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

1. Which practices help maintain data integrity across large datasets in Pandas workflows?
(Choose two)

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

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

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

3. Which of the following statements best describes the structural relationship between Pandas Series and DataFrames?

A) A Series can only be created from a DataFrame
B) A DataFrame is a two-dimensional container of Series objects
C) A Series contains multiple DataFrames
D) A DataFrame is a one-dimensional array of Series

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

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

5. What is the purpose of using the groupby() function in a Pandas DataFrame when analyzing a dataset with multiple categories and numerical values?

A) To append new rows to the DataFrame
B) To sort the DataFrame by a specific column
C) To filter rows based on index values
D) To split the data into subgroups for aggregation

Solutions: