Extracting PDF tables and appending when some column names are not the same

Hello,

I am trying to expand multiple binaries (PDF tables) in multiple nested folders so the table content from these PDF files are all usable as data points. I've put in a custom function with a sample file but the problem is that not all of these PDF's have the same format although majority of them do contain the same column names. 

Here are the challenges:

1. Col names in each pdf file may be different (majority are the same)
2. Some col names are repeated (since in the original pdf file, a column may be stored in two cells stacked on top of each other)
3. The number of columns are different for each pdf file. Some files contain 

I want to put in an M query that has a logic as such:

* If column X exists in the table I read from the PDF file, then rename as XX else pass

In Python this would look something like:

for table in tables:
    for i in table.columns:
        if i in c.keys():
            mylist.append(c[i])
        else:
            mylist.append(i)

# VARS defined:
table = pd.DataFrame({"Customer Name": [1,2,3,4], "Content": ["s","a","3","4"], "Not exist": ["s","a","3","4"]})
a = ['Content',
 'Filename',
 'Extension',
 'Date accessed',
 'Date modified',
 'Date created',
 'Folder Path',
 'Customer Name',
 'Assumed Eff. Date']
b = ['Content Temp',
 'Filename Temp',
 'Extension Temp',
 'Date accessed Temp',
 'Date modified Temp',
 'Date created Temp',
 'Folder Path Temp',
 'Customer Name Temp',
 'Assumed Eff. Date Temp']
c = dict(zip(a,b))

# CODE
for i in df.columns:
    if i in c.keys():
        mylist.append(c[i])
    else:
        mylist.append(i)
            

Is this possible? 

Thank you!!