本文整理匯總了Python中pandas.core.sparse.SparseSeries.cumsum方法的典型用法代碼示例。如果您正苦於以下問題：Python SparseSeries.cumsum方法的具體用法？Python SparseSeries.cumsum怎麽用？Python SparseSeries.cumsum使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.core.sparse.SparseSeries的用法示例。
在下文中一共展示了SparseSeries.cumsum方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: TestSparseSeries
# 需要導入模塊: from pandas.core.sparse import SparseSeries [as 別名]
# 或者: from pandas.core.sparse.SparseSeries import cumsum [as 別名]
#.........這裏部分代碼省略.........
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_valid(self):
sp = SparseSeries([0, 0, 0, nan, nan, 5, 6],
fill_value=0)
sp_valid = sp.valid()
assert_almost_equal(sp_valid, sp.to_dense().valid())
self.assert_(sp_valid.index.equals(sp.to_dense().valid().index))
self.assertEquals(len(sp_valid.sp_values), 2)
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 = spm.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)}
nose.tools.assert_raises(Exception, spm.homogenize, data)
def test_fill_value_corner(self):
cop = self.zbseries.copy()
cop.fill_value = 0
result = self.bseries / cop
self.assert_(np.isnan(result.fill_value))
cop2 = self.zbseries.copy()
cop2.fill_value = 1
result = cop2 / cop
self.assert_(np.isnan(result.fill_value))
def test_shift(self):
series = SparseSeries([nan, 1., 2., 3., nan, nan],
index=np.arange(6))
shifted = series.shift(0)
self.assert_(shifted is not series)
assert_sp_series_equal(shifted, series)
f = lambda s: s.shift(1)
_dense_series_compare(series, f)
f = lambda s: s.shift(-2)
_dense_series_compare(series, f)
series = SparseSeries([nan, 1., 2., 3., nan, nan],
index=DateRange('1/1/2000', periods=6))
f = lambda s: s.shift(2, timeRule='WEEKDAY')
_dense_series_compare(series, f)
f = lambda s: s.shift(2, offset=datetools.bday)
_dense_series_compare(series, f)
def test_cumsum(self):
result = self.bseries.cumsum()
expected = self.bseries.to_dense().cumsum()
self.assert_(isinstance(result, SparseSeries))
assert_series_equal(result.to_dense(), expected)
result = self.zbseries.cumsum()
expected = self.zbseries.to_dense().cumsum()
self.assert_(isinstance(result, Series))
assert_series_equal(result, expected)