本文整理汇总了Python中pandas.core.sparse.api.SparseDataFrame.apply方法的典型用法代码示例。如果您正苦于以下问题：Python SparseDataFrame.apply方法的具体用法？Python SparseDataFrame.apply怎么用？Python SparseDataFrame.apply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.core.sparse.api.SparseDataFrame的用法示例。
在下文中一共展示了SparseDataFrame.apply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.core.sparse.api import SparseDataFrame [as 别名]
# 或者: from pandas.core.sparse.api.SparseDataFrame import apply [as 别名]
#.........这里部分代码省略.........
assert 'B' not in self.frame
tm.assert_sp_series_equal(self.frame['A'], A)
tm.assert_sp_series_equal(self.frame['C'], C)
del self.frame['D']
assert 'D' not in self.frame
del self.frame['A']
assert 'A' not in self.frame
def test_set_columns(self):
self.frame.columns = self.frame.columns
pytest.raises(Exception, setattr, self.frame, 'columns',
self.frame.columns[:-1])
def test_set_index(self):
self.frame.index = self.frame.index
pytest.raises(Exception, setattr, self.frame, 'index',
self.frame.index[:-1])
def test_append(self):
a = self.frame[:5]
b = self.frame[5:]
appended = a.append(b)
tm.assert_sp_frame_equal(appended, self.frame, exact_indices=False)
a = self.frame.iloc[:5, :3]
b = self.frame.iloc[5:]
appended = a.append(b)
tm.assert_sp_frame_equal(appended.iloc[:, :3], self.frame.iloc[:, :3],
exact_indices=False)
def test_apply(self):
applied = self.frame.apply(np.sqrt)
assert isinstance(applied, SparseDataFrame)
tm.assert_almost_equal(applied.values, np.sqrt(self.frame.values))
applied = self.fill_frame.apply(np.sqrt)
assert applied['A'].fill_value == np.sqrt(2)
# agg / broadcast
broadcasted = self.frame.apply(np.sum, broadcast=True)
assert isinstance(broadcasted, SparseDataFrame)
exp = self.frame.to_dense().apply(np.sum, broadcast=True)
tm.assert_frame_equal(broadcasted.to_dense(), exp)
assert self.empty.apply(np.sqrt) is self.empty
from pandas.core import nanops
applied = self.frame.apply(np.sum)
tm.assert_series_equal(applied,
self.frame.to_dense().apply(nanops.nansum))
def test_apply_nonuq(self):
orig = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=['a', 'a', 'c'])
sparse = orig.to_sparse()
res = sparse.apply(lambda s: s[0], axis=1)
exp = orig.apply(lambda s: s[0], axis=1)
# dtype must be kept
assert res.dtype == np.int64
# ToDo: apply must return subclassed dtype
assert isinstance(res, pd.Series)
tm.assert_series_equal(res.to_dense(), exp)