1762 search results for "ggplot2"

Customizing ggplot graphs

August 7, 2012
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There are many things I love about the R package ggplot2. For the most part, they fall into two categories:The "grammar of graphics" approach builds a hierarchical relationship between the data and the graphic, which creates a consistent, int...

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Unify R plots with pander

August 7, 2012
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Unify R plots with pander

MotivationR has a great variety of plotting tools (just to mention a few: the base graphics and e.g. lattice and ggplot2 packages building on grid) and most R user has a preference for either of them.I think all of you would agree with me: each package...

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At A Glance View of the 2012 Olympics Heptathlon Performances

August 4, 2012
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At A Glance View of the 2012 Olympics Heptathlon Performances

I spent most of today, err, yesterday, failing to hold back the tears as the medal performances from the Team GB Olympians kept rolling in… So to celebrate one of those wonderful performances, here are a couple of quick sketches of how Jessica Ennis made her medal in the Heptathlon. (The data is cut and

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Horizon Plots in Base Graphics

August 3, 2012
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Horizon Plots in Base Graphics

for background please see prior posts More on Horizon Charts, Application of Horizon Plots, Horizon Plot Already Available, and Cubism Horizon Charts in R There are three primary graphics routes in R (base graphics, lattice, and ggplot2), and each have...

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2012 Olympics Swimming – 100m Butterfly Men Finals prediction

August 3, 2012
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2012 Olympics Swimming – 100m Butterfly Men Finals prediction

2012 Olympics Swimming - 100m Butterfly Men Finals prediction Author: Matt Malin Inspired by mages’ blog with predictions for 100m running times, I’ve decided to perform some basic modelling (loess and linear modelling) on previous Olympic results for the 100m Butterfly Men’s medal winning results. Code setup library(XML) library(ggplot2) swimming_path <- "http://www.databasesports.com/olympics/sport/sportevent.htm?sp=SWI&enum=200" swimming_data <- readHTMLTable( readLines(swimming_path), which = 3, stringsAsFactors...

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R training: Visualization, Big Data, Data Mining, and Marketing Analytics

August 2, 2012
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Revolution Analytics is hosting several live and online courses over the next couple of months that will be of interest to R users looking to hone their skills: Visualization in R with ggplot2. Garrett Grolemund and Winston Chang instruct how to use the ggplot2 package to make, format, label and adjust graphs using R. (August 28, Redwood City, CA.)...

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Genetic algorithms: a simple R example

August 1, 2012
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Genetic algorithms: a simple R example

Genetic algorithm is a search heuristic. GAs can generate a vast number of possible model solutions and use these to evolve towards an approximation of the best solution of the model. Hereby it mimics evolution in nature. GA generates a population, the individuals in this population (often called chromosomes) have  Read more »

Genetic algorithms: a simple R example

August 1, 2012
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Genetic algorithms: a simple R example

Genetic algorithm is a search heuristic. GAs can generate a vast number of possible model solutions and use these to evolve towards an approximation of the best solution of the model. Hereby it mimics evolution in nature. GA generates a population, the individuals in this population (often called chromosomes) have a given state. Once the population is generated, the state of these individuals is evaluated...

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Text and symbol size in multi-panel figures in R

July 31, 2012
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Text and symbol size in multi-panel figures in R

In R, there are a couple of packages that allow you to create multi-panel figures (see examples here and here), but, of course, you can also make multi-panel figures in the base package*. Below I provide a simple example for creating a multi-panel figure in the R base package with the focus on making the

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Yet Another Forecast Dashboard

July 30, 2012
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Yet Another Forecast Dashboard

Recently, I came across quite a few examples of time series forecasting using R. Here are some examples: Time series cross-validation 4: forecasting the S&P 500 Holt-Winters forecast using ggplot2 Autoplot: Graphical Methods with ggplot2 Large-Scale Parallel Statistical Forecasting Computations in R (2011) by M. Stokely, F. Rohani, E. Tassone Forecasting time series data ARIMA

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