- Blog Categories
- Software Development Projects and Ideas
- 12 Computer Science Project Ideas
- 28 Beginner Software Projects
- Top 10 Engineering Project Ideas
- Top 10 Easy Final Year Projects
- Top 10 Mini Projects for Engineers
- 25 Best Django Project Ideas
- Top 20 MERN Stack Project Ideas
- Top 12 Real Time Projects
- Top 6 Major CSE Projects
- 12 Robotics Projects for All Levels
- Java Programming Concepts
- Abstract Class in Java and Methods
- Constructor Overloading in Java
- StringBuffer vs StringBuilder
- Java Identifiers: Syntax & Examples
- Types of Variables in Java Explained
- Composition in Java: Examples
- Append in Java: Implementation
- Loose Coupling vs Tight Coupling
- Integrity Constraints in DBMS
- Different Types of Operators Explained
- Career and Interview Preparation in IT
- Top 14 IT Courses for Jobs
- Top 20 Highest Paying Languages
- 23 Top CS Interview Q&A
- Best IT Jobs without Coding
- Software Engineer Salary in India
- 44 Agile Methodology Interview Q&A
- 10 Software Engineering Challenges
- Top 15 Tech's Daily Life Impact
- 10 Best Backends for React
- Cloud Computing Reference Models
- Web Development and Security
- Find Installed NPM Version
- Install Specific NPM Package Version
- Make API Calls in Angular
- Install Bootstrap in Angular
- Use Axios in React: Guide
- StrictMode in React: Usage
- 75 Cyber Security Research Topics
- Top 7 Languages for Ethical Hacking
- Top 20 Docker Commands
- Advantages of OOP
- Data Science Projects and Applications
- 42 Python Project Ideas for Beginners
- 13 Data Science Project Ideas
- 13 Data Structure Project Ideas
- 12 Real-World Python Applications
- Python Banking Project
- Data Science Course Eligibility
- Association Rule Mining Overview
- Cluster Analysis in Data Mining
- Classification in Data Mining
- KDD Process in Data Mining
- Data Structures and Algorithms
- Binary Tree Types Explained
- Binary Search Algorithm
- Sorting in Data Structure
- Binary Tree in Data Structure
- Binary Tree vs Binary Search Tree
- Recursion in Data Structure
- Data Structure Search Methods: Explained
- Binary Tree Interview Q&A
- Linear vs Binary Search
- Priority Queue Overview
- Python Programming and Tools
- Top 30 Python Pattern Programs
- List vs Tuple
- Python Free Online Course
- Method Overriding in Python
- Top 21 Python Developer Skills
- Reverse a Number in Python
- Switch Case Functions in Python
- Info Retrieval System Overview
- Reverse a Number in Python
- Real-World Python Applications
- Data Science Careers and Comparisons
- Data Analyst Salary in India
- Data Scientist Salary in India
- Free Excel Certification Course
- Actuary Salary in India
- Data Analyst Interview Guide
- Pandas Interview Guide
- Tableau Filters Explained
- Data Mining Techniques Overview
- Data Analytics Lifecycle Phases
- Data Science Vs Analytics Comparison
- Artificial Intelligence and Machine Learning Projects
- Exciting IoT Project Ideas
- 16 Exciting AI Project Ideas
- 45+ Interesting ML Project Ideas
- Exciting Deep Learning Projects
- 12 Intriguing Linear Regression Projects
- 13 Neural Network Projects
- 5 Exciting Image Processing Projects
- Top 8 Thrilling AWS Projects
- 12 Engaging AI Projects in Python
- NLP Projects for Beginners
- Concepts and Algorithms in AIML
- Basic CNN Architecture Explained
- 6 Types of Regression Models
- Data Preprocessing Steps
- Bagging vs Boosting in ML
- Multinomial Naive Bayes Overview
- Gini Index for Decision Trees
- Bayesian Network Example
- Bayes Theorem Guide
- Top 10 Dimensionality Reduction Techniques
- Neural Network Step-by-Step Guide
- Technical Guides and Comparisons
- Make a Chatbot in Python
- Compute Square Roots in Python
- Permutation vs Combination
- Image Segmentation Techniques
- Generative AI vs Traditional AI
- AI vs Human Intelligence
- Random Forest vs Decision Tree
- Neural Network Overview
- Perceptron Learning Algorithm
- Selection Sort Algorithm
- Career and Practical Applications in AIML
- AI Salary in India Overview
- Biological Neural Network Basics
- Top 10 AI Challenges
- Production System in AI
- Top 8 Raspberry Pi Alternatives
- Top 8 Open Source Projects
- 14 Raspberry Pi Project Ideas
- 15 MATLAB Project Ideas
- Top 10 Python NLP Libraries
- Naive Bayes Explained
- Digital Marketing Projects and Strategies
- 10 Best Digital Marketing Projects
- 17 Fun Social Media Projects
- Top 6 SEO Project Ideas
- Digital Marketing Case Studies
- Coca-Cola Marketing Strategy
- Nestle Marketing Strategy Analysis
- Zomato Marketing Strategy
- Monetize Instagram Guide
- Become a Successful Instagram Influencer
- 8 Best Lead Generation Techniques
- Digital Marketing Careers and Salaries
- Digital Marketing Salary in India
- Top 10 Highest Paying Marketing Jobs
- Highest Paying Digital Marketing Jobs
- SEO Salary in India
- Brand Manager Salary in India
- Content Writer Salary Guide
- Digital Marketing Executive Roles
- Career in Digital Marketing Guide
- Future of Digital Marketing
- MBA in Digital Marketing Overview
- Digital Marketing Techniques and Channels
- 9 Types of Digital Marketing Channels
- Top 10 Benefits of Marketing Branding
- 100 Best YouTube Channel Ideas
- YouTube Earnings in India
- 7 Reasons to Study Digital Marketing
- Top 10 Digital Marketing Objectives
- 10 Best Digital Marketing Blogs
- Top 5 Industries Using Digital Marketing
- Growth of Digital Marketing in India
- Top Career Options in Marketing
- Interview Preparation and Skills
- 73 Google Analytics Interview Q&A
- 56 Social Media Marketing Q&A
- 78 Google AdWords Interview Q&A
- Top 133 SEO Interview Q&A
- 27+ Digital Marketing Q&A
- Digital Marketing Free Course
- Top 9 Skills for PPC Analysts
- Movies with Successful Social Media Campaigns
- Marketing Communication Steps
- Top 10 Reasons to Be an Affiliate Marketer
- Career Options and Paths
- Top 25 Highest Paying Jobs India
- Top 25 Highest Paying Jobs World
- Top 10 Highest Paid Commerce Job
- Career Options After 12th Arts
- Top 7 Commerce Courses Without Maths
- Top 7 Career Options After PCB
- Best Career Options for Commerce
- Career Options After 12th CS
- Top 10 Career Options After 10th
- 8 Best Career Options After BA
- Projects and Academic Pursuits
- 17 Exciting Final Year Projects
- Top 12 Commerce Project Topics
- Top 13 BCA Project Ideas
- Career Options After 12th Science
- Top 15 CS Jobs in India
- 12 Best Career Options After M.Com
- 9 Best Career Options After B.Sc
- 7 Best Career Options After BCA
- 22 Best Career Options After MCA
- 16 Top Career Options After CE
- Courses and Certifications
- 10 Best Job-Oriented Courses
- Best Online Computer Courses
- Top 15 Trending Online Courses
- Top 19 High Salary Certificate Courses
- 21 Best Programming Courses for Jobs
- What is SGPA? Convert to CGPA
- GPA to Percentage Calculator
- Highest Salary Engineering Stream
- 15 Top Career Options After Engineering
- 6 Top Career Options After BBA
- Job Market and Interview Preparation
- Why Should You Be Hired: 5 Answers
- Top 10 Future Career Options
- Top 15 Highest Paid IT Jobs India
- 5 Common Guesstimate Interview Q&A
- Average CEO Salary: Top Paid CEOs
- Career Options in Political Science
- Top 15 Highest Paying Non-IT Jobs
- Cover Letter Examples for Jobs
- Top 5 Highest Paying Freelance Jobs
- Top 10 Highest Paying Companies India
- Career Options and Paths After MBA
- 20 Best Careers After B.Com
- Career Options After MBA Marketing
- Top 14 Careers After MBA In HR
- Top 10 Highest Paying HR Jobs India
- How to Become an Investment Banker
- Career Options After MBA - High Paying
- Scope of MBA in Operations Management
- Best MBA for Working Professionals India
- MBA After BA - Is It Right For You?
- Best Online MBA Courses India
- MBA Project Ideas and Topics
- 11 Exciting MBA HR Project Ideas
- Top 15 MBA Project Ideas
- 18 Exciting MBA Marketing Projects
- MBA Project Ideas: Consumer Behavior
- What is Brand Management?
- What is Holistic Marketing?
- What is Green Marketing?
- Intro to Organizational Behavior Model
- Tech Skills Every MBA Should Learn
- Most Demanding Short Term Courses MBA
- MBA Salary, Resume, and Skills
- MBA Salary in India
- HR Salary in India
- Investment Banker Salary India
- MBA Resume Samples
- Sample SOP for MBA
- Sample SOP for Internship
- 7 Ways MBA Helps Your Career
- Must-have Skills in Sales Career
- 8 Skills MBA Helps You Improve
- Top 20+ SAP FICO Interview Q&A
- MBA Specializations and Comparative Guides
- Why MBA After B.Tech? 5 Reasons
- How to Answer 'Why MBA After Engineering?'
- Why MBA in Finance
- MBA After BSc: 10 Reasons
- Which MBA Specialization to choose?
- Top 10 MBA Specializations
- MBA vs Masters: Which to Choose?
- Benefits of MBA After CA
- 5 Steps to Management Consultant
- 37 Must-Read HR Interview Q&A
- Fundamentals and Theories of Management
- What is Management? Objectives & Functions
- Nature and Scope of Management
- Decision Making in Management
- Management Process: Definition & Functions
- Importance of Management
- What are Motivation Theories?
- Tools of Financial Statement Analysis
- Negotiation Skills: Definition & Benefits
- Career Development in HRM
- Top 20 Must-Have HRM Policies
- Project and Supply Chain Management
- Top 20 Project Management Case Studies
- 10 Innovative Supply Chain Projects
- Latest Management Project Topics
- 10 Project Management Project Ideas
- 6 Types of Supply Chain Models
- Top 10 Advantages of SCM
- Top 10 Supply Chain Books
- What is Project Description?
- Top 10 Project Management Companies
- Best Project Management Courses Online
- Salaries and Career Paths in Management
- Project Manager Salary in India
- Average Product Manager Salary India
- Supply Chain Management Salary India
- Salary After BBA in India
- PGDM Salary in India
- Top 7 Career Options in Management
- CSPO Certification Cost
- Why Choose Product Management?
- Product Management in Pharma
- Product Design in Operations Management
- Industry-Specific Management and Case Studies
- Amazon Business Case Study
- Service Delivery Manager Job
- Product Management Examples
- Product Management in Automobiles
- Product Management in Banking
- Sample SOP for Business Management
- Video Game Design Components
- Top 5 Business Courses India
- Free Management Online Course
- SCM Interview Q&A
- Fundamentals and Types of Law
- Acceptance in Contract Law
- Offer in Contract Law
- 9 Types of Evidence
- Types of Law in India
- Introduction to Contract Law
- Negotiable Instrument Act
- Corporate Tax Basics
- Intellectual Property Law
- Workmen Compensation Explained
- Lawyer vs Advocate Difference
- Law Education and Courses
- LLM Subjects & Syllabus
- Corporate Law Subjects
- LLM Course Duration
- Top 10 Online LLM Courses
- Online LLM Degree
- Step-by-Step Guide to Studying Law
- Top 5 Law Books to Read
- Why Legal Studies?
- Pursuing a Career in Law
- How to Become Lawyer in India
- Career Options and Salaries in Law
- Career Options in Law India
- Corporate Lawyer Salary India
- How To Become a Corporate Lawyer
- Career in Law: Starting, Salary
- Career Opportunities: Corporate Law
- Business Lawyer: Role & Salary Info
- Average Lawyer Salary India
- Top Career Options for Lawyers
- Types of Lawyers in India
- Steps to Become SC Lawyer in India
- Tutorials
- C Tutorials
- Recursion in C: Fibonacci Series
- Checking String Palindromes in C
- Prime Number Program in C
- Implementing Square Root in C
- Matrix Multiplication in C
- Understanding Double Data Type
- Factorial of a Number in C
- Structure of a C Program
- Building a Calculator Program in C
- Compiling C Programs on Linux
- Java Tutorials
- Handling String Input in Java
- Determining Even and Odd Numbers
- Prime Number Checker
- Sorting a String
- User-Defined Exceptions
- Understanding the Thread Life Cycle
- Swapping Two Numbers
- Using Final Classes
- Area of a Triangle
- Skills
- Software Engineering
- JavaScript
- Data Structure
- React.js
- Core Java
- Node.js
- Blockchain
- SQL
- Full stack development
- Devops
- NFT
- BigData
- Cyber Security
- Cloud Computing
- Database Design with MySQL
- Cryptocurrency
- Python
- Digital Marketings
- Advertising
- Influencer Marketing
- Search Engine Optimization
- Performance Marketing
- Search Engine Marketing
- Email Marketing
- Content Marketing
- Social Media Marketing
- Display Advertising
- Marketing Analytics
- Web Analytics
- Affiliate Marketing
- MBA
- MBA in Finance
- MBA in HR
- MBA in Marketing
- MBA in Business Analytics
- MBA in Operations Management
- MBA in International Business
- MBA in Information Technology
- MBA in Healthcare Management
- MBA In General Management
- MBA in Agriculture
- MBA in Supply Chain Management
- MBA in Entrepreneurship
- MBA in Project Management
- Management Program
- Consumer Behaviour
- Supply Chain Management
- Financial Analytics
- Introduction to Fintech
- Introduction to HR Analytics
- Fundamentals of Communication
- Art of Effective Communication
- Introduction to Research Methodology
- Mastering Sales Technique
- Business Communication
- Fundamentals of Journalism
- Economics Masterclass
- Free Courses
Segmented Bar Group in Data Analytics : Complete Guide
Updated on 30 November, 2022
5.58K+ views
• 10 min read
Table of Contents
A segmented bar graph is a familiar concept in Data Analytics. But are you aware of its basics?
Graphs are one of the most common ways to represent the relationship between data, especially those too complicated and numerous for convenient illustration within a limited space and time. With the massive amount of information collected and processed through data analysis, it is pertinent to have a way to present that data for accurate interpretation and inference. Data visualization gives us a lucid picture of what the information means by giving it a visual form through charts and graphs. Hence, data becomes more understandable to the human mind and they can quickly identify patterns, trends, and anomalies within large datasets. If you are a beginner in data analytics and data science, upGrad’s data science certifications can definitely help you dive deeper into the world of data and analytics.
The ability to make convincing arguments through data visualization is one of the outstanding qualities of a skilled Data Science professional. While there are several graph and chart options
one can choose from to illustrate data in different scenarios, a segmented bar graph or segmented bar chart gets quite the attention among Data Analysts.
This article will walk you through the fundamentals of the segmented bar graph, why it is used, where it is used, and the upGrad Data Science courses that can help you master the skills required to be a successful Data Analyst.
