May 24, 2022
John Oliver Coffey

Jumping into Data Visualization

Data Visualization, Data Viz for short, is a very old practice that is finding itself on the spotlight due to the huge amounts of data we have in our hands today and the need to understand and make decisions based upon it. Data Viz excels at this and is the fastest and more trustworthy way to understand the distribution and behavior in a data set.

As an example we have Alberto Cairo’s Datasaurus, based on Anscome’s Quartet, this allows us to see how summary statistics can be similar even when the underlying data is extremely different. As a rule of thumb when working with data , summary statistics are not enough it is always better to visualize the data.

But data visualization can be much more. In recent years thanks to several Open Data initiatives we have access to all kind of information. Journalists are using this newfound data to find stories and data visualization to share those stories with the world. Nowadays it’s common to see newsrooms with data analysts or data visualization designers working side by side with journalists on a story.

Data visualization is going into a golden age with new publications, studies and projects pushing the discipline further and creating new and interesting ways to make data visual.

Here are some of them:

Resources

References

This are some of the best players out there, they keep pushing the boundaries of the field in an interesting and provocative way.

Books

Data visualization is ever changing but it also has deep roots some of these books shaped how people perceived graphs and of the possibilities they hold.

Blogs

It’s important to be up to date. These blogs have monthly or weekly articles about new ideas or the state of data visualization. They also have great resources for begginers and it’s a good place to start looking ideas when in a pinch.

Tools

Code:

Using code to make your idea come to life opens the door to a lot of new possibilities Most libraries built for this task are mainly in Javascript but Python and R have several good options to create amazing work.

No Code:

In case you don’t code there are several tools that will make your work easier and allow you an easy and quick way to jump into visualizing information.

For Color:

Color is one of the most important and usually most forgotten elements in a data visualization. With these tools you can choose and test the colors you want to use on you project.

Data

There are several places you can get data to start working on personal projects. Using these resources you will be able to build a portfolio using open data shared for everyone use.

Community

Jobs

Data jobs are booming right now and every week there seems to be a new opening somewhere, if you are looking for oportunities this are some useful starting points.

Social Media

Finally is important to be where the action is at, many experts in data visualization have social media accounts and they talk about their work, ideas and issues in the data vis community. It’s a very open space and it never hurts to join in.

Finally I want to state that I didn’t include every library, publication or tool available. There are many great resources that were not included because there would be simply to many, but in case you want to know more about the field and are interest in going more in-depth I’m here to help.

Do you have an idea? Let’s talk about it.