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| Section | Weight | Objectives |
|---|
| Python Programming for Data Analysis | 30% | - Control Flow and Functions
- 1. Return values and scope
- 2. Loops (for, while)
- 3. Function definitions and parameters
- 4. Conditional statements (if, elif, else)
- Python Data Types and Structures
- 1. Lists, tuples, dictionaries, sets
- 2. Data type conversions
- 3. Numbers, strings, booleans
- File Operations
- 1. Reading from files (text, CSV)
- 2. Context managers (with statement)
- 3. Writing to files
|
| Working with Data Using Python Libraries | 30% | - Pandas Library
- 1. Series and DataFrame structures
- 2. DataFrame operations (merge, join, concat)
- 3. Handling missing data
- 4. GroupBy operations
- 5. Data selection and filtering
- Data Visualization
- 1. Customizing plots
- 2. Creating basic charts (line, bar, scatter, histogram)
- 3. Matplotlib basics
- 4. Seaborn introduction
- NumPy Fundamentals
- 1. NumPy arrays and operations
- 2. Vectorized operations
- 3. Array indexing and slicing
- 4. Basic statistical functions
|
| Data Analysis Fundamentals | 20% | - Introduction to Data Analysis
- 1. Data analysis process lifecycle
- 2. Types of data (structured, unstructured, semi-structured)
- 3. Data analysis concepts and terminology
- Data Collection and Preparation
- 1. Data sources and acquisition methods
- 2. Data cleaning and preprocessing basics
- 3. Data import/export operations
|
| Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
- 1. Pattern identification
- 2. Correlation analysis
- 3. Descriptive statistics computation
- 4. Data distribution analysis
- Data Analysis Workflow
- 1. Problem definition
- 2. Analysis and modeling
- 3. Results interpretation and presentation
- 4. Data exploration and cleaning
|
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q136-Q141):
NEW QUESTION # 136
Which features are commonly supported by both Matplotlib and Seaborn for customizing visualizations?
(Choose two)
- A. Adding plot titles and axis labels
- B. Automatic plot animations
- C. Inserting audio annotations
- D. Changing plot color palettes
Answer: A,D
NEW QUESTION # 137
Which technique is considered a primary defense against SQL injection when executing database queries from Python?
- A. Closing the database cursor after each query
- B. Using parameterized queries
- C. Encrypting the database connection
- D. Escaping quotes manually in SQL strings
Answer: B
NEW QUESTION # 138
What is the primary reason to use .head() and .tail() methods in pandas when exploring datasets?
- A. To rename columns
- B. To create visualizations
- C. To preview the first and last few rows of data
- D. To delete missing values
Answer: C
NEW QUESTION # 139
Which of the following statistical measures are considered measures of central tendency?
(Choose two)
- A. Mode
- B. Variance
- C. Interquartile range
- D. Mean
Answer: A,D
NEW QUESTION # 140
Which practices contribute to better exception handling in data pipelines involving file I/O and numerical computations?
(Choose two)
- A. Suppressing all error output using pass
- B. Logging error messages for later inspection during failures
- C. Catching all exceptions using a generic except: clause without specifying the error
- D. Using specific exception types like FileNotFoundError or ZeroDivisionError
Answer: A,B
NEW QUESTION # 141
......
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