DataSciPy: Julia Data Analysis


Jason Grafft will lead us through a data analysis using Julia programming language.

We'll look at the California Smarter Balanced Test Results from 2015 to 2018, and investigate factors affecting performance on the two Smarter Balanced exams (content areas English Language and Mathematics).

Starting from CSV files downloaded from the State's website, we'll examine the steps, techniques, and rationale used to bring the dataset from preparation to analysis and visualization. Our toolchain will use command line tools and Julia, featuring packages such as JuliaDB, Plots.jl, StatPlots.jl, and a handful of related statistical and numerical processing libraries.

Design and implementation are well-separated, making this a great case study for anyone working with data!