Loop logic % change function modification

Question

My df, call it table A:

A   B   C    A_Q  B_Q     C_Q
27  40  41    2    1      etc
28  39  40    1    5    
30  28  29    3    6    
28  27  28    4    1    
15  10  11    5    4    
17  13  14    1    5    
16  60  17    8    10   
14  21  18    9    1    
20  34  23    10   2    
21  45  34    7    4    

My goal is to get to here, call this table B:

A   B   C    A_Q  B_Q     C_Q    A_S        B_S         C_S etc
27  40  41    2    1      etc
28  39  40    1    5    
30  28  29    3    6    
28  27  28    4    1    
15  10  11    5    4    
17  13  14    1    5    
16  60  17    8    10                        50
14  21  18    9    1    
20  34  23    10   2             -25.9
21  45  34    7    4    

The function I'm using is (got some great help here):

def func(col1, col2):
    l = []
    x = None
    for index in range(0, len(col1)):
        if x is None and col1[index] == 1:
            x = col2[index]
        elif not(x is None) and col1[index] == 10:
            y = col2[index]
            l.append(((float(y)/x)-1)*100)
            x = None
    return l

The logic behind this function is: I want to iterate through each row in every column with a _Q suffix, starting with A_Q and do the following:

1. if row value = '1', grab the corresponding value in col 'A'

2. assign that value to a variable, call it x

3. keep looping down the col A_Q

4. if row value is either 1,2,3,4,5,6,7,8 or 9, ignore

5. if the value is 10, then get the corresponding value in col 'A' and assign that to variable y

6. calculate % change, call it chg, between y and x: (y/x)-1)*100

7. keep going down the column with steps 1-7 above until the end

Edit: this is the part that differentiates this question from my previous question:

Now for the final steps, which is to run the function across all columns and append the results of the func above to my df in a new col, I thought of doing something like this:

q = [col for col in df.columns if '_Q' in col]
for col in q:
    df["{}_S".format(col)] = df.apply(func(df[col], df[col[:len(col)-2]]))

but the error message I get is: "ValueError: no results"

How to troubleshoot/fix this? Maybe an issue is that the function returns a list which then cannot get passed to the new column? Thanks for your help!