Tidyverse

Spatial data science in the Tidyverse

rstudio::conf 2019

Spatial data science in the Tidyverse

January 25, 2019

Package sf (simple feature) and ggplot2::geom_sf have caused a fast uptake of tidy spatial data analysis by data scientists. Important spatial data science challenges are not handled by...

Melt the clock Tidy time series analysis

rstudio::conf 2019

Melt the clock Tidy time series analysis

January 25, 2019

Time series can be frustrating to work with, particularly when processing raw data into model-ready data. This work presents two new packages that address a gap in existing methodology for...

Working with categorical data in R without losing your mind

rstudio::conf 2019

Working with categorical data in R without losing your mind

January 24, 2019

Categorical data, called “factor” data in R, presents unique challenges in data wrangling. R users often look down at tools like Excel for automatically coercing variables to incorrect datatypes, but

Solving R for data science

rstudio::conf 2019

Solving R for data science

January 24, 2019

While teaching a course using "R for Data Science", I wrote a complete set of solutions to its exercises and posted them on GitHub. Then other people started finding them. And now I'm here.

Box plots A case study in debugging and perseverance

rstudio::conf 2019

Box plots A case study in debugging and perseverance

January 23, 2019

Come on a journey through pull request #2196. What started as a seemingly simple fix for a bug in ggplot2's box plots developed into an entirely new placement algorithm for ggplot2 geoms.