Tidyverse

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rstudio::glimpse() Newsletter

October 26, 2022 | R package build

Welcome to the rstudio::glimpse() newsletter. Get a glimpse into our tools and how to use them.

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rstudio::glimpse() Newsletter

September 29, 2022 |

Welcome to the rstudio::glimpse() newsletter. Get a glimpse into our tools and how to use them.

blog

From Biology to Healthcare Analytics: My Data Science Journey

September 22, 2022 |

Austin Chia, Founder of Any Instructor, describes his transition from studying biology to becoming a healthcare data analyst.

blog

rstudio::glimpse() Newsletter

August 30, 2022 |

Welcome to the rstudio::glimpse() newsletter. Get a glimpse into our tools and how to use them.

blog

rstudio::glimpse() Newsletter

July 14, 2022 |

Welcome to the rstudio::glimpse() newsletter. Get a glimpse into our tools and how to use them.

rstudio::conf 2020

TidyBlocks: using the language of the Tidyverse in a blocks-based interface

February 4, 2020 |

Blocks-based coding environments are a popular way to introduce programming to novices. Instead of typing in code, users click blocks together to create loops, conditionals, and expressions.

rstudio::conf 2020

Making a tidy dress

February 4, 2020 |

After at least a year of dreaming about it, I finally produced the #rstats / #Tidyverse dress of my dreams.

rstudio::conf 2020

Platelet Transfusion Management using R and the Tidyverse

January 31, 2020 |

Development of a web-based clinical decision support application for platelet transfusion management using R and the Tidyverse Blood product transfusion is a high risk and costly medical procedure.

rstudio::conf 2020

R + Tidyverse in Sports

January 30, 2020 |

There are many ways in which R and the Tidyverse can be used to analyze sports data and the unique considerations that are involved in applying statistical tools to sports problems.

rstudio::conf 2020

FlatironKitchen: How we overhauled a Frankensteinian SQL workflow with the Tidyverse

January 30, 2020 |

FlatironKitchen: How we overhauled a Frankensteinian SQL workflow with the Tidyverse to enable fast, reproducible, elegant analyses of electronic health records.

Webinars

A Gentle Introduction to Tidy Statistics in R

June 12, 2019 |

R is a fantastic language for statistical programming, but making the jump from point and click interfaces to code can be intimidating for individuals new to R.

rstudio::conf 2019

Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition

January 25, 2019 |

An organization that loses 200 high-performing employees per year has a lost productivity cost of about $15M/year. This cost is massive, yet many organizations don’t know it exists.

rstudio::conf 2019

Learning and using the Tidyverse for historical research

January 24, 2019 |

My talk will discuss how R, the Tidyverse, and the community around R helped me to learn to code and create my first R package. My positive experiences with the resources for learning R and...

Webinars

How to Work with List Columns

August 11, 2018 |

This webinar breaks down one of the most esoteric concepts in the Tidyverse: list columns.

Webinars

Usando R para la Ciencia de Datos

May 25, 2018 |

La extracción de conocimiento mediante el análisis de datos es usualmente una tarea compleja y ardua. Las extensiones de R, llamadas paquetes, que son parte de lo que en inglés llamamos “Tidyverse”.

Webinars

Thinking inside the box: you can do that inside a data frame?!

April 13, 2018 |

The data frame is a crucial data structure in R and, especially, in the Tidyverse. Working on a column or a variable is a very natural operation, which is great. But what about row-oriented work?

Webinars

Tidyverse visualization manipulation basics

September 14, 2017 |

This introduction to the tidyverse will cover several best practices for analyzing data with R.

Webinars

What's new in dplyr 0.7.0

June 22, 2017 |

dplyr provides a “grammar” of data transformation, making it easy and elegant to solve the most common data manipulation challenges.

Webinars

The Tidyverse and RStudio Connect

April 21, 2017 |

A model for data science that begins with importing and tidying data, continues with an iterative cycle of transforming, modeling, and visualizing data, and ends with communication.

blog

purrr 0.1.0

September 29, 2015 |

blog

rvest 0.3.0

September 24, 2015 |

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tidyr 0.3.0

September 13, 2015 |

R Packages

January 1, 0001 |