Question

我的问题与我为R（divide by previous element by group）发布的问题相同，除了我现在想在Pandas做同样的事情。

我有一个如下所示的数据框：

import gulp from 'gulp';
import riot from 'gulp-riot';

gulp.task('tags', () => {
  return gulp.src([`${srcDir}/*`])
    .pipe(riot({
      type: 'es6'
    }))
    .pipe(gulp.dest(`${destDir}/`));
});

我想要做的是将origdate = pd.Series(np.repeat(['2011-01-01', '2011-02-01', '2011-03-01'],[5, 4, 3])) date = pd.Series(['2011-01-01', '2011-02-01', '2011-03-01', '2011-04-01', '2011-05-01', '2011-02-01', '2011-03-01', '2011-04-01', '2011-05-01', '2011-03-01', '2011-04-01', '2011-05-01']) bal = pd.Series(range(20,32)) A = pd.DataFrame({'origdate': origdate, 'date': date, 'bal': bal}) A bal date origdate 0 20 2011-01-01 2011-01-01 1 21 2011-02-01 2011-01-01 2 22 2011-03-01 2011-01-01 3 23 2011-04-01 2011-01-01 4 24 2011-05-01 2011-01-01 5 25 2011-02-01 2011-02-01 6 26 2011-03-01 2011-02-01 7 27 2011-04-01 2011-02-01 8 28 2011-05-01 2011-02-01 9 29 2011-03-01 2011-03-01 10 30 2011-04-01 2011-03-01 11 31 2011-05-01 2011-03-01除以bal的每个增量bal，而不是date更改时的origdate。所以我想要获得的内容显示在下面的dbal列中：

     origdate       date bal     dbal
1  2011-01-01 2011-01-01  20       NA
2  2011-01-01 2011-02-01  21 1.050000
3  2011-01-01 2011-03-01  22 1.047619
4  2011-01-01 2011-04-01  23 1.045455
5  2011-01-01 2011-05-01  24 1.043478
6  2011-02-01 2011-02-01  25       NA
7  2011-02-01 2011-03-01  26 1.040000
8  2011-02-01 2011-04-01  27 1.038462
9  2011-02-01 2011-05-01  28 1.037037
10 2011-03-01 2011-03-01  29       NA
11 2011-03-01 2011-04-01  30 1.034483
12 2011-03-01 2011-05-01  31 1.033333

Answer 1

使用groupby + pct_change + add(1)

A.assign(dbal=A.groupby('origdate').bal.pct_change().add(1))

或groupby + shift + div

A.assign(dbal=A.groupby('origdate').bal.apply(lambda x: x.div(x.shift())))

两者都屈服

    bal        date    origdate      dbal
0    20  2011-01-01  2011-01-01       NaN
1    21  2011-02-01  2011-01-01  1.050000
2    22  2011-03-01  2011-01-01  1.047619
3    23  2011-04-01  2011-01-01  1.045455
4    24  2011-05-01  2011-01-01  1.043478
5    25  2011-02-01  2011-02-01       NaN
6    26  2011-03-01  2011-02-01  1.040000
7    27  2011-04-01  2011-02-01  1.038462
8    28  2011-05-01  2011-02-01  1.037037
9    29  2011-03-01  2011-03-01       NaN
10   30  2011-04-01  2011-03-01  1.034483
11   31  2011-05-01  2011-03-01  1.033333

在Pandas中除以前一个元素

1 个答案: