Okabe-Ito Palette Hex Codes: Full 8-Color Reference with Code Examples [2026]

The Okabe-Ito Palette, Explained for Figure Designers

If you just need the eight hex codes, jump to the reference table below and paste them straight into your script. If you want to understand why this particular set of colors keeps showing up in published research, read on.

The Okabe-Ito palette is a categorical color scheme designed so that none of its hues collapse into one another for readers with color vision deficiency (CVD). Masataka Okabe and Kei Ito assembled it under the umbrella of the Color Universal Design organization, choosing eight tones that stay separable across the common forms of CVD rather than picking colors that merely look attractive on a screen.

Its credibility in academic circles is hard to overstate. Bang Wong highlighted the same set in a 2011 Nature Methods column, and the name Wong palette stuck to it afterward. Claus Wilke later wired it in as the go-to categorical scheme throughout Fundamentals of Data Visualization. In short, three independent sources of authority point at the same eight colors.

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The Full Okabe-Ito Hex Code Table

Here is the canonical set. Each row gives the published color name, its hex string, the matching RGB triplet, and a swatch so you can eyeball the tone at a glance.

Grab the whole sequence in one line:

#E69F00, #56B4E9, #009E73, #F0E442, #0072B2, #D55E00, #CC79A7, #000000

Why Researchers Keep Reaching for It

Roughly one in twelve men and one in two hundred women see color differently from the rest of the population. A figure that relies on red-versus-green to separate two trend lines can become unreadable for a sizable slice of your audience. The Okabe-Ito set was built to dodge exactly that failure mode. A few properties make it dependable:

• Separation under every common CVD type. Whether a reader has protanopia, deuteranopia, or tritanopia, each of the eight colors stays its own identifiable thing.
• Lightness that survives a black-and-white printer. Because the colors differ in luminance and not just hue, the figure still parses when a reviewer prints it in grayscale.
• Designed, not patched. CVD safety was the starting constraint of the design, so you are not relying on a palette that was tweaked after the fact to pass a checker.
• A category count that fits real figures. Eight slots handle the overwhelming majority of grouped charts you will ever build for a paper.

It is no accident that author guidelines at Nature, Science, and Cell all nudge contributors toward colorblind-safe schemes. Accessibility has quietly become part of what reviewers expect from a clean figure.

Drop-In Snippets for Your Plotting Stack

Pick the language you work in and paste. Each block defines the same eight colors and wires them in as the default cycle so your existing chart code picks them up automatically.

Python (matplotlib / seaborn)

# Define the Okabe-Ito palette
okabe_ito = ['#E69F00', '#56B4E9', '#009E73', '#F0E442',
             '#0072B2', '#D55E00', '#CC79A7', '#000000']

# Use with matplotlib
import matplotlib.pyplot as plt
plt.rcParams['axes.prop_cycle'] = plt.cycler(color=okabe_ito)

# Use with seaborn
import seaborn as sns
sns.set_palette(okabe_ito)

R (ggplot2)

# Define the palette
okabe_ito <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442",
               "#0072B2", "#D55E00", "#CC79A7", "#000000")

# Use with ggplot2
library(ggplot2)
ggplot(data, aes(x, y, color = group)) +
  geom_point() +
  scale_color_manual(values = okabe_ito)

# Or use the built-in scale (ggplot2 >= 3.4.0)
ggplot(data, aes(x, y, color = group)) +
  geom_point() +
  scale_color_okabeito()

MATLAB

% Define the Okabe-Ito palette as RGB (0-1 range)
okabe_ito = [
    230/255, 159/255, 0;       % Orange
    86/255,  180/255, 233/255;  % Sky Blue
    0,       158/255, 115/255;  % Bluish Green
    240/255, 228/255, 66/255;   % Yellow
    0,       114/255, 178/255;  % Blue
    213/255, 94/255,  0;        % Vermillion
    204/255, 121/255, 167/255;  % Reddish Purple
    0,       0,       0         % Black
];

% Set as default color order
set(groot, 'defaultAxesColorOrder', okabe_ito);

CSS Custom Properties

:root {
  --oi-orange: #E69F00;
  --oi-sky-blue: #56B4E9;
  --oi-green: #009E73;
  --oi-yellow: #F0E442;
  --oi-blue: #0072B2;
  --oi-vermillion: #D55E00;
  --oi-purple: #CC79A7;
  --oi-black: #000000;
}

How It Stacks Up Against Other Accessible Palettes

A quick rule of thumb: reach for Okabe-Ito when your data is split into named groups that have no inherent order, things like bar charts, line plots with several series, clustered scatter plots, and the legends that label them. The moment your variable runs along a continuous scale instead, say a temperature heatmap or a population density map, hand the job to a sequential scheme such as Viridis or one of the ColorBrewer ramps.

For a deeper walkthrough of all of these options, hex codes included, see our scientific color palette guide.

Where It Came From and How to Cite It

The palette traces back to the Color Universal Design (CUD) effort that Masataka Okabe and Kei Ito ran out of the University of Tokyo. Their original resource is still online:

A few years later, Bang Wong put the same colors in front of a much larger audience:

Which one to cite: both references are accepted, so let your field decide. Many design and visualization papers point to Okabe and Ito (2008), while life-sciences manuscripts often cite the Wong (2011) Nature Methods piece. Either choice is defensible.

Frequently Asked Questions

Are "Okabe-Ito" and "Wong palette" two different things?

No, they label the same eight colors. The "Wong" name simply spread after Bang Wong reprinted the set in his 2011 Nature Methods column. Compare the hex strings from either source and you will find them byte for byte identical.

How many colors does the palette contain?

Eight in the standard form: Orange (#E69F00), Sky Blue (#56B4E9), Bluish Green (#009E73), Yellow (#F0E442), Blue (#0072B2), Vermillion (#D55E00), Reddish Purple (#CC79A7), and Black (#000000).

Is it free to use in commercial work?

Yes. It was published openly through the Color Universal Design project with no licensing fee, so commercial figures, products, and paid publications are all fair game.

Can ggplot2 apply Okabe-Ito without a manual vector?

Yes. As of ggplot2 3.4.0 the scales ship in the box, so scale_color_okabeito() and scale_fill_okabeito() work directly and save you from typing out the hex list.

What should I do when eight colors are not enough?

First, consider whether a second visual channel could carry some of the load. Mapping a few groups to distinct marker shapes or fill patterns often lets you keep the eight-color set without crowding the chart. If you genuinely need more hues, the Paul Tol palette extends to 12 colorblind-safe categorical colors. Our palette comparison guide lays the options out side by side.

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