本文整理汇总了Python中pandas._libs.lib.is_bool_array方法的典型用法代码示例。如果您正苦于以下问题：Python lib.is_bool_array方法的具体用法？Python lib.is_bool_array怎么用？Python lib.is_bool_array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.is_bool_array方法的3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: is_bool_indexer
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import is_bool_array [as 别名]
def is_bool_indexer(key):
if isinstance(key, (ABCSeries, np.ndarray, ABCIndex)):
if key.dtype == np.object_:
key = np.asarray(_values_from_object(key))
if not lib.is_bool_array(key):
if isna(key).any():
raise ValueError('cannot index with vector containing '
'NA / NaN values')
return False
return True
elif key.dtype == np.bool_:
return True
elif isinstance(key, list):
try:
arr = np.asarray(key)
return arr.dtype == np.bool_ and len(arr) == len(key)
except TypeError: # pragma: no cover
return False
return False 示例2: is_bool
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import is_bool_array [as 别名]
def is_bool(self):
""" we can be a bool if we have only bool values but are of type
object
"""
return lib.is_bool_array(self.values.ravel())
# TODO: Refactor when convert_objects is removed since there will be 1 path 示例3: is_bool_indexer
# 需要导入模块: from pandas._libs import lib [as 别名]
# 或者: from pandas._libs.lib import is_bool_array [as 别名]
def is_bool_indexer(key):
# type: (Any) -> bool
"""
Check whether `key` is a valid boolean indexer.
Parameters
----------
key : Any
Only list-likes may be considered boolean indexers.
All other types are not considered a boolean indexer.
For array-like input, boolean ndarrays or ExtensionArrays
with ``_is_boolean`` set are considered boolean indexers.
Returns
-------
bool
Raises
------
ValueError
When the array is an object-dtype ndarray or ExtensionArray
and contains missing values.
"""
na_msg = 'cannot index with vector containing NA / NaN values'
if (isinstance(key, (ABCSeries, np.ndarray, ABCIndex)) or
(is_array_like(key) and is_extension_array_dtype(key.dtype))):
if key.dtype == np.object_:
key = np.asarray(values_from_object(key))
if not lib.is_bool_array(key):
if isna(key).any():
raise ValueError(na_msg)
return False
return True
elif is_bool_dtype(key.dtype):
# an ndarray with bool-dtype by definition has no missing values.
# So we only need to check for NAs in ExtensionArrays
if is_extension_array_dtype(key.dtype):
if np.any(key.isna()):
raise ValueError(na_msg)
return True
elif isinstance(key, list):
try:
arr = np.asarray(key)
return arr.dtype == np.bool_ and len(arr) == len(key)
except TypeError: # pragma: no cover
return False
return False