I have a named character vector returned from xmlAttrs like this:
testVect <- structure(c(\"11.2.0.3.0\", \"12.89\", \"12.71\"), .Names = c(\"db_version\"
The answers from @MatthewPlourde and @JackRyan work, but if you have a long named vector it is annoying to have a data frame with one row and many columns. If you'd rather have a "key" column and a "value" column with many rows, any of the following should work:
data.frame(keyName=names(testVect), value=testVect, row.names=NULL)
## keyName value
## 1 db_version 11.2.0.3.0
## 2 elapsed_time 12.89
## 3 cpu_time 12.71
## Suggested by @JWilliman
tibble::enframe(testVect)
## # A tibble: 3 x 2
## name value
## <chr> <chr>
## 1 db_version 11.2.0.3.0
## 2 elapsed_time 12.89
## 3 cpu_time 12.71
## Suggested by @Joe
stack(testVect)
## values ind
## 1 11.2.0.3.0 db_version
## 2 12.89 elapsed_time
## 3 12.71 cpu_time
I'm going to take a stab at this:
test.vector <- as.data.frame(t(testVect))
class(test.vector)
named vector %>% as_tibble(.,rownames="column name of row.names")
It's as simple as data.frame(as.list(testVect))
. Or if you want sensible data types for your columns, data.frame(lapply(testVect, type.convert), stringsAsFactors=FALSE)
.
I used to use the functions suggested in these answers (as.list
, as_tibble
, t
, enframe
, etc.) but have since found out that dplyr::bind_rows
now works to do exactly what the original question asks with a single function call.
library(dplyr)
testVect <- structure(c("11.2.0.3.0", "12.89", "12.71"), .Names = c("db_version", "elapsed_time", "cpu_time"))
testVect %>% bind_rows
#> # A tibble: 1 x 3
#> db_version elapsed_time cpu_time
#> <chr> <chr> <chr>
#> 1 11.2.0.3.0 12.89 12.71
Created on 2019-11-10 by the reprex package (v0.3.0)
As shown in tidyverse - prefered way to turn a named vector into a data.frame/tibble