You can’t analyze data if you ain’t cute: Data Visualization

Meme from Reno 911 with the original text stating "You can't fight crime if you ain't cute" but the "fight crime" is crossed out and above is written "analyze Data"

Humans are highly visual creatures, even more so in our hyper-graphic world of ultra-filtered images and short aesthetic videos. Great ideas are ignored into oblivion in favor of shiny graphics and slick illustrations, so even data analysts need to be aware of how they present their findings. A well-designed infographic will be much more impactful, widely shared, and remembered than columns and rows of numbers. Even a simple graph can help people better come to conclusions and absorb information than they ever would with just numbers alone. People who can not only crunch numbers but also create stunning communications about those numbers are a real asset on the job market, so it behooves any hopeful data analyst to at least learn the basics of visualization.

LinkedIn Learning 

  1. Learning Data Visualization 
    1. This course clocks in at just under two hours and aims to give learners the scaffolding for a strong understanding of data visualization. Geared towards true beginners, this course challenges learners to think about their data, audience, and goals to create visuals that maximize impact. Learners will also learn about visual perception and chart selection strategies, which in turn can set users up for a deep understanding of visualization. 
  1. Data Visualization: Best Practices 
    1. A poorly designed visualization can be criminally misleading, causing viewers to come to biased and inaccurate conclusions that can negatively affect everything from their investment choices to their health practices. This 98-minute course will give learners the tools to avoid common visualization missteps and the tricks to make their visualizations better fit their data, audience, and goals. This course uses Adobe Illustrator, so those who are unfamiliar with the program should first check out this quick start introduction to the program on LinkedIn Learning. Remember, UIUC students have free access many Adobe products, including Adobe Illustrator!  
  2. Excel Data Visualization: Mastering 20+ Charts and Graphs 
    1. Once again, we will focus on this data skillset within the context of a familiar software, Excel. While it is not the first software that comes to mind when thinking about visualization, Excel has surprisingly powerful visualization functions that will certainly come in handy when analyzing data. This course covers the humble pie chart to the complex geospatial heat maps and 3D power maps. In just two hours, learners will be able to quickly take their data from tables to graphics.  

O’Reilly Books and Videos

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  1. Fundamentals of Data Visualization 
    1. This handy book goes deep into the technical aspects of data visualizations. Learners will learn basic concepts like color theory along side more complex practices like redundant coding. This eBook also provides a helpful directory of visualizations so users can quickly find visualizations that fit their needs.
  2. The Data Visualization Lifecycle 
    1. This 4-hour course covers the basics of data visualization but looks at the actual process of professional data visualization that the other resources on this list do not address. Learners will gain technical skills in building visualization and a broader understanding of data visualization as a collaborative process based on external and internal stakeholders and audiences. This course teaches users how to interact with different data cultures, collaborate with colleagues, and how to treat visualization as a product.
  3. Interactive Data Visualization for the Web 
    1. Interactive data visualization is a trending skill in almost all fields that rely on data analysis and visualization of any kind. Allowing others to interact with your data and its visualization can make the data more accessible and memorable than ever before. This book gives users the skills to make interactive visuals with the fundamental concepts and methods of D3, the most powerful JavaScript library for expressing data visually in a web browser. Even those who are new to web programming will learn the basics of HTML, CSS, JavaScript, and SVG alongside the data visualization skills.

In the Catalog 

  1. #MakeoverMonday : improving how we visualize and analyze data, one chart at a time by Andrew Michael Kriebel and Eva Katharina Murray 
    1. Hashtags can be the start of beautiful movements, as those in the data analysis field learned as their #MakeoverMonday tag sparked a complete reimagining of how professionals approach data visualization. Readers will learn concepts of data visualization while viewing the real-life results of these concepts as shown by the hashtag-inspired graphics. #MakeoverMonday shows readers the “many ways to walk the line between simple reporting and design artistry to create exactly the visualization the situation requires”.  
  2. The functional art : an introduction to information graphics and visualization by Alberto Cairo 
    1. If there are data visualization celebrities, then Alberto Cairo is an A-lister. Known for his visualization journalism, he is a self-described information designer who has become famous for his gripping visualizations that stand as both formal art and excellent communication of data. This book allows users to learn the ins and outs of design all while strolling through a gallery of amazing visualization examples. This resource leans heavily on the theory of art and design, which makes it stand out from the other resources on this list. Alberto Cairo’s other works, The Truthful Art: data, charts, and maps for communication and How Charts Lie : getting smarter about visual information  are also worthwhile and insightful reads!  
  3. Data visualisation : a handbook for data driven design by Andy Kirk 
    1. Pivoting back to the more practical side of things, this handbook offers clear and useful processes for data driven designing. Readers will learn more about the visualization workflow, formulating briefs, working with data in the context of visualization, representing data accurately, integrating interactivity, and visualization literacy. 

