I have the following data:
| ID | content | date |
|---|---|---|
| 1 | 2429(sach:MySpezialItem :16.59) | 2022-04-12 |
| 2 | 2429(sach:item 13 :18.59)(sach:this and that costs:16.59) | 2022-06-12 |
And I want to achieve the following:
| ID | number | price | date |
|---|---|---|---|
| 1 | 2429 | 2022-04-12 | |
| 1 | 16.59 | 2022-04-12 | |
| 2 | 2429 | 2022-06-12 | |
| 2 | 18.59 | 2022-06-12 | |
| 2 | 16.59 | 2022-06-12 |
What I tried
df['sach'] = df['content'].str.split(r'\(sach:.*\)').explode('content')
df['content'] = df['content'].str.replace(r'\(sach:.*\)','', regex=True)
You can use a single regex with str.extractall:
regex = r'(?P<number>\d+)\(|:(?P<price>\d+(?:\.\d+)?)\)'
df = df.join(df.pop('content').str.extractall(regex).droplevel(1))
NB. if you want a new DataFrame, don't pop:
df2 = (df.drop(columns='content')
.join(df['content'].str.extractall(regex).droplevel(1))
)
output:
ID date number price
0 1 2022-04-12 2429 NaN
0 1 2022-04-12 NaN 16.59
1 2 2022-06-12 2429 NaN
1 2 2022-06-12 NaN 18.59
1 2 2022-06-12 NaN 16.59