966 search results for "rstudio"

Introduction to dplyr: data manipulation made easy(er) and fun(er)

January 30, 2014
By
Introduction to dplyr: data manipulation made easy(er) and fun(er)

If you are just getting started in R, checkout my post on good references for beginners.  Hadly Wickham has come out with yet another R package that is destined to improve my workflow and let me concentrate less on getting R to do things, and more on my research questions. The package is dplyr, a reboot...

Read more »

dplyr 0.1.1

January 30, 2014
By
dplyr 0.1.1

We’re pleased to announce a new minor version of dplyr. This fixes a few bugs that crashed R, adds a few minor new features (like a sort argument to tally()), and uses shallow copying in a few more places. There is one backward incompatible change: explain_tbl() has been renamed to explain. For a complete list

Read more »

roxygen2 3.1.0

January 30, 2014
By
roxygen2 3.1.0

We’re pleased to announce a new version of roxygen2. The biggest news is that roxygen2 now recognises reference class method docstrings and will automatically add them to the documentation. 3.1.0 also offers a number of minor improvements and bug fixes, as listed on the github release notice. As always, you can install the latest version with install.packages("roxygen2").

Read more »

Fast and easy data munging, with dplyr

January 22, 2014
By

RStudio's Hadley Wickham has just introduced a new package for filtering, selecting, restructuring and aggregating tabular data in R: the dplyr package. It's similar in concept to Hadley's original plyr package from 2009, but with several key improvements: It works exclusively with data in R data frames; It can process data in remote databases (with the transformations done in-database...

Read more »

The performance of dplyr blows plyr out of the water

January 22, 2014
By

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 ›

Read more »

CrimeMap, LondonR and a Book Review

January 22, 2014
By
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...

Read more »

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

January 22, 2014
By
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

Read more »

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

January 20, 2014
By
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"...

Read more »

Introducing dplyr

January 20, 2014
By
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,

Read more »

Using the plyr package

January 18, 2014
By
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...

Read more »