Intersession and Summer Hours

Congratulations for all of you graduating this year! You have worked hard and we are proud of you!

For those who will be here with us for a little while longer, fear not! We are here to help you during the summer months. Our hours will be as follows:

May 13-22nd, 9am-5pm M-F, Closed Saturday and Sunday.

From May 23rd-August 5th:
Monday-Thursday: 9am-9pm
Friday: 9am-5pm
Saturday: 10am-6pm
Sunday: Closed

We will be closed May 30th for Memorial Day and July 4th for Independence Day. We can’t wait to see you in the summer months!

Digital Centers Intern Showcase, May 5th

Don’t miss the Digital Centers Intern Showcase on May 5 from 12pm – 2pm in the Studio@Butler!DCIP Intern Showcase Slide (2)

This program, held every year, is the chance to see the fruits of the labors of the interns in the Digital Centers Internship Program (

Our interns will share their projects and answer questions about their work and their experiences collaborating with the staff of the Libraries. We at the Digital Centers are very proud of the work that our interns do, and we are excited to share all of their accomplishments with you.

Using R with ArcGIS

With a successful collaboration between DSSC and ESRI, a hands-on workshop on ESRI R plugin was presented by Shaun Walbridge, a senior developer from ESRI, on Wednesday, April 20. Shaun provided an in-depth tutorial on how to use R in ESRI, and answered questions from students and librarians.

Our audiences were from a broad background: librarians from Columbia and other institutions in NYC, PhD students, Master’s students, people from administrations, etc.


Presentation Highlights:

SP data types in R
  • 0D: SpatialPoints
  • 1D: SpatialLines
  • 2D: SpatialPolygons
  • 3D: Solid
  • 4D: Space-time
R — ArcGIS Bridge
  • Store your data in ArcGIS, access it quickly in R, return R objects back to ArcGIS native data types (e.g. geodatabase feature classes).
  • Knows how to convert spatial data to sp objects.
  • Package Documentation
  • Upcoming: Conda for managing R environments

For more information about this workshop, please visit

Thank you again for joining us!



Extended Hours and Study Hall

Can you believe it is already getting close to finals? We can’t either! To help you in your mad rush to the end of the year the library will begin extended hours and study hall starting April 17, 2016. The hours will be as follows:

Sunday: 11am-Midnight, Study Hall Midnight-4am
Monday-Thursday: 9am-Midnight, Study Hall 8am-9am, Midnight-4am
Friday:9am-10pm, Study Hall 8am-9am, 10pm-4am
Saturday: 10am-10pm, Study Hall 10pm-4am

Service desks will be closed Sunday-Thursday at 11:45PM and Friday & Saturday at 9:45PM from 4/18-5/12 during study hall hours. It will remain open as a study hall space from 4/18 midnight until 4AM and 4/18-4/11 8am-9am, midnight until 4am. We will close at Midnight on 5/12 and begin winter intersession hours on 5/13.

Happy Studying!

R Open Labs: mi

Last week, Professor Ben Goodrich stopped by R Open Labs to show us how to use the mi package, which he worked on with Professor Andrew Gelman.

As the name ‘mi’ suggests, this package does multiple imputations to help you predict missing values in your data sets.


Screen capture of mi demo by Benjamin Goodrich





Check out the demo if you’d like to give the mi package a try!

R Open Labs continues every Weds, 10 am -12pm, through April 20th.  Drop in anytime! 



R Open Labs: QQPlot

Post by Ellie Ransom, Research Services Coordinator, Science and Engineering Libraries

At last week’s R Open Lab, we visualized our data to test our assumptions of normality using two of of R’s native commands, qqnorm and qqline.

We practiced using the built in dataset, trees, and looked at the variables Height and Volume separately.

Notice how the Height variable is basically normal, but the Volume variable appears to be skewed.


Inline image 2


Inline image 3

It might make sense to transform the skewed data before analyzing it!


Inline image 4

Share your thoughts and suggestions with us here, and we’ll see you next week!

R Open Labs: Loading Data

At last week’s R Open Lab, we explored two packages (Memisc and foreign) as well as some of R’s native commands for loading data files into our R Studio workspace.

View Slides

I <3 R









We practiced with ASCII, .TSV, .SAV, and .DTA files, all available from ICPSR, a data archive with a rich collection of social science data sets.

We’re taking a break from  R Open Labs this week, but we’ll be back on February 17 at 10 am in the DSSC.

Share your thoughts and suggestions with us here, and we’ll see you next week!


R Open Lab: Week 1

I <3 R

Last week, we kicked off R Open Labs with a demo on Base Graphics, or how to make graphics using basic commands. We also gave a brief intro to Swirl, a great package for learning R.

You can catch up here with these helpful slides: Base Graphics System

Check back next week, Wednesday, Feb. 3 at 10 am, for a quick demo on how to load different data files into R, a free I <3 R button, and plenty of time to practice your code and ask questions.

Got feedback or want to suggest a package to demo? Leave a comment or take our short survey!

Lehman Library Spring 2016 Hours

26777r Welcome back! We hope you had a relaxing winter recces! Lehman Library will be open from 9am-5pm on January 18th, 2016.Starting January 19th we will begin our normal semester hours which are as follows:

Monday-Thursday: 9am-Midnight
Friday: 9am-7pm
Saturday: 10am-6pm
Sunday: 11am-11pm

We look forward to seeing you soon!

R Open Labs this Spring in the DSSC

By WOCinTech Chat [CC BY-SA 2.0], via Flickr

By WOCinTech Chat [CC BY-SA 2.0], via Flickr

10am – 12pm
Every Wednesday
Digital Social Science Center

Stop by any Wednesday this Spring for R Open Labs. We start off every Open Lab with a 10 minute exploration of an R package or dataset; the rest of the time is yours to work on homework, research or building your coding skills in good company.

This Spring we’ll be digging into:

  • dplyr
  • ggplot2
  • Shiny
  • mySQL
  • your choice!

Beginners welcome!  We want to hear from you which datasets and packages you want to learn.

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