The goal of this tutorial is to learn how to melt a table. The process of melting consists of transforming a table with different variables in a table where the columns are melted into variable and value. We can define which columns to use as ids and the rest will be melted.
library(reshape2)
# In this tutorial we are going to use a handmade dataframe
my_dataframe <- data.frame(Person = c("Peter", "Perry"), age = c(33, 37), origin = c("Valencia", "Barcelona"), height = c(178, 183))
my_dataframe## Person age origin height
## 1 Peter 33 Valencia 178
## 2 Perry 37 Barcelona 183# We can use one of the columns as id and we will get as many rows as different columns we had
melt(my_dataframe, id = "Person")## Warning: attributes are not identical across measure variables; they will
## be dropped## Person variable value
## 1 Peter age 33
## 2 Perry age 37
## 3 Peter origin Valencia
## 4 Perry origin Barcelona
## 5 Peter height 178
## 6 Perry height 183# However we could use more columns as id
melt(my_dataframe, id = c("Person", "origin"))## Person origin variable value
## 1 Peter Valencia age 33
## 2 Perry Barcelona age 37
## 3 Peter Valencia height 178
## 4 Perry Barcelona height 183In this tutorial we have learnt how to use one ore more columns to melt the variables of a table. This could be useful when we want to know the weight of a variable compared with the other variables.