thumbnail for video 10 - can you use excel to create a powerful chart

Can you use Excel to create a powerful chart?

Can you use Excel to create a powerful chart?

Spreadsheet tools such as Microsoft Excel or Numbers might not be the first thing on your mind when considering data visualization tools, but they can be pretty solid choices to build data visuals. Don’t let anyone convince you that using Excel to create data visuals is unprofessional. In my practice as an information designer I have created many charts in both Excel and PowerPoint, in particular for clients who wanted some degree of flexibility in modifying the visuals themselves.

Spreadsheet tools are more powerful than you might think

Spreadsheet applications allow us to create almost any type of chart in the family of bar charts, line charts and pie charts – including stacked bar charts, area charts, and so on. But even more ‘exotic’ alternatives such as treemaps, sunburst diagrams, candlestick charts, radar charts and waterfall charts are available.

The strength of spreadsheet tools lies more in building the charts than in polishing their design. We could use Excel to create the basic shapes that will make up the core of the data visual, and then export them to another, more design-oriented tool such as PowerPoint or Adobe Illustrator to further modify the colours, annotations and layout – or to combine multiple graphs into a single chart. Nevertheless, most of these things are possible in spreadsheet tools as well, although they might require a bit more tinkering and clicking around.

Move away from the defaults

The challenge in these situations is to move away from the default options. It takes some time and patience, and maybe some visual trickery, but it pays off!

This is how a default visual might look like: it has no visual hierarchy, boring default colors, the legend takes up a lot of space, and the numbers are hard to read.

Groundwater use by agriculture in Flanders

In the reworked visual below we changed the orientation of the bar chart from vertical to horizontal, we chose a better colour scheme, and we used direct labelling to remove the legend and gridlines. The end result contains exactly the same data as the default chart, but presented in a much clearer and more structured way.

Reworked visual of the groundwater bar chart

Both of these charts were created from scratch using nothing but Microsoft Excel. Creating powerful charts is not about the tools you use, it’s all about applying the right principles!

If you want to know more about visualizing data in the right way, you can check out the other videos in this series. Or I invite you to read my book, Powerful Charts, that will give you actionable insights and practical guidelines to create data visuals that truly engage and inspire your audience.

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We are really into visual communication!

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thumbnail for video 09 - choosing the right font for your data visual

Choosing the right font for your data visual

Choosing the right font for your data visual

Typography is a fascinating domain. Fonts evoke emotions: there are very sophisticated fonts, playful fonts, attention-grabbing fonts, and elegant handwritten fonts. Using the wrong type of font can have a lot of impact. In data visualization the implications of typography are mainly focused on readability. Labels and annotations can easily become so small they get hard to read. Above all else, we should choose a font which is readable at small sizes.

What influences readability?

The readability of a font at small sizes is mainly determined by three aspects: the x-height, the counter, and the serifs.

The x-height of a font is the height of the lowercase letters compared to the height of the line itself. Fonts with a lower x-height are more difficult to read than fonts with a higher x-height.

The counter is the enclosed space inside a letter, such as in the letters ‘o’, ‘a’ or ‘e’. The larger the counter size, the easier it becomes to read a font at small sizes.

Finally, the serifs. Sans-serif fonts are generally easier to read at small sizes than serif fonts. The different serifs – the small lines and strokes attached to the end of individual letters – make longer texts easier to read, because our brains can more easily distinguish different letters from each other. That’s why almost any book is set in a serif font. But for small text, the serifs get in the way and sans-serif fonts are the way to go.

Where to find the perfect font?

If you’re struggling to find the perfect font, a good website like Google Fonts can help you out. With over 1300 free font families, there’s always something for every situation. You can enter your own text and immediately see how it will look in all of these different fonts. You can filter by category or you can look specifically for very bold fonts, wide fonts, etc. Once you’ve found the perfect font, all you have to do is download it and install it on your computer.

The best fonts for data visualization

If you still find looking for the perfect font a daunting task, try some of the fonts developed specifically for readability:

Assistant | Lato | Noto Sans | Roboto | Source Sans

If you want to know more about visualizing data in the right way, you can check out the other videos in this series. Or I invite you to read my book, Powerful Charts, that will give you actionable insights and practical guidelines to create data visuals that truly engage and inspire your audience.

Read more:

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Last February, on a cold and rainy day, I received the Dear Data book as part of a Dataviz Drawing workshop by Stefanie Posavec. A pretty large and heavy book, the kind you could put on your coffee table to show off (which I did!). Let's review it!

Read More

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Read More

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We are really into visual communication!

Every now and then we send out a newsletter with latest work, handpicked inspirational infographics, must-read blog posts, upcoming dates for workshops and presentations, and links to useful tools and tips. Leave your email address here and we’ll add you to our mailing list of awesome people!