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

1. Which method allows you to detect and remove rows with duplicate values across all columns in a Pandas DataFrame?

A) DataFrame.drop_duplicates()
B) DataFrame.unique()
C) DataFrame.nunique()
D) DataFrame.remove_duplicates()

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

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

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

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

4. What is the function of the melt() operation in Pandas when reshaping wide-format data?

A) Sorts the DataFrame based on a column
B) Converts column values into rows
C) Transposes the DataFrame
D) Combines multiple DataFrames

5. Why is it important to define and apply validation rules consistently across all stages of a data pipeline?

A) It guarantees compatibility with visualization tools
B) It prevents the propagation of corrupted or invalid data
C) It automatically optimizes SQL queries
D) It reduces processing time by skipping null checks

Solutions: