Learn how Deephaven works
You will build analytics and applications with both updating (streaming) and static (batch) data sets, become familiar with the Deephaven IDE experience, apply your Python functions to your data, build a dashboard, create a notebook, and build and launch a stand-alone application. With a bit more time, you’ll then develop a Python client application that uses the API to receive data from your server application.
3. Create columns & merge tables
Examine metadata, cast types, create new columns, and combine static and updating tables.
5. Filter, join, & as-of join
Perform as-of and classic joins based on a variety of key combinations.
The goal of this tutorial is to help you create a mental model for how Deephaven works and to introduce you to its capabilities and workflows.