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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Visualization and Communication
Topic 2: Data Acquisition and Pre-Processing	29.2%
Topic 3: Statistical Methods and Modeling
Topic 4: Exploratory Data Analysis
Topic 5: SQL and Data Management

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q144-Q149):

NEW QUESTION # 144
What is the main advantage of using Seaborn over Matplotlib when creating complex statistical visualizations in Python?

A. Seaborn requires no data preprocessing for missing values
B. Seaborn automatically saves plots as image files
C. Seaborn works exclusively with NumPy arrays
D. Seaborn provides high-level abstractions for attractive and informative graphics

Answer: D

NEW QUESTION # 145
Which SQL commands are typically used to retrieve and manipulate data in a data analysis context?
(Choose all that apply)
Response:

A. ROLLBACK
B. INSERT
C. SELECT
D. UPDATE

Answer: B,C

NEW QUESTION # 146
What does the describe() method in Pandas provide when applied to a numerical DataFrame column?

A. A normalized version of the data column
B. Only the standard deviation of the data
C. A histogram of the data distribution
D. Basic descriptive statistics such as count, mean, and quartiles

Answer: D

NEW QUESTION # 147
What is the best approach when comparing SQL NULL values with Python data during conditional checks?

A. Convert all NULL to string before comparison
B. Use == None directly in SQL queries
C. Use Python's None and SQL's IS NULL clause
D. Replace NULL with zero before importing

Answer: C

NEW QUESTION # 148
Which type of chart is most appropriate when comparing the distribution of a numerical variable across multiple categories?

A. Scatter plot
B. Box plot
C. Line chart
D. Pie chart

Answer: B

NEW QUESTION # 149
......

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