Use R for Business- Competition worth $ 20,000 #rstats

All you contest junkies, R lovers and general change the world people, here’s a new contest to use R in a business application

http://www.revolutionanalytics.com/news-events/news-room/2011/revolution-analytics-launches-applications-of-r-in-business-contest.php

REVOLUTION ANALYTICS LAUNCHES “APPLICATIONS OF R IN BUSINESS” CONTEST

$20,000 in Prizes for Users Solving Business Problems with R

PALO ALTO, Calif. – September 1, 2011 – Revolution Analytics, the leading commercial provider of R software, services and support, today announced the launch of its “Applications of R in Business” contest to demonstrate real-world uses of applying R to business problems. The competition is open to all R users worldwide and submissions will be accepted through October 31. The Grand Prize winner for the best application using R or Revolution R will receive $10,000.

The bonus-prize winner for the best application using features unique to Revolution R Enterprise – such as itsbig-data analytics capabilities or its Web Services API for R – will receive $5,000. A panel of independent judges drawn from the R and business community will select the grand and bonus prize winners. Revolution Analytics will present five honorable mention prize winners each with $1,000.

“We’ve designed this contest to highlight the most interesting use cases of applying R and Revolution R to solving key business problems, such as Big Data,” said Jeff Erhardt, COO of Revolution Analytics. “The ability to process higher-volume datasets will continue to be a critical need and we encourage the submission of applications using large datasets. Our goal is to grow the collection of online materials describing how to use R for business applications so our customers can better leverage Big Analytics to meet their analytical and organizational needs.”

To enter Revolution Analytics’ “Applications of R in Business” competition Continue reading “Use R for Business- Competition worth $ 20,000 #rstats”

More fun on Google Plus

I have been posting cool stuff from my G+ stream almost since the social network got released so continuing the series of posts on great stuff I get in my Google Plus stream

1) Photographers are good sharers

Anna Rumiantseva originally shared this post:

Photos from our recent trip to Santa Fe, NM. These are of Loretto Chapel which has the Miraculous Staircase. This staircase has a mystery to it has it is said to be built without nails by a carpenter who showed up after the sisters of the chapel prayed for 9 days. It took several months to be built by this carpenter who then left without pay and could not be found. The sisters believe it was St. Joseph himself that built the staircase and answered their prayers.
Please share if you like!

New Mexico (4 photos)

2) Cool Designer Retro Stuff

the water cooler at my workplace.

3) Social Media Experts-

Jay Jaboneta originally shared this post:

GMA Network launched an online campaign to raise awareness about the responsible use of social media, so please think before you click.

Jay Jaboneta changed his profile photo.

4) No you cant share gifs on Facebook

amazing rescue in Utah. http://www.sltrib.com/sltrib/news/52574438-78/story.csp?page=1

5) Cool Art

Monica Rocha originally shared this post:

6) Toons

Rupesh Nandy originally shared this post:

Birthdays – Then & Now

8) Geeks rock!

David Smith originally shared this post:

Yet another instance of the Golden Ratio in Nature: Irene.

lastly 9) Digital art

Marcelo Almeida originally shared this post:

behind the smile

But Willie Nelson rules them all

Willie Nelson covers Coldplay. Sounds pretty good! This reminds me of Johnny Cash’s cover ofHurt. (Yes, this is a Chipotle ad. It’s still pretty cool.)

Back to the Start

youtube.com – Coldplay’s haunting classic ‘The Scientist’ is performed by country music legend Willie Nelson

https://www.youtube-nocookie.com/v/aMfSGt6rHos?version=3&hl=en_US&rel=0

– see earlier posts at

Warning- this and earlier post deals with cute memes that can take a lot of time and energy!

Page Mathematics

I was looking at the site http://www.google.com/adplanner/static/top1000/index.html

and I saw this list (Below) and using a Google Doc at https://docs.google.com/spreadsheet/pub?hl=en_US&hl=en_US&key=0AtYMMvghK2ytdE9ybmVQeUxMeXdjWlVKYzRlMkxjX0E&output=html.

I then decided to divide pageviews by users to check the maths

Facebook is AAAAAmazing! and the Russian social network is amazing too!

