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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Perform basic operations with NumPy arrays
  • 3. Utilize the collections module for specialized containers
  • 4. Use the math and statistics modules for basic calculations
- Simple Analytical Techniques
  • 1. Identify basic patterns and trends in data
  • 2. Calculate descriptive statistics (mean, median, mode)
Topic 2: Python Basics for Data Analysis32.5%- Python Fundamentals
  • 1. Define and use functions
  • 2. Implement control flow structures (loops, conditionals)
  • 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)
Topic 3: Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Recognize common visualization types (bar, line, pie charts)
  • 2. Interpret simple data visualizations
  • 3. Select appropriate visuals for different data types
- Data Storytelling and Reporting
  • 1. Present insights with visual and verbal techniques
  • 2. Create clear and concise analytical reports
  • 3. Structure insights as a narrative
Topic 4: 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. 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?

A) 1, 3
B) 2, 4, 6
C) 1, 2, 3, 4, 5
D) 1, 3, 5


2. 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)


3. A dictionary is defined as d = {"a":1, "b":2}. The programmer accesses d["c"]. What happens when this line executes?

A) Returns 0
B) Raises KeyError
C) Adds key automatically
D) Returns None


4. A student writes a program using input() to collect user data, then tries to add 5 to the input value without conversion. The program crashes. What is the most likely cause of this behavior?

A) input returns float
B) input returns int
C) input returns string
D) Syntax error


5. You are reading a data.csvfile line by line. To prepare each line for formatting with f-strings, you need to remove extra whitespace and split the values by commas.
Which line should you insert to correctly clean and parse the input?

A) fields = line.split().strip(', ')
B) fields = line.split(', ').trim()
C) fields = line.replace(', ', '|').split('|')
D) fields = line.strip().split(', ')


Solutions:

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

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