我有一个适用于单个值的函数,但是当我将它与pandas series.apply()一起使用时,它会产生OverflowError。
from __future__ import division
import pandas as pd
import numpy as np
birthdays = pd.DataFrame(np.empty([365,2]), columns = ['k','probability'], index = range(1,366))
birthdays['k'] = birthdays.index
我做了一个功能:
def probability_of_shared_bday(k):
end_point = 366 - k
numerator = 1
for i in range(end_point, 366):
numerator = numerator*i
denominator = 365**k
probability_of_no_match = (1 - numerator/denominator)
return probability_of_no_match
当我尝试使用单个整数时,它可以正常工作:
probability_of_shared_bday(1)
0.0
probability_of_shared_bday(100)
0.9999996927510721
但是当我尝试使用此函数时,请使用:
birthdays['probability'] = birthdays['k'].apply(probability_of_shared_bday, convert_dtype=False)
OverflowError:对于float
,整数除法结果太大无论convert_dtype
是True还是False,都会发生这种情况。
检查birthdays['k'].dtypes
我得到dtype('int64')
答案 0 :(得分:1)
我不确定你为什么会遇到apply
这个问题,但是你不应该像开始那样编写函数。这是一个建议,避免将两个巨大的数字分开:
def probability_of_shared_bday(k):
end_point = 366 - k
ratio = 1
for i in range(end_point, 366):
ratio *= i / 365
probability_of_no_match = (1 - ratio)
return probability_of_no_match
问题消失了!