DUCKDB: EMBEDDED ANALYTICS FOR DATA SCIENTISTS AND PYTHON DEVELOPERS: Process Gigabytes Locally with SQL, Pandas Integration and Real-World Projects
Format:
Hardcover
En stock
0.87 kg
Sí
Nuevo
Amazon
USA
- Run serious analytics on your laptop with fast, honest SQL that works with your Python tools.Many data scientists feel stuck between slow notebooks and heavyweight warehouses. This book shows a clean local-first path with DuckDB: query files directly, work bigger than RAM with predictable spilling, and keep results reproducible without servers.You will set up a reliable Python environment, use SQL alongside pandas, Arrow, and Polars, and apply patterns that hold up in production. Each chapter focuses on real workflows, from files and lakehouse formats to extensions that solve concrete problems.Replacement scans that query pandas Arrow and Polars in placeRelational API pipelines in Python with clear step by step compositionWindow functions partitions frames and QUALIFY for practical analyticsAsOf joins for time aligned data and recursive CTEs for graphsWork bigger than RAM with memory_limit temp_directory and spill controlCSV Parquet JSON Arrow over local and remote HTTP and S3Iceberg reads and writes Delta reads with deletion vector notes and DuckLake tasksIndexes statistics and pruning plus trustworthy EXPLAIN ANALYZEJSON table functions BM25 full text search vector search with VSS and HNSWSpatial analytics with GEOMETRY and R tree indexesSecrets and connectors Excel SQLite httpfs S3 AzureMotherDuck sessions data movement query differences and dbt adapter guidanceDuckDB WASM for browser analytics with embedded Parquet and uploadsProjects that tie it together hybrid log search feature store geospatial proximity and a local Parquet lakeOperations playbook profiling testing packaging versioning and safe upgradesThis is a code heavy guide. You get working SQL and Python snippets that you can paste into notebooks and scripts to build real projects end to end.Grab your copy today and make local analytics fast reliable and repeatable.
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