在Pandas DataFrame中按字典分组(Group by a Dictionary in Pandas DataFrame)

在Pandas DataFrame中按字典分组(Group by a Dictionary in Pandas DataFrame)

我从excel文件中读取数据，它是这样的：

我想得到每个员工的Q1和Q2的总和，所以我创建了一个字典，并希望根据它进行分组，

import pandas as pd mb2 = pd.read_excel('C:\\Users\\IBM_ADMIN\\Desktop\\ml-1m\\工作簿1.xlsx', sheetname='Sheet3') mapping = {'Jan':'Q1','Feb':'Q1','Mar':'Q1','Apr':'Q2','May':'Q2','Jun':'Q2'} mb2.groupby(by=mapping,axis=1).sum()

如何显示字段名称？ 我尝试这样做，但它不起作用：

mb2.groupby(by=(mapping,'Name'),axis=1).sum()

I read data from an excel file, it is like this:

and I want to get the sum of Q1 and Q2 for each employee, so I create a dictionary, and want to group by based on that,

import pandas as pd mb2 = pd.read_excel('C:\\Users\\IBM_ADMIN\\Desktop\\ml-1m\\工作簿1.xlsx', sheetname='Sheet3') mapping = {'Jan':'Q1','Feb':'Q1','Mar':'Q1','Apr':'Q2','May':'Q2','Jun':'Q2'} mb2.groupby(by=mapping,axis=1).sum()

How to show also the field Name? I try to do like this, but it didn't work:

mb2.groupby(by=(mapping,'Name'),axis=1).sum()

最满意答案

一个快速的解决方案是将生成的DataFrame保存在一个新变量（以下代码中的grouped_data ）中，然后使用原始DataFrame为其分配Name列：

grouped_data = mb2.groupby(by=mapping,axis=1).sum() grouped_data['Name'] = mb2['Name'] print(grouped_data)

编辑：实现相同结果的另一种方法是修改mapping字典，向其添加"Name": "Name"对，并像以前一样调用mb2.groupby(by=mapping,axis=1).sum() 。

A quick solution is to save the resulting DataFrame in a new variable (grouped_data in the following code) and then assign the Name column to it using the original DataFrame:

grouped_data = mb2.groupby(by=mapping,axis=1).sum() grouped_data['Name'] = mb2['Name'] print(grouped_data)

EDIT: Another way of achieving the same result is to modify the mapping dictionary, adding a "Name": "Name" pair to it, and calling mb2.groupby(by=mapping,axis=1).sum() as before.