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To visualize the relationship between three variables, we generally need a three-dimensional graph. Surface plots are two-dimensional diagrams of three-dimensional data. Surface plots show the functional relationship between independent and dependent variables.

Example of a Surface Plot

In Python, we draw surface plots using matplotlib.

**1. Import libraries**

We don’t need to import the entire matplotlib module, pyplot should be enough. Make sure to import numpy for any mathematics needed for the plot.

```
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
```

**2. Introduce data**

This usually comprises of two independent-variable arrays and a dependent variable array.

```
x = np.arange(0, 25, 1)
y = np.arange(0, 25, 1)
x, y = np.meshgrid(x, y)
z = x + y
```

**3. Draw a plot**

```
fig = plt.figure()
axes = fig.gca(projection ='3d')
axes.plot_surface(x, y, z)
plt.show()
```

import numpy as np # For mathematics, and making arrays import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D # Arrays x, y and z for data plot visualization x = np.arange(0, 25, 1) y = np.arange(0, 25, 1) # meshgrid makes a retangular grid out of two 1-D arrays. x, y = np.meshgrid(x, y) z = x**2 + y**2 # x^2+y^2 # surface plot for x^2 + y^2 fig = plt.figure() # creates space for a figure to be drawn # Uses a 3d prjection as model is supposed to be 3D axes = fig.gca(projection ='3d') # Plots the three dimensional data consisting of x, y and z axes.plot_surface(x, y, z) # show command is used to visualize data plot plt.show()

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