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In Python, libraries like Matplotlib and Plotly support CSS named colors, allowing you to style plots using human-readable color names instead of hex codes. These names follow the standard HTML/CSS color specification, making them easy to remember and use.
Example: Using CSS Colors in Matplotlib
import matplotlib.pyplot as pltcolors = ['royalblue', 'tomato', 'gold', 'seagreen']plt.bar(['A', 'B', 'C', 'D'], [5, 7, 3, 8], color=colors)plt.title("Bar Chart with CSS Colors")plt.show()Copied!✕CopyThis will render a bar chart where each bar uses a different CSS color name.
Using CSS Colors in Plotly Plotly also supports all standard CSS color names for properties like marker_color or line_color.
import plotly.graph_objects as gofig = go.Figure([go.Bar(x=['Jan', 'Feb', 'Mar'],y=[20, 14, 25],marker_color='mediumseagreen' # Named CSS color)])fig.show()Copied!✕CopyHere, mediumseagreen is directly recognized without needing RGB or hex values.
python - Named colors in matplotlib - Stack Overflow
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Code sample
colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)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)...Supported CSS Colors in Python - Plotly
Detailed examples of Supported CSS Colors including changing color, size, log axes, and more in Python.
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