Jackson Two

Tag: iron viz

  • Without Water an Iron Viz feeder

    Without Water an Iron Viz feeder

    Jump directly to the viz

    At the time of writing it is 100°F outside my window in Arizona and climbing.  It’s also August and we’re right in the middle of feeder round 3 for Tableau Public’s Iron Viz contest.  Appropriately timed, the theme for this round is water.  So it’s only fitting that my submission for this round would take into consideration the mashup of these two and form my submission: Without Water, 2 decades of drought & damage in Arizona.

    The Genesis of the Idea

    I’ll start by saying that water is a very tricky topic.  The commonplace of it makes searching for data and a narrative direction challenging.  It’s necessary for sustaining life, so it seems to want to have a story tied directly to humankind – something closely related to water quality, water availability, loss of water – essentially something that impacts humans.  And because it’s so vital, there are actually several organizations and resources doing fantastic things to demonstrate the points above.  Unicef tracks drinking water and sanitation, Our World in Data has a lengthy section devoted to the topic, there’s the Flint Water Study, and the Deepwater Horizon oil spill.

    This realization around the plethora of amazing resources associated with water led me to the conclusion that I would have to get personal and share a story not broadly known.  So what could be more personal than the place I’ve called home for 14 years of my life: Arizona.

    Arizona is a very interesting state, it’s home to the Grand Canyon, several mountain ranges, and of course a significant portion of the Sonoran desert.  This means that in October it can be snowing in the mountains of Flagstaff and a stifling 90°F two hours south in Phoenix.  And, despite the desert, it needs water.  Particularly in the large uninhabited sections of the mountains covered with forests.  Getting to the punchline: since my time in Arizona, the state has been in a long sustained drought.  A drought that’s caused massive wildfires, extreme summer heat, and conversation thread that never steers far from the weather.

    Getting Started

    A quick google search led me to my first major resource: NOAA has a very easy to use data portal for climate data which includes: precipitation, various drought indices, and temperatures – all by month/state/and division.  This served as the initial data set along with the joining of climate division shapefiles maintained by NCEI.  Here’s the first chart I made showing the divisions by their drought index.  This uses the long term Palmer Drought Severity Index and any positive values (non-drought) are zeroed out to focus attention on deficit.

    My next major find was around wildfire data from the Federal Fire Occurrence website.  Knowing that fire is closely associated with drought, it seemed a natural progression to include.  Here’s an early iteration of total acres destroyed by year:

    It’s clear that after 2002 a new normal was established.  Every few years massive fires were taking place.

    And after the combination of these two data sets – the story started developing further – it was a time bound story of the last 20 years.

    Telling the Story

    I headed down the path of breaking out the most relevant drought headlines by year with the idea of creating 20 micro visualizations.  Several more data sources were added (including dust storms, heat related deaths, and water supply/demand).  An early iteration had them in a 4 x 5 grid:

    As the elements started to come together, it was time to share and seek feedback.  Luke Stanke was the first to see and gave me the idea of changing  from a static grid to a scrolling mobile story.  And that’s where things began to lock into place.  Several iterations later and with input from previous Iron Viz winner Curtis Harris – the collection of visualizations was starting to become more precisely tuned to the story.  White space became more defined and charts were sharpened.

    My final pass of feedback included outsourcing to Arizona friends (including Josh Jackson) to ask if it evoked the story we’re all experiencing and it’s what led to the ultimate change in titles from years to pseudo-headlines.

    Wrapping Up

    My one last lingering question: Mobile only or to include a desktop version?  The ultimate choice and deciding factor was to create a medium and version that was optimized for getting to the largest end audience – thus, mobile only.

