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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Visualization and Communication | 15% | - Visualization principles and best practices
|
| Topic 2: Data Exploration and Statistical Analysis | 25% | - Descriptive statistics
|
| Topic 3: Data Acquisition and Preprocessing | 30% | - Data collection, integration and storage
|
| Topic 4: Data Modeling and Machine Learning Basics | 20% | - Supervised learning fundamentals
|
| Topic 5: SQL and Database Integration | 10% | - Relational database concepts
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
1. What object-oriented principle allows a child class to reuse and extend the behavior of a parent class in a Python data modeling scenario?
A) Encapsulation
B) Inheritance
C) Abstraction
D) Composition
2. What does the describe() method in Pandas provide when applied to a numerical DataFrame column?
A) Only the standard deviation of the data
B) A normalized version of the data column
C) A histogram of the data distribution
D) Basic descriptive statistics such as count, mean, and quartiles
3. Which method is appropriate for combining two DataFrames based on a shared key column where non-matching rows should be excluded from the result?
A) concat()
B) merge(..., how='inner')
C) append()
D) join(..., how='outer')
4. When joining two tables in a relational database using SQL, which clause is used to specify the relationship between their columns?
A) GROUP BY
B) JOIN ON
C) FROM
D) HAVING
5. Which Python constructs are useful for comparing and managing object identity in a data pipeline?
(Choose all that apply)
A) == operator for checking value equivalence
B) is operator for memory-level comparison
C) id() function to retrieve unique object identifiers
D) str() function to convert data formats
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: B,C |
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