800 search results for "Maps"

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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NCEP Global Forecast System

December 16, 2009
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NCEP Global Forecast System

Just about everyone is familiar with weather maps. There are many situations where it is useful to combine the underlying numerical weather data with other types of information. Accessing  the weather data is a necessary first step. The output from the U.S. National Centers for Environmental Prediction (NCEP) Global  Forecast System (GFS) is freely available.

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APIs: I wish the life sciences would learn from social networks

December 10, 2009
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APIs: I wish the life sciences would learn from social networks

I was prompted by a thread on the apparent decline of FriendFeed to look for evidence of declining participation in my networks. First, a quick and dirty Ruby script, tls.rb to grab the Life Scientists feed and count the likes and comments: #!/usr/bin/ruby require 'rubygems' require 'json/pure' require 'net/http' require 'open-uri' def format_date(d) if d

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R, REvolution named in top analytic trends for 2010

December 7, 2009
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Author and enterprise software executive Nenshad Bardoliwalla lists his Top 10 Trends for 2010 in Analytics, Business Intelligence, and Performance Management at the website Enterprise Irregulars. If you've been following the Business Intelligence space (and who hasn't, right?) you'll recognize some familiar themes: predictive analytics, Web 2.0, Software-as-a-Service, risk, IBM. What's interesting about this list is that it raises...

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In case you missed it: November roundup

December 4, 2009
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In case you missed them, here are some articles from last month of particular interest to R users. This post demonstrated reader Paul Bleicher's code for visualizing a time series as a heat-map calendar. This post and followup showed (with thanks to Drew Conway) how to use R to perform social network analysis on live data from Twitter. This...

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My Five Rules for Data Visualization

December 3, 2009
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My Five Rules for Data Visualization

Tonight the NYC R Meetup will be discussing data visualization in R using ggplot2. As part of tonight’s meeting I will be providing a very brief show and tell, which includes mostly code examples and external resources. This exercise has had me thinking quite a bit about data visualization. In addition, a

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Export Trade Clusters

November 24, 2009
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Export Trade Clusters

This post, as with the prior ones on trade clusters, aims to help visualize patterns of trade in the OECD from 50 years of partner trade statistics. The data is rich, meaning we should be able to develop rich intuition by exploring it visually. These slides follow the method laid out in Jong-Eun Lee, “Two

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Mapping Biomes

November 20, 2009
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Mapping Biomes

Recently (2008) the European Space Agency produced GlobCover (ESA GlobCover Project, led by MEDIAS-France), the highest resolution (300m) global land cover map to date. GlobCover uses 21 primary land cover classes and many more sub-classes. Land cover classification (LCC) schemes divide the earth into biomes. Biomes are the simplest way to classify vegetation which can

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