I can’t believe how fast time is flying by in this course. We are currently on Week 7, making next week our last week in the online portion of the course. In Week 6, we reviewed data management plans – I enjoyed this week because it provided an opportunity to apply some of the concepts and principles that we had learned in previous weeks in a real, practical way. This week, we’re learning about data wrangling, one of the most interesting phrases I’ve heard in a while.

Data wrangling is a component of data science, something that ties in fairly closely with data management. What excited me the most about this topic was the potential for librarian support in the area of programming. A key part of data wrangling is altering the format of a data set to better suit computational analysis, and programs like R and Python are some commonly used tools for this element of the data science process (both in wrangling and analysis).

I had developed some interest in Python a few years ago and dabbled in some introductory instruction through Codecademy. Due to a busy schedule, I was never able to develop any kind of expertise in the programming language. Incidentally, I found out last year that my husband also had a dream of mastering a programming language and I encouraged my parents to get him a “Learn to Code Python”-type book for Christmas. We got busy again after the holiday, and unfortunately neither of us has had the time to dig in to the book.

But now I have some extra motivation to add this endeavor to my project list. I don’t know how useful this would end up being to my future RDM services – it’s very possible (and even likely) that no researcher would ever ask for my assistance in designing code for a data science project in my current position. But since this is a skill I’ve been wanting to develop anyway, I might as well add it to my repertoire. It’s so nice when personal desires and professional development come together.

P.S. If anyone is curious, this is the book I plan to use to teach myself some Python.

Image Credit: Python by Chris Parker via Flickr