Managing Data with R - (TRA111)
Friday, January 23, 2015 from 1:00 PM to 5:00 PM (EST)
Managing Data with R
Before you can analyze data, it must be in the right form. Getting it into that form is often where we spend most of our time. This 4-hour workshop shows how to perform the most commonly used data management tasks in R. We will cover how to use R’s popular add-on packages (dplyr, stringr, lubridate, tidyr, broom, compare, TableToLongForm, sqldf) and compare them to R’s older built-in functions.
Most of our time will be spent working through examples that you may run simultaneously on your computer. However, the handouts include each step and its output, so feel free to just relax and take notes. Most examples come from the extensive data management examples in the books, R for SAS and SPSS Users, R for Stata Users, and the web site, http://r4stats.com. That makes it easy to review what we did later with full explanations, or to learn more about a particular subject by extending an example which you have already learned.
At the end of the workshop, you will receive a set of practice exercises for you to do on your own time, as well as solutions to the problems. The instructor is available via email to address these problems or any other topics in his workshops or books.
Attendees should know basic R programming, including how to read data files and call functions.
When finished, you will be able to prepare most data sets for analysis.
Robert A. Muenchen is the creator of the web site http://r4stats.com and is the author of the books, R for SAS and SPSS Users, and, with Joseph Hilbe, R for Stata Users. An Accredited Professional Statistician™ with over 30 years of experience, Bob is the Manager of Research Computing Support (formerly the Statistical Consulting Center) at the University of Tennessee. Bob has served on the advisory boards of SAS Institute, SPSS Inc., the Statistical Graphics Corporation and PC Week Magazine. His suggested improvements or programming code have been incorporated into SAS®, SPSS®, JMP®, STATGRAPHICS® and several R packages.
1. Selecting/keeping Variables & Observations
2. Combining Steps: subset VS. nest vs. pipe
3. Copying & deleting/removing
4. Renaming data sets and variables
5. Transforming variables
6. Conditional transformations
7. Summarising/aggregating columns
8. Summarising/aggregating rows
9. Advanced by-group / split-file processing
with output management
10. Sorting/Ordering data
11. Selecting first or last observation per group
12. Stacking/concatenating data frames
13. Finding and removing duplicate observations
14. Merging/Joining data frames
15. Reshaping data frames
16. Comparing objects
17. Character string manipulations
18. Date & time manipulations
19. Using SQL within R
20. General Q & A
If you will be taking this course behind a firewall, you will need to access, dowwload and install the course material one week prior to the start of the class.
You will also need to have:
-RStudio installed on your machine prior to the begining of the course
-be able to unzip and install some working files
This course optionally follows a 2-day course called "R for SAS, SPSS, Stata Users"
We have the right to cancel the event for any reason at any time. Revolution Analytics will refund all monies paid for ticket sales in full in the event of a cancellation. We are not responsible for any travel related expenses incurred by attendees for this event. This includes but not limited to transportation, hotel accommodations or any other travel related expenses secured by the attendee, due to a cancellation on our part.
· 30 or more days from the event date: Full refund less 10%
· 16-29 days from the event date: 50% refund
· 15 or less days from the event date: No refund
· All related transaction fees PayPal and Eventbrite are not refundable
· Discount offers cannot be combined
· A student ID Number is not a proof of full time university enrollment to get the student’s discount. Proof of enrollment in 9 units or more on a current academic registration document will be required to receive the student's discount.
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