Fix pandas-nightly (#654)

* Mostly fix pandas-nightly

* pd.PeriodDtype(freq=CustomBusinessDay)

tests/test_api_types.py

@@ -8,7 +8,10 @@
 
 from pandas._typing import DtypeObj
 
-from tests import check
+from tests import (
+    check,
+    pytest_warns_bounded,
+)
 
 nparr = np.array([1, 2, 3])
 arr = pd.Series([1, 2, 3])
@@ -52,15 +55,20 @@ def test_is_bool_dtype() -> None:
 
 
 def test_is_categorical_dtype() -> None:
-    check(assert_type(api.is_categorical_dtype(arr), bool), bool)
-    check(assert_type(api.is_categorical_dtype(nparr), bool), bool)
-    check(assert_type(api.is_categorical_dtype(dtylike), bool), bool)
-    check(
-        assert_type(api.is_categorical_dtype(dframe), bool),
-        bool,
-    )
-    check(assert_type(api.is_categorical_dtype(ind), bool), bool)
-    check(assert_type(api.is_categorical_dtype(ExtensionDtype), bool), bool)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="is_categorical_dtype is deprecated and will be removed in a future version",
+        lower="2.0.99",
+    ):
+        check(assert_type(api.is_categorical_dtype(arr), bool), bool)
+        check(assert_type(api.is_categorical_dtype(nparr), bool), bool)
+        check(assert_type(api.is_categorical_dtype(dtylike), bool), bool)
+        check(
+            assert_type(api.is_categorical_dtype(dframe), bool),
+            bool,
+        )
+        check(assert_type(api.is_categorical_dtype(ind), bool), bool)
+        check(assert_type(api.is_categorical_dtype(ExtensionDtype), bool), bool)
 
 
 def test_is_complex() -> None:
@@ -124,15 +132,20 @@ def test_is_datetime64_ns_dtype() -> None:
 
 
 def test_is_datetime64tz_dtype() -> None:
-    check(assert_type(api.is_datetime64tz_dtype(arr), bool), bool)
-    check(assert_type(api.is_datetime64tz_dtype(nparr), bool), bool)
-    check(assert_type(api.is_datetime64tz_dtype(dtylike), bool), bool)
-    check(
-        assert_type(api.is_datetime64tz_dtype(dframe), bool),
-        bool,
-    )
-    check(assert_type(api.is_datetime64tz_dtype(ind), bool), bool)
-    check(assert_type(api.is_datetime64tz_dtype(ExtensionDtype), bool), bool)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="is_datetime64tz_dtype is deprecated and will be removed in a future version",
+        lower="2.0.99",
+    ):
+        check(assert_type(api.is_datetime64tz_dtype(arr), bool), bool)
+        check(assert_type(api.is_datetime64tz_dtype(nparr), bool), bool)
+        check(assert_type(api.is_datetime64tz_dtype(dtylike), bool), bool)
+        check(
+            assert_type(api.is_datetime64tz_dtype(dframe), bool),
+            bool,
+        )
+        check(assert_type(api.is_datetime64tz_dtype(ind), bool), bool)
+        check(assert_type(api.is_datetime64tz_dtype(ExtensionDtype), bool), bool)
 
 
 def test_is_dict_like() -> None:
@@ -209,15 +222,20 @@ def test_is_hashable() -> None:
 
 
 def test_is_int64_dtype() -> None:
-    check(assert_type(api.is_int64_dtype(arr), bool), bool)
-    check(assert_type(api.is_int64_dtype(nparr), bool), bool)
-    check(assert_type(api.is_int64_dtype(dtylike), bool), bool)
-    check(
-        assert_type(api.is_int64_dtype(dframe), bool),
-        bool,
-    )
-    check(assert_type(api.is_int64_dtype(ind), bool), bool)
-    # check(assert_type(api.is_int64_dtype(ExtensionDtype), bool), bool) pandas GH 50923
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="is_int64_dtype is deprecated and will be removed in a future version",
+        lower="2.0.99",
+    ):
+        check(assert_type(api.is_int64_dtype(arr), bool), bool)
+        check(assert_type(api.is_int64_dtype(nparr), bool), bool)
+        check(assert_type(api.is_int64_dtype(dtylike), bool), bool)
+        check(
+            assert_type(api.is_int64_dtype(dframe), bool),
+            bool,
+        )
+        check(assert_type(api.is_int64_dtype(ind), bool), bool)
+        # check(assert_type(api.is_int64_dtype(ExtensionDtype), bool), bool) pandas GH 50923
 
 
 def test_is_integer() -> None:
@@ -257,16 +275,21 @@ def test_is_interval() -> None:
 
