本文整理匯總了Python中pandas.core.sorting.is_int64_overflow_possible方法的典型用法代碼示例。如果您正苦於以下問題：Python sorting.is_int64_overflow_possible方法的具體用法？Python sorting.is_int64_overflow_possible怎麽用？Python sorting.is_int64_overflow_possible使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.core.sorting的用法示例。
在下文中一共展示了sorting.is_int64_overflow_possible方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: _get_join_keys
# 需要導入模塊: from pandas.core import sorting [as 別名]
# 或者: from pandas.core.sorting import is_int64_overflow_possible [as 別名]
def _get_join_keys(llab, rlab, shape, sort):
# how many levels can be done without overflow
pred = lambda i: not is_int64_overflow_possible(shape[:i])
nlev = next(filter(pred, range(len(shape), 0, -1)))
# get keys for the first `nlev` levels
stride = np.prod(shape[1:nlev], dtype='i8')
lkey = stride * llab[0].astype('i8', subok=False, copy=False)
rkey = stride * rlab[0].astype('i8', subok=False, copy=False)
for i in range(1, nlev):
with np.errstate(divide='ignore'):
stride //= shape[i]
lkey += llab[i] * stride
rkey += rlab[i] * stride
if nlev == len(shape): # all done!
return lkey, rkey
# densify current keys to avoid overflow
lkey, rkey, count = _factorize_keys(lkey, rkey, sort=sort)
llab = [lkey] + llab[nlev:]
rlab = [rkey] + rlab[nlev:]
shape = [count] + shape[nlev:]
return _get_join_keys(llab, rlab, shape, sort) 示例2: _get_join_keys
# 需要導入模塊: from pandas.core import sorting [as 別名]
# 或者: from pandas.core.sorting import is_int64_overflow_possible [as 別名]
def _get_join_keys(llab, rlab, shape, sort):
# how many levels can be done without overflow
pred = lambda i: not is_int64_overflow_possible(shape[:i])
nlev = next(filter(pred, range(len(shape), 0, -1)))
# get keys for the first `nlev` levels
stride = np.prod(shape[1:nlev], dtype='i8')
lkey = stride * llab[0].astype('i8', subok=False, copy=False)
rkey = stride * rlab[0].astype('i8', subok=False, copy=False)
for i in range(1, nlev):
stride //= shape[i]
lkey += llab[i] * stride
rkey += rlab[i] * stride
if nlev == len(shape): # all done!
return lkey, rkey
# densify current keys to avoid overflow
lkey, rkey, count = _factorize_keys(lkey, rkey, sort=sort)
llab = [lkey] + llab[nlev:]
rlab = [rkey] + rlab[nlev:]
shape = [count] + shape[nlev:]
return _get_join_keys(llab, rlab, shape, sort)