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Data Visualization 13,040

Visualization is a part of Data Science which is a presentation of data in visual form. Data Visualization is used in most companies. is a great place to start learning to improve your data visualization skills. At, we have a section dedicated to data visualization tutorials and resources. Here you can watch live streams of data visualization and search for Data visualization topics in our video library. Join the data visualization community and improve your career prospects

Data Visualization Introduction

Data Visualization is a part of Data Science. It is the presentation of data in visual form. According to Wikipedia, Data Visualization can also be viewed as the equivalent of visual communication in a modern sense. With data visualization, anyone can make decisions based on the visual representation of data. New patterns can easily be found in Data visualization. Different tools and methodologies are used for proper data visualization.

Big companies like Facebook, Google, Apple, etc. use data visualization on a regular basis to make decisions. They gather a lot of data, and data visualization makes it easy for them to make better decisions. Data visualization also come handy in smaller projects as we all know how visualization can help digest information better, thanks to how our brain works.

History of Data Visualization

Data visualization dates back to the 17th century. The concept of understanding data from pictures was used in maps, graphs and pie charts. The pie chart was invented in the early 1800s. For the next century, data visualization didn’t get that much attention until Charles Minard mapped Napoleon’s invasion of Russia. The map was unique in many ways. First, it showed how big the army of Napoleon was, and it also showed how he retreated from Moscow. Furthermore, each action was tied to time and temperature scale for better understanding. Without data visualization, this type of insight is impossible.

There is a history of data visualization: beginning in the 2nd century C.E. with data arrangement into columns and rows and evolving to the initial quantitative representations in the 17th century. According to the Interaction Design Foundation, French philosopher and mathematician René Descartes laid the groundwork for Scotsman William Playfair. Descartes developed a two-dimensional coordinate system for displaying values, which in the late 18th century Playfair saw the potential for graphical communication of quantitative data. In the second half of the 20th century, Jacques Bertin used quantitative graphs to represent information intuitively, clearly, accurately, and efficiently.

John Tukey and Edward Tufte pushed the bounds of data visualization; Tukey with his new statistical approach of exploratory data analysis and Tufte with his book "The Visual Display of Quantitative Information" paved the way for refining data visualization techniques for more than statisticians. With the progression of technology came the progression of data visualization; starting with hand-drawn visualizations and evolving into more technical applications – including interactive designs leading to software visualization. Programs like SAS, SOFA, R, Minitab, and more allow for data visualization in the field of statistics.

Data Visualization Tools

Current technology has changed how data visualization works. Computers are now capable of processing data at a very fast rate, enabling data scientists and data wranglers to make meaning out of tons of data in no time. In recent times, data visualization is a part of both science and art. Let’s go through some of the best data visualization tools that you can use.

  • Plotly With Plotly, anyone can perform data analysis using popular programming languages such as R, Python, JavaScript, Matlab, etc. You can make presentations, charts and dashboards with the help of Plotly. It also offers a good visualization library to work with.
  • Chart.js If you are working on a small project and need a tool that can help you make awesome data visualization, Chart.js is what you need. You can make six chart types. This tool uses HTML5 and JavaScript to power itself up. It is also open source.
  • Wolfram Alpha Wolfram Alpha is a fully-fledged search engine capable of showing great visual arts. All you need to do is type in the plot or the data, and the search engine will build the visualization for you. Wolfram Alpha is also known as the computational knowledge engine and is a rival to the Google search engine.
  • Data Hero Data Hero is an easy-to-use tool that can be used by team members to create amazing data visualizations. It uses cloud services to make it happen. Most of the stuff is automated so that anyone without technical abilities can create charts or visuals.
  • D3.js D3.js is one of the popular JavaScript libraries that can be used to render amazing data visualization. It uses SVG, HTML, and CSS to render its stuff. It is open source and can be used to create advanced data visualization.

LiveEdu Data Visualization Streamers

If you are wondering where to get started to learn Data Visualization, then our recommendation would be to watch data visualization streams on LiveEdu. You can also search for Data Visualization from our video library. Let’s list the top 5 data visualization streamers on LiveEdu.


Data Visualization Best Books

There are plenty of data visualization books online. The best way to start learning data visualization is to invest in the books. So, why the wait? Let’s go through the best books for learning the Data Visualization. The books are categorized into beginner, intermediate and advanced levels. So pick the book that best suits you.

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    Cool Infographics: Effective Communication with Data Visualization and Design

    by Randy Krum

    Research shows that visual information is more quickly and easily understood, and much more likely to be remembered. This innovative book presents the design process and the best software tools for creating infographics that communicate. It includes a special section on how to construct the increasingly popular infographic resume, the book offers graphic designers, marketers, and business professionals vital information on the most effective ways to present data..

