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

1. What is the outcome of the following code?
data = [5, 10, 15]
result = [x**2 for x in data if x > 5]
print(result)

A) [25, 100, 225]
B) [10, 15]
C) [100, 225]
D) [25, 100]

2. What is the most efficient way to handle missing values in a Pandas DataFrame when preparing a dataset for analysis that must maintain original index structure and avoid row deletions?

A) Use fillna() with a constant value
B) Apply interpolate() method
C) Use drop() to remove null rows
D) Use dropna() with axis=1

3. Which actions are considered part of basic data validation tasks in Python using Pandas?
(Choose two)

A) Confirming numeric columns contain only integers
B) Checking for duplicate rows
C) Replacing NULL values with placeholders
D) Sorting the data frame by index

4. Which of the following are limitations of manual data collection methods?
(Choose two)

A) Seamless integration with big data tools
B) Time-consuming process
C) High scalability
D) Increased chance of human error

5. When analyzing a dataset, which of the following functions would best help detect skewness or asymmetry in the data distribution?

A) mean()
B) skew()
C) sum()
D) std()

Solutions: