LFCS Essential Commands Practice Question
A developer needs to extract the third column from a CSV file where columns are separated by commas, but some fields contain commas within double quotes. Which command correctly handles this?
⚠ Common exam trap
It's easy for candidates to default to using `cut` or simple `awk` with a delimiter, not realizing that CSV files with quoted fields require a pattern-based field definition like `FPAT` to correctly parse embedded commas.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
awk 'BEGIN { FPAT = "[^,]*|\\"[^\\"]+\\"" } { print $3 }' file.csv
It uses `awk` with the `FPAT` variable to define a field pattern that correctly handles commas inside double-quoted fields. The pattern `[^,]*|\"[^\"]+\"` matches either a sequence of non-comma characters or a double-quoted string (including any commas within it), ensuring that the third column is extracted accurately even when fields contain embedded commas.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
cut -d',' -f3 file.csv
Why it's wrong here
cut does not handle quoted commas.
- ✗
awk -F',' '{ print $3 }' file.csv
Why it's wrong here
Simple comma split fails on quoted commas.
- ✓
awk 'BEGIN { FPAT = "[^,]*|\\"[^\\"]+\\"" } { print $3 }' file.csv
Why this is correct
FPAT regex matches non-comma sequences or quoted strings.
- ✗
sed 's/[^,]*,[^,]*,\\([^,]*\\).*/\1/' file.csv
Why it's wrong here
sed regex fails on quoted commas.
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