The best architects can reduce their creations to the essence without sacrificing what was important for their purpose. This is the same philosophy we must embrace regarding data visualizations. Always start with the audience, and their information needs in mind. This will guide your choices when exploring data, comparing data and creating final visualizations.
Choosing the Right Chart Type
When creating data visualizations, choose a chart type that suits your needs. The types of metrics or features that you’re analyzing and the audience for your visualization will impact which chart type works best for your situation.
Some chart types, such as line and area charts, are ideal for displaying time-series data. These are great tools for showing trends or changes over some time, such as the daily number of support tickets or monthly sales numbers. Other charts, like scatter charts and grouped bar charts, are good for comparing individual values.
These are ideal for showing differences within a category, such as the average age between countries or website visitors by device type. If your data is highly correlated, a heatmap may be a better option to show patterns or relationships between values. The key is to find a way to reduce your data set to its most essential elements without introducing inaccuracies or skewing the information.
Choosing the Right Chart Colors
A good data visualization color palette like those at Delta Electronics can make your graphics look great and communicate the right information. However, a bad one can obscure the message and confuse your viewers.
It’s important to remember that the objective of data visualization is not to look pretty but to communicate key results and findings. Choosing colors should be strategic and carefully considered to achieve this goal. Sequential colors are hues with varying lightness and saturation.
They’re useful for ordinal, interval, and ratio scales. Categorical colors are hues without a specific order and should be used for categorical data. Using the right chart colors can improve your visuals and speed up your workflow. With the right tools, creating various charts and graphs is easy.
Choosing the Right Chart Format
The right chart type can help you compare values, analyze trends, and show how different parts contribute to the whole. It can also convey important information in a way that is easy for your audience to understand and remember.
When choosing the right chart format, ask yourself what data you need to visualize. For example, a bullet graph is a great choice to show performance metrics, such as sales per month or the number of customer support tickets.
A choropleth map is the best way to represent data that varies across geographic areas, such as temperature and humidity levels. Make sure your chart design is as simple and uncluttered as possible for any chart.
Grids, varying colors, and other distracting elements can lead to misinterpretation of the data. Therefore, it is best to lighten labels and gridlines, avoid 3D effects, and remove backgrounds to ensure that your data is the most prominent element.
Choosing the Right Chart Style
The type of chart you choose will depend on the information you need to communicate, including comparisons, relationships, and trends. However, using the wrong chart style could confuse your viewer and lead to misinterpretation.
The design of a chart should be simple enough to be understood without verbal explanation. To test this, have a friend look at your chart and resist the urge to explain it to them.
They can’t understand your chart without verbal explanation; it may be too complicated. The chart should also be minimal, with a large share of the ink used to print the chart representing data information (rather than extra decoration).
For example, grid lines and labels should be lightened or eliminated, and colors should be kept simple. Consider avoiding 3D effects as they tend to be difficult to read. Instead, use headers or annotations to clearly state the information you want your audience to take away from the graph.
Choosing the Right Chart Size
There’s no one-size-fits-all when it comes to chart sizes. You must carefully consider how many categories you want to compare, how big or small each segment should be and how your axes will be scaled.
For example, suppose you are using a number graph. In that case, limiting the number of numbers you include is important, as they can quickly become difficult to read, especially when there are multiple categories.
This can dilute your data narrative and cause the viewer to lose sight of your main point. It’s also a good idea to vary the size of each bar if your comparison is focused on specific portion sizes (for example, comparing the average order profit per product or channel). This will help highlight the most pertinent information and provide context by allowing you to see the size of individual data points at a glance.
Choosing the Right Chart Labels
Whether you are designing an infographic to showcase a data set or sharing your findings with others, charts are a useful tool for conveying information in an easy-to-understand format.
But understanding the different types of graphs can be overwhelming for beginners. To help you get started, this guide will focus on the 20 most popular chart categories and their use cases.
Each chart type will accompany a visual example that Datapine’s professional dashboard software generates. Comparison charts are ideal for comparing categorical data.
When selecting a chart for this purpose, choose one that orders data points according to their significance. This can be done by calling data points from the earliest time or date to the most recent or ranking data values in order of size to emphasize large numbers and small amounts at a glance. For this type of comparison, line, bar, column, pyramid, and pie charts are all excellent choices.
