python - Pandas:如何使用 json 数组分解数据框

Question

如何对pandas数据框进行爆破？

输入 df:

要求的输出 df:

+----------------+------+-----+------+
|level_2         | date | val | num  | 
+----------------+------+-----+------+
| name_1a        | 2020 |  1  | null |
| name_1b        | 2019 |  2  | null |
| name_1b        | 2020 |  3  | null |
| name_10000_xyz | 2018 |  4  | str  |
| name_10000_xyz | 2019 |  5  | null |
| name_10000_xyz | 2020 |  6  | str  |
+------------------------------------+

重现输入 df:

import pandas as pd
pd.set_option('display.max_colwidth', None)
data={'level_2':{1:'name_1a',3:'name_1b',5:'name_10000_xyz'},'value':{1:[{'date':'2020','val':1}],3:[{'date':'2019','val':2},{'date':'2020','val':3}],5:[{'date':'2018','val':4,'num':'str'},{'date':'2019','val':5},{'date':'2020','val':6,'num':'str'}]}}
df = pd.DataFrame(data)

Answer 1

分解 value 列上的数据框，然后弹出 value 列并从中创建一个新的数据框然后 加入 新框架和分解框架。

s = df.explode('value', ignore_index=True)
s.join(pd.DataFrame([*s.pop('value')], index=s.index))

---

          level_2  date  val  num
0         name_1a  2020    1  NaN
1         name_1b  2019    2  NaN
2         name_1b  2020    3  NaN
3  name_10000_xyz  2018    4  str
4  name_10000_xyz  2019    5  NaN
5  name_10000_xyz  2020    6  str