def test_notna_notnull(notna_f): assert notna_f(1.) assert not notna_f(None) assert not notna_f(np.NaN) with cf.option_context("mode.use_inf_as_na", False): assert notna_f(np.inf) assert notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.all() with cf.option_context("mode.use_inf_as_na", True): assert not notna_f(np.inf) assert not notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.sum() == 2 with cf.option_context("mode.use_inf_as_na", False): for s in [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries(), tm.makeTimeSeries(), tm.makePeriodSeries()]: assert (isinstance(notna_f(s), Series))
def test_notna_notnull(notna_f): assert notna_f(1.0) assert not notna_f(None) assert not notna_f(np.NaN) with cf.option_context("mode.use_inf_as_na", False): assert notna_f(np.inf) assert notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.all() with cf.option_context("mode.use_inf_as_na", True): assert not notna_f(np.inf) assert not notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.sum() == 2 with cf.option_context("mode.use_inf_as_na", False): for s in [ tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries(), tm.makeTimeSeries(), tm.makePeriodSeries(), ]: assert isinstance(notna_f(s), Series)
def test_matplotlib_formatters(self): units = pytest.importorskip("matplotlib.units") # Can't make any assertion about the start state. # We we check that toggling converters off remvoes it, and toggling it # on restores it. with cf.option_context("plotting.matplotlib.register_converters", True): with cf.option_context("plotting.matplotlib.register_converters", False): assert Timestamp not in units.registry assert Timestamp in units.registry
def test_display_max_dir_items(self): # display.max_dir_items increaes the number of columns that are in __dir__. columns = ["a" + str(i) for i in range(420)] values = [range(420), range(420)] df = DataFrame(values, columns=columns) # The default value for display.max_dir_items is 100 assert "a99" in dir(df) assert "a100" not in dir(df) with option_context("display.max_dir_items", 300): df = DataFrame(values, columns=columns) assert "a299" in dir(df) assert "a300" not in dir(df) with option_context("display.max_dir_items", None): df = DataFrame(values, columns=columns) assert "a419" in dir(df)
def test_matplotlib_formatters(self): units = pytest.importorskip("matplotlib.units") assert Timestamp in units.registry ctx = cf.option_context("plotting.matplotlib.register_converters", False) with ctx: assert Timestamp not in units.registry assert Timestamp in units.registry
def test_matplotlib_formatters(self): units = pytest.importorskip("matplotlib.units") assert Timestamp in units.registry ctx = cf.option_context("plotting.matplotlib.register_converters", False) with ctx: assert Timestamp not in units.registry assert Timestamp in units.registry
def test_notna_notnull(notna_f): assert notna_f(1.0) assert not notna_f(None) assert not notna_f(np.NaN) with cf.option_context("mode.use_inf_as_na", False): assert notna_f(np.inf) assert notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.all() with cf.option_context("mode.use_inf_as_na", True): assert not notna_f(np.inf) assert not notna_f(-np.inf) arr = np.array([1.5, np.inf, 3.5, -np.inf]) result = notna_f(arr) assert result.sum() == 2
def test_ambiguous_width(self): adj = fmt.EastAsianTextAdjustment() assert adj.len("¡¡ab") == 4 with cf.option_context("display.unicode.ambiguous_as_wide", True): adj = fmt.EastAsianTextAdjustment() assert adj.len("¡¡ab") == 6 data = [["あ", "b", "c"], ["dd", "ええ", "ff"], ["ggg", "¡¡ab", "いいい"]] expected = "あ dd ggg \nb ええ ¡¡ab\nc ff いいい" adjoined = adj.adjoin(2, *data) assert adjoined == expected
def test_ambiguous_width(self): adj = fmt.EastAsianTextAdjustment() assert adj.len('¡¡ab') == 4 with cf.option_context('display.unicode.ambiguous_as_wide', True): adj = fmt.EastAsianTextAdjustment() assert adj.len('¡¡ab') == 6 data = [['あ', 'b', 'c'], ['dd', 'ええ', 'ff'], ['ggg', '¡¡ab', 'いいい']] expected = 'あ dd ggg \nb ええ ¡¡ab\nc ff いいい' adjoined = adj.adjoin(2, *data) assert adjoined == expected
def test_ambiguous_width(self): adj = fmt.EastAsianTextAdjustment() assert adj.len('¡¡ab') == 4 with cf.option_context('display.unicode.ambiguous_as_wide', True): adj = fmt.EastAsianTextAdjustment() assert adj.len('¡¡ab') == 6 data = [['あ', 'b', 'c'], ['dd', 'ええ', 'ff'], ['ggg', '¡¡ab', 'いいい']] expected = 'あ dd ggg \nb ええ ¡¡ab\nc ff いいい' adjoined = adj.adjoin(2, *data) assert adjoined == expected
def test_isna_old_datetimelike(self): # isna_old should work for dt64tz, td64, and period, not just tznaive dti = pd.date_range("2016-01-01", periods=3) dta = dti._data dta[-1] = pd.NaT expected = np.array([False, False, True], dtype=bool) objs = [dta, dta.tz_localize("US/Eastern"), dta - dta, dta.to_period("D")] for obj in objs: with cf.option_context("mode.use_inf_as_na", True): result = pd.isna(obj) tm.assert_numpy_array_equal(result, expected)
def test_option_no_warning(self): pytest.importorskip("matplotlib.pyplot") ctx = cf.option_context("plotting.matplotlib.register_converters", False) plt = pytest.importorskip("matplotlib.pyplot") s = Series(range(12), index=date_range("2017", periods=12)) _, ax = plt.subplots() # Test without registering first, no warning with ctx: ax.plot(s.index, s.values) # Now test with registering register_matplotlib_converters() with ctx: ax.plot(s.index, s.values)
