Episode 25: How to Design a More Inviting Data Viz - Featured Data Visualization by Sarah Bartlett
 
 Sarah Bartlett ( source )

Sarah Bartlett (source)

 

Welcome to episode 25 of Data Viz Today. How can you create a data viz that feels inviting to your reader? Host Alli Torban explores the specific design elements that can offer your reader an enjoyable experience. Featured data visualization by Sarah Bartlett perfectly demonstrates how investing in an inviting design can lead to a pleasant, informative, and memorable experience.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:25 - Today’s episode is about what makes a design inviting. What do I mean by inviting… the definition of inviting is “offering the promise of an enjoyable experience.” To me, an inviting design is one with a harmonious color palette, it’s easy to read and orient myself, and basically the whole thing doesn’t look intimidating, like it’s going to be a lot of mental work to decipher.

  • 01:35 - Today’s featured data viz project is called “Explore European Cities on a Budget” by Sarah Bartlett. Sarah’s a data visualisation consultant & Tableau Ambassador based in London.

  • 02:40 - Sarah said she almost didn’t submit a viz into the feeder competition this year because she had gotten super busy and her search for a dataset was turning out to be uninspiring. There was only 6 days left until the deadline so it seemed hopeless. Then she received the best advice from a former iron viz champ Tristan Guillevin: don’t get hung up on the data set. It’s never going to be perfect and exactly what you envisioned. Pick one, start visualizing it in tableau and a new idea and story will come to you.

  • 03:26 - So with this new perspective of finding something basic and building up from it, Sarah started searching with a tourism perspective and found a website called www.priceoftravel.com that breaks down the costs of traveling to different cities, like lodging, food, activities.

  • 03:50 - But she had a problem…She couldn’t get the data off of the website easily. Her friend Lorna Eden scraped the data from the website using Alteryx.

  • 04:28 - For design inspiration she used pinterest and the site CSS Drive to upload an image of a European city that she liked and it automatically generated a color palette for her to use which had soft blues and browns.

  • 05:40 - She added two things that I think really take it from a nice viz to a really inviting viz.

    1. She added a small map with her color palette using Mapbox and picture for each city. It’s super easy to create custom styled maps in mapbox and if you’ve been wanting to try it, check out my free Mapbox course.

    2. She used icons instead of labels for her bar chart.

      • Pros of icons: save a lot of real estate by replacing text with pictures, and these pictures give your readers the benefit of being able to easily scan and process the information. It’s inviting because people are drawn to real life objects that they’re familiar with and the data doesn’t seem so intimidating.

      • Cons of icons: you have to use icons that are really easily understandable so you don’t make it even harder to understand than text (test it with your audience). It can look cluttered if you don’t use the similar colors and style (like line thickness, curved or straight edges).

  • 08:25 - Sarah used the website NounProject to download royalty free icons

  • 09:45 - Then she asked some fellow tableau users to give her feedback. She said it’s always amazing to her how helpful getting feedback is because you just get so blind to easy mistakes because you’re staring at the viz for so long.

  • 10:33 - Sarah was able to pack in so much information but make it so inviting and fun to explore. I think the top 3 things that contributed to this was her harmonious color palette, the map and image that orients you to the city, and the icons that just give the charts a less intimidating feel.

  • 10:55 - Applying these three things to the viz that I did about chess in episode 11 because it just feels like kind of a cold viz to me, but it’s about something fun and interesting, so I think it could benefit from some design elements that make it softer and more inviting.

  • 11:40 - So first thing, color. I used CSS Drive to get the color palette out of an image of a forest that I chose because it made me think of those chess sets that are carved out of wood.

  • 12:10 - I added a map of the small town outside of Amsterdam where the tournament takes place to orient the reader to what this is. I used Mapbox’s site called Cartogram which lets you upload an image and it’ll automatically style your map features based on colors from your image. So my color palette was extended to my map.

  • 12:38 - Then I started looking for places that I could add icons to make it easier to read. I used a brown person icon and an image of the eventual winner Magnus Carlsen instead of diamonds in the viz.

BEFORE

AFTER

 

  • 13:37 - My final takeaway is that inviting design is your way of offering the promise of an enjoyable experience to your reader. And to me, an inviting design is one that’s easy to read, orients you, and doesn’t feel intimidating and cluttered.

  • 13:55 - Try using a color palette inspired by nature or art, use a map and pictures to orient your reader, and use icons to reduce clutter and make your information easier to process.

  • 14:06 - Sarah’s advice to designers just starting out: “Get as much practice as you can. Practice your craft every day if possible. To avoid getting bored, try and visualise data on a subject you enjoy such as your favourite band, movie or hobbies.”

  • 14:40 - Follow Sarah on her website and on Twitter

  • 14:55 - Come and join the Northern Virginia in-person version of the Data Vis Book Club (started by Lisa Charlotte Rost) on August 22nd!


Episode 24: [Mini] 3 Questions to Ask Yourself Before You Viz for Free
 
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Welcome to episode 24 of Data Viz Today. Have you ever heard these words? "We don't have a budget for this work, but we can offer you exposure!" Whether you're more in the graphic design camp or the data journalism camp, you'll probably run up against this at some point in your freelancing journey. In this episode, I offer 3 questions to ask yourself before agreeing to do data viz work for free so that you can protect your time and engage in projects that are truly a win-win.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 01:00 - If you’re a data viz freelancer, whether your foot is more in the graphic design camp or the data journalism camp, then you probably have run up against people who expect you to work for free… what they like to call “for exposure” or “for experience”... and you consider doing it because you’re building a portfolio or resume or trying to get your name out there to get more work.

  • 01:25 - In this episode, I offer 3 questions to ask yourself before accepting a free project.

  • 01:50 - Listen for my story about hearing this for the first time: “Not sure what you mean by rate...we will print it to give you exposure.”

  • 03:20 - Some people might think of it as paying your dues - you just need to suck it up and get paid nothing or very little at the beginning while you build up your expertise, and I’d tend to agree with the idea of working up the ladder, but I see a big problem with this ‘work for exposure’ model…

  • 03:43 - Unpaid work is a barrier to social mobility. You’re excluding the people who truly can’t afford to do any work for free. We want diverse voices and by making working for free as a requirement to building a portfolio or expertise, then we make hearing diverse voices that much harder. And the more that people accept working for free as ‘just the way you pay your dues’ then the more companies come to expect it and more people are asked to work for free year after year. And it’s a vicious cycle. Not to mention, it’s straight up rude to de-value someone’s time and effort.

  • 04:30 - I’m not going to sit here and tell you never to work for free in order to build up your expertise or portfolio, because we all have different situations and I have worked for free plenty too.

  • 04:45 - Here are three questions that you should ask yourself before data vizzing for free (so that all free work is super strategic!):

 

  • 05:00 - Question #1: Where does this fall on the ladder to your ideal job?

    • If you’re not really sure what your end goal is - like you want to be a data journalist for the Washington Post or you want be a freelancer who provides custom dashboards to local banks - then define that first. Then you can easily assess how this project fits on your ladder to your goal. Is this project a solid rung that you can stand on to get closer to your goal?

 

  • 05:56 - Question #2: Could you turn this into a passion project instead for similar or better exposure?

    • With social media, you can create and share a cool project so easily and it can spread to just as many eyes as if you had done it for a company or magazine.

    • So if you’re in a situation where you think this project is interesting and could get some eyes on your work… ask yourself if there’s a way you could do a similar project just on your own as a passion project. You get the chance to learn new tools or techniques by creating it, and then share it across your network, tag people who you think would be interested and get exposure for yourself.

    • If you want to hear more about how to create a fulfilling passion project, check out Episode 18: How to Start a Passion Project That Hones Your Skills & Opens New Doors.

      There are so many benefits - like you have complete control over the project, you’re able to direct people to your personal site, you get to see all of the metrics on views and engagement, which you probably wouldn’t get if you gave it to someone else, and this would be one fewer instance of someone getting work for free.

 

  • 07:35 - Question #3: Can this person or company afford to pay you for this work? Are they making money off of your efforts?

    • Your time has value. Your current expertise has value. Just because you’re not where you ultimately want to be, that doesn’t mean that someone should make money off of you without compensating you.

    • So if you got the point where you answered question 1 that ‘yes, this would be a solid rung on my ladder to my goal,’ and ‘no, this wouldn’t work better as a passion project,’ then ask yourself what exactly are they gaining by receiving work from you.

    • Are you saving them money by building a dashboard that will streamline their process? Are you giving them interesting content to print in a magazine on the same page as a paid ad? If they’re making money because of your work, then you should ask to get paid. Or at the very least, get creative and ask for some kind of trade. Like in return you get an in-depth case study or testimonial, or a day with the editor to shadow the release process.

    • If they are technically saving money or making money off of you, BUT it’s for a cause that you’re really passionate about, then that might be a good reason to agree to work for exposure.

  • 09:45 - Sometimes taking on a few free projects to show that you can deliver can help get you to where you want to be. You can benefit from the exposure, experience, testimonials, and the relationships. But on the other hand, you can’t buy food with exposure, and it limits opportunities for people who really can’t afford to work for free.

 

  • 10:05 - My final takeaway is that while I don’t like the idea of people expecting work for free, there are cases where it could be a win-win. Just make sure you acknowledge that this should only be a short season, and that you are really thoughtful about the answers to these 3 questions:

1. Where does this fall on the ladder to your ideal job?

2. Could you turn this into a passion project for similar or better exposure?

3. Can they afford to pay you / are they making money off of your work?

  • 10:45 - I hope that these questions help you make a more informed decision in the future so you can protect your time and engage in projects that are truly a win-win.

  • 10:55 - Have you ever worked for free and it turned out great? Or really bad? Hit me up on Twitter or Instagram… I’d love to hear what happened.


