On Fri, Jun 20, 2014 at 4:10 AM, Jamie Mitchell <jamiemitchell1...@gmail.com > wrote:
> Hi folks, > > Instead of colouring the entire bar of a histogram i.e. filling it, I > would like to colour just the outline of the histogram. Does anyone know > how to do this? > Version - Python2.7 > Look at the matplotlib.pyplot.hist function documentation: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hist In addition to the listed parameters, you'll see the "Other Parameters" taken are those that can be applied to the created Patch objects (which are the actual rectangles). For the Patch keywords, see the API documentation on the Patch object ( http://matplotlib.org/api/artist_api.html#matplotlib.patches.Patch). So you can do one of two things: 1) Pass the necessary Patch keywords to effect what you want e.g. (untested): import matplotlib.pyplot as plt plt.hist(dataset, bins=10, range=(-5, 5), normed=True, edgecolor='b', linewidth=2, facecolor='none', # Patch options ) plt.show() 2) Iterate over the Patch instances returned by plt.hist() and set the properties you want. e.g. (untested): import matplotlib.pyplot as plt n, bins, patches = plt.hist(dataset, bins=10, range=(-5, 5), normed=True) for patch in patches: patch.set_edgecolor('b') # color of the lines around each bin patch.set_linewidth(2) # Set width of bin edge patch.set_facecolor('none') # set no fill # Anything else you want to do plt.show() Approach (1) is the "easy" way, and is there to satisfy the majority of use cases. However, approach (2) is _much_ more flexible. Suppose you wanted to highlight a particular region of your data with a specific facecolor or edgecolor -- you can apply the features you want to individual patches using approach (2). Or if you wanted to highlight a specific bin with thicker lines. This is a common theme in matplotlib -- you can use keywords to apply the same features to every part of a plot or you can iterate over the drawn objects and customize them individually. This is a large part of what makes matplotlib nice to me -- it has a "simple" mode as well as a predictable API for customizing a plot in almost any way you could possibly want. HTH, Jason -- Jason M. Swails BioMaPS, Rutgers University Postdoctoral Researcher
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