Handling missing data
In this recipe, you will find out how to create a correlation matrix from DataFrame of numbers whose entries can contain missing values.
Getting ready
Make sure you have the CSV.jland 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")
Also, download the following file and load it into a variable called df by using the following commands:
julia> download("https://openmv.net/file/class-grades.csv", "grades.csv") julia> using CSV, DataFrames, Statistics julia> df = CSV.read("grades.csv");
Note
In the GitHub repository for this recipe, you will find the commands.txt file, which contains the presented sequence of shell and Julia commands. An additional example related to this recipe can be found in the cor.jl file. The grades.csv file is also stored in the repository, in case you have problems with downloading it.
Now, continue working...
