1067 search results for "how to import image file to R"

The R-Files: Saptarshi Guha

October 11, 2010
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The R-Files: Saptarshi Guha

"The R-Files" is an occasional series from Revolution Analytics, where we profile prominent members of the R Community. Name: Saptarshi Guha Background: Ph.D. in Statistics, Purdue University Nationality: India Years Using R: 6 Known for: Developing RHIPE package for R + Hadoop integration At just 31 years old, Saptarshi Guha has emerged as a cutting-edge contributor to the R...

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Getting going – importing data and plotting a simple graphic

July 20, 2010
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Getting going – importing data and plotting a simple graphic

The most difficult part of the learning curve in R is often getting going – many datasets are pre-installed in the packages and organised, so it is difficult to see how you to import your own data into R.  This post takes you step by step through the process of making a table from a

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Speed-reading files, revisited

December 29, 2009
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Speed-reading files, revisited

In a post earlier this month, it seemed as though compressing a data file before reading it into R could save you some time. With some feedback from readers and further experimentation, we might need to revisit that conclusion To recap, in our previous experiment it took 170 seconds to read a 182Mb text file into R. But if...

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Image Compression with the SVD in R

December 17, 2009
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Image Compression with the SVD in R

Over the next few posts, I’m going to be reviewing the use of R to implement the most commonly used matrix techniques for image manipulation. The code will be surprisingly simple to understand, because the real magic behind these techniques lies in the mathematics that R provides an abstract interface to. To start, I’m going

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Export Data Frames To Multi-worksheet Excel File

October 6, 2009
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Export Data Frames To Multi-worksheet Excel File

A few weeks ago I needed to export a number of data frames to separate worksheets in an Excel file. Although one could output csv-files from R and then import them manually or with the help of VBA into Excel, I was after a more streamlined solution, as I would need to repeat this process

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How to Import MS Excel Data into R

September 26, 2009
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How to Import MS Excel Data into R

s Sir Francis Bacon said, “Histories make men wise; poets witty; the mathematics subtile; natural philosophy deep; moral grave; logic and rhetoric able to contend.” And Windows stupid. He should have added the last sentence if he were a Windows user in this age. 1. Avoid Using M$ Excel A lot of R users often ask this question:

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Producing a Control Chart in R – An Application in Analytical Chemistry

Producing a Control Chart in R – An Application in Analytical Chemistry

Introduction Many processes in chemistry, especially in synthesis, require attaining a certain target value for a property of interest.  For example, when synthesizing drug capsules that contain a medicine, a chemist has to ensure that the concentration of the medicine meets a target value.  If the concentration is too high or too low, then the patient

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15 Questions All R Users Have About Plots

July 30, 2015
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15 Questions All R Users Have About Plots

R allows you to create different plot types, ranging from the basic graph types like density plots, dot plots, bar charts, line charts, pie charts, boxplots and scatter plots, to the more statistically complex types of graphs such as probability plots, mosaic plots and correlograms. In addition, R is pretty known for its data visualization The post

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MRAN’s Packages Spotlight

July 30, 2015
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MRAN’s Packages Spotlight

by Joseph Rickert New R packages just keep coming. The following plot, constructed with information from the monthly files on Dirk Eddelbuettel's CRANberries site, shows a plot of the number of new packages released to CRAN between January 1, 2013 and July 27, 2015 by month (not quite 31 months). This is amazing growth! The mean rate is about...

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Empirical bias analysis of random effects predictions in linear and logistic mixed model regression

July 30, 2015
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Empirical bias analysis of random effects predictions in linear and logistic mixed model regression

In the first technical post in this series, I conducted a numerical investigation of the biasedness of random effect predictions in generalized linear mixed models (GLMM), such as the ones used in the Surgeon Scorecard, I decided to undertake two explorations: firstly, the behavior of these estimates as more and more data are gathered for each

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