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

1. What is the purpose of using df.loc[2:5, 'column1'] in a Pandas DataFrame?

A) Returns rows 2 through 5 in 'column1'
B) Returns rows 2 to 4 in 'column1'
C) Returns the entire DataFrame
D) Returns a new DataFrame excluding 'column1'

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

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

3. Which refinements are typically used to enhance clarity and presentation quality in visualizations?
(Choose two)

A) Avoiding color entirely
B) Adding descriptive axis labels
C) Customizing tick labels
D) Disabling grid lines in all cases

4. Which techniques can be used to select a subset of rows and columns from a DataFrame using labels?
(Choose two)

A) df.loc[2:7, ['col1', 'col2']]
B) df.iloc[0:5, 'col2']
C) df.loc[:, 'col1']
D) df['col1', 'col2']

5. What is the primary reason to use .head() and .tail() methods in pandas when exploring datasets?

A) To preview the first and last few rows of data
B) To delete missing values
C) To create visualizations
D) To rename columns

Solutions: