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 "Julia for HPC" minisymposium aims to gather current and prospective Julia practitioners in the field of high-performance computing (HPC) from multidisciplinary applications. We invite participation from industry, academia, and government institutions interested in Julia’s capabilities for supercomputing. The goal is to provide a venue for Julia enthusiasts to share best practices, discuss current limitations, and identify future developments in the scientific HPC community.