How To Design Perfect Charts
and Graphs For Your Data

There’s no doubt about the fact that part of modern-day living now requires some sort of data management, one way or another. From the way we create our daily schedules to the information we choose to take in every day, to even the social media accounts we use, it’s all about digesting the huge swathe of information that’s already available to us and trying to make sense of it. The best way to do that, of course, is through data visualization. Defined as the tool for graphical representation of quantitative and categorical data, it’s mainly composed of elements like charts, graphs, or maps.

But creating and designing these elements may be daunting for some. The good news is that there are a variety of chart and graph maker apps online that could make the process painless, without users having to worry about details.

However, for those who want to customize their graphs further and integrate basic design principles into them, here’s a short guide.

Pick the Right Type of Chart

Depending on your information and what aspect of it you want to present, you’ll have to use the right type of visualization.

Ask yourself, what are you trying to prove with your data? Is it the composition of something? Or a comparison, a relationship, or perhaps a distribution between them?

If that’s too vague then there are 5 main categories in big data visualization you can look to as a guide instead:

1. Temporal:  Charts that fall under this category are linear and one-dimensional and are some of the simplest ways to compare different data sets or show development over time. Types of visualizations under this include bar charts, Gantt charts, or line graphs.

2. Hierarchical:  Charts in this category are for data that originates from a single root the branches out. Samples of this type include tree diagrams, cone trees, or flow charts.

3. Network:  Charts here are made of visualizations that emphasize deep connections between multiple datasets through visual representations. Types here include matrix charts or word clouds.

4. Multidimensional:  This category is special, as charts here have two or more variables active at all times. Samples of this are heat maps, matrices, pie charts, or histograms.

5. Geospatial:  Simply put, these are used for times when real-world representations of locations are needed with the data being overlaid on top. Think cartograms or density maps.

Once this foundational part is settled, then it’s time to move on to the actual visualization.

How to Design Charts and Graphs

There are lots of software options out there for those who want to create their designs completely on their own. Adobe Photoshop, GIMP, and Corel Draw are some of the most common picks for it.

But for those who don’t want to have to worry about actually having to create from scratch, then there are websites like Venngage. It’s an online design editing tool geared towards making graphics accessible and easy, and it comes with premade templates for charts. All you have to do is input your data into the appropriate fields and you’re done.

Further customization is still an option, of course, and basic design principles still apply. Consider doing the following:

Remove Background Lines and Unnecessary Details

It goes without saying but a clean visualization is a key to being able to communicate your trends clearly. To increase focus on that, remove details like background lines and irrelevant labels, such as markings on numerous data points or unnecessary axes. That makes things more digestible and leaves nothing to distract the eye from the chart’s visual structures itself.

However, don’t forget to also mark important elements such as the title, the encodings, the units, the axes, the descriptions, and other pertinent details.

Style According to Your Needs

The best graph and chart designs are those that fully visually align with what your data is saying. Conducting a report on the environment? Consider a green color palette. Presenting on hard data? Use a minimalist layout and muted colors. Keep your aesthetics in mind.

Also, don’t forget that the little things add up. The font you choose, the colors you pick, and the shapes you use for your visualization all come together to form one cohesive visual, so take your time with all of them.

Sort Your Data Well

It also helps to arrange your data in a logical way so your charts make sense at first glance. Show only relevant data points, make the trends obvious, and don’t stuff too much information into one chart.

At the end of the day, chart design is subjective, and as long as you are able to communicate your data’s points clearly, cleanly, and concisely then it shouldn’t be an issue. Data visualization is all but an exercise in communication, after all.