Www.the-data-mine.co.uk Best of UseR! 2011 A personal & biased view with an emphasis on data visualisation Andy Pryke [email protected] Birmingham.

www.the-data-mine.co.uk

Best of UseR! 2011

A personal & biased view with an emphasis on data visualisation

Andy Pryke

[email protected]

Birmingham R User Meeting20th March 2012


My Bias…

I work in commercial data mining, data analysis and data visualisation

Background in computing and artificial intelligence

Use R to write programs which analyse data


Using Google Visualisation API from R

Speaker: Markus Gesmann, LloydsMotivation: Display statistics about publications on a website

•18 different charts are available through Google API•Requires internet access & viewed through web browser•Data is embedded in HTML, with call to google's javascript visualisation API•Using RAPACHE you can mix HTML & R (bit like Sweave)•Can update data & look of chart from R by modifying the object returned by the plotting method


Google Visualisation API - Code

install.packages("googleVis")library("googleVis")demo("googleVis")demo(package="googleVis")

# Example from demo:require(datasets)states <- data.frame(state.name, state.x77)GeoStates <- gvisGeoChart(states, "state.name", "Illiteracy", options=list(region="US",displayMode="regions", resolution="provinces",width=600, height=400))plot(GeoStates)


Google Visualisation API – More info

Use at Lloyds: http://lloyds.com/stats

Video demo: http://goo.gl/zfQdG


Google Visualisation API - Examples












More Information…

In use on Lloyds website: http://lloyds.com/stats

Original Slides: http://web.warwick.ac.uk/statsdept/user-2011/TalkSlides/Contributed/16Aug_0950_Kaleid_Ib_2-Gesmann.pdf - Includes good list of other interesting packages

http://lloyds.com/stats


Nomograms for visualising relationshipsbetween three variables

Jonathan Rougier - Dept Mathematics, Univ. Bristol

Kate Milner - Crossroads Veterinary Centre,Buckinghamshire


How to Use R, in a Morocan Marketplace, to Improve the Life of Donkeys

It's hard to weigh donkeys in North Africa, but useful to know their weight when prescribing drugs.

1) Measure the weight, height,girth, body condition, age and gender of donkeys.

2) Use R to create a predictive model of weight3) Create a nonographic model which can be used by

vets on the ground


How Heavy is that Donkey?

Initial Model – Complex !

sqrt(Weight) ~ BCSis + Gender + Age + log(HeartGirth) + log(Height) + log(HeartGirth):log(Height) + BCSis:log(HeartGirth) + Gender:log(HeartGirth) + Age:log(HeartGirth) + BCSis:log(Height) + Gender:log(Height) + Age:log(Height)


How Heavy is that Donkey?

Use stepAIC in the MASS package to simplify the model…

Final Model:

sqrt(Weight) ~ BCSis + Age + log(HeartGirth) + log(Height)

Still hard to use in a dust marketplace though…


Solution - Nomograms

“Graphical representation of formula allowing calculations to be made using paper and a ruler”

Published in books & on charts to make complex calculations possible before calculators & computers

Ron Doerfler, 2009, The Lost Art of Nomography, The UMAP Journal, 30(4), pp. 457-493.

http://myreckonings.com/wordpress/wp-content/uploads/JournalArticle/The Lost Art of Nomography.pdf




More information…

Jonty’s Home page with links to slides & code from: http://www.maths.bris.ac.uk/~MAZJCR/#pres

Presentation Slides: http://www.maths.bris.ac.uk/~MAZJCR/jontyUseR.pdf

Package Design also has a nomogram function() – Not in Cran any more but old versions available.


Easy interactive ggplots

Speaker: Richie CottonClever use of packages ggplots and gWidgetstcltk

together, allowing clear and simple code for interactive control of charts

Example data: Chromium exposure of welders. Took air concentations & urine samples (pre/post exposure)


More Information…

Links at: http://www.bitly.com/jV1NBnCode linked directly from

http://4dpiecharts.com/2011/08/17/user2011-easy-interactive-ggplots-talk/

See also: package gWidgets - wraps 5 UI toolkits


Predicting Personality fromSocial Network Data

Speaker: Daniel Chapsky, Hampshire CollegeThis was quite a fast talk, but one of my favourite pieces of work, so

apologies if I've mis-interpreted anything!

Big 5 theory of personality is that 5 dimensions can predict attitude, views, behaviour

This work attempts to build a model which predicts someone's "big 5" values from Online Social Network (OSN) data


Predicting Personality - Data

• 615 respondents• 100 question open source personality test, "IPIP NEO"• Data last.fm, netflicks, etc – e.g. genres listened to• Distance from home town to current residence

- liberallity correlates with amount of moving around• Mean income, Education level• Race inferred from surname• Data was continuous• Missing data was inferred using gibbs sampling


Predicting Personality – Model

Continuous bayesian networks - discrete needs more data - Often weaker prediction than black box + Clear semantics + Works with limited evidence + Hybrid network


Predicting Personality – Packages

Database connectivity - RMySQLWeb scraping / API connection - RCurl, RJSONIO, XML Inference through mashups - psych, geosphereData Cleaning - plyr, reshape2, bayestree, mice, tm, mvoutlier Bayesian Network construction - bnlearn, pcalg Parallelization of optimization - foreach, snow Graphics - Latticist, bnlearn, ggplot2


Agreeableness = 42.4

- 1.26(Sex.Missing)

- 2.47(Sex.Male)

- 25.99(Home.Teen.Prop)

- 0.63(Movie.Dystopia-Political)

- 0.49(Movie.Action-thriller)

+ 6.51(Wall.Status.Ratio)

+ 0.08(Conscientiousness)

- 0.29(Neuroticism)

R2 = 0.46


More Information

Original Slides:http://web.warwick.ac.uk/statsdept/user-2011/TalkSlides/Contributed/17Aug_1115_FocusIII_5-DataMining_2-Chapsky.pdf

Www.the-data-mine.co.uk Best of UseR! 2011 A personal & biased view with an emphasis on data visualisation Andy Pryke [email protected] Birmingham.

Documents

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