Converting a data frame between wide and narrow formats

There are two typical approaches to storing data in a data frame:

• The wide format: Each row of a data frame contains one observation, possibly consisting of several measurements

• The long format(sometimes called the entity-attribute-valuemodel): Each row of a data frame contains one measurement, a single observation can span across several rows of a data frame

Both formats can be useful in statistical analysis; therefore, the DataFrames.jl package provides functionality allowing data frames to be converted from one format to another.

Getting ready

In this recipe, we use the Iris data set that we already used in the Reading CSV data from the internet recipe.

Make sure you have the CSV.jl and DataFrames.jl packages installed. If they are missing, add them using the following commands:

julia> using Pkg

julia> Pkg.add("DataFrames")

julia> Pkg.add("CSV")

Before we begin, start the Julia command line and load theiris.csvfile into adata...