    WITHOUT WATER

    And now that all leads to the final product.  A mobile only narrative data story highlighting the many facets of drought and it’s consequences for the state of Arizona.  Click on the image to view the interactive version on Tableau Public.

    click to view on Tableau Public

     

     

  • The Shape of Shakespeare’s Sonnets | #IronViz Books & Literature

    The Shape of Shakespeare’s Sonnets | #IronViz Books & Literature

    Jump directly to the viz

    If it’s springtime that can only mean that it’s time to begin the feeder rounds for Tableau’s Iron Viz contest.  The kick-off global theme for the first feeder is books & literature, a massive topic with lots of room for interpretation.  So without further delay, I’m excited to share my submission: The Shape of Shakespeare’s Sonnets.

    The genesis of the idea

    The idea came after a rocky start and abandoned initial idea.  My initial idea was to approach the topic with a meta-analysis or focus on the overall topic (‘books’) and to avoid focusing on a single book.  I found a wonderful list of NYT non-fiction best sellers lists, but was uninspired after spending a significant amount of time consuming and prepping the data.  So I switched mid-stream and decided to keep the parameters of a meta-analysis, but change to a body of literature that a meta-analysis could be performed on.  I landed on Shakespeare’s Sonnets for several reasons:

    • Rigid structure – great for identifying patterns
    • 154 divides evenly for small multiples (11×14 grid)
    • Concepts of rhyme and sentiment could easily be analyzed
    • More passionate subject: themes of love, death, wanting, beauty, time
    • Open source text, should be easy to find
    • Focus on my strengths: data density, abstract design, minimalism
    Getting Started

    I wasn’t disappointed with my google search, it took me about 5 minutes to locate a fantastic CSV containing all of the Sonnets (and more) in a nice relational format.  There were some criteria necessary for the data set to be usable – namely each line of the sonnet needed to be a record.  After that point, I knew I could explode and reshape the data as necessary to get to a final analysis.

    Prepping & Analyzing the Data

    The strong structuring of the sonnets meant that counting things like number of characters and number of words would yield interesting results.  And that was the first data preparation moment.  Using Alteryx I expanded out line into columns for individual words.  Those were then transposed back into rows and affixed to the original data set.  Why?  This would allow for quick character counting in Tableau, repeated dimensions (like line, sonnet number), and dimensions for the word number in each line.

    I also extracted out all the unique words, counted their frequency, and exported them to a CSV for sentiment analysis.  Sentiment analysis is a way to score words/phrases/text to determine the intention/sentiment/attitude of the words.  For the sake of this analysis, I chose to go with a negative/positive scoring system.  Using Python and the nltk package, each word’s score was processed (with VADER).  VADER is optimized for social media, but I found the results fit well with the words within the sonnets.

    The same process was completed for each sonnet line to get a more aggregated/overall sentiment score.  Again, Alteryx was the key to extracting the data in the format I needed to quickly run it through a quick Python script.

    Here’s the entire Alteryx workflow for the project:

    The major components
    • Start with original data set (poem_lines.csv)
      • filter to Sonnets
      • Text to column for line rows
      • Isolate words, aggregate and export to new CSV (sonnetwords.csv)
      • Isolate lines, export to new CSV (sonnetlines)
      • Join swordscore to transformed data set
      • Join slinescore to transformed data set
      • Export as XLSX for Tableau consumption (sonnets2.xlsx)
    Python snippet
    make sure you download nltk leixcons after importing; thanks to Brit Cava for code inspiration

    The Python code is heavily inspired by a blog post from Brit Cava in December 2016.  Blog posts like hers are critically important, they help enable others within the community do deeper analysis and build new skills.

    Bringing it all together

    Part of my vision was the provoke patterns, have a highly dense data display, and use an 11×14 grid.  My first iteration actually started with mini bar charts for number of characters in each word.  The visual this produced was what ultimately led to the path of including word sentiment.

    height = word length, bars are in word order

    This eventually changed to circles, which led to the progression of adding a bar to represent the word count of each individual line.  The size of the words at this point became somewhat of a disruption on the micro-scale, so sentiment was distilled down into 3 colors: negative, neutral, or positive.  The sentiment of the entire line instead has a gradient spectrum (same color endpoints for negative/positive).  Sentiment score for each word was reserved for a viz in tool tip – which provides inspiration for the name of the project.

