Skip to main content

Menu

LEVEL 0
0/5 XP
HomeAboutTopicsPricingMy VaultStats

Categories

🤖 Artificial Intelligence
☁️ Cloud and Infrastructure
💾 Data and Databases
💼 Professional Skills
🎯 Programming and Development
🔒 Security and Networking
📚 Specialized Topics
DATA_AND_DATABASES
HomeAboutTopicsPricingMy VaultStats
LEVEL 0
0/5 XP
GitHub
© 2026 CheatGrid™. All rights reserved.
Privacy PolicyTerms of UseAboutContact

DuckDB for Analytical Data Science Cheat Sheet

DuckDB for Analytical Data Science Cheat Sheet

Back to Data ScienceUpdated 2026-05-15

DuckDB is an in-process analytical database designed for OLAP workloads without server management — think SQLite for analytics. It runs directly within your Python, R, or CLI environment, offering columnar storage, vectorized execution, and zero-copy integration with pandas, Polars, and Apache Arrow. Unlike traditional databases, DuckDB executes queries in-memory with automatic spill-to-disk for larger-than-RAM datasets, enabling fast aggregations, window functions, and complex analytical queries on CSV, Parquet, JSON, and cloud storage (S3/GCS) without ETL.

What This Cheat Sheet Covers

This topic spans 26 focused tables and 143 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Database Connection & InitializationTable 2: Reading Data FilesTable 3: Python API Relation MethodsTable 4: Window FunctionsTable 5: Aggregate FunctionsTable 6: Data Types (Nested)Table 7: Table FunctionsTable 8: User-Defined Functions (UDFs)Table 9: Prepared StatementsTable 10: ExtensionsTable 11: Cloud Storage IntegrationTable 12: JOIN TypesTable 13: Transaction ManagementTable 14: Query Optimization & AnalysisTable 15: Import/Export OperationsTable 16: Date & Time FunctionsTable 17: String & Pattern MatchingTable 18: Performance ConfigurationTable 19: Common Table Expressions (CTEs)Table 20: Advanced SQL FeaturesTable 21: SamplingTable 22: Conditional ExpressionsTable 23: Sorting & OrderingTable 24: JSON FunctionsTable 25: Spatial Functions (Extension)Table 26: Comparison with Other Databases

Table 1: Database Connection & Initialization

MethodExampleDescription
duckdb.connect()
con = duckdb.connect()
Creates an in-memory database connection; data lost when process ends.
duckdb.connect() persistent
con = duckdb.connect('db.duckdb')
Opens or creates a persistent database file on disk; survives process restarts.
duckdb.connect() read-only
con = duckdb.connect('db.duckdb', read_only=True)
Opens database in read-only mode; multiple read-only connections allowed across processes.

More in Data Science

  • Design of Experiments (DOE) Cheat Sheet
  • Econometrics Cheat Sheet
  • AB Testing and Online Experimentation Cheat Sheet
  • GeoPandas Cheat Sheet
  • OpenRefine Cheat Sheet
  • SciPy Cheat Sheet
View all 47 topics in Data Science