Makeover Monday Week 5…Christopher’s Take on Ann’s Viz

Well I’m back…as much as I talked about competition last week Ann has certainly been a model of consistency and graciously accepted my apology for slacking off last week…of course she is always happy to take the tiara and be crowned Viz Queen!

So here we are, 5 weeks down and still at 100% a piece!  This week’s data set presented quite a challenge in that we were only given 3 data points, no time series, and only a handful of countries.  Well 2 weeks in a row all I can say is: color me IMPRESSED!

In the data visualization/Tableau world pie charts are anathema:

See – http://www.evolytics.com/blog/tableau-pie-chart-a-better-approach/

http://www.businessinsider.com/pie-charts-are-the-worst-2013-6

and the Godfather of all things viz, Stephen Few, http://www.perceptualedge.com/articles/visual_business_intelligence/save_the_pies_for_dessert.pdf

So the only task…stay away from the PIE!  Like a diet…I digress.

Ann definitely surprised me with the scatter plot.  Quickly we can derive value from this somewhat ambiguous data set.  The reference line easily tells me exactly how I should interpret the relationship between the employment share and the net employment growth share.

Visually it is simple and elegant.  I’m not a big fan of grid lines but in this case they work as a contrast to the beige background.  Also I’m assuming the color codes were for continent/region…an interesting and purposeful take on a limited data set.

Overall I would recommend the UK Business Insider use THIS viz instead of the 2 ATROCIOUS pie charts!

Thank you Ann for your commitment to our project, to making me a better vizzer, and for maintaining your regal demure in the midst of it all!

On my process…Christopher’s take on #makeovermonday week 3

By popular demand (read because Ann practically BEGGED me to) I will go through my process for this week’s Makeover Monday…and my process in general with how I interact with and present social data.  A quick shoutout to my friend and Tableau social buddy Michelle Wallace who did an amazing presentation at TC16 on some of the concepts I’ll cover here in greater detail.

I have been working with social media (Twitter, Facebook, Blogs, etc.) data for the past year.  Typically there are 2 ways to go about accessing this data: through a third-party vendor or through the service itself.  Third party vendors usually aggregate things and export in nice neat csv’s or xlsx’s but can be expensive.  I personally like going directly to the source.  When I first started working with this data it wasn’t long before my searching on google led me to a host of other Tableau developers encountering similar issues: how to glean value out of social media data.  I noticed very quickly that a lot of folks were utilizing Tableau’s Web Data Connector to connect directly to the Twitter and Facebook data stores.

A great starting point is hitting up the Tableau Junkie (also known as Alex Ross) for his blog on creating a Twitter Web Data Connector

A forewarning this connects to Twitter’s Public Search API which is limited to the latest 5000 tweets, for anything more than this you will have to purchase Twitter’s “firehose” data stream called GNIP.

Once you bring in the data you get a similar set of fields like we saw on this week’s Makeover Monday.  The key to social media analysis is asking the basic 5 questions: who, what, where, when, and why.  We want to know who said it, what they were saying, where they said it, when they said it and all of this hopefully combines together to get at the why they said it.  A key ingredient to this equation is the “what” portion…in our data that was the “Status Text”.  There are a lot of ways to glean keywords and hashtags using regex and other methods but I wanted to see the frequency and prevalence of the exact words…ALL of the exact words.

My first thought was to use the “Text to Columns” function in Excel.  However, I quickly realized that each tweet might contain 10, 15, 20+ words and multiply that times 5,000 tweets at a minimum (if only using the Twitter Public API) we are talking 100,000+ rows of data, not the easiest thing to drag down in Excel.  Then even if we could get all those words we just have the words I wanted to be able to see what those words connected to, who said them, when were they said…and eventually be able to derive my own sentiment analysis using those words…a little more googling and VOILA: ALTERYX!

Alteryx not only has a text to columns, but the key was a text to “rows” function.  For example if you have a tweet that reads:

“Today is a good day”

What should return is:

Text                                               Word

Today is a good day          Today

Today is a good day            is

Today is a good day            a

Today is a good day            good

Today is a good day            day

You get the picture.  A little clean up and employing the NLTK (Natural Language ToolKit) stop words ridding us of those nasty “the” and “me” and “and” and now we’re starting to get down to the meat!

One of my absolute favorite features in Tableau is the word cloud…a very simple visual utilizing the tree map and changing the mark type to “Text” for more info see a step-by-step how-to here.

A final piece that I could not get to work in a timely fashion was the search box parameter (thank you Matt Francis for the great trick) but there’s some magic needed to be able to create an action on the word cloud, the trend line, AND make the text searchable.

Needless to say I think this is a very helpful way for anyone to be able to explore the data at a high level and then drill down into the content of the posts.

 

On collaboration…or a loooooong way to Christopher’s take on Ann’s Makeover Monday Week 2 Viz

Perhaps I am the child of my generation…riddled with ADD, chasing endless rabbit trails, searching for the source of the mysterious light that appears and then disappears…squirrel!  Ann’s comment about “brain sweat” had me googling to no end (ahh the wonders of the internet)…to which I found these 3 images:

this is what I imagine Ann’s brain  looks like…

this was just too funny to pass up…

and this was from a short and insightful presentation on the importance of creativity and divergent thinking here.

With all that said I echo Ann’s sentiment that I am consistently amazed week after week how different our visualizations are and how the techniques and creativity gleaned from each other’s interpretation are invaluable!

So here we are week 2…Ann has done an incredible job detailing her process in creating her dashboard here  so i will not spill any more virtual ink trying to get at the what and the why behind the visualization.  Suffice it to say…

At first glance the dashboard appears a little busy and plain.  I’m not a big fan of “serif” fonts so seeing them in the titles was a bit lackluster.  Having seen some of the other Makeover Monday submissions prior to and after viewing Ann’s viz I was expecting some cool backgrounds and colors and “Apple-esque” design…then it hit me, much like Apple the beauty is in the simplicity and more so in what’s just under the surface!

Ann has already admitted that she cheated by adding secondary data sources…so I will not beat a dead horse, but just so you know Ann: I WIN!!!  All jokes aside the intuition to glean the data from Statistica on global and US smartphone trends was pure genious.  Leave it to Ann once again to drive the story with the data and creative captions.  Unlike my visualization nothing is left to the end user to decipher or dive in to.  A clear and concise visualization concentrating on one metric to tell the story, and what is MORE to give Apple the benefit of the doubt, unlike the original viz (probably by some Mac-haters) that though the trend appears that the iPhone and Apple in general may be slowing in their astronomical growth maybe the market is just saturated.  I am thankful for this beautiful simplistic design and the ingenuity to weave a complex story and create a different narrative than a surface reading of the original data.

So here’s to brain-sweats all around!

#makeovermonday Week 1 – Christopher’s take on Ann’s Viz

Let me begin by saying that this blog/challenge/dynamic duo has been driven by the enthusiasm, drive, and passion of my cohort Ann!  The idea sparked in my mind at TC16 when she showed off her Tableau Public and my first reaction was to nit-pick and criticize…when in reality I realized my Tableau Public page was empty and I had NEVER done a Makeover Monday!  To my surprise, and delight, Ann came right back and said “where is yours?” to which I sheepishly replied “I don’t have any” :'(…and then her words were like a bitter medicine, necessary but painful…”then do one!”

So here we are one down 51 to go…100% Club here we come!

After Ann’s gracious feedback yesterday I am once again overwhelmed with the task of rising to her ever increasing over achievement!  So here is my humble attempt:

Right off the bat I have to say I’m  a sucker for good color/color schemes!  Ann nails this.  Tableau out-of-the-box gives a wide variety of color palettes so this can often be a difficult task to manage the line between beauty and overkill.  In this same vein the consistency of colors within the viz with the lines and font is a very nice touch.  After reading an earlier comment about the “floating legends” I see that she put the text box and legend in a horizontal container below the viz, this is an excellent technique when designing for the web/server/mobile/etc. as you never know how the visualization will be rendered in its final state when you employ the floating tiles.  The last technical piece I will applaud is the use of dynamic filters:

Not only is this an extremely creative way to employ the calculated fields used and describe the visual BUT it paints the picture so beautifully.

And with that we move on to the greatest aspect of this Makeover Monday: the story!  The ability to tell a story and communicate something so vividly is an incredible talent.  Though Ann herself does not have a daughter, the way she draws you in with the title and the once again, ingenious way she uses the field names in the tool tips, shows she is genuinely concerned about this unknown Australian daughter she might have had in a former life!  She brings the data to life, opens your front door, and sits down on your sofa to have a cup of coffee with you.

If this is the caliber of vizes we can expect from Ann Jackson this year you better buckle up your seatbelt because we are all in for a RIDE!  Looking forward to seeing what else she comes up with.

To see this and all of the rest of Mrs. Jackson’s creativity peek your head in at https://public.tableau.com/profile/ann.jackson#!/ and follow 🙂

Stay tuned for more next week…until then

Happy vizzing,

CS