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1. Become (re-)familiar with available geoms 2. Become (re-)familiar with aesthetic mappings in geoms (st*oke who Two weeks go I made whipped cream for the first time. In a tweet I lamented not having tried making it earlier in my life: This was an error that resulted in missing out because of a lack of confidence. Now the opposite tale. Missing out because of false confidence. I know ggplot2…there’s nothing new to learn. Recently I realized it’s been too long since I’ve re-read the docu*entation. I’m betting my time making this blog post that there’s a few more like me. I’m teaching an upcoming an*lysis course.  To prepare I’m reading and rereading many important texts including R for Data Science Didn’t know that…I figure I needed to spend a bit more time with the docu*entation and really get to know geoms and aesthetics that I > In brief, the grammar tells us that a statistical graphic is a > mapping from data to aesthetic attributes (colour, shape, size) of > geometric objects (points, lines, bars)….aesthetics…are the > properties that can be perceived on the graphic. Each aesthetic can Before getting started note that wordpress.com destroys code. To get the undestroyed version of code from this blog use this gist: I wasn’t sure how I was going to accomplish this task but a little digging showed that it was pretty easy.  First I used Dason ggplot2.  This is where I first hit a road block.  How do I get the aesthetics for a geom?  I recalled that the docu*entation tells you following line that creates the aesthetics reference in the docu*entation: That allowed me to follow the bread crumbs to make the following code to grab the aesthetics per geom and a flag for when an aesthetic is         aesthetic = union(req, sort(obj$aesthetics())),         required = aesthetic %in% req,     name <- switch(name,         jitter = point,         freqpoly = line,         histogram = bar,


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Title: TRinker's R Blog | Experiments & Experiences in Could be improved
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H1: TRinker's R BlogIs it informative enough?
H2: ggplot2: How Geoms & Aesthetics ≈ Whipped Cream
H3: Load PackagesIs it informative enough?

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About | TRinker's R Blog

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I'm a husband and father of 2 awesome s. I have a bent for the quantitative and a p ion for text. I use R to improve efficiency and effectiveness in my research tasks.   My research interests are: • Data Visualization • Discourse ysis • Text ysis • Improving Research Methods I have been an…

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My R Packages | TRinker's R Blog

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CRAN Packages I have developed multiple packages on CRAN pacman       [Development Version] qdap        [Development Version] qdapDictionaries       [Development Version] qdapRegex       [Development Version] qdapTools       [Development Version] regexr       [Development Version] reports       [Development Version] Github Packages embodied gmailR mapit metaDat plotflow shortcut

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/my-r-packages/qdap/:
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qdap | TRinker's R Blog

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qdap (Quantitative Discourse ysis Package) is an R package designed to ist in quantitative discourse ysis. The package stands as a bridge between qualitative transcripts of dialogue and statistical ysis and visualization. Installation To the development version of qdap: the zip ball or tar ball, decompress and run R CMD INSTALL on it,…

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/my-r-packages/qdapregex/:
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qdapRegex | TRinker's R Blog

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qdapRegex is a collection of regular expression tools ociated with the qdap package that may be useful outside of the context of discourse ysis. Tools include removal/extraction/replacement of abbreviations, dates, dollar amounts, email addresses, hash tags, numbers, percentages, person tags, phone numbers, times, and zip codes. Installation To the development version of qdapRegex: …

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/my-r-packages/qdaptools/:
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qdapTools | TRinker's R Blog

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qdapTools is an R package that contains tools ociated with the qdap package that may be useful outside of the context of text ysis. Installation To the development version of qdapTools: the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the devtools package to install the…

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