How to delete a particular column in csv file without pandas library

Question

I am trying to delete particular columns in csv file.

CSV file:

Name,Age,YearofService,Department,Allocation
Birla,49,12,Welding,Production
Robin,38,10,Molding,Production

I am trying to delete Entire column having column header "Department" and "Allocation".

My code :

 with open(input.csv,'r') as i:
    with open(output.csv,'w',new line='') as o:
       reader=csv.reader(i)
       writer = csv.writer(o)
       for row in reader:
          for i in range(len(row)):
            if row[i]!="Department" and row[i]!="Allocation":
              writer.writerow(row)

My output:

Name
Birla
Robin
Age
49
38
YearofService
12
10

Expected output:

Name,Age,YearofService
Birla,49,12
Robin,38,10

We cannot gaurantee Department and Allocation will be in column header position "3" and "4". thats y am using iteration through length of row

Answer 1

In this case, the csv.DictReader and csv.DictWriter classes are very handy:

import csv

with open("input.csv") as instream, open("output.csv", "w") as outstream:
    # Setup the input
    reader = csv.DictReader(instream)

    # Setup the output fields
    output_fields = reader.fieldnames
    output_fields.remove("Department")
    output_fields.remove("Allocation")

    # Setup the output
    writer = csv.DictWriter(
        outstream,
        fieldnames=output_fields,
        extrasaction="ignore",  # Ignore extra dictionary keys/values
    )

    # Write to the output
    writer.writeheader()
    writer.writerows(reader)

Notes

• For input, each of the row will be a dictionary such as

  {'Name': 'Birla', 'Age': '49', 'YearofService': '12', 'Department': 'Welding', 'Allocation': 'Production'}
  

• For output, we remove those columns (fields) that we don't need, see output_fields

• The extraaction parameter tells DictReader to ignore extra keys/values from the dictionaries

Update

In order to remove columns from a CSV file we need to

1. Open the input file, reader all the rows, close it
2. Open it again to write.

Here is the code, which I modified from the above

import csv

with open("input.csv") as instream:
    # Setup the input
    reader = csv.DictReader(instream)
    rows = list(reader)

    # Setup the output fields
    output_fields = reader.fieldnames
    output_fields.remove("Department")
    output_fields.remove("Allocation")

with open("input.csv", "w") as outstream:
    # Setup the output
    writer = csv.DictWriter(
        outstream,
        fieldnames=output_fields,
        extrasaction="ignore",  # Ignore extra dictionary keys/values
    )

    # Write to the output
    writer.writeheader()
    writer.writerows(rows)