[image] nathan chapelier: Is there a way to color a string or a list/tuple ? for example something that we can do is the following: `` It’s important to understand here that the colouring done here is completely out of Python’s hands. When you run the Python interpreter in a terminal window,… Answer from kknechtel on discuss.python.org
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Colour Science
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Colour Science for Python | Colour Science
Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.
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Python Graph Gallery
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Tips about colors with Python
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Readthedocs
colour.readthedocs.io › en › v0.3.11
Colour Science for Python — Colour 0.3.11 documentation
Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.
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colour
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Google Sites
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paztronomer - python colors
Python's most used plotting library is matplotlib. With it you can do most of the visualizations, and if stuff gets complicated you can turn to other libraries (build on top of matplotlib) as seaborn, bokeh, vaex, and others. That being said, the named colors we are going to "unveil" here can be used across most (if not all) the available plotting libraries.
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Python.org
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Color a list or a string - Python Help - Discussions on Python.org
April 2, 2023 - Hi everyone, Is there a way to color a string or a list/tuple ? for example something that we can do is the following: H = 'hello' res = '' for i in range(len(H)): res += f'\033[0;33m{H[i]}' print(res) This will …
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Rhino
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Rhino - Colors in Python
December 5, 2018 - Colors in Python · Guides / Rhino.Python Guides / Colors in Python · by Scott Davidson (Last updated: Wednesday, December 5, 2018) Colors in Rhino are represented as zero-based, one-dimensional arrays that contain four values. The first 3 values are the Red, Green and Blue channels.
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Like Geeks
likegeeks.com › home › python › the unconventional guide to colors in python
The Unconventional Guide to Colors In Python
October 15, 2023 - Python’s colour module is a simple, yet powerful library to store, convert and manipulate colors.
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Readthedocs
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Colour Science for Python — Colour 0.3.8 documentation
Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.
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GitHub
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GitHub - colour-science/colour: Colour Science for Python · GitHub
Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.
Author: colour-science
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Matplotlib
matplotlib.org › stable › gallery › color › named_colors.html
List of named colors — Matplotlib 3.11.2 documentation
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Colour Science for Python — Colour 0.3.7 documentation
Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.
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Kaggle
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Python Colors for COLOR, CMAP and PALETTE
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Matplotlib
matplotlib.org › stable › users › explain › colors › colors.html
Specifying colors — Matplotlib 3.11.2 documentation
import matplotlib.colors as mcolors import matplotlib.patches as mpatch overlap = {name for name in mcolors.CSS4_COLORS if f'xkcd:{name}' in mcolors.XKCD_COLORS} fig = plt.figure(figsize=[9, 5]) ax = fig.add_axes((0, 0, 1, 1)) n_groups = 3 n_rows = len(overlap) // n_groups + 1 for j, color_name in enumerate(sorted(overlap)): css4 = mcolors.CSS4_COLORS[color_name] xkcd = mcolors.XKCD_COLORS[f'xkcd:{color_name}'].upper() # Pick text colour based on perceived luminance.
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wikiPython
wikipython.com › tkinter-ttk-tix › summary-information › colors
COLORS – wikiPython
March 22, 2022 - Python has a great many named colors you can choose by using the color’s name. A condensed list of officially recognized symbolic color names can be found in the program below. The page “… more Colors” shows another view, compliments of PySimpleGUI.
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Codú
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Adding Colour To Python Code | by Amy Richardson | Codú
March 15, 2023 - Colorama is a built-in Python module which displays text in different styles and colours.
Top answer
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513

I constantly forget the names of the colors I want to use and keep coming back to this question =)

The previous answers are great, but I find it a bit difficult to get an overview of the available colors from the posted image. I prefer the colors to be grouped with similar colors, so I slightly tweaked the matplotlib answer that was mentioned in a comment above to get a color list sorted in columns. The order is not identical to how I would sort by eye, but I think it gives a good overview.

I updated the image and code to reflect that 'rebeccapurple' has been added and the three sage colors have been moved under the 'xkcd:' prefix since I posted this answer originally.

