cut Command — Extracting Columns from Text¶

The cut command is used to extract specific columns, fields, or characters from text files. It is especially useful when working with structured data such as CSV files, log files, configuration files, and command output. Mastering cut helps Linux administrators and DevOps engineers quickly retrieve only the information they need.

Learning Path¶

Linux Mastery → Module 3: Text Processing → Lesson 3

Difficulty: Beginner → Intermediate

Reading Time: 30 Minutes

Course Progress

Course: Linux Mastery

Module: Text Processing

Lesson: 3 of 18

What You'll Learn¶

After completing this lesson, you'll be able to:

Understand the cut command
Extract characters from text
Extract fields using delimiters
Extract multiple fields
Work with CSV files
Process Linux configuration files
Combine cut with pipes

Prerequisites¶

Before starting this lesson, complete:

Module 1 – Linux Fundamentals
Module 2 – Linux Command Line Essentials
Module 3 Lessons 1–2

Why Learn cut?¶

Imagine you have the following file:

Alice,Engineering,India

Bob,HR,USA

Charlie,Finance,UK

David,Engineering,Germany

You only need:

Engineering

HR

Finance

Engineering

Instead of manually editing the file:

cut -d "," -f2 employees.csv

Done in seconds.

What is cut?¶

The cut command extracts selected portions of each line from a file.

It can extract:

Characters
Bytes
Fields

Syntax:

cut [OPTION] FILE

Sample File¶

Create a file.

cat > employees.csv

Contents:

Alice,Engineering,India

Bob,HR,USA

Charlie,Finance,UK

David,Engineering,Germany

Press:

Ctrl + D

Extract Fields¶

Fields are separated by delimiters.

Delimiter:

Display only names.

cut -d "," -f1 employees.csv

Output:

Alice

Bob

Charlie

David

Extract Department¶

cut -d "," -f2 employees.csv

Output:

Engineering

HR

Finance

Engineering

Extract Country¶

cut -d "," -f3 employees.csv

Output:

India

USA

UK

Germany

Extract Multiple Fields¶

cut -d "," -f1,2 employees.csv

Output:

Alice,Engineering

Bob,HR

Charlie,Finance

David,Engineering

Extract Field Range¶

cut -d "," -f2-3 employees.csv

Output:

Engineering,India

HR,USA

Finance,UK

Engineering,Germany

Character Extraction¶

Suppose:

Linux

Extract first three characters.

echo Linux | cut -c1-3

Output:

Lin

Extract first character.

echo Linux | cut -c1

Output:

Extract characters 3 to 5.

echo Kubernetes | cut -c3-5

Output:

ber

Working with /etc/passwd¶

Linux user information is stored in:

/etc/passwd

Example entry:

basha:x:1000:1000:Basha:/home/basha:/bin/bash

Display usernames.

cut -d ":" -f1 /etc/passwd

Display user IDs.

cut -d ":" -f3 /etc/passwd

Display login shells.

cut -d ":" -f7 /etc/passwd

Working with Command Output¶

Extract only usernames.

who | cut -d " " -f1

Display filesystem names.

df -h | cut -d " " -f1

Combining with Pipes¶

Search Engineering department.

cut -d "," -f2 employees.csv | grep Engineering

Sort countries.

cut -d "," -f3 employees.csv | sort

Remove duplicates.

cut -d "," -f2 employees.csv | sort | uniq

Count unique departments.

cut -d "," -f2 employees.csv | sort | uniq | wc -l

Common Options¶

Option	Description
`-d`	Specify delimiter
`-f`	Select fields
`-c`	Select characters
`--complement`	Display everything except selected fields

Using --complement¶

Display everything except department.

cut -d "," -f2 --complement employees.csv

Output:

Alice,India

Bob,USA

Charlie,UK

David,Germany

Real Production Examples¶

Extract usernames.

cut -d ":" -f1 /etc/passwd

Extract mounted filesystems.

mount | cut -d " " -f3

Extract pod names.

kubectl get pods | cut -d " " -f1

Extract IP addresses.

ip addr | grep inet | cut -d " " -f6

Extract Docker image names.

docker images | cut -d " " -f1

Production Perspective¶

The cut command is frequently used to:

Process CSV reports
Extract usernames
Analyze logs
Parse configuration files
Build shell scripts
Process Kubernetes and Docker output

It is lightweight, fast, and commonly combined with other text-processing tools.

