Motivation Lately, I, Edward, have been programming in Julia a lot. Two times in the last week, I’ve needed a function like R’s tapply(), but in Julia. With a little bit of searching around the interwebs, I hacked together a reasonable equivalent to R’s tapply() written in Julia. This blog post will explain the function tapply() and briefly introduce the two examples where I used tapply(). Last, I’ll provide my Julia code which replicates R’s tapply() function.
Data is not neutral, nor are the algorithms that control how the data that governs our lives are used. Interpretations and recommendations made using data are subjective. This course introduces students how to start harnessing the power of data to intelligently cope with the requirements of citizenship, employment, and family to be prepared for a healthy, happy and productive life. In this class students will practice collecting and wrangling data into a usable form, visualizing large data sets to discover patterns, representing data in a meaningful way, exploring varying interpretations of the data and results, and discussing potentials for misuse and abuse.
Logistics / Setup Presenter: Robin Donatello, Assistant Professor of Statistics Date: Tuesday February 19th, 2019 Time: 3-3:50 pm Location: Tehama 116 RSVP: http://goo.gl/forms/BnjV0y5zoz09tUU83 Description You’ve got person level data (like country of origin) in one data set, annual data (like income) for each person across multiple years in another data set, but each person is on a team and team characteristics are on yet a THIRD data set. How do you link all this information together to gain any kind of insights?
Spring 19 semester is upon us and we’re exicted to start up Community Coding again. Dates & Times: Tuesday & Thursday - 2-4pm Location : Tehama (THMA) 116 What is community coding? Students, staff, faculty, and the public are invited to join our Community Coding sessions. Bring your computer, coding projects, and your questions to this open working environment. What is this for credit option? Commit to studying 1 hr.
Logistics / Setup Date: Tuesday April 24, 2018 Time: 2-3:50 pm Location: MLIB 442 Description Planning on participating in Data Fest 2018? Want to practice your data wrangling skills? On Tuesday we will be doing a “dry run” of DataFest by using 2017 data. Basically here’s the data and the overall analysis goal. GO!
April is Data Fest Prep month! Hone your skills in preparation for this exciting data hackathon event! Logistics / Setup Date: Thursday April 12, 2018 Time: 3-3:50 pm Location: MLIB 442 Presenter: Edward Roualdes Workshop Materials Python Notebook HTML version of the notebook Description In this workshop, we’ll explore Python and Jupyter notebooks as data analysis tools. The basics of statistical analysis will be focused on Python’s library Pandas.