本文整理汇总了Python中pandas.sparse.api.SparseDataFrame.cumsum方法的典型用法代码示例。如果您正苦于以下问题：Python SparseDataFrame.cumsum方法的具体用法？Python SparseDataFrame.cumsum怎么用？Python SparseDataFrame.cumsum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类pandas.sparse.api.SparseDataFrame的用法示例。
在下文中一共展示了SparseDataFrame.cumsum方法的4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: TestSparseDataFrameAnalytics
# 需要导入模块: from pandas.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.sparse.api.SparseDataFrame import cumsum [as 别名]
class TestSparseDataFrameAnalytics(tm.TestCase):
def setUp(self):
self.data = {'A': [nan, nan, nan, 0, 1, 2, 3, 4, 5, 6],
'B': [0, 1, 2, nan, nan, nan, 3, 4, 5, 6],
'C': np.arange(10),
'D': [0, 1, 2, 3, 4, 5, nan, nan, nan, nan]}
self.dates = bdate_range('1/1/2011', periods=10)
self.frame = SparseDataFrame(self.data, index=self.dates)
def test_cumsum(self):
result = self.frame.cumsum()
expected = SparseDataFrame(self.frame.to_dense().cumsum())
tm.assert_sp_frame_equal(result, expected)
def test_numpy_cumsum(self):
result = np.cumsum(self.frame, axis=0)
expected = SparseDataFrame(self.frame.to_dense().cumsum())
tm.assert_sp_frame_equal(result, expected)
msg = "the 'dtype' parameter is not supported"
tm.assertRaisesRegexp(ValueError, msg, np.cumsum,
self.frame, dtype=np.int64)
msg = "the 'out' parameter is not supported"
tm.assertRaisesRegexp(ValueError, msg, np.cumsum,
self.frame, out=result)示例2: TestSparseDataFrameAnalytics
# 需要导入模块: from pandas.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.sparse.api.SparseDataFrame import cumsum [as 别名]
class TestSparseDataFrameAnalytics(tm.TestCase):
def setUp(self):
self.data = {'A': [nan, nan, nan, 0, 1, 2, 3, 4, 5, 6],
'B': [0, 1, 2, nan, nan, nan, 3, 4, 5, 6],
'C': np.arange(10, dtype=float),
'D': [0, 1, 2, 3, 4, 5, nan, nan, nan, nan]}
self.dates = bdate_range('1/1/2011', periods=10)
self.frame = SparseDataFrame(self.data, index=self.dates)
def test_cumsum(self):
expected = SparseDataFrame(self.frame.to_dense().cumsum())
result = self.frame.cumsum()
tm.assert_sp_frame_equal(result, expected)
result = self.frame.cumsum(axis=None)
tm.assert_sp_frame_equal(result, expected)
result = self.frame.cumsum(axis=0)
tm.assert_sp_frame_equal(result, expected)
def test_numpy_cumsum(self):
result = np.cumsum(self.frame)
expected = SparseDataFrame(self.frame.to_dense().cumsum())
tm.assert_sp_frame_equal(result, expected)
msg = "the 'dtype' parameter is not supported"
tm.assertRaisesRegexp(ValueError, msg, np.cumsum,
self.frame, dtype=np.int64)
msg = "the 'out' parameter is not supported"
tm.assertRaisesRegexp(ValueError, msg, np.cumsum,
self.frame, out=result)
def test_numpy_func_call(self):
# no exception should be raised even though
# numpy passes in 'axis=None' or `axis=-1'
funcs = ['sum', 'cumsum', 'var',
'mean', 'prod', 'cumprod',
'std', 'min', 'max']
for func in funcs:
getattr(np, func)(self.frame)示例3: TestSparseDataFrame
# 需要导入模块: from pandas.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.sparse.api.SparseDataFrame import cumsum [as 别名]
#.........这里部分代码省略.........
