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AWK: if-else and for Loop Syntax with Examples

if-else Syntax in AWK

if (condition) {
    commands
} else {
    commands
}

Example 1: Using Inline AWK Command

Input File: emp.txt

eno ename esal eaddr
100 Tanya 1000 Mumbai
200 Bunny 2000 Hyderabad
300 Chinny 3000 Hyderabad
400 Vinny 4000 Chennai
500 Pinny 5000 Mumbai

AWK Command:

awk 'NR!=1 {
    if ($3 > 3000) {
        print $2 " is very costly employee"
    } else {
        print $2 " is not costly employee"
    }
}' emp.txt

Output:

Tanya is not costly employee
Bunny is not costly employee
Chinny is not costly employee
Vinny is very costly employee
Pinny is very costly employee

Example 2: Using an AWK Script File

Input File: emp.csv

eno,ename,esal,eaddr
100,Tanya,1000,Mumbai
200,Bunny,2000,Hyderabad
300,Chinny,3000,Hyderabad
400,Vinny,4000,Chennai
500,Pinny,5000,Mumbai
20,Durga,7000,Hyderabad

AWK Script File: x.txt

BEGIN {
    FS = ",";
}
NR != 1 {
    if ($3 > 3000) {
        print $2 " is very costly employee"
    } else {
        print $2 " is not costly employee"
    }
}

Run the Script:

awk -f x.txt emp.csv

Output:

Tanya is not costly employee
Bunny is not costly employee
Chinny is not costly employee
Vinny is very costly employee
Pinny is very costly employee
Durga is very costly employee

for Loop Syntax in AWK

for (initialization; condition; increment/decrement) {
    commands
}

Example 1: Basic for Loop

awk 'BEGIN {
    for (i = 1; i <= 5; i++) {
        print "The Iteration Number:" i
    }
}'

Output:

The Iteration Number:1
The Iteration Number:2
The Iteration Number:3
The Iteration Number:4
The Iteration Number:5

Example 2: Iterating Over Fields in a String

echo "CAT DOG RAT TIGER" | awk '{
    for (i = 1; i <= NF; i++) {
        print "Field:" i ":" $i
    }
}'

Output:

Field:1:CAT
Field:2:DOG
Field:3:RAT
Field:4:TIGER

Example 3: Iterating Over Fields in a File

Command:

cat emp.txt | awk '{
    for (i = 1; i <= NF; i++) {
        print "Field:" i ":" $i
    }
    print ""
}'

Conditionals in AWK with Case Study

Types of conditionals in AWK:

  • if
  • if-else
  • if-else if-else
  • Ternary operator (condition ? expression1 : expression2)

1. if Statement in AWK

Syntax:

if (condition) {
    commands
}

Example:

awk '{ if ($3 > 3000) print $2 " has a high salary"; }' emp.txt

Explanation:
Prints employee names whose salary is greater than 3000.

2. if-else Statement in AWK

Syntax:

if (condition) {
    commands
} else {
    commands
}

Example:

awk '{
    if ($3 > 3000) {
        print $2 " is highly paid"
    } else {
        print $2 " is not highly paid"
    }
}' emp.txt

Explanation:
Classifies employees based on their salary.

3. if-else if-else Ladder in AWK

Syntax:

if (condition1) {
    commands
} else if (condition2) {
    commands
} else {
    commands
}

Example:

awk '{
    if ($3 >= 5000) {
        print $2 " is a top earner"
    } else if ($3 >= 3000) {
        print $2 " is a mid-level earner"
    } else {
        print $2 " is a junior earner"
    }
}' emp.txt

Explanation:
Categorizes employees into three earning levels.

4. Ternary Operator in AWK

Syntax:

condition ? expression_if_true : expression_if_false

Example:

awk '{ print $2, ($3 > 3000 ? "Expensive Employee" : "Affordable Employee") }' emp.txt

Explanation:
Performs a compact if-else operation in a single line.

5. Logical Operators in AWK Conditionals

  • && (AND): Executes if both conditions are true.
  • || (OR): Executes if at least one condition is true.
  • ! (NOT): Executes if the condition is false.

Example:

awk '{
    if ($3 > 3000 && $4 == "Mumbai") {
        print $2 " is a high earner in Mumbai"
    }
}' emp.txt

Case Study: Employee Data Analysis Using AWK Conditionals

Scenario:
Analyze an employee dataset to classify employees based on salary, location, and experience.

Dataset: emp.csv

eno,ename,esal,eaddr,exp
100,Tanya,1000,Mumbai,1
200,Bunny,2000,Hyderabad,3
300,Chinny,3000,Hyderabad,5
400,Vinny,4000,Chennai,8
500,Pinny,5000,Mumbai,10
600,Durga,7000,Hyderabad,12

AWK Script: employee_analysis.awk

BEGIN {
    FS = ",";
    print "Employee Analysis Report\n---------------------------"
}

NR != 1 {
    # Salary-based classification
    if ($3 >= 5000) {
        salary_status = "Top Earner"
    } else if ($3 >= 3000) {
        salary_status = "Mid-Level Earner"
    } else {
        salary_status = "Junior Earner"
    }

    # Experience-based classification
    experience_status = ($5 >= 10) ? "Highly Experienced" : ($5 >= 5) ? "Experienced" : "Fresher"

    # Location-based classification
    if ($4 == "Mumbai" && $3 > 4000) {
        location_status = "Premium Mumbai Employee"
    } else if ($4 == "Hyderabad") {
        location_status = "Hyderabad Employee"
    } else {
        location_status = "Other Location Employee"
    }

    # Final report
    print $2 " | " salary_status " | " experience_status " | " location_status
}

Run the Script:

awk -f employee_analysis.awk emp.csv

Output:

Employee Analysis Report
---------------------------
Tanya | Junior Earner | Fresher | Premium Mumbai Employee
Bunny | Junior Earner | Fresher | Hyderabad Employee
Chinny | Mid-Level Earner | Experienced | Hyderabad Employee
Vinny | Mid-Level Earner | Experienced | Other Location Employee
Pinny | Top Earner | Highly Experienced | Premium Mumbai Employee
Durga | Top Earner | Highly Experienced | Hyderabad Employee

Key Features:

  1. Layered Conditionals:

    • Used nested if-else statements for multi-level salary classification.
    • Implemented ternary operators for concise experience-based classification.

