Triangle Julia User – Getting Started with Julia for Data Analysis

April 18th at Durham

On April 18th, I went to the Getting Started with Julia for Data Analysis event organized by Triangle Julia Users. The event was very different from what I thought it would be. Originally, I thought the process would be the presenter open up Julia and teach us step by step on basic functionalities of Julia. However, this introduction event was very technical. The presenter started with all the packages available for Julia on Github and explained Julia’s relationship with Python, Kaggle, and etc. Then he introduced several Julia IDE and cloud-programming tools, and talked about the advantages and disadvantages of each of those. The emphasis was really on the compatibility of Julia with other programming tools or systems. The presenter did not really show the basic functionalities of Julia but just listed out several reference links from where one can learn the language. Since it was a little too technical, there were several times that I got lost in their conversations.

After the event, I was surprised to learn that Github is much more powerful than I thought it was. Basically everything about Julia is on Github. By looking at it briefly, Julia language is a lot like a combination of Python and R. Sounded like that Julia ran faster than R and the coding was more intuitive. I would love to explore Julia sometime after the finals.