WiDS Conference 2017

Last week, I watched speakers at the Woman in Data Science conference (WiDS)  at Stanford via a local meet-up here in North Carolina.  The meeting was a world-wide event with speakers simulcast over the globe.

One talk that particularly interested me was on Data Visualization given by Miriah Meyer, a professor at the University of Utah.  You can watch her talk at 55:00 minutes into the livestream.  She gives some great examples about the insights we can gain by visualizing data.

During the Q&A session, Dr. Meyer was asked about the next great challenge in visualization. She responded that, “… It turns out we still don’t have good tools for non-programmers to use to create very rich and unique visualizations.”

…we still don’t have good tools
for non-programmers … to create very
rich and unique visualizations…
–  Miriah Meyer, PhD

DataGraph is not a programing language but it definitely has a programming attitude. I strongly believe that DataGraph can help bridge this gap to allow non-programmers, and programmers alike, to create rich data visualizations. The program gives you (1) virtually complete control of what you see in a graphic, and (2) a visual interface for combining commands and creating graphics.

For this post, I wanted to provide a couple of examples created in DataGraph that would be hard or impossible to do in a standard graphing program.

****************************

The first example is inspired by a second comment by Dr. Meyer that people working in data journalism or designing infographics are, “…somewhat limited in what they can do with data, unless they get some programming skills.”

I posted an example a few months ago to illustrate how DataGraph can be used to create infographics that are data driven.  On the left is an infographic that was made by the CDC.  On the right is my re-creation of this graphic using DataGraph.

In the CDC version, the U.S. is given the same color as New Zealand and Canada, despite being almost twice the amount.

In DataGraph version, the U.S. color is much darker than the other countries, which makes sense given the underlying data. To achieve this look, the color scheme is set up with a color ramp using bins, such that the same color is used for data between 2 and 3,  3 and 4,  4 and 5, … and so on.

Admittedly, this is a relatively simple graphic but the cool thing here is that the graphic is entirely data-driven. If I decide to add more countries or update the data when a new report comes out, I don’t have to recreate my graphic.

****************************

The next example is an animation, inspired by the well-known statistician Hans Rosling, who sadly passed away this week with pancreatic cancer.

 

This particular video shows the relationship between fertility and life expectancy for 100 years of data in one minute, using data downloaded from Gapminder.com.  Each moving point represents a country where the size  is scaled by population and the color is determined by the continent.

Rosling used similar animations in a number of highly watched TED talks that brought data to life in a unique way.  The one I have linked to here has over 11 Million views!  Clearly, well worth the watch.

****************************

To try DataGraph, download a free 14 day trial.

Download DataGraph files:
Infographic Example.dgraph
Gap Minder Example.dgraph

 

New Features in Version 4.2

On January 30th, we released the newest version of DataGraph, version 4.2.  This version has some great features, many of which were requested by our users.  These include:

  • violin plots,
  • confidence intervals in regressions,
  • a new Bracket command, and
  • improved color scheme options for larger data sets.

 

One of my personal favorites is the ability to extract x and y locations from the Label, Bracket, Region, and Range commands. This adds an interesting level of interactivity to graphics.


 

In the short video above, note how both graphs vary based on the location of the arrow, which we can drag around. To create this interactivity, the location of the arrow is extracted as a global variable. The value for the arrow location can then be used in other commands.

For a more detailed demo, check out the following video. Watch here or on our YouTube Channel.


 

Click below to download the file used in the demo:
2017-02-01 Old Faithful.dgraph

For more information on all the new features in DataGraph go to:
https://www.visualdatatools.com/DataGraph/Versions/50/

 

 

Happy New Year!

We recently added a new time variable to the DataGraph Beta version.

You can add this variable using the Other drop-down menu in the Global variables section of DataGraph.

 

We used the new time variable to create a DataGraph file that you can use to count down to the New Year.   The file is set up to show a ‘Ball Drop’ in New York and San Francisco.  You can also select your own time zone.

Click below to download the file and try out the new time variable. Note that you must use the Beta for this file to work.

2017-HappyNewYear.dgraph

In the Beta: Color Schemes and Plots

The most recent update to the DataGraph Beta includes new color scheme options and updates to the Plots command.

In the current release version of DataGraph (version 4.1), you can get suggested color schemes that depend on the number of items in your list. These suggested schemes were limited to 12 items or less.

In the most recent Beta, there are two new color schemes,  a Rainbow and a Gray scale color scheme, that can be created for longer lists.  You can also easily create custom color schemes that interpolate between two colors.

The Plots command is only in the Beta and the most recent Beta version has given this command a significant face lift.  The Plots command allows you to quickly create multiple line graphs and vary the color of each.

View a demonstration:  YouTube: DataGraph News

Download examples used in the video: DGBeta_2016-12-12.dgraph

For these examples to work, you must download the current Beta: http://www.visualdatatools.com/DataGraph/Versions/Beta/

Whether you purchased a DataGraph licenses through the Mac App store or from Visual Data Tools, you can use the Beta version without restrictions.

 

Sideways Histograms

The above image is featured in one of our Mac App Store screenshots.  It includes sideways histograms of monthly temperature data from three U.S. cities: Greensboro, NC; San Francisco, CA; and Flint, MI.

We were recently asked how to create this graphic. Although DataGraph has a Histogram command, it only creates a single histogram at a time. To create a series of sideways histograms, we are actually using the Box command, often used to create box-and-whisker plots.

First, let me show you what this data looks like using a Plot command for one of the cities.  These are average daily temperatures over 10 years.

time-series

Plotting the same data using a Box command, where the Values are set to the ‘temperature’ and the Position is set to ‘month’, results in the following image.

Box Whisker

To create the sideways histograms, go into the detail view of the Box command and modify the Type drop-down menu from ‘Whisker’ to ‘Probability’.  Now you have sideways histograms!

Probability Plots

Note that these are slightly different representations of your data when compared to the Histogram command, as each sideways histogram is scaled to the same height.

To create a graphic with all three cities, we used three Box commands and added a fill to each.  In the Axis settings, we also set the X-tick marks drop-down box to ‘Categories’ and set the Labels to a column with the name of each month.

Sideways Histograms

You can see why Mark Twain said, “The coldest winter I ever spent was a summer in San Francisco”, as this west-coast city does not warm up in the summer, when compared to locations like Flint or Greensboro. Although, I wonder whether or not he ever spent a winter in Flint?

For more details, click here to download a DataGraph file containing the data and graphics:  Sideways-Histograms.dgraph

Creating Infographics

The U.S. Center for Disease Control (CDC) recently published a number of infographics about motor vehicle safety.  This inspired me to create a similar looking infographic using DataGraph.

InfographicV1

The key to creating this graphic was to use the Bar command.  This command allows you to use a color scheme, such that each bar can have a different color.

For further information use the link below to download the DataGraph file that creates this image and has lots of annotations to help you create your own infographics.

Download DataGraph File: MotorVehicleCrashes.dgraph

Download a Free 14 day Trial of DataGraph

DataGraph on YouTube

DataGraph now has a YouTube Channel with several tutorial videos on two featured playlists.

The first playlist, Getting Started with DataGraph, contains how-to-videos that review the basics.  If you want to learn how to use DataGraph this is where to start!

The second playlist, DataGraph Demos, uses realistic datasets to create graphics using the wide array of techniques and functionally available in DataGraph.

If you have suggestions for topics you would like covered we would love to hear from you.