Create Stunning 3D Plots in Python with Matplotlib: Lines, Scatter, and Surfaces

3D Line Plot

<code># 3D line plot
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

# generate canvas
fig = plt.figure()
ax = fig.gca(projection='3d')  # specify 3D projection

# generate (x, y, z) data
theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
z = np.linspace(-2, 2, 100)
r = z ** 2 + 1
x = r * np.sin(theta)
y = r * np.cos(theta)

# draw plot (same plot function as 2D)
ax.plot(x, y, z)
plt.show()
</code>

3D Scatter Plot

<code># 3D scatter plot
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

# generate canvas
fig = plt.figure()
ax = fig.gca(projection='3d')  # specify 3D projection

# draw 100 red points
x1 = np.random.random(100) * 20
y1 = np.random.random(100) * 20
z1 = x1 + y1
ax.scatter(x1, y1, z1, c='r', marker='o')

# draw 100 blue points
x2 = np.random.random(100) * 20
y2 = np.random.random(100) * 20
z2 = x2 + y2
ax.scatter(x2, y2, z2, c='b', marker='^')

plt.show()
</code>

3D Surface Plot

<code># 3D surface plot
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np

# generate canvas
fig = plt.figure()
ax = fig.gca(projection='3d')  # specify 3D projection

# generate data (x, y, z)
x = np.arange(-5, 5, 0.25)
y = np.arange(-5, 5, 0.25)
x, y = np.meshgrid(x, y)  # key: use meshgrid to create coordinate grid
z = np.sin(np.sqrt(x ** 2 + y ** 2))

# use plot_surface function (cmap=cm.coolwarm sets color map)
surf = ax.plot_surface(x, y, z, cmap=cm.coolwarm)
plt.show()
</code>