python - 如何从 Pandas 中的另一列扩展范围的数据表

Question

我有以下数据表

import pandas as pd
  dt = pd.DataFrame({'id_audience': ['Female 13-17', 'Female 18-20'],
                       'gender': ['female', 'female'],
                       'age_min': [13, 18],
                       'age_max': [17, 20]})

我想扩展这个数据框，有一个额外的列(age)，age 应该是 age_min 和age_max。

最终结果是这样的:

 dt = pd.DataFrame({'id_audience': ['Female 13-17', 'Female 13-17', 'Female 13-17', 'Female 13-17',
                                   'Female 13-17', 'Female 18-20', 'Female 18-20', 'Female 18-20', ],
                   'gender': ['female', 'female', 'female', 'female', 'female', 'female', 'female', 'female'],
                   'age_min': [13, 13, 13, 13, 18, 18, 18, 18],
                   'age_max': [17, 17, 17, 17, 20, 20, 20, 20],
                   'age': [13, 14, 15, 16, 17, 18, 19, 20]})

有什么想法吗？

Answer 1

也像@Wen一样使用explode，但是在最小/最大年龄列上直接访问范围

---

dt.assign(
  age=[np.arange(x, y+1) for x, y in zip(dt['age_min'], dt['age_max'])]
).explode('age').reset_index(drop=True)

    id_audience  gender  age_min  age_max age
0  Female 13-17  female       13       17  13
1  Female 13-17  female       13       17  14
2  Female 13-17  female       13       17  15
3  Female 13-17  female       13       17  16
4  Female 13-17  female       13       17  17
5  Female 18-20  female       18       20  18
6  Female 18-20  female       18       20  19
7  Female 18-20  female       18       20  20