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

1. What result will the following Pandas expression return: df['Age'].notnull().all()?

A) Returns the number of NULL values in 'Age'
B) Returns True if at least one value in 'Age' is not NULL
C) Returns True if all values in 'Age' are NULL
D) Returns True if all values in 'Age' are not NULL

2. Which method is best suited to transform inconsistent entries such as "N/A", "missing", and empty strings into a standard missing value representation in a Pandas DataFrame?

A) df.dropna()
B) df.rename()
C) df.sort_values()
D) df.replace()

3. Which technique is considered a primary defense against SQL injection when executing database queries from Python?

A) Using parameterized queries
B) Encrypting the database connection
C) Closing the database cursor after each query
D) Escaping quotes manually in SQL strings

4. What is the primary goal of pre-processing data before performing analysis?

A) To ensure the data is clean, consistent, and suitable for modeling
B) To obscure sensitive information
C) To compress datasets for storage efficiency
D) To minimize the number of data points

5. What is one potential risk of dynamically constructing SQL queries using string concatenation in Python scripts?

A) Exposure to SQL injection attacks
B) Slower database performance
C) Missing foreign key constraints
D) Increased memory usage

Solutions: