# Category Archives: R Colors

## R Graphics: Color Ramp Functions

Color ramp functions in R simplify color selection and assignment.  Visual reference examples are provided to illustrate their use and flexibility.

#### Color Ramp: rainbow()

The rainbow() ramp is is the standard light spectrum with red, green and blue as its base. The functional form is rainbow(n, s=1, v=1, start=0, end=max(1, n-1)/n, alpha=1).  The s and v values correspond to saturation and value from the HCL color scheme (described below).  The parameters `start` and `end` can be used to specify particular subranges of hues. The following values can be used when generating such a subrange: red = 0, yellow = 1/6, green = 2/6, cyan = 3/6, blue = 4/6 and magenta =5/6.

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## Colors in ggplot

There are number of ways to control the default colors in ggplot.

#### The HCL Color Wheel

ggplot simplifies color choice with its default color selection, which are based on a “color wheel.”  The result is a well balanced graphic that doesn’t draw too much attention to any one color.  ggplot uses the HCL color wheel and the hue_pal() function from the scales package.  Specifically, if there are two colors, then they will be selected from opposite points on the circle; if there are three colors, they will be 120° apart on the color circle; and so on.  This ensure that discrete data has maximum contrast as a function of the number variables present.

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## R Graphics: Grey Scales

Grey scales in R can be used effectively in data visualization.  Several simple functions can be used to great effect.

#### Creating Gray Scales

The gray.colors() function creates a vector of interpolated values that represent evenly-spaced gray colors.

The function has the form gray.colors(num_colors, start = value, end = value, gamma = value).  End and start define the endpoints of the range of grays, with 0 = black and 1 = white being the extreme values. (By default, start = 0.3 and end = 0.9.) gamma is an optional argument which controls luminance.

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## R Graphics: Heat Colors

Heat colors in R utilize basic color ramp  functions.  Simple example scripts with basic control options follow.

#### Heat Colors

The heat.colors() function creates a ramp of contiguous colors clustered around the color orange in the red spectrum of the RGB scale.  The function has the form heat.colors(num_colors, alpha=value).

#### Alpha Transparency

Heat color transparency is controlled with the optional alpha argument.  The default value is alpha=1.

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## R Color Basics

#### R Color Basics

R graphical devices support a broad range of colors and color functions.  The colors() command with no input arguments returns a list of all available colors in R.  Presently, there are 657 colors.  In practice, declaring colors can be achieved three ways:

• character names (e.g. “red”, “orange”, “yellow”),
• 3-digit RGB values (e.g. 255 0 0265 155 0255 255 0), and
• hexadecimal strings (e.g. “#FF0000”, “#FFA500”, “#FFFF00”).
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The following page provides R color tables by name and hexadecimal code. The tables can be downloaded for local reference or recreated with R code provided.

#### R Color Tables: By Name

Click to enlarge

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## Color Palettes in R

The following list details all color palettes and color ramp functions in R.  Detailed color tables are created for long-term reference and to aide code scripting.  The objective is to simplify the delivery of publication quality graphics.

Next

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## RColorBrewer Palettes

#### Color Groups

RColorBrewer is an R packages that uses the work from http://colorbrewer2.org/ to help you choose sensible colour schemes for figures in R.  The colors are split into three group, sequential, diverging, and qualitative.

• Sequential – Light colours for low data, dark for high data
• Diverging –  Light colours for mid-range data, low and high contrasting dark colours
• Qualitative – Colours designed to give maximum visual difference between classes
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