"LISA is the home of ops people who do ops correctly. I’m always motivated by the conference content and hallway conversations to be better, and I take home the knowledge needed to move closer to that goal. "
Tony Del Porto, Cisco Systems, Inc.
"LISA is the best mix of training, talks, and networking of any events I've been to. That's the reason I've been to 11 of them.”
LISA14 Attendee
"If you're a sysadmin slaving away in a metaphorical basement and re-inventing the wheel every time your employer's business goals change slightly, LISA will help pull you into the light."
Marc Chiarini, Long-Time IT Admin and Researcher, MarkLogic Corp
"This was my first LISA. It was great attending a conference that focused on my role without trying to shoehorn every challenge into a specific vendor's solution. The same mix of awesome sessions, speakers, and other attendees will bring me back every year."
LISA14 Attendee
"Great sessions, great presenters, great community. I feel like I can make up a year of following news and forums on the subject in a week."
LISA14 Attendee
"No matter if you are dealing with the latest tech or trying to maintain something from the dark ages of the ‘90s, there are people at LISA who are experienced with it. Heck, many of the people who _developed_ this tech attend. This is a great place to get answers and ideas."
Lee Damon, University of Washington
"In a world where technology changes rapidly, it's hard to find great resources for in-depth expertise. LISA has a terrific combination of people who create the technology and people who implement it effectively for their companies."
Matt Simmons, Northeastern University
"I like seeing where the industry is heading, how SysAdmins/engineers are evolving, tools they are using, common problems and solutions across the world."
The R programming language and ecosystem constitute a rich tool set for performing system analyses, for communicating the results and importance of those analyses, and for ensuring reproducible and repeatable results.
This tutorial is designed to
motivate you to pick up R,
demonstrate useful techniques using R,
illustrate ways to simplify your life by automating data analysis and reporting
Examples will be based on situations that the instructor encountered during routine system operations. Additional exercises and data sets that students can explore following the workshop will be provided. The instructor will be available in the LISA Lab after the workshop.
Who should attend:
System administrators who are awash in operational data and want to do a more effective job of understanding their data and communicating their findings should attend this class. Prior knowledge of R is not required, but if you are already working with R, you are welcome! Facility with programming and a knowledge of basic descriptive statistics will be assumed.
Take back to work:
This introduction to R and its ecosystem provides a walk along the R main line—coming up to speed on R, accessing data, analyzing data, and getting the message out. The key points include:
Acquaintance with R, R packages, and R Studio
Understanding where R fits into the system administrator’s tool set
Familiarity with basic R data manipulation techniques
Basic principles for ensuring reproducible and automated analyses
Motivation to learn or improve your R skills
Next steps in mastering R
Topics include:
Introduction to the R ecosystem (R, R Studio, CRAN)
Why should you consider R?
The R programming model: functions, tables, and packages
The basic data analysis workflow
Reading and writing data from files and pipes
Data frames and data frame manipulations
Using the plyr and dplyr packages to slice and dice data
Using the ggplot2 package for graphing
Overview of the R package system
Other useful R packages
Additional Materials:
The following software packages should be installed in advance of the tutorial:
R: Version 3 or later from CRAN or as supported by your OS. Some distributions have packages already available; others have both pre-compiled binaries and source code available from CRAN). R requires about 160MB (installed) on Mac OS X. Source code is available. License: GNU General Public License (GPL).
Optional: R Studio. Requires R, plus an additional 305MB on Mac OS X. Binary installations are available for Ubuntu, Fedora, Mac OS X, and Windows. Source code is available. R Studio does not appear to be supported for the BSD distributions. License: GNU Affero General Public License.
Once you have installed R and (optional) R Studio, you can download contributed packages. Class demonstrations will use plyr and ggplot2. Other packages will be introduced as needed.
