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Python Institute PCAD-31-02 real answers - Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)

PCAD-31-02
  • Exam Code: PCAD-31-02
  • Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
  • Updated: Aug 11, 2026
  • Q & A: 146 Questions and Answers
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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Analysis Fundamentals20%- Data Collection and Preparation
  • 1. Data import/export operations
  • 2. Data cleaning and preprocessing basics
  • 3. Data sources and acquisition methods
- Introduction to Data Analysis
  • 1. Data analysis process lifecycle
  • 2. Types of data (structured, unstructured, semi-structured)
  • 3. Data analysis concepts and terminology
Topic 2: Working with Data Using Python Libraries30%- Data Visualization
  • 1. Creating basic charts (line, bar, scatter, histogram)
  • 2. Customizing plots
  • 3. Matplotlib basics
  • 4. Seaborn introduction
- NumPy Fundamentals
  • 1. Array indexing and slicing
  • 2. Vectorized operations
  • 3. Basic statistical functions
  • 4. NumPy arrays and operations
- Pandas Library
  • 1. GroupBy operations
  • 2. Data selection and filtering
  • 3. DataFrame operations (merge, join, concat)
  • 4. Series and DataFrame structures
  • 5. Handling missing data
Topic 3: Python Programming for Data Analysis30%- Control Flow and Functions
  • 1. Return values and scope
  • 2. Loops (for, while)
  • 3. Conditional statements (if, elif, else)
  • 4. Function definitions and parameters
- Python Data Types and Structures
  • 1. Data type conversions
  • 2. Lists, tuples, dictionaries, sets
  • 3. Numbers, strings, booleans
- File Operations
  • 1. Reading from files (text, CSV)
  • 2. Writing to files
  • 3. Context managers (with statement)
Topic 4: Applied Data Analysis Projects20%- Exploratory Data Analysis (EDA)
  • 1. Correlation analysis
  • 2. Data distribution analysis
  • 3. Pattern identification
  • 4. Descriptive statistics computation
- Data Analysis Workflow
  • 1. Analysis and modeling
  • 2. Data exploration and cleaning
  • 3. Problem definition
  • 4. Results interpretation and presentation

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

1. When joining two tables in a relational database using SQL, which clause is used to specify the relationship between their columns?

A) JOIN ON
B) HAVING
C) FROM
D) GROUP BY


2. Which of the following correctly demonstrates the use of parameterized queries using Python's sqlite3 module?

A) cursor.execute("SELECT * FROM users WHERE id = ?", user_id)
B) cursor.execute("SELECT * FROM users WHERE id = " + user_id)
C) cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
D) cursor.execute("SELECT * FROM users WHERE id = ':id'", {'id': user_id})


3. What is the main reason for using try-except blocks in a data analysis script that reads multiple files?

A) To ensure functions always return None
B) To automatically restart the script after execution
C) To enforce strict type annotations
D) To gracefully handle runtime errors without crashing the program


4. Which technique is considered a primary defense against SQL injection when executing database queries from Python?

A) Using parameterized queries
B) Encrypting the database connection
C) Escaping quotes manually in SQL strings
D) Closing the database cursor after each query


5. What is the primary purpose of using annotations in a data visualization?

A) To highlight important data points and provide contextual information
B) To ensure faster rendering in large datasets
C) To enhance interactivity in static plots
D) To replace the need for axes


Solutions:

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

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