本文介绍了如何根据上述行的值添加新列的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个数据框,如下所示.首先,它们具有三列(日期",时间",标志").我想根据标志和日期添加一列,这意味着当我获得flag = 1时,那么今天剩下的目标是1,否则目标是零.
I have one dataframe as below. At first,they have three columns('date','time','flag'). I want to add one column which based on the flag and date which means when I get flag=1 ,then the rest of this day the target is 1, otherwise the target is zero.
date time flag target
0 2017/4/10 10:00:00 0 0
1 2017/4/10 11:00:00 1 1
2 2017/4/10 12:00:00 0 1
3 2017/4/10 13:00:00 0 1
4 2017/4/10 14:00:00 0 1
5 2017/4/11 10:00:00 1 1
6 2017/4/11 11:00:00 0 1
7 2017/4/11 12:00:00 1 1
8 2017/4/11 13:00:00 1 1
9 2017/4/11 14:00:00 0 1
10 2017/4/12 10:00:00 0 0
11 2017/4/12 11:00:00 0 0
12 2017/4/12 12:00:00 0 0
13 2017/4/12 13:00:00 0 0
14 2017/4/12 14:00:00 0 0
15 2017/4/13 10:00:00 0 0
16 2017/4/13 11:00:00 1 1
17 2017/4/13 12:00:00 0 1
18 2017/4/13 13:00:00 1 1
19 2017/4/13 14:00:00 0 1
推荐答案
使用 DataFrameGroupBy.cumsum
以获取累积总和flag
值,与0
进行比较,最后将蒙版转换为integer
:
Use DataFrameGroupBy.cumsum
for cumulative sum flag
values, compare with 0
and last cast mask to integer
:
df['new'] = (df.groupby('date')['flag'].cumsum() > 0).astype(int)
print (df)
date time flag target new
0 2017/4/10 10:00:00 0 0 0
1 2017/4/10 11:00:00 1 1 1
2 2017/4/10 12:00:00 0 1 1
3 2017/4/10 13:00:00 0 1 1
4 2017/4/10 14:00:00 0 1 1
5 2017/4/11 10:00:00 1 1 1
6 2017/4/11 11:00:00 0 1 1
7 2017/4/11 12:00:00 1 1 1
8 2017/4/11 13:00:00 1 1 1
9 2017/4/11 14:00:00 0 1 1
10 2017/4/12 10:00:00 0 0 0
11 2017/4/12 11:00:00 0 0 0
12 2017/4/12 12:00:00 0 0 0
13 2017/4/12 13:00:00 0 0 0
14 2017/4/12 14:00:00 0 0 0
15 2017/4/13 10:00:00 0 0 0
16 2017/4/13 11:00:00 1 1 1
17 2017/4/13 12:00:00 0 1 1
18 2017/4/13 13:00:00 1 1 1
19 2017/4/13 14:00:00 0 1 1
这篇关于如何根据上述行的值添加新列的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!