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.
In this article, the task is to mark different color points in a graph based on a condition that the values of the elements of the list say x is less than or equal to 7 should be colored in blue and those greater should be colored magenta. The idea is to plot a graph having points grouped under one condition in different colors, basically to group the clusters in one color. For this, we run a loop for all values of x and assign a color value to the corresponding value of x. A list will be made of blue and magenta colors specifying the color at the ith index.
Below is the implementation.
import numpy as npimport matplotlib.pyplot as plt # values of xx = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) # values of yy = np.array([10, 9, 8, 7, 6, 5, 4, 3, 2, 1]) # empty list, will hold color value# corresponding to xcol =[] for i in range(0, len(x)): if x[i]<7: col.append('blue') else: col.append('magenta') for i in range(len(x)): # plotting the corresponding x with y # and respective color plt.scatter(x[i], y[i], c = col[i], s = 10, linewidth = 0) plt.show() |
Output:
