将数据帧中的值列表追加到新列[重复]

Question

我试图做的是从列“in_reply_to_user_id”（不在图片中，因为df太宽，无法容纳）与给定id具有相同值的行中获取文本，并将文本附加到列表中，然后将其放入新列中。例如，所有tweet中的“in_reply_to_user_id”列等于第一条tweet的“id”的文本都应该放在一个列表中，然后添加到数据框中名为“reples”的新列中。以下是我尝试过的一些事情：

for i in testb['in_reply_to_user_id']:
   for j in test['user.id']:
       if i == j:
           index=testb.index()
           test['replies'].append(testb['text'].iloc[index]) ```

test would be the original dataframe and testb would be a copy that i created in order to try to run the code above. it is just a copy of test.

Answer 1

假设原始Dataframe看起来像这样：

         text              user_id   reply_to        
0   this is reply to 3       1         3         
1   this is reply to 3       2         3         
2   this is reply to 2       3         2         
3   this is reply to 2       4         2               
4   this is reply to 1       5         1               

然后通过使用df.loc（）我们可以获得包含对每个文本的回复的记录：

import pandas as pd

data = [['this is reply to 3', 1, 3], ['this is reply to 3', 2, 3],['this is 
reply to 2', 3, 2],['this is reply to 2', 4, 2], ['this is reply to 1', 5,1 ]]

df = pd.DataFrame(data, columns = ['text', 'user_id', 'reply_to']) 

replies = []

for user_id in df.user_id:
    text = df.loc[df['reply_to'] == user_id].text.values
    replies.append(text)

df['replies'] = replies

生成的数据帧如下所示：

         text              user_id   reply_to         replies
0   this is reply to 3       1         3         [this is reply to 1]
1   this is reply to 3       2         3         [this is reply to 2, this is reply to 2]
2   this is reply to 2       3         2         [this is reply to 3, this is reply to 3]
3   this is reply to 2       4         2               []
4   this is reply to 1       5         1               []

Answer 2

这里有一个简单的解决方案，在所有行上循环。

import numpy as np
import pandas as pd

# example data
df = pd.DataFrame({'id': [1, 2, 3, 4],
                   'text': ['How are you?', 'Fine.', 'Okay.', 'hi'], 
                   'in_reply_to_user_id': [4, 1, 1, 3]})

# initiate new column
df['replies'] = np.repeat(None, len(df))

# assign lists as described in the question
for i in df.index:
    df.at[i, 'replies'] = list(df.text[df.in_reply_to_user_id == df.id[i]])

# show results
df

    id  text            in_reply_to_user_id     replies
0   1   How are you?    4                       [Fine., Okay.]
1   2   Fine.           1                       []
2   3   Okay.           1                       [hi]
3   4   hi              3                       [How are you?]