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

  • Exam Code: PCAD-31-02
  • Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
  • Updated: Aug 01, 2026   Q&As: 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 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)
Topic 2: Working with Data Using Python Libraries30%- Data Visualization
  • 1. Seaborn introduction
  • 2. Customizing plots
  • 3. Matplotlib basics
  • 4. Creating basic charts (line, bar, scatter, histogram)
- Pandas Library
  • 1. Series and DataFrame structures
  • 2. Data selection and filtering
  • 3. DataFrame operations (merge, join, concat)
  • 4. Handling missing data
  • 5. GroupBy operations
- NumPy Fundamentals
  • 1. Array indexing and slicing
  • 2. Vectorized operations
  • 3. NumPy arrays and operations
  • 4. Basic statistical functions
Topic 3: Python Programming for Data Analysis30%- File Operations
  • 1. Context managers (with statement)
  • 2. Writing to files
  • 3. Reading from files (text, CSV)
- Control Flow and Functions
  • 1. Function definitions and parameters
  • 2. Conditional statements (if, elif, else)
  • 3. Return values and scope
  • 4. Loops (for, while)
- Python Data Types and Structures
  • 1. Data type conversions
  • 2. Numbers, strings, booleans
  • 3. Lists, tuples, dictionaries, sets
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. Results interpretation and presentation
  • 2. Data exploration and cleaning
  • 3. Analysis and modeling
  • 4. Problem definition

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

1. When merging two Pandas DataFrames using a common key, which parameters are essential to ensure accurate and conflict-free results?
(Choose two)

A) on
B) ignore_index
C) dropna
D) suffixes


2. Which of the following is the most suitable data structure in Python for representing a tabular row with column names?

A) dictionary
B) set
C) list
D) tuple


3. Which data collection method is most appropriate when gathering opinions from a target audience at scale?

A) Web scraping
B) Sensor logs
C) Surveys
D) Transactional data


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

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


5. Which operations are valid when working with Pandas Series?
(Choose two)

A) Using .columns to rename
B) Applying NumPy universal functions
C) Merging by index using merge()
D) Arithmetic vector operations


Solutions:

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

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