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| Section | Objectives |
|---|---|
| Topic 1: Basic Statistics for Data Analysis | - Descriptive statistics
|
| Topic 2: Python Programming Fundamentals | - Basic syntax and data types
|
| Topic 3: Data Analysis and Visualization | - Data visualization
|
| Topic 4: Data Handling and Processing with Python | - Data manipulation libraries
|
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NEW QUESTION # 37
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?
Answer: D
Explanation:
Slicing includes the start index but excludes the end index. Characters at indices 1, 2, and 3 are selected, producing the substring "yth".
NEW QUESTION # 38
A Python loop uses range(5, 0, -2) to iterate backward. The programmer expects a decreasing sequence. Which values will actually be generated when this loop runs?
Answer: C
Explanation:
The range starts at 5 and decreases by 2 each step until it reaches a value greater than 0. The generated sequence is 5, 3, and 1.
NEW QUESTION # 39
You are given the following list of daily step counts:
steps = [8230, 9020, 7640, 8760, 10020, 2546, 9817]
Your task is to calculate:
- the standard deviation of the step counts,
- the average rounded up to the nearest whole number, and
- the median of the step counts.
Which code snippet correctly performs all three tasks? Select the best answer.
import statistics
Answer: D
Explanation:
It uses statistics.stdev() to compute the standard deviation, statistics.mean() to compute the average and math.ceil() to round it up to the nearest whole number, and statistics.median() to compute the median.
NEW QUESTION # 40
A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?
Answer: D
Explanation:
The in operator checks for substring presence. Since the character "a" exists in "apple", the expression evaluates to True, demonstrating how membership works for strings in Python.
NEW QUESTION # 41
You are analyzing survey results from students about their favorite colors. The list colorsstores individual responses:
You want to:
- find the number of unique colors mentioned using NumPy, and
- determine how often each color was chosen using Counter.
Which code snippet correctly performs both tasks? Select the best answer.
from numpy import unique
Answer: C
Explanation:
numpy.unique returns the distinct values in the list, and taking its length gives the number of unique colors. Counter(colors) correctly counts how many times each color appears in the responses.
NEW QUESTION # 42
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