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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Working with Data and Performing Simple Analyses	32.5%	- 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. Use the math and statistics modules for basic calculations 2. Utilize the collections module for specialized containers 3. Work with the datetime module for date/time data 4. Perform basic operations with NumPy arrays
Topic 2: Python Basics for Data Analysis	32.5%	- 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 - Python Fundamentals 1. Implement control flow structures (loops, conditionals) 2. Define and use functions 3. Use variables, data types, and basic operators
Topic 3: Introduction to Data and Data Analysis Concepts	22.5%	- 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 Analysis Process and Workflow 1. Explain the role of data cleaning and preparation 2. Describe the steps of the data analysis process 3. Identify common data sources and collection methods - Data Ethics and Privacy 1. Recognize ethical considerations in data handling 2. Understand basic data privacy concepts
Topic 4: Communicating Insights and Reporting	12.5%	- Data Visualization 1. Select appropriate visuals for different data types 2. Recognize common visualization types (bar, line, pie charts) 3. Interpret simple data visualizations - 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

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q31-Q36):

NEW QUESTION # 31
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(', ').trim()
B. fields = line.replace(', ', '|').split('|')
C. fields = line.strip().split(', ')
D. fields = line.split().strip(', ')

Answer: C

Explanation:
Stripping removes leading and trailing whitespace from the line, and then splitting on the comma- space delimiter correctly separates the values into a list for further formatting.

NEW QUESTION # 32
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 filtered, aggregated, and formatted into summaries - like total visits per category - which then provide traffic reports.
B. Raw event logs are stored, archived, and indexed - like by user ID and session - which then facilitate audit trails.
C. Raw event logs are structured, analyzed, and interpreted into information - like conversion rates by product - which then builds knowledge of customer preferences.
D. Raw event logs are validated, organized, and compiled into datasets - like timestamped user actions - which then support system debugging.

Answer: C

Explanation:
Marketing insights are produced when raw event logs are structured, analyzed, and interpreted to generate meaningful metrics such as conversion rates. These interpreted results transform data into actionable knowledge about customer behavior and preferences.

NEW QUESTION # 33
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. 5, 4, 3, 2, 1
B. 5, 3, 1
C. 4, 2, 0
D. 5, 3

Answer: B

Explanation:
The range starts at 5 and decreases by 2 each step until it reaches a value greater than 0. The generated sequence is 5, 3, and 1.

NEW QUESTION # 34
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. Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
B. Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
C. Descriptive analytics - it reports appointment numbers across past seasons.
D. Predictive analytics - it uses weather and illness trends to forecast future cancellations.

Answer: A

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 # 35
A Python developer is testing truth values of different data types using the bool() function. The expression bool([0]) is evaluated in the script. What result should be expected when this expression is printed?

A. Error
B. False
C. None
D. True

Answer: D

Explanation:
In Python, any non-empty list evaluates to True in a Boolean context. Even though the element inside the list is zero, the list itself is not empty, so the result is True.

NEW QUESTION # 36
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