First, let's import a few common modules, set a random seed so that the code can produce the same results every time it is executed. We will also ignore non-essential warning.
We will also set the rc params to change the label size for the plots' axes, x- and y-axis ticks using rc method.
matplotlib.rc(group, **kwargs)
group is the grouping for the rc, e.g., for lines.linewidth the group is lines, for axes.facecolor, the group is axes, and so on. Group may also be a list or tuple of group names, e.g., (xtick, ytick).
Import sklearn, Numpy as np, and Pandas as pd
import <<your code goes here>>
import numpy as <<your code goes here>>
import pandas as <<your code goes here>>
Set the random.seed to 42
np.random.seed(<<your code goes here>>)
Import Matplotlib as mpl, and Pyplot as plt
%matplotlib inline
import matplotlib as <<your code goes here>>
import matplotlib.pyplot as <<your code goes here>>
Set the rc params for axes, xtick, and ytick
mpl.rc('axes', labelsize=14)
mpl.<<your code goes here>>('xtick', labelsize=12)
mpl.rc('ytick', labelsize=12)
Finally, we will import warnings and ensure that the non-essential warnings are ignored
import <<your code goes here>>
warnings.filterwarnings(action="ignore", message="^internal gelsd")
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