Hands-on Lab¶

Task 1¶

Create:

cat > students.csv

Contents:

Rahul,CSE,80

Priya,IT,90

Arjun,ECE,85

Neha,CSE,95

Task 2¶

Display names.

cut -d "," -f1 students.csv

Task 3¶

Display departments.

cut -d "," -f2 students.csv

Task 4¶

Display marks.

cut -d "," -f3 students.csv

Task 5¶

Display names and marks.

cut -d "," -f1,3 students.csv

Task 6¶

Display usernames.

cut -d ":" -f1 /etc/passwd

Task 7¶

Display login shells.

cut -d ":" -f7 /etc/passwd

Task 8¶

Count departments.

cut -d "," -f2 students.csv | sort | uniq | wc -l

Command Deep Dive¶

Command	Purpose	Production Example
`cut -d "," -f1`	Extract first field	Usernames
`cut -d ":" -f7`	Extract login shell	`/etc/passwd`
`cut -c1-5`	Extract characters	IDs
`cut --complement`	Exclude fields	CSV processing

Production Troubleshooting Scenario¶

Scenario

A Linux administrator receives a CSV report containing server information.

server01,Running,10.0.0.10

server02,Stopped,10.0.0.11

server03,Running,10.0.0.12

server04,Maintenance,10.0.0.13

Tasks:

Display server names.
Display only IP addresses.
Show server names and status.
Count running servers.

Solutions:

cut -d "," -f1 servers.csv

cut -d "," -f3 servers.csv

cut -d "," -f1,2 servers.csv

grep Running servers.csv | wc -l

Mini Challenge¶

Create:

employees.csv

Alice,Engineering,India,85000

Bob,HR,USA,60000

Charlie,Finance,UK,75000

David,Engineering,Germany,90000

Perform the following:

Display employee names.
Display departments.
Display salaries.
Display names and salaries.
Display everything except salary.
Count unique departments.
Show only Engineering employees and their names.

Best Practices¶

Use cut only for consistently delimited data.
Verify the delimiter before extracting fields.
Combine cut with grep, sort, uniq, and wc for advanced processing.
Use meaningful delimiters such as commas, colons, or tabs.
For complex data extraction, consider awk in later lessons.

Common Mistakes¶

❌ Forgetting the delimiter.

✅ Incorrect:

cut -f2 employees.csv

Correct:

cut -d "," -f2 employees.csv

❌ Using cut on irregularly spaced text.

✅ cut works best with structured, delimiter-separated files.

❌ Expecting cut to process variable-width columns.

✅ Use awk for more advanced parsing.

Interview Questions¶

Beginner¶

What is the purpose of the cut command?
What does -d specify?
What does -f do?
How do you extract the first field?

Intermediate¶

Difference between -c and -f?
Explain --complement.
Why is cut useful for CSV files?
When should you use awk instead of cut?

Architect Level¶

How would you process a large CSV report containing millions of records?
Why is cut commonly used in shell scripting?
How would you combine cut, grep, and sort to analyze production data?

Summary¶

In this lesson, you learned:

Extracting fields using delimiters
Extracting character positions
Processing CSV files
Working with /etc/passwd
Combining cut with other text-processing tools
Real-world administration use cases

The cut command is a simple yet powerful utility for extracting structured data. It is commonly used in shell scripts, automation, and production environments.

Key Takeaways¶

cut extracts fields or characters from text.
-d specifies the delimiter.
-f selects fields.
-c selects character positions.
cut works best with consistently structured data.
Combine cut with grep, sort, uniq, and wc for efficient text processing.

What's Next?¶

sort Command — Sorting Text in Linux

In the next lesson, you'll learn:

Alphabetical sorting
Numeric sorting
Reverse sorting
Sorting by specific fields
Removing duplicates with sort
Practical log and report analysis