Prepared for https://odsc.com/europe/, 10:15-11:45 AM GMT, June 9, 2021
In many data science ecosystems data frame is a pivotal object. It is not only very useful conceptually, but also ensures that data transformation operations can be performed efficiently. Therefore packages like data.table in R or pandas in Python are star players.
With the Julia language the situation is different because it gives you the speed out of the box. Therefore the DataFrames.jl package is designed to be a sidekick that conveniently supports your core data analysis pipeline. It has a more focused functionality than e.g. pandas, but at the same time it seamlessly integrates with the whole Julia data science ecosystem.
During this workshop, using hands-on examples, I will discuss the design principles behind DataFrames.jl and walk you through key functionalities provided by this package.
Please check the flights.jl file in this repository for the instructions.
This version of the tutorial was updated to use Julia 1.9.0 and DataFrames.jl 1.5.0.