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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q83-Q88):

NEW QUESTION # 83
What is the primary purpose of using a requirements.txt file in Python-based data projects?

A. To list the packages and versions required for consistent environment setup
B. To track script runtime dependencies during execution
C. To store the current working directory of Python modules
D. To automatically compress source code for deployment

Answer: A

NEW QUESTION # 84
Which practices enhance both readability and professionalism in spreadsheet formatting?
(Choose two)

A. Using uniform date formats across columns
B. Applying consistent font and cell styling
C. Aligning column headers to the left
D. Centering all data regardless of type

Answer: A,B

NEW QUESTION # 85
Which characteristics are typically associated with supervised learning algorithms?
(Choose two)

A. They require labeled training data
B. They are useful for regression and classification tasks
C. They work only with numerical features
D. They automatically detect outliers

Answer: A,B

NEW QUESTION # 86
When working with relational databases in Python, what are key components required to establish and manage database connections?
(Choose all that apply)

A. Cursor object for executing queries
B. Python's random module for generating keys
C. Database driver or module (e.g., sqlite3)
D. Connection object to interface with the database

Answer: C,D

NEW QUESTION # 87
Which methods are typically used to assess relationships between variables in exploratory data analysis?
(Choose two)

A. Box plots
B. Scatter plots
C. Histogram analysis
D. Correlation matrix

Answer: B,D

NEW QUESTION # 88
......

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