Dataframe 0.13 Help

Working with Data Schemas

The Kotlin Dataframe library provides typed data access via generation of extension properties for type DataFrame<T>, where T is a marker class that represents DataSchema of DataFrame.

Schema of DataFrame is a mapping from column names to column types of DataFrame. It ignores order of columns in DataFrame, but tracks column hierarchy.

In Jupyter environment compile-time DataFrame schema is synchronized with real-time data after every cell execution.

In IDEA projects, you can use the Gradle plugin to extract schema from the dataset and generate extension properties.

Here's a list of the most popular use cases with Data Schemas.

Last modified: 29 March 2024