Sample PCED-30-02 Exam & PCED-30-02 Test Questions Pdf

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
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. Understand basic data privacy concepts
  • 2. Recognize ethical considerations in data handling
- Define and Classify Data
  • 1. Differentiate structured, semi-structured, and unstructured data
  • 2. Classify data as quantitative or qualitative
  • 3. Explain how data becomes meaningful
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
- Data Analysis with Python Libraries
  • 1. Work with the datetime module for date/time data
  • 2. Utilize the collections module for specialized containers
  • 3. Use the math and statistics modules for basic calculations
  • 4. Perform basic operations with NumPy arrays
- 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. Implement control flow structures (loops, conditionals)
  • 2. Define and use functions
  • 3. Use variables, data types, and basic operators
- 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)
Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Interpret simple data visualizations
  • 2. Recognize common visualization types (bar, line, pie charts)
  • 3. Select appropriate visuals for different data types
- Data Storytelling and Reporting
  • 1. Structure insights as a narrative
  • 2. Present insights with visual and verbal techniques
  • 3. Create clear and concise analytical reports

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q36-Q41):

NEW QUESTION # 36
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.

Answer: B

Explanation:
It wraps file reading and integer conversion in a try block, catches the relevant file, conversion, and indexing exceptions, prints the value only in the no-error path using an else block, and uses a finally block to always print the final message.


NEW QUESTION # 37
A healthcare provider analyzes patient records to determine that appointment cancellations spike during weather alerts and flu season.
What type of analytics is this?

Answer: C

Explanation:
It examines existing data to understand why cancellations increase, identifying underlying causes such as weather alerts and flu season, which characterizes diagnostic analytics.


NEW QUESTION # 38
A loop is designed using range(1, 6, 2) to iterate through numbers. The developer wants to know exactly which values will be generated during execution. Which sequence correctly represents the values produced?

Answer: C

Explanation:
The range(start, stop, step) function generates numbers starting from 1, increasing by 2, and stopping before 6. Therefore, the resulting sequence is 1, 3, and 5.


NEW QUESTION # 39
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?

Answer: B

Explanation:
Slicing includes the start index but excludes the end index. Characters at indices 1, 2, and 3 are selected, producing the substring "yth".


NEW QUESTION # 40
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 # 41
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