JuliaCon 2022 (Times are UTC)

A Complete Guide to Efficient Transformations of data frames
07-26, 14:00–17:00 (UTC), Red

DataFrames.jl provides a comprehensive set of functions that allow performing transformations of tabular data using an operation specification language. This language lets users pass columns from a source data frame, a function to apply to them, and column names to store the result in the target data frame. In this workshop, I will explain the functionalities that it provides. Here you can find workshop materials.

The operation specification language that is part of DataFrames.jl can be used to perform transformations of data frames and split-apply-combine operations of grouped data frames. It is supported by the following functions combine, select, select!, transform, transform!, subset, and subset!.

Over the years, following users' requests, DataFrames.jl operation specification language has evolved over the years to efficiently support virtually any operation typically needed when working with tabular data. However, this means that it has become relatively complex. New users often feel overwhelmed by the number of options it provides.

This workshop aims to give a comprehensive guide to DataFrames.jl operation specification language. The presented material will help users learn this language and will be a reference resource.

Workshop materials are available for download here.

I am a researcher in the fields of operations research and computational social science.

For development I mostly use Julia language.

I am one of the maintainers of DataFrames.jl.