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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q25-Q30):

NEW QUESTION # 25
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 # 26
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. Error
B. False
C. True
D. None

Answer: C

Explanation:
The in operator checks for substring presence. Since the character "a" exists in "apple", the expression evaluates to True, demonstrating how membership works for strings in Python.

NEW QUESTION # 27
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

A. Commuting is the second most time-consuming activity.
B. Leisure and meals combined equal the time spent at school.
C. Sleep and school take up the majority of time in a day.
D. School and homework together take up half of the day's time.
E. More time is spent commuting than on leisure.
F. Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.

Answer: C,F

Explanation:
The largest portions of the chart are sleep and school, and together they clearly make up more than half of the day. Leisure appears as a mid-sized segment that is larger than commuting but smaller than school, fitting the description of a moderate portion.

NEW QUESTION # 28
Which of the following statements about Python functions are correct? (Choose two.)

A. Functions can only return numeric values or strings.
B. A function cannot call itself or be passed as an argument to itself.
C. If a function does not contain a returnstatement, it returns Noneby default.
D. Default parameters must always come before required ones in the parameter list.
E. passexecutes the function body and returns its result.
F. Positional arguments must be passed in the order defined, while keyword arguments can be passed in any order using their parameter names.

Answer: C,F

Explanation:
Positional arguments are matched to parameters by their position, so they must follow the defined order, while keyword arguments are matched by name and can be provided in any order. If a function completes without an explicit return statement, Python returns None automatically.

NEW QUESTION # 29
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

A. Commuting is the second most time-consuming activity.
B. Leisure and meals combined equal the time spent at school.
C. Sleep and school take up the majority of time in a day.
D. School and homework together take up half of the day's time.
E. More time is spent commuting than on leisure.
F. Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.

Answer: C,F

NEW QUESTION # 30
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