Processing CSV files in Bash Scripting - Practice Problems & Coding Challenges

Challenge - 5 Problems

💻 Command Output

intermediate

Extract the second column from a CSV file

Given a CSV file data.csv with the following content:

name,age,city
Alice,30,New York
Bob,25,Los Angeles
Carol,27,Chicago

Which command outputs only the age column values (excluding the header)?

A tail -n +2 data.csv | cut -d',' -f2

B cut -d',' -f2 data.csv

C awk -F',' '{print $2}' data.csv

D sed '1d' data.csv | cut -d',' -f3

💡 Hint

Use a command to skip the header line, then extract the second column.

Option A skips the first line (header) using tail -n +2 and then extracts the second column with cut -d',' -f2. Option A includes the header. Option A prints the header too. Option A extracts the third column, not the second.

💻 Command Output

intermediate

Count rows where the city is 'Chicago'

Using the same data.csv file, which command outputs the number of rows where the city is exactly Chicago?

A grep -c '^.*,.*,Chicago$' data.csv

B sed -n '/Chicago/p' data.csv | wc -l

C awk -F',' '$3 == "Chicago" {count++} END {print count}' data.csv

D grep -c 'Chicago' data.csv

💡 Hint

Use a tool that can compare exact field values.

Option C uses awk to check if the third field equals 'Chicago' exactly and counts matches. Option C matches lines ending with Chicago but includes header if it matches. Option C counts any line with 'Chicago' anywhere, including header. Option C counts lines containing 'Chicago' but includes header if present.

🔧 Debug

advanced

Fix the script to sum ages from CSV

This script aims to sum all ages from data.csv (excluding header):

total=0
while IFS=',' read name age city; do
  total=$((total + age))
done < data.csv
echo $total

What is the main reason this script does not produce the correct sum?

Bash Scripting

total=0
while IFS=',' read name age city; do
  total=$((total + age))
done < data.csv
echo $total

A The script includes the header line, causing a non-numeric addition error.

B The IFS variable is not set correctly to split CSV fields.

C The variable 'total' is not initialized before the loop.

D The read command does not split fields because of missing quotes.

💡 Hint

Check if the header line is processed as data.

The script reads the header line 'name,age,city' and tries to add 'age' (a string) to total, causing an error or wrong result. Skipping the header fixes this.

🚀 Application

advanced

Extract unique cities sorted alphabetically

Which command pipeline extracts all unique city names from data.csv (excluding header) and sorts them alphabetically?

A sed '1d' data.csv | cut -d',' -f3 | sort -r | uniq

B cut -d',' -f3 data.csv | sort -u

C tail -n +2 data.csv | cut -d',' -f3 | sort | uniq

D awk -F',' 'NR>1 {print $3}' data.csv | sort | uniq

💡 Hint

Skip the header, extract the third column, then sort and remove duplicates.

Option D uses awk to skip the header (NR>1), prints the third field, sorts, and removes duplicates with uniq. Option D works but uniq after sort is less efficient than sort -u. Option D includes header. Option D sorts in reverse order, not alphabetical.

🧠 Conceptual

expert

Why is parsing CSV with simple tools risky?

Why can using basic tools like cut or awk with a comma delimiter be unreliable for processing CSV files?

A Because CSV files always use tabs, not commas, as delimiters.

B Because CSV fields can contain commas inside quoted strings, breaking simple delimiter splitting.

C Because these tools do not support reading files larger than 1MB.

D Because these tools cannot handle files with more than 3 columns.

💡 Hint

Think about how commas inside quotes affect splitting.

CSV fields may contain commas inside quotes, so splitting by commas blindly breaks fields. Proper CSV parsers handle quoted fields correctly. Options A, B, and D are incorrect statements.