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

1. Which operations are recommended when organizing messy tabular data in Pandas for further transformation and statistical modeling?
(choose two)

A) Ensuring consistent data types
B) Converting the DataFrame to a Series
C) Resetting the index after filtering
D) Dropping column headers

2. 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.remove_duplicates()
C) DataFrame.nunique()
D) DataFrame.unique()

3. Which practices enhance both readability and professionalism in spreadsheet formatting?
(Choose two)

A) Aligning column headers to the left
B) Centering all data regardless of type
C) Using uniform date formats across columns
D) Applying consistent font and cell styling

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

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

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

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

Solutions: