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Python SparseSeries.dropna方法代码示例

本文整理汇总了Python中pandas.sparse.api.SparseSeries.dropna方法的典型用法代码示例。如果您正苦于以下问题:Python SparseSeries.dropna方法的具体用法?Python SparseSeries.dropna怎么用?Python SparseSeries.dropna使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在pandas.sparse.api.SparseSeries的用法示例。


在下文中一共展示了SparseSeries.dropna方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: TestSparseSeries

# 需要导入模块: from pandas.sparse.api import SparseSeries [as 别名]
# 或者: from pandas.sparse.api.SparseSeries import dropna [as 别名]

#.........这里部分代码省略.........

    def test_reductions(self):
        def _compare_with_dense(obj, op):
            sparse_result = getattr(obj, op)()
            series = obj.to_dense()
            dense_result = getattr(series, op)()
            self.assertEqual(sparse_result, dense_result)

        to_compare = ['count', 'sum', 'mean', 'std', 'var', 'skew']

        def _compare_all(obj):
            for op in to_compare:
                _compare_with_dense(obj, op)

        _compare_all(self.bseries)

        self.bseries.sp_values[5:10] = np.NaN
        _compare_all(self.bseries)

        _compare_all(self.zbseries)
        self.zbseries.sp_values[5:10] = np.NaN
        _compare_all(self.zbseries)

        series = self.zbseries.copy()
        series.fill_value = 2
        _compare_all(series)

        nonna = Series(np.random.randn(20)).to_sparse()
        _compare_all(nonna)

        nonna2 = Series(np.random.randn(20)).to_sparse(fill_value=0)
        _compare_all(nonna2)

    def test_dropna(self):
        sp = SparseSeries([0, 0, 0, nan, nan, 5, 6], fill_value=0)

        sp_valid = sp.valid()

        expected = sp.to_dense().valid()
        expected = expected[expected != 0]

        tm.assert_almost_equal(sp_valid.values, expected.values)
        self.assertTrue(sp_valid.index.equals(expected.index))
        self.assertEqual(len(sp_valid.sp_values), 2)

        result = self.bseries.dropna()
        expected = self.bseries.to_dense().dropna()
        self.assertNotIsInstance(result, SparseSeries)
        tm.assert_series_equal(result, expected)

    def test_homogenize(self):
        def _check_matches(indices, expected):
            data = {}
            for i, idx in enumerate(indices):
                data[i] = SparseSeries(idx.to_int_index().indices,
                                       sparse_index=idx)
            homogenized = spf.homogenize(data)

            for k, v in compat.iteritems(homogenized):
                assert (v.sp_index.equals(expected))

        indices1 = [BlockIndex(10, [2], [7]), BlockIndex(10, [1, 6], [3, 4]),
                    BlockIndex(10, [0], [10])]
        expected1 = BlockIndex(10, [2, 6], [2, 3])
        _check_matches(indices1, expected1)
开发者ID:jcfr,项目名称:pandas,代码行数:69,代码来源:test_series.py

示例2: TestSparseSeries

# 需要导入模块: from pandas.sparse.api import SparseSeries [as 别名]
# 或者: from pandas.sparse.api.SparseSeries import dropna [as 别名]

#.........这里部分代码省略.........
        pass

    def test_fillna(self):
        pass

    def test_groupby(self):
        pass

    def test_reductions(self):
        def _compare_with_dense(obj, op):
            sparse_result = getattr(obj, op)()
            series = obj.to_dense()
            dense_result = getattr(series, op)()
            self.assertEquals(sparse_result, dense_result)

        to_compare = ["count", "sum", "mean", "std", "var", "skew"]

        def _compare_all(obj):
            for op in to_compare:
                _compare_with_dense(obj, op)

        _compare_all(self.bseries)
        self.bseries.sp_values[5:10] = np.NaN
        _compare_all(self.bseries)

        _compare_all(self.zbseries)
        self.zbseries.sp_values[5:10] = np.NaN
        _compare_all(self.zbseries)

        series = self.zbseries.copy()
        series.fill_value = 2
        _compare_all(series)

    def test_dropna(self):
        sp = SparseSeries([0, 0, 0, nan, nan, 5, 6], fill_value=0)

        sp_valid = sp.valid()
        assert_almost_equal(sp_valid.values, sp.to_dense().valid().values)
        self.assert_(sp_valid.index.equals(sp.to_dense().valid().index))
        self.assertEquals(len(sp_valid.sp_values), 2)

        result = self.bseries.dropna()
        expected = self.bseries.to_dense().dropna()
        self.assert_(not isinstance(result, SparseSeries))
        tm.assert_series_equal(result, expected)

    def test_homogenize(self):
        def _check_matches(indices, expected):
            data = {}
            for i, idx in enumerate(indices):
                data[i] = SparseSeries(idx.to_int_index().indices, sparse_index=idx)
            homogenized = spf.homogenize(data)

            for k, v in homogenized.iteritems():
                assert v.sp_index.equals(expected)

        indices1 = [BlockIndex(10, [2], [7]), BlockIndex(10, [1, 6], [3, 4]), BlockIndex(10, [0], [10])]
        expected1 = BlockIndex(10, [2, 6], [2, 3])
        _check_matches(indices1, expected1)

        indices2 = [BlockIndex(10, [2], [7]), BlockIndex(10, [2], [7])]
        expected2 = indices2[0]
        _check_matches(indices2, expected2)

        # must have NaN fill value
        data = {"a": SparseSeries(np.arange(7), sparse_index=expected2, fill_value=0)}
开发者ID:klausz,项目名称:pandas,代码行数:70,代码来源:test_sparse.py


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