Excel at Excel Charts: Give That Messy Default Chart A Makeover.

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Excel at Excel Charts: Give That Messy Default Chart A Makeover.

Not all graphs are fit for presentations. Chances are, your auto-generated charts from Excel won’t help you communicate data effectively. For starters, default Excel charts have the tendency to be quite confusing due to excess lines, legends, and figures. The father of information design, Edward Tufte, calls this “chart junk.”





Chart junk distracts from the meaning you’re trying to convey with the data in question. Non-essential elements in your charts causes them to be hard-to-scan and understand.





While the easiest thing to do is toto put a screenshot of your chart into your deck, you’re not paying the data the respect it deserves. Default Excel charts are ugly, potentially misleading, and definitely distracting from the story your data has to tell.


“Okay, so Excel charts are awful, what should we do about it?”


Don’t worry, Deliverable Coaching has got you covered! In under 60 seconds we’ll help you turn around the quality of that nasty looking Excel chart. With this step-by-step process, you can better visualize your data to tell the story behind the numbers.


Step 1: Choose The Right Chart

For example purposes, we’ll start with a sample data set that shows the most endangered species of bear on the planet.





In order to tell the story behind the data, you have to first choose the right chart that will highlight the key data points. In this case, the data suggests that Giant Panda bears are the most endangered bear species.


It can be overwhelming and confusing to pick among a variety of charts that currently exist in the data viz world. There are line, column, bar, bubble, scatter, and treemap charts at your disposal but only one usually portrays the data’s story accurately.


The key to this is to experiment and try a few charts before settling on one. As a rule line, column, and bar charts are best for data comparison – which is exactly what we’ve got here, a comparison of how many different bears are left in the wild.


So let’s create a basic column chart:





Let’s assess the default chart.. It’s so vanilla it hurts. The fonts don’t match my presentation’s fonts (Roboto vs. Calibri, yuck), and the labels below are inconsistently broken into one or two lines. Aside from this, the viewer’s eyes have to go back and forth between the figures and the y-axis to understand the data story.


So, we start experimenting. What if we change this column chart into a bar chart?





There’s still clutter there but it’s a bit of an improvement from the previous one. Why? The one-line labels on the left side of the graph look cleaner and more legible as they are all one line.


Can we keep improving? I wouldn’t be writing this article if we couldn’t!


Let’s try putting the data into descending order so that it goes from most common to most rare species.






In this version, your eyes no longer frantically skim through the page to decipher the data. What we’ve done is mimic movement that our eyes are accustomed to. In this case, our eyes naturally go up and down the page without any disturbance.


Step 2: Obliterate Clutter

While our current draft is already an improvement, there is still a ton of chart junk visible. Next, let’s go ahead and get rid of the unnecessary axis above our chart. We’ll lose context by doing this, but there’s a better way, as we’ll see, to add that context back in.





Now, we have a significant amount of space to let our eyes breathe a little. Even after removing the horizontal axis, we can still see that Giant Panda bears are lagging behind in terms of their numbers.


Since we’ve already removed this axis, there’s really no point in keeping the vertical grid lines, am I right? So let’s go ahead and remove ‘em.





Mmm… what a nice spacious page! We’re well on our way to oblittering the clutter in this chart.Such a nice improvement!


Step 3: Add Back Those Important Details!

Since we removed the horizontal axis, we don’t really know the figures behind the data set. To add this context back in, we “Add Data Labels” in Excel to the outside-end of each type of bear species.





In the example above, I’ve added the data right where the bars end. This way, our eyes don’t need to “guess” what the data is by looking at an axis. Instead, the data is right there for us to see.





As another step, I went ahead and added a descriptive title to our graph and changed the color to fit our brand colors.


We’re almost done!


Step 4: Highlight Your Key Takeaway

The data set reports that Giant Panda bears are the rarest among bear species. Let’s stay true to the data story and highlight it so our audience instantly understands what we’re trying to communicate.






I’ve achieved this by reducing the Transparency of every bar except Giant Pandas. Poor guys. This can also be achieved by placing a semi-transparent white rectangle over what you want to de-emphasize.


There you have it; a nice, clear chart about endangered bears Our audience can easily decipher your data at first glance because of the visual story we’ve established.

Putting it in action


To recap:

  • Step 1: Choose The Right Chart

  • Step 2: Obliterate Clutter and Chart Junk

  • Step 3: Add Back Those Important Details

  • Step 4: Highlight Your Key Takeaway


This four-step process helps us achieve our goal of: obliterating chart junk.


Remember: give that data some respect by styling your charts so that it’s easy to understand the story that it’s telling.


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