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Convert a row of a data frame to vector

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How do I turn a Dataframe row into a vector?

If we want to turn a dataframe row into a character vector then we can use as. character() method In R, we can construct a character vector by enclosing the vector values in double quotation marks, but if we want to create a character vector from data frame row values, we can use the as character function.

How do you vectorize a data frame?

To create a vector of data frame values by rows we can use c function after transposing the data frame with t. For example, if we have a data frame df that contains many columns then the df values can be transformed into a vector by using c(t(df)), this will print the values of the data frame row by row.

How do I convert a row vector to a column vector in R?

Rotating or transposing R objects frame so that the rows become the columns and the columns become the rows. That is, you transpose the rows and columns. You simply use the t() command. The result of the t() command is always a matrix object.


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.


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

Here is a dplyr based option:

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

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

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

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"