The maths is wrong! (maybe sampling, maybe virtual pageviews caused by friendstream refresh)

but the average of 1,136 page views per unique visitor per month means 36 page views /visitor a Day!

Rank Site     Category        Unique Visitors (users) Page Views Views/Visitors

1  facebook.com	  Social Networks	880000000 1000000000000	1,136
29 linkedin.com	  Social Networks	80000000     2500000000	31
38 orkut.com	  Social Networks	66000000     4000000000	61
40 orkut.com.br	  Social Networks	62000000    43000000000	694
65 weibo.com	  Social Networks	42000000     2800000000	67
66 renren.com	  Social Networks	42000000     3300000000	79
84 odnoklassniki.ru Social Networks	37000000    13000000000	351
90 scribd.com	  Social Networks	34000000      140000000	4
95 vkontakte.ru	  Social Networks	34000000    48000000000	1,412

and

Rank Site	Category  Unique Visitors (users)Page Views	Page Views/Visitors
1 facebook.com	Social Networks	880000000	1000000000000	1,136
2 youtube.com	Online Video	800000000	100000000000	125
3 yahoo.com	Web Portals	590000000	77000000000	131
4 live.com	Search Engines	490000000	84000000000	171
5 msn.com	Web Portals	440000000	20000000000	45
6 wikipedia.org	Dict    	410000000	6000000000	15
7 blogspot.com	Blogging	340000000	4900000000	14
8 baidu.com	Search Engines	300000000	110000000000	367
9 microsoft.com	Software	250000000	2500000000	10
10	 qq.com	Web Portals	250000000	39000000000	156

see complete list at http://www.google.com/adplanner/static/top1000/index.html Continue reading “Page Mathematics”

#rstats -Basic Data Manipulation using R

Continuing my series of basic data manipulation using R. For people knowing analytics and

new to R.

1 Keeping only some variables

Using subset we can keep only the variables we want-

Sitka89 <- subset(Sitka89, select=c(size,Time,treat))

Will keep only the variables we have selected (size,Time,treat).

2 Dropping some variables

Harman23.cor$cov.arm.span <- NULL

This deletes the variable named cov.arm.span in the dataset Harman23.cor

3 Keeping records based on character condition

Titanic.sub1<-subset(Titanic,Sex=="Male")

Note the double equal-to sign

4 Keeping records based on date/time condition

subset(DF, as.Date(Date) >= '2009-09-02' & as.Date(Date) <= '2009-09-04')

5 Converting Date Time Formats into other formats

if the variable dob is “01/04/1977) then following will convert into a date object

z=strptime(dob,”%d/%m/%Y”)

and if the same date is 01Apr1977

z=strptime(dob,"%d%b%Y")

6 Difference in Date Time Values and Using Current Time

The difftime function helps in creating differences in two date time variables.

difftime(time1, time2, units='secs')

or

difftime(time1, time2, tz = "", units = c("auto", "secs", "mins", "hours", "days", "weeks"))

For current system date time values you can use

Sys.time()

Sys.Date()

This value can be put in the difftime function shown above to calculate age or time elapsed.

7 Keeping records based on numerical condition

Titanic.sub1<-subset(Titanic,Freq >37)

For enhanced usage-

you can also use the R Commander GUI with the sub menu Data > Active Dataset

8 Sorting Data

Sorting A Data Frame in Ascending Order by a variable

AggregatedData<- sort(AggregatedData, by=~ Package)

Sorting a Data Frame in Descending Order by a variable

AggregatedData<- sort(AggregatedData, by=~ -Installed)

9 Transforming a Dataset Structure around a single variable

Using the Reshape2 Package we can use melt and acast functions

library("reshape2")

tDat.m<- melt(tDat)

tDatCast<- acast(tDat.m,Subject~Item)

If we choose not to use Reshape package, we can use the default reshape method in R. Please do note this takes longer processing time for bigger datasets.

df.wide <- reshape(df, idvar="Subject", timevar="Item", direction="wide")

10 Type in Data

Using scan() function we can type in data in a list

11 Using Diff for lags and Cum Sum function forCumulative Sums

We can use the diff function to calculate difference between two successive values of a variable.

