1972 search results for "ggplot"

The Egyptian Revolution, in tweets

February 16, 2011
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The Egyptian Revolution, in tweets

Twitter played a significant role in the recent uprising in Egypt, with protesters communicating via tweets marked with the #25bahman hastag (February 14 in the arabic calendar) to plan and rally for the demonstration. Michael Bommarito downloaded all such tweets and plotted their frequency over time using R's ggplot2 library: Not surprisingly, the activity peaked on February 14. The...

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Mapping London’s Population Change 1801-2030

February 16, 2011
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Mapping London’s Population Change 1801-2030

Buried in the London Datastore are the population estimates for each of the London Boroughs between 2001 – 2030. They predict a declining population for most boroughs with the exception of a few to the east. I was surprised by this general decline and also the numbers involved- I expected larger changes from one year to ...

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Regional Variation in Law Enforcement Deaths – Part A

February 15, 2011
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Regional Variation in Law Enforcement Deaths – Part A

In recent months, there has been a series of high profile incidents in the United States where police officers were killed. While such events are unfortunate, the data suggests that it is extremely rare for an officer to be harmed or killed while on duty. In this post, I examine whether there are significant regional

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The Most Romantic Electro-Grunge Statistical Computing Song Ever Made

February 14, 2011
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The Most Romantic Electro-Grunge Statistical Computing Song Ever Made

Warning message: This song contains highly suggestive coefficients and graphic depictions of exuberant R-core lovin’. “Plotting Ihaka” is based on Rotting Piñata by Sponge, and reflects a small measure of my boundless joy in the world of R. Despite being a firm proponent of muffins, I can confidently say that I would rather live in

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The cranky guide to trying R packages

February 13, 2011
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The cranky guide to trying R packages

This is a tutorial on how to try out a new package in R. The summary is: expect errors, search out errors and don’t start with the built in examples or real data. Suppose you want to try out a novel statistical technique? A good fraction of the time R is your best bet for Related posts:

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Statistical Analysis with R, a Review

February 12, 2011
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Statistical Analysis with R, a Review

Long Version: I have a Bachelor’s degree in Computer Science.  I’m pretty handy when it comes to

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Troubling news for the teaching of evolution

February 9, 2011
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Troubling news for the teaching of evolution

A recent survey reported in Science ("Defeating Creationism in the Courtroom, but not in the Classroom"),  suggests that high school teachers are not teaching evolution to the fullest extent, say, that grammar is being taught in the English c...

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Opinions Not Backed by Money Are Not That Believable–Updated and with R

February 8, 2011
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Opinions Not Backed by Money Are Not That Believable–Updated and with R

As an update to http://timelyportfolio.blogspot.com/2010/12/opinions-not-backed-with-money-are-not.html, I have updated the revised data, added the past two months, and translated to R. If the world really is overly bullish on stocks as some suggest, I...

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Weight Loss Predictor

February 5, 2011
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Weight Loss Predictor

Got for 2010 Xmas a very cool book called the "4 Hour Body"(thanks Jose Santos) written by Tim Ferriss who write a previous favorite of mine about productivity, the 4 hour work week. Its an interesting book, because it has a scientific approach, it ...

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Speed up your R code with C++

February 3, 2011
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Speed up your R code with C++

Hi again, Recently, Julyan blogged about allocating memory first before modifying R objects. That’s a very useful trick that applies to most programming languages. Tonight I want to blog about something a bit more complicated and more specific to R, but which can lead to massive speed-ups: interfacing C/C++ within R codes. The rationale behind

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