with_explicit_index_type([False] * len(tc), dtype="bool")
 
     if tc.dtype == "bool":
         # 0 -> False and 1-> True

pandas/tests/series/methods/test_interpolate.py

@@ -6,6 +6,7 @@
 import pandas as pd
 from pandas import Index, MultiIndex, Series, date_range, isna
 import pandas._testing as tm
+from pandas.core.construction import create_series_with_explicit_index_type
 
 
 @pytest.fixture(
@@ -169,7 +170,7 @@ def test_interpolate_corners(self, kwargs):
         s = Series([np.nan, np.nan])
         tm.assert_series_equal(s.interpolate(**kwargs), s)
 
-        s = Series([], dtype=object).interpolate()
+        s = Series([], dtype=object, index=pd.RangeIndex(0)).interpolate()
         tm.assert_series_equal(s.interpolate(**kwargs), s)
 
     def test_interpolate_index_values(self):

pandas/tests/series/methods/test_quantile.py

@@ -1,6 +1,7 @@
 import numpy as np
 import pytest
 
+from pandas.core.construction import create_series_with_explicit_index_type
 from pandas.core.dtypes.common import is_integer
 
 import pandas as pd
@@ -104,7 +105,7 @@ def test_quantile_nan(self):
         assert result == expected
 
         # all nan/empty
-        s1 = Series([], dtype=object)
+        s1 = create_series_with_explicit_index_type([], dtype=object)
         cases = [s1, Series([np.nan, np.nan])]
 
         for s in cases:
@@ -163,8 +164,8 @@ def test_quantile_box(self, case):
 
     def test_datetime_timedelta_quantiles(self):
         # covers #9694
-        assert pd.isna(Series([], dtype="M8[ns]").quantile(0.5))
-        assert pd.isna(Series([], dtype="m8[ns]").quantile(0.5))
+        assert pd.isna(create_series_with_explicit_index_type([], dtype="M8[ns]").quantile(0.5))
+        assert pd.isna(create_series_with_explicit_index_type([], dtype="m8[ns]").quantile(0.5))
 
     def test_quantile_nat(self):
         res = Series([pd.NaT, pd.NaT]).quantile(0.5)
@@ -186,7 +187,7 @@ def test_quantile_sparse(self, values, dtype):
     def test_quantile_empty(self):
 
         # floats
-        s = Series([], dtype="float64")
+        s = create_series_with_explicit_index_type([], dtype="float64")
 
         res = s.quantile(0.5)
         assert np.isnan(res)
@@ -196,7 +197,7 @@ def test_quantile_empty(self):
         tm.assert_series_equal(res, exp)
 
         # int
-        s = Series([], dtype="int64")
+        s = create_series_with_explicit_index_type([], dtype="int64")
 
         res = s.quantile(0.5)
         assert np.isnan(res)
@@ -206,7 +207,7 @@ def test_quantile_empty(self):
         tm.assert_series_equal(res, exp)
 
         # datetime
-        s = Series([], dtype="datetime64[ns]")
+        s = create_series_with_explicit_index_type([], dtype="datetime64[ns]")
 
         res = s.quantile(0.5)
         assert res is pd.NaT

pandas/tests/series/test_apply.py

@@ -4,6 +4,7 @@
 import numpy as np
 import pytest
 
+from pandas.core.construction import create_series_with_explicit_index_type
 from pandas.core.dtypes.generic import ABCMultiIndex
 
 import pandas as pd
@@ -519,7 +520,7 @@ def test_map_empty(self, indices):
         if isinstance(indices, ABCMultiIndex):
             pytest.skip("Initializing a Series from a MultiIndex is not supported")
 
-        s = Series(indices)
+        s = create_series_with_explicit_index_type(indices)
         result = s.map({})
 
         expected = pd.Series(np.nan, index=s.index)

pandas/tests/series/test_combine_concat.py

@@ -3,6 +3,7 @@
 
 import pandas as pd
 from pandas import Series
+from pandas.core.construction import create_series_with_explicit_index_type
 
 
 class TestSeriesConcat:
@@ -94,7 +95,7 @@ def test_concat_empty_series_dtype_category_with_array(self):
         # GH 18515
         assert (
             pd.concat(
-                [Series(np.array([]), dtype="category"), Series(dtype="float64")]
+                [create_series_with_explicit_index_type(np.array([]), dtype="category"), Series(dtype="float64")]
             ).dtype
             == "float64"
         )

pandas/tests/series/test_constructors.py

@@ -8,6 +8,7 @@
 from pandas._libs import lib
 from pandas._libs.tslib import iNaT
 
+from pandas.core.construction import create_series_with_explicit_index_type
 from pandas.core.dtypes.common import is_categorical_dtype, is_datetime64tz_dtype
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
@@ -134,12 +135,21 @@ def test_constructor_empty(self, input_class):
 
         # With explicit dtype:
         empty = Series(dtype="float64")
-        empty2 = Series(input_class(), dtype="float64")
+
+        if input_class is list:
+            with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+                empty2 = Series(input_class(), dtype="float64")
+        else:
+            empty2 = Series(input_class(), dtype="float64")
         tm.assert_series_equal(empty, empty2, check_index_type=False)
 
         # GH 18515 : with dtype=category:
         empty = Series(dtype="category")
-        empty2 = Series(input_class(), dtype="category")
+        if input_class is list:
+            with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+                empty2 = Series(input_class(), dtype="category")
+        else:
+            empty2 = Series(input_class(), dtype="category")
         tm.assert_series_equal(empty, empty2, check_index_type=False)
 
         if input_class is not list:
@@ -1391,7 +1401,7 @@ def test_constructor_generic_timestamp_no_frequency(self, dtype):
         msg = "dtype has no unit. Please pass in"
 
         with pytest.raises(ValueError, match=msg):
-            Series([], dtype=dtype)
+            create_series_with_explicit_index_type([], dtype=dtype)
 
     @pytest.mark.parametrize(
         "dtype,msg",
@@ -1404,7 +1414,7 @@ def test_constructor_generic_timestamp_bad_frequency(self, dtype, msg):
         # see gh-15524, gh-15987
 
         with pytest.raises(TypeError, match=msg):
-            Series([], dtype=dtype)
+            create_series_with_explicit_index_type([], dtype=dtype)
 
     @pytest.mark.parametrize("dtype", [None, "uint8", "category"])
     def test_constructor_range_dtype(self, dtype):

pandas/tests/series/test_dtypes.py

@@ -7,6 +7,7 @@
 import pytest
 
 from pandas._libs.tslibs import iNaT
+from pandas.core.construction import create_series_with_explicit_index_type
 
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
@@ -404,9 +405,9 @@ def test_astype_empty_constructor_equality(self, dtype):
             "M",
             "m",  # Generic timestamps raise a ValueError. Already tested.
         ):
-            init_empty = Series([], dtype=dtype)
+            init_empty = create_series_with_explicit_index_type([], dtype=dtype)
             with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
-                as_type_empty = Series([]).astype(dtype)
+                as_type_empty = create_series_with_explicit_index_type([]).astype(dtype)
             tm.assert_series_equal(init_empty, as_type_empty)
 
     def test_arg_for_errors_in_astype(self):