matplotlib.pyplot.annotate | Annotate the point xy with text

The matplotlib.pyplot.annotate function in the matplotlib.pyplot module is used to Annotate the point xy with text text.

In the simplest form, the text is placed at xy.

Optionally, the text can be displayed in another position xytext. An arrow pointing from the text to the annotated point xy can then be added by defining arrowprops.

matplotlib.pyplot.annotate Syntax

The syntax of the matplotlib.pyplot.annotate method is as follows:

matplotlib.pyplot.annotate(text, xy, *args, **kwargs)

matplotlib.pyplot.annotate Parameters

The matplotlib.pyplot.annotate accepts the following parameters:

Parameter	Description
text	string. The text of the annotation.
xy	(float, float) The point (x, y) to annotate. The coordinate system is determined by xycoords.
xytext	(float, float), default: xy The position (x, y) to place the text at. The coordinate system is determined by textcoords.
xycoords	string or Artist or Transform or callable or (float, float), default: ‘data’ The coordinate system that xy is given in. An Artist: xy is interpreted as a fraction of the artist’s Bbox. E.g. (0, 0) would be the lower left corner of the bounding box and (0.5, 1) would be the center top of the bounding box. A Transform to transform xy to screen coordinates. A function with one of the following signatures: def transform(renderer) -> Bbox def transform(renderer) -> Transform A tuple (xcoords, ycoords) specifying separate coordinate systems for x and y. xcoords and ycoords must each be of one of the above described types.
textcoords	string or Artist or Transform or callable or (float, float), default: value of xycoords The coordinate system that xytext is given in.
arrowprops	dict The properties used to draw a FancyArrowPatch arrow between the positions xy and xytext. Defaults to None, i.e. no arrow is drawn. For historical reasons there are two different ways to specify arrows, "simple" and "fancy".
annotation_clip	bool or None, default: None Whether to draw the annotation when the annotation point xy is outside the axes area. If True, the annotation will only be drawn when xy is within the axes. If False, the annotation will always be drawn. If None, the annotation will only be drawn when xy is within the axes and xycoords is ‘data’.
**kwargs	Additional kwargs are passed to Text.

For xycoords, The following types of values are supported:

Value	Description
‘figure points’	Points from the lower left of the figure
‘figure pixels’	Pixels from the lower left of the figure
‘figure fraction’	Fraction of figure from lower left
‘subfigure points’	Points from the lower left of the subfigure
‘subfigure pixels’	Pixels from the lower left of the subfigure
‘subfigure fraction’	Fraction of subfigure from lower left
‘axes points’	Points from lower left corner of axes
‘axes pixels’	Pixels from lower left corner of axes
‘axes fraction’	Fraction of axes from lower left
‘data’	Use the coordinate system of the object being annotated (default)
‘polar’	(theta, r) if not native ‘data’ coordinates

Note that ‘subfigure pixels’ and ‘figure pixels’ are the same for the parent figure, so users who want code that is usable in a subfigure can use ‘subfigure pixels’.

Simple arrow:

If arrowprops does not contain the key ‘arrowstyle’ the allowed keys are:

Key	Description
width	The width of the arrow in points
headwidth	The width of the base of the arrow head in points
headlength	The length of the arrow head in points
shrink	Fraction of total length to shrink from both ends
?	Any key to matplotlib.patches.FancyArrowPatch

The arrow is attached to the edge of the text box, the exact position (corners or centers) depending on where it’s pointing to.

Fancy arrow:

This is used if ‘arrowstyle’ is provided in the arrowprops.

Valid keys are the following FancyArrowPatch parameters:

Key	Description
arrowstyle	the arrow style
connectionstyle	the connection style
relpos	see below; default is (0.5, 0.5)
patchA	default is bounding box of the text
patchB	default is None
shrinkA	default is 2 points
shrinkB	default is 2 points
mutation_scale	default is text size (in points)
mutation_aspect	default is 1.
?	any key for matplotlib.patches.PathPatch

The exact starting point position of the arrow is defined by relpos. It’s a tuple of relative coordinates of the text box, where (0, 0) is the lower left corner and (1, 1) is the upper right corner. Values <0 and >1 are supported and specify points outside the text box. By default (0.5, 0.5) the starting point is centered in the text box.

matplotlib.pyplot.annotate Returns

The return value of the matplotlib.pyplot.annotate function is annotation.

Demo #1: Basic usage of matplotlib.pyplot.annotate

The following example demonstrates the use of the matplotlib.pyplot.annotate method −

# Demo of matplotlib.pyplot.annotate function

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2*np.pi*t)
line, = ax.plot(t, s, lw=2)

ax.annotate('local max', xy=(4, 1), xytext=(3, 1.5),
            arrowprops=dict(facecolor='black', shrink=0.05),
            )
ax.annotate('local min', xy=(3.5, -1), xytext=(3, -1.5),
            arrowprops=dict(facecolor='red', shrink=0.1),
            )
ax.set_ylim(-2, 2)
plt.title('matplotlib.pyplot.annotate ApiDemos.com')
plt.show()

When we run above program, it produces following result −

Demo#2：

# Demo of matplotlib.pyplot.annotate function

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0, 10, 0.005)
y = np.exp(-x / 3.) * np.sin(3 * np.pi * x)

fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(0, 10)
ax.set_ylim(-1, 1)

# Setting up the parameters
xdata, ydata = 2, 0
xdisplay, ydisplay = ax.transData.transform((xdata, ydata))

bbox = dict(boxstyle="round", fc="0.8")
arrowprops = dict(
    arrowstyle="->",
    connectionstyle="angle, angleA = 0, angleB = 90,\
    rad = 10")

offset = 72

# Annotation
ax.annotate('data = (%.1f, %.1f)' % (xdata, ydata),
            (xdata, ydata), xytext=(-2 * offset, offset),
            textcoords='offset points',
            bbox=bbox, arrowprops=arrowprops)

disp = ax.annotate('display = (%.1f, %.1f)' % (xdisplay, ydisplay),
                   (xdisplay, ydisplay), xytext=(0.5 * offset, -offset),
                   xycoords='figure pixels',
                   textcoords='offset points',
                   bbox=bbox, arrowprops=arrowprops)

plt.title('matplotlib.pyplot.annotate ApiDemos.com')
plt.show()

When we run above program, it produces following result −