 # Getting Stared with Matplotlib - Create 3D Projections using Matplotlib

Creating 3D projections in Matplotlib is very simple. You need to import `Axes3D`, which registers the `"3d"` projection. Then create a subplot setting the `projection` to `"3d"`. This returns an `Axes3DSubplot` object, which you can use to call `plot_surface`, giving x, y, and z coordinates, plus optional attributes.

INSTRUCTIONS
• Import `Axes3D`:

``````from mpl_toolkits.mplot3d import << your code goes here >>
``````
• Import other libraries

``````import numpy as np
import matplotlib.pyplot as plt
import matplotlib
``````
• Create the projection:

``````x = np.linspace(-5, 5, 50)
y = np.linspace(-5, 5, 50)
X, Y = np.meshgrid(x, y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
``````

Here, `linspace` returns evenly spaced numbers over a specified interval. `meshgrid` returns coordinate matrices from coordinate vectors.

• Finally, we will create the `figure`, the subplot, and call the `plot_surface` with the coordinates we created earlier:

``````figure = plt.figure(1, figsize = (12, 4))
subplot3d = plt.subplot(111, projection='3d')
surface = subplot3d.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=matplotlib.cm.coolwarm, linewidth=0.1)
plt.show()
``````

The `figure` module provides the top-level Artist , the Figure , which contains all the plot elements. The `figsize` marks the `width` and `height` of the plot.

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