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

1. Which methods can be used to validate data types and structure in a Pandas DataFrame?
(Choose two)

A) df.dtypes
B) df.to_csv()
C) df.info()
D) df.memory_usage()

2. Which of the following are key differences between Pandas and NumPy arrays?
(Choose two)

A) NumPy supports string indexing; Pandas does not
B) Pandas Series are more memory efficient than NumPy arrays
C) Pandas handles labeled data; NumPy does not
D) Pandas integrates better with tabular data and missing values

3. Why is it important to manage object identity correctly in complex data analysis pipelines?

A) It ensures type casting is consistently applied
B) It avoids redundant copies and preserves shared state when required
C) It guarantees consistent hashing of string values
D) It prevents reloading modules unnecessarily

4. Which of the following improves the readability of a spreadsheet used for collaborative data analysis?

A) Converting numeric values into images
B) Adding freeze panes to lock header rows
C) Removing gridlines from all sheets
D) Using colored fonts to highlight every cell

5. Which of the following libraries is specifically optimized for high-performance numerical computation with multi-dimensional arrays in Python?

A) NumPy
B) matplotlib
C) pandas
D) seaborn

Solutions: