In this book you will learn how to use [Apache Spark](https://spark.apache.org/) with R

A companion guide to [Dan Quintana’s thread](https://twitter.com/dsquintana/status/1139846569623281664)

This site is about everything that comes up during data analysis except for statistical modelling and inference

This book supplements my presentation at the Omaha R User Group on Thursday, April 4, 2019. If you develop Shiny Applications and your back end is a relational database, then this book is for you. The demos and code snippets are written in T-SQL, Microsoft SQL Server dialect of SQL, but the core concepts are applicable across all RDBMS systems. Data Scientists using R are the primary audience. Database Developers, BI Developers, Software Engineers, Data Analysts and Managers wanting to learn more about Shiny Database applications will also benefit from the material.

Adopt or revise good practices (organization of projects, work environment)

A quick introduction on using Docker for reproducibility in R

Materials of web scraping workshop carried out as part of the summer school 2018 of the LabEx DynamITe

This lesson will help you store large amounts of historical data in a structured manner, search and filter that data, and visualize some of the data as a graph. Lesson from [The Programming Historian](https://programminghistorian.org/)

Formation donnée à la Drees en Avril 2018

Plateforme open-source de traitement de données et un espace communautaire pour la statistique publique