ChatGPT解决这个技术问题 Extra ChatGPT

Convert a row of a data frame to vector

I want to create a vector out of a row of a data frame. But I don't want to have to row and column names. I tried several things... but had no luck.

This is my data frame:

> df <- data.frame(a=c(1,2,4,2),b=c(2,6,2,1),c=c(2.6,8.2,7.5,3))
> df
  a b   c
1 1 2 2.6
2 2 6 8.2
3 4 2 7.5
4 2 1 3.0

I tried:

> newV <- as.vector(df[1,])
> newV
  a b   c
1 1 2 2.6

But I really want something looking like this:

> newV <- c( 1,2,2.6)
> newV
[1] 1.0 2.0 2.6
I suggest you format the data you've shown properly. Looks like you are missing some line breaks.
I want a row. Row '1' and not column 'a'.
Is there a way to apply this to all rows of a data frame and thereby merging all vectors to a single vector?
@stephanmg: What about something like: c(t(as.matrix(df)))?
Andri: That's working, though I could solve it differently too.

B
Ben Bolker

When you extract a single row from a data frame you get a one-row data frame. Convert it to a numeric vector:

as.numeric(df[1,])

As @Roland suggests, unlist(df[1,]) will convert the one-row data frame to a numeric vector without dropping the names. Therefore unname(unlist(df[1,])) is another, slightly more explicit way to get to the same result.

As @Josh comments below, if you have a not-completely-numeric (alphabetic, factor, mixed ...) data frame, you need as.character(df[1,]) instead.


it might be +1 (or 0 down-votes) to the OP for giving code that illustrated clearly what they wanted even though the text and title of the question were garbled ...
@ChinmayPatil, what are their other options? Their code example certainly makes it look like that's what they want.
It should be noted that a data frame is already a vector and hence as.vector sees it is a vector of mode "list" and does nothing. To facilitate understanding of the underlying mechanisms try as.vector(df[1,], mode="numeric") which is more illustrative. This is what as.numeric does.
no problem. I'm only stating that for this problem they give exactly the same answer.
Might have been changed in the meantime, but today unlist allows dropping names: identical(unlist(df[1,], use.names = FALSE), as.numeric(df[1,])) (and btw df still is not a sensible name for a data.frame... ;-))
R
Roland

I recommend unlist, which keeps the names.

unlist(df[1,])
  a   b   c 
1.0 2.0 2.6 

is.vector(unlist(df[1,]))
[1] TRUE

If you don't want a named vector:

unname(unlist(df[1,]))
[1] 1.0 2.0 2.6

s
sbha

Here is a dplyr based option:

newV = df %>% slice(1) %>% unlist(use.names = FALSE)

# or slightly different:
newV = df %>% slice(1) %>% unlist() %>% unname()

C
CHP

If you don't want to change to numeric you can try this.

> as.vector(t(df)[,1])
[1] 1.0 2.0 2.6

this doesn't make much sense to me: str(as.vector(t(df)[,1])) is num [1:3] 1 2 2.6, i.e. your code does convert the results to a numeric vector ...
specifically, when you use t(df) R coerces the data frame to a matrix, in this case a numeric matrix because all the elements are numeric. Then [,1] extracts the first column (a numeric vector, because the redundant dimension is automatically dropped). as.vector() just drops the names (which you could also do with unname()).
It seems to work for characters as well. But you are right about coersion. FWIW, my solution will work on character data frames as well.. with caveat of all the data being converted to character
I would say that the unname(unlist(x)) solution is a little better (more efficient and more transparent).
as.vector(t(df)[,1]) I love it ! Exactly what I need it !
R
Rtist

Note that you have to be careful if your row contains a factor. Here is an example:

df_1 = data.frame(V1 = factor(11:15),
                  V2 = 21:25)
df_1[1,] %>% as.numeric() # you expect 11 21 but it returns 
[1] 1 21

Here is another example (by default data.frame() converts characters to factors)

df_2 = data.frame(V1 = letters[1:5],
                  V2 = 1:5)
df_2[3,] %>% as.numeric() # you expect to obtain c 3 but it returns
[1] 3 3
df_2[3,] %>% as.character() # this won't work neither
[1] "3" "3"

To prevent this behavior, you need to take care of the factor, before extracting it:

df_1$V1 = df_1$V1 %>% as.character() %>% as.numeric()
df_2$V1 = df_2$V1 %>% as.character()
df_1[1,] %>% as.numeric()
[1] 11  21
df_2[3,] %>% as.character()
[1] "c" "3"

J
Jonathan Christensen

Columns of data frames are already vectors, you just have to pull them out. Note that you place the column you want after the comma, not before it:

> newV <- df[,1]
> newV
[1] 1 2 4 2

If you actually want a row, then do what Ben said and please use words correctly in the future.


but I think the OP wants the first row ?
@BenBolker Maybe so... I just assumed that he wanted what his title and question said he wanted.