And that’s it, folks!

With these visualization resources, the Winter Break Data Analysis series is ending on a pretty note. Hopefully, you have been able to keep your mind sharp and develop a new skill over the last month, but even if the timing was off, these resources and many more are available to students all year long! Did you enjoy one of these resources or posts? Do you have questions about any of these topics or suggestions for future series? Please tell us about it at sc@library.illinois.edu or on twitter at @ScholCommons. Thank you for joining this series and happy analyzing!  

Exploring Data Visualization #18

In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

Painting the World with Water

Creating weather predictions is a complex tasks that requires global collaboration and advanced scientific technologies. Most people know very little about how a weather prediction is put together and what is required to make it possible. NASA gives us a little glimpse into the complexities of finding out just how we know if it’s going to rain or snow anywhere in the world.

Continue reading

Exploring Data Visualization #17

In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

The unspoken rules of visualization

Title header of essay "The unspoken rules of data visualization" by Kaiser Fung. White text on a black background with green and red patches Continue reading

Exploring Data Visualization #16

Daylight Saving Time Gripe Assistant Tool

Clocks fell back this weekend, which means the internet returns once again to the debate of whether or not we still need Daylight Saving Time. Andy Woodruff, a cartographer for Axis Maps, created a handy tool for determining how much you can complain about the time change. You input your ideal sunset and sunrise times, select whether the sunset or sunrise time you chose is more important, and the tool generates a map that shows whether DST should be gotten rid of, used year-round, or if no changes need to be made based on where you live. The difference a half hour makes is surprising for some of the maps, making this a fun data viz to play around with and examine your own gripes with DST.

A map of the United States with different regions shaded in different colors to represent if they should keep (gray) or get rid of (gold) changing the clocks for Daylight Saving Time. Blue represents areas that should always use Daylight Saving Time.

This shows an ideal sunrise of 7:00 am and an ideal sunset of 6:00 pm.

Laughing Online

Conveying tone through text can be stressful—finding the right balance of friendly and assertive in a text is a delicate operation that involves word choice and punctuation equally. Often, we make our text more friendly through exclamations points! Or by adding a quick laugh, haha. The Pudding took note of how varied our use of text-based laughs can be and put together a visual essay on how often we use different laughs and whether all of them actually mean we are “laughing out loud.” The most common laugh on Reddit is “lol,” while “hehe,” “jaja,” and “i’m laughing” are much less popular expressions of mirth.

A proportional area chart showing which text laughs are most used on Reddit.

“ha” is the expression most likely to be used to indicate fake laughter or hostility

how to do it in Excel: a shaded range

Here’s a quick tip for making more complex graphs using Excel! Storytelling with Data’s Elizabeth Ricks put together a great how-to article on making Excel show a shaded range on a graph. This method involves some “brute force” to make Excel’s functions work in your favor, but results in a clean chart that shows a shaded range rather than a cluster of multiple lines.

A shaded area chart in Excel

Pixelation to represent endangered species counts

On Imgur, user JJSmooth44 created a photo series to demonstrate the current status of endangered species using pixilation. The number of squares represent the approximate number of that species that remains in the world. The more pixelated the image, the fewer there are left.

A pixelated image of an African Wild Dog. The pixelation represents approximately how many of this endangered species remain in the wild (estimated between 3000 and 5500). The Wild Dog is still distinguishable, but is not clearly visible due to the pixelation.

The African Wild Dog is one of the images in which the animal is still mostly recognizable.