Tidyverse

readr 0.1.0

2015-04-09 Hadley Wickham
I’m pleased to announced that readr is now available on CRAN. Readr makes it easy to read many types of tabular data: Delimited files withread_delim(), read_csv(), read_tsv(), and read_csv2(). Fixed width files with read_fwf(), and read_table(). Web log files with read_log(). You can install it by running: install.packages("readr") Compared to the equivalent base functions, readr functions are around 10x faster. They’re also easier to use because they’re more consistent, they produce data frames that are easier to use (no more stringsAsFactors = FALSE! Read more →

haven 0.1.0

2015-03-04 Hadley Wickham
I’m pleased to announced that the new haven package is now available on CRAN. Haven makes it easy to read data from SAS, SPSS and Stata. Haven has the same goal as the foreign package, but it: Can read binary SAS7BDAT files. Can read Stata13 files. Always returns a data frame. (Haven also has experimental support for writing SPSS and Stata data. This still has some rough edges but please try it out and report any problems that you find. Read more →

tidyr 0.2.0 (and reshape2 1.4.1)

2014-12-08 Hadley Wickham
tidyr 0.2.0 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") There are three important additions to tidyr 0.2.0: expand() is a wrapper around expand. Read more →

dplyr 0.3

2014-10-13 Hadley Wickham
I’m very pleased to announce that dplyr 0.3 is now available from CRAN. Get the latest version by running: install.packages("dplyr") There are four major new features: Four new high-level verbs: distinct(), slice(), rename(), and transmute(). Three new helper functions between, count(), and data_frame(). More flexible join specifications. Support for row-based set operations. There are two new features of interest to developers. They make it easier to write packages that use dplyr: Read more →