You have several options to create and display 3D plots within Databricks:

1. Plotly: Plotly is a powerful plotting library that supports 3D visualizations. You can easily integrate Plotly with Databricks notebooks using the displayHTML function.
2. Matplotlib with 3D Projection: Matplotlib, another popular library, can be used to create 3D plots using its mplot3d toolkit. While Databricks doesn’t directly support interactive Matplotlib plots, you can still create static 3D plots.
3. Other Libraries: You can explore Python libraries like Volume or PyVista, which specialize in 3D visualizations and can be integrated with Databricks notebooks.

Example using Plotly:

Python

import plotly.graph_objects as go

# Sample data

z_data = [[1, 20, 30],

          [20, 1, 60],

          [30, 60, 1]]

fig = go.Figure(data=[go.Surface(z=z_data)])

fig.update_layout(title=’3D Surface Plot’, autosize=False,

                  width=500, height=500,

                  margin=dict(l=65, r=50, b=65, t=90))

fig.show()

This code will generate a 3D surface plot using the sample data.

Remember that you might need to install the required libraries (like Plotly) within your Databricks environment using pip install.