1713 search results for "Excel"

Running Back-tests in parallel

November 11, 2013
By
Running Back-tests in parallel

Once you start experimenting with many different asset allocation algorithms, the computation time of running the back-tests can be substantial. One simple way to solve the computation time problem is to run the back-tests in parallel. I.e. if the asset allocation algorithm does not use the prior period holdings to make decision about current allocation,

Read more »

Merge Relational Dataframes

November 11, 2013
By
Merge Relational Dataframes

A Question Recently, a student, working on her Senior Thesis at Northland College, asked me the following question: Attached is an Excel file with three “important to R” worksheets. The only thing that connects all 3 worksheets is the Lift.ID … Continue reading →

Read more »

What’s in my Pocket? (Part II) – Analysis of Pocket App Article Tagging

November 10, 2013
By
What’s in my Pocket? (Part II) – Analysis of Pocket App Article Tagging

IntroductionYou know what's still awesome? Pocket.As I noted in an earlier post (oh god, was that really more than a year ago?!) I started using the Pocket application, previously known as Read It Later, in July of 2011 and it has changed my readi...

Read more »

Hurricanes and Reproducible Research

November 8, 2013
By
Hurricanes and Reproducible Research

On vacation with my family this week and that means I have a few minutes now and again to read. One of the books I brought along is Christopher Gandrud’s excellent “Reproducible Research with R and RStudio”. Looking for some data as a test project, I latched onto Hurricane data. Folly Beach was hit pretty

Read more »

The R Backpages

November 7, 2013
By
The R Backpages

by Joseph Rickert As an avid newspaper reader (I still get the print edition of the New York Times delivered every Sunday morning) I have always thought that some of the most interesting news is to be found in the back pages. So, in that spirit here are some things that I thought might be fit to print. Plotly...

Read more »

Unsupervised data pre-processing: individual predictors

November 7, 2013
By
Unsupervised data pre-processing: individual predictors

I just got the excellent book Applied Predictive Modeling, by Max Kuhn and Kjell Johnson . The book is designed for a broad audience and focus on the construction and application of predictive models. Besides going through the necessary theory in a not-so-technical way, the book provides R code at the end of each chapter.

Read more »

NYC R Programming Classes – starting this coming Sunday

November 5, 2013
By
NYC R Programming Classes – starting this coming Sunday

Guest post by Vivian Zhang, original post. You can sign up for our Sunday Intensive beginner level R classes at NYC Data Science Academy meetup page or [email protected] more info. Brief: The course (which will meet five Sundays) will start from the basics, introducing the building blocks used for programming in R and building intuition for writing clean and robust code....

Read more »

Archival and analysis of #GI2013 Tweets

November 4, 2013
By
Archival and analysis of #GI2013 Tweets

I archived and analyzed all Tweets containing #GI2013 from the recent Cold Spring Harbor Genome Informatics meeting, using my previously described code.Friday was the most Tweeted day. Perhaps this was due to Lior Pachter's excellent keynote, "Stories ...

Read more »

Dream Team – combining Tableau and R

November 3, 2013
By
Dream Team – combining Tableau and R

Last quarter was a bit too busy to write some new blog post because of a new job. And changing the job often come along with changing the tools you work with. That was my way to Tableau. Tableau is one of the new stars in the BI/Analytics world and definitely worth a look. The people at Tableau...

Read more »

Data Preparation – Part I

October 31, 2013
By
Data Preparation – Part I

The R language provides tools for modeling and visualization, but is still an excellent tool for handling/preparing data. As C++ or python, there is some tricks that bring performance, make the code clean or both, but especially with R these choices can have a huge impact on performance and the “size” of your code. A The post Data...

Read more »

Sponsors

Mango solutions



RStudio homepage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training



http://www.eoda.de









ODSC

CRC R books series











Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)