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Five Charts and How to Fix Them

When creating data visualization charts, you have so many options to choose from. This is especially true when working with spreadsheets.

Although having many options is often a good thing, and having the ability to customize almost every aspect of a chart introduces some wonderful opportunities, it can be all too easy to make a sub-par chart. In fact, many people accidentally create charts that are not very useful. The intention is good, but the execution is poor.

In this article, we will present five examples of seemingly well-built charts that aren’t so good. We will then show how these charts can be modified or improved to present the data more effectively.

Example 1 – The Overuse of Color

Take a look at the chart shown below.

Overall, this chart is well-built and easy to read. However, there is one small error. Can you guess what it is? It is the unneeded use of many different colors.

Colors can often represent meaning and even guide the reader’s attention. However, in this case, the several different colors are unnecessary. The labels at the bottom of each bar differentiate each metric, so there is no need for colors to do the same.

This chart would be much better off having one color for the bars. This way, the reader isn’t wondering if there is a hidden meaning behind each color.

Also, an example of using different colors to guide the reader’s attention can be seen below. In this case, the color serves a specific purpose.

In the graph above, the blue color is used to highlight Product B. This would be very useful if you intend to guide the reader to focus specifically on Product B in comparison to all of the other products.

Example 2 – The Use of 3D

Take a look at the chart shown below.

Overall, this chart depicts the data quite clearly. The one major drawback is the use of 3D bars.

The use of 3D in your charts may make them “look cool,” but the reality is that 3D takes away from charts rather than adds to them. The 3D effect makes charts more difficult to read and interpret.

Take a look at the 2D chart shown below.

As you can see, replacing the 3D bars with 2D bars immediately makes the chart easier to see and understand. You don’t have to squint your eyes and look closely to see the subtle differences. The differences are much more apparent compared to the 3D bars from before.

The moral of this story is simple. Don’t use 3D in your charts. Keep all your charts in 2D.

Example 3 – Misleading Bars

Take a look at the bar chart shown below. Can you see the one major issue with this chart?

If you guessed that the big issue is the vertical axis, then you are correct. Looking closely, you can see that the vertical axis does not begin at zero. Instead, it starts at the value of 1680.

The benefit of starting at a higher value makes it easier to see the differences between bars. The major drawback is that this comparison is misleading.

When we look at the bars, we compare their lengths. Based on the chart above, you see that the South bar is about two times the size of the North bar. Your brain then makes the inference that the South region has produced almost double the profit of the North region. This, of course, is quite incorrect.

The South bar shows a total profit of about 1800, and the North bar shows a total profit of about 1725. The number 1800 is certainly not twice the size of the number 1725. So how do we fix this problem?

The first and most obvious solution is to start the vertical axis at zero.

All of a sudden, the bars are no longer misleading. However, you now have a different problem. It is difficult to distinguish the differences between the bars.

If you intend to depict the subtle differences between the profit values per region without misleading the reader, here is what you can do. Take a look at the chart below.

In this chart, dots are used instead of bars. Our brains do not compare the distances from the horizontal axis to the dots like they do with the length of bars. So the misleading problem is no longer present. Furthermore, a note is placed near the bottom of the chart indicating that the axis does not start at zero. This way, there is no confusion for the reader.

Example 4 – Improper Use of the Line Chart

Take a look at the chart below. Do you see any issues?

This time, the problem is the type of chart that is used. A line chart is typically used to depict change through time or to show the overall shape of the data.

In this case, we are trying to compare the different sales values for the various products. Using a line to illustrate this is not very effective. We are not trying to show how sales change over time.

A much better solution would be to use bars.

A bar chart is one of the best charts to use to show comparisons of different values. A line chart is better at showing change through time.

Example 5 – Don’t Use a Pie Chart

Take a look at the chart below.

If you are working with more than two categories or metrics, do not use a pie graph to depict percentages.

It is difficult for our brains to compare pie slices. In the chart above, it is a challenge to see the subtle difference between Product C and Product B.

The above chart also contains an abundance of color which we discussed earlier in this article. For the pie chart, the color is necessary, but it makes the chart appear rather busy.

Instead of using a pie chart, use a bar chart instead. Take a look at the chart below.

As you look at this chart, your brain can immediately recognize which product has the largest percentage of sales and which has the smallest. Furthermore, there is no question or confusion as to where the other products stand in comparison. Everything is very clear and easy to understand.

If you would like to read more about use and misuse of pie charts, check out our article, “Too Much Pie.”

We hope you had fun reading this article, and hopefully you learned something new along the way. Be sure to leave a comment below if you have any questions or have anything else to add!

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