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

1. 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 Series are more memory efficient than NumPy arrays
D) Pandas handles labeled data; NumPy does not

2. Which practices are considered part of professional Python scripting standards?
(Choose two)

A) Including in-line comments and docstrings
B) Avoiding use of modules and libraries
C) Avoiding error handling to keep code clean
D) Using consistent indentation and naming conventions

3. What is the most efficient way to handle missing values in a Pandas DataFrame when preparing a dataset for analysis that must maintain original index structure and avoid row deletions?

A) Use fillna() with a constant value
B) Use drop() to remove null rows
C) Use dropna() with axis=1
D) Apply interpolate() method

4. Which actions are considered part of basic data validation tasks in Python using Pandas?
(Choose two)

A) Confirming numeric columns contain only integers
B) Replacing NULL values with placeholders
C) Sorting the data frame by index
D) Checking for duplicate rows

5. Which practices are essential to ensure a fair evaluation of a machine learning model's performance?
(Choose two)

A) Training on the entire dataset including test records
B) Splitting data into training and test sets
C) Using cross-validation to assess generalizability
D) Randomizing the test dataset labels

Solutions: