Machine learning deals with creating models from data, and generalizing on never before seen data. The data provided to a machine learning model as input should be such that it should be understood by the system properly, so that it can interpret the data and produce results.
Visualizing data is an important step since it helps understand what is going on in the data without actually looking at the numbers and performing complicated computations.
This interface helps in customizing and controlling the kind of data and how it behaves when certain filters are applied to it. The ‘despine’ function can be used to remove the background axis spines while displaying the data visually on the console. Let us see an example to remove the background axis spines −
import numpy as np from matplotlib import pyplot as plt def sin_plot(flip=1): x = np.linspace(0, 14, 99) for i in range(1, 5): plt.plot(x, np.sin(x + i * .59) * (11 - i) * flip) import seaborn as sb sb.set_style("white") print("The data is being plotted ") sin_plot() sb.despine() plt.show()