Okabe-Ito Palette Hex Codes for Python, R & CSS

Okabe-Ito Palette Hex Codes: Complete Reference

Need the Okabe-Ito palette hex codes? Copy this sequence:

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

The Okabe-Ito palette is the most widely recommended colorblind-safe color palette for scientific figures. Created by Masataka Okabe and Kei Ito at the Color Universal Design organization, it provides 8 colors that remain distinguishable for people with all common types of color vision deficiency (CVD).

This palette is explicitly recommended by Nature Methods (where it is sometimes called the Wong palette after Bang Wong's 2011 article) and is the default categorical palette in Claus Wilke's Fundamentals of Data Visualization.

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All 8 Okabe-Ito Hex Codes

Here are the complete Okabe-Ito palette hex codes, ready to copy and paste:

Quick copy (all 8 hex codes):

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

Why the Okabe-Ito Palette Is the Gold Standard

Approximately 8% of men and 0.5% of women have some form of color vision deficiency. The Okabe-Ito palette addresses this by providing colors that:

• Remain distinguishable for protanopia (red-blind), deuteranopia (green-blind), and tritanopia (blue-blind)
• Have distinct luminance values, so the palette works even in grayscale printouts
• Were designed for CVD from the start -- not retrofitted or "tested" after creation
• Cover 8 distinct categories, which is sufficient for most scientific figures

This is why journals like Nature, Science, and Cell explicitly recommend colorblind-safe palettes in their author guidelines.

Code Snippets: Use Okabe-Ito in Your Plots

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;
}

Okabe-Ito vs. Other Colorblind-Safe Palettes

When to use Okabe-Ito: Use it whenever you need distinct categorical colors -- bar charts, line graphs with multiple series, scatter plots with groups, legends, and labels. For sequential or diverging data (heatmaps, geographic maps), use Viridis or ColorBrewer instead.

For a complete guide covering all these palettes with hex codes, see our comprehensive scientific color palette guide.

Okabe-Ito Palette Origin and Citation

The palette was first published by Masataka Okabe and Kei Ito as part of the Color Universal Design (CUD) project at the University of Tokyo:

It gained widespread recognition after Bang Wong's 2011 article in Nature Methods:

How to cite in your paper: Reference either the original Okabe & Ito (2008) source or Wong (2011) Nature Methods article, depending on your field's convention.

Frequently Asked Questions

Is the Okabe-Ito palette the same as the Wong palette?

Yes, effectively. Bang Wong popularized the Okabe-Ito palette in his 2011 Nature Methods column, and many researchers refer to it as the "Wong palette." The hex codes are identical.

How many colors are in the Okabe-Ito palette?

The standard Okabe-Ito palette contains 8 colors: Orange (#E69F00), Sky Blue (#56B4E9), Bluish Green (#009E73), Yellow (#F0E442), Blue (#0072B2), Vermillion (#D55E00), Reddish Purple (#CC79A7), and Black (#000000).

Can I use the Okabe-Ito palette commercially?

Yes. The palette was published as part of the Color Universal Design project and is freely available for any use, including commercial applications.

Does ggplot2 have a built-in Okabe-Ito scale?

Yes. Starting with ggplot2 version 3.4.0, you can use scale_color_okabeito() and scale_fill_okabeito() directly without defining the hex codes manually.

What if I need more than 8 colors?

If you need more than 8 distinct categories, consider combining the Okabe-Ito palette with shape or pattern encoding. Alternatively, the Paul Tol palette offers up to 12 colorblind-safe categorical colors. See our full palette comparison guide for details.

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