Allison Torbanmini, free
Episode 23: How to Visualize Streaks for Pattern Analysis and Perspective - Featured Data Visualization by Frank Elavsky
 
 Frank Elavsky. ( Source )

Frank Elavsky. (Source)

 

Welcome to episode 23 of Data Viz Today. How can visualizing streaks in your data help you find patterns and gain perspective? Host Alli Torban dives into specific ways you can see your data in a new way by highlighting the period of time that something is happening - a streak! Featured data visualization by Frank Elavsky perfectly demonstrates how streaks are not only beautiful, but can also reveal patterns and new questions.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:55 - Today’s featured data viz project is called “Hot Streaks” by Frank Elavsky

  • 01:03 - Frank’s a data visualization specialist who collaborates with and trains researchers at Northwestern University.

  • 01:37 - He was connected to the researcher Dashun Wang (Professor at Kellogg School of Management at Northwestern) to create a data visualization for his recent research results on creative hot streaks - the idea that winning begets more winnings.

  • 02:00 - They looked at the careers of thousands of movie directors, artists and scientists and studied their hot streaks - the periods when someone’s performance was substantially better than their typical performance, this was determined by the top 3 IMdb score of movies for directors, the top 3 sales for artists and the 3 most cited publications for scientists.

  • 02:30 - Almost everyone experienced at least one hot streak during their career, and it usually lasted a few years, but there’s no way to determine when it’ll happen.

  • 02:45 - They wanted to create a viz that was beautiful and would captivate their audience, but also convey how ambitious the model and the datasets were.

  • 03:07 - Frank went through a very iterative process, doing about 40 different sketches before sending a few over to the research team for feedback.

  • 03:23 - He started to code one line represented each person’s career, and he stacked them on top of each other so they all had the same beginning and end point. He highlighted each hot streak in organge-gold colors (which was inspired by God of War concept art), but leaving it like this made it look like everyone had a hot streak that lasted their entire career.

  • 03:45 - Frank explained that it’s a result of perceptual biases that we have in our visual system: we see brightness as a visual feature much more readily than we see darkness.

  • 04:00 - So he knew that he had to sort the data meaningfully in order to make the design meaningful. He ended up using a sorting algorithm that he called “streak middle,” which finds the first time someone begins a hot streak and then the last time someone ends a hot streak. We then find the point in their career that is between these two, and sort based on that position, from people whose "streak-middle" was early-career to those whose streak-middle was late career.

  • 04:45 - This is what led to the final viz where you could start to see a pattern that suggested that directors tend to streak much earlier than Artists and Scientists, while Scientists seem to streak the latest. The viz was not only cool to look at, it actually raised new questions for the research team - why do people in certain careers tend to streak earlier in their careers? Can they build a model to explore this relationship?

  • 05:00 - Frank used javascript and d3.js for the final viz.

  • 05:30 - He said the hardest part though was that they had a very short window for completion, so he had to rapidly iterate and make a lot of decisions about which features to drop.

  • 06:25 - Other applications of streaks:

    • Sports - stack the football seasons for one team on top of each other and see if there’s a pattern to when your team has a winning or losing streak

    • Marketing - like streaks of high traffic to your website every week. Are there patterns throughout the year? If you’re looking to launch a product, maybe you want to time it with your longest streaks of heavy traffic.

    • Or visualize streaks in gambling, financial markets, video gaming, or tracking health related streaks like visualizing the days you go without smoking - is there a pattern in when your streaks occur or are broken?

    • Example about my podcast release day - I could visualize the hot streaks of downloads every week by stacking every week on top of each other, and visualize the 3 consecutive days with the highest number of downloads in every week, and see if there’s a pattern or general trend… Maybe my download streaks are actually over the weekend so it’d be better to release then to better fit your guy’s actual listening habits. If I felt like I needed to experiment with something like that, then first analyzing the pattern in my download streaks might be a good first step.

  • 08:20 - Inspired viz about putting recent rain streaks and rainfall in perspective for July in the D.C. area.

  • 09:10 - I downloaded the daily rainfall from 1948 to 2018 for the Reagan National weather station from the National Oceanic and Atmospheric Administration website

  • 09:24 - After I downloaded the data, I added a new column to represent streaks. I used an excel formula to count consecutive rain days, and then pulled my csv into tableau.

  • 09:36 - Andy Kriebel’s Visual Vocabulary with a bunch of useful charts that you can download!

  • 10:25 - I struggled with simply showing rain streaks and amount of rainfall. I’m still iterating!

  • 11:20 - You can immediately take away that there’s not really any pattern and that the recent rain streak was pretty long and heavy compared to past years but not the biggest.

My inspired viz. A work in progress. :)

 

  • 11:37 - So my final takeaway is that next time you have data over time, think about whether visualizing a hot streak could reveal any useful patterns or insight or give you a different perspective on your data. Line up your data with the same start and end points and stack em up!

  • 11:55 - Frank’s advice to newbie designers: learn to sketch out your data viz, and more importantly, consult with your audience - it’s the best way for you to know how effective your data viz is - you need to know how your intended audience is perceiving and understanding your message in order to make a really powerful data visualization.

  • 12:26 -Follow Frank on Twitter!

