Question

我的数据框中有这样的一列：

  ___________________________
 |  columnn                  |
 ____________________________
 | [happiness#sad]           |
 | [happy ness#moderate]     |
 | [happie ness#sad]         |
 ____________________________

我想用“幸福”代替“幸福”，“幸福”，“幸福”。我目前正在使用此方法，但没有任何改变。

  string exactly matching 
  happy ness===> happyness
  happiness  ===> happyness
  happie ness===>happyness

我尝试以下两种方法

第一种方法

   df['column']
   df.column=df.column.replace({"happiness":"happyness" ,"happy ness":"happyness" ,"happie ness":"happynesss" })

第二种方法

   df['column']=df['column'].str.replace("happiness","happyness").replace(“happy ness”.”happyness”).replace(“happie ness”,”happynesss”)

所需的输出：

           ______________________
          |  columnn             |
           _______________________
          | [happyness,sad]      |
          | [happyness,moderate] |
          | [happyness,sad]      |
          _______________________

Answer 1

这是将replace与regex=True结合使用的一种方法。

例如：

import pandas as pd

df = pd.DataFrame({"columnn": [["happiness#sad"], ["happy ness#moderate"], ["happie ness$sad"]]})
data = {"happiness":"happyness" ,"happy ness":"happyness" ,"happie ness":"happynesss" }
df["columnn"] = df["columnn"].apply(lambda x: pd.Series(x).replace(data, regex=True).tolist())
print(df)

输出：

                columnn
0       [happyness#sad]
1  [happyness#moderate]
2      [happynesss$sad]

Answer 2

尝试这种方法，我认为这将为您工作。

df['new_col']=df['column'].replace(to_replace = 
['happyness','happiness','happie ness'], value = 
['happyness','happyness','happyness'])

替换Python列表内的pandas数据框列中的字符串值

2 个答案: