如果从熊猫数据框列值中删除句子，则删除第一个单词

Question

I have a data frame like this:

df:
col1      col2
 A        blue berry
 B        nice water bottle

I want to remove first word from the col2 values, the final data frame will look like this:

df1:
col1       col2
 A         berry
 B         water bottle

How to do this in most effective way using pandas

Answer 1

d['col2'] = d['col2'].apply(lambda x: ' '.join(x.split(' ')[1:]))

Output

  col1          col2
0    A         berry
1    B  water bottle

Answer 2

in your case

df1.col2 = df1.col2.str.split(" ",1).str[1]

might do the trick. The .str gives you vectorised string functionality on columns and and split takes an additional argument which says how often it will maximaly split.

Answer 3

Use split by first whitespace with n=1 and then select second lists by indexing:

df['col2'] = df['col2'].str.split(n=1).str[1]
print (df)
  col1          col2
0    A         berry
1    B  water bottle

Detail :

print (df['col2'].str.split(n=1))
0           [blue, berry]
1    [nice, water bottle]
Name: col2, dtype: object

If performance is important and no missing values convert solution to list comprehension:

df['col2'] = [x.split(maxsplit=1)[1] for x in df['col2']]