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 (e.g. 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.
CodePudding user response：
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])