PCAD-31-02 Exams Collection & PCAD-31-02 Official Practice Test

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| Section | Weight | Objectives |
|---|
| Topic 1: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 2: Data Visualization and Communication | | |
| Topic 3: Exploratory Data Analysis | | |
| Topic 4: SQL and Data Management | | |
| Topic 5: Statistical Methods and Modeling | | |
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q93-Q98):
NEW QUESTION # 93
Which of the following are key differences between Pandas and NumPy arrays?
(Choose two)
- A. Pandas integrates better with tabular data and missing values
- B. NumPy supports string indexing; Pandas does not
- C. Pandas handles labeled data; NumPy does not
- D. Pandas Series are more memory efficient than NumPy arrays
Answer: A,C
NEW QUESTION # 94
What is one potential risk of dynamically constructing SQL queries using string concatenation in Python scripts?
- A. Slower database performance
- B. Increased memory usage
- C. Exposure to SQL injection attacks
- D. Missing foreign key constraints
Answer: C
NEW QUESTION # 95
Which method in a Python class is responsible for initializing the object's attributes at the time of creation?
- A. __str__()
- B. __init__()
- C. __getattr__()
- D. __main__()
Answer: B
NEW QUESTION # 96
Which methods can be used to validate data types and structure in a Pandas DataFrame?
(Choose two)
- A. df.info()
- B. df.memory_usage()
- C. df.dtypes
- D. df.to_csv()
Answer: A,C
NEW QUESTION # 97
When fetching DATETIME values from a SQL database into Python, which Python data type is most appropriate for storing and manipulating these values?
- A. float
- B. datetime.datetime
- C. time.struct_time
- D. str
Answer: B
NEW QUESTION # 98
......
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