使用lambda条件和pandas str.contains来整理字符串

Question

Trying to learn some stuff, I'm messing around with the global shark attack database on Kaggle and I'm trying to find the best way to lump strings using a lambda function and str.contains .

Basically anywhere a string contains a phrase with skin diving eg 'skin diving for abalone' , in the data['Activity'] column I want to replace the activity with skin diving . (there are 92 variations for skin diving hence trying to use the lambda function)

I can return a boolean series using

data['Activity].str.contains('skin diving')

But I'm unsure how to change the value if this condition is true

My lambda function = data.apply(lambda x: 'free diving' if x.str.contains('free diving)) but i'm getting a syntax error and i'm not familiar enough with lambda functions and pandas to get it right, any help would be appreciated.

Answer 1

您可以使用lambda中的in运算符来测试子字符串，而不是使用Series.str方法

data['activity'] = data['activity'].apply(lambda x: 'skin diving' if 'skin diving' in x else x)

Answer 2

You could use str.contains method with np.where

In [141]: df
Out[141]:
         activity
0  free diving ok
1              ok

In [142]: df.activity = np.where(df.activity.str.contains('free diving'),
                                 'free diving', df.activity)

In [143]: df
Out[143]:
      activity
0  free diving
1           ok