Creating empty dataframe with column names as in a vector

[pallav12364]

I have a vector say x <- c('a','b','c')
now I want to create an empty dataframe with column names as those in x. Values in x can be any character value, doesn't need to be a,b,c necessarily.

[pieterjanvc]

Hi,

Here is one way:

x = c("A", "B", "C")

myData = as.data.frame(matrix(numeric(),nrow = 0, ncol = length(x)))
colnames(myData) = x

myData
[1] A B C
<0 rows> (or 0-length row.names)

Question: why do you want to do this?

Hope this helps,
PJ

[Solarion]

to add to PJ's solution:
you can also declare the colnames while constructing the matrix.

x <- c('a','b','c')

df <- as.data.frame(
  matrix(ncol = length(x), nrow=0,
             dimnames = list(NULL,x))
)

the dimnames argument must be a list of 2 vectors, first the rownames, then the colnames

[nutterb]

I don't know why, but I got completely engrossed in code golfing this question. The most succinct I've been able to come up with are

x <- c("A", "B", "C")
df <- as.data.frame(sapply(x, function(x) numeric()))
df <- as.data.frame(vapply(x, function(x) numeric(), numeric()))
df <- as.data.frame(replicate(length(x), numeric()), col.names = x)
df <- as.data.frame(matrix(ncol = length(x), nrow=0, dimnames = list(NULL,x)))
df <- as.data.frame(matrix(numeric(),nrow = 0, ncol = length(x))); names(df) <- x

But succinct doesn't translate into efficient. I timed this over data frames from 1 to 500 columns (why anyone would ever make 500 columns of a data frame like this, I don't know, but let's not have reality interfere with ridiculous fun)

The best performer ends up being

df <- as.data.frame(matrix(ncol = length(x), nrow=0, dimnames = list(NULL,x)))`

in case you're really desperate to save yourself a few microseconds. (and I might need a better hobby)

library(dplyr)
library(tidyr)
library(ggplot2)

bench_fun <- function(x){
  x <- sprintf("X%s", seq_len(x))
  microbenchmark(
    sapply = df <- as.data.frame(sapply(x, function(x) numeric())), 
    vapply = df <- as.data.frame(vapply(x, function(x) numeric(), numeric())),
    replicate = df <- as.data.frame(replicate(length(x), numeric()), col.names = x), 
    name_with = df <- as.data.frame(matrix(ncol = length(x), nrow=0, dimnames = list(NULL,x))),
    name_separately = {df <- as.data.frame(matrix(numeric(),nrow = 0, ncol = length(x))); names(df) <- x}
  )
}

Bench <- 
  data_frame(ncol = 1:500) %>% 
  mutate(result = lapply(ncol, bench_fun))

X <- Bench %>% 
  mutate(result = lapply(result, as.data.frame)) %>% 
  unnest(result) %>% 
  group_by(ncol, expr) %>% 
  summarise(median = median(time, na.rm = TRUE)) %>% 
  ungroup()

ggplot(data = X, 
       mapping = aes(x = ncol, 
                     y = median, 
                     colour = expr)) + 
  geom_line()

[pieterjanvc]

@nutterb

I just love your thoroughness and the fact you go all out on something like this

Sometimes coding is just fun for the sillyness of it... keep doing that! Although I must say I like the benchmarking you did. It's often overlooked how efficiency is an integral part of good coding practices.

PJ

[pallav12364]

You are crazy man. Anyway good effort, impressed