groupby之后，如何展平列标题? [英] After groupby, how to flatten column headers?

问题描述

我试图在单个Id列上保留多个熊猫数据框的联接，但是当我尝试合并时，我得到警告:

I'm trying to left join multiple pandas dataframes on a single Id column, but when I attempt the merge I get warning:

KeyError:"Id".

KeyError: 'Id'.

我认为可能是因为我的数据框具有由groupby语句产生的偏移列，但是我很可能是错误的.无论哪种方式，我都无法弄清楚如何拆堆"我的数据框列标题. 此问题的答案均无效.

I think it might be because my dataframes have offset columns resulting from a groupby statement, but I could very well be wrong. Either way I can't figure out how to "unstack" my dataframe column headers. None of the answers at this question seem to work.

我的groupby代码:

step1 = pd.DataFrame(step3.groupby(['Id', 'interestingtabsplittest2__grp'])['applications'].sum())
step1.sort('applications', ascending=False).head(3)

返回:

如何将那些偏移量标头放到顶层?

How to get those offset headers into the top level?

推荐答案

您正在寻找

You're looking for .reset_index().

In [11]: df = pd.DataFrame([[2, 3], [5, 6]], pd.Index([1, 4], name="A"), columns=["B", "C"])

In [12]: df
Out[12]:
   B  C
A
1  2  3
4  5  6

In [13]: df.reset_index()
Out[13]:
   A  B  C
0  1  2  3
1  4  5  6

---

注意:进行分组时，可以通过使用as_index=False来避免此步骤.

---

Note: That you can avoid this step by using as_index=False when doing the groupby.

step1 = step3.groupby(['Id', 'interestingtabsplittest2__grp'], as_index=False)['applications'].sum()

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