But first, let us brush up on bar graphs.
Bar Graphs
Among the most frequently used graph/chart types, a bar chart or bar graph is composed of a series of bars portraying the comparison among distinct categories of data. Bar charts are one of the most common chart types and are usually easily understandable due to their familiarity.
Despite the simplicity of bar charts, they have limited use. Before illustrating data in a bar chart, it is crucial to assess the nature of the data and the number of variables added to the chart. Ideally, bar charts are an excellent choice when we want to follow the development of one or maybe two variables over time. We can indeed use them to compare several variables in the form of a clustered bar chart. However, such comparisons may lead to a cluttered representation that could lead to confusion.
Given below are two illustrations – the first one is of a simple bar chart (using one variable), and the second example shows a clustered bar chart (using two variables). Both the illustrations show the development of company revenue over a given period – a typical application of bar charts in corporate scenarios. The second example shows the comparison of revenues of two companies during a particular time frame.
Illustration 1 (Image Source)
Illustration 2 (Image Source)
Stacked Bar Graphs
Unlike a clustered bar chart which displays the bars side-by-side, stacked bar graphs divide the bars into sections. Stacked bar graphs are used to show how a larger category is fragmented into smaller categories and how each part impacts the total amount. The bars in a stacked bar chart are categorized into stacking order, representing different values. One axis shows the discrete values, and the other axis indicates the variable bars in stacking order. Different colors are used to show the distinctive parts of the entire bar.
Given below is an illustration depicting a stacked bar chart:
Stacked Bar Graph and Segmented Bar Graph
Stacked bar graphs are of two types: Simple stacked bar graphs and 100% stack bar graphs.
- In simple stacked bar graphs, each value for the segment is placed after the previous one. Hence, the total value of the bar is the summation of all the segment values. Thus, simple stacked bar graphs are great for comparing the total amount with each group/segmented bar.
- A 100% stack bar graph or segmented bar graph is a stacked bar graph where the segmented bars add up to 100%. In other words, the stacked bars show the relative percentage of multiple data series, and the total of each stacked bar is always 100%. Therefore, it is essential to ensure that each bar represents 100% while constructing a segmented bar chart. Or else, it will become a simple stacked bar chart.
Stacked bar charts show a part-to-whole relationship and can even show how parts change over time. Below is a simple illustration of a segmented bar chart showing how a product’s market share changes every year. A significant drawback of such segmented bar charts is that while it is easy to compare the first data series (right next to the vertical axis in the illustration below), subsequent ones are harder to compare because they are not aligned to a common baseline.
Get data science certification online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.
The following illustration will further clarify the anatomical difference between a simple stacked bar chart and a segmented bar chart:
Points To Remember While Constructing A Segmented Bar Chart
- Both stacked and segmented bar charts have a two-dimensional representation with two axes – one axis shows the categories, and the other shows the numerical values. The axis representing categories does not have a scale to indicate that it refers to mutually exclusive groups (for example, companies, years, etc.). But the axis with numerical values has a scale with the corresponding measurement units.
- The bars can be oriented either vertically or horizontally. Each principal category is divided into segments, where each segment represents subcategories of a second categorical variable.
- The height or length of the rectangular segments shows each subcategory’s quantity and is stacked end-to-end vertically or horizontally.
- Each bar’s final length or height represents the total amount in each principal category (100% in segmented bar charts).
- Equivalent subcategories should be represented with the same color.
- Some space must be left between bars of principal categories to indicate that they represent discrete groups.
Pros and Cons of Segmented Bar Charts
A segmented bar chart is a handy tool for data visualization. It has the inherent simplicity of a bar graph and yet finds application in many data analysis operations. However, it does have several drawbacks, which limit its use to specific scenarios of data analysis.
Following are the pros and cons of segmented bar charts:
Pros:
- It is pretty easy to understand the composition of categorical data.
- They depict part-to-whole changes over time.
