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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Python Basics for Data Analysis	32.5%	- Python Fundamentals 1. Implement control flow structures (loops, conditionals) 2. Use variables, data types, and basic operators 3. Define and use functions - Data Structures 1. Apply common operations and methods to data structures 2. Work with lists, tuples, dictionaries, and sets - File Handling 1. Read from and write to files (text, CSV) 2. Use the csv module for basic CSV operations
Topic 2: Working with Data and Performing Simple Analyses	32.5%	- Simple Analytical Techniques 1. Calculate descriptive statistics (mean, median, mode) 2. Identify basic patterns and trends in data - Data Cleaning and Transformation 1. Perform basic data transformation (filtering, sorting, grouping) 2. Handle missing and inconsistent data - 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 3: Introduction to Data and Data Analysis Concepts	22.5%	- Data Analysis Process and Workflow 1. Describe the steps of the data analysis process 2. Identify common data sources and collection methods 3. Explain the role of data cleaning and preparation - 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. Classify data as quantitative or qualitative 3. Explain how data becomes meaningful
Topic 4: Communicating Insights and Reporting	12.5%	- Data Visualization 1. Recognize common visualization types (bar, line, pie charts) 2. Select appropriate visuals for different data types 3. Interpret simple data visualizations - 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 (Q25-Q30):

NEW QUESTION # 25
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.strip().split(', ')
B. fields = line.split().strip(', ')
C. fields = line.replace(', ', '|').split('|')
D. fields = line.split(', ').trim()

Answer: A

NEW QUESTION # 26
Which of the following statements about Python functions are correct? (Choose two.)

A. Positional arguments must be passed in the order defined, while keyword arguments can be passed in any order using their parameter names.
B. Default parameters must always come before required ones in the parameter list.
C. Functions can only return numeric values or strings.
D. If a function does not contain a returnstatement, it returns Noneby default.
E. passexecutes the function body and returns its result.
F. A function cannot call itself or be passed as an argument to itself.

Answer: A,D

Explanation:
Positional arguments are matched to parameters by their position, so they must follow the defined order, while keyword arguments are matched by name and can be provided in any order. If a function completes without an explicit return statement, Python returns None automatically.

NEW QUESTION # 27
Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.

A. Developing machine learning algorithms to predict user behavior.
B. Creating summary tables and charts to describe patterns in historical data.
C. Designing a data pipeline to ingest and process real-time sensor data.
D. Recommending pricing strategies using predictive modeling and A/B testing.

Answer: B

Explanation:
Creating summary tables and charts to describe patterns in historical data is a core responsibility of a data analyst, focusing on descriptive analytics and reporting rather than building predictive models, machine learning systems, or engineering data pipelines.

NEW QUESTION # 28
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?

A. 4 and 3
B. 3 and 4
C. 3.5 and 3
D. 3 and 3.5

Answer: C

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 # 29
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?

Answer: A

Explanation:
Adding an integer and a float produces a float result, so checking that the type of the sum is float evaluates to True. The variable holding 3.0 is a float, so the isinstance check for float also evaluates to True.

NEW QUESTION # 30
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