def test_density(self):
df = SparseDataFrame(
{
"A": [nan, nan, nan, 0, 1, 2, 3, 4, 5, 6],
"B": [0, 1, 2, nan, nan, nan, 3, 4, 5, 6],
"C": np.arange(10),
"D": [0, 1, 2, 3, 4, 5, nan, nan, nan, nan],
}
)
self.assertEquals(df.density, 0.75)
def test_to_dense(self):
def _check(frame):
dense_dm = frame.to_dense()
assert_frame_equal(frame, dense_dm)
self._check_all(_check)
def test_stack_sparse_frame(self):
def _check(frame):
dense_frame = frame.to_dense()
wp = Panel.from_dict({"foo": frame})
from_dense_lp = wp.to_frame()
from_sparse_lp = spf.stack_sparse_frame(frame)
self.assert_(np.array_equal(from_dense_lp.values, from_sparse_lp.values))
_check(self.frame)
_check(self.iframe)
# for now
self.assertRaises(Exception, _check, self.zframe)
self.assertRaises(Exception, _check, self.fill_frame)
def test_transpose(self):
def _check(frame):
transposed = frame.T
untransposed = transposed.T
assert_sp_frame_equal(frame, untransposed)
self._check_all(_check)
def test_shift(self):
def _check(frame):
shifted = frame.shift(0)
self.assert_(shifted is not frame)
assert_sp_frame_equal(shifted, frame)
f = lambda s: s.shift(1)
_dense_frame_compare(frame, f)
f = lambda s: s.shift(-2)
_dense_frame_compare(frame, f)
f = lambda s: s.shift(2, timeRule="WEEKDAY")
_dense_frame_compare(frame, f)
f = lambda s: s.shift(2, offset=datetools.bday)
_dense_frame_compare(frame, f)
self._check_all(_check)
def test_count(self):
result = self.frame.count()
dense_result = self.frame.to_dense().count()
assert_series_equal(result, dense_result)
result = self.frame.count(1)
dense_result = self.frame.to_dense().count(1)
# win32 don't check dtype
assert_series_equal(result, dense_result, check_dtype=False)
def test_cumsum(self):
result = self.frame.cumsum()
expected = self.frame.to_dense().cumsum()
self.assert_(isinstance(result, SparseDataFrame))
assert_frame_equal(result.to_dense(), expected)
def _check_all(self, check_func):
check_func(self.frame)
check_func(self.iframe)
check_func(self.zframe)
check_func(self.fill_frame)
def test_combine_first(self):
df = self.frame
result = df[::2].combine_first(df)
result2 = df[::2].combine_first(df.to_dense())
expected = df[::2].to_dense().combine_first(df.to_dense())
expected = expected.to_sparse(fill_value=df.default_fill_value)
assert_sp_frame_equal(result, result2)
assert_sp_frame_equal(result, expected)示例4: TestSparseDataFrame
# 需要导入模块: from pandas.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.sparse.api.SparseDataFrame import cumsum [as 别名]
#.........这里部分代码省略.........
# int is coerced to float dtype
tm.assert_frame_equal(shifted.to_dense(), exp, check_dtype=False)
shifted = frame.shift(1)
exp = orig.shift(1)
tm.assert_frame_equal(shifted, exp)
shifted = frame.shift(-2)
exp = orig.shift(-2)
tm.assert_frame_equal(shifted, exp)
shifted = frame.shift(2, freq='B')
exp = orig.shift(2, freq='B')
exp = exp.to_sparse(frame.default_fill_value)
tm.assert_frame_equal(shifted, exp)
shifted = frame.shift(2, freq=datetools.bday)
exp = orig.shift(2, freq=datetools.bday)
exp = exp.to_sparse(frame.default_fill_value)
tm.assert_frame_equal(shifted, exp)
self._check_all(_check)
def test_count(self):
result = self.frame.count()
dense_result = self.frame.to_dense().count()
tm.assert_series_equal(result, dense_result)
result = self.frame.count(1)
dense_result = self.frame.to_dense().count(1)
# win32 don't check dtype
tm.assert_series_equal(result, dense_result, check_dtype=False)
def test_cumsum(self):
result = self.frame.cumsum()
expected = self.frame.to_dense().cumsum()
tm.assertIsInstance(result, SparseDataFrame)
tm.assert_frame_equal(result.to_dense(), expected)
def _check_all(self, check_func):
check_func(self.frame, self.orig)
check_func(self.iframe, self.iorig)
check_func(self.zframe, self.zorig)
check_func(self.fill_frame, self.fill_orig)
def test_combine_first(self):
df = self.frame
result = df[::2].combine_first(df)
result2 = df[::2].combine_first(df.to_dense())
expected = df[::2].to_dense().combine_first(df.to_dense())
expected = expected.to_sparse(fill_value=df.default_fill_value)
tm.assert_sp_frame_equal(result, result2)
tm.assert_sp_frame_equal(result, expected)
def test_combine_add(self):
df = self.frame.to_dense()
df2 = df.copy()
df2['C'][:3] = np.nan
df['A'][:3] = 5.7
result = df.to_sparse().add(df2.to_sparse(), fill_value=0)
expected = df.add(df2, fill_value=0).to_sparse()
tm.assert_sp_frame_equal(result, expected)