144

I need to transpose a large data frame and so I used:

df.aree <- t(df.aree) df.aree <- as.data.frame(df.aree)

This is what I obtain:

df.aree[c(1:5),c(1:5)] 10428 10760 12148 11865 name M231T3 M961T5 M960T6 M231T19 GS04.A 5.847557e+03 0.000000e+00 3.165891e+04 2.119232e+04 GS16.A 5.248690e+04 4.047780e+03 3.763850e+04 1.187454e+04 GS20.A 5.370910e+03 9.518396e+03 3.552036e+04 1.497956e+04 GS40.A 3.640794e+03 1.084391e+04 4.651735e+04 4.120606e+04

My problem is the new column names(10428, 10760, 12148, 11865) that I need to eliminate because I need to use the first row as column names.

I tried with col.names() function but I haven't obtain what I need.

Do you have any suggestion?

EDIT

Thanks for your suggestion!!! Using it I obtain:

df.aree[c(1:5),c(1:5)] M231T3 M961T5 M960T6 M231T19 GS04.A 5.847557e+03 0.000000e+00 3.165891e+04 2.119232e+04 GS16.A 5.248690e+04 4.047780e+03 3.763850e+04 1.187454e+04 GS20.A 5.370910e+03 9.518396e+03 3.552036e+04 1.497956e+04 GS40.A 3.640794e+03 1.084391e+04 4.651735e+04 4.120606e+04 GS44.A 1.225938e+04 2.681887e+03 1.154924e+04 4.202394e+04

Now I need to transform the row names(GS..) in a factor column....

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  • 1
    Have you tried colnames(df.aree)<-df.aree[1,];df.aree<-df.aree[2:nrow(df.aree),]? Commented Jul 21, 2011 at 15:54
  • 5
    Data frames aren't naturally meant to be transposable. If yours is, then perhaps it should be in matrix form instead. Commented Jul 21, 2011 at 16:01
  • Agree; ting data frame is also quite inefficient. If you can, use matrix. Commented Jul 21, 2011 at 16:31
  • 5
    Transposing a data.frame that contains a string column in it turns ALL values into strings! NOT good. See my answer below for a work-around. Commented Jul 21, 2011 at 16:50

7 Answers 7

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140

You'd better not transpose the data.frame while the name column is in it - all numeric values will then be turned into strings!

Here's a solution that keeps numbers as numbers:

# first remember the names n <- df.aree$name # transpose all but the first column (name) df.aree <- as.data.frame(t(df.aree[,-1])) colnames(df.aree) <- n df.aree$myfactor <- factor(row.names(df.aree)) str(df.aree) # Check the column types
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1 Comment

If you want to use transpose with data.frame, df <- df %>% mutate_if(is.character,as.numeric) can be used to change characters back to numeric.
89

You can use the transpose function from the data.table library. Simple and fast solution that keeps numeric values as numeric.

library(data.table) # get data data("mtcars") # transpose t_mtcars <- transpose(mtcars) # get row and colnames in order colnames(t_mtcars) <- rownames(mtcars) rownames(t_mtcars) <- colnames(mtcars)
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also, setnames(t_mtcars, rownames(mtcars)) would be the data.table-way of setting names on a data.table (and if using a data.table object you wouldn't set the rownames)
Also, within data.table::transpose you can use the arguments make.names to select the column (usually a character vector) whose names will become the column names for the transposed data.frame. You can also use the argument keep.names to choose a column name for the new column (a character vector) which will store the previous column names from the pre-transposed data.frame).
50 
df.aree <- as.data.frame(t(df.aree)) colnames(df.aree) <- df.aree[1, ] df.aree <- df.aree[-1, ] df.aree$myfactor <- factor(row.names(df.aree))
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@Riccardo If so, accept his answer by clicking a gray tick next to it.
one problem with this - column names take the numeric representation of the factor level.
5

Take advantage of as.matrix:

# keep the first column names <- df.aree[,1] # Transpose everything other than the first column df.aree.T <- as.data.frame(as.matrix(t(df.aree[,-1]))) # Assign first column as the column names of the transposed dataframe colnames(df.aree.T) <- names
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5

With tidyr, one can transpose a dataframe with "pivot_longer" and then "pivot_wider".

To transpose the widely used mtcars dataset, you should first transform rownames to a column (the function rownames_to_column creates a new column, named "rowname").

library(tidyverse) mtcars %>% rownames_to_column() %>% pivot_longer(!rowname, names_to = "col1", values_to = "col2") %>% pivot_wider(names_from = "rowname", values_from = "col2")
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0

You can give another name for transpose matrix

df.aree1 <- t(df.aree) df.aree1 <- as.data.frame(df.aree1)
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As it’s currently written, your answer is unclear. Please edit to add additional details that will help others understand how this addresses the question asked. You can find more information on how to write good answers in the help center.
0

Personally I find the rotate_df function from the sjmisc package the most intuitive way to rotate a data.frame while conserving the row and column names.

library(sjmisc) rotate_df(df.aree, rn = "First Col Name Of Transposed DF", cn = TRUE)
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