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

PCAD-31-02
  • Exam Code: PCAD-31-02
  • Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
  • Updated: Aug 07, 2026
  • Q & A: 146 Questions and Answers
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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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

1. Which Python library is most commonly used to establish a connection to a SQLite database and perform SQL operations?

A) pymysql
B) psycopg2
C) sqlalchemy
D) sqlite3


2. Which features are commonly supported by both Matplotlib and Seaborn for customizing visualizations?
(Choose two)

A) Inserting audio annotations
B) Automatic plot animations
C) Adding plot titles and axis labels
D) Changing plot color palettes


3. In a scatter plot showing the relationship between advertising spend and sales revenue, the points form a tight upward-sloping pattern. What conclusion can be drawn?

A) Advertising has no effect on sales
B) There is a strong positive correlation
C) The correlation is weak and likely negative
D) The data shows no apparent relationship


4. Why is it important to use a test dataset separate from the training dataset when evaluating a machine learning model?

A) To evaluate the model's performance on unseen data
B) To optimize the model's training accuracy
C) To reduce the number of iterations during training
D) To ensure the loss function is minimized


5. Which technique would be most appropriate to handle missing numerical values in a dataset intended for machine learning?

A) Replacing with NULL
B) Imputation using mean or median
C) Filling with random values
D) Dropping all columns


Solutions:

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

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