Time/Date: Jan 26, 6 PM – 7 PM
Room: Conference Room
Instructor: Lydia Jessup
Description
So you’ve connected to an API, found an open data portal or recieved a csv in your inbox. What next? In the real world, data are messy and need to be checked, prepared and cleaned before being analyzed, turned into a data visualization or fed into a machine learning algorithm. This workshop will cover the basics of the steps to go through in order to 1) get to know your raw data and 2) tidy your data. We’ll discuss what people want to do with data (machine learning, visualization, analysis, other??) and we’ll work through examples of how to get the data ready for that together. I’ll be going through these examples in R (the favorite statistical software among data scientists) but the concepts and steps can be applied to other statistical software or coding languages.
Prerequisites
Bring a laptop and dataset or project idea if you want, but I’ll have example data to use if you don’t have anything specific in mind!
Veronica Alfaro
Ji Young
Nick
Google drive folder here: https://drive.google.com/drive/folders/1Z2piLb5ZQyEv7QA9LvE73709IpQyoYMV?usp=sharing