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

1. What is a best practice when organizing data in a spreadsheet for analysis?

A) Use consistent column headers across all sheets
B) Merge cells to reduce redundancy
C) Apply conditional formatting to entire rows only
D) Place charts in the middle of data tables

2. Which two benefits are most closely associated with using object-oriented programming (OOP) in data analysis pipelines?
(Choose two)

A) Supports clearer abstraction by modeling real-world entities
B) Encourages code reuse through inheritance and modularity
C) Allows the use of lambda for procedural logic
D) Enables procedural programming only through decorators

3. Which actions are valid techniques for handling erroneous categorical values in a dataset?
(Choose two)

A) Replacing inconsistent labels with a standardized value
B) Removing rows with invalid labels
C) Normalizing using min-max scaling
D) Converting all values to integers

4. Which Python control structures are commonly used for data filtering and iterative operations in real-world analytics tasks?
(Choose two)

A) while loops
B) match-case statements
C) decorators
D) list comprehensions

5. Which Python constructs are useful for comparing and managing object identity in a data pipeline?
(Choose all that apply)

A) == operator for checking value equivalence
B) is operator for memory-level comparison
C) id() function to retrieve unique object identifiers
D) str() function to convert data formats

Solutions: