Quarto Basics

For a demonstration of a line plot on a polar axis, see Figure 1.

1 Colors

• Red
• Green
• Blue

2 Shapes

• Square
• Circle
• Triangle

import numpy as np
import matplotlib.pyplot as plt

r = np.arange(0, 2, 0.01)
theta = 2 * np.pi * r
fig, ax = plt.subplots(
  subplot_kw = {'projection': 'polar'} 
)
ax.plot(theta, r)
ax.set_rticks([0.5, 1, 1.5, 2])
ax.grid(True)
plt.show()

Figure 1

3 Placing Colorbars

Colorbars indicate the quantitative extent of image data. Placing in a figure is non-trivial because room needs to be made for them. The simplest case is just attaching a colorbar to each axes:¹.

import matplotlib.pyplot as plt
import numpy as np

fig, axs = plt.subplots(2, 2)
fig.set_size_inches(20, 8)
cmaps = ['RdBu_r', 'viridis']
for col in range(2):
    for row in range(2):
        ax = axs[row, col]
        pcm = ax.pcolormesh(
          np.random.random((20, 20)) * (col + 1),
          cmap=cmaps[col]
        )
        fig.colorbar(pcm, ax=ax)
plt.show()

Footnotes

1. See the Matplotlib Gallery to explore colorbars further