Python PCAD-31-02 Dumps (V8.02) for Preparation: Master the Certified Associate Data Analyst with Python Exam Content in 2026

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)

2. Which SQL commands are typically used to retrieve and manipulate data in a data analysis context? (Choose all that apply)

3. Which Python feature allows the reuse of logic in different data processing steps, reducing duplication and improving maintainability?

4. What is the key difference between the .iloc[] and .loc[] accessors when working with Series or DataFrames?

5. What may occur if a model is evaluated using the same data it was trained on?

6. Which storage system is best suited for storing and retrieving large volumes of unstructured data, such as images or logs?

7. Which of the following best describes the purpose of the plt.subplot() function in Matplotlib?

8. Which of the following is the most suitable data structure in Python for representing a tabular row with column names?

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

10. What is the main purpose of defining a class when working with complex data structures in a Python-based analysis project?

11. In a scatter plot showing the relationship between advertising spend and sales revenue, the points form a tight upward-sloping pattern.

What conclusion can be drawn?

12. Which conditions typically necessitate data normalization or scaling before analysis? (Choose two)

13. When performing bootstrapping on a dataset with 500 observations, what is a typical procedure?

14. Why might using a pie chart to represent category proportions be less effective than a bar chart?

15. Which file format is most suitable for exchanging large tabular datasets with consistent column data types across systems?

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

17. Which SQL commands can be used to modify the contents of a table's data directly? (Choose all that apply)

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

19. Which SQL command should a data analyst use to modify existing records in a database table based on specific conditions?

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

21. How would you extract the last three rows of a DataFrame df using position-based indexing?

22. What is the main purpose of validating a dataset before applying statistical analysis?

23. What is a key assumption of linear regression that distinguishes it from logistic regression?

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

25. Which file formats are commonly used for hierarchical or nested data structures in data acquisition? (Choose two)

26. Which of the following correctly demonstrates the use of parameterized queries using Python’s sqlite3 module?

27. What is the primary reason for converting all categorical labels to lowercase during the data cleaning process?

28. Which techniques are commonly used to manage type conversion between SQL and Python when importing database values? (choose two)

29. Which of the following are key differences between Pandas and NumPy arrays? (choose two)

30. Which methods can be used to validate data types and structure in a Pandas DataFrame? (Choose two)

31. Which Python control structures are commonly used for data filtering and iterative operations in real-world analytics tasks? (Choose two)

32. Why is it important to use a test dataset separate from the training dataset when evaluating a machine learning model?

33. When analyzing a dataset of customer ages, you calculate the mean, median, and mode.

What does it indicate if all three values are approximately equal?

34. Which practices are typically part of the data integration process? (Choose two)

35. What is the primary difference between the == operator and the is operator in Python when used in a data pipeline?

36. Why is it important to adjust data presentations based on the audience's background?

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

38. Which Python library is most commonly used to establish a connection to a SQLite database and perform SQL operations?

39. Which Python constructs are useful for comparing and managing object identity in a data pipeline? (Choose all that apply)

40. Which type of regression is most appropriate when the response variable is categorical, such as predicting customer churn (Yes/No)?

41. Which practices are considered part of professional Python scripting standards? (Choose two)

42. 1.What is a major challenge in aggregating data from multiple sources?

43. 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?

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

45. Which method in the pandas library allows efficient loading of large datasets in chunks to conserve memory?

46. Which transformation method adjusts the mean of the dataset to 0 and the standard deviation to 1?

47. Which packages are most commonly used together in a data science workflow for data manipulation and visualization? (Choose two)

48. Which operation would most efficiently apply element-wise multiplication to two NumPy arrays of equal size?

49. Which method allows you to detect and remove rows with duplicate values across all columns in a Pandas DataFrame?

50. What is the primary purpose of using annotations in a data visualization?