Data Viz Done Right

February 13, 2019

Tableau Tip Tuesday: How to Convert a Reference Line into a Table Calculation

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In this tip, I show you how a reference line is merely a table calculation that Tableau makes easy for you. I'll show you how to write any reference line as a table calc for use later.

February 12, 2019

Makeover Monday: When did President Trump spend the most Executive Time?

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I've already written about what works and what doesn't about the original visualization (read it here) and since the two current The Data School cohorts had to create a Makeover Monday viz in an hour, I thought I should do the same.

I wanted to create a calendar view that only show the Executive Time. It's easy enough to filter to just that data, however, there are days when there was no executive time, which led to holes in the calendar. To overcome this, I created an Excel spreadsheet with every day from 1 December 2018 through 31 January 2019, then I joined the two data sets, ensuring that my Excel spreadsheet was the primary data source so that all dates would be in the data set (in other words, NOT an inner join).

From there, creating the calendar was simple, adding the color was simple. I spent most of my time fiddling with the formatting.

Click on the image below for the interactive version.

February 11, 2019

Makeover Monday: How President Trump Spends His Executive Time

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Axios published a fascinating article and data set last week with details of President Trump's hourly schedule. To say "Executive Time" is a major part of his day would be a gross understatement. The article doesn't give any specifics about how that time is actually spent, however it does provide some interesting insight:

  • Trump usually spends the first 5 hours of the day in Executive Time.
  • He spends his mornings in the residence, watching TV, reading the papers, and responding to what he sees and reads by phoning aides, members of Congress, friends, administration officials and informal advisers.
  • Trump doesn't take an intelligence briefing until 11am or 11:30am, and they only last 30 minutes.

The list, sadly, goes on. The viz they posted that we're making over this week is this simple stacked bar chart.

What works well?

  • Using a color that stands out over the others to highlight executive time
  • The title tells me what the viz is about.
  • The subtitle provides context as to the amount of data that the chart summarizes.
  • Simple labeling
  • Including the total time at the bottom and stretching the lines to the ends of the stacked bar chart

What could be improved?

  • It's hard to compare the executive time to all other time. A percentage would be helpful.
  • Would the stacked chart be better as a horizontal bar chart with two rows?

What I did

  • I wanted to look at the frequency of executive time by hour of day and day of week. Does Trump spend the same amount of executive time each day?
    RESULT: The first couple heatmaps looked terrible, but visualizing by weekday looks ok.
  • Do big numbers help tell the story in the data?
    RESULT: Yes, they help summarize the data well, but didn't help my end product.
  • Are there any trends in the data? That is, is executive time increasing or decreasing? Or has it been consistent?
    RESULT: The trends are not very useful.

In the end, I thought visualizing the data as stacked bar charts by weekday looked the best. I built quite a few charts that turned out completely useless. However, there comes a point when something is good enough. That's where I ended up. Click on the image below for the interactive version.

February 6, 2019

Hospital Closures in Rural America

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Today is my first time participating in Lindsay Betzendahl's great collaboration project #ProjectHealthViz. She first told me about back at TC and I told her I would participate when time permitted. So here I am, participating for the first time.

The data set Lindsay posted was about hospital closures in rural parts of America. My mind immediately went to poverty in the South (I wasn't too far off), access to medical care, and the cost of healthcare.

After exploring the data and getting feedback from Lindsay, I settled on a simple story that answers  few simple questions:

  1. How many hospitals have closed?
  2. How many beds are no longer available?
  3. How many people are impacted (I added data from the US Census)?
  4. How many hospital bed days have been lost?

In the end, this is a pretty simple viz that I hope communicates the message well. In my opinion, access to healthcare should be a right, not a privilege. Click on the image for the interactive version.

February 3, 2019

Makeover Monday: How Chinese New Year Compares With Thanksgiving

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This week, Eva chosen another viz from Statista, this time the chart attempts to compare Chinese New Year with Thanksgiving in the U.S.

What works well?

  • Good title and subtitle
  • Using colors that are easy to distinguish from each other
  • Including the numbers to give the circles context

What could be improved?

  • Comparing circles is very difficult; what are we to compare? The size? The diameter? Either way, it's very difficult.
  • Remove the background image
  • Make the numbers comparable. China's population with way bigger than the US. Converting them to per capita would make for better comparisons.

What did I do

  • Transposed the data so that I had a column for each measure
  • Create per capita calculations for each measure
  • The trips and spending data looked like the most interesting, do I discarded the viewership data since that really has nothing to do with the other data.
  • Changed the circles to simple bar charts
  • Made the titles of the charts state the message of the chart