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Taught by Hadley Wickham. September 2012. Applied Statistics 2012, Rigno, Slovenia. Data science in R. July 2012. OSCON, Portland, OR. R development master class. June 2012. Bay Area/New York City. Big data summer institute. Rice University, Houston, TX. June 2012. CSIRO, Canberra. October 2011. Data visualisation in R with ggplot2 and plyr. Rice University. September 2011. Visualisation and data manipulation in R. R development master class. The Institute of Statistical Mathematics. November 2010.

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Taught by Hadley Wickham. September 2012. Applied Statistics 2012, Rigno, Slovenia. Data science in R. July 2012. OSCON, Portland, OR. R development master class. June 2012. Bay Area/New York City. Big data summer institute. Rice University, Houston, TX. June 2012. CSIRO, Canberra. October 2011. Data visualisation in R with ggplot2 and plyr. Rice University. September 2011. Visualisation and data manipulation in R. R development master class. The Institute of Statistical Mathematics. November 2010.

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3 effective visualisation

4 package development

5 ggplot2

6 introduction to plyr

7 user

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10 please email me

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Courses | courses.had.co.nz Reviews

https://courses.had.co.nz

Taught by Hadley Wickham. September 2012. Applied Statistics 2012, Rigno, Slovenia. Data science in R. July 2012. OSCON, Portland, OR. R development master class. June 2012. Bay Area/New York City. Big data summer institute. Rice University, Houston, TX. June 2012. CSIRO, Canberra. October 2011. Data visualisation in R with ggplot2 and plyr. Rice University. September 2011. Visualisation and data manipulation in R. R development master class. The Institute of Statistical Mathematics. November 2010.

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courses.had.co.nz

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An introduction to plyr: understanding large data with many models

http://courses.had.co.nz/09-user

An introduction to plyr: understanding large data with many models. A common pattern in the analysis of large data is to perform the same analysis on many (many many) smaller subsets of data. In this tutorial you will learn some basic statistical and computation strategies for solving this type of problem. During the course of the tutorial we will fit tens of thousands of linear models to a variety of datasets and explore how we can summarise the results to gain insight into our data. Tweaking your plots...

2

R development master class

http://courses.had.co.nz/12-devtools

R development master class. New York. 21-22 June 2012. Day 1: Advanced R programming. Introductions, outline and revision. Day 2: Package development. Outline of day two. All code and data.

3

Data science in R

http://courses.had.co.nz/12-oscon

Data science in R. OSCON, Portland, OR. July 16 2012. Make sure you have the following software installed:. Once you have R and Rstudio installed, open Rstudio and run the following code:. Install.packages(c(ggplot2, plyr, reshape2, stringr). You can check everything is installed correctly by running:. Library(ggplot2) qplot(mpg, wt, data = mtcars). Introductions and course outline. R language and ecosystem. Introduction to R and some of the thing that make it special as a language and an ecosystem.

4

Data manipulation and visualisation with R

http://courses.had.co.nz/09-umsl

Data manipulation and visualisation with R. Biology Department, University of Missouri, St Louis, MO. October 2009. How to create scatterplots, and how to add extra variables with aesthetics (like colour, shape and size) or facetting. Data: fuel economy of US cars. Graphics for large data. Group-wise summaries and transformations to add extra information to your plots. How to visualise time series. Data: trends in US baby names over the last 120 years. Polishing plots for publication. All code and data.

5

Effective Visualisation

http://courses.had.co.nz/12-effective-vis

Ribno, Slovenia. September 20, 2012. This half-day course will help you create better visualisations by teaching you about the findings from cognitive psychology that help us understand how the brain processes visual information. You’ll learn important principles that underlying all visual displays and find out about some common mistakes that lead to confusion and inaccurate perception. We’ll focus on four important principles:. Match perceptual and data topology. Make important comparisons easy.

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rdatamining.com

Online Documents, Books and Tutorials - RDataMining.com: R and Data Mining

http://www.rdatamining.com/resources/onlinedocs

RDataMining.com: R and Data Mining. Machine Learning 102 Workshop. Introduction to Data Mining with R. R Reference Card for Data Mining. R and Data Mining: Examples and Case Studies. Introduction to Data Mining with R and Data Import/Export in R. Data Exploration and Visualization with R. Regression and Classification with R. Data Clustering with R. Association Rule Mining with R. Text Mining with R. Twitter Data Analysis with R. Time Series Analysis and Mining with R. Principal Component Analysis (PCA).

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Taught by Hadley Wickham. September 2012. Applied Statistics 2012, Rigno, Slovenia. Data science in R. July 2012. OSCON, Portland, OR. R development master class. June 2012. Bay Area/New York City. Big data summer institute. Rice University, Houston, TX. June 2012. CSIRO, Canberra. October 2011. Data visualisation in R with ggplot2 and plyr. Rice University. September 2011. Visualisation and data manipulation in R. R development master class. The Institute of Statistical Mathematics. November 2010.

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