Updated: Sep 03, 2026
No. of Questions: 146 Questions & Answers with Testing Engine
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| Certification Vendor: | Python Institute |
|---|---|
| Exam Name: | Python Institute Certified Associate Data Analyst with Python |
| Exam Number: | PCAD-31-02 |
| Exam Format: | Single-select questions, Multiple-select questions |
| Real Exam Qty: | 48 |
| Passing Score: | 75% |
| Available Languages: | English, German, Spanish, French, Japanese |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | 6 years |
| Exam Price: | $195 USD |
| Related Certifications: | PCAP – Certified Associate in Python Programming PCED – Certified Associate in Python Engineering PCEP – Certified Entry-Level Python Programmer |
| Recommended Training: | PCAD Official Syllabus and Resources Edube Interactive Learning Platform |
| Exam Registration: | Python Institute Official Registration |
| Sample Questions: | Python Institute PCAD-31-02 Sample Questions |
| Exam Way: | Online proctored or onsite at authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended: PCAP – Certified Associate in Python Programming or equivalent knowledge, basic understanding of statistics and data concepts |
| Official Syllabus URL: | https://pythoninstitute.org/pcad |
| Section | Weight | Objectives |
|---|---|---|
| SQL and Database Integration | 10% | - Python-database connectivity
|
| Data Exploration and Statistical Analysis | 25% | - Descriptive statistics
|
| Data Visualization and Communication | 15% | - Data storytelling and reporting
|
| Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Data Acquisition and Preprocessing | 30% | - Data preparation with Pandas and NumPy
|
Question 1
Which actions are valid techniques for handling erroneous categorical values in a dataset?
(Choose two)
A. Replacing inconsistent labels with a standardized value
B. Converting all values to integers
C. Normalizing using min-max scaling
D. Removing rows with invalid labels
Question 2
When analyzing a sales dataset using Pandas, which of the following techniques help extract key insights by grouping and summarizing the data?
(Choose two)
A. Using rename() to change column headers
B. Applying agg() to calculate multiple metrics like mean and max
C. Using fillna() to replace missing product prices
D. Using groupby() to compute total sales per region
Question 3
Which method is typically used in Pandas to check if a column contains only values within an expected range?
A. df.sort_values()
B. df.sample()
C. df.clip()
D. df.isin()
Question 4
Which of the following practices contributes most to making Python scripts modular and maintainable?
A. Hard-coding file paths in every function
B. Writing all logic in the global scope
C. Structuring code with reusable functions and modules
D. Using global variables freely
Question 5
Which of the following improves the readability of a spreadsheet used for collaborative data analysis?
A. Adding freeze panes to lock header rows
B. Using colored fonts to highlight every cell
C. Converting numeric values into images
D. Removing gridlines from all sheets
Solutions:
| Question 1 Answer: A,D | Question 2 Answer: B,D | Question 3 Answer: D | Question 4 Answer: C | Question 5 Answer: A |
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