Ibis Cheat Sheet

Updated 2026-03-19

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Ibis is a portable Python dataframe library that provides a backend-agnostic API for data manipulation and analytics across 20+ execution engines including DuckDB, BigQuery, PostgreSQL, Snowflake, Spark, and Polars. Unlike pandas which operates in-memory, Ibis uses lazy evaluation to compile Python expressions into optimized SQL or engine-native code, enabling scalable analytics on massive datasets without loading data into memory. The key insight: write transformation logic once in a pandas-like API, then execute it on any supported backend—from local DuckDB for prototyping to cloud data warehouses for production—without rewriting code.

What This Cheat Sheet Covers

This topic spans 17 focused tables and 140 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Backend Connection and ConfigurationTable 2: Table Selection and ProjectionTable 3: Filtering and Row OperationsTable 4: Aggregations and GroupingTable 5: Joins and Set OperationsTable 6: Window Functions and AnalyticsTable 7: String OperationsTable 8: Date and Time OperationsTable 9: Data Type OperationsTable 10: Conditional LogicTable 11: Array and JSON OperationsTable 12: Schema and MetadataTable 13: Execution and MaterializationTable 14: User-Defined FunctionsTable 15: Advanced OperationsTable 16: Backend-Specific FeaturesTable 17: Installation and Configuration

Table 1: Backend Connection and Configuration

Method	Example	Description
ibis.duckdb.connect()	`con = ibis.duckdb.connect()` `con = ibis.duckdb.connect("db.duckdb")`	• Connect to in-memory DuckDB or persistent database file • DuckDB is the default backend for local development.
ibis.bigquery.connect()	`con = ibis.bigquery.connect(` `project_id="my-project"` `)`	• Connect to Google BigQuery • requires project_id and authentication via service account or user credentials.
ibis.postgres.connect()	`con = ibis.postgres.connect(` `host="localhost",` `database="mydb"` `)`	• Connect to PostgreSQL database • supports standard connection parameters including host, port, user, password, and database.
ibis.snowflake.connect()	`con = ibis.snowflake.connect(` `account="xy12345",` `user="name"` `)`	• Connect to Snowflake data warehouse using account identifier and authentication • supports SSO and key-pair authentication.
ibis.connect()	`con = ibis.connect("duckdb://mydb.db")` `con = ibis.connect("postgres://localhost/db")`	• Universal connection method that infers backend from connection string URI • simplifies multi-backend workflows.

Table 1: Backend Connection and Configuration

Method	Example	Description
ibis.duckdb.connect()	`con = ibis.duckdb.connect()` `con = ibis.duckdb.connect("db.duckdb")`	• Connect to in-memory DuckDB or persistent database file • DuckDB is the default backend for local development.
ibis.bigquery.connect()	`con = ibis.bigquery.connect(` `project_id="my-project"` `)`	• Connect to Google BigQuery • requires project_id and authentication via service account or user credentials.
ibis.postgres.connect()	`con = ibis.postgres.connect(` `host="localhost",` `database="mydb"` `)`	• Connect to PostgreSQL database • supports standard connection parameters including host, port, user, password, and database.
ibis.snowflake.connect()	`con = ibis.snowflake.connect(` `account="xy12345",` `user="name"` `)`	• Connect to Snowflake data warehouse using account identifier and authentication • supports SSO and key-pair authentication.
ibis.connect()	`con = ibis.connect("duckdb://mydb.db")` `con = ibis.connect("postgres://localhost/db")`	• Universal connection method that infers backend from connection string URI • simplifies multi-backend workflows.