Using the existing column name, add a new column first_name to df such that the new column splits the name into multiple words and takes the first word as its first name. For example, if the name is Elon Musk, it is split into two words in the list ['Elon', 'Musk'] and the first word Elon is taken as its first name. If the name has only one word, then the word itself is taken as its first name.

A snippet of the data frame

This is what I have so far. I am not sure how to extract the name after I tokenize it

import nltk
first = df.name.apply(lambda x: nltk.word_tokenize(x))
df["first_name"] = This is where I'm stuck

CodePudding user response：

Try this snippet:

df["first_name"] = df['Name'].map(lambda x: x.split(' ')[0])
df["last_name"] = df['Name'].map(lambda x: x.split(' ')[1])