python 将列中的字符串重命名为指定字符串

Question

我有一列包含许多不同的字符串，我想做的只是将我指定的所有字符串重命名为一个字符串，以便它们都具有相同的字符串。所以我的数据框看起来像这样：

          My_strings
1   I bumped my knee because I fell
2   I fell off my bike but I had a helmet
3   I am alright I just need to be alert
4   If I fall I will get back up

所以在我的专栏中说 My_strings 我想查找包含特定单词的句子。

df.loc[df.T_L_DESC.str.contains("fell|fall|fallen", na=False), 'Slippery'] = df.T_L_DESC

我要查找的特定词是 "fell|fall|fallen" 一旦在我的专栏的句子中找到这些词，它们就会被分解到另一个名为 'Slip_Fall'

的栏中

我只想将所有包含这些词的字符串重命名为一个特定的字符串。当我运行上面的代码时要注意一件事，它使每个句子都不包含其中指定的单词 NaN 所以我的最终数据框看起来像这样：

            My_strings                           Slippery
1   I bumped my knee because I fell            Life_Lessons   
2   I fell off my bike but I had a helmet      Life_Lessons
3   NaN                                        NaN 
4   If I fall I will get back up               Life_Lessons

所以我不想明显地将我在数据框中获得的 NaN 值更改为 Life_Lessons 我只想将包含我的关键字的句子更改为 Life_Lessons

提前致谢

Answer 1

一个简单的解决方案：

In [191]: df.loc[df.T_L_DESC.str.contains("fell|fall|fallen", na=False), 'Slippery'] = 'Life_Lessons'

In [192]: df
Out[192]:
                                T_L_DESC      Slippery
0        I bumped my knee because I fell  Life_Lessons
1  I fell off my bike but I had a helmet  Life_Lessons
2   I am alright I just need to be alert           NaN
3           If I fall I will get back up  Life_Lessons

In [193]: df.loc[df.Slippery!='Life_Lessons', 'T_L_DESC'] = np.nan

In [194]: df
Out[194]:
                                T_L_DESC      Slippery
0        I bumped my knee because I fell  Life_Lessons
1  I fell off my bike but I had a helmet  Life_Lessons
2                                    NaN           NaN
3           If I fall I will get back up  Life_Lessons

python 将列中的字符串重命名为指定字符串

python renaming strings in a column to a specified string

python

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dataframe

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