遍历列并减去 pd.dataframe 中的最后一列

Question

I am a python newbie and currently sitting on the evaluation of my simulations. I have read the results of the tab files into a pandas dataframe.
My index is the frequency. The remaining columns represent the amplitude of the calculated PSD.

I want to subtract these columns (eg a,b,c,d...) with the last column, which is my test data.

The first table is an example of my current Dataframe. I want to substract each column/row with the test_data to get at the end the Standard deviation etc. of each column like in the following table:

frequency (index)	A	B	C	test_data
1	1.2	5.0	2.4	1.9
2	2.1	3.0	2.7	2.6
3	3.0	6.0	2.9	2.8

The following table/dataframe is the wanted outcome after the loop.

frequency (index)	A	B	C	test_data
1	test_data[1]-A[1]	test_data[1]-B[1]	test_data[1]-C[1]	1.9
...	...	...	...	....
3	test_data[n]-A[n]	test_data[n]-B[n]	test_data[n]-C[n]	2.8
average of column	0.33	-2.3	-0.233

frequency (index)	A	B	C	test_data
1	0.7	-3.1	-0.5	1.9
2	0.5	-0.4	-0.1	2.6
3	-0.2	-3.2	-0.1	2.8
average of column	0.33	-2.3	-0.233

I woult be very very grateful for any help regarding the loop.

Answer 1

You can use drop to get rid of the non target columns, then rsub to subtract the test_data. Finally concat to the original dataset:

df2 = df.drop(columns=['frequency (index)', 'test_data']).rsub(df['test_data'] ,axis=0)

out = pd.concat([df.assign(**df2), df2.sum().to_frame().T])