给定数据:
| Id | start Date | Frequency | Date1 | Dat2 | Date3 | Date4 |Date5 |
| -------- | -------------- | --------- | ----------- | ----------- | ----------- | ----------- | ----------- |
| 1 | 10-10-2014 | 1 | 10-10-2015 | 10-10-2016 | 10-10-2017 | 10-10-2018 | 10-10-2019 |
| 2 | 20–10-2015 | 2 | 20-04-2016 | 20-10-2016 | 20-04-2017 | 20-10-2017 | 20-14-2018 |
所需数据集
| Id | start Date | Frequency | Date1 | Dat2 | Date3 | Date4 |Date5 |
| -------- | -------------- | --------- | ----------- | ----------- | ----------- | ----------- | ----------- |
| 1 | 10-10-2014 | 1 | 10-10-2016 | 10-10-2017 | 10-10-2018 | 10-10-2019 | |
| 2 | 20–10-2015 | 2 | 20-10-2016 | 20-04-2017 | 20-10-2017 | 20-14-2018 | |
需要删除 2016 年 10 月之前的日期,接下来将填充删除的日期单元格。
我的代码在 2,00,000 行上很耗时,有没有简单的方法?
for i in range(0,len(f1)) :
ff0=f1.loc[f1_index[i]].tolist()
dt1= pd. DataFrame (ff0)
dft1 = dt1[~(dt1[0]<' 2015-01-01' )]
dtL1= dft1[0]. tolist()
a_series1= pd. Series (dtL1, index= f1. columns[0:len(dtL1)])
F2=F2.append (a_seriesl, ignore index = True)