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Python Institute PCED-30-02 Questions & Answers - in .pdf

PCED-30-02 pdf
  • Total Q&A: 52
  • Update: Jul 23, 2026
  • Price: $59.99
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  • Vendor: Python Institute
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
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Exact Python Institute PCED-30-02 Exam Questions with Correct Answers, verified by Experts with years of Experience in IT Field.

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Python Institute PCED-30-02 Q&A - Testing Engine

PCED-30-02 Study Guide
  • Total Q&A: 52
  • Update: Jul 23, 2026
  • Price: $59.99
Testing Engine
  • Vendor: Python Institute
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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

1. Consider a Python program that assigns a string value "5" to a variable and then attempts to multiply it by an integer 3. The programmer expects numeric multiplication. What will actually happen when the code is executed?

A) 8
B) Error
C) 15
D) "555"


2. A teacher wants to compare the number of students in different school clubs:

Which type of chart would be most appropriate to show this comparison? Select the best answer.

A) Bar chart
B) Pie chart
C) Line chart
D) Bubble chart


3. A healthcare provider analyzes patient records to determine that appointment cancellations spike during weather alerts and flu season.
What type of analytics is this?

A) Descriptive analytics - it reports appointment numbers across past seasons.
B) Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
C) Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
D) Predictive analytics - it uses weather and illness trends to forecast future cancellations.


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


5. You are given two lists representing daily page views and sign-ups on a website:
views = [120, 130, 128, 700, 115, 123, 119, 680, 122]
signups = [12, 15, 13, 50, 11, 14, 10, 55, 13]
You want to:
- remove outliers (views > 600), and
- calculate correlation between the cleaned lists.
Which code accomplishes this correctly? Select the best answer.

A)

B)

C)

D)


Solutions:

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

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