Nov 14-15, 2016
9:00 - 16:30
Instructors: Mateusz Kuzak, Moritz Neeb
Helpers: Andrew MacDonald
Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.
We will cover Data organization in spreadsheets and OpenRefine, Introduction to R, Data analysis and visualization in R and SQL for data management. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.
Who: The course is aimed at graduate students and other researchers.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating sytem (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.
Contact: Please mail the FRB team for more information.
Please be sure to complete these surveys before and after the workshop.
|Morning||Data organization in spreadsheets and OpenRefine|
|Afternoon||Introduction to R|
|Morning||Data analysis and visualization in R|
|Afternoon||SQL for data management|
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Data Carpentry workshop, you will need working copies of the described software. Please make sure to install everything (or at least to download the installers) before the start of your workshop. Participants should bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.
Please follow these Setup Instructions.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.