本文整理汇总了Python中pandas.sparse.api.SparseDataFrame.iteritems方法的典型用法代码示例。如果您正苦于以下问题：Python SparseDataFrame.iteritems方法的具体用法？Python SparseDataFrame.iteritems怎么用？Python SparseDataFrame.iteritems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.iteritems方法的1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: TestSparseDataFrame
# 需要导入模块: from pandas.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.sparse.api.SparseDataFrame import iteritems [as 别名]
class TestSparseDataFrame(TestCase, test_frame.SafeForSparse):
klass = SparseDataFrame
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 = DateRange("1/1/2011", periods=10)
self.frame = SparseDataFrame(self.data, index=self.dates)
self.iframe = SparseDataFrame(self.data, index=self.dates, default_kind="integer")
values = self.frame.values.copy()
values[np.isnan(values)] = 0
self.zframe = SparseDataFrame(values, columns=["A", "B", "C", "D"], default_fill_value=0, index=self.dates)
values = self.frame.values.copy()
values[np.isnan(values)] = 2
self.fill_frame = SparseDataFrame(values, columns=["A", "B", "C", "D"], default_fill_value=2, index=self.dates)
self.empty = SparseDataFrame()
def test_as_matrix(self):
empty = self.empty.as_matrix()
self.assert_(empty.shape == (0, 0))
no_cols = SparseDataFrame(index=np.arange(10))
mat = no_cols.as_matrix()
self.assert_(mat.shape == (10, 0))
no_index = SparseDataFrame(columns=np.arange(10))
mat = no_index.as_matrix()
self.assert_(mat.shape == (0, 10))
def test_copy(self):
cp = self.frame.copy()
self.assert_(isinstance(cp, SparseDataFrame))
assert_sp_frame_equal(cp, self.frame)
self.assert_(cp.index is self.frame.index)
def test_constructor(self):
for col, series in self.frame.iteritems():
self.assert_(isinstance(series, SparseSeries))
self.assert_(isinstance(self.iframe["A"].sp_index, IntIndex))
# constructed zframe from matrix above
self.assertEquals(self.zframe["A"].fill_value, 0)
assert_almost_equal([0, 0, 0, 0, 1, 2, 3, 4, 5, 6], self.zframe["A"].values)
# construct from nested dict
data = {}
for c, s in self.frame.iteritems():
data[c] = s.to_dict()
sdf = SparseDataFrame(data)
assert_sp_frame_equal(sdf, self.frame)
# TODO: test data is copied from inputs
# init dict with different index
idx = self.frame.index[:5]
cons = SparseDataFrame(
self.frame._series,
index=idx,
columns=self.frame.columns,
default_fill_value=self.frame.default_fill_value,
default_kind=self.frame.default_kind,
)
reindexed = self.frame.reindex(idx)
assert_sp_frame_equal(cons, reindexed)
# assert level parameter breaks reindex
self.assertRaises(Exception, self.frame.reindex, idx, level=0)
def test_constructor_ndarray(self):
# no index or columns
sp = SparseDataFrame(self.frame.values)
# 1d
sp = SparseDataFrame(self.data["A"], index=self.dates, columns=["A"])
assert_sp_frame_equal(sp, self.frame.reindex(columns=["A"]))
# raise on level argument
self.assertRaises(Exception, self.frame.reindex, columns=["A"], level=1)
# wrong length index / columns
self.assertRaises(Exception, SparseDataFrame, self.frame.values, index=self.frame.index[:-1])
self.assertRaises(Exception, SparseDataFrame, self.frame.values, columns=self.frame.columns[:-1])
def test_constructor_empty(self):
sp = SparseDataFrame()
self.assert_(len(sp.index) == 0)
self.assert_(len(sp.columns) == 0)
#.........这里部分代码省略.........