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init import
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tavisrudd committed Mar 23, 2011
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* Useful Links
https://bitbucket.org/tavisrudd/r_users_group_1/src
https://bitbucket.org/tavisrudd/r_users_group_1/get/tip.zip
https://bitbucket.org/tavisrudd/r_users_group_1/get/tip.tar.gz

* What's with the microphone??
** Sore arms from too much typing!
Please ignore it, and just focus on what commands I would have typed.



* Introductions And A Quick Survey
** Name and background
** Experience with R?
** Statistical training/experience?
** Programming experience?
** If no R experience, what have you heard about R?

** If no R experience, what do you want to learn?

* Thanks to our Sponsors!
** Pulse Energy, our host
** Revolution Analytics

* Goals
** Today
*** stoke your interest!
*** have some fun playing with it
*** line up speakers for next meeting in May
** For the Group
*** Not just about R!
Data management, analysis and visualization in general
*** meetings every 2 months
*** mix of interactive sessions and talks
* R as an Environment
** long history (S, S-PLUS)
** huge, rapidly growing community
thousands of libraries
http://crantastic.org/
http://cran.r-project.org/
Lots of interesting blogs:
http://www.r-bloggers.com/
http://learnr.wordpress.com/

** optimized for fast, INTERACTIVE data exploration
** awesome help system
** very easy to learn the basics, while doing useful things
* A Few Quick Examples
** employment data
[[file:unemployment.R::library(ggplot2)][unemployment]]

** US crimes by state
[[file:murder.R::crime%20<-%20read.csv("http:/datasets.flowingdata.com/crimeRatesByState2008.csv",][ murder_vs_burglary]]

** timeseries lattice graphics of sales data
[[file:lattice_timeseries_plots.R::require(zoo)][lattice_example]]

** Crayola colours over the years
[[file:crayola.R::library(Cairo)][crayola]]

** calendar heat map of blog posts
[[file:life_sciences_heatmap.R::library(ggplot2)%20#%20also%20loads%20library%20plyr][heatmap]]
* R as a Programming Language
** assignment with <- instead of =
** not zero indexed, starts at 1..
** vector-based rather than scalar based (very important!)
** functional, in a loose sense
*** higher order functions
*** lexical scoping
*** an "expression language"
*** looping in R syntax is inefficient
... but there are higher order functions that make it very efficient and easy.
*** not side-effect free, like Haskell or Erlang!
** Very useful built-in data types (similar to Python)
*** with a very useful vector/array/matrix slicing syntax
** functions take keyword arguments, with optional defaults
** "object-oriented", but with "generic functions"
** obj$attr NOT obj.attr
this.is.just.a.variable.name
this_is_NOT_valid
** a bit inconsistent and idiosyncratic, but awesome nonetheless
* Exercises
** import a small tabular / numeric dataset into R
Preferably your own data from real life projects, but there is plenty
of interesting CSV data on the web if you can't use your own.
** print summary descriptive statistics of the data
** examine the data structures that R stores it in
** create subsets of it
** create same basic charts of the data
** if applicable, explore relationships in the data (correlation, etc.)
* Resources
** http://www.statmethods.net/index.html
** http://www.r-tutor.com/
* What's next???
** A source of meeting / talk ideas:
http://www.meetup.com/R-Users/#past

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