Reputation: 21497
Using the tidyverse
a lot i often face the challenge of turning named vectors into a data.frame
/tibble
with the columns being the names of the vector.
What is the prefered/tidyversey way of doing this?
EDIT: This is related to: this and this github-issue
So i want:
require(tidyverse)
vec <- c("a" = 1, "b" = 2)
to become this:
# A tibble: 1 × 2
a b
<dbl> <dbl>
1 1 2
I can do this via e.g.:
vec %>% enframe %>% spread(name, value)
vec %>% t %>% as_tibble
Usecase example:
require(tidyverse)
require(rvest)
txt <- c('<node a="1" b="2"></node>',
'<node a="1" c="3"></node>')
txt %>% map(read_xml) %>% map(xml_attrs) %>% map_df(~t(.) %>% as_tibble)
Which gives
# A tibble: 2 × 3
a b c
<chr> <chr> <chr>
1 1 2 <NA>
2 1 <NA> 3
Upvotes: 30
Views: 9728
Reputation: 47320
The idiomatic way would be to splice the vector with !!!
within a tibble()
call so the named vector elements become column definitions :
library(tibble)
vec <- c("a" = 1, "b" = 2)
tibble(!!!vec)
#> # A tibble: 1 x 2
#> a b
#> <dbl> <dbl>
#> 1 1 2
Created on 2019-09-14 by the reprex package (v0.3.0)
Upvotes: 7
Reputation: 4534
This is now directly supported using bind_rows
(introduced in dplyr 0.7.0
):
library(tidyverse))
vec <- c("a" = 1, "b" = 2)
bind_rows(vec)
#> # A tibble: 1 x 2
#> a b
#> <dbl> <dbl>
#> 1 1 2
This quote from https://cran.r-project.org/web/packages/dplyr/news.html explains the change:
bind_rows()
andbind_cols()
now accept vectors. They are treated as rows by the former and columns by the latter. Rows require inner names likec(col1 = 1, col2 = 2)
, while columns require outer names:col1 = c(1, 2)
. Lists are still treated as data frames but can be spliced explicitly with!!!
, e.g.bind_rows(!!! x)
(#1676).
With this change, it means that the following line in the use case example:
txt %>% map(read_xml) %>% map(xml_attrs) %>% map_df(~t(.) %>% as_tibble)
can be rewritten as
txt %>% map(read_xml) %>% map(xml_attrs) %>% map_df(bind_rows)
which is also equivalent to
txt %>% map(read_xml) %>% map(xml_attrs) %>% { bind_rows(!!! .) }
The equivalence of the different approaches is demonstrated in the following example:
library(tidyverse)
library(rvest)
txt <- c('<node a="1" b="2"></node>',
'<node a="1" c="3"></node>')
temp <- txt %>% map(read_xml) %>% map(xml_attrs)
# x, y, and z are identical
x <- temp %>% map_df(~t(.) %>% as_tibble)
y <- temp %>% map_df(bind_rows)
z <- bind_rows(!!! temp)
identical(x, y)
#> [1] TRUE
identical(y, z)
#> [1] TRUE
z
#> # A tibble: 2 x 3
#> a b c
#> <chr> <chr> <chr>
#> 1 1 2 <NA>
#> 2 1 <NA> 3
Upvotes: 33
Reputation: 2950
Interestingly you can use the as_tibble()
method for lists to do this in one call. Note that this isn't best practice since this isn't an exported method.
tibble:::as_tibble.list(vec)
Upvotes: 1