PCAD-31-02 Python Data Analysis: 360 Practice Questions

This course contains the use of artificial intelligence. AI assisted question drafting and the cover illustration; the questions and explanations were subsequently reviewed and revised.

Build your ability to reason through a data analysis workflow for PCAD-31-02 — Certified Associate Data Analyst with Python. A script can run successfully while still using the wrong denominator, mixing incompatible keys or drawing an unsupported conclusion. These practice questions ask you to identify both computational behavior and analytical meaning.

What is included

• 360 original questions across six tests: four topic drills with 84, 90, 50 and 40 questions, followed by two 48-question mock exams.
• Each mock allows 60 minutes and follows the published five-block allocation of 14/16/4/9/5 questions.
• Every question includes feedback for every answer option, an overall explanation, a focused study suggestion and links to supporting learning material.
• Small, self-contained Python and SQL examples sit alongside calculations, diagnostic scenarios, chart decisions and reporting tasks.

Work through acquisition and validation, Python functions and objects, SQL joins and transactions, descriptive statistics, bootstrap reasoning, linear and logistic regression, pandas alignment and reshaping, NumPy arrays, visual analysis and evidence communication. Pay attention to missing values, sampling units, identifier meaning, data leakage and the strength of the claims your results support.

How to use the tests

Start with a topic drill and study the feedback for the options you considered. Recreate code examples in the stated environment when useful. Then attempt each mock under its time allowance and revisit the decision rule behind each error. The topic-drill durations are study allowances rather than official exam timings.

Code questions state relevant environments and assumptions, including Python 3.12, pandas 3.0, NumPy 2.x or a specific plotting library when behavior depends on them. You should already be comfortable with basic Python and introductory data analysis; these tests provide practice rather than a complete first course.

The practice threshold is 75%. Questions are equally weighted, and multiple-select items require the complete correct selection. These practice scores are not an official score conversion or a prediction of exam results. This is independent preparation, unaffiliated with Python Institute or OpenEDG. It contains original exercises, not actual exam questions, and does not guarantee certification.