通过定界符在Pandas中拆分列的值而不会丢失定界符 [英] Splitting Columns' Values in Pandas by delimiter without losing delimiter

问题描述

我有一个遵循以下格式的数据框:

Hi I have a dataframe that follows this format:

df = pd.DataFrame(np.array([[1, 2, 'Apples 20pk ABC123', 4, 5], [6, 7, 
'Oranges 40pk XYZ123', 9, 0], [5, 6, 'Bananas 20pk ABC123', 8, 9]]), columns=
               ['Serial #', 'Branch ID', 'Info', 'Value1', 'Value2'])

         Serial#  Branch ID    Info                  Value1   Value2
  0         1       2          Apples 20pk ABC123       4        5
  1         6       7          Bananas 20pk ABC123      9        0
  2         5       6          Oranges 40pk XYZ123      8        9

我想基于"pk"字符拆分信息"列的值.本质上，我想创建两个新列，如下面的数据框所示:

I want to split the "Info" column's values based on the "pk" character. Essentially, I want to create two new columns, like in the dataframe below:

         Serial#  Branch ID    Package        Branch   Value1   Value2
  0         1       2          Apples 20pk    ABC123      4        5
  1         6       7          Bananas 20pk   ABC123      9        0
  2         5       6          Oranges 40pk   XYZ123      8        9

我尝试使用:

info = df["Info"].str.split("pk ", n=1, expand=True)
df['Package'] = branch[0]
df['Branch'] = branch[1]
del df['Info']

但是结果是，在df的包装"列中，我只获得了"Apples 20"，而不是"Apples 20pk".

but the result is that in df's column, 'Package', I only get "Apples 20" instead of "Apples 20pk".

我想使用"字符(一个空格)进行分割，但是我得到了三个值('Apples'，'20pk'，'ABC123').

I wanted to split using the " " character (a space) but, then I get three values ('Apples', '20pk', 'ABC123').

因为有n行(而不仅仅是3行)，所以我想知道最有效的方法是什么?谢谢！

Because there are n number of rows (not just 3), I was wondering what's the most efficient way to go about this? Thanks!

推荐答案

我们可以在此处使用正向表达式使用正则表达式.在这种情况下，我们在空格( \ s )上分割，该空格前面(?< = )的字符串是 pk :

We can use regular expression here with positive lookbehind. In this case we split on a whitespace (\s) which is preceded (?<=) by the string pk:

df['Info'].str.split('(?<=pk)\s', expand=True)

              0       1
0   Apples 20pk  ABC123
1  Oranges 40pk  XYZ123
2  Bananas 20pk  ABC123

为了获得您期望的输出，我们一次性创建了两列，然后放置 Info :

To get your expected output, we create the two columns in one go and drop Info afterwards:

df[['Package', 'Branch']] = df['Info'].str.split('(?<=pk)\s', expand=True)

df.drop('Info', axis=1, inplace=True)

  Serial # Branch ID Value1 Value2       Package  Branch
0        1         2      4      5   Apples 20pk  ABC123
1        6         7      9      0  Oranges 40pk  XYZ123
2        5         6      8      9  Bananas 20pk  ABC123

这篇关于通过定界符在Pandas中拆分列的值而不会丢失定界符的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！