    Sonnet 72, line 2

    Each component is easy to see and repeated in macro format at the bottom – it also gives the end user an easy way to read each Sonnet from start to finish.

    designed to show the progression of abstraction

    And there you have it – a grand scale visualization showing the sentiment behind all 154 of Shakespeare’s Sonnets.  Spend some time reciting poetry, exploring the patterns, and finding the meaning behind this famous body of literature.

    Closing words: thank you to Luke Stanke for being a constant source of motivation, feedback, and friendship.  And to Josh Jackson for helping me battle through the creative process.

    The Shape of Shakespeare’s Sonnets

    click to interact at Tableau Public

     

     

     

  • A follow up to The Women of #IronViz

    A follow up to The Women of #IronViz

    It’s now 5 days removed from the Tableau Conference (#data17) and the topic of women in data visualization and the particularly pointed topic of women competing in Tableau’s #IronViz competition is still fresh on everyone’s mind.

    First – I think it’s important to recognize how awesome the community reception of this topic has been.  Putting together a visualization that highlights a certain subsection of our community is not without risk.  While going through the build process, I wanted to keep the visualization in the vein of highlighting the contributions of women in the community.  It wasn’t meant to be selective or exclusive, instead, a visual display of something I was interested in understanding more about.  Despite being 5 days removed from the conference, the conversations I’ve been involved in (and observed from a distance) have all remained inclusive and positive.  I’ve seen plenty of people searching for understanding and hunting for more data points.  I’ve also seen a lot of collaboration around solutions and collecting the data we all seek.  What I’m thankful that I have not witnessed is blame or avoidance.  In my mind this speaks volumes to the brilliant and refined members of our community and their general openness and acceptance of change, feedback, and improvement.

    One thing circling the rounds that I felt compelled to iterate off of, is @visualibrarian’s recent blog post that has interview style questions and answers around the topic.  I am a big believer in self reflection and exploration and was drawn to her call to action (maybe it was the punny and sarcastic nature of the ask) to answer the questions she put forth.

    1. Tell me about yourself. What is your professional background? When did you participate in Iron Viz?

    My professional background is that of a data analyst.  Although I have a bachelor’s degree in Mathematics, my first professional role was as a Pharmacy Technician entering prescriptions.  That quickly morphed into someone dedicated to reducing prescription entry errors and built on itself over and over to be put in roles like quality improvement and process engineering.  I’ve always been very reliant on data and data communication (in my early days as PowerPoint) to help change people and processes.  About 2 or 3 years ago I got fed up with being the business user at the mercy of traditional data management or data owners and decided to brute force my way into the “IT” side of things.  I was drawn to doing more with data and having better access to it.  Fast-forward to the role I’ve had for a little over 8 months as a Data Visualization Consultant.  Which essentially means I spend a significant amount of my time partnering with organizations to either enable them to use visual analytics, improve the platforms that they are currently using, or overcoming any developmental obstacles they may have.  It also means I spend a significant amount of time championing the power of data visualization and sharing “best practices” on the topic.  I often call myself a “data champion” because I seek simply to be the voice of the data sets I’m working with.  I’m there to help people understand what they’re seeing.

    In terms of Iron Viz – I first participated in 2016’s 3rd round feeder, Mobile Iron Viz.  I’ve since participated in every feeder round since.  And that’s the general plan on my end, continue to participate until I make it on stage or they tell me to stop 🙂

    2. Is Tableau a part of your job/professional identity?

    Yes – see answer to question #1.  It’s pretty much my main jam right now.  But I want to be very clear on this point – I consider my trade visual analytics, data visualization, and data analytics.  Tableau is to me the BEST tool to use within my trade.  By no means the only tool I use, but the most important one for my role.

    3. How did you find out about Iron Viz?

    When I first started getting more deeply involved in my local User Group, I found out about the competition.  Over time I became the leader of my user group and a natural advocate for the competition.  Once I became a part of the social community (via Twitter) it was easy to keep up with the ins and outs of the competition.

