Mastering Color in Data Visualization: A Guide to Creating a Custom Color Interpolator
Reading time: 2min
In data visualization, color plays a crucial role in conveying information effectively. However, finding the right balance between automated color generation and manual control can be challenging. Let's look at how you can create a color interpolator that generates a palette of colors between two specified values.
The Need for a Custom Color Interpolator
While experimenting with generated color palettes for a data visualization project, we encountered a need for greater control over the color transitions. The standard methods provided either too much automation or required extensive manual input. Thus, the color interpolator was born out of necessity, providing a solution that bridges this gap.
Core Concepts of the Color Interpolator
The color interpolator generates intermediate colors from two input colors. This process involves:
- Defining a starting and an ending color in RGB format.
- Specifying the number of steps or intermediate colors required.
- Utilizing an interpolation function to blend the colors.
Implementation
The implementation involves two primary functions: interpolateColor
and
interpolateColors
. interpolateColor
blends two colors based on a given
factor, while interpolateColors
generates an array of colors between the two
specified colors. The code snippet demonstrates the process in JavaScript,
applicable for web-based data visualization.
Usage
The usage involves:
- Defining the start and end colors (
COLOR_ONE
andCOLOR_TWO
). - Setting the number of desired color steps (
STEPS
). - Applying the generated colors to HTML elements, in this case, divs within a wrapper.
See the Pen{' '} Interpolate colors {' '} by Benjamin Charity ( @benjamincharity) on{' '} CodePen.
This color interpolator exemplifies how a simple yet powerful tool can significantly enhance the aesthetic and functional aspects of data visualization. Bridging the gap between automated color generation and manual control empowers developers to craft visually appealing and informative visualizations easily. This adaptable and straightforward tool is not just a solution to a specific problem but a valuable addition to the broader toolkit of any developer engaged in the art and science of data visualization.