python - 如果 token 存在于数据框中，则分配 True/False

Question

我当前的数据框是:

     |articleID | keywords                                               | 
     |:-------- |:------------------------------------------------------:| 
0    |58b61d1d  | ['Second Avenue (Manhattan, NY)']                      |     
1    |58b6393b  | ['Crossword Puzzles']                                  |          
2    |58b6556e  | ['Workplace Hazards and Violations', 'Trump, Donald J']|            
3    |58b657fa  | ['Trump, Donald J', 'Speeches and Statements'].        |  

我想要一个类似于以下内容的数据框，其中根据关键字中是否提到特朗普标记“特朗普，唐纳德 J”添加一列，如果是，则将其分配为 True:

     |articleID | keywords                                               | trumpMention |
     |:-------- |:------------------------------------------------------:| ------------:|
0    |58b61d1d  | ['Second Avenue (Manhattan, NY)']                      | False        |      
1    |58b6393b  | ['Crossword Puzzles']                                  | False        |          
2    |58b6556e  | ['Workplace Hazards and Violations', 'Trump, Donald J']| True         |           
3    |58b657fa  | ['Trump, Donald J', 'Speeches and Statements'].        | True         |       

我尝试了多种使用 df 函数的方法。但无法达到我想要的结果。我尝试过的一些方法是:

df['trumpMention'] = np.where(any(df['keywords']) == 'Trump, Donald J', True, False) 

或

df['trumpMention'] = df['keywords'].apply(lambda x: any(token == 'Trump, Donald J') for token in x) 

或

lst = ['Trump, Donald J']  
df['trumpMention'] = df['keywords'].apply(lambda x: ([ True for token in x if any(token in lst)]))   

原始输入:

df = pd.DataFrame({'articleID': ['58b61d1d', '58b6393b', '58b6556e', '58b657fa'],
                   'keywords': [['Second Avenue (Manhattan, NY)'],
                                ['Crossword Puzzles'],
                                ['Workplace Hazards and Violations', 'Trump, Donald J'],
                                ['Trump, Donald J', 'Speeches and Statements']],
                   'trumpMention': [False, False, True, True]})

Answer 1

试试

df["trumpMention"] = df["keywords"].apply(lambda x: "Trump, Donald J" in x)