How to interpolate more points without losing the shape of the image

Question

I am making a polygon shape do the a simulation with matplotlib and using plt.fill to fill in the shape. What I want to do is to increase the number of points for x and y without losing the shape. But when I try to interpolate the shape is lot.

from scipy.interpolate import interp1d
import pandas as pd
import matplotlib.pyplot as plt


var = pd.read_excel("pathtotheexcel\lens1.ods", engine="odf")


x = list(var['x'])
y = list(var['y'])


#Plotting original image
plt.fill(x, y, 'k')
plt.show()


#Doing interpolation
f = interp1d(x, y, kind='nearest')
xnew = np.linspace(min(x), max(x), 1000000)

plt.plot(xnew, f(xnew))
fig, (ax1, ax2) = plt.subplots(1, 2)


ax1.plot(x, y)
ax1.set_title('Without Interpolate')
ax2.plot(xnew, f(xnew))
ax2.set_title('With Interpolation')
fig.show()

The attached is the plot of the differences.

As you can see on the right there are some "jiggling" with the interpolation. How can I get a smoother plot with more points? I want to increase the number of points for both x and y coordinates without losing the shape of the plot.

You can find the lens data for plotting here