Databricks 3D Visualization


          Databricks 3D Visualization

However, you can achieve 3D visualizations using Databricks in a couple of ways:

  1. Export and Visualize:
  • Export your processed data from Databricks (e.g., as a CSV file).
  • Use external 3D visualization tools like Plotly, Matplotlib (with mplot3d), or specialized libraries like Mayavi to create and display your 3D plots.
  1. Integrate with 3D Visualization Platforms:
  • Connect Databricks to platforms like Power BI or Tableau, which have robust 3D visualization capabilities.
  • Push your Databricks data into these platforms and leverage their tools to build interactive 3D visuals.

Example: 3D Scatter Plot using Plotly (Python)

Assuming you have your data in a Databricks DataFrame, you can follow these steps:

  1. Export Data: Convert your DataFrame to a Pandas DataFrame and export it as a CSV.


import pandas as pd


# Assuming ‘df‘ is your Databricks DataFrame

pandas_df = df.toPandas()

pandas_df.to_csv(“data.csv”, index=False)

  1. Create 3D Plot using Plotly:


import as px


df = pd.read_csv(“data.csv”)

fig = px.scatter_3d(df, x=’x_column’, y=’y_column’, z=’z_column’)


Additional Notes:

  • You might need to install required libraries (like Plotly) within your Databricks environment.
  • The choice of method depends on your specific requirements, data size, and preferred tools.

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



Unogeeks is the No.1 IT Training Institute for Databricks Training. Anyone Disagree? Please drop in a comment

You can check out our other latest blogs on Databricks Training here – Databricks Blogs

Please check out our Best In Class Databricks Training Details here – Databricks Training

 Follow & Connect with us:


For Training inquiries:

Call/Whatsapp: +91 73960 33555

Mail us at:

Our Website ➜

Follow us:





Leave a Reply

Your email address will not be published. Required fields are marked *