malloy-patterns

Malloy patterns documentation provides indexed access to common analytical patterns like year-over-year, cohorts, and percent of total calculations. You can discover and implement these patterns directly in your Malloy models for data processing and visualization tasks.

Yes, Malloy supports database dialects like BigQuery, DuckDB, PostgreSQL, and Snowflake. This Skill provides indexed documentation detailing how Malloy's language reference, queries, and rendering features operate across these supported database platforms.

The best way to learn Malloy language reference is through this Skill's indexed documentation, which covers sources, queries, views, fields, aggregates, joins, filters, expressions, and functions. It organizes these topics for quick discovery and implementation in your data models.

To render data visualizations in Malloy, this Skill indexes documentation topics covering rendering options and visualization techniques. You can explore these indexed topics to understand and implement visual outputs for your Malloy models and queries.

Yes, you can use Malloy with Jupyter notebooks and the Python package. This Skill indexes documentation on notebooks, the Python package, MalloySQL, and Jupyter integration to help you configure and execute your Malloy data processing workflows.

For Malloy multi-file projects, this Skill indexes documentation on imports, computed sources, and access modifiers. You can use these indexed topics to understand how to structure, import, and manage complex Malloy models across multiple files.