A gallery of charts, diagrams, and plot types What would you recommend as a comprehensive gallery of data presentation techniques? A source that could be used to refer to while you're thinking about better ways of presenting your data?
I've identified the following ones, but will be glad if you could add yours:
Online galleries:


*

*http://www.mathworks.com/discovery/gallery.html

*http://www.idlcoyote.com/gallery/

*https://developers.google.com/chart/interactive/docs/gallery?csw=1

*http://www.walkingrandomly.com/?p=4788

*http://en.wikipedia.org/wiki/Category:Statistical_charts_and_diagrams
(does not provide one-page graphic gallery)

*http://docs.ggplot2.org/current/

*http://www.itl.nist.gov/div898/handbook/graphgal.htm

*http://scikit-learn.org/stable/auto_examples/index.html

*http://www.stata.com/support/faqs/graphics/gph/stata-graphs/

*http://shiny.rstudio.com/gallery/

*https://bl.ocks.org/ (interactive and vector graphics)

*http://www.texample.net/tikz/examples/ (TikZ and PGP visualization with code)


Books (plots scattered across pages):


*

*Edward R. Tufte, The Visual Display of Quantitative Information

*Nathan Yau, Data Points
 A: I personally prefer the D3 gallery because many of the plots there are dynamic and interactive (not to mention incredibly appealing and professional-looking from a graphic design perspective).  There's also a tremendous range of variability in the style of plots and the type of information being displayed, so it makes a good place to peruse just for general inspiration to "up your game" with regard to data visualization. 
A: There is the R Graphical Manual.  Although it is presumably somewhat less useful for people who use other software, you can still look up topics and see some examples of possibilities that you could then try to reproduce by other means.  
A: Ralph Lengler and Martin J. Eppler's Periodic Table of Visualization Methods   is an ingenious and far-ranging single-page display of about a hundred types of charts and diagrams for visualizing data as well as concepts, strategies, processes, and so on.  A nice reference when looking for a catchy or creative way to display something.
A: For a good overview of different types of plots (and examples good and bad), including a timeline of graphical development, there is plenty to explore here:
http://www.datavis.ca/gallery/
A: I would like to propose the R graph gallery. It displays more than hundred graphics, all made with the R software, and always giving the associated code to make it reproducible !
A: There's an excellent gallery from UBC Statistics dept made by an undergraduate research student.
You can preview with Shiny here, or get full code and fork on GitHub.
It's currently my go-to resource for ease of use, like picking a graph off a shelf, selection on the basis of whether it's "recommended", pointing out what styles ought be avoided etc.
A: Nathan Yau's books might be useful for people starting off, but are pitched lower than most visitors here should want to reach. I gave a very qualified 4 stars to "Data points" on amazon.com as can be seen at http://www.amazon.com/Data-Points-Visualization-Means-Something/dp/111846219X/ 
I can be very much more positive about William Cleveland's outstanding books (see http://www.hobart.com/). One of many compliments about Cleveland's books is that although now 19 or 20 years old, they don't really date at all. Indeed, it is now much easier to do what Cleveland did across a wide range of software. 
I am a fan of Tufte's work (indeed should disclose an interest as a very marginal contributor to the enterprise). Of his four books on graphics that cited remains the place to start. See http://www.edwardtufte.com/tufte/ (Visual display is often misrepresented as Tufte's first book; not so). 
But probably the widest collection of statistical graphics is to be found in Leland Wilkinson's magnum opus The Grammar of Graphics
R users should know about that as the main inspiration for ggplot2. 
A: Highcharts and highstocks, something like d3, might also give you lots of inspiration. Consider for example http://www.highcharts.com/demo/polar-wind-rose. On the left of that page, you can click around in their library of graphs.
A: Coming from a python environment I can recommend:
http://matplotlib.org/gallery.html
http://bokeh.pydata.org/en/latest/docs/gallery.html