Have you ever created a streak data viz? Comment below! :)


Episode 22: [Mini] How My Design Process Has Improved Since Episode #1
 
 Photo by  Icons8 team  on  Unsplash

Photo by Icons8 team on Unsplash

 

Welcome to episode 22 of Data Viz Today. How has my data viz design process changed over the past 5 months? Well, it was pretty non-existent to start with, but after interviewing 20 top data viz designers, I've learned a lot and now have a much more defined design process. I want to share my process and would love to hear what yours is like so we can learn from each other!

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

design.png
  • Welcome! I'm Alli Torban.

  • 00:40 - Today’s topic: how my workflow has improved over the past almost 5 months of doing this podcast based on what I’ve learned from the designers that I’ve featured.

  • 00:50 - When I first started making data viz on purpose like a year ago, my workflow would go something like… have some data, put it in a chart whose type was determined by my whims, see if I could clutter it up with some color or complexity so it would be more interesting, add a data source at the bottom and done…

  • 01:15 - How are we supposed to know what makes a good data viz workflow? I learn the best by hearing real-life stories and hearing about one person’s experiences, so I wanted to share with you what my data viz process looks like now that I’ve been studying data viz designers and learning about their design process every week for the past almost 5 months. My hope is that it’ll provide some insight or inspiration for your workflow.

  • 02:10 - Here’s my workflow right now (assuming I already have a clean data set and I’m ready to start designing):

  • 02:20 - First step: I write my goal in one sentence, think about the balance I want to strike between attention/beauty, understanding, implication. And write out some descriptive words and motivations of my audience. Referenced: Episode 1 and 6.

  • 03:20 - Second step: Exploring different chart types based on my data. Diagrams that I use: Chart Choosing Diagram by Andrew Abela and data-to-viz website. Then sketch out different options. Referenced: Episode 4

  • 05:03 - Third step: recreate my sketch in a tool/software using a basic chart type. Referenced: Episode 12

  • 05:30 - Fourth step: Add design elements/creativity to try to humanize the data and connect my audience to my story. I use color (Viz Palette tool), visual metaphor, etc. Referenced: Episode 5, 9, 14

  • 07:15 - Fifth step: I add the annotation layer that has a clear visual hierarchy and simplify the viz. Referenced: Episode 7

  • 08:20 - Sixth step: Seek feedback from others. Referenced: Episode 10, 21

  • 10:00 - Seventh step: Step away to get perspective. Referenced: Episode 19

  • 10:21 - There is it! Clearly define my goal, the needs of my audience, explore my chart options based on my data, sketch, make a clear, basic chart, then think about adding creativity and engagement through things like color or visual metaphor as necessary, add my annotation layer, seek feedback, iterate.

  • 10:45 - I fully expect that I’ll be slowly refining and improving this workflow over the next 5 months as well!


Episode 21: How to Gain Insights by Identifying Intervals in Your Line Chart - Featured Data Visualization by Ben Jones
 
 Ben Jones. Image via  LinkedIn .

Ben Jones. Image via LinkedIn.

 

Welcome to episode 21 of Data Viz Today. How can segmenting your line chart into intervals help you gain insights into your data? Host Alli Torban dives into specific ways you can visually break up your line chart into intervals as a way to quickly see your data from a different perspective. Example questions you could answer: Which marketing campaign had the greatest effect on sales? Does varying the basketball shot clock length change how many points are scored? Featured data visualization by Ben Jones perfectly models how this technique can visually communicate a relationship between two metrics.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

"Monthly US Unemployment Rate by Presidential Term" by Ben Jones

  • Welcome! I'm Alli Torban.

  • 00:25 - Today’s episode is about visually breaking up your line chart into intervals to help see how your metric’s variation coincides with something else, so that you can gain insights and possibly take action. What are some examples where this would be helpful and how can you create your own?

  • 01:20 - Today’s featured data viz project is called “Monthly US Unemployment Rate by Presidential Term” by Ben Jones. Ben is a technical evangelism director for Tableau Software and teaches data visualization at the University of Washington.

  • 01:55 - Ben created his viz because he noticed that Political leaders often claim credit or assign blame for economic indicators, such as the seasonally adjusted unemployment rate, but he wanted to understand how this particular indicator has changed over time in the United States, relative to the presidential administrations that have coincided with the periodic swings. His goal was to plot the unemployment rate over time, and see how the presidential terms coincided with rise and fall of the unemployment rate.

  • 02:25 - Ben grabbed the unemployment rate from the Bureau of Labor and Statistics website. He added columns for president and party.

  • 02:50 - He used Tableau, and visually showed us the presidential intervals by using color, vertical lines, and labels at the top.

  • 04:30 - You can quickly look at this chart and visually comprehend how the presidential terms coincided with rise and fall of the unemployment rate, which was Ben’s goal.

  • 05:15 - Lots of use cases for plotting metrics over time and identifying intervals of change in power or leadership, like Ben did, whether it’s the president, or the CEO of a company.

  • 05:28 - You could also use it build a viz that will help you visually understand the impact of different marketing campaigns on a metric that’s important to you. Great way to visually assess periods of experimentation.

  • 06:15 - Other examples could be plotting sales and visually identify intervals where there was a tariff in place or not.

  • 06:26 - Or in sports, you can plot a particular metric and visually identify intervals where different rules were in place to see if that rule might have been affecting the game in some way.

