On 05/03/2018 01:28 PM, Hadley Wickham wrote:
On Wed, May 2, 2018 at 11:53 AM, Jeff Newmiller
<jdnew...@dcn.davis.ca.us> wrote:
Another approach:
########
library(tidyr)
L <- list( A = data.frame( x=1:2, y=3:4 )
, B = data.frame( x=5:6, y=7:8 )
)
D <- data.frame( Type = names( L )
, stringsAsFactors = FALSE
)
D$data <- L
unnest(D, data)
#> Type x y
#> 1 A 1 3
#> 2 A 2 4
#> 3 B 5 7
#> 4 B 6 8
########
I think a slightly more idiomatic tidyverse solution is dplyr::bind_rows()
l <- list(
A = data.frame(x = 1:2, y = 3:4),
B = data.frame(x = 5:6, y = 7:8)
)
dplyr::bind_rows(l, .id = "type")
#> type x y
#> 1 A 1 3
#> 2 A 2 4
#> 3 B 5 7
#> 4 B 6 8
This also has the advantage of returning a data frame when the inputs
are data frames.
Hadley
I _clearly_ need to learn the dplyr package.
--
Kevin E. Thorpe
Head of Biostatistics, Applied Health Research Centre (AHRC)
Li Ka Shing Knowledge Institute of St. Michael's Hospital
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.tho...@utoronto.ca Tel: 416.864.5776 Fax: 416.864.3016
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