I’m pleased to announce tibble, a new package for manipulating and printing data frames in R. Tibbles are a modern reimagining of the data.frame, keeping what time has proven to be effective, and throwing out what is not. The name comes from dplyr: originally you created these objects with tbl_df(), which was most easily pronounced as “tibble diff”. Install tibble with: install.packages("tibble") This package extracts out the tbl_df class associated functions from dplyr. Read more →

I’m very pleased to announce the release of ggplot2 2.1.0, scales 0.4.0, and gtable 0.2.0. These are set of relatively minor updates that fix a whole bunch of little problems that crept in during the last big update. The most important changes are described below. When mapping an aesthetic to a constant the default guide title is the name of the aesthetic (i.e. “colour”), not the value (i.e. “loess”). This is a really handy technique for labelling individual layers: ggplot(mpg, aes(displ, 1 / hwy)) + geom_point() + geom_smooth(method = lm, aes(colour = "lm"), se = FALSE) + geom_smooth(aes(colour = "loess"), se = FALSE) stat_bin() (which powers geom_histogram() and geom_freqpoly()), has been overhauled to use the same algorithm as ggvis. Read more →

I’m pleased to announce tidyr 0.4.0. tidyr makes it easy to “tidy” your data, storing it in a consistent form so that it’s easy to manipulate, visualise and model. Tidy data has a simple convention: put variables in the columns and observations in the rows. You can learn more about it in the tidy data vignette. Install it with: install.packages("tidyr") There are two big features in this release: support for nested data frames, and improved tools for turning implicit missing values into explicit missing values. Read more →

I’m pleased to announce purrr 0.2.0. Purrr fills in the missing pieces in R’s functional programming tools, and is designed to make your pure (and now) type-stable functions purrr. I’m still working out exactly what purrr should do, and how it compares to existing functions in base R, dplyr, and tidyr. One main insight that has affected much of the current version is that functions designed for programming should be type-stable. Read more →

readr 0.2.0 is now available on CRAN. readr makes it easy to read many types of tabular data, including csv, tsv and fixed width. Compared to base equivalents like read.csv(), readr is much faster and gives more convenient output: it never converts strings to factors, can parse date/times, and it doesn’t munge the column names. This is a big release, so below I describe the new features divided into four main categories: Read more →

Purrr is a new package that fills in the missing pieces in R’s functional programming tools: it’s designed to make your pure functions purrr. Like many of my recent packages, it works with magrittr to allow you to express complex operations by combining simple pieces in a standard way. Install it with: install.packages("purrr") Purrr wouldn’t be possible without Lionel Henry. He wrote a lot of the package and his insightful comments helped me rapidly iterate towards a stable, useful, and understandable package. Read more →

I’m pleased to announce rvest 0.3.0 is now available on CRAN. Rvest makes it easy to scrape (or harvest) data from html web pages, inspired by libraries like beautiful soup. It is designed to work with pipes so that you can express complex operations by composed simple pieces. Install it with: install.packages("rvest") What’s new The biggest change in this version is that rvest now uses the xml2 package instead of XML. Read more →

tidyr 0.3.0 is now available on CRAN. tidyr makes it easy to “tidy” your data, storing it in a consistent form so that it’s easy to manipulate, visualise and model. Tidy data has variables in columns and observations in rows, and is described in more detail in the tidy data vignette. Install tidyr with: install.packages("tidyr") tidyr contains four new verbs: fill(), replace() and complete(), and unnest(), and lots of smaller bug fixes and improvements. Read more →

dplyr 0.4.3 includes over 30 minor improvements and bug fixes, which are described in detail in the release notes. Here I wanted to draw your attention five small, but important, changes: mutate() no longer randomly crashes! (Sorry it took us so long to fix this - I know it’s been causing a lot of pain.) dplyr now has much better support for non-ASCII column names. It’s probably not perfect, but should be a lot better than previous versions. Read more →

I’m very excited to announce the 1.0.0 release of the stringr package. If you haven’t heard of stringr before, it makes string manipulation easier by: Using consistent function and argument names: all functions start with str_, and the first argument is always the input string This makes stringr easier to learn and easy to use with the pipe. Eliminating options that you don’t need 95% of the time. Read more →