Python csv file - Open a csv file and take all info from 2 columns, get unique values and then remove some replies(without Pandas)

Question

I have created a csv file with 5 columns

Machines | VM | Status | Node | Resolve

I want to take all values under Node and Resolve, find the unique values and then remove certain responses(There are some "none" and "record" there which I don't need).

What is the best way to do this?

I was trying to take 1 column at a time and then putting it in sets which did work but is there a quicker way? From the set I was then trying to take away the values I didn't need but realised I was ending up with some values have \n at the end.

Usually I use Pandas which I love to us but I am unable to use this on the machine I am working on at the moment.

unique3=[]

with open("machines.csv", "r") as file:
    mach = file.readlines()
    
     for c in mach:
        split_lines = c.split(",")[3]
        unique3.append(split_lines)
       
unique4=[]

with open("machines.csv", "r") as file2:
    mach2 = file2.readlines()

    for c in mach2:
        split_lines2 = c.split(",")[4]
        unique4.append(split_lines2)

uniqueunique = (set(unique4 + unique3))

Any help greatly appreciated, I know this is probably straight forward but I struggle with lists and strings

Answer 1

Something like this:

import csv

with open("machines.csv", "r") as f:
    rdr = csv.reader(f)
    next(rdr) # skip header if any, otherwise - remove this line
    *_, node, resolve = zip(*rdr)
    unique = set(node).union(set(resolve))
    print(unique)

Then you can remove unwanted values