1877 search results for "Tutorial"

shinyEvents: build shiny apps with event handlers

January 15, 2015
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shinyEvents: build shiny apps with event handlers

RStudio's shiny is a great framework to generate web applications with R. In a classical shiny app, interactivity is not generated via event handlers but by reactive programming. For details, see the shiny documentation and tutorials under http://shiny.rstudio.com/. While shiny's reactive programming model is great for smaller apps, I personally found it less useful for bigger applications that create...

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Debugging with restore points instead of break points

January 14, 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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Creating WEB APPS WITH SHINY – REACTIVE GRAPH OF AVERAGE US HOUSEHOLD INCOME BY RACE

January 13, 2015
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Creating WEB APPS WITH SHINY – REACTIVE GRAPH OF AVERAGE US HOUSEHOLD INCOME BY RACE

I finally finished my first Shiny application! You can click this link to check it out. Below is a screenshot of what it looks like. I got all the data from the United States Census Bureau website. What the app does is provide a comparison of average income by race for...

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How to format your chart and axis titles in ggplot2

January 13, 2015
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How to format your chart and axis titles in ggplot2

Once you know how to create simple plots you’ll want to learn how to design more sophisticated plots. A large part of being able to design sophisticated plots is having control over the “non-data elements” of the plot, such as the plot title and axis titles.You want to be able to format those and polish The post

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Interactive visualizations with R – a minireview

January 9, 2015
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2015-01-10 00_34_37-Clipboard

Interactive visualization allows deeper exploration of data than static plots. Javascript libraries such as d3 have made possible wonderful new ways to show data. Luckily the R community has been active in developing R interfaces to some popular javascript libraries to enable R users to create interactive visualizations without knowing any javascript. In this post I have reviewed...

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Nine Interactive 3D Graphs That Let You Zoom, Flip, & Spin

January 8, 2015
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Nine Interactive 3D Graphs That Let You Zoom, Flip, & Spin

Plotly’s interactive 3D graphs have new capabilities: multiple scenes, streaming graphs, and contour lines. Plot from our web app, Excel, Google Docs, Python, MATLAB, and R. Contact us if you’re interested in running Plotly on-premise to integrate your own applications. Click any image to go to the full-screen interactive version. Mount Bruno Elevation...

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WrightMap: Multifaceted models

January 7, 2015
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WrightMap: Multifaceted models

We received an email from a user who was interested in displaying results from a multifaceted model in WrightMap. In the WrightMap manual, we show how to use multifaceted results from ConQuest: fpath <- system.file("extdata", package = "WrightMap") model4 <- CQmodel(file.path(fpath, "ex4a.mle"), file.path(fpath, "ex4a.shw")) wrightMap(model4, item.table = "rater", interactions = "rater*topic", step.table = "topic") (See this tutorial for more details.) But...

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Top 77 R posts for 2014 (+R jobs)

January 7, 2015
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Top 77 R posts for 2014 (+R jobs)

R-bloggers.com is 5 years old this month! In celebration, this post share links to the top 77 most read R posts of 2014 (+stats on R-bloggers, + top R jobs for the beginning of 2015)

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Run scoring trends: using Shiny to create dynamic charts and tables in R

January 7, 2015
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Or, Retracing my stepsAs I’ve been learning the functionality of Shiny, the web app for R, I have used the helpful tutorials available from the developers at RStudio. At some point, though, one needs to break out and develop one’s own application.  My Shiny app “MLB run scoring trends” can be found at (

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Mapping Seattle Crime

January 6, 2015
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Mapping Seattle Crime

Last week I published a data visualization of San Francisco crime. This week, I’m mapping Seattle crime data. The map above is moderately complicated to create, so I’ll start this tutorial with a simpler case: the dot distribution map. Seattle crime map, simplified version First, we’ll start by loading the data. Note that I already The post

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