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Python Institute PCED PCED-30-02 Braindumps

PCED-30-02

Exam Code: PCED-30-02

Exam Name: PCED - Certified Entry-Level Data Analyst with Python

Updated: Sep 09, 2026

Q & A: 52 Questions and Answers

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Python Basics for Data Analysis32.5%- Control flow and functions
  • 1. Conditional statements, loops, iteration
  • 2. Defining and calling functions, parameters, return values
  • 3. Basic exception handling
- Built-in modules for data work
  • 1. math, statistics, datetime, collections, csv
- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
- Core Python syntax and data types
  • 1. Lists, tuples, sets, dictionaries
  • 2. Variables, numbers, strings, booleans
Working with Data and Performing Simple Analysis25%- Exploratory data analysis
  • 1. Identifying patterns, trends, and outliers
  • 2. Calculating mean, median, mode, range, variance, standard deviation
- Data cleaning and preparation
  • 1. Filtering, sorting, transforming data
  • 2. Formatting and standardizing values
  • 3. Handling missing values, duplicates, and errors
- Data acquisition and loading
  • 1. Reading text, CSV, and structured files
  • 2. Importing data from external sources
- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
Introduction to Data and Data Analysis Concepts22.5%- Data lifecycle and ethical considerations
  • 1. Data collection, storage, processing, usage, and sharing
  • 2. Privacy, security, bias, and fairness in data
- Definition and classification of data
  • 1. Role of data in decision-making and business
  • 2. Process of turning raw data into insights
  • 3. Difference between data, information, and knowledge
- Basic statistical concepts
  • 1. Descriptive vs inferential statistics
  • 2. Population, sample, variable, observation
- Data types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
Data Visualization and Communication20%- Principles of effective data visualization
  • 1. Clarity, simplicity, and accuracy
  • 2. Choosing appropriate chart types
- Interpreting and presenting results
  • 1. Deriving conclusions and insights
  • 2. Reporting findings clearly and concisely
- Creating basic visualizations
  • 1. Line charts, bar charts, histograms, pie charts
  • 2. Using text and simple plotting tools

Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:

Question #1

An online retailer collects customer reviews, order transaction logs, and product ratings.
Which of the following correctly classifies these types of data? Select the best answer.

A. Product ratings are qualitative and unstructured; customer reviews are quantitative and structured; transaction logs are semi-structured and qualitative.
B. Product ratings are qualitative and structured; customer reviews are qualitative and unstructured; transaction logs are quantitative and semi-structured.
C. Product ratings are quantitative and structured; customer reviews are qualitative and unstructured; transaction logs are structured and quantitative
D. Product ratings are quantitative and unstructured; customer reviews are structured and qualitative; transaction logs are quantitative and unstructured.


Question #2

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

A.

B.

C.

D.


Question #3

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


Question #4

A program compares two values using == and is. The variables a = 256 and b = 256 are defined.
What is the expected result of a is b in most Python implementations?

A. None
B. Error
C. True
D. False


Question #5

A program uses while False: followed by print statements inside the loop. The developer expects output. What will actually happen during execution?

A. Error
B. Infinite loop
C. Prints once
D. No execution


Solutions:

Question #1
Answer: C
Question #2
Answer: B
Question #3
Answer: A
Question #4
Answer: C
Question #5
Answer: D

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