Keyword args like horizontalalignment, verticalalignment andįontsize are passed from the `~matplotlib.Axes. To do so, Matplotlib provides us with the Annotation feature which allows us to plot arrows and text labels on the graphs to give them more meaning.
In an annotation, there are two points to consider: the location being annotated represented by the argument xy and the location of the text xytext. The text in this example is placed in theįractional figure coordinate system. A common use case of text is to annotate some feature of the plot, and the annotate() method provides helper functionality to make annotations easy. In the example below, the xy point is in native coordinates Move the tip and base some percent away from The width of the base of the arrow head in points The fraction of the arrow length occupied by the head Properties in the optional keyword argument arrowprops. Optionally, you can specify arrow properties which draws an arrowįrom the text to the annotated point by giving a dictionary of arrow However, the origin is from the (right, top) of the figure or axes,Īnalogous to negative indexing of sequences. annotate ( 'local max', xy = ( 3, 1 ), xycoords = 'data', xytext = ( 0.8, 0.95 ), textcoords = 'axes fraction', arrowprops = dict ( facecolor = 'black', shrink = 0.05 ), horizontalalignment = 'right', verticalalignment = 'top', )įor physical coordinate systems (points or pixels) the origin is the
Axes.annotate also provides an optional arrow from the text to the data and this arrow can be styled in various ways. You might want to add a small buffer etc, but the idea would stay the same.Ax. annotate supports a number of coordinate systems for flexibly positioning data and annotations relative to each other and a variety of options of for styling the text. Rect = patches.Rectangle((xmin,ymin),xmax-xmin,ymax-ymin, facecolor='grey', alpha=0.2, transform=fig.transFigure) T3 = axs.text(0.6,0.4, 'Hello world line 3', ha='center', color='blue', weight='bold', transform=axs.transAxes) T2 = axs.text(0.5,0.5, 'Hello world line 2', ha='center', color='green', weight='bold', transform=axs.transAxes) T1 = axs.text(0.4,0.6, 'Hello world line 1', ha='center', color='red', weight='bold', transform=axs.transAxes) Perhaps my example can be improved, transformations always confuse me a bit.
The method suggested in the accepted answer to Matplotlib overlapping annotations looks extremely promising, however is for bar graphs.
#Annotate text matplotlib how to
Among other things, it allows you to place your text at an offsent in points from a particular data position.Ī solution could be to explore the boundingbox from the text objects and generate a box yourself. How to fix overlapping annotations / text Ask Question Asked 9 years, 9 months ago Modified 8 months ago Viewed 96k times 90 I'm trying to stop annotation text overlapping in my graphs. (Which is rather annoying for simple things like padding, though it makes the implementation simpler behind-the-scenes.)Īlso, if you're labeling things in your plot, you'll probably find that annotate is a better choice. The last two are "Fancy" bbox patches, so the padding, etc is set in a different manner. I assume you're confused on how to set the color, etc, of the box? As a quick example: import matplotlib.pyplot as pltībox=dict(facecolor='none', edgecolor='red'))ībox=dict(facecolor='none', edgecolor='blue', pad=10.0))ībox=dict(facecolor='none', edgecolor='green', boxstyle='round'))ībox=dict(facecolor='none', edgecolor='black', boxstyle='round,pad=1')) As the example you linked to mentions, you can use the bbox kwarg to add a box.
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