Named colors in matplotlib Named colors in matplotlib python python

Named colors in matplotlib


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.

enter image description here

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

import matplotlib.pyplot as pltfrom matplotlib import colors as mcolorscolors = 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 = 4nrows = n // ncolsfig, ax = plt.subplots(figsize=(12, 10))# Get height and widthX, Y = fig.get_dpi() * fig.get_size_inches()h = Y / (nrows + 1)w = X / ncolsfor 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!

enter image description here

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:

enter image description here

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.



Matplotlib uses a dictionary from its colors.py module.

To print the names use:

# python2:import matplotlibfor name, hex in matplotlib.colors.cnames.iteritems():    print(name, hex)# python3:import matplotlibfor 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 pltimport matplotlib.patches as patchesimport matplotlib.colors as colorsimport mathfig = plt.figure()ax = fig.add_subplot(111)ratio = 1.0 / 3.0count = math.ceil(math.sqrt(len(colors.cnames)))x_count = count * ratioy_count = count / ratiox = 0y = 0w = 1 / x_counth = 1 / y_countfor 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 += 1plt.show()


In addition to BoshWash's answer, here is the picture generated by his code:

Named colors


matomo