Silence test time deprecation warnings

pandas/tests/arrays/sparse/test_arithmetics.py

@@ -9,6 +9,7 @@
 
 
 @pytest.mark.filterwarnings("ignore:Sparse:FutureWarning")
+@pytest.mark.filterwarnings("ignore:Series:FutureWarning")
 class TestSparseArrayArithmetics:
 
     _base = np.array

pandas/tests/arrays/test_integer.py

@@ -659,6 +659,7 @@ def test_cross_type_arithmetic():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('op', ['sum', 'min', 'max', 'prod'])
 def test_preserve_dtypes(op):
     # TODO(#22346): preserve Int64 dtype
@@ -684,6 +685,7 @@ def test_preserve_dtypes(op):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('op', ['mean'])
 def test_reduce_to_float(op):
     # some reduce ops always return float, even if the result

pandas/tests/extension/test_datetime.py

@@ -232,6 +232,7 @@ class TestSetitem(BaseDatetimeTests, base.BaseSetitemTests):
     pass
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestGroupby(BaseDatetimeTests, base.BaseGroupbyTests):
     pass
 

pandas/tests/extension/test_integer.py

@@ -204,6 +204,7 @@ class TestCasting(base.BaseCastingTests):
     pass
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestGroupby(base.BaseGroupbyTests):
     pass
 

pandas/tests/extension/test_interval.py

@@ -90,6 +90,7 @@ class TestGetitem(BaseInterval, base.BaseGetitemTests):
     pass
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestGrouping(BaseInterval, base.BaseGroupbyTests):
     pass
 

pandas/tests/extension/test_numpy.py

@@ -181,6 +181,7 @@ def test_take_series(self, data):
         super().test_take_series(data)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestGroupby(BaseNumPyTests, base.BaseGroupbyTests):
     @skip_nested
     def test_groupby_extension_apply(

pandas/tests/extension/test_period.py

@@ -151,6 +151,7 @@ class TestSetitem(BasePeriodTests, base.BaseSetitemTests):
     pass
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestGroupby(BasePeriodTests, base.BaseGroupbyTests):
     pass
 

pandas/tests/frame/test_analytics.py

@@ -948,6 +948,7 @@ def test_sem(self, datetime_frame):
             result = nanops.nansem(arr, axis=0)
             assert not (result < 0).any()
 
+    @pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
     @td.skip_if_no_scipy
     def test_kurt(self):
         index = MultiIndex(levels=[['bar'], ['one', 'two', 'three'], [0, 1]],

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -21,6 +21,7 @@ def test_agg_regression1(tsframe):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_must_agg(df):
     grouped = df.groupby('A')['C']
 
@@ -31,6 +32,7 @@ def test_agg_must_agg(df):
         grouped.agg(lambda x: x.index[:2])
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_ser_multi_key(df):
     # TODO(wesm): unused
     ser = df.C  # noqa
@@ -145,6 +147,7 @@ def test_aggregate_str_func(tsframe, groupbyfunc):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_aggregate_item_by_item(df):
     grouped = df.groupby('A')
 
@@ -172,6 +175,7 @@ def aggfun(ser):
     assert len(result) == 0
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_wrap_agg_out(three_group):
     grouped = three_group.groupby(['A', 'B'])
 
@@ -210,6 +214,7 @@ def test_multiple_functions_tuples_and_non_tuples(df):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_multiple_functions_too_many_lambdas(df):
     grouped = df.groupby('A')
     funcs = ['mean', lambda x: x.mean(), lambda x: x.std()]
@@ -219,6 +224,7 @@ def test_agg_multiple_functions_too_many_lambdas(df):
         grouped.agg(funcs)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_more_flexible_frame_multi_function(df):
     grouped = df.groupby('A')
 
@@ -287,6 +293,7 @@ def test_multi_function_flexible_mix(df):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_groupby_agg_coercing_bools():
     # issue 14873
     dat = pd.DataFrame(
@@ -316,6 +323,7 @@ def test_order_aggregate_multiple_funcs():
     tm.assert_index_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('dtype', [np.int64, np.uint64])
 @pytest.mark.parametrize('how', ['first', 'last', 'min',
                                  'max', 'mean', 'median'])
@@ -329,6 +337,7 @@ def test_uint64_type_handling(dtype, how):
     tm.assert_frame_equal(result, expected, check_exact=True)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 class TestNamedAggregation:
 
     def test_agg_relabel(self):

pandas/tests/groupby/aggregate/test_cython.py

@@ -128,6 +128,7 @@ def test_cython_fail_agg():
     tm.assert_series_equal(summed, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('op, targop', [
     ('mean', np.mean),
     ('median', np.median),
@@ -148,6 +149,7 @@ def test__cython_agg_general(op, targop):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('op, targop', [
     ('mean', np.mean),
     ('median', lambda x: np.median(x) if len(x) > 0 else np.nan),

pandas/tests/groupby/aggregate/test_other.py

@@ -19,6 +19,7 @@
 from pandas.io.formats.printing import pprint_thing
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_api():
     # GH 6337
     # http://stackoverflow.com/questions/21706030/pandas-groupby-agg-function-column-dtype-error
@@ -83,6 +84,7 @@ def test_agg_period_index():
     list(grouped)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_dict_parameter_cast_result_dtypes():
     # GH 12821
 
