3D graphs with Matplotlib

Hello and welcome to a 3D graphing in Matplotlib tutorial. Three dimensional graphing in Matplotlib is already built in, so we do not need to download anything more. First, we need to bring in some integral modules:

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt

The axes3d is used since it takes a different kind of axis in order to actually graph something in three dimensions. Next:

fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')

Here, we define the figure as usual, and then we define the ax1 as a typical subplot, just with a 3d projection this time. We need to do this in order to alert Matplotlib that we're about to throw three dimensional data at it.

Now let's create some 3D data:

x = [1,2,3,4,5,6,7,8,9,10]
y = [5,6,7,8,2,5,6,3,7,2]
z = [1,2,6,3,2,7,3,3,7,2]

Next, we plot it. First, let's show a simple wire frame example:

ax1.plot_wireframe(x,y,z)

Finally:

ax1.set_xlabel('x axis')
ax1.set_ylabel('y axis')
ax1.set_zlabel('z axis')

plt.show()

Our full code is:

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import style

style.use('fivethirtyeight')

fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')

x = [1,2,3,4,5,6,7,8,9,10]
y = [5,6,7,8,2,5,6,3,7,2]
z = [1,2,6,3,2,7,3,3,7,2]

ax1.plot_wireframe(x,y,z)

ax1.set_xlabel('x axis')
ax1.set_ylabel('y axis')
ax1.set_zlabel('z axis')

plt.show()

The result here (including adding the use of a style):

These 3D graphs can be interacted with. First, you can use the left mouse click to click and drag in order to move the graph around. You can also use the right mouse button to click and drag in or out to zoom in or out.

The next tutorial: 3D Scatter Plot with Matplotlib