VizWiz

Tableau Public is the heart and soul of Tableau. Tableau Public is THE BOND that holds the Community together. Tableau Public is THE PLATFORM for sharing our work. Tableau Public is THE SOURCE for getting inspiration from others.

Without Tableau Public, learning, sharing, and exploring would be significantly more challenging.

Without Tableau Public, there would be no Makeover Monday. There would be no Makeover Monday book. There would be far less people improving their skills week by week. There would be far less engagement within in the Community. The thousands of people that have participated, never would have engaged. If there was no Tableau Public, would these people have ever found Tableau?

Without Tableau Public there would be no Viz for Social Good. There would be no Workout Wednesday. There would be no Sports Viz Sunday. Without Tableau Public there would be far fewer people practicing data visualization and data analysis week after week through these Community projects.

Without Tableau Public there would far fewer friendships born out of a common love for data. There would be far fewer people finding the careers they love.

Without Tableau Public, would there be a Tableau Community?

Picture this: you've purchased a new office and need to hire a designer to help you make the space yours. How would you go about hiring this person? Would you scan LinkedIn and look for people with the title "Interior Designer" or look for people that went to design school? Of course you wouldn't. You would ask to see their portfolio. Imagine a designer coming in to meet you and not bringing a portfolio of their work. Would you hire them? Of course not. You're interested in WHAT they've done, not where they went to school. Their portfolio IS their CV.

From a Tableau perspective, Tableau Public is the new CV. The secret to hiring people that are great at Tableau is to look at their Tableau Public profiles. If someone doesn't have a Tableau Public profile, don't hire them. Those people, more often than not, don't understand the ethos of the Tableau Community. And if they aren't part of the Community, I would seriously question their skills. How can you evaluate their work if they don't have a portfolio? Simple...you can't!

Eva and I have been asking people to tell us how Makeover Monday has helped them get a job they love. Person after person has told us that their Tableau Public profile was the major differentiator for them getting the job. People have been able to DEMONSTRATE their work, live in front of those interviewing them. They've been able to prove they have the skills needed for the role. Those companies may have asked for a CV, but what really mattered to them was WHAT people have done.

Through Tableau Public, you can see the progression of someone's skills. You want to look for people that have clearly shown improvement. Without Tableau Public, how would any of these people have been able to show their progression?

DEVELOPING SKILLS

Let's have a look at Stephen's viz:

• It's simple and easy to understand.
• Nice and clean; there's no unnecessary decoration
• Using colors that represent the parties
• Using a line chart to represent change over time
• Labeling the end point makes us aware of the current situation

• The stepped lines are necessary.
• The ratio of the chart looks strange to me.
• The title could be more impactful.
• Adding a y-axis would add context.

• Focus on the % of women and men in each party
• Use the party colors, but still be able to distinguish men and women
• Use a line to break up the area chart
• Use an impactful title and subtitle
• Use a viz in tooltip to show BANs

With that, here's my Makeover Monday for week 42. Click on the image for the interactive version:

1. Creating the small multiples layout
2. Limiting the data to 2017/2018. I chose to do this via a data source filter so that I didn't have to worry about adding the date field as a filter and add it to context.
3. Creating the line chart
4. Formatting the axis properly
5. Creating the calculation needed for the shading (I approached it by doing one of the top calculations, then one of the bottom calculations, then the combined)
6. Creating the total sales text at the top-center of the chart

1. I knew I had to calculation right for the label for the latest month, but for the life of me I couldn't get it working. I felt like I needed another axis for the mark, then it dawned on me like a slap in the face how simple the solution is.

Here's a gif of the working solution. Click on the gif for the interactive version.

• Simple title that explains what the viz is about
• Cancer types are sorted from highest to lowest based on the five-year survival rate
• "All cancers" is sorted at the top since it's the overall statistic
• Using arrows to indicate improving or declining
• Using different colored dots for each time period
• Including an explanation for how the data came about

• The subtitle is long. I had to read it a couple times to understand it.
• The viz overall feels kind of busy.
• By using directional arrows, the change over time is lost. The change isn't linear, but the design could be interpreted that way.
• Color the arrows by increasing or decreasing. Uterus and Cervix Uteri cancer survival rates have decreased, but that could easily be missed.

• Incorporatde the change over time
• Used BANs for the first period and the last period measured and the difference
• Used a big dot to indicate a reduction in survival rate
• Used row banding to guide the eye from left to right (taking a lesson from last week's Workout Wednesday)
• Provided an option to filter by race and gender
• Used a set to split the view into the top 9 on the left and the rest on the right; my first version was one long viz, but I didn't like how I had to scroll.
• Used reference bands vertically and horizontally to give the labels space on the ends of the lines

Click on the image below for the interactive version.

Really good challenge. I particularly enjoy the workouts that have practical use cases for every day work. Thanks Luke for the challenge!

For the chart:

1. I used an area chart on one axis.
2. I used a line chart on the other axis.
3. I used an ascii ● as a label on each mark on the line. This has to be centered vertically and horizontally for it to appear in the correct place for each month.
4. For the vertical label, I used this knowledge base article to add a line break after each letter. Since there are 8 letters max, my formula has 8 lines and then I trim the text.

