有没有比bdate_range()更好的方法来通过熊猫测量两列日期之间的工作日?
df = pd.DataFrame({ 'A' : ['1/1/2013', '2/2/2013', '3/3/2013'], 'B': ['1/12/2013', '4/4/2013', '3/3/2013']}) print df df['A'] = pd.to_datetime(df['A']) df['B'] = pd.to_datetime(df['B']) f = lambda x: len(pd.bdate_range(x['A'], x['B'])) df['DIFF'] = df.apply(f, axis=1) print df
输出为:
A B 0 1/1/2013 1/12/2013 1 2/2/2013 4/4/2013 2 3/3/2013 3/3/2013 A B DIFF 0 2013-01-01 00:00:00 2013-01-12 00:00:00 9 1 2013-02-02 00:00:00 2013-04-04 00:00:00 44 2 2013-03-03 00:00:00 2013-03-03 00:00:00 0
谢谢!
brian_the_bungler是使用numpy的busday_count实现此目的的最有效方法:
brian_the_bungler
numpy
busday_count
import numpy as np A = [d.date() for d in df['A']] B = [d.date() for d in df['B']] df['DIFF'] = np.busday_count(A, B) print df
在我的机器上,这比您的测试用例快300倍,在更大的日期数组上快1000倍