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Parallel Coordinates in Matplotlib
  • Last Updated : 24 Jan, 2021

In this article, we will learn How to Plot Parallel Coordinates in Matplotlib. So, first discuss some concepts :

  • Matplotlib may be a tremendous visualization library in Python for 2D plots of arrays. Matplotlib could also be a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter within the year 2002.
  • One of the best benefits of visualization is that it allows us visual access to large amounts of knowledge in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc.
  • Parallel coordinates may be a method for exploring the spread of multidimensional data on a categorical response, and taking a look at whether there’re any trends to the features.
  • Two and three-dimensional data are often viewed relatively straight-forwardly using traditional plot types. Even with four dimensional data, we will often find how to display the info.

Steps Needed 

  1. Import libraries (matplotlib)
  2. Create / Load data
  3. Make subplots with share y-axes equal to False
  4. Plot all the subplots
  5. Set x-axis limit for x-axis labels
  6. Make the width space zero
  7. Show the plot for final output

Examples

Here, we will discuss some examples by applying above mentioned steps. In these examples, we will work on dummy data in linear and multi-dimensions.

Example 1: (Simple Parallel Coordinate Plot)

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# import packages
import matplotlib.pyplot as plt
  
# create data
x=[1,2,3,4,5]
y=[2,4,1,5,3]
  
# make subplots
fig,(ax1,ax2) = plt.subplots(1, 2, sharey=False)
  
# plot the subplots
ax1.plot(x,y)
ax2.plot(x,y)
  
# set x limits
ax1.set_xlim([ x[0],x[2]])
ax2.set_xlim([ x[2],x[4]])
  
# set width space to zero
plt.subplots_adjust(wspace=0)
  
# show the plots
plt.show()

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Output:



Example 2: (Parallel Coordinate Plot with multiple lines and multiple axes)

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# import packages
import matplotlib.pyplot as plt
  
# create data
x=[1,2,3,4,5,6,7,8,9]
y1=[2,4,1,5,3,4,2,5,2]
y2=[3,4,3,5,2,6,4,2,3]
  
# make subplots
fig, (ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8) = plt.subplots(1, 8, sharey=False)
ax = (ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8)
  
# plot subplots and set xlimit
for i in range(8):
    ax[i].plot(x,y1,'g-.',x,y2,'r--')
    ax[i].set_xlim([ x[i],x[i+1]])
  
# set width space to zero
plt.subplots_adjust(wspace=0)
  
# show plot
plt.show()

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Output :

Example 3: (Parallel Coordinate Plot over multi-dimensions data)

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# import packages
import numpy as np
import matplotlib.pyplot as plt
  
# create data
x = np.arange(1,6)
data = [x,x*2,x*x,np.sqrt(x),-x*x,np.sin(x),np.cos(x)]
print(data)
  
# make subplots
fig, (ax1,ax2,ax3,ax4) = plt.subplots(1, 4, sharey=False)
ax = (ax1,ax2,ax3,ax4)
  
# plot subplots and set xlimit
for i in range(4):
    for j in range(len(data)):
        ax[i].plot(data[0],data[j])
    ax[i].set_xlim([x[i],x[i+1]])
  
# set width space to zero
plt.subplots_adjust(wspace=0)
  
# show plot
plt.show()

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Output :


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