Unnest a list column directly into several columns
With data.table
it's pretty simple:
library("data.table")
setDT(df1)
df1[, c("V1", "V2") := transpose(values)]
df1
# gr values V1 V2
# 1: a 1,2 1 2
# 2: b 3,4 3 4
# 3: c 5,6 5 6
library(tibble)
df1 <- data_frame(
gr = c('a', 'b', 'c'),
values = list(1:2, 3:4, 5:6)
)
library(tidyverse)
df1 %>%
mutate(r = map(values, ~ data.frame(t(.)))) %>%
unnest(r) %>%
select(-values)
# # A tibble: 3 x 3
# gr X1 X2
# <chr> <int> <int>
# 1 a 1 2
# 2 b 3 4
# 3 c 5 6
Maybe this:
cbind(df1[, "gr"], do.call(rbind, df1$values))
with tidyr 1.0.0 you can do :
library(tidyr)
df1 <- tibble(
gr = c('a', 'b', 'c'),
values = list(1:2, 3:4, 5:6)
)
unnest_wider(df1, values)
#> New names:
#> * `` -> ...1
#> * `` -> ...2
#> New names:
#> * `` -> ...1
#> * `` -> ...2
#> New names:
#> * `` -> ...1
#> * `` -> ...2
#> # A tibble: 3 x 3
#> gr ...1 ...2
#> <chr> <int> <int>
#> 1 a 1 2
#> 2 b 3 4
#> 3 c 5 6
Created on 2019-09-14 by the reprex package (v0.3.0)
The output is verbose here because the elements that were unnested horizontally (the vector elements) were not named, and unnest_wider
doesn't want to guess silently.
We can name them beforehand to avoid it :
df1 %>%
dplyr::mutate(values = purrr::map(values, setNames, c("V1","V2"))) %>%
unnest_wider(values)
#> # A tibble: 3 x 3
#> gr V1 V2
#> <chr> <int> <int>
#> 1 a 1 2
#> 2 b 3 4
#> 3 c 5 6
Or just use suppressMessages()
or purrr::quietly()