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Python Institute PCED-30-02

PCED-30-02

Exam Code: PCED-30-02

Exam Name: PCED - Certified Entry-Level Data Analyst with Python

Updated: Sep 17, 2026

Q&A Number: 52 Q&As

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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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

Question #1
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?

A. yth
B. tho
C. ytho
D. ythn


Question #2
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.


Question #3
A Python loop uses range(5, 0, -2) to iterate backward. The programmer expects a decreasing sequence. Which values will actually be generated when this loop runs?

A. 4, 2, 0
B. 5, 3, 1
C. 5, 4, 3, 2, 1
D. 5, 3


Question #4
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 stored, archived, and indexed - like by user ID and session - which then facilitate audit trails.
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 validated, organized, and compiled into datasets - like timestamped user actions - which then support system debugging.
D. Raw event logs are structured, analyzed, and interpreted into information - like conversion rates by product - which then builds knowledge of customer preferences.


Question #5
You are given the following list of daily step counts:
steps = [8230, 9020, 7640, 8760, 10020, 2546, 9817]
Your task is to calculate:
- the standard deviation of the step counts,
- the average rounded up to the nearest whole number, and
- the median of the step counts.
Which code snippet correctly performs all three tasks? Select the best answer.
import statistics

A. import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics
B. import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
C. import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics
D. import math
print(statistics.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))


Solutions:

Question #1
Correct Answer: A
Question #2
Correct Answer: A
Question #3
Correct Answer: B
Question #4
Correct Answer: D
Question #5
Correct Answer: D

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