  • 06:40 - My inspired viz: Showing the average points per game in Men’s College Basketball in the ACC from 1977 to 2017 and identifying the intervals by what kind of shot clock was in place at that time.

  • 07:25 - My goal was to plot the average points per game over time, and see how the change in the length of the shot clock coincided with the rise and fall of the scores. I used Tableau. See it here:

My inspired viz.

  • 09:35 - Final takeaway is that you can visually break up your line chart into intervals to help see how your metric’s variation coincides with something else. Then when you add small things like coloring the line by which interval it’s in, adding vertical markers, labeling each interval at the top and in the same color, and even adding trend lines or average lines, and then you have a powerful tool to assess what’s going on.

  • 10:15 - Listen for Ben’s 8 tips for data viz newbies!

  • 11:15 - Follow Ben on Twitter! @dataremixed

  • 11:42 - Get mapping right away with my free-mini course “Make Your First Custom Map in Under 30 Minutes”.


Episode 20: How to Use Isochrone Maps for Art or Advanced Analysis - Featured Data Viz by Topi Tjukanov
 
 Topi Tjukanov. Image via  Twitter .

Topi Tjukanov. Image via Twitter.

 

Welcome to episode 20 of Data Viz Today. What are isochrone maps and how can you use them for advanced analysis or data art? Host Alli Torban dives into specific ways you can create and use isochrones for personal or work challenges. Featured data visualization project by Topi Tjukanov perfectly models how isochrones can bring out interesting insights.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

  • Welcome! I'm Alli Torban.

  • 00:25 - Today’s episode is all about isochrones! What they are and how you can use them for some interesting analysis and beautiful data art. The word isochrone comes from the Greek isos meaning equal and chrono meaning time. Equal time. It’s a line on a diagram or map connecting points relating to the same time or equal times. The useful aspect of isochrones is that the travel times are realistic because it takes into account where the roads are and even traffic conditions.

  • 01:40 - Today’s featured data viz project is called “Urban Forms” by Topi Tjukanov.

  • 02:40 - The first known isochronic map was created by Francis Galton in 1881.

  • 02:50 - So how do you make an isochrone map anyway? Mark your starting point, map out every possible route leaving that point, and then think about your assumptions - how fast are you traveling, and what’s the maximum amount of time that you want to travel. Then for every route, you use the classic formula: distance = rate * time. Solve for distance, and then you can mark a point on the map at the distance you can go when you’re going a certain speed for a certain amount of time. And you repeat that for every possible route. Connect all those points and you have a polygon around your starting point that shows how far you can travel in every direction during that amount of time.

  • 03:30 - As you can imagine, this is really labor intensive, but now there are  APIs you can use that can quickly grab all that route and travel distance information for you.

  • 03:40 - When Topi came across the HERE.com API and a python tutorial on how to convert the coordinates to polygons, he decided to try the code out for himself and experiment with what the different isochrone polygons looked like for different cities.

  • 04:15 - The Python scripts that can be run inside the QGIS Python Console.

  • 04:45 - He dropped starting points in 20 different european cities and ran generated 144 isochrones for each city - one for every 10 minutes during a 24 hour period and over-layed all those isochrones on top of each other so that you can get a realistic view of how far you can go in each city in an hour by car no matter what the traffic is like.

  • 06:15 - It’s fun thinking about the transportation infrastructure of the city that’s causing these different shapes, or the natural features like oceans, lakes, mountains that also affect the shape. It’s like a fingerprint for the city.

  • 06:55 - What are some ways you can use isochrones for geospatial analysis?

    1. You can do two isochrones - one around your work and another around your partner’s work and see where they overlap so you can find a home that’s in an area where you both have suitable commutes.

    2. Or you can map out potential store locations within a city and try to minimize the overlap of the isochrones around each location so your store locations cover as much of the city as possible.

    3. What kind of foot traffic can we expect for a store, at this location? What kind of delivery coverage can we offer? Where are our competitor’s delivery holes that we could fill.

    4. How many homes can a firehouse serve within a 10-minute drive?

    5. Where should we put each firehouse so that there’s a firehouse within 5 minutes of every house?

    6. Which workers are within a 15 minute drive of this outage?

    7. How far could this stolen vehicle have gotten by now?

    8. If we put a bus stop there, how many riders will live within a 5-minute walk?

    9. It’s also used to show how long it takes for runoff water within a drainage basin to reach a lake or outlet.

    10. Chris Slatt used an isochrone map to show how much time it took for residents in different parts of a Maryland city to take public transit to jury duty and showed that more than half wouldn’t be able to make it to the courthouse by the time it opens in the morning.

  • 08:40 - How do you generate an isochrone?

    1. Carto

    2. ARCGIS Online

    3. Mapbox isochrone plugin

    4. Google API

    5. HERE.com API

    6. TravelTime Platform by iGeolise

    7. Demo to try

  • 09:45 - My inspired viz - I used isochrones for analysis for an article that I wrote for a local magazine to see how much extra it costs to buy a house that’s within a 10 minute walk of a metro station compared to the rest of the city.

