Matplotlib.colors.to_rgb() in Python

07 Oct, 2021
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. 
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  
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  
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 pltimport matplotlib.colors as mcolors  # helper function to plot a color tabledef 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 colorsimport 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)
Output: 
 
adnanirshad158
Python-matplotlib
Python
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