Python Institute PCED-30-02 Q&A - in .pdf

  • PCED-30-02 pdf
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Updated: Aug 08, 2026
  • Q & A: 52 Questions and Answers
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  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
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  • Updated: Aug 08, 2026
  • Q & A: 52 Questions and Answers
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  • PCED-30-02 Testing Engine
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Updated: Aug 08, 2026
  • Q & A: 52 Questions and Answers
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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Select appropriate visuals for different data types
  • 2. Recognize common visualization types (bar, line, pie charts)
  • 3. Interpret simple data visualizations
- Data Storytelling and Reporting
  • 1. Create clear and concise analytical reports
  • 2. Structure insights as a narrative
  • 3. Present insights with visual and verbal techniques
Introduction to Data and Data Analysis Concepts22.5%- Data Ethics and Privacy
  • 1. Understand basic data privacy concepts
  • 2. Recognize ethical considerations in data handling
- Define and Classify Data
  • 1. Classify data as quantitative or qualitative
  • 2. Differentiate structured, semi-structured, and unstructured data
  • 3. Explain how data becomes meaningful
- Data Analysis Process and Workflow
  • 1. Explain the role of data cleaning and preparation
  • 2. Identify common data sources and collection methods
  • 3. Describe the steps of the data analysis process
Python Basics for Data Analysis32.5%- Python Fundamentals
  • 1. Implement control flow structures (loops, conditionals)
  • 2. Use variables, data types, and basic operators
  • 3. Define and use functions
- Data Structures
  • 1. Apply common operations and methods to data structures
  • 2. Work with lists, tuples, dictionaries, and sets
- File Handling
  • 1. Use the csv module for basic CSV operations
  • 2. Read from and write to files (text, CSV)
Working with Data and Performing Simple Analyses32.5%- Data Cleaning and Transformation
  • 1. Handle missing and inconsistent data
  • 2. Perform basic data transformation (filtering, sorting, grouping)
- Data Analysis with Python Libraries
  • 1. Perform basic operations with NumPy arrays
  • 2. Work with the datetime module for date/time data
  • 3. Use the math and statistics modules for basic calculations
  • 4. Utilize the collections module for specialized containers
- Simple Analytical Techniques
  • 1. Calculate descriptive statistics (mean, median, mode)
  • 2. Identify basic patterns and trends in data

Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:

1. Below are six possible summaries for your presentation:
- Summary 1: "The data revealed a moderate positive correlation between age and recycling frequency. While 72% of students reported recycling paper regularly, only 39% reported recycling plastic."
- Summary 2: "Analysis showed notable differences in recycling habits by material type, with paper being most recycled and plastic least recycled."
- Summary 3: "Older kids recycled more than younger ones. Paper was the most recycled item- plastic got forgotten a lot."
- Summary 4: "Student responses showed positive environmental habits overall, though participation varied by waste type."
- Summary 5: "A lot of students said they recycle. Some didn't answer every question, so we couldn't figure out everything."
- Summary 6: "We asked more than 300 students about recycling. Most said they recycle paper, but way fewer recycle plastic." Which communication style is the best fit for Group A (data scientists) and Group B (12-year- olds), respectively? Select the best answer.

A) Summary 1 for Group A, Summary 6 for Group B
B) Summary 6 for Group A, Summary 5 for Group B
C) Summary 6 for Group A, Summary 3 for Group B
D) Summary 4 for Group A, Summary 3 for Group B
E) Summary 1 for Group A, Summary 3 for Group B
F) Summary 2 for Group A. Summary 6 for Group B


2. What will be the output of the following code?

A) 10 5
B) 5 10
C) 5 5
D) 10 10


3. You are writing a function named process_data()to read and process numerical input from a file. The function must:
- read the file data.txt,
- attempt to convert the first line into an integer,
- handle file, conversion, or index-related exceptions,
- print the value only if no error occurs,
- and always print a final message after execution.
Which implementation correctly and robustly meets all these conditions? Select the best answer.

A)

B)

C)


4. A programmer writes a script to test operator precedence using the expression 3 + 4 * 2 ** 2. The goal is to evaluate the result correctly based on Python's operator hierarchy rules. What result should the script produce?

A) 19
B) 28
C) 35
D) 49


5. An e-commerce site records every product view and purchase.
Which of the following best describes how these logs become marketing insights?

A) Raw event logs are structured, analyzed, and interpreted into information - like conversion rates by product - which then builds knowledge of customer preferences.
B) Raw event logs are filtered, aggregated, and formatted into summaries - like total visits per category - which then provide traffic reports.
C) Raw event logs are stored, archived, and indexed - like by user ID and session - which then facilitate audit trails.
D) Raw event logs are validated, organized, and compiled into datasets - like timestamped user actions - which then support system debugging.


Solutions:

Question # 1
Answer: E
Question # 2
Answer: C
Question # 3
Answer: B
Question # 4
Answer: A
Question # 5
Answer: A

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