2063 search results for "ggplot2"

ngramr – an R package for Google Ngrams

July 16, 2013
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ngramr – an R package for Google Ngrams

The recent post How common are common words? made use of unusually explicit language for the Stubborn Mule. As expected, a number of email subscribers reported that the post fell foul of their email filters. Here I will return to the topic of n-grams, while keeping the language cleaner, and describe the R package I developed

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Popularity bigdata / large data packages in R and ffbase useR presentation

Popularity bigdata / large data packages in R and ffbase useR presentation

(This article was first published on BNOSAC - Belgium Network of Open Source Analytical Consultants, and kindly contributed to R-bloggers) A few weeks ago, Rstudio released it's download logs, showing who downloaded R packages through their CRAN mirror. More info: http://blog.rstudio.org/2013/06/10/rstudio-cran-mirror/ This is very nice information and it can be used to show the popularity of packages with R, which has...

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Visualizing a tiny slice of India’s demographics with information from Wikipedia

July 10, 2013
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Visualizing a tiny slice of India’s demographics with information from Wikipedia

This post presents a tiny slice of a complex and diverse India using charts. (Data retrieval from Wikipedia on 9 July, 2013 and the analysis were performed using R; charts were generated using ggplot2, googleVis and wordcloud. More information can be f...

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rCharts version of d3 horizon

July 10, 2013
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rCharts version of d3 horizon

I love horizon plots.  My love shows up throughout my blog, and I have plotted horizon charts in base graphics, xtsExtra, lattice, and ggplot2.  Now with rCharts, we can implement Jason Davies d3.js horizon chart plugin to plot R data in...

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Unicode Tips in Python 2 and R

July 9, 2013
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Unicode Tips in Python 2 and R

Most of time, I don’t need to deal with different encodings at all. When possible, I use ASCII characters. And when there is a little processing in Chinese characters or other Unicode characters, I use .Net languages or JVM languages, in which every string is Unicode and of course when the characters are displayed they are displayed as characters...

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Interactive Heatmaps (and Dendrograms) – A Shiny App

July 7, 2013
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Interactive Heatmaps (and Dendrograms) – A Shiny App

Heatmaps are a great way to visualize data matrices. Heatmap color and organization can be used to  encode information about the data and metadata to help learn about the data at hand. An example of this could be looking at the raw data  or hierarchically clustering samples and variables based on their similarity or differences.

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ggmap : Interesting toolbox for spatial analysis

July 7, 2013
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ggmap : Interesting toolbox for spatial analysis

ggmap is a new tool which enables such visualization by combining the spatial information of static maps from Google Maps, OpenStreetMap, Stamen Maps or CloudMade Maps with the layered grammar of graphics implementation of ggplot2The library is developped by David Kahle and Hadley Wickham and in the latest R/Journal (Volume 5/1, June 2013),...

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A Recipe for Trellis/Faceted Plots Using Base R Graphics

July 5, 2013
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A Recipe for Trellis/Faceted Plots Using Base R Graphics

I frequently use lattice and ggplot2 to create trellis/faceted graphics. But, I gave up using these packages in a recent application, where I had initially constructed a complex graphic using the base R plotting functions. When I later decided that I wanted a faceted version, there was a dilema: re-create the complex graphic using lattice

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Creating good looking survival curves – the ‘ggsurv’ function

July 4, 2013
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Creating good looking survival curves – the ‘ggsurv’ function

This is a guest post by Edwin Thoen Currently I am doing my master thesis on multi-state models. Survival analysis was my favourite course in the masters program, partly because of the great survival package which is maintained by Terry Therneau. The …Read more »

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Fun simulating Wimbledon in R and Python

July 4, 2013
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Fun simulating Wimbledon in R and Python

R and Python have different strengths. There's little you can do in R you absolutely can't do in Python and vice versa, but there's a lot of stuff that's really annoying in one and nice and simple in the other. I'm sure simulations can be run in R, but it seems frightfully tricky. Recently I wrote a simple Tennis simulator...

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