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A <- c(1,6) B <- c(2,7) C <- c(3,8) D <- c(4,9) E <- c(5,0) df <- data.frame(A,B,C,D,E) df A B C D E 1 1 2 3 4 5 2 6 7 8 9 0 I would like to have this:
df 1 2 A 1 6 B 2 7 C 3 8 D 4 9 E 5 0 
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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.
How do I transpose data in R? Transposing data, e.g. in a data frame or matrix, is easy to do with the t() function. For example, if you want to transpose a data frame you can type t(dataFrame) .
To change the row order in an R data frame, we can use single square brackets and provide the row order at first place.
Thus, to convert columns of an R data frame into rows we can use transpose function t. For example, if we have a data frame df with five columns and five rows then we can convert the columns of the df into rows by using as.data.frame (t (df)).
You can use the following syntax to replace a particular value in a data frame in R with a new value: df [df == 'Old Value'] <- 'New value' You can use the following syntax to replace one of several values in a data frame with a new value: df [df == 'Old Value 1' | df == 'Old Value 2'] <- 'New value'
Now, we can use the rownames_to_column function to add the row names of our data as variable: Note that the rownames_to_column command adds the row_names column at the first index position of our data frame (in contrast to our R syntax of Example 1).
As you can see based on the output of the RStudio console, our example data frame object contains five rows and two columns. If we want to use the values stored in one of our variables as row names of our data frame (or a matrix), we can use the row.names function in R:
If your dataframe is truly in that format, then all of your vectors will be character vectors. Or, you basically have a character matrix and you could do this:
data.frame(t(df)) It would be better, though, to just define it the way you want it from the get-go
df <- data.frame(c('A','B','C','D','E'), c(1, 2, 3, 4, 5), c(6, 7, 8, 9, 0)) You could also do this
df <- data.frame(LETTERS[1:5], 1:5, c(6:9, 0)) If you wanted to give the columns names, you could do this
df <- data.frame(L = LETTERS[1:5], N1 = 1:5, N2 = c(6:9, 0)) Sometimes, if I use read.DIF of Excel data the data gets transposed. Is that how you got the original data in? If so, you can call
read.DIF(filename, transpose = T) to get the data in the correct orientation.
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I really recommend data.table approach without manual steps becauce they are error-prone
A <- c(1,6) B <- c(2,7) C <- c(3,8) D <- c(4,9) E <- c(5,0) df <- data.frame(A,B,C,D,E) df library('data.table') dat.m <- melt(as.data.table(df, keep.rownames = "Vars"), id.vars = "Vars") # https://stackoverflow.com/a/44128640/54964 dat.m Output
A B C D E 1 1 2 3 4 5 2 6 7 8 9 0 Vars variable value 1: 1 A 1 2: 2 A 6 3: 1 B 2 4: 2 B 7 5: 1 C 3 6: 2 C 8 7: 1 D 4 8: 2 D 9 9: 1 E 5 10: 2 E 0 R: 3.4.0 (backports)
OS: Debian 8.7
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