英文:
How to get first name and last name when last name is multiple names in pandas
问题
我有一个数据框，需要分离名字的姓和名。到目前为止，我已经做到了这一步。
df = [['Victor De La Cruz', 'Ashley Smith', 'Angel Miguel Hernandez', 'Hank Hill']]df['first_name'] = df.str.split().str[0]df['last_name'] = df.str.split().str[1:]
输出结果如下：
first_name last_name0 Victor [De, La, Cruz]1 Ashley [Smith]2 Angel [Miguel, Hernandez]3 Hank [Hill]
我尝试使用 df['last_name'].replace('[', '') 来去除不需要的所有字符，但没有成功。
期望的输出如下：
first_name last_name0 Paul De La Cruz1 Ashley Smith2 Angel Miguel Hernandez3 Hank Hill
有任何建议吗？谢谢！
英文:
I have a data frame and need to separate first and last name. So far this is where I got to.
df = [['Victor De La Cruz', 'Ashley Smith', 'Angel Miguel Hernandez', 'Hank Hill']]df['first_name'] = df.str.split().str[0]df['last_name'] = df.str.split().str[1:]
OutPut
first_name last_nameVictor [De, La, Cruz]Ashley [Smith]Angel [Miguel, Hernandez]Hank [Hill]
I have tried using df'last_name'].replace('[', '')for all characters not wanted but it didn't work.
Desired Output
first_name last_namePaul De La CruzAshley SmithAngel Miguel HernandezHank Hill
Any Suggestions would be helpful thank you!
答案1
得分: 1
在 split() 后，您的系列中包含列表对象，而不是字符串，这就是为什么 .replace() 没有意义的原因。
英文:
Just join back
df['last_name'] = df['last_name'].str.join(' ')
After the split(), you have list objects in your series, not strings, which is why .replace() doesn't make sense.
答案2
得分: 1
I'd suggest using the n keyword argument to limit the splits to only the first space. You could also use expand=True:
import pandas as pds = pd.Series(['Victor De La Cruz','Ashley Smith','Angel Miguel Hernandez','Hank Hill'])df = s.str.split(n=1, expand=True)df.columns = ["first_name", "last_name"]
first_name last_name0 Victor De La Cruz1 Ashley Smith2 Angel Miguel Hernandez3 Hank Hill
英文:
I'd suggest using the n keyword argument to limit the splits to only the first space. You could also use expand=True:
import pandas as pds = pd.Series(['Victor De La Cruz','Ashley Smith','Angel Miguel Hernandez','Hank Hill'])df = s.str.split(n=1, expand=True)df.columns = ["first_name", "last_name"]
first_name last_name0 Victor De La Cruz1 Ashley Smith2 Angel Miguel Hernandez3 Hank Hill</details>
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