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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
|
| Data Analysis Fundamentals | 20% | - Data Collection and Preparation
|
| Working with Data Using Python Libraries | 30% | - NumPy Fundamentals
|
| Python Programming for Data Analysis | 30% | - Control Flow and Functions
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
Which approaches are commonly used to extract structured data from APIs in Python?
(Choose two)
- A. Load CSV directly with re.compile()
- B. Open Excel files using matplotlib
- C. Access data using requests.get() and parse it with .json()
- D. Use the requests module to retrieve JSON responses
Correct Answer: C,D 🗳️
Which of the following libraries is specifically optimized for high-performance numerical computation with multi-dimensional arrays in Python?
- A. pandas
- B. matplotlib
- C. NumPy
- D. seaborn
Correct Answer: C 🗳️
Which of the following exceptions would most likely be raised if a string is directly converted to an integer in Python?
- A. RuntimeError
- B. IOError
- C. ValueError
- D. TypeError
Correct Answer: C 🗳️
Which method is commonly used to handle missing numerical data in a dataset?
- A. Replacing with text labels
- B. Multiplying all missing values by zero
- C. Filling with the mean or median
- D. Dropping all columns
Correct Answer: C 🗳️
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. join(..., how='outer')
- C. append()
- D. merge(..., how='inner')
Correct Answer: D 🗳️
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