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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Working with Data and Performing Simple Analysis	25%	- 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 - 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 Visualization and Communication	20%	- Interpreting and presenting results 1. Deriving conclusions and insights 2. Reporting findings clearly and concisely - Principles of effective data visualization 1. Choosing appropriate chart types 2. Clarity, simplicity, and accuracy - Creating basic visualizations 1. Using text and simple plotting tools 2. Line charts, bar charts, histograms, pie charts
Python Basics for Data Analysis	32.5%	- Introduction to NumPy 1. Arrays, basic operations, indexing, slicing - Core Python syntax and data types 1. Variables, numbers, strings, booleans 2. Lists, tuples, sets, dictionaries - Control flow and functions 1. Basic exception handling 2. Conditional statements, loops, iteration 3. Defining and calling functions, parameters, return values - Built-in modules for data work 1. math, statistics, datetime, collections, csv
Introduction to Data and Data Analysis Concepts	22.5%	- Basic statistical concepts 1. Descriptive vs inferential statistics 2. Population, sample, variable, observation - 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 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. Qualitative vs quantitative data 2. Nominal, ordinal, interval, ratio scales

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q19-Q24):

NEW QUESTION # 19
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. True
B. False
C. Error
D. None

Answer: A

Explanation:
Python caches small integers for efficiency. Since 256 is typically within the cached range, both variables reference the same object in memory, making a is b evaluate to True.

NEW QUESTION # 20
You are working with city names entered by users. These names may contain inconsistent capitalization and unwanted spaces.
To standardize the data, you want to:
- Remove any leading or trailing whitespace, and
- Capitalize the first letter of each word (e.g., convert "new york" to "New York").
For example:
" New york " → "New York"
"lOS ANGELES" → "Los Angeles"
You are given a variable citythat contains the raw input.
Which line of code correctly updates the value of cleaned_cityto apply the required transformation? Select the best answer.

A. cleaned_city = city.upper().replace(" ", "")
B. cleaned_city = city.strip().title()
C. cleaned_city = city.upper().strip()
D. cleaned_city = city.strip().capitalize()

Answer: B

Explanation:
Stripping removes leading and trailing whitespace, and applying title formatting capitalizes the first letter of each word while converting the remaining letters to lowercase, producing the correctly standardized city name.

NEW QUESTION # 21
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

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

NEW QUESTION # 22
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

A. More time is spent commuting than on leisure.
B. Commuting is the second most time-consuming activity.
C. Leisure and meals combined equal the time spent at school.
D. School and homework together take up half of the day's time.
E. Sleep and school take up the majority of time in a day.
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: E,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 # 23
Consider the following Python code:

What will be printed when the code above is executed?
40

A. [10, 20, 30, 40]
1
[1, 2, 4, 5, 6]
50
B. [20, 30, 40]
1
[1, 2, 4, 5, 6]
50
C. [20, 30, 40]
1
[1, 2, 4, 5, 6]
D. [10, 20, 30, 40]
0
[1, 2, 3, 4, 5, 6]
50

Answer: C

Explanation:
The last element of the original list is 50. The slice from index 1 up to (but not including) index 4 is
[20, 30, 40]. After removing 30 and appending 60, the list contains one occurrence of 10, and integer division by 10 produces [1, 2, 4, 5, 6].

NEW QUESTION # 24
......

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