DA0-002 Data Acquisition and Preparation Practice Question
An analyst is using Python pandas and has a DataFrame 'sales' with columns 'date', 'product', 'revenue'. They need to create a pivot table showing total revenue per product per month. Which pandas function is most appropriate?
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
✓
sales.pivot_table(index='product', columns='month', values='revenue', aggfunc='sum')
pivot_table is specifically designed to reshape data and aggregate values based on index and columns.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
sales.groupby(['product', 'month']).sum()
Why it's wrong here
groupby can produce a similar result but does not create a pivot layout with rows and columns as separate dimensions.
- ✗
sales.pivot(index='product', columns='month', values='revenue')
Why it's wrong here
pivot requires unique index/column pairs and no aggregation.
- ✓
sales.pivot_table(index='product', columns='month', values='revenue', aggfunc='sum')
Why this is correct
pivot_table creates a matrix with products as rows and months as columns.
- ✗
sales.melt(id_vars=['product'], value_vars=['month', 'revenue'])
Why it's wrong here
melt is for unpivoting, not creating pivot tables.
Go deeper
Related to this question
About these practice questions
One of 986 original DA0-002 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.