PCED-30-02 Top Questions, PCED-30-02 Study Reference

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Python Institute PCED-30-02 Exam Syllabus Topics:

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

>> PCED-30-02 Top Questions <<

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q13-Q18):

NEW QUESTION # 13
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().strip(', ')
B. fields = line.strip().split(', ')
C. fields = line.split(', ').trim()
D. fields = line.replace(', ', '|').split('|')

Answer: B

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 # 14
You are writing a function named process_data()to read and process numerical input from a file. The function must:
- read the file data.txt,
- attempt to convert the first line into an integer,
- handle file, conversion, or index-related exceptions,
- print the value only if no error occurs,
- and always print a final message after execution.
Which implementation correctly and robustly meets all these conditions? Select the best answer.

Answer: A

Explanation:
It wraps file reading and integer conversion in a try block, catches the relevant file, conversion, and indexing exceptions, prints the value only in the no-error path using an else block, and uses a finally block to always print the final message.

NEW QUESTION # 15
You are working with city names entered by users. These names may contain inconsistent capitalization and unwanted spaces.
To standardize the data, you want to:
- Remove any leading or trailing whitespace, and
- Capitalize the first letter of each word (e.g., convert "new york" to "New York").
For example:
" New york " → "New York"
"lOS ANGELES" → "Los Angeles"
You are given a variable citythat contains the raw input.
Which line of code correctly updates the value of cleaned_cityto apply the required transformation? Select the best answer.

A. cleaned_city = city.upper().replace(" ", "")
B. cleaned_city = city.strip().capitalize()
C. cleaned_city = city.strip().title()
D. cleaned_city = city.upper().strip()

Answer: C

Explanation:
Stripping removes leading and trailing whitespace, and applying title formatting capitalizes the first letter of each word while converting the remaining letters to lowercase, producing the correctly standardized city name.

NEW QUESTION # 16
You have collected sales data and want to compute the average using the NumPy library.
Which option correctly shows how to install NumPy and use it in your code to perform this task?

A. To install NumPy:
pip install numpy
Then run this code:
import numpy as np
data = numpy.arr([10, 20, 30])
print(numpy.mean(data))
B. To install NumPy:
pip install numpy as np
Then run this code:
import np
data = np.array([10, 20, 30])
print(np.mean(data))
C. To install NumPy:
from pip install numpy
Then run this code:
import numpy as np
data = np.array([10, 20, 30])
print(np.mean(data))

Answer: C

Explanation:
NumPy is installed with pip install numpy, then imported with import numpy as np. After that, you can create an array and compute the mean using np.array(...) and np.mean(...).

NEW QUESTION # 17
A health researcher uses wearable devices to record physical activity and sends a survey to randomly selected participants across age groups.
Why can this approach be effective? Select the best answer.

A. It uses unstructured interviews to validate automated tracking, improving bias detection.
B. It limits sampling to one demographic, ensuring high-quality data within a specific group.
C. It relies on observational methods, which are more accurate than surveys or sensors.
D. It combines automated data collection with representative sampling, reducing the risk of bias.

Answer: D

Explanation:
Combining automated wearable data with a randomly selected survey sample integrates objective measurements with representative participant input, which helps reduce bias and improves the reliability and generalizability of the findings.

NEW QUESTION # 18
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