Part III: Short Answer (15 Points) Instructions: Answer each question clearly and concisely. Support your answers with appropriate reasoning whenever necessary.

Which Pandas object is specifically designed to represent two-dimensional tabular data?

Throughout this course, Python has primarily been used as

Explain why Pandas DataFrames are generally preferred over standard Python lists for analyzing structured datasets. Your answer should include at least two advantages.

Which machine learning algorithm attempts to identify the optimal boundary separating different classes?

What does an algorithm with time complexity O(log n) generally indicate?

Which Pandas method returns summary statistics for numerical columns?

Part VI: Integrated Scientific Computing Case Study (10 Points) Instructions: Read the following scenario carefully and answer all questions. Support your answers using concepts learned throughout the course.

A data analyst is preparing a dataset for analysis. (4 Points) import pandas as pdemployees = pd.read_csv(“employees.csv”)print(employees.describe()) Answer the following questions. What information does this code produce? Why is this step useful before building a machine learning model? Besides descriptive statistics, identify two additional aspects of the dataset that should be examined during exploratory data analysis. Name one Pandas function that could be used to identify missing values in the dataset.

Part II: Code Interpretation and Analysis (20 Points) Instructions: Read each code segment carefully. Answer all questions. Show your reasoning where appropriate.