Example of my isochrone analysis of home prices around metro stations. Article about results.

 

  • 10:30 - My final takeaway is that isochrones are a super cool tool for art and analysis - and now there are more and more ways that for everyone to take advantage of them. Take a page out of Topi’s book and experiment with it a little, maybe make some data art with it, and then you’ll know how to do it when it comes time to use it!

  • 11:15 - Check out Topi’s website and follow him on Twitter!

  • 11:35 - Get mapping right away with my free-mini course “Make Your First Custom Map in Under 30 Minutes”.


Episode 19: [Mini] How to See Your Data Viz With Fresh Eyes
 
 Photo by  Bud Helisson  on  Unsplash

Photo by Bud Helisson on Unsplash

 

Welcome to episode 19 of Data Viz Today. How can you see your data viz with fresh eyes? Host Alli Torban dives into specific ways you can view your work from a new perspective when you're short on time!

  • Welcome! I'm Alli Torban.

  • 00:45 - This week’s mini-episode is about how you can hack the “fresh-eyes effect” and see your data viz from a new perspective immediately!

  • 01:25 - I put together a list of 5 of my favorite ways to quickly see your data viz from a new perspective. Here we go.

    1. Read it out loud. Read your title and accompanying text or annotations out loud. When you pull it outside of your head, the main message of your viz can feel different. Or, even better, record yourself reading it and then play it back with your eyes closed - and focus on what your words are making you envision.

    2. Print it out. You can print out your viz in a few slightly altered ways to give yourself a new perspective. Like, you can print it in black and white, or print it on a smaller scale. Then you can do other things with it like hold it up to a mirror or turn it upside down. Think about what stands out to you in your viz when looking at it in these different ways?

    3. Change your scenery. Try to re-read your assignment or goal and then grab your print out and look it over while you’re walking or ideally outside. Changing your physical location can help get you out of all the minutiae of designing your viz and help you see it from the perspective of someone who’s looking to learn something. Think about whether you’re clearly communicating your main point and desired action?

    4. Imagine the best compliment. Think about the moment you send your viz to your client or boss. What is the most meaningful compliment you could receive about your viz? Are you hoping to hear something like “this viz is so engaging!” or “wow, we really need to take action” or “this is beautifully designed” - think about the compliment you’d want to receive the most, and that can help you re-frame how you’re seeing your viz. Ask yourself if your viz offers enough to be complimented in that specific way.

    5. Pretend to start over. Imagine that you just lost all of your work and you need to quickly recreate the viz in one sketch. You can think about your specific assignment or goal again, and then sketch out on a piece of paper a viz that solves that problem. I find that I sometimes go in a particular direction when creating a viz for whatever reason, and with this exercise, I get the chance to re-make the decisions that I made at the beginning, which can help alert me to problems or give me a new idea. So try to recreate your viz with a quick sketch with your final goal in mind, and notice if you’re drawn to creating anything differently.

    6. BONUS tip: Ask someone else. This one is obvious but worth mentioning - you can try to use someone else’s fresh eyes - give it to someone else and let them look at it for an appropriate amount of time (like if your goal is for someone to understand something quickly, then give them a handful of seconds, but if your viz is meant to be more exploratory, give them more time), and then ask them what they took away from the viz. If they seemed to miss the mark, maybe there’s something you could change to help.

  • 04:50 - My final takeaway is that real, true fresh eyes are the best way to give you some perspective on your data viz, but if you’re short on time, there are a few ways to hack it - you can read it out loud, print it out, change your scenery, think about your most desired compliment, or sketch out a redo.

  • 05:30 - Nominate a data viz to be featured on the show!

  • P.S. Get mapping right away with my free-mini course “Make Your First Custom Map in Under 30 Minutes”.


Episode 18: How to Start a Passion Project That Hones Your Skills & Opens New Doors - Featured Data Viz by Amy Cesal
 
  Amy Cesal . Image via Amy.

Amy Cesal. Image via Amy.

 

Welcome to episode 18 of Data Viz Today. How can you start your own data viz passion project that hones your skills and opens the door to new opportunities? Host Alli Torban dives into specific ways you can find and execute a passion project that brings you joy and growth. Featured data visualization project by Amy Cesal perfectly models how a passion project can be fun, bring new opportunities, and grow your skills!

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

 "Day Doh Viz" project by Amy Cesal. Image via her  website .

"Day Doh Viz" project by Amy Cesal. Image via her website.

  • Welcome! I'm Alli Torban.

  • 00:25 - This week’s episode is about how you can start a passion project that brings you happiness, hones your data viz skills, builds your portfolio and opens new doors.

  • 01:00 - Check out artist Heidi Horchler’s Instagram - she’s creating a watercolor version of my cover art, which came from her passion project.

  • 01:35 - Featured data viz called “Day Doh Viz” by Amy Cesal.

  • 01:40 - Amy is a graphic designer who specializes in data visualization.

  • 02:00 - Amy wanted to do a 100-day project that included data viz, 3-D objects, and was away from the computer.

  • 02:35 - She thought about her nostalgia around play-doh, so she decided to create a data viz made out of play-doh every day.