    4. Did you have any reservations about participating in Iron Viz?

    Absolutely – I still have reservations.  The first one I participated in was sort of on the off chance because I found something that I want to re-visualize in a very pared down elegant, simplistic way.  I ended up putting together the visualization in a very short period of time and after comparing it to the other entries I felt my entry was very out of place.  I tend to shy away from putting text heavy explanations within my visualizations, so I’ve felt very self-conscience that my designs don’t score well on “story telling.”  It was also very hard in 2016 and the beginning of 2017.  Votes were based off of Twitter.  You could literally search for your hashtag and see how many people liked your viz.  It’s a very humbling and crushing experience when you don’t see any tweets in your favor.

    5. Talk me through your favorite submission to Iron Viz. What did you like about it? Why?

    Ah – they are all my favorite for different reasons.  For each entry I’ve always remained committed and deeply involved in what the data represents.  Independent of social response, I have always been very proud of everything I’ve developed.  For no other reason than the challenge of understanding a data set further and for bringing a new way to visually display it.  My mobile entry was devastatingly simple – I love it to death because it is so pared down (the mobile version).  For geospatial I made custom shapes for each of the different diamond grades.  It’s something I don’t think anyone in the world knows I did – and for me it really brought home the lack of interest I have in diamonds as rare coveted items.

    6. What else do you remember about participating in Iron Viz?

    The general anxiety around it.  For geospatial 2017 I procrastinated around the topic so much.  My parents actually came to visit me and I took time away from being with them to complete.  I remember my mom consoling me because I was so adamant that I needed to participate.

    Safari and Silver Screen were different experiences for me.  I immediately locked in on data sets on subjects I loved, so there was less stress.  When I did the Star Trek entry I focused on look and feel of the design and was so stoked that the data set even existed.  Right now I am watching The Next Generation nightly and I go back to that visualization to see how it compares to my actual perception of each episode (in terms of speaking pace and flow).

    7. Which Iron Viz competitions did you participate in, and why?

    Everything since 2016 feeder round 3.  I felt a personal obligation and an obligation to my community to participate.  It was also a great way for me to practice a lot of what I tell others – face your fears and greet them as an awesome challenge.  Remain enthusiastic and excited about the unknown.  It’s not always easy to practice, but it makes the results so worth it.

    8. What competitions did you not participate in, and why?

    Anything before mobile – and only because I (most likely) didn’t know about it.  Or maybe more appropriately stated – I wasn’t connected enough to the community to know of it’s existence or how to participate.

    9. Do you participate in any other (non Iron Viz) Tableau community events?

    Yes – I participate in #MakeoverMonday and #WorkoutWednesday.  My goal for the end of 2017 is to have all 52 for each completed.  Admittedly I am a bit off track right now, but I plan on closing that gap soon.  I also participate in #VizForSocialGood and have participated in past User Group viz contests.  I like to collect things and am a completionist – so these are initiatives that I’ve easily gotten hooked on.  I’ve also reaped so many benefits from participation.  Not just the growth that’s occurred, but the opportunity to connect with like-minded individuals across the globe.  It’s given me the opportunity to have peers that can challenge me and to be surrounded by folks that I aspire to be more like.  It keeps me excited about getting better and knowing more about our field.  It’s a much richer and deeper environment than I have ever found working within a single organization.

    10. Do you have any suggestions for improving representation in Iron Viz?

    • Make it more representative of the actual stage contest
    • Single data set
    • Everyone submits on the same day
    • People don’t tweet or reveal submissions until contest closes
    • Judges provide scoring results to individual participants
    • The opportunity to present analysis/results, the “why”
    • Blind submissions – don’t reveal participants until results are posted
    • Incentives for participation!  It would be nice to have swag or badges or a gallery of all the submissions afterward

    And in case you just came here to see the visualization that’s set as the featured image, here’s the link.

