PROGRAMMING SKILLS

Pandas test for hiring

See how candidates read and write pandas code for everyday work with tabular data.

12 minutes
18 questions
Intermediate
Multiple choice
Questions in English
Desktop only

Use this test free See the question formats

The short answer

The pandas assessment is a 12-minute test of practical work with the pandas library for Python. It measures how well candidates read and write code to select, clean, combine, and summarize tabular data. Use it for analyst roles that work in Python, data science and data engineering positions, machine learning practitioners, and Python developers handling tabular data.

What it measures

How well a candidate reads and writes pandas code to select, clean, combine and summarize tabular data.

Selecting and indexing

Candidates select rows and columns from small DataFrames.

Cleaning and reshaping data

Candidates clean and transform values in tabular data.

Merging and concatenating

Candidates join tables and combine data.

Grouping and summarizing

Candidates create grouped summaries from data.

Question formats

Multiple choice

The candidate: Reads a short situation, table or statement and picks the right answer, or every right answer.

You see: Whether the candidate knows the material well enough to apply it, not just recognize it.

18 questions in 12 minutes, served one at a time.

Roles this test fits

Analyst roles that work in Python, data science and data engineering positions, machine learning practitioners, and Python developers who handle tabular data day to day.

What the pandas assessment can show

Practical code reading
See whether candidates can work out what short pandas snippets return, rather than relying only on a resume or a list of tools.
Coverage of everyday data tasks
The 18 multiple-choice questions cover selecting, cleaning, transforming, joining, and summarizing data in small DataFrames.
A focused first step
Use the 12-minute result to decide where a follow-up work sample or conversation could add useful evidence.
A consistent starting point
Every candidate sees self-contained snippets with the data shown in full, so the questions do not require a particular industry dataset.

What you get for each candidate

Example report (fictional data)Pandas

73%Percentile 51. Benchmark: HireValid candidates, n = 873

Selecting and indexing68%

Cleaning and reshaping data81%

Merging and concatenating74%

Grouping and summarizing67%

Integrity ScoreHigh confidence

Stayed on the test tab throughout
No pasted answers
Answered at a steady pace

Scores, profiles and integrity signals are evidence for you to review alongside an interview, never an automatic decision.

Use this test free

How the assessment handles integrity signals

Each candidate gets a different set of questions from large pools. Question order and answer options are shuffled, and the browser shows one question at a time. Timing runs on the server; reloading returns the same question with only the time left. Candidates cannot copy or select question text, and a blocked copy attempt is recorded in the timeline. The test lasts 12 minutes and candidates cannot go back to an earlier question. HireValid records signals such as time away from the test tab, pastes into answers, and answers faster than a question can be read. The employer can review those signals in an Integrity Score and evidence timeline; the score never decides on its own. With candidate consent, the employer can add webcam photos at random moments.

How we prevent AI cheating · Integrity signals

Use the score as one piece of evidence

Treat the score as a signal for a person to review, not a hiring decision. Pair it with a short work sample using tabular data and a structured interview about how the candidate selects, cleans, joins, and summarizes data. Keep the work sample and interview focused on tasks relevant to the role. For broader data workflow context, compare it with the ETL test or SQL Coding: Querying.

Structured interview questions

Tell me how you would check a small DataFrame before selecting rows and columns for an analysis.
Listen for a clear sequence of checks and an explanation of how the candidate would confirm the selected data is what the task calls for.
Describe how you would clean and transform values when a dataset does not match the format needed for a summary.
Listen for a practical approach to identifying inconsistent values and checking the result of the transformation.
Walk me through how you would combine two tables and produce a grouped summary for a task.
Listen for how the candidate would reason about joining the tables, grouping the data, and checking whether the summary answers the request.

Understand scoring and benchmarks

Fairness and accommodations

Every question is a short, self-contained snippet with the data shown in full, so no knowledge of a particular industry or dataset is needed. Column names and values use plain English words, metric units and names from many backgrounds, with no money symbols, sports or holidays. Questions follow current pandas 2 behavior and avoid features that changed between versions or produce warnings. Scratch paper is allowed for every candidate.

You can give any candidate extra time as an accommodation. Results are evidence for a person to review, never an automatic decision.

Provisional: reliability is reported once 200 candidates have completed it.

Read our fairness approach

Test details

A timed test of practical work with the pandas library for Python. Candidates read short snippets that operate on small DataFrames and work out what they return, or pick the code that does a described job. Questions cover selecting rows and columns, cleaning and transforming values, joining tables, and grouped summaries.

Questions are in English.
Aids allowed: Scratch paper.
Each question is answered once, in order, with no going back.
4 practice questions, 4 minutes, before the timed test.
Taken on a desktop or laptop computer.

pandas, Python are trademarks of their owners. HireValid is not affiliated with or endorsed by them.

Frequently asked questions

What does the pandas assessment measure?+

It measures practical pandas code reading and writing. Candidates read short snippets operating on small DataFrames to work out what they return or choose code for a described task. Topics include selecting rows and columns, cleaning and transforming values, joining tables, and grouped summaries.

How long is the pandas assessment, and what is the format?+

The assessment has 18 multiple-choice questions and takes 12 minutes. It is in English, is desktop-only, and does not allow candidates to return to earlier questions. Scratch paper is allowed. A separate practice set has 4 questions and takes 4 minutes.

Who should use the pandas assessment?+

It is intended for analyst roles that work in Python, data science and data engineering positions, machine learning practitioners, and Python developers who handle tabular data day to day. It focuses on pandas tasks such as selecting, cleaning, joining, and summarizing data.

How should I interpret a pandas assessment score?+

Use the score as evidence for a person to review, alongside a relevant work sample and structured interview. The questions use short, self-contained snippets with the data shown in full. The test follows current pandas 2 behavior and avoids features that changed between versions or produce warnings.