Data visualization is one of the final steps in Data Science. It is very important because it can be used to present the results of the analysis to the end user. For this reason, it is very important to take care of every aspect of the graph, such as shapes, texts, and animations.
With this article, I will start with a series of articles that would explain some basic principles of graphic design visualization to make it very attractive and user-friendly.
In this tutorial, I will cover the following aspects:
White m.p.ace is an empty space among the elements of the graphic composition. Good use of small spaces will come increase readability and focus readers ’attention. For example, inside text, spaces divide large pieces of text into small pieces, making them easy to understand. In addition, spaces emphasize and emphasize some elements of visualization and thus emphasize the main content.
There are two types of spaces in visualization:
Macro white modes – all spaces around the main content, such as the empty space behind the image. In the example below, the white states of the macro are marked in pink.
When drawing infographics, there is usually the idea that all white spaces in the macro must be filled. However, this strategy can lead to data overload, which can cause confusion for the target user. Therefore, it is very important to balance the white spaces of the macro.
Micro spacing – any spaces between text numbers, axis, and text or bar chart bars. The following image shows some micro-white spaces in pink:
The use of text in visualization helps the reader understand the context. An example of chart text is axis tags, title, and some annotations. The main principles of graph design related to the consideration of text design (such as bold, italic, underlined text), Font size, font family, spacing and sharing a song. This last aspect is not very common as a plot unless the chart shows some long notations.
Choosing the right combination of the previous considerations makes the chart more or less readable and enjoyable. For example, the font size and font family (Monotype Corsiva) in the following chart are very small and complex, so reading them is not immediate.
Color is the most effective way to convey emotions and sensations. When choosing colors it is very important to follow standards like red in dangerous situations, green to say that everything is fine and so on.
Each color is characterized by three aspects:
- Hue is a “pure” color, that is, it has only one wavelength in the optical spectrum of light.
- Brightness refers to the intensity of the color, separated by the amount of shading mixed with the hue.
- Saturation refers to the intensity of color separated by an amount mixed with white light and hue
In visualization, colors can be combined to create a consistent graph. There are many tools for creating a color palette, including the following:
- Color Hunt, which allows you to create a multi-color palette
- Pine Tools, which allows the formation of monochrome palettes
- Google Art Paletteto create a palette from an image.
In this short tutorial, I have illustrated some of the basic principles of data visualization. These principles are: spaces, text, and color.
Remember that all data visualizations should be designed with the target audience and its potential feelings in mind. In addition, one of the most important principles of data visualization is graph consistency, that is, each element of the graphic composition must follow and enhance the object of the composition in the most natural way possible without mixing.
In the next article in this series, I will discuss other principles of data visualization, such as animation. Stay tuned for more details 🙂