1002 search results for "RStudio"

The performance of dplyr blows plyr out of the water

January 22, 2014
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Together with many other packages written by Hadley Wickham, plyr is a package that I use a lot for data processing. The syntax is clean, and it works great for breaking down larger data.frame‘s into smaller summaries. The greatest disadvantage… See more ›

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CrimeMap, LondonR and a Book Review

January 22, 2014
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CrimeMap, LondonR and a Book Review

In preparation for my LondonR talk in March, I am polishing up my CrimeMap (see previous blog post here and here) in my spare time. Thanks to Chris Beeley and Packt, I won a free e-copy of Chris Beeley’s book following his great talk about...

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Using One Programming Language In the Context of Another – Python and R

January 22, 2014
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Using One Programming Language In the Context of Another – Python and R

Over the last couple of years, I’ve settled into using R an python as my languages of choice for doing stuff: R, because RStudio is a nice environment, I can blend code and text using R markdown and knitr, ggplot2 and Rcharts make generating graphics easy, and reshapers such as plyr make wrangling with data

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Fast-track publishing using knitr: stitching it together (part V)

January 20, 2014
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Fast-track publishing using knitr: stitching it together (part V)

Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. There has been plenty of feedback and interest for the series, and in this post I would like to provide (1) a brief summary and (2) an example showing how to put all the pieces together. [caption id="attachment_1094"...

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Introducing dplyr

January 20, 2014
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Introducing dplyr

dplyr is a new package which provides a set of tools for efficiently manipulating datasets in R. dplyr is the next iteration of plyr, focussing on only data frames. dplyr is faster, has a more consistent API and should be easier to use. There are three key ideas that underlie dplyr: Your time is important,

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Using the plyr package

January 18, 2014
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Using the plyr package

Introduction The base R system provides lapply() and related functions, and the package plyr provides alternatives that are worth considering. It will be assumed that readers are familiar with lapply() and are willing to spend a few moments reading the plyr documentation, to see why the illustration here will use the ldply() function. The test task will be extraction of...

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Fast-track publishing using knitr: table mania (part IV)

January 15, 2014
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Fast-track publishing using knitr: table mania (part IV)

Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. While illustrations (previous post) are optional, tables are not, and this fourth article is therefore devoted to tables. Tables through knitr is probably one of the most powerful fast-track publishing tools, in this article I will show (1) how...

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Example 2014.1: "Power" for a binomial probability, plus: News!

January 14, 2014
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Example 2014.1: "Power" for a binomial probability, plus: News!

Hello, folks! I'm pleased to report that Nick and I have turned in the manuscript for the second edition of SAS and R: Data Management, Statistical Analysis, and Graphics. It should be available this summer. New material includes some of our more po...

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Calling Python from R with rPython

January 13, 2014
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Calling Python from R with rPython

Python has generated a good bit of buzz over the past year as an alternative to R. Personal biases aside, an expert makes the best use of the available tools, and sometimes Python is better suited to a task. As a case in point, I recently wanted to pull data via the Reddit API. There The post Calling...

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Why R is Better Than Excel for Fantasy Football (and most other) Data Analysis

January 13, 2014
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Many articles have been written on why R is better than Excel for data analysis.  In this post, I will summarize the reasons why R is advantageous in most data The post Why R is Better Than Excel for Fantasy Football (and most other) Data Analysis appeared first on Fantasy Football Analytics.

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