问题

我有一个类似下面的pandas表格，已经使用groupby得到了如下的Groups 0, 1和2：

Group 0	Group 1	Group 2	Count
A	X1	577.5000	6
		894.8700	2
	X2	2697.3100	48
		2697.3100	1
	B3	2697.3100	30
B	C12	34.2700	9
		39.2700	3

我想在pandas中按组得到如下的总计：

Group 0	Group 1	Group 2	Count	Group 1 Count 总计
A	X1	577.5000	6	8
		894.8700	2	8
	X2	2697.3100	48	49
		2697.3100	1	49
	B3	2697.3100	30	30
B	C12	34.2700	9	12
		39.2700	3	12

英文:

I have a pandas table like below with groupby applied to get Groups 0, 1 and 2 as follows:

Group 0	Group 1	Group 2	Count
A	X1	577.5000	6
		894.8700	2
	X2	2697.3100	48
		2697.3100	1
	B3	2697.3100	30
B	C12	34.2700	9
		39.2700	3

I would like to get group wise total in pandas like below:

Group 0	Group 1	Group 2	Count	Group 1 Total by Count
A	X1	577.5000	6	8
		894.8700	2	8
	X2	2697.3100	48	49
		2697.3100	1	49
	B3	2697.3100	30	30
B	C12	34.2700	9	12
		39.2700	3	12

I am able to calculate cumulative sum using df.groupby(level=[0,1]).cumsum() but now sure if there is a way to achieve this.

答案1

得分: 2

你可以使用`groupby.transform`来对分组进行`sum`调用的转换。

英文:

You can use groupby.transform to transform a sum call over the groups.

df[&#39;Group 1 Total by Count&#39;] = df.groupby([&#39;Group 0&#39;, &#39;Group 1&#39;])[&#39;Count&#39;].transform(&#39;sum&#39;)

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