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

Python Institute PCAD-31-02 exam
  • Exam Code: PCAD-31-02
  • Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
  • Updated: Aug 22, 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. Series and DataFrame structures
  • 2. Data selection and filtering
  • 3. Handling missing data
  • 4. DataFrame operations (merge, join, concat)
  • 5. GroupBy operations
- NumPy Fundamentals
  • 1. Array indexing and slicing
  • 2. Basic statistical functions
  • 3. Vectorized operations
  • 4. NumPy arrays and operations
- Data Visualization
  • 1. Customizing plots
  • 2. Seaborn introduction
  • 3. Matplotlib basics
  • 4. Creating basic charts (line, bar, scatter, histogram)
Topic 2: Data Analysis Fundamentals20%- Data Collection and Preparation
  • 1. Data import/export operations
  • 2. Data sources and acquisition methods
  • 3. Data cleaning and preprocessing basics
- Introduction to Data Analysis
  • 1. Types of data (structured, unstructured, semi-structured)
  • 2. Data analysis process lifecycle
  • 3. Data analysis concepts and terminology
Topic 3: Applied Data Analysis Projects20%- Exploratory Data Analysis (EDA)
  • 1. Data distribution analysis
  • 2. Correlation analysis
  • 3. Descriptive statistics computation
  • 4. Pattern identification
- Data Analysis Workflow
  • 1. Results interpretation and presentation
  • 2. Data exploration and cleaning
  • 3. Problem definition
  • 4. Analysis and modeling
Topic 4: Python Programming for Data Analysis30%- Control Flow and Functions
  • 1. Conditional statements (if, elif, else)
  • 2. Loops (for, while)
  • 3. Function definitions and parameters
  • 4. Return values and scope
- File Operations
  • 1. Reading from files (text, CSV)
  • 2. Context managers (with statement)
  • 3. Writing to files
- Python Data Types and Structures
  • 1. Lists, tuples, dictionaries, sets
  • 2. Data type conversions
  • 3. Numbers, strings, booleans

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

1. What is the recommended Python library to connect and extract tabular data directly from an Excel file?

A) openpyxl
B) matplotlib
C) sqlite3
D) csv


2. What may occur if a model is evaluated using the same data it was trained on?

A) Overfitting
B) Data leakage
C) Overgeneralization
D) Underfitting


3. Which approaches help tailor data visualizations for non-technical stakeholders?
(Choose two)

A) Use jargon-rich annotations
B) Use raw code outputs for clarity
C) Add context through narrative or titles
D) Focus on trend and summary metrics


4. Which methods are typically used to assess relationships between variables in exploratory data analysis?
(Choose two)

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


5. What is a key assumption of linear regression that distinguishes it from logistic regression?

A) Output values must be binary
B) Predictors must be independent
C) The target variable is unordered categorical
D) The relationship between predictors and the outcome is linear


Solutions:

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

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