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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q19-Q24):

NEW QUESTION # 19
What will the following function return?
def average(*args):
return sum(args) / len(args)
average(4, 5, 6)

Answer: C


NEW QUESTION # 20
Which operation would most efficiently apply element-wise multiplication to two NumPy arrays of equal size?

Answer: D


NEW QUESTION # 21
Which actions are considered part of basic data validation tasks in Python using Pandas?
(Choose two)

Answer: A,C


NEW QUESTION # 22
When joining two tables in a relational database using SQL, which clause is used to specify the relationship between their columns?

Answer: D


NEW QUESTION # 23
Which of the following practices contributes most to making Python scripts modular and maintainable?

Answer: C


NEW QUESTION # 24
......

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