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 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 pltalpha = 0.5kwargs = 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:
