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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Working with Data and Performing Simple Analyses	32.5%	- Data Cleaning and Transformation 1. Perform basic data transformation (filtering, sorting, grouping) 2. Handle missing and inconsistent data - Simple Analytical Techniques 1. Calculate descriptive statistics (mean, median, mode) 2. Identify basic patterns and trends in data - Data Analysis with Python Libraries 1. Use the math and statistics modules for basic calculations 2. Utilize the collections module for specialized containers 3. Perform basic operations with NumPy arrays 4. Work with the datetime module for date/time data
Introduction to Data and Data Analysis Concepts	22.5%	- Define and Classify Data 1. Explain how data becomes meaningful 2. Differentiate structured, semi-structured, and unstructured data 3. Classify data as quantitative or qualitative - Data Analysis Process and Workflow 1. Identify common data sources and collection methods 2. Explain the role of data cleaning and preparation 3. Describe the steps of the data analysis process - Data Ethics and Privacy 1. Recognize ethical considerations in data handling 2. Understand basic data privacy concepts
Communicating Insights and Reporting	12.5%	- Data Visualization 1. Select appropriate visuals for different data types 2. Interpret simple data visualizations 3. Recognize common visualization types (bar, line, pie charts) - Data Storytelling and Reporting 1. Create clear and concise analytical reports 2. Present insights with visual and verbal techniques 3. Structure insights as a narrative
Python Basics for Data Analysis	32.5%	- Data Structures 1. Apply common operations and methods to data structures 2. Work with lists, tuples, dictionaries, and sets - Python Fundamentals 1. Implement control flow structures (loops, conditionals) 2. Define and use functions 3. Use variables, data types, and basic operators - File Handling 1. Read from and write to files (text, CSV) 2. Use the csv module for basic CSV operations

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

Question #1

You are given two lists representing daily page views and sign-ups on a website:
views = [120, 130, 128, 700, 115, 123, 119, 680, 122]
signups = [12, 15, 13, 50, 11, 14, 10, 55, 13]
You want to:
- remove outliers (views > 600), and
- calculate correlation between the cleaned lists.
Which code accomplishes this correctly? Select the best answer.

Reveal Solution Discussion 0

Correct Answer: B 🗳️

Explanation: Only visible for ValidExam members. You can sign-up / login (it's free).

Question #2

Given the following string:
text = "Report2024Final"
Which of the following statements are entirely correct? (Choose two.)

A. text.capitalize()changes Report2024Finalto REPORT2024FINAL, and text.find("2024")returns 6
B. text.isalpha()returns True, and text.find ("2024")returns True
C. text.capitalize()changes Finalto lowercase, and text.find ("L")returns True
D. text[-6].isdigit() returns True, text.startswith("r") returns True
E. text[6:8].isdigit()returns True, and text.endswith("Final")returns True
F. text[0:6].isalpha() returns True, and text.find("2024") returns 6

Reveal Solution Discussion 0

Correct Answer: C,E,F 🗳️

Explanation: Only visible for ValidExam members. You can sign-up / login (it's free).

Question #3

A loop includes a break statement when a condition is met. The programmer wants to understand how break affects loop execution. What happens when break is executed inside the loop?

A. Loop ends immediately
B. Loop restarts
C. Skips one iteration
D. Error

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Explanation: Only visible for ValidExam members. You can sign-up / login (it's free).

Question #4

A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?

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

Reveal Solution Discussion 0

Correct Answer: D 🗳️

Explanation: Only visible for ValidExam members. You can sign-up / login (it's free).

Question #5

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