  • Star Trek The Next Generation: Every Episode (#IronViz 3)

    Star Trek The Next Generation: Every Episode (#IronViz 3)

    It’s that time again – Iron Viz feeder contest!  The third and final round for a chance to battle at conference in a chef coat is upon us.  This round the focus was on anything ‘Silver Screen.’

    With a limitless topic I was certain that I would find myself in a creative rut that would likely result in submitting something at the end of the submission time period (August 13th).  So I am as shocked as anyone else that I have a fully formed submission way before deadline.

    So what’s the topic and what got me unstuck?  Star Trek of course!  The backstory here is amazing – I went to a belated wedding shower for a few friends and they mentioned to me that they were going to the annual Star Trek convention.  And more specifically there was a special celebration occurring – the 30th anniversary of Star Trek: The Next Generation.  Not even up for debate – it just IS the best incarnation of the Star Trek universe.

    So I decided to take a moment to do some research on finding TNG data.  It didn’t take me long to unearth this fantastic data set on GitHub that includes each episode’s script parsed out by character.

    Really inspired by the thought of seeing each word of each episode visualized – I set forth on my mission.  As I got started there was one component that was mission critical: the bold colors present throughout the world of Star Trek.  The bold and moody colors of Star Trek are fantastic – especially paired with a black background.  And working with individual scripts meant that I could use color to accentuate different characters – much like their uniforms do in the episodes.

    The next component that I wanted to invoke on this (again – design focused here) was the electronics and computer interfaces.  I particularly like the rounded edges and strong geometric shapes that are on the computer screens across all iterations of Star Trek.  So that describes most of the design – the choice of colors and how some of the visualizations were setup.

    Now on to the next important component here: analysis.  When you see this visualization you may find yourself realizing that I don’t draw any conclusions.  For this collection of visualizations I am playing the role of curator.  I am developing a visual world for you to interact with, to go deep and wide in your understanding.  I am not attempting to summarize data for you or force conclusions upon you.  I am inviting you to come into the world of Star Trek, unearth who speaks during each episode, find out what that character is saying.  I want there to be an unending number of takeaways and perceptions generated from this.

    And the last part you need to understand is the story telling.  This entire visualization has an untold number of stories in it by virtue of it being a visualization of the entire series.  If you want a meta-story to tell it’s simply this: Star Trek The Next Generation is such a deep and rich world that you should go get lost.  And while you’re on the path of getting lost do me a favor: retain some leadership tidbits from Picard and sprinkle in some logical takeaways from Data.

     

  • #IronViz – Let’s Go on a Pokémon Safari!

    #IronViz – Let’s Go on a Pokémon Safari!

    It’s that time again – Iron Viz!  The second round of Iron Viz entered my world via an email with a very enticing “Iron Viz goes on Safari!” theme.  My mind immediately got stuck on one thing: Pokémon Safari Zone.

    Growing up I was a huge gamer and Pokémon was (and still is) one of my favorites.  I even have a cat named after a Pokémon, it’s Starly (find her in the viz!).  So I knew if I was going to participate that the idea for Pokémon Safari was the only way to go.

    I spent a lot of time thinking about how I might want to bring this to life.  Did I want to do a virtual safari of all the pocket monsters?  Did I want to focus on the journey of Ash Ketchum through the Safari Zone?  Did I want to focus on the video games?

    After all the thoughts swirled through my mind – I settled on the idea of doing a long form re-creation of Ash Ketchum’s adventure through the Safari Zone in the anime.  I sat down and googled to figure out the episode number and go watch.  But to my surprise the episode has been banned.  It hasn’t made it on much TV and the reason it is banned makes it very unattractive and unfriendly for an Iron Viz long form.  I was gutted and had to set off on a different path.

    The investment into the Safari Zone episode got me looking through the general details of the Safari Zone in the games.  And that’s what ended up being my hook.  I tend to think in a very structured format and because there were 4 regions that HAD Safari Zones (or what I’d consider to be the general spirit of one) it made it easy for me to compare each of them against each other.

