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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Visualization and Communication	20%	- Creating basic visualizations 1. Using text and simple plotting tools 2. Line charts, bar charts, histograms, pie charts - Principles of effective data visualization 1. Choosing appropriate chart types 2. Clarity, simplicity, and accuracy - Interpreting and presenting results 1. Reporting findings clearly and concisely 2. Deriving conclusions and insights
Topic 2: Working with Data and Performing Simple Analysis	25%	- Data cleaning and preparation 1. Filtering, sorting, transforming data 2. Handling missing values, duplicates, and errors 3. Formatting and standardizing values - Exploratory data analysis 1. Identifying patterns, trends, and outliers 2. Calculating mean, median, mode, range, variance, standard deviation - Data acquisition and loading 1. Reading text, CSV, and structured files 2. Importing data from external sources - Data aggregation and grouping 1. Summarizing and grouping datasets
Topic 3: Introduction to Data and Data Analysis Concepts	22.5%	- Basic statistical concepts 1. Population, sample, variable, observation 2. Descriptive vs inferential statistics - 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 - Definition and classification of data 1. Process of turning raw data into insights 2. Role of data in decision-making and business 3. Difference between data, information, and knowledge
Topic 4: Python Basics for Data Analysis	32.5%	- Introduction to NumPy 1. Arrays, basic operations, indexing, slicing - Built-in modules for data work 1. math, statistics, datetime, collections, csv - Control flow and functions 1. Conditional statements, loops, iteration 2. Basic exception handling 3. Defining and calling functions, parameters, return values - Core Python syntax and data types 1. Lists, tuples, sets, dictionaries 2. Variables, numbers, strings, booleans

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

1. A loop is designed using range(1, 6, 2) to iterate through numbers. The developer wants to know exactly which values will be generated during execution. Which sequence correctly represents the values produced?

A) 1, 3
B) 1, 2, 3, 4, 5
C) 1, 3, 5
D) 2, 4, 6

2. A data analyst exports a cleaned dataset from Python and wants to share it with a colleague for easy use in Excel.
Which file format is best suited for this purpose? Select the best answer.

A) SQL, because it directly converts tabular data into database tables that Excel can open.
B) CSV, because it stores tabular data in plain text and is compatible with spreadsheet applications.
C) XML, because it automatically preserves spreadsheet formatting and charts.
D) JSON, because it stores hierarchical data and is designed for visual presentation in Excel.

3. 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()

4. An online retailer collects customer reviews, order transaction logs, and product ratings.
Which of the following correctly classifies these types of data? Select the best answer.

A) Product ratings are quantitative and structured; customer reviews are qualitative and unstructured; transaction logs are structured and quantitative
B) Product ratings are qualitative and unstructured; customer reviews are quantitative and structured; transaction logs are semi-structured and qualitative.
C) Product ratings are qualitative and structured; customer reviews are qualitative and unstructured; transaction logs are quantitative and semi-structured.
D) Product ratings are quantitative and unstructured; customer reviews are structured and qualitative; transaction logs are quantitative and unstructured.

5. 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) Syntax error
B) input returns string
C) input returns int
D) input returns float

Solutions:

Question # 1
Answer: C

Question # 2
Answer: B

Question # 3
Answer: B

Question # 4
Answer: A

Question # 5
Answer: B