Week 20

DATA VISUALIZATION

Introduction to Data Visualization

Words don’t always paint the clearest picture. Raw data doesn’t always tell the most compelling story.

The human mind is very receptive to visual information. That’s why data visualization is a powerful tool for communication.

Data visualization is used everywhere.

Businesses use data visualization for reporting, forecasting, and marketing.

Nonprofits use data visualizations to put stories and faces to numbers.

Scholars and scientists use data visualization to illustrate concepts and reinforce their arguments.

Reporters use data visualization to show trends and contextualize stories.While data visualizations can make your work more professional, they can also be a lot of fun.

What is data visualization? A simple definition of data visualization:

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map.

The field of data visualization combines both art and data science. While a data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data.

What is data visualization used for?

Data, especially a lot of data, can be difficult to wrap your head around. Data visualization can help both you and your audience interpret and understand data.

Data visualizations often use elements of visual storytelling to communicate a message supported by the data.

There are many situations where you would want to present data visually.

Data visualization can be used for:

• Making data engaging and easily digestible

• Identifying trends and outliers within a set of data

• Telling a story found within the data

• Reinforcing an argument or opinion

• Highlighting the important parts of a set of data

Let’s look at some examples for each use case.

1. Make data digestible and easy to understand

Often, a large set of numbers can make us go cross-eyed. It can be difficult to find the significance behind rows of data.

Data visualization allows us to frame the data differently by using illustrations, charts, descriptive text, and engaging design. Visualization also allows us to group and organize data based on categories and themes, which can make it easier to break down into understandable chunks.

For example, this infographic breaks down the concept of neuroplasticity in an approachable way:

The same goes for complex, specialized concepts. It can often be difficult to break down the information in a way that non-specialists will understand. But an infographic that organizes the information, with visuals, can demystify concepts for novice readers.

2. Identify trends and outliers

If you were to sift through raw data manually, it could take ages to notice patterns, trends or outlying data. But by using data visualization tools like charts, you can sort through a lot of data quickly.

Even better, charts enable you to pick up on trends a lot quicker than you would sifting through numbers.

For example, here’s a simple chart generated by Google Search Console that shows the change in Google searches for “toilet paper”. As you can see, in March 2020 there was a huge increase in searches for toilet paper:

This chart shows an outlier in the general trend for toilet paper-related Google searches. The reason for the outlier? The outbreak of COVID-19 in North America. With a simple data visualization, we’ve been able to highlight an outlier and hint at a story behind the data.

Uploading your data into charts, to create these kinds of visuals is easy. While working on your design in the editor, select a chart from the left panel. Open the chart and find the green IMPORT button under the DATA tab. Then upload the CSV file and your chart automatically visualizes the information.

3. Tell a story within the data

Numbers on their own don’t tend to evoke an emotional response. But data visualization can tell a story that gives significance to the data.

Designers use techniques like color theory, illustrations, design style and visual cues to appeal to the emotions of readers, put faces to numbers, and introduce a narrative to the data.

For example, here’s an infographic created by World Vision. In the infographics, numbers are visualized using illustrations of cups. While comparing numbers might impress readers, reinforcing those numbers with illustrations helps to make an even greater impact.

Meanwhile, this infographic uses data to draw attention to an often overlooked issue:

4. Reinforce an argument or opinion

When it comes to convincing people your opinion is right, they often have to see it to believe it. An effective infographic or chart can make your argument more robust and reinforce your creativity.

For example, you can use a comparison infographic to compare sides of an argument, different theories, product/service options, pros and cons, and more. Especially if you’re blending data types.

5. Highlight an important point in a set of data

Sometimes we use data visualizations to make it easier for readers to explore the data and come to their own conclusions. But often, we use data visualizations to tell a story, make a particular argument, or encourage readers to come to a specific conclusion.

Designers use visual cues to direct the eye to different places on a page. Visual cues are shapes, symbols, and colors that point to a specific part of the data visualization, or that make a specific part stand out.

For example, in this data visualization, contrasting colors are used to emphasize the difference in the amount of waste sent to landfills versus recycled waste:

Here’s another example. This time, a red circle and an arrow are used to highlight points on the chart where the numbers show a drop:

Highlighting specific data points helps your data visualization tell a compelling story.

6. Make books, blog posts, reports and videos more engaging

At Venngage, we use data visualization to make our blog posts more engaging for readers. When we write a blog post or share a post on social media, we like to summarize key points from our content using infographics.

The added benefit of creating engaging visuals like infographics is that it has enabled our site to be featured in publications like The Wall Street Journal, Mashable, Business Insider, The Huffington Post and more.

That’s because data visualizations are different from a lot of other types of content people consume on a daily basis. They make your brain work. They combine concrete facts and numbers with impactful visual elements. They make complex concepts easier to grasp.

Here’s an example of an infographic we made that got a lot of media buzz:

We created this infographic because a bunch of people on our team are big Game of Thrones fans and we wanted to create a visual that would help other fans follow the show. Because we approached a topic that a lot of people cared about in an original way, the infographic got picked up by a bunch of media sites.

Whether you’re a website looking to promote your content, a journalist looking for an original angle, or a creative building your portfolio, data visualizations can be an effective way to get people’s attention.

Types of data visualizations

Data visualizations can come in many different forms. People are always coming up with new and creative ways to present data visually.

Generally speaking, data visualizations usually fall under these main categories:

Infographics

An infographic is a collection of imagery, charts, and minimal text that gives an easy-to-understand overview of a topic.

Charts

n the simplest terms, a chart is a graphical representation of data. Charts use visual symbols like line, bars, dots, slices, and icons to represent data points.

Some of the most common types of charts are:

• Bar graphs/charts

• Line charts

• Pie charts

• Bubble charts

• Stacked bar charts

• Treemaps

• Word clouds

• Pictographs

• Area charts

• Scatter plot charts

• Multi-series charts

The question that inevitably follows is: what type of chart should I use to visualize my data? Does it matter?

Short answer: yes, it matters. Choosing a type of chart that doesn’t work with your data can end up misrepresenting and skewing your data.

For example: if you’ve been in the data viz biz for a while, then you may have heard some of the controversy surrounding pie charts. A rookie mistake that people often make is using a pie chart when a bar chart would work better.

Pie charts display portions of a whole. A pie chart works when you want to compare proportions that are substantially different. Like this:

But when your proportions are similar, a pie chart can make it difficult to tell which slice is bigger than the other. That’s why, in most other cases, a bar chart is a safer bet.

Here is a cheat sheet to help you pick the right type of chart for your data:

Diagrams

Similar to a chart, a diagram is a visual representation of information. Diagrams can be both two-dimensional and three-dimensional.

Some of the most common types of diagrams are:

• Flowcharts

• Mind maps

• Venn diagrams

• Tree diagrams

• SWOT analysis

• Fishbone diagrams

• Histograms

• Wireframes

• Site maps

• Use case diagrams

Diagrams are used for mapping out processes, helping with decision making, identifying root causes, connecting ideas, and planning out projects.

Maps

A map is a visual representation of an area of land. Maps show physical features of land like regions, landscapes, cities, roads, and bodies of water.

A common type of map you have probably come across in your travels is a choropleth map. Choropleth maps use different shades and colors to indicate average quantities.

For example, a population density map uses varying shades to show the difference in population numbers from region to region:

Matplotlib and Seaborn Libraries for Data Visualization