01 Intro

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  • Hi, Juan Fukushima, I am, a young economist in the north of Peru, I like to study in every case about stadistics, because i am looking for create new methods in my box tools. (in my profile). sometimes I has felt lost in the R code, but, thanks for paper as you write, i can found to help here, Thank you very much
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01 Intro

  1. 1. plyr Introduction Hadley Wickham Tuesday, 7 July 2009
  2. 2. 1. About me 2. Active learning 3. Resources 4. Outline of the course Tuesday, 7 July 2009
  3. 3. About me New assistant professor at Rice University. Interested in developing tools that make analysis easier - focussing more on data cleaning, organisation and exploration than traditional statistics. Have written 17 R packages at last count. Tuesday, 7 July 2009
  4. 4. Active learning Hard to absorb much information from pure lecture format (especially after lunch!), so we’ll be breaking things up with some short interactive activities. Please take 30 seconds now to introduce yourself to your neighbours. You’ll be working with them in a bit. Tuesday, 7 July 2009
  5. 5. Resources All code, data & slides available at http://had.co.nz/plyr/09-user Tutorial covers most of the material in http://had.co.nz/plyr/plyr-intro.pdf, but with more examples, and at a higher level. Problems or questions? Use the manipulatr mailing list: http://groups.google.com/group/manipulatr Tuesday, 7 July 2009
  6. 6. Outline Basic strategy: split-apply-combine. Exploring US baby name trends Modelling Texas house sales Wrap up: how it all fits together Can’t go into much detail in 3 hours, but hopefully this tutorial will get you off to a good start. Tuesday, 7 July 2009
  7. 7. Code bnames-explore.r—what we’ll work through next bnames-cluster.r—expanded example showing how to find cluster of similar names tx-explore-houston.r—introduction to housing data tx-explore-all.r—process of model building for large data nnet.r—fitting a neural network with many random starts and varying parameters Tuesday, 7 July 2009
  8. 8. Split-apply-combine Split up a big dataset Apply a function to each piece Combine all the pieces back together Keep this theme in mind as we work through the examples. Tuesday, 7 July 2009

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