I'm sure there's a better way to do the vertical labels using the length of the string, but this works. In programming, I'd use a WHILE loop. Thanks Rody!

• Using a line chart makes it easy to see the rising price.
• The title, while simple, tells us what the chart is about.
• The subtitle provides context.

• There's no indication of the currency. The article mentions both US and Mexico as main sources, but the chart doesn't indicate whether it's dollars or pesos.
• The avocado in the background is distracting and completely unnecessary.
• If the avocado is removed, the line could be made black.
• Labeling the ends of the lines would add context.
• The title could be changed to something that tells the story in the data.
• Is this good or bad? Rising prices could be good if you're the produce, but bad for consumers.
• The gridlines could be more subtle.

• I wanted to create something that shows the trends for each city plus the overall.
• Simplify the colors.
• Include BANs for the current price and an indicator of the change.
• Create "cards" for each region, similar to the profit and loss statement I created.
• Include a mobile version

• The colors are easy to distinguish.
• The footnotes help to explain the percentages...sort of.
• The chart layouts are easy to understand. Bar charts nearly always work well.
• Labeling the top of each bar removes the need for an axis.
• Good drill down from the overall to the per region level.

• I find the chart titles quite confusing.
• Comparisons within a single region are difficult.
• I had no idea how to read these charts without reading the article. A chart should, ideally, be able to stand on its own.

• I focused on making over the bottom chart.
• I kept the original colors.
• I changed the bars to dots to help show the range of responses better.
• I didn't convert the responses to percentages as I wasn't confident it was accurate.
• I included a sorting option to allow sorting by the total responses or the responses within a region.
• Based on a twitter conversation with Dan Caroli last week, I turned on advanced logging feature which tracks each change you make in a sheet and then I turned them into this gif.

• Simple title and subtitle that explain what the viz is about
• Line colors are easy to distinguish
• Good small multiples layout
• Reversing the time scale so that the larger number is to the last since it represents more days in the past
• Making the obvious
• Sorting the routes by distance

• Reduce the font size for additional information like the footnote and the source
• Move the subtitle closer to the title and add space between the subtitle and the first chart
• Label the ends of the lines

I don't mind the original too much other than I feel like it's missing some context. I decided to basically recreate the chart, but show the change in price as the days got closer. For me, this helped show how much more expensive tickets will be if you wait until the last minute.

According to UC Berkley, learning is a process that:

As an example, I am actively look for reasons to practice features in the Tableau 2018.3 beta, especially around density mapping. I was reading an article this morning about Clayton Kershaw, whom many consider the best pitcher in Major League Baseball. He also has highest base salary at $33M for 2018.

Most of the density maps I've seen have had a mapping component. In the case of baseball, and pitching in particular, the spatial zone is the strike zone. Data is easily accessible to get the coordinates of every pitch as it crosses home plate.

For this project, the learning process:

1. is active in that I am building my knowledge as I explore the data set and learn the new features.
2. builds on my prior knowledge of how the feature works and my knowledge of the game of baseball. However, I had never done a scatterplot of pitching before, so I had to learn new terminology in the data. This knowledge will help me be more productive and learn faster in the future.
3. is situated in the authentic context of engaging with the ideas and visual concepts that I saw online and drew on paper.
4. required my motivation and engagement to see the project through to fruition and the persistent to make the display visually accurate.

I hope my thought process helps you focus your learning. I love helping people get better at what they do and if I can help you speed up your learning, then we'll all be better for it.

With that in mind, here are two images I created for this project. The first is all pitches by Kershaw and the second is of his curveballs, which is known to be his most potent pitch. Once Tableau Public supports Tableau 2018.3, I'll publish them and include links on the images.

• Colors are easy to distinguish
• Good interactivity for additional information
• Filter options are obvious and easy to use
• Sizing the blocks gives you relative comparisons
• Good use of annotations
• Stacking the blocks makes it obvious there were more records in one month versus another

• Using size for the blocks makes exact comparisons difficult
• Include a title
• Include a subtitle with additional context
• Provides the user the ability to ask "How does this affect me?"

• I explored the data quite a bit, before focusing on Washington. I did this because I saw a large increase in spending after Trump was elected.
• Use simple colors like the original
• Compare spending during the Campaign vs since Trump has been President
• Use BANs to call out the import information

With that, here's my viz for Makeover Monday week 37:

• The summary card on the right is packed full of information and as you zoom, you get different levels of detail.
• Keeping the map a single color allows you to focus on where the factories are located.
• Excellent interactivity
• Overall, everything is simple and clean.

• Adding some filtering capabilities
• Make it easier to identify the smaller countries, possibly by outlining the countries with a white border.

• Mimic the style of the cards with its BANs
• Make some of the importion that's buried deeper in the map more evident
• Use Nike official colors
• Add some simple interactivity through actions

This is a pretty simple viz this week and I really enjoyed making it. It's almost like a report card.