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Accepted
Dan
Asked: 2023-12-07 22:44:41 +0800 CST

pandas 字符串替换不会替换所有选择

  • 772

我有这个数据框：

dfsupport = pd.DataFrame({'Date': ['8/12/2020','8/12/2020','13/1/2020','24/5/2020','31/10/2020','11/7/2020','11/7/2020'],
                          'Category': ['Table','Chair','Cushion','Table','Chair','Mats','Mats'],
                          'Sales': ['1 table','3chairs','8 cushions','3Tables','12 Chairs','12Mats','4Mats'],
                          'Paid': ['Yes','Yes','Yes','Yes','No','Yes','Yes',],
                          'Amount': ['93.78','$51.99','44.99','38.24','£29.99','29 only','18']
                          })

我试图用空白替换货币符号，但下面的方法不起作用。

patternv='|'.join(['$', '£'])
dfsupport['Amount'] = dfsupport['Amount'].str.replace(patternv,'')

为什么这不起作用？

在上述之后打印数据框：

          Date Category       Sales Paid   Amount
0   8/12/2020    Table     1 table  Yes    93.78
1   8/12/2020    Chair     3chairs  Yes   $51.99
2   13/1/2020  Cushion  8 cushions  Yes    44.99
3   24/5/2020    Table     3Tables  Yes    38.24
4  31/10/2020    Chair   12 Chairs   No   £29.99
5   11/7/2020     Mats      12Mats  Yes  29 only
6   11/7/2020     Mats       4Mats  Yes       18
         Date Category      Sales Paid  Amount
1   8/12/2020    Chair    3chairs  Yes  $51.99
4  31/10/2020    Chair  12 Chairs   No  £29.99

我确实遵循了这个问题，所以不确定为什么我的不起作用。

python

3 个回答

  1. Best Answer

    你错过了两件重要的事情：

    • 使用re.escape($表示“字符串结尾”) 转义正则表达式字符
    • 定义regex=True模式str.replace（现在False默认）
    import re

patternv='|'.join(map(re.escape, ['$', '£']))
dfsupport['Amount'] = dfsupport['Amount'].str.replace(patternv, '', regex=True)

    输出：

             Date Category       Sales Paid   Amount
0   8/12/2020    Table     1 table  Yes    93.78
1   8/12/2020    Chair     3chairs  Yes    51.99
2   13/1/2020  Cushion  8 cushions  Yes    44.99
3   24/5/2020    Table     3Tables  Yes    38.24
4  31/10/2020    Chair   12 Chairs   No    29.99
5   11/7/2020     Mats      12Mats  Yes  29 only
6   11/7/2020     Mats       4Mats  Yes       18
    • 6

  2. 首先在生成器理解中转义正则表达式字符，然后指定regex=TrueforSeries.str.replace替换子字符串：

    import re

patternv='|'.join(re.escape(x) for x in ['$', '£'])
dfsupport['Amount'] = dfsupport['Amount'].str.replace(patternv,'', regex=True)
print (dfsupport)
         Date Category       Sales Paid   Amount
0   8/12/2020    Table     1 table  Yes    93.78
1   8/12/2020    Chair     3chairs  Yes    51.99
2   13/1/2020  Cushion  8 cushions  Yes    44.99
3   24/5/2020    Table     3Tables  Yes    38.24
4  31/10/2020    Chair   12 Chairs   No    29.99
5   11/7/2020     Mats      12Mats  Yes  29 only
6   11/7/2020     Mats       4Mats  Yes       18
    • 2

  3. 另一种可能的解决方案，使用pandas.Series.str.extract：

    dfsupport['Amount'] = dfsupport['Amount'].str.extract(r'(\d+\.\d+|\d+)')

    输出：

             Date Category       Sales Paid Amount
0   8/12/2020    Table     1 table  Yes  93.78
1   8/12/2020    Chair     3chairs  Yes  51.99
2   13/1/2020  Cushion  8 cushions  Yes  44.99
3   24/5/2020    Table     3Tables  Yes  38.24
4  31/10/2020    Chair   12 Chairs   No  29.99
5   11/7/2020     Mats      12Mats  Yes     29
6   11/7/2020     Mats       4Mats  Yes     18
    • 1

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