@@ -121,6 +123,7 @@ def test_agg_dict_parameter_cast_result_dtypes():
     tm.assert_series_equal(grouped.time.count(), exp)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_cast_results_dtypes():
     # similar to GH12821
     # xref #11444
@@ -291,6 +294,7 @@ def test_agg_nested_dicts():
     tm.assert_frame_equal(result, expected, check_like=True)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_item_by_item_raise_typeerror():
     df = DataFrame(np.random.randint(10, size=(20, 10)))
 
@@ -312,6 +316,7 @@ def test_series_agg_multikey():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_series_agg_multi_pure_python():
     data = DataFrame(
         {'A': ['foo', 'foo', 'foo', 'foo', 'bar', 'bar', 'bar', 'bar',
@@ -333,6 +338,7 @@ def bad(x):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_consistency():
     # agg with ([]) and () not consistent
     # GH 6715
@@ -356,6 +362,7 @@ def P1(a):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_callables():
     # GH 7929
     df = DataFrame({'foo': [1, 2], 'bar': [3, 4]}).astype(np.int64)
@@ -396,6 +403,7 @@ def test_agg_over_numpy_arrays():
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_timezone_round_trip():
     # GH 15426
     ts = pd.Timestamp("2016-01-01 12:00:00", tz='US/Pacific')
@@ -427,6 +435,7 @@ def test_agg_timezone_round_trip():
     assert ts == grouped.apply(lambda x: x.iloc[-1])[0]
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_sum_uint64_overflow():
     # see gh-14758
     # Convert to uint64 and don't overflow
@@ -447,6 +456,7 @@ def test_sum_uint64_overflow():
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize("structure, expected", [
     (tuple, pd.DataFrame({'C': {(1, 1): (1, 1, 1), (3, 4): (3, 4, 4)}})),
     (list, pd.DataFrame({'C': {(1, 1): [1, 1, 1], (3, 4): [3, 4, 4]}})),
@@ -465,6 +475,7 @@ def test_agg_structs_dataframe(structure, expected):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize("structure, expected", [
     (tuple, pd.Series([(1, 1, 1), (3, 4, 4)], index=[1, 3], name='C')),
     (list, pd.Series([[1, 1, 1], [3, 4, 4]], index=[1, 3], name='C')),
@@ -500,6 +511,7 @@ def test_agg_category_nansum(observed):
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_list_like_func():
     # GH 18473
     df = pd.DataFrame({'A': [str(x) for x in range(3)],
@@ -511,6 +523,7 @@ def test_agg_list_like_func():
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_agg_lambda_with_timezone():
     # GH 23683
     df = pd.DataFrame({

pandas/tests/groupby/test_apply.py

@@ -259,6 +259,7 @@ def desc3(group):
     assert result3.index.names == ('A', 'B', None)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_apply_series_to_frame():
     def f(piece):
         with np.errstate(invalid='ignore'):
@@ -277,6 +278,7 @@ def f(piece):
     tm.assert_index_equal(result.index, ts.index)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_apply_series_yield_constant(df):
     result = df.groupby(['A', 'B'])['C'].apply(len)
     assert result.index.names[:2] == ('A', 'B')
@@ -301,6 +303,7 @@ def test_apply_frame_to_series(df):
     tm.assert_numpy_array_equal(result.values, expected.values)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_apply_frame_concat_series():
     def trans(group):
         return group.groupby('B')['C'].sum().sort_values()[:2]
@@ -319,6 +322,7 @@ def trans2(group):
     assert result.name == 'C'
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_apply_transform(ts):
     grouped = ts.groupby(lambda x: x.month)
     result = grouped.apply(lambda x: x * 2)

pandas/tests/groupby/test_categorical.py

@@ -30,6 +30,7 @@ def f(a):
     return result.reindex(index).sort_index()
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_apply_use_categorical_name(df):
     cats = qcut(df.C, 4)
 
@@ -43,6 +44,7 @@ def get_stats(group):
     assert result.index.names[0] == 'C'
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 def test_basic():
 
     cats = Categorical(["a", "a", "a", "b", "b", "b", "c", "c", "c"],
@@ -991,6 +993,7 @@ def df_cat(df):
     return df_cat
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('operation, kwargs', [
     ('agg', dict(dtype='category')),
     ('apply', dict())])
@@ -1006,6 +1009,7 @@ def test_seriesgroupby_observed_true(df_cat, operation, kwargs):
     assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize('operation', ['agg', 'apply'])
 @pytest.mark.parametrize('observed', [False, None])
 def test_seriesgroupby_observed_false_or_none(df_cat, observed, operation):
@@ -1022,6 +1026,7 @@ def test_seriesgroupby_observed_false_or_none(df_cat, observed, operation):
     assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:NDFrame:FutureWarning")
 @pytest.mark.parametrize("observed, index, data", [
     (True, MultiIndex.from_tuples(
         [('foo', 'one', 'min'), ('foo', 'one', 'max'),