Matplotlib.colors.to_rgb() in Python

Last Updated : 25 Apr, 2025

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.colors.to_rgb()

The matplotlib.colors.to_rgb() function is used convert c (ie, color) to an RGB color. It converts the color name into a array of RGB encoded colors. It returns an RGB tuple of three floats from 0-1.

Syntax: matplotlib.colors.to_rgb(c)
Parameters:

c: This accepts a string that represents the name of the color. It can be an RGB or RGBA sequence or a string in any of several forms:
a hex color string, like ‘#000FFF’

a standard name, like ‘green’

a letter from the set ‘rgbcmykw’

a string representation of a float, like ‘0.4’, indicating gray on a 0-1 scale

Example 1:

Python3

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


# helper function to plot a color table
def colortable(colors, title, colors_sort = True, emptycols = 0):
 
    # cell dimensions
    width = 212
    height = 22
    swatch_width = 48
    margin = 12
    topmargin = 40
 
    # Sorting colors based on hue, saturation,
    # value and name.
    if colors_sort is True:
        to_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))),
                         name)
                        for name, color in colors.items())
        
        names = [name for hsv, name in to_hsv]
        
    else:
        names = list(colors)
 
    length_of_names = len(names)
    length_cols = 4 - emptycols
    length_rows = length_of_names // length_cols + int(length_of_names % length_cols > 0)
 
    width2 = width * 4 + 2 * margin
    height2 = height * length_rows + margin + topmargin
    dpi = 72
 
    figure, axes = plt.subplots(figsize =(width2 / dpi, height2 / dpi), dpi = dpi)
    figure.subplots_adjust(margin / width2, margin / height2,
                        (width2-margin)/width2, (height2-topmargin)/height2)
    
    axes.set_xlim(0, width * 4)
    axes.set_ylim(height * (length_rows-0.5), -height / 2.)
    axes.yaxis.set_visible(False)
    axes.xaxis.set_visible(False)
    axes.set_axis_off()
    axes.set_title(title, fontsize = 24, loc ="left", pad = 10)
 
    for i, name in enumerate(names):
        
        rows = i % length_rows
        cols = i // length_rows
        y = rows * height
 
        swatch_start_x = width * cols
        swatch_end_x = width * cols + swatch_width
        text_pos_x = width * cols + swatch_width + 7
 
        axes.text(text_pos_x, y, name, fontsize = 14,
                horizontalalignment ='left',
                verticalalignment ='center')
 
        axes.hlines(y, swatch_start_x, swatch_end_x,
                  color = colors[name], linewidth = 18)
 
    return figure
 
colortable(mcolors.BASE_COLORS, "Base Colors",
                colors_sort = False, emptycols = 1)
colortable(mcolors.TABLEAU_COLORS, "Tableau Palette",
                colors_sort = False, emptycols = 2)
colortable(mcolors.CSS4_COLORS, "CSS Colors")
 
plt.show()

Output:

Example 2:

Python3

from matplotlib import colors
import matplotlib.pyplot as plt


alpha = 0.5

kwargs = dict(edgecolors ='none', s = 3900, marker ='s')

for i, color in enumerate(['pink', 'brown', 'green']):

    rgb = colors.to_rgb(color)
    plt.scatter([i], [0], color = color, **kwargs)
    plt.scatter([i], [1], color = color, 
                alpha = alpha, **kwargs)
    plt.scatter([i], [2], color = rgb, **kwargs)