Ggplot2

What Hacker News says

1. npgatechMay 2017
   I find it the opposite. The syntax is the most intuitive of all plotting applications.

   Layers are as follows [1]

   1. Data

   2. Aesthetic mappings

   3. Statistical transformation (stat)

   4. Geometric object (geom)

   5. Position adjustment

   Once you get a hang of this, it becomes easy to create new plots purely from the understanding of the layers. In matplotlib or even in Seaborn, I find myself constantly Googling for examples.

   ggplot2 is the most beautiful thing to happen in visualization space!

   [1] Wickham, Hadley, and Carson Sievert. "4.4.1 Layers." Ggplot2: Elegant Graphics for Data Analysis. Dordrecht: Springer, 2016. N. pag. Print.

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2. hazexpJan 2012
   If you're interested in good references for being able to produce `visual stories' I suggest you have a look into the R package `ggplot2' [1].

   It's a great way (although a little challenging at first) of being able to produce almost all of the types of plots you're interested in creating. The author of the package also wrote a great book [2] on the package which is worth a read.

   A note though, most information on `ggplot2' isn't really aimed at informing you which is the most appropriate plot, merely that a type of plot can be quickly produced.

   [1] http://had.co.nz/ggplot2/

   [2] http://www.amazon.com/gp/product/0387981403?ie=UTF8&tag=...

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3. rosenbergdmMay 2010
   One of the best all-around plotting packages for R (in my opinion) is Hadley Wickham's ggplot2 .

   Take a look at the following pages: http://had.co.nz/ggplot2/scale_datetime.html http://had.co.nz/ggplot2/geom_line.html

   While not specifically inentended as a 'time-series' package, ggplot2's facilities handle time-series data well. Ggplot2 is available on CRAN (i.e. install.packages('ggplot2'); ).

   In truth, you don't even have to use a special package if the 'prettiness isn't important.'

   df <- data.frame( day7 = start + round(runif(100, max = 7 * 86400)), hour10 = start + round(runif(100, max = 10 * 3600)), y = runif(100) ); plot(df$day7, df$y); plot(df$hour10, df$y);

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4. Anon84Apr 2010
   Leland Wilkinson's "The Grammar of Graphics" http://www.amazon.com/Grammar-Graphics-Leland-Wilkinson/dp/0... is also excellent and fully implemented in the R programming language/statistics package ( http://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis... )
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5. gtaniSep 2009
   GGplot2, by H Wickham

   http://had.co.nz/ggplot2/

   and the bay Area user's group

   http://www.meetup.com/R-Users/calendar/10446894/

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6. 6502nerdfaceOct 2015
   > > And it's really hard to beat ggplot.

   > To be honest, matplotlib seems a good contender to me (http://matplotlib.org/).

   They're quite different, though, and I can see why many prefer ggplot. It's a declarative, domain-specific language that implements a Tufte-inspired "grammar of graphics" (hence the gg- in the name; see section 1.3 of [1], and [2,3]) for very fast and convenient interactive plotting, whereas matplotlib is just a clone of MATLIB's procedural plotting API.

   [1] http://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis...

   [2] http://www.amazon.com/The-Grammar-Graphics-Statistics-Comput...

   [3] http://vita.had.co.nz/papers/layered-grammar.html

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