The goal of this tutorial is to learn how to transpose a dataframe. We will show two different ways to do it.
# Transposing is the act of interchanging rows by columns in a dataframe
# We are going to use a modified version of the iris dataframe
iris_df <- read.csv("iris_transpose.csv", header = TRUE, stringsAsFactors = FALSE)
head(iris_df)## X Sepal.Length Sepal.Width Petal.Length Petal.Width
## 1 setosa 5.006 3.428 1.462 0.246
## 2 versicolor 5.936 2.770 4.260 1.326
## 3 virginica 6.588 2.974 5.552 2.026# The first column is actually the row names
rownames(iris_df) <- iris_df$X
iris_df$X <- NULL
head(iris_df)## Sepal.Length Sepal.Width Petal.Length Petal.Width
## setosa 5.006 3.428 1.462 0.246
## versicolor 5.936 2.770 4.260 1.326
## virginica 6.588 2.974 5.552 2.026# We create a new dataframe using the transpose of a matrix
iris_transpose <- as.data.frame(t(as.matrix(iris_df)))
iris_transpose## setosa versicolor virginica
## Sepal.Length 5.006 5.936 6.588
## Sepal.Width 3.428 2.770 2.974
## Petal.Length 1.462 4.260 5.552
## Petal.Width 0.246 1.326 2.026library(data.table)
iris_transpose <- transpose(iris_df)
iris_transpose## V1 V2 V3
## 1 5.006 5.936 6.588
## 2 3.428 2.770 2.974
## 3 1.462 4.260 5.552
## 4 0.246 1.326 2.026# However we have to get back the row and col names
rownames(iris_transpose) <- colnames(iris_df)
colnames(iris_transpose) <- rownames(iris_df)
iris_transpose## setosa versicolor virginica
## Sepal.Length 5.006 5.936 6.588
## Sepal.Width 3.428 2.770 2.974
## Petal.Length 1.462 4.260 5.552
## Petal.Width 0.246 1.326 2.026In this tutorial we have learnt how to transpose a dataframe in two different ways.