The first argument of the "label" command is a list of artist to be labeled. And it does not matter whether they are associated with axes or not. What you can do, therefore, is
1) draw something as you want them in the legend 2) remove them from the axes 3) make a legend from these artists. l1, = plt.plot([1,2,3]) l1.remove() plt.legend([l1], ["test"]) If you know how to create artists w/o using axes method (or. pyplot function), you may do so of course. Regards, -JJ On Thu, Jun 2, 2011 at 3:41 AM, htaunay <htau...@gmail.com> wrote: > > Is there anyway to set/create legends independent of what I am plotting? > Simply manually create, position and show legends, that not necessarily are > directly linked to the graph. > > To be specific, I am plotting several points, in a scatter form, > individually, and depending on the given attributes, I manually set what > colour and marker each point will present. My intention is to create legends > that specify the categories of my data, in a way that I can manually define > what colour/marker they are linked to. > > Thanks in advance for any help! > -- > View this message in context: > http://old.nabble.com/Independent-Legends-tp31752112p31752112.html > Sent from the matplotlib - users mailing list archive at Nabble.com. > > > ------------------------------------------------------------------------------ > Simplify data backup and recovery for your virtual environment with vRanger. > Installation's a snap, and flexible recovery options mean your data is safe, > secure and there when you need it. Data protection magic? > Nope - It's vRanger. Get your free trial download today. > http://p.sf.net/sfu/quest-sfdev2dev > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > ------------------------------------------------------------------------------ Simplify data backup and recovery for your virtual environment with vRanger. Installation's a snap, and flexible recovery options mean your data is safe, secure and there when you need it. Discover what all the cheering's about. Get your free trial download today. http://p.sf.net/sfu/quest-dev2dev2 _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
