str_replace_all（）在python中是等效的

我正在从R转换到Python，并有一个示例数据帧，如下所示：

df = df = pd.DataFrame({'characterisitics': pd.Series(['Walter White made meth', 'Jessie Pinkman was called meth-head', 'Saul Goodman is always happy']), 'name': pd.Series(['Walter White', 'Jessie Pinkman', 'Saul Goodman'])})

         characteristics                        name
0               Walter White made meth      Walter White
1  Jessie Pinkman was called meth-head     Jessie Pinkman
2         Saul Goodman is always happy       Saul Goodman

       characteristics            name
0             made meth    Walter White
1  was called meth-head  Jessie Pinkman
2       is always happy    Saul Goodman

我想使用替换与每行的“name”列匹配的“characteristics”部分。在R中，我可以使用：

str_replace_all(string = df$characteristics, pattern = fixed(df$name), replacement = '')

我的输出如下：

df = df = pd.DataFrame({'characterisitics': pd.Series(['Walter White made meth', 'Jessie Pinkman was called meth-head', 'Saul Goodman is always happy']), 'name': pd.Series(['Walter White', 'Jessie Pinkman', 'Saul Goodman'])})

         characteristics                        name
0               Walter White made meth      Walter White
1  Jessie Pinkman was called meth-head     Jessie Pinkman
2         Saul Goodman is always happy       Saul Goodman

       characteristics            name
0             made meth    Walter White
1  was called meth-head  Jessie Pinkman
2       is always happy    Saul Goodman

如果我想在Python中实现这一点，我应该使用什么语法

---

谢谢

我认为对于这一行，您必须对每一行应用一个快速的

lambda

。对于简单的示例，实际上不需要正则表达式，因此标准的

str.replace（）

可以正常工作：

df.apply(lambda row: row['characterisitics'].replace(row['name'], ''), axis='columns')
Out[8]: 
0                made meth
1     was called meth-head
2          is always happy
dtype: object