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)