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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q90-Q95):

NEW QUESTION # 90
Which method is typically used in Pandas to check if a column contains only values within an expected range?

Answer: D


NEW QUESTION # 91
What is the primary reason to use .head() and .tail() methods in pandas when exploring datasets?

Answer: B


NEW QUESTION # 92
Which of the following exceptions would most likely be raised if a string is directly converted to an integer in Python?

Answer: A


NEW QUESTION # 93
Which Python library is most commonly used to establish a connection to a SQLite database and perform SQL operations?

Answer: B


NEW QUESTION # 94
What result will the following Pandas expression return: df['Age'].notnull().all()?

Answer: A


NEW QUESTION # 95
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