Despite being one of the most popular frameworks for data analysis, pandas isn’t distributed and can’t process TB of data. Databricks solves this issue by allowing users to leverage pandas API while processing the data with Spark distributed engine. This demo shows you how to process big data using pandas API (previously known as Koalas).

To install the demo, get a free Databricks workspace and execute the following two commands in a Python notebook

%pip install dbdemos

import dbdemos
dbdemos.install('pandas-on-spark')

Dbdemos is a Python library that installs complete Databricks demos in your workspaces. Dbdemos will load and start notebooks, Delta Live Tables pipelines, clusters, Databricks SQL dashboards, warehouse models … See how to use dbdemos

Dbdemos is distributed as a GitHub project.

For more details, please view the GitHub README.md file and follow the documentation.
Dbdemos is provided as is. See the License and Notice for more information.
Databricks does not offer official support for dbdemos and the associated assets.
For any issue, please open a ticket and the demo team will have a look on a best-effort basis.