Python testing.makeStringSeries方法代码示例

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_transpose(self):
        msg = (r"transpose\(\) got multiple values for "
               r"keyword argument 'axes'")
        for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
                  tm.makeObjectSeries()]:
            # calls implementation in pandas/core/base.py
            tm.assert_series_equal(s.transpose(), s)
        for df in [tm.makeTimeDataFrame()]:
            tm.assert_frame_equal(df.transpose().transpose(), df)

        with catch_warnings(record=True):
            simplefilter("ignore", FutureWarning)
            for p in [tm.makePanel()]:
                tm.assert_panel_equal(p.transpose(2, 0, 1)
                                      .transpose(1, 2, 0), p)
                with pytest.raises(TypeError, match=msg):
                    p.transpose(2, 0, 1, axes=(2, 0, 1)) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_take(self):
        indices = [1, 5, -2, 6, 3, -1]
        for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
                  tm.makeObjectSeries()]:
            out = s.take(indices)
            expected = Series(data=s.values.take(indices),
                              index=s.index.take(indices), dtype=s.dtype)
            tm.assert_series_equal(out, expected)
        for df in [tm.makeTimeDataFrame()]:
            out = df.take(indices)
            expected = DataFrame(data=df.values.take(indices, axis=0),
                                 index=df.index.take(indices),
                                 columns=df.columns)
            tm.assert_frame_equal(out, expected)

        indices = [-3, 2, 0, 1]
        with catch_warnings(record=True):
            simplefilter("ignore", FutureWarning)
            for p in [tm.makePanel()]:
                out = p.take(indices)
                expected = Panel(data=p.values.take(indices, axis=0),
                                 items=p.items.take(indices),
                                 major_axis=p.major_axis,
                                 minor_axis=p.minor_axis)
                tm.assert_panel_equal(out, expected) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_var_std(self):
        string_series = tm.makeStringSeries().rename('series')
        datetime_series = tm.makeTimeSeries().rename('ts')

        alt = lambda x: np.std(x, ddof=1)
        self._check_stat_op('std', alt, string_series)

        alt = lambda x: np.var(x, ddof=1)
        self._check_stat_op('var', alt, string_series)

        result = datetime_series.std(ddof=4)
        expected = np.std(datetime_series.values, ddof=4)
        tm.assert_almost_equal(result, expected)

        result = datetime_series.var(ddof=4)
        expected = np.var(datetime_series.values, ddof=4)
        tm.assert_almost_equal(result, expected)

        # 1 - element series with ddof=1
        s = datetime_series.iloc[[0]]
        result = s.var(ddof=1)
        assert pd.isna(result)

        result = s.std(ddof=1)
        assert pd.isna(result) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_sem(self):
        string_series = tm.makeStringSeries().rename('series')
        datetime_series = tm.makeTimeSeries().rename('ts')

        alt = lambda x: np.std(x, ddof=1) / np.sqrt(len(x))
        self._check_stat_op('sem', alt, string_series)

        result = datetime_series.sem(ddof=4)
        expected = np.std(datetime_series.values,
                          ddof=4) / np.sqrt(len(datetime_series.values))
        tm.assert_almost_equal(result, expected)

        # 1 - element series with ddof=1
        s = datetime_series.iloc[[0]]
        result = s.sem(ddof=1)
        assert pd.isna(result) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_skew(self):
        from scipy.stats import skew

        string_series = tm.makeStringSeries().rename('series')

        alt = lambda x: skew(x, bias=False)
        self._check_stat_op('skew', alt, string_series)

        # test corner cases, skew() returns NaN unless there's at least 3
        # values
        min_N = 3
        for i in range(1, min_N + 1):
            s = Series(np.ones(i))
            df = DataFrame(np.ones((i, i)))
            if i < min_N:
                assert np.isnan(s.skew())
                assert np.isnan(df.skew()).all()
            else:
                assert 0 == s.skew()
                assert (df.skew() == 0).all() 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_transpose(self):
        msg = (r"transpose\(\) got multiple values for "
               r"keyword argument 'axes'")
        for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
                  tm.makeObjectSeries()]:
            # calls implementation in pandas/core/base.py
            tm.assert_series_equal(s.transpose(), s)
        for df in [tm.makeTimeDataFrame()]:
            tm.assert_frame_equal(df.transpose().transpose(), df)

        with catch_warnings(record=True):
            for p in [tm.makePanel()]:
                tm.assert_panel_equal(p.transpose(2, 0, 1)
                                      .transpose(1, 2, 0), p)
                tm.assert_raises_regex(TypeError, msg, p.transpose,
                                       2, 0, 1, axes=(2, 0, 1)) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_take(self):
        indices = [1, 5, -2, 6, 3, -1]
        for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
                  tm.makeObjectSeries()]:
            out = s.take(indices)
            expected = Series(data=s.values.take(indices),
                              index=s.index.take(indices), dtype=s.dtype)
            tm.assert_series_equal(out, expected)
        for df in [tm.makeTimeDataFrame()]:
            out = df.take(indices)
            expected = DataFrame(data=df.values.take(indices, axis=0),
                                 index=df.index.take(indices),
                                 columns=df.columns)
            tm.assert_frame_equal(out, expected)

        indices = [-3, 2, 0, 1]
        with catch_warnings(record=True):
            for p in [tm.makePanel()]:
                out = p.take(indices)
                expected = Panel(data=p.values.take(indices, axis=0),
                                 items=p.items.take(indices),
                                 major_axis=p.major_axis,
                                 minor_axis=p.minor_axis)
                tm.assert_panel_equal(out, expected) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def setUp(self):
        self.dirpath = tm.get_data_path()

        self.ts = tm.makeTimeSeries()
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series'

        self.objSeries = tm.makeObjectSeries()
        self.objSeries.name = 'objects'

        self.empty_series = Series([], index=[])
        self.empty_frame = DataFrame({})

        self.frame = _frame.copy()
        self.frame2 = _frame2.copy()
        self.intframe = _intframe.copy()
        self.tsframe = _tsframe.copy()
        self.mixed_frame = _mixed_frame.copy() 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def setup_method(self, method):
        self.dirpath = tm.get_data_path()

        self.ts = tm.makeTimeSeries()
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series'

        self.objSeries = tm.makeObjectSeries()
        self.objSeries.name = 'objects'

        self.empty_series = Series([], index=[])
        self.empty_frame = DataFrame({})

        self.frame = _frame.copy()
        self.frame2 = _frame2.copy()
        self.intframe = _intframe.copy()
        self.tsframe = _tsframe.copy()
        self.mixed_frame = _mixed_frame.copy()
        self.categorical = _cat_frame.copy() 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def setup_method(self, method):
        TestPlotBase.setup_method(self, method)
        import matplotlib as mpl
        mpl.rcdefaults()

        self.ts = tm.makeTimeSeries()
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series'

        self.iseries = tm.makePeriodSeries()
        self.iseries.name = 'iseries' 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def setup_method(self):
        self.ts = tm.makeTimeSeries()  # Was at top level in test_series
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series' 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_neg(self):
        ser = tm.makeStringSeries()
        ser.name = 'series'
        assert_series_equal(-ser, -1 * ser) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def test_invert(self):
        ser = tm.makeStringSeries()
        ser.name = 'series'
        assert_series_equal(-(ser < 0), ~(ser < 0)) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
def series(self):
        series = tm.makeStringSeries()
        series.name = 'series'
        return series 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeStringSeries [as 别名]
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))