def test_option_no_warning(self): pytest.importorskip("matplotlib.pyplot") ctx = cf.option_context("plotting.matplotlib.register_converters", False) plt = pytest.importorskip("matplotlib.pyplot") s = Series(range(12), index=date_range("2017", periods=12)) _, ax = plt.subplots() # Test without registering first, no warning with ctx: # GH#30588 DeprecationWarning from 2D indexing on Index with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False): ax.plot(s.index, s.values) # Now test with registering register_matplotlib_converters() with ctx: with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False): ax.plot(s.index, s.values)
def test_option_no_warning(self): pytest.importorskip("matplotlib.pyplot") ctx = cf.option_context("plotting.matplotlib.register_converters", False) plt = pytest.importorskip("matplotlib.pyplot") s = Series(range(12), index=date_range('2017', periods=12)) _, ax = plt.subplots() converter._WARN = True # Test without registering first, no warning with ctx: with tm.assert_produces_warning(None) as w: ax.plot(s.index, s.values) assert len(w) == 0 # Now test with registering converter._WARN = True register_matplotlib_converters() with ctx: with tm.assert_produces_warning(None) as w: ax.plot(s.index, s.values) assert len(w) == 0
def test_option_no_warning(self): pytest.importorskip("matplotlib.pyplot") ctx = cf.option_context("plotting.matplotlib.register_converters", False) plt = pytest.importorskip("matplotlib.pyplot") s = Series(range(12), index=date_range("2017", periods=12)) _, ax = plt.subplots() converter._WARN = True # Test without registering first, no warning with ctx: with tm.assert_produces_warning(None) as w: ax.plot(s.index, s.values) assert len(w) == 0 # Now test with registering converter._WARN = True register_matplotlib_converters() with ctx: with tm.assert_produces_warning(None) as w: ax.plot(s.index, s.values) assert len(w) == 0
def test_string_categorical_index_repr(self): # short idx = pd.CategoricalIndex(["a", "bb", "ccc"]) expected = """CategoricalIndex(['a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(["a", "bb", "ccc"] * 10) expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(["a", "bb", "ccc"] * 100) expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', ... 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list("abcdefghijklmmo")) expected = """CategoricalIndex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'm', 'o'], categories=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # short idx = pd.CategoricalIndex(["あ", "いい", "ううう"]) expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 10) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 100) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', ... 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list("あいうえおかきくけこさしすせそ")) expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し', 'す', 'せ', 'そ'], categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # Emable Unicode option ----------------------------------------- with cf.option_context("display.unicode.east_asian_width", True): # short idx = pd.CategoricalIndex(["あ", "いい", "ううう"]) expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 10) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 100) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', ... 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list("あいうえおかきくけこさしすせそ")) expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し', 'す', 'せ', 'そ'], categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected
def test_string_categorical_index_repr(self): # short idx = pd.CategoricalIndex(['a', 'bb', 'ccc']) expected = """CategoricalIndex(['a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 10) expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 100) expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', ... 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list('abcdefghijklmmo')) expected = """CategoricalIndex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'm', 'o'], categories=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # short idx = pd.CategoricalIndex(['あ', 'いい', 'ううう']) expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(['あ', 'いい', 'ううう'] * 10) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(['あ', 'いい', 'ううう'] * 100) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', ... 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list('あいうえおかきくけこさしすせそ')) expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し', 'す', 'せ', 'そ'], categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # Emable Unicode option ----------------------------------------- with cf.option_context('display.unicode.east_asian_width', True): # short idx = pd.CategoricalIndex(['あ', 'いい', 'ううう']) expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # multiple lines idx = pd.CategoricalIndex(['あ', 'いい', 'ううう'] * 10) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected # truncated idx = pd.CategoricalIndex(['あ', 'いい', 'ううう'] * 100) expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', ... 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)""" # noqa assert repr(idx) == expected # larger categories idx = pd.CategoricalIndex(list('あいうえおかきくけこさしすせそ')) expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し', 'す', 'せ', 'そ'], categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa assert repr(idx) == expected
def test_string_index_repr_with_unicode_option(self, index, expected): # Enable Unicode option ----------------------------------------- with cf.option_context("display.unicode.east_asian_width", True): result = repr(index) assert result == expected
def test_repr_summary(self): with cf.option_context("display.max_seq_items", 10): result = repr(Index(np.arange(1000))) assert len(result) < 200 assert "..." in result
def test_null_check_is_series(null_func, ser): with cf.option_context("mode.use_inf_as_na", False): assert isinstance(null_func(ser), Series)