Data analysis (Pandas): practice, test and prove it

Covers DataFrame basics, loc and iloc, filtering, groupby, merges, missing values, apply and pivot tables.

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Start the data analysis (pandas) test Read the first lesson

Pandas screenings rarely ask you to recite the documentation. They show a small DataFrame or a line of code and ask what comes out: how many rows a slice returns, what a groupby produces, or why a filter raises an error. Many analyst take-home tasks are built on exactly these operations.

This page lets you practise those questions with short explanations after each answer. The lessons cover the two areas where most candidates lose marks: selecting data with loc and iloc, and summarising or combining tables with groupby, merge and pivot_table.

Benchmark: The pass mark on this site is 80%, and pandas questions commonly appear in screenings for data analyst, business analyst and junior data science roles. Requirements vary by employer.

Lessons

Selecting rows and columns with loc, iloc and filtersHow loc and iloc differ, why slice ends behave differently, and how to write combined filters that do not break.Lesson 1

Summarising and combining data with groupby, merge and pivot_tableHow to aggregate by group, join two tables without losing or duplicating rows, and reshape results with pivot_table.Lesson 2

Missing values and data types: isna, fillna, dropna and conversionsHow to find and handle NaN, convert text columns to numbers and dates, and avoid the type mistakes that make totals silently wrong.Lesson 3

Transforming columns: apply, map, str methods and avoiding slow loopsHow to create and change columns with vectorised operations and .str methods, and when apply and map are the right tool.Lesson 4

Interview prep

Data analysis (Pandas) interview questionsQuestions interviewers commonly ask analysts about pandas, with answers that show how you actually work with data.6 questions

Certificate

Free with an accountA PDF with your name, best score and date. Records this site's tests only.

Common questions

Do I need to know NumPy before pandas?

Not deeply. Knowing that pandas columns are arrays and that operations apply to the whole column at once is enough for most analyst screenings.

Which pandas version do these questions assume?

The questions use stable behaviour that has worked the same way across recent versions, such as loc, iloc, groupby and merge. They avoid features that changed recently.

Is pandas tested alongside SQL?

Often, yes. Many analyst screenings include both, and the ideas map closely: a filter is a WHERE clause, groupby is GROUP BY, and merge is a JOIN.

Data analysis (Pandas) test for interviewWhat the screening round looks like, with a 5-question sample.