    Beyond that I knew I wanted to keep the spirit of the styling similar to the games.  My goal for the viz is to give the end user an understanding of the types of Pokémon in each game.  To show some basic details about each pocket monster, but to have users almost feel like they’re on the Safari.

    There’s also this feeling I wanted to capture – for anyone who has played Pokémon you may know it.  It’s the shake of the tall grass.  It is the tug of the Fishing Pole.  It’s the screen transition.  In a nutshell: what Pokémon did I just encounter?  There is a lot of magic in that moment of tall grass shake and transition to ‘battle’ or ‘encounter’ screen.

    My hope is that I captured that well with the treemaps.  You are walking through each individual area and encountering Pokémon.  For the seasoned Safari-goer, you’ll be more interested in knowing WHERE you should go and understanding WHAT you can find there.  Hence the corresponding visuals surrounding.

    The last component of this visualization was the Hover interactivity.  I hope it translates well because I wanted the interactivity to be very fluid.  It isn’t a click and uncover – that’s too active.  I wanted this to be a very passive and openly interactive visualization where the user would unearth more through exploring and not have to click.

  • #IronViz Entry – Mobile Design

    #IronViz Entry – Mobile Design

    Part of being involved in the Tableau community means publicly publishing visualizations to learn and grow.  It’s also a great way to find inspiration.

    As I’ve pushed myself to be more active within the local Phoenix Tableau community and social (Twitter) community, I knew it was time to “step up” and make an Iron Viz.

    My design aesthetic tends to be minimal, slightly formal, and geared toward (in my mind) elegance.  I like to make dashboards and visualizations that highlight the data, but don’t jump to many conclusions.  I’m very conclusion agnostic, so leading people too far down a path doesn’t always seem right.

    All that being said – I wanted to make an Iron Viz entry, but it needed to be simple.  The deadline is September 18 (today as I’m writing this).  So I wanted to develop something relatively straightforward that got to the heart of mobile design.

    The data inspiration for the viz actually came from an animated bar chart .gif showing the “Top 10 Economies” growth from 1969 to 2030 that I saw on Twitter.  I thought it would make a nice bump chart or slope chart, and the conclusion of the data was already compelling.

    First the data gathering process – relatively simple on this one.  The .gif referenced the source, a quick Google search led me to the results.  I’m going to loosely promise to publish the excel file at some point.

    Next up was diving right in.  I recently made a “micro viz” in Tableau 10, designing it exclusively for a very tiny space.  I actually didn’t use the device designer for this one, instead opting to develop the whole thing with my intended sizing.  With the sizing set, development was similar to what I’ve done in the past in v9.3 (version of Tableau I use at my job).

    Transitioning to device specific design was different than I thought.  Since I knew the final product (in my mind) would need to have more emphasis placed on the mobile view.  It is after all a mobile design challenge!

    Like I mentioned above, I had a pretty good idea of what I wanted the final viz to look like.  I knew there needed to be a bump chart and I was going to call attention to China and India.  What I didn’t realize is that the device designer is really geared toward creating a “master view” and then augmenting that master for the device.  This makes sense to me as I rethink the way the feature was presented.

    What this meant for the creative process?  I wasn’t able to make visualizations (sheets) and quickly drop them on the mobile layout.  For each new “potential viz” I had to first drop it on the overall dashboard and then bring it on to the mobile specific dash.  It made the whole process kind of clunky.

    I also struggled a bit with getting to formatting features quickly.  I can’t double click on titles to adjust font sizes in device preview, gotta go back to the default layout.  I’ll have to adjust my thought process next time and really think about starting from the default view and optimizing a mobile version.

    I probably cheated the viz out of more depth that could have been added if I had truly started with the default dashboard and then made a mobile design.  It is fair to say that the default dashboard has real estate for more data insight and data depth.  I am still very pleased with the overall final results.