Pandas - combine series with unique values, matching across rows

Question

I'll start by dropping in my code and then explain what I'm trying to accomplish:

names = [
    'ABX-B767-200BDSF (767-3A)',
    'ABX-B767-200BDSF (DAR 767-3A)',
    'ABX-B767-200BDSF (DAR 767-4)',
]

i1 = pd.read_csv(f'{path}/{files[0]}', skiprows=4, nrows=1)
i2 = pd.read_csv(f'{path}/{files[1]}', skiprows=4, nrows=1)
i3 = pd.read_csv(f'{path}/{files[2]}', skiprows=4, nrows=1)

df_list = [i1, i2, i3]

cl1 = pd.Series(df_list[0].columns.values, name=names[0])
cl2 = pd.Series(df_list[1].columns.values, name=names[1])
cl3 = pd.Series(df_list[2].columns.values, name=names[2])

col_list = [cl1, cl2, cl3]
final_frame = pd.concat([df for df in col_list], axis=1)

final_frame.fillna('', inplace=True)

Yes I know this is inefficient and long, please work with me.

My actual data has more than these 3 series, I've got 11 but for the sake of simplicity I'm only showing the code as if I had three.

Right now, my output looks like this:

ABX-B767-200BDSF (767-3A)   ABX-B767-200BDSF (DAR 767-3A)   ABX-B767-200BDSF (DAR 767-4)
0   Offset  Offset  Offset
1   A/C NUMBER  A/C NUMBER  10 MI RANGE SEL CAPT
2   A/C TYPE    A/C TYPE    10 MI RANGE SEL F/O
3   A/P CAUTION FCC-C   A/P CAUTION FCC-C   160 MI RANGE SEL CAPT
4   A/P CAUTION FCC-L   A/P CAUTION FCC-L   160 MI RANGE SEL F/O

and I need it to look like this:

    ABX-B767-200BDSF (767-3A)   ABX-B767-200BDSF (DAR 767-3A)   ABX-B767-200BDSF (DAR 767-4)
0   OFFSET  OFFSET  OFFSET
1                   10 MI RANGE SEL CAPT
2                   10 MI RANGE SEL F/O
3                   160 MI RANGE SEL CAPT
…           
13  A/C NUMBER  A/C NUMBER  
14  A/C TYPE    A/C TYPE    

Where values are matched across the the rows, and rows that don't have a match are filled with white space. I've tried using a merge with wide variance of arguments and I've simply had no luck. Any ideas how to get my desired result here?

As requested, .head(10)s of my cl1, 2, 3:

cl1.head(10).to_dict()
{0: 'Offset',
 1: 'A/C NUMBER',
 2: 'A/C TYPE',
 3: 'A/P CAUTION FCC-C',
 4: 'A/P CAUTION FCC-L',
 5: 'A/P CAUTION FCC-R',
 6: 'A/P CMD C ENGA FCC-C',
 7: 'A/P CMD C ENGA FCC-L',
 8: 'A/P CMD C ENGA FCC-R',
 9: 'A/P CMD C ENGA MCP'}

cl2.head(10).to_dict()
{0: 'Offset',
 1: 'A/C NUMBER',
 2: 'A/C TYPE',
 3: 'A/P CAUTION FCC-C',
 4: 'A/P CAUTION FCC-L',
 5: 'A/P CAUTION FCC-R',
 6: 'A/P CMD C ENGA FCC-C',
 7: 'A/P CMD C ENGA FCC-L',
 8: 'A/P CMD C ENGA FCC-R',
 9: 'A/P CMD C ENGA MCP'}

cl3.head(10).to_dict()
{0: 'Offset',
 1: '10 MI RANGE SEL CAPT',
 2: '10 MI RANGE SEL F/O',
 3: '160 MI RANGE SEL CAPT',
 4: '160 MI RANGE SEL F/O',
 5: '20 MI RANGE SEL CAPT',
 6: '20 MI RANGE SEL F/O',
 7: '40 MI RANGE SEL CAPT',
 8: '40 MI RANGE SEL F/O',
 9: '5 MI RANGE SEL CAPT'}

Answer 1

1. Create a master list that consists of all the value from your series.
2. reindex each series to the master list
3. concat the reindexed series

srs_list = [cl1, cl2, cl3]
master = pd.concat(srs_list).drop_duplicates()
parsed_list = [srs.to_frame().set_index(srs).reindex(master) for srs in srs_list]
output = pd.concat(parsed_list,axis=1).reset_index(drop=True)

>>> output
   ABX-B767-200BDSF (767-3A) ABX-B767-200BDSF (DAR 767-3A)  \
0                     Offset                        Offset   
1                 A/C NUMBER                    A/C NUMBER   
2                   A/C TYPE                      A/C TYPE   
3          A/P CAUTION FCC-C             A/P CAUTION FCC-C   
4          A/P CAUTION FCC-L             A/P CAUTION FCC-L   
5          A/P CAUTION FCC-R             A/P CAUTION FCC-R   
6       A/P CMD C ENGA FCC-C          A/P CMD C ENGA FCC-C   
7       A/P CMD C ENGA FCC-L          A/P CMD C ENGA FCC-L   
8       A/P CMD C ENGA FCC-R          A/P CMD C ENGA FCC-R   
9         A/P CMD C ENGA MCP            A/P CMD C ENGA MCP   
10                       NaN                           NaN   
11                       NaN                           NaN   
12                       NaN                           NaN   
13                       NaN                           NaN   
14                       NaN                           NaN   
15                       NaN                           NaN   
16                       NaN                           NaN   
17                       NaN                           NaN   
18                       NaN                           NaN   

   ABX-B767-200BDSF (DAR 767-4)  
0                        Offset  
1                           NaN  
2                           NaN  
3                           NaN  
4                           NaN  
5                           NaN  
6                           NaN  
7                           NaN  
8                           NaN  
9                           NaN  
10         10 MI RANGE SEL CAPT  
11          10 MI RANGE SEL F/O  
12        160 MI RANGE SEL CAPT  
13         160 MI RANGE SEL F/O  
14         20 MI RANGE SEL CAPT  
15          20 MI RANGE SEL F/O  
16         40 MI RANGE SEL CAPT  
17          40 MI RANGE SEL F/O  
18          5 MI RANGE SEL CAPT