python - "\r\n" is ignored at csv file end -

import csv  impfilename = [] impfilename.append("file_1.csv") impfilename.append("file_2.csv")  expfilename = "masterfile.csv" l = [] overwrite = false comma = ","  f in range(len(impfilename)):     open(impfilename[f], "r") impfile:         table = csv.reader(impfile, delimiter = comma)          row in table:             data_1 = row[0]             data_2 = row[1]             data_3 = row[2]             data_4 = row[3]             data_5 = row[4]             data_6 = row[5]          dic = {"one":data_1, "two":data_2, "three":data_3, "four":data_4, "five":data_5, "six":data_6}          in range(len(l)):             if l[i]["one"] == data_1:                 print("data, 1 = " + data_1 + " has been updated using data " + impfilename[f])                 l[i] = dic                 overwrite = true                 break          if overwrite == false:             l.append(dic)         else:             overwrite = false     print(impfilename[f] + " has been added list 'l'")  open(expfilename, "a") expfile:     print("master file being created...")     in range(len(l)):         expfile.write(l[i]["one"] + comma + l[i]["two"] + comma + l[i]["three"] + comma + l[i]["four"] + comma + l[i]["five"] + comma + l[i]["six"] + "\r\n")  print("process complete") 

this program takes 2 (or more) .csv files , compares uniqueid (data_1) of each row others. if match, assumes current row updated version overwrites it. if there no match it's new entry.

i store each row's data in dictionary, stored in list "l".

once files have been processed, output list "l" "masterfile.csv" in specified format.

---the problem---
last row of "file_1.csv" , first row of "file_2.csv" end on same line in output file. continue on new line.

--visual

... data_1,data_2,data_3,data_4,data_5,data_6 data_1,data_2,data_3,data_4,data_5,data_6data_1,data_2,data_3,data_4,data_5,data_6 data_1,data_2,data_3,data_4,data_5,data_6 ... 

note: there no header rows in of .csv files.
i've tried using "\n" @ end of "expfile.write" - same result

just little suggestion. comparing 2 files in way looks expensive . try using pandas in following way.

import pandas data1 = pandas.read_csv("file_1.csv") data2 = pandas.read_csv("file_2.csv")  # merging 2 dataframes  combineddata = data1.append(data2,ignore_index=true)  # dropping duplicates # give name of column on comparing uniqueness uniquedata = combineddata.drop_duplicates(["columnname"])