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Python Institute PCED - Certified Entry-Level Data Analyst with Python : PCED-30-02 Exam

PCED-30-02 actual test
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Updated: Aug 29, 2026
  • Q & A: 52 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $59.99  

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
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. Variables, numbers, strings, booleans
  • 2. Lists, tuples, sets, dictionaries
- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
- Control flow and functions
  • 1. Defining and calling functions, parameters, return values
  • 2. Conditional statements, loops, iteration
  • 3. Basic exception handling
Data Visualization and Communication20%- Principles of effective data visualization
  • 1. Choosing appropriate chart types
  • 2. Clarity, simplicity, and accuracy
- 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
Working with Data and Performing Simple Analysis25%- Data cleaning and preparation
  • 1. Handling missing values, duplicates, and errors
  • 2. Filtering, sorting, transforming data
  • 3. Formatting and standardizing values
- Exploratory data analysis
  • 1. Calculating mean, median, mode, range, variance, standard deviation
  • 2. Identifying patterns, trends, and outliers
- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
- Data acquisition and loading
  • 1. Importing data from external sources
  • 2. Reading text, CSV, and structured files
Introduction to Data and Data Analysis Concepts22.5%- 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
- Data lifecycle and ethical considerations
  • 1. Privacy, security, bias, and fairness in data
  • 2. Data collection, storage, processing, usage, and sharing
- Data types and measurement scales
  • 1. Nominal, ordinal, interval, ratio scales
  • 2. Qualitative vs quantitative data
- Basic statistical concepts
  • 1. Population, sample, variable, observation
  • 2. Descriptive vs inferential statistics

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

Question 1

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 2

You are writing a function to validate battery voltage readings. The rules are:
- If the reading is "MISSING"or None, return "Missing".
- If the value is below 2.5or above 4.2, return "Outlier".
Otherwise, return "Normal".
Which version correctly implements this logic using the most robust conditional and nested structures? Select the best answer.

A.

B.

C.

D.


Question 3

Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.

A. Developing machine learning algorithms to predict user behavior.
B. Creating summary tables and charts to describe patterns in historical data.
C. Designing a data pipeline to ingest and process real-time sensor data.
D. Recommending pricing strategies using predictive modeling and A/B testing.


Question 4

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

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


Question 5

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


Solutions:

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

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