(This article was first published on

**RStudio Blog**, and kindly contributed to R-bloggers)I’m pleased to announce tidyr 0.5.0. 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")`

This release has three useful new features:

`separate_rows()`

separates values that contain multiple values separated by a delimited into multiple rows. Thanks to Aaron Wolen for the contribution!`df <- data_frame(x = 1:2, y = c("a,b", "d,e,f")) df %>% separate_rows(y, sep = ",") #> Source: local data frame [5 x 2] #> #> x y #>`

#> 1 1 a #> 2 1 b #> 3 2 d #> 4 2 e #> 5 2 f Compare with

`separate()`

which separates into (named) columns:`df %>% separate(y, c("y1", "y2", "y3"), sep = ",", fill = "right") #> Source: local data frame [2 x 4] #> #> x y1 y2 y3 #> *`

#> 1 1 a b #> 2 2 d e f `spread()`

gains a`sep`

argument. Setting this will name columns as “key|sep|value”. This is useful when you’re spreading based on a numeric column:`df <- data_frame( x = c(1, 2, 1), key = c(1, 1, 2), val = c("a", "b", "c") ) df %>% spread(key, val) #> Source: local data frame [2 x 3] #> #> x 1 2 #> *`

#> 1 1 a c #> 2 2 b df %>% spread(key, val, sep = "_") #> Source: local data frame [2 x 3] #> #> x key_1 key_2 #> * #> 1 1 a c #> 2 2 b `unnest()`

gains a`.sep`

argument. This is useful if you have multiple columns of data frames that have the same variable names:`df <- data_frame( x = 1:2, y1 = list( data_frame(y = 1), data_frame(y = 2) ), y2 = list( data_frame(y = "a"), data_frame(y = "b") ) ) df %>% unnest() #> Source: local data frame [2 x 3] #> #> x y y #>`

#> 1 1 1 a #> 2 2 2 b df %>% unnest(.sep = "_") #> Source: local data frame [2 x 3] #> #> x y1_y y2_y #> #> 1 1 1 a #> 2 2 2 b It also gains a

`.id`

column that makes the names of the list explicit:`df <- data_frame( x = 1:2, y = list( a = 1:3, b = 3:1 ) ) df %>% unnest() #> Source: local data frame [6 x 2] #> #> x y #>`

#> 1 1 1 #> 2 1 2 #> 3 1 3 #> 4 2 3 #> 5 2 2 #> 6 2 1 df %>% unnest(.id = "id") #> Source: local data frame [6 x 3] #> #> x y id #> #> 1 1 1 a #> 2 1 2 a #> 3 1 3 a #> 4 2 3 b #> 5 2 2 b #> 6 2 1 b

tidyr 0.5.0 also includes a bumper crop of bug fixes, including fixes for `spread()`

and `gather()`

in the presence of list-columns. Please see the release notes for a complete list of changes.

To

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