PythonBeginner · Windows, macOS, or Linux with Python 3.12+

Filter CSV rows by an exact value

Copy only rows whose chosen field exactly matches a value.

Before you begin

  • Python 3.12 or newer
What this script changesReads source data without editing it. Creates a new destination and refuses overwrite. Rows are held in memory. Spreadsheet formulas in cell text are preserved as text in the CSV; inspect untrusted data before opening in a spreadsheet.

Set up your example

  1. Save the complete code as csv-filter-rows.py in a working folder.
  2. Save the provided sample files in that same folder; run commands from that folder.

Sample files in this download:

  • sample.csv
  • lookup.csv
  • second.csv
  • wide.csv
  • numbers.csv
  • sample.tsv

Download the ZIP, extract it, and open a terminal inside the extracted folder. The source file is csv-filter-rows.py.

Run the script

Run command
python "csv-filter-rows.py" --input "sample.csv" --column "team" --equals "Red" --output "red.csv"

If your system uses python3 instead of python, use that command for Python examples. Keep paths containing spaces in quotes. Required inputs and optional settings are described in the code and setup steps.

What to expect

Copy only rows whose chosen field exactly matches a value. The sample keeps Ada and Cy and excludes Bo.

The complete script

csv-filter-rows.py
#!/usr/bin/env python3
'Filter CSV rows by an exact value'
import argparse
import json
from pathlib import Path

def write_json(path, value):
    data = json.dumps(value, indent=2, ensure_ascii=False, allow_nan=False) + "\n"
    with Path(path).open("x", encoding="utf-8", newline="") as handle:
        handle.write(data)

import csv
import random
from collections import Counter, defaultdict
from decimal import Decimal
from datetime import datetime

def read_csv(path, delimiter=","):
    with Path(path).open(encoding="utf-8-sig", newline="") as handle:
        reader = csv.DictReader(handle, delimiter=delimiter)
        fields = reader.fieldnames
        if not fields or any(not f for f in fields) or len(set(fields)) != len(fields):
            raise ValueError("Use a nonempty, unique header for every column.")
        rows = list(reader)
    if any(None in row or None in row.values() for row in rows):
        raise ValueError("Every row must have exactly the header's number of cells.")
    return fields, rows

def require(fields, names):
    missing = set(names) - set(fields)
    if missing:
        raise ValueError("Missing columns: " + ", ".join(sorted(missing)))

def write_csv(path, fields, rows):
    with Path(path).open("x", encoding="utf-8", newline="") as handle:
        writer = csv.DictWriter(handle, fieldnames=fields)
        writer.writeheader()
        writer.writerows(rows)

def number(value):
    result = Decimal(value or "0")
    if not result.is_finite():
        raise ValueError("Numbers must be finite.")
    return result

def main():
    parser = argparse.ArgumentParser(description='Filter CSV rows by an exact value')
    parser.add_argument("--input", required=True, help="CSV input with a header")
    parser.add_argument("--output", required=True, help="New destination file or directory")
    parser.add_argument("--column", required=True)
    parser.add_argument("--equals", required=True)
    args = parser.parse_args()
    fields, rows = read_csv(args.input)
    require(fields, [args.column])
    result_fields = fields
    result = [row for row in rows if row[args.column] == args.equals]
    write_csv(args.output, result_fields, result)

if __name__ == "__main__":
    try:
        main()
    except (OSError, ValueError, KeyError, TypeError, ArithmeticError, IndexError, LookupError) as exc:
        raise SystemExit(str(exc))

Open source as plain text · Download source and sample files

How it works

  1. read_csv checks unique headers and row widths before processing.
  2. Comparison is literal and case-sensitive, so Red and red remain different.
  3. The sample keeps Ada and Cy and excludes Bo.

Make it your own

--equals

Change --equals to Blue to select Bo.

Adapt the processing

Edit the list-comprehension condition to use .casefold() on both sides for case-insensitive matching.

Change one setting at a time, run it again on sample data, and compare the output. The customization guide walks through this process.

If something goes wrong

The result contains only a header.

Check --equals for case and surrounding spaces.

The destination already exists.

Choose a new --output path. The script deliberately refuses to replace an existing result.

Reference & next steps

These official references explain the underlying tools. The Scriptage example and guide are original instructional content. See verification notes for what has been checked and the limits of those checks.

Copies a template for your own notes. It does not send anything.