本文整理汇总了Python中pandas._libs.lib.to_object_array_tuples方法的典型用法代码示例。如果您正苦于以下问题：Python lib.to_object_array_tuples方法的具体用法？Python lib.to_object_array_tuples怎么用？Python lib.to_object_array_tuples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._libs.lib的用法示例。
在下文中一共展示了lib.to_object_array_tuples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: test_to_object_array_tuples
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import to_object_array_tuples [as 别名]
def test_to_object_array_tuples(self):
r = (5, 6)
values = [r]
result = lib.to_object_array_tuples(values)
try:
# make sure record array works
from collections import namedtuple
record = namedtuple('record', 'x y')
r = record(5, 6)
values = [r]
result = lib.to_object_array_tuples(values) # noqa
except ImportError:
pass 示例2: _list_to_arrays
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import to_object_array_tuples [as 别名]
def _list_to_arrays(data, columns, coerce_float=False, dtype=None):
if len(data) > 0 and isinstance(data[0], tuple):
content = list(lib.to_object_array_tuples(data).T)
else:
# list of lists
content = list(lib.to_object_array(data).T)
return _convert_object_array(content, columns, dtype=dtype,
coerce_float=coerce_float) 示例3: from_tuples
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import to_object_array_tuples [as 别名]
def from_tuples(cls, tuples, sortorder=None, names=None):
"""
Convert list of tuples to MultiIndex
Parameters
----------
tuples : list / sequence of tuple-likes
Each tuple is the index of one row/column.
sortorder : int or None
Level of sortedness (must be lexicographically sorted by that
level)
Returns
-------
index : MultiIndex
Examples
--------
>>> tuples = [(1, u'red'), (1, u'blue'),
(2, u'red'), (2, u'blue')]
>>> MultiIndex.from_tuples(tuples, names=('number', 'color'))
See Also
--------
MultiIndex.from_arrays : Convert list of arrays to MultiIndex
MultiIndex.from_product : Make a MultiIndex from cartesian product
of iterables
"""
if not is_list_like(tuples):
raise TypeError('Input must be a list / sequence of tuple-likes.')
elif is_iterator(tuples):
tuples = list(tuples)
if len(tuples) == 0:
if names is None:
msg = 'Cannot infer number of levels from empty list'
raise TypeError(msg)
arrays = [[]] * len(names)
elif isinstance(tuples, (np.ndarray, Index)):
if isinstance(tuples, Index):
tuples = tuples._values
arrays = list(lib.tuples_to_object_array(tuples).T)
elif isinstance(tuples, list):
arrays = list(lib.to_object_array_tuples(tuples).T)
else:
arrays = lzip(*tuples)
return MultiIndex.from_arrays(arrays, sortorder=sortorder, names=names) 示例4: from_tuples
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import to_object_array_tuples [as 别名]
def from_tuples(cls, tuples, sortorder=None, names=None):
"""
Convert list of tuples to MultiIndex
Parameters
----------
tuples : list / sequence of tuple-likes
Each tuple is the index of one row/column.
sortorder : int or None
Level of sortedness (must be lexicographically sorted by that
level)
Returns
-------
index : MultiIndex
Examples
--------
>>> tuples = [(1, u'red'), (1, u'blue'),
(2, u'red'), (2, u'blue')]
>>> MultiIndex.from_tuples(tuples, names=('number', 'color'))
See Also
--------
MultiIndex.from_arrays : Convert list of arrays to MultiIndex
MultiIndex.from_product : Make a MultiIndex from cartesian product
of iterables
"""
if len(tuples) == 0:
if names is None:
msg = 'Cannot infer number of levels from empty list'
raise TypeError(msg)
arrays = [[]] * len(names)
elif isinstance(tuples, (np.ndarray, Index)):
if isinstance(tuples, Index):
tuples = tuples._values
arrays = list(lib.tuples_to_object_array(tuples).T)
elif isinstance(tuples, list):
arrays = list(lib.to_object_array_tuples(tuples).T)
else:
arrays = lzip(*tuples)
return MultiIndex.from_arrays(arrays, sortorder=sortorder, names=names)