177 search results for "geographical"

Working with geographical Data. Part 1: Simple National Infomaps

December 21, 2012
By
Working with geographical Data. Part 1: Simple National Infomaps

There is a popular expression in my country called “Gastar polvora en chimangos”, whose translation in English would be “spending gunpowder in chimangos”. Chimango is a kind of bird whose meat is useless for humans. So “spending gunpowder in chimangos” … Continue reading →

Read more »

A brief script on Geographical data analysis in R

A brief script on Geographical data analysis in R

I saw this post and I decided to replicated that good example but with data closer to me, particulary data of my country. So, I've got the shape data of the capital of my country (You can download the data from here). The data comes from the 2002 CENSO...

Read more »

How to map geographically-detailed survey responses?

January 17, 2012
By

David Sparks writes: I am experimenting with the mapping/visualization of survey response data, with a particular focus on using transparency to convey uncertainty. See some examples here. Do you think the examples are successful at communicating both local values of the variable of interest, as well as the lack of information in certain places? Also, The post How...

Read more »

Creating 3D geographical plots in R using RGL

July 11, 2011
By
Creating 3D geographical plots in R using RGL

I've been playing around with the rgl package in the last week, as part of an ongoing quest to come up with nice-looking (but more importantly, useful) data vizualisations. It's a nice little package, and once you've run through the excell...

Read more »

Geographic data to service the needs of a remote employee – part1

April 4, 2016
By
Geographic data to service the needs of a remote employee – part1

By Ava Yang Background Ever since I started working remotely, some friends suggested “Why not work as usual as you travel across China, instead of staying in Shanghai?” Many cool people have practiced the lifestyle, but most of the time … Continue reading →

Read more »

Election analysis contest entry part 1 – introducing the nzelect R package

April 2, 2016
By
Election analysis contest entry part 1 – introducing the nzelect R package

The contest Inspired by Ari Lamstein’s R Election Analysis Contest, I’ve fast-tracked a project that’s been at the back of my mind for a while, to make available in a friendly, tidy R package a range of data about New Zealand elections. My entry for the contest will involve 3 or 4 posts over the next week or...

Read more »

Easier Composite U.S. Choropleths with albersusa

March 29, 2016
By
Easier Composite U.S. Choropleths with albersusa

Folks who’ve been tracking this blog on R-bloggers probably remember this post where I showed how to create a composite U.S. map with an Albers projection (which is commonly referred to as AlbersUSA these days thanks to D3). I’m not sure why I didn’t think of this earlier, but you don’t need to do those

Read more »

inegiR version 1.2

February 21, 2016
By
inegiR version 1.2

Version 1.2 of inegiR is now on CRAN so I thought I’d write a few words/vignette about what’s new or different, if at all. By the way, i’m writing in english because more people seem to read r-bloggers than my blog (no surprise there), however the pdf manual and most documentation is still in spanish. Bug fixes Thanks...

Read more »

Clustering French Cities (based on Temperatures)

February 11, 2016
By
Clustering French Cities (based on Temperatures)

In order to illustrate hierarchical clustering techniques and k-means, I did borrow François Husson‘s dataset, with monthly average temperature in several French cities. > temp=read.table( + "http://freakonometrics.free.fr/FR_temp.txt", + header=TRUE,dec=",") We have 15 cities, with monthly observations > X=temp > boxplot(X) Since the variance seems to be rather stable, we will not ‘normalize’ the variables here, > apply(X,2,sd) Janv Fevr Mars...

Read more »

Google Geo Data – Data Access Without Restrictions

January 18, 2016
By
Google Geo Data – Data Access Without Restrictions

Geo-Distances are of great importance: Researchers from various disciplines refer to geographic distances – health researchers refer to geographic data when analyzing the spread of diseases, economists when evaluating the impact of transaction costs on human behavior, or sociologists when evaluating interpersonal distances (based on external factors) in human interaction. However, each query sent to The post

Read more »

Sponsors

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)