767 search results for "maps"

In case you missed it: January roundup

February 2, 2010
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In case you missed them, here are some articles from last month of particular interest to R users. This post linked to slides and video from a 30-minute "Introduction to R" talk I gave on January 28, with links to many useful R resources. This post brought news that R's creators Robert Gentleman and Ross Ihaka have jointly won...

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Ensemble Prediction

February 2, 2010
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Ensemble Prediction

Weather is unpredictable. Small differences in initial conditions can develop into big differences in the pattern of circulation, in the timing and location of cyclones, rainfall etc. This is true no matter how good the initial observing system is. The approach taken by organisations such as ECMWF or NCEP is to re-run numerical forecast models

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Re-mapping Massachusetts Special election results

January 27, 2010
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Re-mapping Massachusetts Special election results

I had previously posted maps showing the difference in major party vote share between the 2008 Presidential election and the 2010 special Senate election in Massachusetts. Colleagues and readers of the Revolutions blog had some very insightful criticisms of these maps, in particular that the color scale was over-stating the swing in voter sentiment. I’ve

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Mapping MA election results

January 25, 2010
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Mapping MA election results

The Swing State Project recently had some very interesting maps comparing last week’s election results from Massachusetts to 2008 presidential primary results. Their maps posted show some very interesting trends, but the maps themselves are lacking in information and the color schemes are pretty ugly. Using my own source data I recreated their election night

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How to make a heat map in R

January 21, 2010
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How to make a heat map in R

FlowingData has just posted a nice step-by-step tutorial on how to make a heat-map in R, like this one on attributes of NBA scorers: If you want to take the concept a step further with time-series data, you can also create calendar heat-maps in R. For example, you can track the level of activity in a forum, or the...

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Interesting use of levelplot() for time series data

January 16, 2010
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Interesting use of levelplot() for time series data

levelplot example: soil temperature (left) and moisture (right) Several recent articles appeared on the R-bloggers feed aggregator that demonstrated an interesting visualization of time series data using color. This style of visualization was readily adapted for the time...

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A new twist on the identifier mapping problem

January 11, 2010
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A new twist on the identifier mapping problem

Yesterday, Deepak wrote about BridgeDB, a software package to deal with the “identifier mapping problem”. Put simply, biologists can name a biological entity in any way that they like, leading to multiple names for the same object. Easily solved, you might think, by choosing one identifier and sticking to it, but that’s apparently way too

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Analyzing a FriendFeed group with Ruby and R

January 5, 2010
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Analyzing a FriendFeed group with Ruby and R

FriendFeed is a social media service, where groups of people can post interesting information from the Web, and "like" or comment posts from others. Statistical Bioinformatician Neil Saunders is a member of the "Life Scientists" group, and has posted an analysis of the group's activity in 2009 to his blog. He used Ruby and the FriendFeed API to extract...

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The Life Scientists at FriendFeed: 2009 summary

December 23, 2009
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The Life Scientists at FriendFeed: 2009 summary

It’s Christmas Eve tomorrow and so I declare the year over. My Christmas gift to you is a summary of activity in 2009 at the FriendFeed Life Scientists group. It’s crafted using R + Ruby, with raw data and some code snippets available. If you want to see the most popular items from the group

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Visualizing Unemployment in Mexico

December 22, 2009
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Visualizing Unemployment in Mexico

What has been the impact of the economic crisis on employment? And how has it affected the different regions of Mexico? To answer the questions the first step was to obtain the unemployment data from the Banco de Información Económica at the INEGI. ...

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