将数据框中的值列表附加到新列[重复]

Posted 2023-02-23

【中文标题】将数据框中的值列表附加到新列[重复]

【英文标题】：Appending a list of values in a dataframe to a new column [duplicate]

【发布时间】：2020-09-12 02:30:57

【问题描述】：

我有一个包含如下推文的数据框：

我要做的是从列“in_reply_to_user_id”（不在图片中，因为 df 太宽而无法容纳）与给定 id 具有相同值的行中获取文本，并将文本附加到然后我想把它放在一个新列中。例如，列“in_reply_to_user_id”等于第一条推文的“id”的所有推文中的文本应该放在一个列表中，然后将其附加到数据框中称为“回复”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.

【参考方案1】：

这是一个简单的解决方案，遍历所有行。

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?]

【讨论】：

使用你提供的代码给了我错误：'BlockManager' object has no attribute t

@Luca Marinescu 嗯，你能说得更具体点吗？哪一行导致错误？什么是追溯？您能否缩小导致错误的数据的哪一部分？

【参考方案2】：

假设原始 Dataframe 如下所示：

         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 Dataframe 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               []

【讨论】：

你好@AmrSherbiny！请直接将您的数据框粘贴到您的答案中，这样社区可以更轻松地阅读或复制/粘贴它。