  • 03:00 - Her 100-day project’s goals:

    1. Get away from the computer and create more data visualizations for fun.

    2. Expand her network on social media - reaching and interacting with more people.

    3. Highlight data that she found interesting - mostly around personal finance.

  • 03:40 - Lessons learned: creating a play-doh viz every day was too cumbersome for her schedule so she scaled back to a few a week.

  • 04:15 - Skills learned: improved data collection and cleaning, how to use a clay extruder gun, photography, lighting, social media, copywriting, and kicking her perfectionism.

  • 05:15 - Has she achieved her goals? She’s had fun, moved away from the computer screen, gained hundreds of twitter followers, inspired teachers and others to explore play-doh vizzes, was asked to write guest blog posts for prominent blogs, more clearly defined her creative point of view, and it has given her more confidence.

  • 06:15 - How can you get started with your own passion project?

    1. Write a list of skills you want to improve upon or want to show off.

    2. Write another list of your unique experiences, things you’re passionate about, and things that bring out emotion in you (nostalgia, joy, anger, frustration).

    3. Combine things from both of these lists, think about the experience you want to have when doing this project, which will help lead you to the right project.

    4. Then write out what success looks like to you.

    5. Start creating and sharing!

    6. Or base you passion project on your dream job! If you want to be a data journalist for a big news outlet, pick items from your “passion” list and create vizzes in the style of that news outlet so you end up with a portfolio that has your point of view that looks like it’s already apart of their team.

  • 07:45 - Be open to tweaking the project if it’s not fun or achieving your goals.

  • 08:00 - THIS podcast is my passion project! Listen for my story.

  • 10:30 - I created a new passion project by going through the exercise above - listing out skills I wanted to improve and things that I care about.

  • 10:45 - It’s “Mini Data Reporter” - brings together my desire to improve children’s data literacy, serve the low-vision community, and improve my design skills. It’s a one-page assignments that leads kindergarten-aged kids.

  • 11:30 - My goal is to have these fun assignments for my daughter and I to do together, allow other low-vision kids/parents to use these worksheets to have fun learning data literacy, and improve my design/formatting skills.

 My passion project.

My passion project.

  • 12:00 - My final takeaway is that I really believe that growth brings happiness, and of course it’s possible to grow within your day job, but a passion project allows you to grow in ways that you choose while also having fun.

    1. Write a list of things that are unique to you, things that bring out an emotion in you, and skills that you’re looking to improve or show off. Combine these things, talk to your family and friends about it, and you will think of something fun to try. Then wrap some constraints around it and share what you create.

    2. The worst thing that can happen is that you discover something that you don’t actually like to do and you try another idea! The best that can happen is that you learn a new skill, connect with like minded people, build your portfolio and find new opportunities.

    3. Give it a try and tag me on twitter or instagram with your passion project because I’d love to see it and share it!

  • 12:45 - Amy’s advice to designers just starting a passion project: just do it, create something every day and let go of perfectionism.

  • 13:10 - Follow Amy on Twitter and check out her website! Thanks, Amy!

Get mapping right away with my free-mini course “Make Your First Custom Map in Under 30 Minutes”.


Episode 17: 3 Ways to Amp-Up Your Scatter Plot! Featured Data Viz by Maarten Lambrechts
 
 Maarten Lambrechts. Image via his  Twitter .

Maarten Lambrechts. Image via his Twitter.

 

Welcome to episode 17 of Data Viz Today. How can you take your scatter plot to the next level? Host Alli Torban dives into 3 ways you can layer onto a scatter plot to enhance your reader’s understanding of the data.

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

 "Lazy MP's" by Maarten Lambrechts. Image via his  website .

"Lazy MP's" by Maarten Lambrechts. Image via his website.

  • Welcome! I'm Alli Torban.

  • 01:00 - This week’s episode is about 3 things that you can layer onto a scatter plot to enhance your reader’s understanding of the data.

  • 01:15 - Check out artist Heidi Horchler’s Instagram - she’s creating a watercolor version of my cover art!

  • 02:00 - Today’s featured viz is called Lazy MP’s by Maarten Lambrechts. Maarten is a freelance data journalist and visualization consultant from Belgium.

  • 02:30 - He began this project because as a data journalist, he wanted to visualize who the lazy MP’s are in the Flemish Parliament.

  • 03:20 - He scraped the data on the Parliament’s website using R script.

  • 04:00 - He needed to pitch the story to his editors and thought a visual would help sell the story so he decided to use a scatter plot since he’s comparing two variables to see if there were any trends.

  • 04:38 - He used ggplot2 in R to create the initial scatter plot and in order to help readers quickly orient themselves to where each MP fell in relation to their colleagues, Maarten added a line to represent the Median for the x-axis and another Median line for the y-axis. The median is so easy for people to understand in a scatter plot - half the dots are above and half the dots are below. This is #1 on my list of 3 ways to amp-up your scatter plot - add lines that help orient your reader quickly - this can be median lines like in this case, or a trend line so readers can quickly see what kind of correlation there might be, or you can add a line that’s specific for your data - like here’s a line representing minimum wage, and then you can easily identify the dots below or above that line.

