VizNetwork Blog » data analysis

Using Visualization to Think

thcrawford — Tue, 28 Jun 2011 06:00:25 +0000

Often, we focus on visualization as an output, as a form of communication or speaking. It’s happens all to easily, since it’s the thing we see. However, often the real value of visualization comes in the process which causes, maybe forces, us to think differently. Sometimes the thinking and the speaking worlds come together and that’s exactly what’s shown in this presentation by Jameson Toole.

Jameson is a PhD in MIT’s Engineering Systems Division with the support of a National Science Foundation Graduate Research Fellowship. His research focuses on using large behavioral data sets generated from the web (Twitter, Facebook, Google, etc.), cell phones, or any other means, to find emergent patterns in human behavior and dynamics.

He has done some fascinating work bringing thinking and visualization together. Two of my favorite examples are in this talk we worked on for TEDxUofM. First, he looks at his relationship with his girlfriend through the lens of chat, texts, and e-mails which leads to an onstage apology. He then looks at the types of cellphone usage over time as a method for thinking about urban planning.

So as you watch the video, pay attention not only to his great delivery and unique wit, but also to how he used visualization to think about the world differently.

Well-formed Data – Part 4: Missing Data

thcrawford — Wed, 10 Feb 2010 19:02:23 +0000

How often do you get data that needs to be charted or graphed only to find out some of the data’s missing? We see it all the time. However, just because it’s missing, doesn’t mean you can ignore it. You need to know how to make it consistent, how to deal with it if it is missing, or sometimes even how to recover it. In this 9:12 video, the fourth in our series on well-formed data for charts & graphs, we cover:

types of missing data
differences between incomplete, space, blank/null, and 0 data
dealing with missing text
dealing with missing numbers
dealing with implied data

Let me know what you think!

Also, be sure to check out the other 3 videos in this series:

Part 1: Consistency (9:43)
Part 2: Concatenation & Extraction (9:57)
Part 3: Normalization (8:52)
Part 4: Missing Data (9:12)

Next up, more tips on using PowerPoint to create a visual impact.

Well-formed Data – Part 3: Normalization

thcrawford — Mon, 08 Feb 2010 19:14:23 +0000

Our lives are made up almost exclusively of relationships and that includes data. In fact, it’s hard to think of examples of data that doesn’t involve a relationship. Customers (hopefully) have many Orders. Companies have multiple employees. People (hopefully) have multiple friends, who also have multiple friends, and may even share some of each others friends. People may have multiple phone numbers, e-mail addresses, and so on.

Admittedly, this may be the geekiest of topics on creating well-formed data. In part 3 of our 4 part series, we discuss one way to make sure your data follows the ”1 Concept per Row” rule. Normalization is used whenever one concept relates to another concept. Given that almost all data is about relationships and we want to analyze that data, we have to know a bit about normalization which is all about those relationships. There are whole college classes dedicated to this topic, so we won’t be able to cover it all in this 8:52 video, but hopefully you’ll understand enough that you can do the basics yourself or talk intelligently to your data warehouse person.

In the video we discuss, 2 types of relationships…1 to many (e.g. 1 person may have 1 or more orders) and many to many (e.g. people have many friends that can overlap). These require slightly different solutions. There is a 3rd type of relationship, 1 to 1, however, dealing with that one doesn’t require normalization. That data can just be stored in the same spreadsheet since it follows the “1 Concept per Row” rule. The examples use Excel and the vLookup() function to illustrate the concepts.

Let me know what you think!

In the final video, we’ll wrap up our tour of well-formed data with a discussion on how to deal with missing data.

Well-formed Data – Part 2: Concatenation & Extraction

thcrawford — Mon, 18 Jan 2010 23:54:20 +0000

Continuing our series on preparing data for analysis & visualization, we’ve just released the next video on concatenation and extraction. The ability to break data apart and put it back together in new ways is essential to preparing data. By storing data at the lowest sensible level, it can be used separately or combined with other data for interesting analysis and visualization. In this practical video, we discuss 6 key Excel functions for extraction including left(), mid(), right(), search(), len(), and trunc().

Check out this 9:57 video to learn how to take the next step in preparing your data for analysis and visualization:

In the next 2 videos, we’ll continue the discussion with Normalization (advanced ideas to support One Concept per Row), and Missing Data (how to deal with missing or implied data).

Well-formed Data – Part 1: Consistency

thcrawford — Sun, 17 Jan 2010 15:23:55 +0000

Data visualization and analysis are powerful tools for discovering and communicating stories held in your data. However, before most of today’s data visualization tools can be used effectively, the data must be cleaned, organized and prepared. Over the next 4 videos, I’ll be discussing how to prepare your data to be visualized. The first step in the process is consistency. Consistency is made up of 4 principles:

One Concept per Row
One Data Type per Column
One Format per Data Type
Using the Lowest Sensible Level

Check out this 9:43 video to begin the most important step in preparing your data:

In the next 3 videos, we’ll continue the discussion with Concatenation & Extraction (how to put things together and take them apart), Normalization (advanced ideas to support One Concept per Row), and Missing Data (how to deal with missing or implied data).

Interactive Area Charts in Excel

thcrawford — Mon, 14 Dec 2009 21:00:04 +0000

In a recent post by Nathan from FlowingData, he does a great job of explaining how to interactive area charts. For the average person, though, his approach requires a lot of existing knowledge…Flash, Flex, coding, etc. So, I wanted to create a version that most people could create and use with NO coding required. For all the grief (often deserved) that Microsoft gets, there’s actually a lot of power in the Office suite, and Excel is no exception.

In the following 3 videos, I cover how to create an interactive area chart in Excel without coding. While I use Excel 2007, most of the features are available in at least the last two versions. As with everything, this approach has limitations…two big ones, in fact. First, it only works on PC. It takes advantage of the Active X controls and those are, sadly, PC only. Second, deals with a feature of charts in Excel that displays the label of lines/area with values of all zeros. There is a work around for the second issue, but since it requires code, I decided that I could live with the limitation. Generally, you won’t be displaying graph items with all zeros anyway, because why would you graph them? But that’s another post.

In the first video (6:29), I discuss how to set up the basic spreadsheet to make the interactive chart:

In the second video (8:12), I show you how to create the first set of controls:

In the final video (5:48), we finish off all the controls and talk about the limitations:

I hope you find this useful! Please let me know what you think and if you’d like to see other topics.