Diff(Dataset$X)

Cumsum function helps to give cumulative sum

Cumsum(Dataset$X)

> x=rnorm(10,20) #This gives 10 Randomly distributed numbers with Mean 20

> x

[1] 20.76078 19.21374 18.28483 20.18920 21.65696 19.54178 18.90592 20.67585

[9] 20.02222 18.99311

> diff(x)

[1] -1.5470415 -0.9289122 1.9043664 1.4677589 -2.1151783 -0.6358585 1.7699296

[8] -0.6536232 -1.0291181 >

cumsum(x)

[1] 20.76078 39.97453 58.25936 78.44855 100.10551 119.64728 138.55320

[8] 159.22905 179.25128 198.24438

> diff(x,2) # The diff function can be used as diff(x, lag = 1, differences = 1, ...) where differences is the order of differencing

[1] -2.4759536 0.9754542 3.3721252 -0.6474195 -2.7510368 1.1340711 1.1163064

[8] -1.6827413

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

12 Merging Data

Deducer GUI makes it much simpler to merge datasets. The simplest syntax for a merge statement is

totalDataframeZ <- merge(dataframeX,dataframeY,by=c("AccountId","Region"))

13 Aggregating and group processing of a variable

We can use multiple methods for aggregating and by group processing of variables.

Two functions we explore here are aggregate and Tapply.

Refering to the R Online Manual at

[http://stat.ethz.ch/R-manual/R-patched/library/stats/html/aggregate.html]

## Compute the averages for the variables in 'state.x77', grouped

## according to the region (Northeast, South, North Central, West) that

## each state belongs to

aggregate(state.x77, list(Region = state.region), mean)

Using TApply

## tapply(Summary Variable, Group Variable, Function)

Reference

[http://www.ats.ucla.edu/stat/r/library/advanced_function_r.htm#tapply]

We can also use specialized packages for data manipulation.

For additional By-group processing you can see the doBy package as well as Plyr package

 for data manipulation.Doby contains a variety of utilities including:

 1) Facilities for groupwise computations of summary statistics and other facilities for working with grouped data.

 2) General linear contrasts and LSMEANS (least-squares-means also known as population means),

 3) HTMLreport for autmatic generation of HTML file from R-script with a minimum of markup, 4) various other utilities and is available at[ http://cran.r-project.org/web/packages/doBy/index.html]

Also Available at [http://cran.r-project.org/web/packages/plyr/index.html],

Plyr is a set of tools that solves a common set of problems:

you need to break a big problem down into manageable pieces,

operate on each pieces and then put all the pieces back together.

 For example, you might want to fit a model to each spatial location or

 time point in your study, summarise data by panels or collapse high-dimensional arrays

 to simpler summary statistics.

Interview Beth Schultz Editor AllAnalytics.com

Here is an interview with Beth Scultz Editor in Chief, AllAnalytics.com .

Allanalytics.com http://www.allanalytics.com/ is the new online community on Predictive Analytics, and its a bit different in emphasizing quality more than just quantity. Beth is veteran in tech journalism and communities.

Ajay-Describe your journey in technology journalism and communication. What are the other online communities that you have been involved with?

Beth- I’m a longtime IT journalist, having begun my career covering the telecommunications industry at the brink of AT&T’s divestiture — many eons ago. Over the years, I’ve covered the rise of internal corporate networking; the advent of the Internet and creation of the Web for business purposes; the evolution of Web technology for use in building intranets, extranets, and e-commerce sites; the move toward a highly dynamic next-generation IT infrastructure that we now call cloud computing; and development of myriad enterprise applications, including business intelligence and the analytics surrounding them. I have been involved in developing online B2B communities primarily around next-generation enterprise IT infrastructure and applications. In addition, Shawn Hessinger, our community editor, has been involved in myriad Web sites aimed at creating community for small business owners.

Ajay- Technology geeks get all the money while journalists get a story. Comments please

Beth- Great technology geeks — those being the ones with technology smarts as well as business savvy — do stand to make a lot of money. And some pursue that to all ends (with many entrepreneurs gunning for the acquisition) while others more or less fall into it. Few journalists, at least few tech journalists, have big dollars in mind. The gratification for journalists comes in being able to meet these folks, hear and deliver their stories — as appropriate — and help explain what makes this particular technology geek developing this certain type of product or service worth paying attention to.

Ajay- Describe what you are trying to achieve with the All Analytics community and how it seeks to differentiate itself with other players in this space.