I really didn't change much from the matplotlib example, but here is the code for completeness.

import matplotlib.pyplot as plt
from matplotlib import colors as mcolors


colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)

# Sort colors by hue, saturation, value and name.
by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), name)
                for name, color in colors.items())
sorted_names = [name for hsv, name in by_hsv]

n = len(sorted_names)
ncols = 4
nrows = n // ncols

fig, ax = plt.subplots(figsize=(12, 10))

# Get height and width
X, Y = fig.get_dpi() * fig.get_size_inches()
h = Y / (nrows + 1)
w = X / ncols

for i, name in enumerate(sorted_names):
    row = i % nrows
    col = i // nrows
    y = Y - (row * h) - h

    xi_line = w * (col + 0.05)
    xf_line = w * (col + 0.25)
    xi_text = w * (col + 0.3)

    ax.text(xi_text, y, name, fontsize=(h * 0.8),
            horizontalalignment='left',
            verticalalignment='center')

    ax.hlines(y + h * 0.1, xi_line, xf_line,
              color=colors[name], linewidth=(h * 0.8))

ax.set_xlim(0, X)
ax.set_ylim(0, Y)
ax.set_axis_off()

fig.subplots_adjust(left=0, right=1,
                    top=1, bottom=0,
                    hspace=0, wspace=0)
plt.show()

Additional named colors

Updated 2017-10-25. I merged my previous updates into this section.

xkcd

If you would like to use additional named colors when plotting with matplotlib, you can use the xkcd crowdsourced color names, via the 'xkcd:' prefix:

plt.plot([1,2], lw=4, c='xkcd:baby poop green')

Now you have access to a plethora of named colors!

Tableau

The default Tableau colors are available in matplotlib via the 'tab:' prefix:

plt.plot([1,2], lw=4, c='tab:green')

There are ten distinct colors:

HTML

You can also plot colors by their HTML hex code:

plt.plot([1,2], lw=4, c='#8f9805')

This is more similar to specifying and RGB tuple rather than a named color (apart from the fact that the hex code is passed as a string), and I will not include an image of the 16 million colors you can choose from...


For more details, please refer to the matplotlib colors documentation and the source file specifying the available colors, _color_data.py.


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348

Matplotlib uses a dictionary from its colors.py module.

To print the names use:

# python2:

import matplotlib
for name, hex in matplotlib.colors.cnames.iteritems():
    print(name, hex)

# python3:

import matplotlib
for name, hex in matplotlib.colors.cnames.items():
    print(name, hex)

This is the complete dictionary:

cnames = {
'aliceblue':            '#F0F8FF',
'antiquewhite':         '#FAEBD7',
'aqua':                 '#00FFFF',
'aquamarine':           '#7FFFD4',
'azure':                '#F0FFFF',
'beige':                '#F5F5DC',
'bisque':               '#FFE4C4',
'black':                '#000000',
'blanchedalmond':       '#FFEBCD',
'blue':                 '#0000FF',
'blueviolet':           '#8A2BE2',
'brown':                '#A52A2A',
'burlywood':            '#DEB887',
'cadetblue':            '#5F9EA0',
'chartreuse':           '#7FFF00',
'chocolate':            '#D2691E',
'coral':                '#FF7F50',
'cornflowerblue':       '#6495ED',
'cornsilk':             '#FFF8DC',
'crimson':              '#DC143C',
'cyan':                 '#00FFFF',
'darkblue':             '#00008B',
'darkcyan':             '#008B8B',
'darkgoldenrod':        '#B8860B',
'darkgray':             '#A9A9A9',
'darkgreen':            '#006400',
'darkkhaki':            '#BDB76B',
'darkmagenta':          '#8B008B',
'darkolivegreen':       '#556B2F',
'darkorange':           '#FF8C00',
'darkorchid':           '#9932CC',
'darkred':              '#8B0000',
'darksalmon':           '#E9967A',
'darkseagreen':         '#8FBC8F',
'darkslateblue':        '#483D8B',
'darkslategray':        '#2F4F4F',
'darkturquoise':        '#00CED1',
'darkviolet':           '#9400D3',
'deeppink':             '#FF1493',
'deepskyblue':          '#00BFFF',
'dimgray':              '#696969',
'dodgerblue':           '#1E90FF',
'firebrick':            '#B22222',
'floralwhite':          '#FFFAF0',
'forestgreen':          '#228B22',
'fuchsia':              '#FF00FF',
'gainsboro':            '#DCDCDC',
'ghostwhite':           '#F8F8FF',
'gold':                 '#FFD700',
'goldenrod':            '#DAA520',
'gray':                 '#808080',
'green':                '#008000',
'greenyellow':          '#ADFF2F',
'honeydew':             '#F0FFF0',
'hotpink':              '#FF69B4',
'indianred':            '#CD5C5C',
'indigo':               '#4B0082',
'ivory':                '#FFFFF0',
'khaki':                '#F0E68C',
'lavender':             '#E6E6FA',
'lavenderblush':        '#FFF0F5',
'lawngreen':            '#7CFC00',
'lemonchiffon':         '#FFFACD',
'lightblue':            '#ADD8E6',
'lightcoral':           '#F08080',
'lightcyan':            '#E0FFFF',
'lightgoldenrodyellow': '#FAFAD2',
'lightgreen':           '#90EE90',
'lightgray':            '#D3D3D3',
'lightpink':            '#FFB6C1',
'lightsalmon':          '#FFA07A',
'lightseagreen':        '#20B2AA',
'lightskyblue':         '#87CEFA',
'lightslategray':       '#778899',
'lightsteelblue':       '#B0C4DE',
'lightyellow':          '#FFFFE0',
'lime':                 '#00FF00',
'limegreen':            '#32CD32',
'linen':                '#FAF0E6',
'magenta':              '#FF00FF',
'maroon':               '#800000',
'mediumaquamarine':     '#66CDAA',
'mediumblue':           '#0000CD',
'mediumorchid':         '#BA55D3',
'mediumpurple':         '#9370DB',
'mediumseagreen':       '#3CB371',
'mediumslateblue':      '#7B68EE',
'mediumspringgreen':    '#00FA9A',
'mediumturquoise':      '#48D1CC',
'mediumvioletred':      '#C71585',
'midnightblue':         '#191970',
'mintcream':            '#F5FFFA',
'mistyrose':            '#FFE4E1',
'moccasin':             '#FFE4B5',
'navajowhite':          '#FFDEAD',
'navy':                 '#000080',
'oldlace':              '#FDF5E6',
'olive':                '#808000',
'olivedrab':            '#6B8E23',
'orange':               '#FFA500',
'orangered':            '#FF4500',
'orchid':               '#DA70D6',
'palegoldenrod':        '#EEE8AA',
'palegreen':            '#98FB98',
'paleturquoise':        '#AFEEEE',
'palevioletred':        '#DB7093',
'papayawhip':           '#FFEFD5',
'peachpuff':            '#FFDAB9',
'peru':                 '#CD853F',
'pink':                 '#FFC0CB',
'plum':                 '#DDA0DD',
'powderblue':           '#B0E0E6',
'purple':               '#800080',
'red':                  '#FF0000',
'rosybrown':            '#BC8F8F',
'royalblue':            '#4169E1',
'saddlebrown':          '#8B4513',
'salmon':               '#FA8072',
'sandybrown':           '#FAA460',
'seagreen':             '#2E8B57',
'seashell':             '#FFF5EE',
'sienna':               '#A0522D',
'silver':               '#C0C0C0',
'skyblue':              '#87CEEB',
'slateblue':            '#6A5ACD',
'slategray':            '#708090',
'snow':                 '#FFFAFA',
'springgreen':          '#00FF7F',
'steelblue':            '#4682B4',
'tan':                  '#D2B48C',
'teal':                 '#008080',
'thistle':              '#D8BFD8',
'tomato':               '#FF6347',
'turquoise':            '#40E0D0',
'violet':               '#EE82EE',
'wheat':                '#F5DEB3',
'white':                '#FFFFFF',
'whitesmoke':           '#F5F5F5',
'yellow':               '#FFFF00',
'yellowgreen':          '#9ACD32'}

You could plot them like this:

import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.colors as colors
import math


fig = plt.figure()
ax = fig.add_subplot(111)

ratio = 1.0 / 3.0
count = math.ceil(math.sqrt(len(colors.cnames)))
x_count = count * ratio
y_count = count / ratio
x = 0
y = 0
w = 1 / x_count
h = 1 / y_count

for c in colors.cnames:
    pos = (x / x_count, y / y_count)
    ax.add_patch(patches.Rectangle(pos, w, h, color=c))
    ax.annotate(c, xy=pos)
    if y >= y_count-1:
        x += 1
        y = 0
    else:
        y += 1

plt.show()
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Michael Currin
michaelcurrin.github.io › dev-cheatsheets › cheatsheets › python › libraries › colors.html
Colors | Dev Cheatsheets
Cheatsheets / Python / Packages / Colors · colour on PyPI. Converts and manipulates common color representation (RGB, HSL, web, …) This isn’t about printing, just switching between formats. >>> from colour import Color >>> c = Color("blue") >>> c <Color blue> >>> c.hex '#00f' >>> c.hsl (0.66..., 1.0, 0.5) >>> c.rgb (0.0, 0.0, 1.0) How to print colored text in Python ·