Enhancing Data Visualizations with Matplotlib's Color Options

Matplotlib is a versatile library that offers a variety of unique features and functionalities for creating captivating visualizations. In this guide, we'll explore features to add color to our plots!

Installing Matplotlib

First, if not already done, install the Matplotlib library:

pip install matplotlib
Installing Matplotlib using pip

Alternative Approaches

Sometimes pip will not configure correctly in your environment. In such cases, alternative approaches can be used for installation. Here are two methods:

Using py:

py -m pip install matplotlib
Installing Matplotlib using py

Using python3:

python3 -m pip install matplotlib
Installing Matplotlib using python3

Importing Matplotlib

Once installed, you can import the Matplotlib library:

import matplotlib.pyplot as plt
Importing Matplotlib

Four Methods for Changing Color Using Matplotlib

The color of plots in Matplotlib is set to blue by default.

import matplotlib.pyplot as plt 
x = [1,2,3,4] # Example x values
y = [5,10,15,20] # Example y values
plt.xlabel('x-axis') # Labeling the x-axis
plt.ylabel('y-axis') # Labeling the y-axis
plt.plot(x,y) # Plotting the line chart
plt.show() # Viewing the line chart

Line Chart Using matplotlib

Creating a default line chart using Matplotlib

Below, we will explore four methods to change color in line charts. Keep in mind this can be used in other plot functions.

Example 1: Change Color Using Color Names

We can add a color parameter to different plotting functions plt.plot(), plt.scatter(), plt.bar() to specify the color of lines, markers, or bars.

import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [5,10,15,20]
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(x,y, color = 'purple') # Assigning purple to the color parameter
plt.show()

Line Chart Using matplotlib

Creating a colored line chart using color names

In this example, a color name was assigned to the color parameter:
color = 'purple'.

Example 2: Change Color Using Color Codes

Matplotlib also lets you use single-character abbreviations to represent colors.

Below are the color codes available for use:

  • 'b': blue
  • 'g': green
  • 'r': red
  • 'c': cyan
  • 'm': magenta
  • 'y': yellow
  • 'k': black
  • 'w': white
import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [5,10,15,20]
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(x,y, color = 'r') # Using the color code 'r'
plt.show()

Line Chart Using matplotlib

Creating a colored line chart using color codes

In this example, the color code 'r' was assigned to the color parameter to make the line red.

Example 3: Change Color Using RGB Values

RGB (Red, Green, Blue) values can be used to specify custom colors. RGB values are specified as tuples where each component ranges from 0 to 1.

  • (1, 0, 0) = red
  • (0, 1, 0) = green
  • (0, 0, 1) = blue

We can create intermediate colors by adjusting the amounts of red, green, and blue components. For instance, (1, 0.5, 0) represents full red, half green, and no blue, resulting in an orange color. Here is the resulting plot using RGB:

import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [5,10,15,20]
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(x,y, color=(1, 0.5, 0)) # Using the RGB value for orange
plt.show()

Line Chart Using matplotlib

Creating a colored line chart using RGB values

Example 4: Change Color Using Hexadecimal Color Codes

Hexadecimal color codes, or hex color codes, offer a wide range of custom colors for our plots. Each code is composed of six characters, combining numbers from 0 to 9 and letters from A to F. These codes represent different intensities of red, green, and blue, allowing us to create unique and customized color palettes for our visualizations.

Below, we will explore two examples:

  1. #008080 represents teal:
  • The first two digits 00 represent the absence of red.
  • The next two digits 80 represent maximum intensity of green.
  • The final two digits 80 represent maximum intensity of blue.
  • Combining these, we get a teal color.
import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [5, 10, 15, 20]
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(x, y, color='#008080')  # Using the hex color code for teal
plt.show()

Line Chart Using matplotlib

Creating a colored line chart using hex color codes
  1. #FFA500 represents orange:
  • The first two digits FF mean maximum intensity of red.
  • The next two digits A5 represent a specific intensity of green.
  • The final two digits 00 mean no blue color contribution.
  • Combining these, you get an orange color.
import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [5, 10, 15, 20]
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(x, y, color= '#FFA500')  # Using the hex color code for orange
plt.show()

Line Chart Using matplotlib

Creating a colored line chart using hex color codes

Conclusion

Matplotlib offers various ways to change colors in plots through color names, color codes, RGB values, and hexadecimal codes. Learning these methods can help make your plots more engaging, clear, and visually appealing. Happy plotting!