 
 def test_is_interval_dtype() -> None:
-    check(assert_type(api.is_interval_dtype(obj), bool), bool)
-    check(assert_type(api.is_interval_dtype(nparr), bool), bool)
-    check(assert_type(api.is_interval_dtype(dtylike), bool), bool)
-    check(assert_type(api.is_interval_dtype(arr), bool), bool)
-    check(
-        assert_type(api.is_interval_dtype(dframe), bool),
-        bool,
-    )
-    check(assert_type(api.is_interval_dtype(ind), bool), bool)
-    check(assert_type(api.is_interval_dtype(ExtensionDtype), bool), bool)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="is_interval_dtype is deprecated and will be removed in a future version",
+        lower="2.0.99",
+    ):
+        check(assert_type(api.is_interval_dtype(obj), bool), bool)
+        check(assert_type(api.is_interval_dtype(nparr), bool), bool)
+        check(assert_type(api.is_interval_dtype(dtylike), bool), bool)
+        check(assert_type(api.is_interval_dtype(arr), bool), bool)
+        check(
+            assert_type(api.is_interval_dtype(dframe), bool),
+            bool,
+        )
+        check(assert_type(api.is_interval_dtype(ind), bool), bool)
+        check(assert_type(api.is_interval_dtype(ExtensionDtype), bool), bool)
 
 
 def test_is_iterator() -> None:

tests/test_dtypes.py

@@ -22,7 +22,10 @@
 from pandas._libs.missing import NAType
 from pandas._typing import Scalar
 
-from tests import check
+from tests import (
+    TYPE_CHECKING_INVALID_USAGE,
+    check,
+)
 
 from pandas.tseries.offsets import (
     BusinessDay,
@@ -54,10 +57,8 @@ def test_period_dtype() -> None:
     check(
         assert_type(pd.PeriodDtype(freq=BusinessDay()), pd.PeriodDtype), pd.PeriodDtype
     )
-    check(
-        assert_type(pd.PeriodDtype(freq=CustomBusinessDay()), pd.PeriodDtype),
-        pd.PeriodDtype,
-    )
+    if TYPE_CHECKING_INVALID_USAGE:
+        pd.PeriodDtype(freq=CustomBusinessDay())  # TODO(raises on 2.1)
     check(
         assert_type(p_dt.freq, pd.tseries.offsets.BaseOffset),
         pd.tseries.offsets.DateOffset,

tests/test_frame.py

@@ -43,6 +43,7 @@
     PD_LTE_20,
     TYPE_CHECKING_INVALID_USAGE,
     check,
+    pytest_warns_bounded,
 )
 
 from pandas.io.formats.style import Styler
@@ -726,12 +727,17 @@ def gethead(s: pd.Series, y: int) -> pd.Series:
 
 def test_types_applymap() -> None:
     df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]})
-    df.applymap(lambda x: x**2)
-    df.applymap(np.exp)
-    df.applymap(str)
-    # na_action parameter was added in 1.2.0 https://pandas.pydata.org/docs/whatsnew/v1.2.0.html
-    df.applymap(np.exp, na_action="ignore")
-    df.applymap(str, na_action=None)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="DataFrame.applymap has been deprecated. Use DataFrame.map instead.",
+        lower="2.0.99",
+    ):
+        df.applymap(lambda x: x**2)
+        df.applymap(np.exp)
+        df.applymap(str)
+        # na_action parameter was added in 1.2.0 https://pandas.pydata.org/docs/whatsnew/v1.2.0.html
+        df.applymap(np.exp, na_action="ignore")
+        df.applymap(str, na_action=None)
 
 
 def test_types_element_wise_arithmetic() -> None:
@@ -875,7 +881,12 @@ def test_types_groupby() -> None:
     df4: pd.DataFrame = df.groupby(by=["col1", "col2"]).count()
     df5: pd.DataFrame = df.groupby(by=["col1", "col2"]).filter(lambda x: x["col1"] > 0)
     df6: pd.DataFrame = df.groupby(by=["col1", "col2"]).nunique()
-    df7: pd.DataFrame = df.groupby(by="col1").apply(sum)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated",
+        lower="2.0.99",
+    ):
+        df7: pd.DataFrame = df.groupby(by="col1").apply(sum)
     df8: pd.DataFrame = df.groupby("col1").transform("sum")
     s1: pd.Series = df.set_index("col1")["col2"]
     s2: pd.Series = s1.groupby("col1").transform("sum")
@@ -1454,9 +1465,19 @@ def test_types_regressions() -> None:
 
     # https://github.com/microsoft/python-type-stubs/issues/115
     df = pd.DataFrame({"A": [1, 2, 3], "B": [5, 6, 7]})
-    pd.DatetimeIndex(
-        data=df["A"], tz=None, normalize=False, closed=None, ambiguous="NaT", copy=True
-    )
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="The 'closed' keyword in DatetimeIndex construction is deprecated",
+        lower="2.0.99",
+    ):
+        pd.DatetimeIndex(
+            data=df["A"],
+            tz=None,
+            normalize=False,
+            closed=None,
+            ambiguous="NaT",
+            copy=True,
+        )
 
 
 def test_read_csv() -> None:
@@ -2022,35 +2043,41 @@ def test_groupby_apply() -> None:
     def sum_mean(x: pd.DataFrame) -> float:
         return x.sum().mean()
 
-    check(assert_type(df.groupby("col1").apply(sum_mean), pd.Series), pd.Series)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated",
+        lower="2.0.99",
+    ):
+        check(assert_type(df.groupby("col1").apply(sum_mean), pd.Series), pd.Series)
 
-    lfunc: Callable[[pd.DataFrame], float] = lambda x: x.sum().mean()
-    check(
-        assert_type(df.groupby("col1").apply(lfunc), pd.Series),
-        pd.Series,
-    )
+        lfunc: Callable[[pd.DataFrame], float] = lambda x: x.sum().mean()
+        check(
+            assert_type(df.groupby("col1").apply(lfunc), pd.Series),
+            pd.Series,
+        )
 
-    def sum_to_list(x: pd.DataFrame) -> list:
-        return x.sum().tolist()
+        def sum_to_list(x: pd.DataFrame) -> list:
+            return x.sum().tolist()
 
-    check(assert_type(df.groupby("col1").apply(sum_to_list), pd.Series), pd.Series)
+        check(assert_type(df.groupby("col1").apply(sum_to_list), pd.Series), pd.Series)
 
-    def sum_to_series(x: pd.DataFrame) -> pd.Series:
-        return x.sum()
+        def sum_to_series(x: pd.DataFrame) -> pd.Series:
+            return x.sum()
 
-    check(
-        assert_type(df.groupby("col1").apply(sum_to_series), pd.DataFrame), pd.DataFrame
-    )
+        check(
+            assert_type(df.groupby("col1").apply(sum_to_series), pd.DataFrame),
+            pd.DataFrame,
+        )
 
-    def sample_to_df(x: pd.DataFrame) -> pd.DataFrame:
-        return x.sample()
+        def sample_to_df(x: pd.DataFrame) -> pd.DataFrame:
+            return x.sample()
 
-    check(
-        assert_type(
-            df.groupby("col1", group_keys=False).apply(sample_to_df), pd.DataFrame
-        ),
-        pd.DataFrame,
-    )
+        check(
+            assert_type(
+                df.groupby("col1", group_keys=False).apply(sample_to_df), pd.DataFrame
+            ),
+            pd.DataFrame,
+        )
 
 
 def test_resample() -> None:

tests/test_series.py

@@ -450,7 +450,12 @@ def square(x: float) -> float:
     def makeseries(x: float) -> pd.Series:
         return pd.Series([x, 2 * x])
 
-    check(assert_type(s.apply(makeseries), pd.DataFrame), pd.DataFrame)
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="Returning a DataFrame from Series.apply when the supplied functionreturns a Series is deprecated",
+        lower="2.0.99",
+    ):
+        check(assert_type(s.apply(makeseries), pd.DataFrame), pd.DataFrame)
 
     # GH 293
 

tests/test_timefuncs.py

@@ -22,6 +22,8 @@
 from pandas._libs.tslibs import BaseOffset
 from pandas._libs.tslibs.offsets import DateOffset
 
+from tests import pytest_warns_bounded
+
 if TYPE_CHECKING:
     from pandas._typing import FulldatetimeDict
 else:
@@ -361,7 +363,13 @@ def test_series_dt_accessors() -> None:
     check(assert_type(s0.dt.freq, Optional[str]), str)
     check(assert_type(s0.dt.isocalendar(), pd.DataFrame), pd.DataFrame)
     check(assert_type(s0.dt.to_period("D"), "PeriodSeries"), pd.Series, pd.Period)
-    check(assert_type(s0.dt.to_pydatetime(), np.ndarray), np.ndarray, dt.datetime)
+
+    with pytest_warns_bounded(
+        FutureWarning,
+        match="The behavior of DatetimeProperties.to_pydatetime is deprecated",
+        lower="2.0.99",
+    ):
+        check(assert_type(s0.dt.to_pydatetime(), np.ndarray), np.ndarray, dt.datetime)
     s0_local = s0.dt.tz_localize("UTC")
     check(
         assert_type(s0_local, "TimestampSeries"),