Question

我正在寻找以下问题的答案，但尚未找到答案。我有一个像这样的小例子的大数据集：

df =

A  B
1  I bought 3 apples in 2013
3  I went to the store in 2020 and got milk
1  In 2015 and 2019 I went on holiday to Spain
2  When I was 17, in 2014 I got a new car
3  I got my present in 2018 and it broke down in 2019

我想要提取> 1950的所有值并将其作为最终结果：

A  B                                                    C
1  I bought 3 apples in 2013                            2013
3  I went to the store in 2020 and got milk             2020
1  In 2015 and 2019 I went on holiday to Spain          2015_2019
2  When I was 17, in 2014 I got a new car               2014
3  I got my present in 2018 and it broke down in 2019   2018_2019

我尝试首先提取值，但没有超出以下范围：

df["C"] = df["B"].str.extract('(\d+)').astype(int)
df["C"] = df["B"].apply(lambda x: re.search(r'\d+', x).group())

但是我得到的只是错误消息（几周前我才启动python并使用文本。）。有人可以帮我吗？

Answer 1

这是使用str.findall并将结果列表中大于1950的那些项目连接起来的一种方法：

s = df["B"].str.findall('\d+')
df['C'] = s.apply(lambda x: '_'.join(i for i in x if int(i)> 1950))

   A                                                  B          C
0  1                          I bought 3 apples in 2013       2013
1  3           I went to the store in 2020 and got milk       2020
2  1        In 2015 and 2019 I went on holiday to Spain  2015_2019
3  2             When I was 17, in 2014 I got a new car       2014
4  3  I got my present in 2018 and it broke down in ...  2018_2019

Answer 2

使用单个正则表达式模式（考虑您的注释“ 需要年发生” ”）

In [268]: pat = re.compile(r'\b(19(?:[6-9]\d|5[1-9])|[2-9]\d{3})')

In [269]: df['C'] = df['B'].apply(lambda x: '_'.join(pat.findall(x)))

In [270]: df
Out[270]: 
   A                                                  B          C
0  1                          I bought 3 apples in 2013       2013
1  3           I went to the store in 2020 and got milk       2020
2  1        In 2015 and 2019 I went on holiday to Spain  2015_2019
3  2             When I was 17, in 2014 I got a new car       2014
4  3  I got my present in 2018 and it broke down in ...  2018_2019

Python-从pandas df中的字符串中提取多个值

2 个答案: