Merge csv

csv1.csv

sku;col1;col2;test
123;456;99;A
234;786;99;
345;678;99;A

csv2.csv

sku;col3;col4;test
123;18-123;9999;A
234;18-786;9999;
345;12-678;9999;A

csv3.csv

sku;col5;col6;test
123;18-123;9999;
234;18-786;9999;A
345;12-678;9999;

merge.py

#!/usr/bin/env python

import csv
import pandas as pd

inputs = ["test/csv1.csv", "test/csv2.csv","test/csv3.csv"]

# First determine the field names from the top line of each input file
fieldnames = []
for filename in inputs:
  with open(filename, "rb") as f_in:
    reader = csv.reader(f_in,delimiter=';')
    headers = next(reader)
    for h in headers:
      if h not in fieldnames:
        fieldnames.append(h)

# Then copy the data
with open("final/out.csv", "w",) as f_out:  
  writer = csv.DictWriter(f_out, fieldnames=fieldnames,delimiter=";")
  #headers
  f_out.write('; '.join(fieldnames)+"\n")
  for filename in inputs:
    with open(filename, "rb") as f_in:
      reader = csv.DictReader(f_in,delimiter=';')  # Uses the field names in this file
      for line in reader:
        writer.writerow(line)


#make unique result
a = pd.read_csv("final/out.csv",sep =';', low_memory=False)
a = a.astype('object')

print (a.groupby(['sku'],as_index=False).first())