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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Data Analysis Fundamentals	20%	- Data Collection and Preparation 1. Data cleaning and preprocessing basics 2. Data sources and acquisition methods 3. Data import/export operations - Introduction to Data Analysis 1. Types of data (structured, unstructured, semi-structured) 2. Data analysis concepts and terminology 3. Data analysis process lifecycle
Python Programming for Data Analysis	30%	- Python Data Types and Structures 1. Data type conversions 2. Lists, tuples, dictionaries, sets 3. Numbers, strings, booleans - Control Flow and Functions 1. Function definitions and parameters 2. Return values and scope 3. Loops (for, while) 4. Conditional statements (if, elif, else) - File Operations 1. Reading from files (text, CSV) 2. Writing to files 3. Context managers (with statement)
Working with Data Using Python Libraries	30%	- Pandas Library 1. Series and DataFrame structures 2. DataFrame operations (merge, join, concat) 3. GroupBy operations 4. Data selection and filtering 5. Handling missing data - NumPy Fundamentals 1. Basic statistical functions 2. Array indexing and slicing 3. NumPy arrays and operations 4. Vectorized operations - Data Visualization 1. Matplotlib basics 2. Creating basic charts (line, bar, scatter, histogram) 3. Seaborn introduction 4. Customizing plots
Applied Data Analysis Projects	20%	- Exploratory Data Analysis (EDA) 1. Correlation analysis 2. Descriptive statistics computation 3. Data distribution analysis 4. Pattern identification - Data Analysis Workflow 1. Results interpretation and presentation 2. Data exploration and cleaning 3. Problem definition 4. Analysis and modeling

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q69-Q74):

NEW QUESTION # 69
Which Python construct allows you to iterate over a list of dictionary values and apply conditional logic to accumulate numerical values that meet a certain threshold?

A. lambda expression with reduce
B. while loop with try block
C. filter() function with map
D. for loop with if condition

Answer: D

NEW QUESTION # 70
What is the primary reason for using parameterized queries instead of directly formatting SQL strings in Python?

A. To simplify data encryption
B. To reduce the number of SQL statements
C. To prevent SQL injection vulnerabilities
D. To allow dynamic table creation

Answer: C

NEW QUESTION # 71
Which function is used to reshape a NumPy array without modifying the original data values?

A. flatten()
B. resize()
C. transpose()
D. reshape()

Answer: D

NEW QUESTION # 72
What distinguishes structured data from unstructured data in the context of data modeling and storage?

A. Unstructured data cannot be stored or analyzed
B. Structured data follows a consistent schema or format
C. Unstructured data contains only numeric values
D. Structured data cannot be stored in databases

Answer: B

NEW QUESTION # 73
Which of the following are key differences between Pandas and NumPy arrays?
(Choose two)

A. Pandas handles labeled data; NumPy does not
B. Pandas integrates better with tabular data and missing values
C. NumPy supports string indexing; Pandas does not
D. Pandas Series are more memory efficient than NumPy arrays

Answer: A,B

NEW QUESTION # 74
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