  2. Multiple Conditions Handling:

    • Logical operators (&&, ||) handled location and salary-based categorization.

  3. Reusable AWK Scripts:

    • Separated business logic into an AWK script (employee_analysis.awk) for reusability.

Field Separators in AWK (FS) with Examples

Field Separator Description Example Command Sample Input Output
Space (default) Default separator (whitespace) awk '{print $1, $2}' data.txt 101 Tanya Pune 101 Tanya
Comma (,) For CSV files awk 'BEGIN{FS=","} {print $1, $3}' employees.csv 101,Tanya,5000,Pune 101 5000
Colon (:) For /etc/passwd-like files awk 'BEGIN{FS=":"} {print $1, $3}' users.txt user:x:1000:1000:/home/user:/bin/bash user 1000
Tab (\t) Tab-separated files awk 'BEGIN{FS="\t"} {print $1, $2}' data.txt 102\tDurga\tDelhi 102 Durga
Pipe (|) Data with pipe delimiter awk 'BEGIN{FS="|"} {print $2, $4}' records.txt 103|Charlie|4500|Bangalore Charlie Bangalore
Multiple Spaces Ignore multiple spaces awk 'BEGIN{FS="[ ]+"} {print $1, $3}' data.txt 104 Diana Mumbai 104 Mumbai
Hyphen (-) Hyphen-separated data awk 'BEGIN{FS="-"} {print $1, $2}' projects.txt 105-Eve-Chennai 105 Eve
Custom RegEx Combination of delimiters awk 'BEGIN{FS="[:,]"} {print $1, $3}' data.txt 106:Frank,6000,Hyderabad 106 6000

Example Files Content

employees.csv:

101,Tanya,5000,Pune
102,Durga,4000,Delhi
103,Charlie,4500,Bangalore
104,Diana,6000,Mumbai

records.txt:

103|Charlie|4500|Bangalore
104|Diana|6000|Mumbai

Dynamic FS using -F option

awk -F"," '{print $1, $4}' employees.csv   # Comma as separator
awk -F"|" '{print $2}' records.txt         # Pipe as separator
awk -F"\t" '{print $1, $2}' data.txt       # Tab as separator

Predefined Variables in AWK

Variable Description Example Command Sample Output
FS Field Separator (default: space/tab) awk 'BEGIN{FS=","} {print $1}' employees.csv 101, 102, 103, 104
NF Number of fields in the current record awk '{print "Fields:", NF}' employees.csv Fields: 4 (for each line)
NR Number of the current record (line number) awk '{print "Line:", NR, $0}' employees.csv Line: 1 101,Tanya,5000,Pune
RS Record Separator (splits records) Newline (\n)

Advanced FS Example (Multiple Delimiters)

awk 'BEGIN{FS="[:,]"} {print $1, $2, $3}' multi_sep.txt

multi_sep.txt:

201:George,7500,Hyderabad
202:Helen,8000,Chennai

Output:

201 George 7500
202 Helen 8000

Examples Using Predefined Variables

FS (Field Separator) Example

echo "Apple,Banana,Carrot" | awk 'BEGIN {FS=","} {print $1, $2, $3}'

Output:

Apple Banana Carrot

NR (Number of Records) & NF (Number of Fields) Example

echo "Apple Banana Carrot" | awk 'END {print "The Number of Records:", NR; print "The Number of Fields:", NF}'

Output:

The Number of Records: 1
The Number of Fields: 3

Note:

  • NR gives the total number of lines processed.
  • NF gives the number of fields in the last processed record.
  • In the BEGIN block, NR and NF are always 0 because no data has been processed yet.

Checking Records in a File (emp.txt)

awk 'END {print "The Number of Records:", NR; print "The Number of Fields:", NF}' emp.txt

Using RS (Record Separator) and FS Together

Sample File (demo.txt):

APPLE,BANANA:CAT,DOG:JAVA,PYTHON

Example Command:

awk 'BEGIN {FS=","; RS=":"} {print "Record Number:", NR; print $1 "--->" $2; print ""} END {print "Total Records:", NR; print "Fields in Last Record:", NF;}' demo.txt

Output:

Record Number: 1
APPLE--->BANANA

Record Number: 2
CAT--->DOG

Record Number: 3
JAVA--->PYTHON

Total Records: 3
Fields in Last Record: 2

BEGIN, ACTION, and END Block Execution Order

awk '{print "ACTION"} BEGIN {print "BEGIN"} END {print "END"}' demo.txt

Output:

BEGIN
ACTION
END

Note:

  • Although you can change the order of BEGIN, ACTION, and END blocks in code, it's not recommended for readability.
  • The execution always follows:
    • BEGIN → ACTION (for each line) → END

Key Takeaways

  • Use FS for customizing field separation (e.g., FS="," for CSV files).
  • NR and NF provide insights into processed data — total lines and fields per line.
  • RS can be customized for non-standard record delimiters (e.g., RS=":").
  • Always remember that NR and NF are 0 in the BEGIN block.