L2 · Working engineerAdvanced L2~6 min · 4 tests#87

Process a CSV: Average Salary

Read CSV text with Python's csv.DictReader and compute the average salary, converting types and handling an empty file. Real-world data task, tested.

The problem

csv_text is CSV with a header row name,salary. Return the average salary as a float, or 0.0 if there are no data rows.

Use the csv module rather than splitting on commas yourself.

Examples

Example 1

Input

average_salary('name,salary\nJohn,50000\nAlice,70000\nBob,60000')

Expected output

60000.0

Example 2

Input

average_salary('name,salary\nA,100')

Expected output

100.0

+ 2 hidden tests on Submit — header only, quoted comma.

Edge cases to ask about

Header only
Quoted fields with commas
Non-numeric salary

Hints

0/3

How an interviewer scores this

0/9

1. Understand the problemRestate it, ask about edge cases and input size.
2. Write a brute-force solutionCorrect first, clever later.
3. Get the correct outputautoAll visible examples pass.
4. Analyse time complexityautoCommit to a Big-O in the Complexity Lab.
5. Analyse space complexityautoExtra memory, not the input.
6. Identify the bottleneckautoMeasure your code — where does it bend?
7. OptimiseUsually: a set or dict instead of a scan.
8. Explain why it worksSay it out loud to Solvi.
9. Test the edge casesautoSubmit passes every hidden test.

Python 3.13 · average_salary

def average_salary(csv_text):
    """Average of the salary column, 0.0 if no rows."""
    # Write your solution here
    pass

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Complexity Lab

What does this cost as n grows?

Interviewers score the analysis as much as the code. Commit to an answer first — then check it, and read why.

Time complexity of the optimal solution

Space complexity (extra memory)

Pick both to reveal the answer.

From brute force to optimal

The progression an interviewer wants to hear, one step at a time.

Approach	Time	Space	Idea
csv.DictReader	O(n)	O(1)	Streams rows; handles quoting and embedded commas.

Walkthrough of the optimal approach (try it yourself first)

csv.DictReader(io.StringIO(text)) yields one dict per row, keyed by header. Keep a running total and count rather than building a list — this version would work on a 10 GB file.

line.split(",") breaks on "Smith, J"; the csv module handles quoting, which is what the hidden test checks.

Complexity: O(n) time, O(1) space. Rows are read one at a time; only a running total and count are kept.

Reveal the reference solution

import csv
import io

def average_salary(csv_text):
    reader = csv.DictReader(io.StringIO(csv_text))
    total = count = 0
    for row in reader:
        total += float(row["salary"])
        count += 1
    return total / count if count else 0.0

Follow-ups interviewers ask

Average per department.
Skip rows with an invalid salary and report them.

Frequently asked interview questions

Core interview concepts, complexities, and follow-ups scored by hiring teams.

What is the time complexity of Process a CSV: Average Salary in Python?

The optimal solution runs in O(n) time and O(1) auxiliary space. Rows are read one at a time; only a running total and count are kept.

What follow-up questions do interviewers ask about Process a CSV: Average Salary?

Average per department. Skip rows with an invalid salary and report them.