By setting the ‘color’ argument, we can specify the color of the lines. Following table summarizes the different formats that we can specify a value to the color argument.
Format |
Description |
Color names |
Color names like 'red', 'green', 'blue', 'black', 'white', 'purple', 'orange' can be specified directly. Reference: https://matplotlib.org/2.0.2/api/colors_api.html |
Color abbreviations |
Single character abbreviations are supported. For example, 'r' for red, 'g' for green, 'b' for blue, 'k' for black, 'w' for white, etc. |
Hexadecimal notation |
Color can be specified using a six-digit hexadecimal representation of colors. For example, '#FF0000' represents red, '#00FF00' represents green, and '#0000FF' represents blue. |
RGB notation |
Color can be specified using RGB tuple. For example, (1, 0, 0) represents red, (0, 1, 0) represents green, and (0, 0, 1) represents blue. |
RGBA notation |
Similar to RGB, but it takes an addition value to represent opacity rangin from 0 to 1. |
Examples
# Red color line
plt.plot(x1, y1, color='red', label='red-line')
# Green color line
plt.plot(x2, y2, color='g', label='green-line')
# Blue color line
plt.plot(x3, y3, color='#0000FF', label='blue-line')
# Aqua color line
plt.plot(x4, y4, color=(0, 1, 1), label='aqua-line')
# Red color line with opacity 0.5
plt.plot(x5, y5, color=(1, 0, 0, 0.5), label='red-line-opacity')
Find the below working application.
line_color.py
import matplotlib.pyplot as plt
import numpy as np
# Sample data
x1 = [5, 10, 15, 20, 25]
y1 = [20, 40, 60, 80, 100]
x2 = [10, 20, 30, 40, 50]
y2 = [30, 60, 90, 120, 150]
x3 = [15, 30, 45, 60, 75]
y3 = [8, 16, 24, 32, 40]
x4 = [12, 24, 36, 48, 60]
y4 = [15, 30, 45, 60, 75]
x5 = [8, 16, 24, 32, 40]
y5 = [25, 50, 75, 100, 125]
# Red color line
plt.plot(x1, y1, color='red', label='red-line')
# Green color line
plt.plot(x2, y2, color='g', label='green-line')
# Blue color line
plt.plot(x3, y3, color='#0000FF', label='blue-line')
# Aqua color line
plt.plot(x4, y4, color=(0, 1, 1), label='aqua-line')
# Red color line with opacity 0.5
plt.plot(x5, y5, color=(1, 0, 0, 0.5), label='red-line-opacity')
# Ti display the legend on the plot
plt.legend()
plt.show()
Output
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