Deleting columns from a CSV file using an if statement

(I am still really new at python/coding) I am working with a program the spits out a text file with thousands of lines of data for an output which I need to plot. I need to parse the first three columns of data remove the rest. When the simulation is done running sometime the program will give me three columns and sometime it will give me up to 10 columns. I have been trying to figure out how to remove the columns I do not need. I have tried a for loop, and I have thought about a while loop but I do not know what to do.

this is what I have for the while loop:

fin = "file location"
fout = "file location"

#delete unused columns
while cols_to_remove in fin >3:
    cols_to_remove = [3, 4, 5] # Column indexes to be removed (starts at 0)
    cols_to_remove = sorted(cols_to_remove, reverse=True) # Reverse so we remove from the end first
    row_count = 0 # Current amount of rows processed
    with open(fin, "r") as source:
        reader = csv.reader(source)
        with open(fout, "w", newline='') as result:
            writer = csv.writer(result)
            for row in reader:
                row_count += 1
                for col_index in cols_to_remove:
                    del row[col_index]
                writer.writerow(row)

The if loop I tried was:

for cols_to_remove in fin == 10:
    cols_to_remove = [3, 4, 5, 6, 7, 8, 9] # Column indexes to be removed (starts at 0)
    cols_to_remove = sorted(cols_to_remove, reverse=True) # Reverse so we remove from the end first
    row_count = 0 # Current amount of rows processed
    reader = csv.reader(source)
    with open(fout, "w", newline='') as result:
        writer = csv.writer(result)
        for row in reader:
            row_count += 1
            for col_index in cols_to_remove:
                del row[col_index]
            writer.writerow(row)
elif cols_to_remove in fin == 9:
    cols_to_remove = [3, 4, 5, 6, 7, 8] # Column indexes to be removed (starts at 0)
    cols_to_remove = sorted(cols_to_remove, reverse=True) # Reverse so we remove from the end first
    row_count = 0 # Current amount of rows processed
    reader = csv.reader(source)
    with open(fout, "w", newline='') as result:
        writer = csv.writer(result)
        for row in reader:
            row_count += 1
            for col_index in cols_to_remove:
                del row[col_index]
            writer.writerow(row)
else:
    break

I am not sure if I am on the right track. If I use the section of code that starts with cols_to_remove and change it to [3, 4] when there are five columns it works fine.

This is what I start with from the Text file (first five lines of data set):

X [m],Y [m],Z [m],Task #,Pulse #,Pixel X,Pixel Y,Pixel #,Return,Intensity
4.630,-5.078,16.517,0,0,0,30,960,0,0.211
4.937,-4.779,13.969,0,0,2,32,1026,0,0.106
4.630,-4.623,16.366,0,0,0,33,1056,0,0.205
4.937,-4.626,14.418,0,0,2,33,1058,0,0.296
5.087,-4.626,14.868,0,0,3,33,1059,0,0.109

This is what I want to end up with (in a CSV file):

X [m],Y [m],Z [m]
4.630,-5.078,16.517
4.937,-4.779,13.969
4.630,-4.623,16.366
4.937,-4.626,14.418
5.087,-4.626,14.868

I think you are thinking about this the opposite way around, why get columns from the csv if you will just delete it later. Instead, only get the columns you need, as so:

new_list = []
with open('example.csv') as f:
    # Create reader object
    reader_obj = csv.reader(f)
    
    #Add next(reader_obj) here

    # Iterate over each row in the csv 
    # file using reader object
    for row in reader_obj:
        new_list.append([row[0], row[1], row[2]]) #get the first 3 elements

print(new_list)

A simpler way

with open('example.csv') as f:
    new_list = [[row[0], row[1], row[2]] for row in csv.reader(f)]

print(new_list)

Note that both these methods will include the header row. To remove it: Add the next() function where I commented in the first code. Or you can simply pop the first element of the new-list afterwards.

new_list.pop(0) #Pop (remove) the first element of the list

Edit:
You can also use pandas, much simpler tbh:

df = pd.read_csv('example.csv', usecols=[0,1, 2], header=0)

@Michael_Butscher's advice to use a slice of the row seems like the easiest approach:

for row in reader:
    writer.writerow(row[:3])

That will include the fields of a row starting at index 0 and going up to (but not including) index 3, or, "the first three fields". When I run that on your input of 10 columns I get:

X [m],Y [m],Z [m]
...

In the future, if you do need to delete certain fields from a row, the approach you showed of looping over indices backwards and deleting the element at that index should work:

for row in reader:
    for i in [9, 7, 2]:
        del row[i]
    writer.writerow(row)

when I run that on your input of 10 columns I get:

X [m],Y [m],Task #,Pulse #,Pixel X,Pixel Y,Return
...

I think the bigger problem with the code you showed was the "outer logic" of the while-loops. As it is written in your questions:

while cols_to_remove in fin >3:
    ...

should produce an error because:

• cols_to_remove is declared inside the while-loop... so it cannot be used as the predicate for the while-loop
• even if cols_to_remove were declare before (outside) the loop, it'd still error because you cannot ask, "is this list of integers in the string of my filename?"

I think what you'd want in that case is:

for row in reader:
    if len(row) > 3:
        # delete some columns

Here's the small, complete program to keep just the first 3 fields of each row. I'm not using with open(...) to keep it looking neater:

import csv

f_in = open("input.csv", newline="")
f_out = open("output.csv", "w", newline="")

reader = csv.reader(f_in)
writer = csv.writer(f_out)

for row in reader:
    writer.writerow(row[:3])

I'm also not closing the files myself because Python will do that when it exits.

You can always do:

with open("input.csv", newline="") as f_in, open("output.csv", "w", newline="") as f_out:
    ...

and if you're using Python 3.10+ you can group them with parentheses and have them on multiple lines:

with (
    open("input.csv", newline="") as f_in,
    open("output.csv", "w", newline="") as f_out,
):
    ...