Case Study: The Bitcoin Economy

For this next case study, I came across an interesting visualization attempting to put Bitcoin economy into perspective.  Bitcoin has been on a tear lately, and which has to make most people wonder how big a deal it is.  We found a visualization that tried to do just that:

The Bitcoin Economy in Perspective (from HowMuch.net)There are a few, many things here that just make me cringe.  So, let’s get into our analysis, and then figure out how we might want to improve it.

Note: According to Coin Desk, the price of a bitcoin was approximately $2800 on June 21, 2017, when this graphic was published.  As of publication, it is nearing $10000.  For consistency with all of the other numbers, we will keep using the June number.

Overview

The goal of this data visualization is to show how small Bitcoin is relative to the monetary supply of the world.  The data used are a mixed of meaningful, and not so meaningful, monetary markers.  The data are visualized with circles representing the relative size of each marker.  There are several factors that impact the ability of this visualization to present a clear, unbiased image.

Explanation of data

The creator of the graphic uses a mix of monetary markers to represent the relative strength of Bitcoin.  The first issue that I came across is that the total value of Bitcoin is on one end of the values.  We only find out the value of things worth more than Bitcoin.  We don’t learn the things it has already surpassed.  This presents a bias in the data intended to show that Bitcoin is still relatively insignificant.

Recommendation 1: Supplement the revised chart with similar monetary markers that are below the value of Bitcoin.

The monetary markers used for the most part are fairly meaningful.  The creator used the the total value of stocks, money, physical money, gold, and U.S currency.  These are things that Bitcoin is often compared to, so these are good comparisons.  The next set of comparison markers are not as meaningful, which are companies and wealthy individuals.  Perhaps these are comparisons that some people would understand.  Larry Page is worth as much as all Bitcoin.  Great! Not sure if it adds anything of real value.   It sends the message that Bitcoin isn’t worth as much as a person.  Again, it would be more interesting to see the names of individuals and companies that Bitcoin was already worth more than, and  that might add some context for comparison to individual wealth.  Overall, I think the dataset is credible, perhaps not the most relevant, and might be skewed to paint a particular picture.

This is one-dimensional data.  Simply, the value of X is Y.  One thing to note is that the complete dataset ranges from $41B to $83.6T.  That’s three orders of magnitude that are not adequate represented.  To properly show that in a graphic, we would likely need to use a logarithmic scale.

Recommendation 2: Use a logarithmic scale to represent the monetary scale.

An interesting thing to note is the url for the article suggests that the title was originally “World’s Money in Perspective,” and was later changed to “The Bitcoin Economy, in Perspective.”  Bitcoin being the hot new thing, a copy writer may have thought that would garner it more attention.

Explanation of visualization techniques

The monetary values are visualized along an axis with the most valuable marker “All Money” on the left, and with Bitcoin, the least valuable, on the far right.  Each of the markers total circle is represented by the area of a circle.  Actually, I, think it’s area, but I’m not positive. This is the first issue I ran into trying to determine whether these circles are relatively sized.  Look at the image below of the right side of the visualization with some area approximations.

What’s going on the right side?

The right side of the visualization is important because it is what we will anchor our understanding of the value of Bitcoin in the graphic.  What I did here was measure the radius in pixels, and find the approximate area in pixels.  You would expect that the area for for Bitcoin to be about one-tenth the area of Amazon, but is only about one-fifth.  Something is not quite right here.

Then, I figured it out with some back-of-the-envelope (okay, I used Excel) calculations.   I have two theories as to how these circles were portioned.  The first one is that you have to take a look at the shading.  It has that lighting effect to make it look three-dimensional.  As in, those are individual spheres, not circles.  The value of each monetary marker is represented by the volume of the sphere.  If this is the case, the graphic falls well short, and over-complicates the graphic.  Why make it three-dimensional when one will do?  Use area if you must and make it two-dimensional.

The other theory I have is that the area represents the logarithmic value of the monetary marker.  In this case, the graphic recognizes that the data goes across three orders of magnitude and must do something to account for it.  If this is the case, the biggest issue is that it’s not indicated anywhere! How are we supposed to know this?  It’s not a terrible method.  Although, in this case we are still using two dimensions to represent one-dimensional data.

I can’t know for certain which method was employed, since I’m limited to measuring the radius from the screen.  The one thing I am certain, either method over-complicated a rather straight-forward dataset.

Recommendation 3: Since it is a one-dimensional dataset, represent it in one dimension.

Effectiveness of the visualization

An important question to ask is whether this visualization achieved its objective.  As I understand from reading the article, the goal of this visualization is to show that despite Bitcoin’s amazing growth, it is still just a tiny amount of the world monetary universe.  This is despite the questionable techniques it used in presenting in the design of the circle.

One of the things this does that is a bit unusual is that it put the largest value on the left, and the smallest one on the right.  I found this particularly odd because the smallest one is the data point of interest.  If you were trying to tell a story about things bigger than Bitcoin, it would be more intuitive to start on the left, and then go to the right.  I think this flip-flopping of large to small causes a delay in understanding the visualization.  Because the eye sees those large circles first, a reader could think that Bitcoin has amassed a large amount of relative value, and is not as insignificant as the others.

Recommendation 4: Present the information in a more intuitive way, which is likely to be left to right, or top to bottom.

Integrity of the visualization

As I mentioned earlier, understanding the relative size of Bitcoin is a bit distorted, since we do not have any monetary markers below the value of Bitcoin for comparison.  I’ve already recommended including some monetary markers below the value of Bitcoin.  This will allow the data to give a more complete picture of how big Bitcoin already is and how far it has to go before it is a major player.

Another thing that is a bit misleading are the labels.  Each label is placed slightly below the one to its right, implying a hierarchy and value.

These labels are adding meaning that’s not there!

The big issue is that despite the fact that Larry Page and Bitcoin are the same value, the lower placement of the Larry Page label implies that Larry Page is worth more than Bitcoin.   The main reason they are oriented this way is because it looks nice.  It doesn’t add one bit of actual information in the way it is arranged, and it implies information that is not there.

Recommendation 5: Display the labels so that they do not add any implied value to the chart.

I should also again note that the circles do not represent anything intuitive.  Either the circles represent the log10 scale of the value of the monetary markers, or the circles are actually spheres that represent the monetary markers’ values.  It should definitely be clear what the actual value of the monetary marker is.  The only reason we know what the value of each marker is that it’s written.  That’s a waste of good data-ink.

Recommendation 6: Since it is one-dimensional data, we should be able to utilize a graphing method that makes labeling the values unnecessary.

Design

Despite all of the issues mentioned, earlier, I don’t think it’s poorly designed.  I like the choice in pink as the primary color because it’s distinctive, and draws your eye to the visualization.

Another good feature of the design is that it is aligned along a single axis.  However, it mars the effectiveness of this single axis, by then using the area of the circle (or volume of a sphere!).  This causes some awkwardness when on the left side of the visualization the circles overlap, and on the right side they have plenty of space.  As Recommendation 3 states, we need to pick a single axis approach.

The little icons used with the labels are all a different style.  Some of logos, some are headshots, and some are clipart-style representations.  These are not a cohesive visual strategy.  In fact, with the labels there, there is no actual need for the imagery.  It’s extraneous data-ink.  We could probably eliminate those images all together.

Recommendation 7: Remove the images (or the text labels).  Having both of them is redundant.

The Bitcoin Economy – Fixed

In total, there were seven different recommendations on enhancing this visualization to be more truthful and effective.  Let’s review:

  1. Supplement the revised chart with similar monetary markers that are below the value of Bitcoin.
  2. Use a logarithmic scale to represent the monetary scale.
  3. Since it is a one-dimensional dataset, represent it in one dimension.
  4. Present the information in a more intuitive way, which is likely to be left to right, or top to bottom.
  5. Display the labels so that they do not add any implied value to the chart.
  6. Since it is one-dimensional data, we should be able to utilize a graphing method that makes labeling the values unnecessary.
  7. Remove the images (or the text labels).  Having both of them is redundant.

Before I decided on what format the visualization should take, I saught out new data.  Let’s start with the people that are used as monetary markers.  Larry Page and Bill Gates are known well, but not nearly as well known as say Tiger Woods and Michael Jordan.  According to Celebrity Net Worth, Michael Jordan is worth $1.5 billion, while Tiger Woods is worth $740 million.  These are well-known athletes that everyone knows to be crazy rich.  The fact that Bitcoin has blown by them in value does say that Bitcoin is at least somewhat significant.

Another data point that we’ll add to the set is the Gross Domestic Product of a couple of countries.  Bitcoin’s value of $41B is higher than roughly half of the countries-by-GDP listing. Some of the highlights are it being larger than first-world Iceland’s GDP of $23B and oil-rich Bahrain’s GDP of$32B.

Lastly, we’ll add the market cap of Twitter ($17B).  Bitcoin is more than double the value of a relatively common stock.  It’s a bit of cherry-picked number as there is nothing special about Twitter other than it being well-known.  The reason to add this point is to give additional depth to understanding the significance of Bitcoin’s value.

We have one monetary indicator to add – the amount of interest the United States pays each month to service its debt.  For October 2018, that number was $24B.  In other words, all of the world’s bitcoin could service the interest on the U.S. Debt for about one-and-a-half months.

Just for fun, since this was a relatively simple dataset (17 data points, including my six additional ones) I decided to limit myself to using Excel.  I know what you’re saying — Excel is guilty of many visual atrocities past and present.  My thought is that creating a clean data visualization of such a simple dataset should be easy to do with just about any tool.

Before, I show you what worked, I’ll throw out some of the options that I looked at before finalizing my visualization.  In this first one, I thought I would see if I could make the circles work:

Sketch 1 – Circles? No circles.

