1881 search results for "tutorial"

Debugging with restore points instead of break points

February 15, 2015
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Debugging with restore points instead of break points

break points and restore points The standard method to debug an R function is to set break points via the browser function. When during execution of the function, browser() is called, the R console immediately changes into an interactive debugging mode that allows to step through the code and enter any R expressions. Thanks to RStudio's visual debugging support, this...

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Part 1: Introduction

February 14, 2015
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The software behind this clickbait data visualization will blow your mind

February 13, 2015
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The software behind this clickbait data visualization will blow your mind

New media sites like Buzzfeed and Upworthy have mastered the art of "clickbait": headlines and content designed to drive as much traffic as possible to their sites. One technique is to use coy headlines like "If you take a puppy video break today, make sure this is the dog video you watch." (Gawker apparently spends longer writing a headline...

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Steps toward recreating The Facebook IPO plot

February 12, 2015
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Steps toward recreating The Facebook IPO plot

NYCDSA Bootcamp 1: February–April 2015, Day 3 As data scientists, we are quite familiar finding and mucking through data. We merge, split, clean, and analyze the data

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Eight New Ideas From Data Visualization Experts

February 12, 2015
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Eight New Ideas From Data Visualization Experts

This post summarizes and visualizes eight key ideas we’ve heard from data visualization experts. Check out our first Case Study to learn more about using Plotly Enterprise on-premise, on your servers. To get started on free online graphing like in this post, check out our tutorials. Make Interactive Graphs Pictures of graphs in PowerPoints, dashboards, and emails can...

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The advantages of using count() to get N-way frequency tables as data frames in R

The advantages of using count() to get N-way frequency tables as data frames in R

Introduction I recently introduced how to use the count() function in the “plyr” package in R to produce 1-way frequency tables in R.  Several commenters provided alternative ways of doing so, and they are all appreciated.  Today, I want to extend that tutorial by demonstrating how count() can be used to produce N-way frequency tables

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The advantages of using count() to get N-way frequency tables as data frames in R

The advantages of using count() to get N-way frequency tables as data frames in R

Introduction I recently introduced how to use the count() function in the “plyr” package in R to produce 1-way frequency tables in R.  Several commenters provided alternative ways of doing so, and they are all appreciated.  Today, I want to extend that tutorial by demonstrating how count() can be used to produce N-way frequency tables

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The HP Workshop on Distributed Computing in R

February 12, 2015
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The HP Workshop on Distributed Computing in R

by Joseph Rickert In the last week of January, HP Labs in Palo Alto hosted a workshop on distributed computing in R that was organized by Indrajit Roy (Principal Researcher, HP) and Michael Lawrence (Genentech and R-core member). The goal was to bring together a small group of R developers with significant experience in parallel and distributed computing to...

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Cache Rules Everything Around Me

February 12, 2015
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Cache Rules Everything Around Me

Title with apologies to the Wu-Tang Clan. In this post, we're going to be discussing: Rcpp R's C interface The importance of CPU caches Performance benchmarking If none of these things is of interest you and you clicked anyway, please enjoy this picture of a cat: Background Cache is like your computer's ram, only very small and 50-100 times...

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Code as Magic, and the Vernacular of Data Wrangling Verbs

February 11, 2015
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Code as Magic, and the Vernacular of Data Wrangling Verbs

It’s been some time now since I drafted most of my early unit contributions to the TM351 Data management and analysis course. Part of the point (for me) in drafting that material was to find out what sorts of thing we actually wanted to say and help identify the sorts of abstractions we wanted to

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