Posts Tagged ‘ Data management ’

Using R — A Script Introduction to R

October 17, 2012
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To many people, R is like the Everglades. They’ve heard of it, they know it’s big and has amazing treasures deep inside. Articles in the media can make it look irresistible. But after a personal or even second hand experience …  &#16...

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Processing Data from a Statistica Worksheet Using R

August 29, 2012
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Processing Data from a Statistica Worksheet Using R

Context: I work with data from non-profit organizations, and so a big concern in many of my analyses is if and how much people are donating from one year to the next.  One of the  things I normally like to do … Continue reading →

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unsupervised classification of a Landsat image in R: the whole story or part two

August 1, 2012
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unsupervised classification of a Landsat image in R: the whole story or part two

The main question when using remote sensed raster data, as we do, is the question of NaN-treatment. Many R functions are able to use an option like rm.NaN=TRUE to treat these missing values. In our case the kmeans function in R is not capable to use such a parameter. After reading the tif-files and creating

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unsupervised classification of a raster in R: the layer-stack or part one.

July 29, 2012
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unsupervised classification of a raster in R: the layer-stack or part one.

In my last post I was explaining the usage of QGis to do a layerstack of a Landsat-scene. Due to the fact that further research and trying out resulted in frustration I decided to stick with a software I know well: R. So download the needed layers here and open up your flavoured version of

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introduction to R: learning by doing (part 1)

July 9, 2012
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introduction to R: learning by doing (part 1)

Geography is often about statistics as it is the basis for fast exchange of information: providing a mean and standard deviation to the audience is often much easier then showing raw data: Learning a script language for this purpose can be a hard-ass work. But I think it is more often a need of practice.

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reproducible documents/analytics in R: the knitr package

June 26, 2012
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reproducible documents/analytics in R: the knitr package

When I am working in new institutions and I am asking: “Do you have a document management system?” I often get the answer:”Yap, we are using folders” … OKAY. Making analysis, developing applications and keeping an eye on code, data and applications make this even harder as it has to be. Of course not many

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reading shape files in R

June 24, 2012
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reading shape files in R

If I would like to adjust a shape file I normally used the way over an excel file or a text file to get a table and to join this with an existing shape file. Due to the sp and rgdal packages in R you can manipulate shapefiles directly in R: now lets map the

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setting your working directory permanently in R

June 24, 2012
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Most of us R users are using a special working directory for the daily work in R. But I was bothered in typing everytime in my command line prior using R. Also using this line at the first position in scripts was not pleasent enough. So how to get around this? There is a special

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Sampling and the Analysis of Big Data

April 8, 2012
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Sampling and the Analysis of Big Data

After my last post, I came across a few articles supporting the opinion that if you have a good reason to take random samples from a “big” dataset, you’re not committing some kind of sin: Big Data Blasphemy: Why Sample? … Continue reading →

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The Clipboard can be Your Friend

January 17, 2011
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The Clipboard can be Your Friend

One of the features I feel that I don’t leverage enough, particularly for ad-hoc questions, is the clipboard feature  in R. I know there are many ways to use it –  as I have been exposed to a few –  but the example below, even without context, should get you thinking about how awesome R

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