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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Handling and Processing with Python	- Data manipulation libraries 1. Pandas fundamentals 2. NumPy basics - Working with data structures 1. Iterating and transformations 2. Lists, tuples, dictionaries
Topic 2: Basic Statistics for Data Analysis	- Descriptive statistics 1. Mean, median, mode 2. Variance and standard deviation
Topic 3: Data Analysis and Visualization	- Data cleaning and preprocessing 1. Data transformation techniques 2. Missing values handling - Data visualization 1. Matplotlib basics 2. Plot interpretation
Topic 4: Python Programming Fundamentals	- Basic syntax and data types 1. Control flow basics 2. Variables and operators

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q18-Q23):

NEW QUESTION # 18
A programmer writes a script to test operator precedence using the expression 3 + 4 * 2 ** 2. The goal is to evaluate the result correctly based on Python's operator hierarchy rules. What result should the script produce?

A. 0
B. 1
C. 2
D. 3

Answer: D

Explanation:
Exponentiation is evaluated first, so 2 ** 2 equals 4. Then multiplication 4 * 4 equals 16. Finally, addition is performed: 3 + 16 results in 19.

NEW QUESTION # 19
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?

Answer: D

Explanation:
Adding an integer and a float produces a float result, so checking that the type of the sum is float evaluates to True. The variable holding 3.0 is a float, so the isinstance check for float also evaluates to True.

NEW QUESTION # 20
You are reading a data.csvfile line by line. To prepare each line for formatting with f-strings, you need to remove extra whitespace and split the values by commas.
Which line should you insert to correctly clean and parse the input?

A. fields = line.split(', ').trim()
B. fields = line.split().strip(', ')
C. fields = line.replace(', ', '|').split('|')
D. fields = line.strip().split(', ')

Answer: D

Explanation:
Stripping removes leading and trailing whitespace from the line, and then splitting on the comma- space delimiter correctly separates the values into a list for further formatting.

NEW QUESTION # 21
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

A. import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics
B. import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
C. import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics
D. import math
print(statistics.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))

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 # 22
How do the analysis and visualization stages of the data lifecycle typically work together?

A. Analysis produces charts and graphs, while visualization interprets the data to detect outliers.
B. Analysis identifies patterns and insights in processed data, which are then communicated through visualizations for informed decision-making.
C. Analysis summarizes archived data, and visualization transforms it into structured tables for storage.
D. Analysis retrieves raw inputs from dashboards, while visualization uses that input to clean the data.

Answer: B

Explanation:
Analysis involves examining processed data to uncover patterns, trends, and insights, and visualization presents those findings in graphical form so stakeholders can clearly understand and act on the results.

NEW QUESTION # 23
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