- They can represent multiple categories and data series in a compact space.
Cons:
- It becomes harder to read with increasing segments in each bar.
- Comparing segments with each other becomes difficult since they are not aligned with a common baseline.
- Since the stacked bars are normalized to 100%, the absolute value dimension is lost.
Way Forward: Future-proof Your Career With upGrad
upGrad is a premier online higher education platform offering industry-relevant programs and courses. With over 40,000 paid learners spread across 85 countries, upGrad’s innovation of combining the latest technology and educational practices has helped more than 500,000 working professionals in their respective fields.
Here’s what the upGrad advantage offers learners:
- Flexible learning and industry-relevant curriculum with personalized industry mentorship, practical hands-on industry project, and live sessions with faculty and experts.
- Peer-to-peer networking, doubt resolution forums, and networking opportunities.
- Faculty from premier universities and companies
- A dedicated team of mentors
- Outcome-driven approach
- 360-degree career assistance
upGrad’s Executive PG Certification in Data Science and Master’s Degree in Data Science are two well-structured programs that will help you get a firm grasp on the skills and knowledge required to flourish in Data Science careers. Each program has its perks to offer, but both are designed to provide an engaging learning experience aligned with the latest industry standards. With ample hands-on industry-relevant projects, certificate-holders can rest assured that they will be ready to face the challenging and ever-competitive job market that requires constant professional upskilling. What’s more, the programs are a unique opportunity to connect with Data Science professionals across all industry sectors.
PG Certification in Data Science Program Highlights:
- Seven months course duration with a fully online format.
- Specially designed for working professionals.
- Postgraduate certification from IIIT Bangalore.
- Covers programming languages and tools such as Excel, Python, Tableau, and MySQL.
- 300+ hours of content with 7+ case studies and projects, 20+ live sessions, and six coding assignments.
Master Degree in Data Science from International University of Applied Sciences, Germany
Program Highlights:
- 24 months course duration (first year online and second year on-campus in Germany).
- Dual accreditation (Executive PG Program from IIIT-B and Master’s Degree from IU, Germany) and NASSCOM certificate.
- No IELTS is required for upGrad learners.
- Comprehensive coverage of 14+ tools and software.
- 500+ hours of content with 60+ case studies and projects, over 20 live sessions, and 25 1:8 coaching sessions with industry experts.
In Conclusion
Knowing how to construct a segmented bar chart is a must for Data Analytics, especially if you are a beginner and just starting with data visualization techniques. Such graphs can be easily constructed in Excel and do not require any advanced knowledge of complicated tools and software. First, however, it is crucial to have a clear idea of the data you are working with and whether it fits into a segmented bar chart representation.
With the potential global market of Big Data and Business Analytics showing promising trends for the future, it is safe to consider that a career in Data Sciences is full of possibilities. So, sign up with upGrad and start learning with the best!
Frequently Asked Questions (FAQs)
1. What is the difference between a graph and a chart?
Charts are a form of visual representation of data that can take the form of a diagram, picture, or graph. In a chart, the categories may or may not be related to each other. On the other hand, a graph is a numerical representation of data that shows how the change in one number or variable affects another. In other words, a graph is a type of chart that focuses on raw data and depicts the trend in such data over time.
2. What is a histogram vs bar graph?
A bar chart uses vertical or horizontal bars to represent categorical data, where the length of each bar is proportional to the data value they represent. A histogram, on the other hand, is a graphical representation of data where the data is organized into continuous number ranges. In a histogram, each vertical bar corresponds to a range.
3. How do I create a segmented bar chart in MS Excel?
Following are the steps to create a segmented bar chart in MS Excel:
Step 1: Enter your data in Excel in clearly labeled columns.
Step 2: Highlight the data.
Step 3: Click the Insert tab. Then, click Insert Column or Bar Chart under the Charts section.
Step 4: Click the option 100% Stacked Column.
Excel will automatically produce the segmented bar chart.