Semantic layer
Turn raw data into semantic-enhanced and clean dataframes
PandasAI 3.0 is currently in beta. This documentation reflects the latest features and functionality, which may evolve before the final release.
PandasAI 3.0 introduces a new feature: the semantic layer, which allows you to turn raw data into semantic-enhanced and clean dataframes, making it easier to work with and analyze your data.
What’s the Semantic Layer?
The semantic layer allows you to turn raw data into dataframes you can ask questions to as conversational AI dashboards. It serves several important purposes:
- Data configuration: Define how your data should be loaded and processed
- Semantic information: Add context and meaning to your data columns
- Data transformation: Specify how data should be cleaned and transformed
How to start using the Semantic Layer?
In order to use the semantic layer, you need to create a new schema for each dataset you want to work with. If you want to learn more about how to create a semantic layer schema, check out how to create a semantic layer schema.