Beth- With AllAnaltyics.com, we’re concentrating on creating the go-to site for CXOs, IT professionals, line-of-business managers, and other professionals to share best practices, concrete experiences, and research about data analytics, business intelligence, information optimization, and risk management, among many other topics. We differentiate ourself by featuring excellent editorial content from a top-notch group of bloggers, access to industry experts through weekly chats, ongoing lively and engaging message board discussions, and biweekly debates.

We’re a new property, and clearly in rapid building mode. However, we’ve already secured some of the industry’s most respected BI/analytics experts to participate as bloggers. For example, a small sampling of our current lineup includes the always-intrigueing John Barnes, a science fiction novelist and statistics guru; Sandra Gittlen, a longtime IT journalist with an affinity for BI coverage; Olivia Parr-Rud, an internationally recognized expert in BI and organizational alignment; Tom Redman, a well-known data-quality expert; and Steve Williams, a leading BI strategy consultant. I blog daily as well, and in particular love to share firsthand experiences of how organizations are benefiting from the use of BI, analytics, data warehousing, etc. We’ve featured inside looks at analytics initiatives at companies such as 1-800-Flowers.com, Oberweis Dairy, the Cincinnati Zoo & Botanical Garden, and Thomson Reuters, for example.

In addition, we’ve hosted instant e-chats with Web and social media experts Joe Stanganelli and Pierre DeBois, and this Friday, Aug. 26, at 3 p.m. ET we’ll be hosting an e-chat with Marshall Sponder, Web metrics guru and author of the newly published book, Social Media Analytics: Effective Tools for Building, Interpreting, and Using Metrics. (Readers interested in participating in the chat do need to fill out a quick registration form, available here http://www.allanalytics.com/register.asp . The chat is available here http://www.allanalytics.com/messages.asp?piddl_msgthreadid=241039&piddl_msgid=439898#msg_439898 .

Experts participating in our biweekly debate series, called Point/Counterpoint, have broached topics such as BI in the cloud, mobile BI and whether an analytics culture is truly possible to build.

Ajay- What are some tips you would like to share about writing tech stories to aspiring bloggers.

Beth- I suppose my best advice is this: Don’t write about technology for technology’s sake. Always strive to tell the audience why they should care about a particular technology, product, or service. How might a reader use it to his or her company’s advantage, and what are the potential benefits? Improved productivity, increased revenue, better customer service? Providing anecdotal evidence goes a long way toward delivering that message, as well.

Ajay- What are the other IT world websites that have made a mark on the internet.

Beth- I’d be remiss if I didn’t give a shout out to UBM TechWeb sites, including InformationWeek, which has long charted the use of IT within the enterprise; Dark Reading, a great source for folks interested in securing an enterprise’s information assets; and Light Reading, which takes the pulse of the telecom industry.

Biography-

Beth Schultz has more than two decades of experience as an IT writer and editor. Most recently, she brought her expertise to bear writing thought-provoking editorial and marketing materials on a variety of technology topics for leading IT publications and industry players. Previously, she oversaw multimedia content development, writing and editing for special feature packages at Network World. Beth has a keen ability to identify business and technology trends, developing expertise through in-depth analysis and early-adopter case studies. Over the years, she has earned more than a dozen national and regional editorial excellence awards for special issues from American Business Media, American Society of Business Press Editors, Folio.net, and others.

Using #Rstats for online data access

There are multiple packages in R to read data straight from online datasets.
These are as follows- Continue reading “Using #Rstats for online data access”

Some future additions to Google Docs

1) More Presentation Templates

2) More HTML 5 clipart

3) Online Latex (lyx) GUI (or a Chrome Extension)

4) Online Speech to Text dictation (or a Chrome Extension)

5) Online Screen Capture software for audio and video editing (or a Chrome Extension)

6) Some sharing of usage and statistics with world tech community

7) An on -site in house version for enterprise software customers (|?)

8) An easy to make HTML5 editor using just the browser

Seriously http://googledocs.blogspot.com/ needs to be challenged more.

REVOLUTION ANALYTICS LAUNCHES “APPLICATIONS OF R IN BUSINESS” CONTEST

$20,000 in Prizes for Users Solving Business Problems with R

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