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    Data Visualization with JavaScript

    by Stephen A. Thomas

    In Data Visualization with JavaScript, you'll learn how to use JavaScript, HTML, and CSS to build the most practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and will have you building basic visualizations, like bar, line, and scatter graphs, in no time

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    Data Visualization with Python and JavaScript: Scrape, Clean, Explore & Transform Your Data

    by Kyran Dale

    Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations.

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    Data Visualization: Principles and Practice, Second Edition

    by Alexandru C. Telea

    Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more.

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    Visualize This: The FlowingData Guide to Design, Visualization, and Statisticss

    by Nathan Yau

    Practical data design tips from a data visualization expert of the modern age
    Data doesn?t decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.

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    Interactive Data Visualization for the Web: An Introduction to Designing with D3

    by Scott Murray

    Build maintainable and performant user interfaces for your web applications using React.js. Create reusable React.js components to save time and effort in maintaining your user interfaces. Learn how to build a ready-to-deploy React.js web application, following our step-by-step tutorial

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    The Visual Display of Quantitative Information

    by Edward R.Tufte

    The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays..

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    Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations

    by Scott Berinato

    In "Good Charts," dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s--on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping. This book is much more than a set of static rules for making visualizations.

  • Book cover

    Data Visualization: Principles and Practice, Second Edition

    by Alexandru C. Telea

    Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more.

Data Visualization Projects

The best way to learn is to evolve yourself with Projects. Let’s look at some of the best data visualization projects that you can follow. You can also find data visualization projects on LiveEdu. If you are interested, check LiveEdu data visualization streamers section for more information.

Vega is a visualization grammar library that lets you create, save and share interactive visualization designs. The format is very useful for visualizing data using HTML5 Canvas and SVG.

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Dimensional charting built to work natively with crossfilter rendered using d3.js. In dc.js, each chart displays an aggregation of some attributes through the position, size, and color of its elements, and also presents a dimension which can be filtered. When the filter or brush changes, all other charts are updated dynamically, using animated transitions.

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Matplotlib is a 2D plotting library developed using Python programming language. With it you can easily develop high quality interactive environments. It works great with Matlab.

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EnvisionJSis fast interactive HTML5 Charts visualization library.

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Leaflet is the leading open-source JavaScript library for mobile-friendly interactive maps. Weighing just about 37 KB of gzipped JS code, it has all the mapping features most developers ever need.

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Data Visualization Community

The community of data visualization is big. There are plenty of websites you can find a community and become part of it. Let’s list some of them below.

  • Data Visualization Community Group runs its own data visualization community group. You can become part of it and contribute to the growth of data visualization.
  • Data Community DC data visualization community A community completely dedicated to the growth of the data visualization and argues one thing, “Is Data Visualization a science or an art?” They offer regular meetups to answer the question.
  • Here you can find all the awesome streamers who love to share their knowledge about Data visualization.

Data Visualization Gurus

  • Stephen Wolfram

    Stephen Wolfram

    Stephen Wolfram (born 29 August 1959) is a British-American computer scientist, physicist, and businessman. He is known for his work in computer science, mathematics, and in theoretical physics. He is the author of the book A New Kind of Science. In 2012 he was named an inaugural fellow of the American Mathematical Society. Check out his channel.

  • David McCandless

    David McChandless is one of the well-known data-visualization specialist. He maintains his blog and has also written popular books. He also has TED talk for the data enthusiasts. All his new work is on the use of data visualization and infographics.

    David McCandless
  • Aaron Koblin

    Aaron Koblin

    Aaron Koblin is an entrepreneur and loves data visualization. He is well known for his work in data visualization. His works also reflected on his career significantly as he created the data arts team at Google and also did multiple TED talk for the people he loves and cares.

  • Evan Sinar

    Evan Sinar is the chief scientist and VP at the Development Dimensions International. He has over 36K followers on Twitter and shares regular insights on data visualization.

    Evan Sinar
  • Cole Nussbaumer

    Cole Nussbaumer

    Cole Nussbaumer is a renowned data visualization expert for her ability to tell stories using data. She is also the author of “Storytelling with data” which helps business to understand their data better.

  • Naomi Robbins

    Naomi Robbins is a seminar and consultant leader who specialize in graphics data display. If you want to learn about new things, it is must to follow Naomi Robbins on Twitter. She has also written the “Creating More Effective Graphs”.

    Naomi Robbins

Data Visualization Conferences

Since data visualization is a trending topic in the market, there are many conferences out there that you can attend. Let’s list some of the best data visualization conferences out there.

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