Both data analysts and artists use elements of art in their work.

A few of the main elements of art that we can consider are as follows.

• line
• shape
• color
• space
• movement

Lines and visualizations can be curved or straight, thick or thin, vertical, horizontal, or diagonal. They can add visual form to your data and help build a structure for your visualization.

Shapes and visualizations should always be two-dimensional. This is because three-dimensional objects in a visualization can complicate the visual and confuse the audience. Shapes are also a great way to add eye-catching contrast, especially size contrast to your data story, marked from 0 hours 1 minutes 5 seconds until 0 hours 1 minutes 25 seconds. Shapes are also known for their variety. Shapes and visualizations should always be two-dimensional. This is because three-dimensional objects in a visualization can complicate the visual and confuse the audience. Shapes are also a great way to add eye-catching contrast, especially size contrast to your data story.

Colors can be described by their hue, intensity, and value. The hue of a color is basically its name, red, green, blue and so on. Intensity is how bright or dull a color is, and finally, there’s value. The value is how light or dark the colors are in a visualization.

Space is the area between, around and in the objects. There should always be space in data visualizations, just not too much or too little. For example, the space between the bars of a bar graph like this one should be smaller than the width of the bars themselves. This will draw the viewer’s attention to the bar and the data it represents instead of the empty space.

Movement allows for a greater volume of data to be displayed and can reveal multiple stories from the same data visualization. Just don’t be distracting.