将pandas行转换为列

Question

我基本上想要采用这个数据帧：

  collector_id        date_created      row_id  question_id  respondent_id  survey_id
0      24785342 2015-02-25 00:40:00  3055824979    319047238     5004656403  101692922
1      24785342 2015-02-25 00:40:00  3055824979    319047238     5004656404  101692922
2      24785342 2015-02-25 00:40:00  3055824980    319047238     5004656405  101692922
3      24785342 2015-02-25 00:40:00  3055824980    319047238     5004656406  101692922
4      24785342 2015-02-25 00:40:00  3055824980    319047238     5004656407  101692922
5      24785342 2015-02-25 00:40:00  3055824980    319047238     5004656408  101692922
6      24785342 2015-02-25 00:40:00  3055824981    319047238     5004656409  101692922

并将其转换为：

   collector_id        date_created  319047238  respondent_id  survey_id
0      24785342 2015-02-25 00:40:00  3055824979  5004656403     101692922
1      24785342 2015-02-25 00:40:00  3055824979  5004656404     101692922
2      24785342 2015-02-25 00:40:00  3055824980  5004656405     101692922
3      24785342 2015-02-25 00:40:00  3055824980  5004656406     101692922
4      24785342 2015-02-25 00:40:00  3055824980  5004656407     101692922
5      24785342 2015-02-25 00:40:00  3055824980  5004656408     101692922
6      24785342 2015-02-25 00:40:00  3055824981  5004656409     101692922

将每个问题ID转换为一个列，然后将row_id放在其下面。

Answer 1

这似乎有效：

df = df.pivot_table(
    'question_id', ['respondent_id', 'survey_id'], 'row_id'
).reset_index()

它返回：

row_id  respondent_id  survey_id  3055827274  3055827275  3055827276
0          5004658716  101693626   319047673         NaN         NaN
1          5004658717  101693626   319047673         NaN         NaN
2          5004658718  101693626         NaN   319047673         NaN
3          5004658719  101693626         NaN   319047673         NaN
4          5004658720  101693626         NaN   319047673         NaN
5          5004658721  101693626         NaN   319047673         NaN
6          5004658722  101693626         NaN         NaN   319047673