That didn’t work, and Sketch 1 was the circle version one that looked the best.  Perhaps if it was multi-dimensional and the big circles didn’t overlap, we would entertain it for more than the two seconds I entertained it.  I should note, the black and white coloring does look nice and simple.  It does have that going for it.

Next up was our good friend the donut chart, also known as the pie chart’s hipper, younger brother.

Sketch 2 – Donut chart? No….

I’ll understand if you need a moment to collect your thoughts after seeing that.  It’s a bit overwhelming, I know.  Aside from the fact that you can’t see the Bitcoin value, you can’t see much of anything else.  This is why people hate Excel.

How about we try something in three-dimensions?  It would be counter-intuitive to go three dimensional, but sometimes the opposite of what you think would be true is true.

Sketch 3 – Three-dimensional conical bar chart.

Nope, that didn’t work.  And, I recind my comment about donut charts being the reason people hate Excel.  That’s because Sketch 3 is the reason why people hate Excel.  Has anyone ever seen a good visualization using this technique?  Aside from the inability to determine dimension, to pick out the actual value, and to identify the labels, it’s just terrible to look out.  It looks like something that might be used in a circus side-show.  Next.

Alas, progress was made.  One of the methods that has intrigued me since I learned about it is the radar chart.  It has an interesting take on representing one-dimensional data.  Looking at the results in Sketch 4 below,  I can see why.

Sketch 4 – Radar Chart – I can live with this.

Sketch 4 isn’t that bad.  The labels are easy to pick out and so are the values of each individual monetary marker.  I would be fine with using this one if I had to.  My only complaint is that it is does make the visualization a little more complicated than it needs to be.  It’s 17 data points, we should do simpler.

Which brought me to the decision I settled on — the bar chart.  Good’ole bar chart.  Simplifying data for centuries.

Sketch 5 – I like this one!

This came out relatively nicely.  It’s clean.  The colors are easy on the eyes (I do have an affinity for orange, so easy on my eyes?), and I used a complementary color of blue to self-identify the Bitcoin bar as the bar of interest.  One of the things I did not like was that the labels are really small when they are horizontal.  Perhaps that’s the reason why the original dataset had 11 points.   In Sketch 6 below, you can see it with labels at a 45-degree angle.  Honestly, either Sketch 5 or 6 work for me.

Sketch 6 – Or this one

One thing that I should note is that I put these on a logarithmic scale.  That’s the only way you can make it so you can see the relative size of everything.  Otherwise, almost everything but the last four data points were essentially zero.  You do risk that individuals won’t notice the scale or won’t know how to read it.   Using the log scale is a reasonable trade-off to make here.

I did take a look at using the original data, and I kind of like that one a little bit better.

Sketch 7 – With Bitcoin back on one end.

In Sketch 7, I moved Bitcoin to the left.  Even on the logarithmic scale, you can see the huge difference in the orders of magnitude between Bitcoin and the rest of the monetary market.  It also allows the labels to get large enough that they are much more legible while horizontal.

Conclusion

So, let’s see how I did against the seven recommendations:

  1. Supplement the revised chart with similar monetary markers that are below the value of Bitcoin.
    • Achieved! I found six other data points that met the same spirit of the original data points.  In Sketch 7, I also found that by putting it on the right scale and visualization, the supplemental data points may not be as useful.
  2. Use a logarithmic scale to represent the monetary scale.
    • Achieved! That was the only way this data set looked good once visualized.
  3. Since it is a one-dimensional dataset, represent it in one dimension.
    • Achieved! Found that a simple bar chart or radar chart does a fairly good job of creating an effective data visualization.
  4. Present the information in a more intuitive way, which is likely to be left to right, or top to bottom.
    • Achieved! Bar charts are classic, simple, and easy to understand.  When you learn about charts, bar charts are probably the first thing you learned.
  5. Display the labels so that they do not add any implied value to the chart.
    • Achieved! The labels are all at the same level.  No implied value imparted.
  6. Since it is one-dimensional data, we should be able to utilize a graphing method that makes labeling the values unnecessary.
    • Achieved! There’s a clean logarithmic scale that allows you to determine each value upon look-up.  We don’t need to include the values.
  7. Remove the images (or the text labels).  Having both of them is redundant.
    • Achieved! No extra images! Yeah! We didn’t waste ink on images that still need explanation.

Overall, score another win for simplicity.  Using Excel was an interesting experience, because it gave me a lot of different options to explore in a very short amount of time.   I easily could have selected something that made for a sub-par visualization.   By keeping my objectives in mind, I’m pretty happy with the results.

Please let me know your thoughts in the comments!

References:

  1. https://howmuch.net/articles/worlds-money-in-perspective
  2. https://www.coindesk.com/price/
  3. https://www.celebritynetworth.com/list/top-50-richest-athletes/
  4. https://finance.yahoo.com/quote/TWTR/
  5. https://www.treasurydirect.gov/govt/reports/ir/ir_expense.htm