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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q69-Q74):

NEW QUESTION # 69
Which practices help maintain data integrity across large datasets in Pandas workflows?
(Choose two)

A. Sorting columns alphabetically
B. Automatically converting all text to uppercase
C. Defining and enforcing schema constraints
D. Using assertions to enforce domain-specific rules

Answer: C,D

NEW QUESTION # 70
Which SQL command should a data analyst use to modify existing records in a database table based on specific conditions?

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

Answer: B

NEW QUESTION # 71
Which chart types are commonly used to represent relationships between two numerical variables in Python-based visualizations?
(choose two)
Response:

A. Histogram
B. Heatmap
C. Line chart
D. Scatter plot

Answer: B,D

NEW QUESTION # 72
What is the main purpose of validating a dataset before applying statistical analysis?

A. To ensure the dataset meets expected quality and structure
B. To generate more columns from the dataset
C. To visualize patterns more clearly
D. To sort the data alphabetically

Answer: A

NEW QUESTION # 73
Which method is best suited to transform inconsistent entries such as "N/A", "missing", and empty strings into a standard missing value representation in a Pandas DataFrame?

A. df.replace()
B. df.dropna()
C. df.rename()
D. df.sort_values()

Answer: A

NEW QUESTION # 74
......

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