Name: Transitioning SQL to dplyr: A Query-by-Query Guide for SQL Professionals Moving to R
SKU: 68914529
Price: 15.49 EUR
Availability: InStock
Author: Darmawikarta, Djoni
ISBN: 9798171937591

portada Transitioning SQL to dplyr: A Query-by-Query Guide for SQL Professionals Moving to R

Transitioning SQL to dplyr: A Query-by-Query Guide for SQL Professionals Moving to R

Type

Physical Book

Publisher

Independently published

Author

Darmawikarta, Djoni

Format

Paperback

ISBN13

9798171937591

Transitioning SQL to dplyr: A Query-by-Query Guide for SQL Professionals Moving to R

Darmawikarta, Djoni (Author) · Independently published · Paperback

New Book Imported to Austria

Delivery: 20 Oct - 22 Oct

15,49 €

Import costs and 10% VAT included in the price ✅

15,49 €

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Synopsis "Transitioning SQL to dplyr: A Query-by-Query Guide for SQL Professionals Moving to R"

If you already know SQL, you already know how to think about data — you just don't yet know how to say it in R. Transitioning SQL to dplyr is built entirely around that premise. Rather than teaching the tidyverse from first principles, it takes every clause, keyword, and pattern a working SQL professional already relies on — SELECT, WHERE, GROUP BY, JOIN, HAVING, window functions, CTEs, INSERT, UPDATE, DELETE, and more — and shows its direct dplyr equivalent, side by side, with small, hand-checkable datasets you can verify yourself at every step. The book moves in the order a SQL query itself is built: choosing and filtering columns and rows, sorting, aggregating with GROUP BY and HAVING, window functions, joins of every kind (including semi- and anti-joins, which have no single SQL keyword of their own), set operations, and the moment many readers find most rewarding — discovering that SQL's subqueries and CTEs collapse into nothing more than R's ordinary, sequential pipeline. From there, it covers dplyr's answers to INSERT, UPDATE, and DELETE, and closes with the two tasks SQL was never quite built for: reshaping data between wide and long formats, and working fluently with text. A closing chapter addresses performance directly, including how to use dplyr syntax against a live database connection via dbplyr — letting the same pipelines you've learned throughout the book translate automatically back into the SQL you started with. A full quick-reference appendix maps every pattern in the book onto a single table, organized by chapter, so the book keeps working as a lookup tool long after a first read. Written for SQL-proficient analysts, data scientists, and database professionals adding R to their toolkit, this book teaches neither SQL nor the R language from scratch — it assumes both, and spends every page instead on the one skill that actually matters for a fast, confident transition: fluent translation between the two.