Latest PCED-30-02 Mock Test & PCED-30-02 Exam Details

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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q45-Q50):

NEW QUESTION # 45
You are developing a temperature control module for a laboratory incubator. Your objectives are to:
- generate timestamps every 10 minutes over a 3-hour span (i.e., 0 to 180 minutes), and
- simulate five evenly spaced target temperatures between 35.0°C and 37.0°C for system calibration.
Which code snippet correctly produces both sequences using NumPy? Select the best answer.
import numpy as np

Answer: C

Explanation:
np.arange(0, 181, 10) generates timestamps from 0 through 180 in 10-minute steps (end is excluded, so using 181 includes 180). np.linspace(35.0, 37.0, 5) generates five evenly spaced temperatures including both 35.0°C and 37.0°C.


NEW QUESTION # 46
You are given a short Python script that uses both arithmetic and assignment operators. The variable x is initialized as 4, then updated using x *= 2 + 3. What will be printed when the final value of x is displayed?

Answer: C

Explanation:
Python evaluates the addition first because of operator precedence. The expression 2 + 3 equals
5, then x *= 5 multiplies the current value of x (4) by 5, resulting in a final value of 20.


NEW QUESTION # 47
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

Answer: B,D


NEW QUESTION # 48
A script attempts to divide two numbers using / and //. The values are 7 and 2. The developer wants to understand the difference between true division and floor division. What are the results respectively?

Answer: D

Explanation:
The / operator performs true division, returning a float result of 3.5. The // operator performs floor division, truncating the decimal part and returning the integer value 3.


NEW QUESTION # 49
A financial technology company is reviewing its data practices to ensure legal and ethical compliance.
Which of the following actions would support responsible data handling and align with regulations like GDPR, HIPAA, and CCPA? (Choose two.)

Answer: D,E

Explanation:
Encrypting stored and transmitted data protects sensitive information from unauthorized access and supports regulatory requirements for data security. Providing clear explanations of data usage and obtaining explicit consent ensures transparency and aligns with core principles of data protection regulations such as lawful processing and user rights.


NEW QUESTION # 50
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