June 14-15, 2017
9:00 am - 5:00 pm
Instructors: Erika Mudrak, Lynn Johnson, David Kent, Stephen Parry
Helpers: Emily Davenport, Francoise Vermeylen, Michael Ko
Our workshop uses Data Carpentry lessons and is aimed at academic researchers in all fields and at all career stages. 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, Data analysis and visualization in R, R for Reproducible Scientific Analysis and Introduction to Python. 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 faculty, research staff, postdocs, graduate students, advanced undergraduates, and other researchers in any field. Priority will be given to people from Cornell Departments that support CSCU. See this page for a list of such departments.
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.
Prerequisites: We especially encourage registration for those who may be less familiar with the above topics. To allow for coverage of more advanced R topics, we require that participants be familiar enough with R and RStudio to:
=) and comments
head() str() summary() nrow() ncol() names() rownames() table() levels() mean() length() max() min()
as.factor() relevel() as.numeric()
seq()and index them with
[,]bracket notion and logical vectors (
==, !=, <, >, %in%) for conditions
plot() barplot() hist()
?or searching the help tab
If you have never used R or want a refresher, please prepare for the Data Carpentry Workshop by attending CSCU's free workshops:
Learn the above in Introductory Statistic Using R on June 12th
Practice the above in Intermediate Statistics Using R on June 13th.
Registration: We charge a $40 fee to help defray costs. Please register here.
Contact: Please mail email@example.com for more information.
Please be sure to complete these surveys before and after the workshop.
|Morning||Data organization in spreadsheets and OpenRefine|
|Afternoon||Data analysis and visualization in R|
|Morning||R for Reproducible Scientific Analysis|
|Afternoon||Introduction to Python|
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.