  • 05:35 - #2 - after Maarten added the Median lines, he then labeled each quadrant. So the bottom top right quadrant was called the busy bees (they had lots of documents filed, lots of things said), then there were the silent forces (lots of documents, few things said), the talkers (few documents, lots of talking) and, of course, the lazy MP's (few documents, few things said). Labeling the quadrants in a way that basically sums up what the implication is of being in that position. I feel like it’s such a smart way to assist your reader with interpreting the chart.

  • 06:25 - Another layer that Maarten added to this scatter plot was his use of color to introduce a third variable, which was which party the MP is a part of. This is #3 on ways to amp-up your scatter plot - using color, size or small multiples to represent a third variable. Be careful adding a fourth variable - that could get a little complicated, and in the book Data Points by Nathan Yau, he suggests using color and size to represent the same third variable so it’s a redundant encoding to really drive home the point. Maarten used small multiples to show the party in another way.

  • 07:45 - The whole process, from scraping to the visualisation was done in R (scraping with Rvest, visualising with ggplot2). Final touches for print were done in Illustrator.

  • 08:18 - So what are the three ways you can amp up your scatter plot?

  • 1. Add lines to help orient your reader to your data - this can be median lines, trend lines, or specific values that matter to your story

  • 2. Name the quadrants - this helps your reader interpret the scatter plot quickly and understand the implications of a point being in a certain position.

  • 3. Add a third variable by using color, size or small multiples - this helps your reader parse through the points a bit better to really understand the story. Just be careful not to encode too much - using color, size or small multiples on the same variable can be a good thing - the redundancy can be helpful to your reader.

  • 09:00 - Maarten’s advice to designers just starting out - Although reading some books about data visualisation obviously helps to learn the basics and get inspired, the most important thing to start with visualisation is just making visualisations. Grab a visualisation you like and try to plug in your own data, or try to remake it with the tool of your choice. What can also be very helpful is getting feedback on your work. Not only from people from the data visualisation community, but also from people with no background in visualisation. It can be really insightful to hear what others see in your work, and what they don't see.

  • 09:40 - If you want to see more of Maarten’s work check out how website www.maartenlambrechts.com and follow him on twitter at @maartenzam

  • 10:10 -  Get mapping right away with my free-mini course “Make Your First Custom Map in Under 30 Minutes”.


Episode 16: How to Persuade & Set Goals Using Simulations - Featured Data Viz by Gabrielle LaMarr LeMee
 
 Gabrielle LaMarr LeMee. Image via her  LinkedIn .

Gabrielle LaMarr LeMee. Image via her LinkedIn.

 

Welcome to episode 16 of Data Viz Today. How can visualizations help people make decisions and set goals? Use a simulation/what-if analysis and visualize the results! Host Alli Torban dives into why simulations are so powerful in persuading people and how to know if your client could benefit from a what-if visualization!

Listen on Apple Podcasts, Google PlayStitcher, SoundCloud & Spotify.

 "Educate Your Child" by Gabrielle LaMarr LeMee. Image via her  website .

"Educate Your Child" by Gabrielle LaMarr LeMee. Image via her website.

  • Welcome! I'm Alli Torban.

  • 01:15 - Check out artist Heidi Horchler’s work at daydreamodyssey.com and follow her on Instagram!

  • 01:30 - Follow #SoDS18 on Twitter for Summer of Data Science goal inspiration! Renee’s blog post about setting goals.

  • 02:15 - Today’s inspired viz “Educate Your Child” by Gabrielle LaMarr LeMee

  • 02:45 - The purpose of her thesis was to explore patterns of segregation in the Chicago school system in order to highlight the systemic and individual choices that create and maintain the problem.

  • 03:15 - Data used: Census data and Chicago Public Schools Data

  • 03:45 - Used R and ArcMap to analyze the data

  • 04:00 - The simulation was first a board game

  • 04:15 - Inspired by Spent interactive simulation

  • 04:25 - Final visualization coded in D3

  • 04:40 - Describing the viz. See it here.

  • 06:15 - She really used the “near-view” by making this simulation about one individual child

  • 06:50 - Benefits of simulations/what-if analysis: no risk, can assess the weaknesses and opportunities quickly, and when you can visualize opportunities, it makes it so much easier to make decisions and to set goals.

  • 07:10 - What do you need to create a what-if analysis? Decide on the factors that you want to vary, the factors you want to see affected, and the formula that combines these factors

  • 07:50 - Examples of what-if analysis: forecasting sales, assessing the impact of increased minimum wage, home buying affordability.

  • 08:55 - What kinds of things should you listen for that would hint that a simulation/what-if analysis would be useful? If you hear a lot of “what if we do this…”, if there’s a big change coming or if you want to propose your own big change, or if you’re in a siutation where it’s impossible or difficult for people to experience someone else’s point of view, or if people are having the same conversation over and over!

  • 09:50 - My inspired viz gives you the opportunity to change various inputs and see how expensive of a house you can afford and when. *I’m not a financial planner - This is for demonstration purposes only. :) Interact with it here.