问题

df2 =(df.set_index(['Name','Source'])
 .apply(lambda x: x.str.split(';').explode())
 .reset_index())

df2 =(df.set_index(['Name','Source']) #Columns that won't be touched by the index
 .apply(lambda x: x.str.split(';').explode()) #split on the ; [its actually a pipe(|) but for visual purposes I used a ;]
 .reset_index())

答案1

得分: 5

首先拆分，然后进行常规的多列展开。例如：

cols = ['Title', 'City', 'Country']
df.assign(**{c: df[c].str.split('; ') for c in cols}).explode(cols)

       Name           Title      City  Country    Source

0 Haliey Wells Data Scientist Paris France Linkedin
0 Haliey Wells Data Analyst Suva FIJI Linkedin
0 Haliey Wells Mathematician Paris France Linkedin
1 Bron Levy Data Scientist HELSINKI Finland Kaggle
1 Bron Levy Data Analyst Berlin Germany Kaggle
2 Grace Kalie Data Analyst Athens Greece Kaggle
2 Grace Kalie Mathematician Budapest Hungary Kaggle
3 Evan James ML Engineer Tokyo Japan Google
3 Evan James Developer Lima Peru Google

<details>
<summary>英文:</summary>

Split first, then do a normal multi-column explode. For example:

cols = ['Title', 'City', 'Country']
df.assign(**{c: df[c].str.split('; ') for c in cols}).explode(cols)

       Name           Title      City  Country    Source

0 Haliey Wells Data Scientist Paris France Linkedin
0 Haliey Wells Data Analyst Suva FIJI Linkedin
0 Haliey Wells Mathematician Paris France Linkedin
1 Bron Levy Data Scientist HELSINKI Finland Kaggle
1 Bron Levy Data Analyst Berlin Germany Kaggle
2 Grace Kalie Data Analyst Athens Greece Kaggle
2 Grace Kalie Mathematician Budapest Hungary Kaggle
3 Evan James ML Engineer Tokyo Japan Google
3 Evan James Developer Lima Peru Google

</details>



# 答案2
**得分**: 2

以下是使用apply而不是字典推导和解包的另一种方法：

```python
df.set_index(['Name', 'Source']) \
  .apply(lambda x: x.str.split(';')) \
  .explode(column=df.columns[1:-1].tolist()).reset_index()

输出：

                Name    Source            Title        City    Country
0  Haliey Wells   Linkedin   Data Scientist       Paris     France
1  Haliey Wells   Linkedin     Data Analyst        Suva       FIJI
2  Haliey Wells   Linkedin   Mathematician       Paris     France 
3     Bron Levy     Kaggle   Data Scientist    HELSINKI    Finland
4     Bron Levy     Kaggle    Data Analyst      Berlin    Germany 
5   Grace Kalie     Kaggle     Data Analyst      Athens     Greece
6   Grace Kalie     Kaggle   Mathematician    Budapest    Hungary 
7    Evan James     Google      ML Engineer       Tokyo      Japan
8    Evan James     Google       Developer        Lima       Peru

df.set_index(['Name', 'Source'])\
  .apply(lambda x: x.str.split(';'))\
  .explode(column=df.columns[1:-1].tolist()).reset_index()

            Name    Source            Title        City    Country
0  Haliey Wells   Linkedin   Data Scientist       Paris     France
1  Haliey Wells   Linkedin     Data Analyst        Suva       FIJI
2  Haliey Wells   Linkedin   Mathematician       Paris     France 
3     Bron Levy     Kaggle   Data Scientist    HELSINKI    Finland
4     Bron Levy     Kaggle    Data Analyst      Berlin    Germany 
5   Grace Kalie     Kaggle     Data Analyst      Athens     Greece
6   Grace Kalie     Kaggle   Mathematician    Budapest    Hungary 
7    Evan James     Google      ML Engineer       Tokyo      Japan
8    Evan James     Google       Developer        Lima       Peru