Set pad between arrow and text in annotate function

Question

How do I set the distance (padding) between the arrow and the text in matplotlib's annotate function? Sometimes the text ends up being too close to the arrow and I would like to move them a little further apart.

Basic example:

import matplotlib.pyplot as plt

plt.annotate('Here it is!',xy=(-1,-1),xytext=(0,0),
             arrowprops=dict(arrowstyle='->',lw=1.5))

plt.xlim(-10,10)
plt.ylim(-10,10)

plt.show()

Answer 1

For fancy arrows you can play with the bbox properties:

fig, ax = plt.subplots(1, 3, figsize=(7, 3))
pad_val = [-5, 0, 5]
for a,p in zip(ax, pad_val):
    a.annotate('Here it is!\npad={}'.format(p),xy=(-1,-1),xytext=(1,1),
                arrowprops=dict(arrowstyle='-|>', fc="k", ec="k", lw=1.5),
                bbox=dict(pad=p, facecolor="none", edgecolor="none"))
    a.set_xlim(-10,10)
    a.set_ylim(-10,10)

Here the drawback is that you can't add a color behind the annotation (facecolor="none" is mandatory), or the arrow will always stick to the border of the frame and it might be ugly.

HTH

Answer 2

You can use the shrink keyword argument in your arrowprops dictionary, but unfortunately the FancyArrowPatch object doesn't support it, so you'd have to remove the arrowstyle='->'.

The value given with shrink is a percentage that the tip/base will move away from the xy and xytext coordinates.

import matplotlib.pyplot as plt

plt.annotate('Here it is!',xy=(-1,-1),xytext=(0,0),
             arrowprops=dict(lw=1.5, shrink=0.15))

plt.xlim(-10,10)
plt.ylim(-10,10)

plt.show()

Answer 3

To have full control of the distance, you must combine jrjc and Ffisegydd answers.

The pad property of the Bbox defines the distance between the text and its containing box. The shrink property of the arrow is the distance between the arrow extremity and the box, not the text itself.

Also, to use shrink with FancyArrowPatch you must defined it separately: shrinkA for the origin (extremity of the arrow close to the text) and shrinkB for the destination. From a demo in Matplotlib's website:

 ax.annotate("",
             xy=(x1, y1), xycoords='data',
             xytext=(x2, y2), textcoords='data',
             arrowprops=dict(arrowstyle="->", color="0.5",
                             shrinkA=5, shrinkB=5,
                             patchA=None, patchB=None,
                             connectionstyle=connectionstyle,
                             ),
             )

So the full answer is both:

plt.annotate('Example text',
             xy=(-1,-1), xytext=(0,0),
             arrowprops=dict(arrowstyle='->', shrinkA=0.15),
             bbox=dict(pad=0),
    )

Examples: