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Python Institute PCED-30-02 dumps - in .pdf

PCED-30-02 pdf
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Updated: Aug 04, 2026
  • Q & A: 52 Questions and Answers
  • Convenient, easy to study.
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  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
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  • Q & A: 52 Questions and Answers
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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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

1. A student writes a program using input() to collect user data, then tries to add 5 to the input value without conversion. The program crashes. What is the most likely cause of this behavior?

A) input returns int
B) Syntax error
C) input returns float
D) input returns string


2. You are creating a presentation slide to communicate findings about student stress levels across four categories over a six-month period. You include the following line graph in your presentation:

Your goal is to help your audience clearly understand trends in stress levels over time.
What is the highest problem with this visual presentation? Select the best answer.

A) The chart should be in 3D format to show depth and highlight differences more clearly.
B) The graph doesn't explain what each stress level means or show exact values for each month, which limits interpretation.
C) The lines are too light and similar in color, making it difficult to distinguish between trends.
D) The font used in the chart is hard to read; using larger, uppercase text would improve clarity.
E) The months should be replaced with week numbers to provide more detailed insight.


3. 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

A) from collections import Counter
unique_colors = len(set(colors))
color_counts = np.unique(colors)
B) from collections import Counter
unique_colors = np.unique(colors)
color_counts = Counter(set(colors))
import numpy as np
C) from collections import Counter
unique_colors = Counter(colors)
color_counts = sum(np.unique(colors))
import numpy as np
D) from collections import Counter
unique_colors = len(unique(colors))
color_counts = Counter(colors)
import numpy as np


4. 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.

A)

B)

C)


5. 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?

A) 5, 3, 1
B) 5, 4, 3, 2, 1
C) 4, 2, 0
D) 5, 3


Solutions:

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

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