Possible to make labels appear when hovering over a point in matplotlib?

Posted on

Solving problem is about exposing yourself to as many situations as possible like Possible to make labels appear when hovering over a point in matplotlib? and practice these strategies over and over. With time, it becomes second nature and a natural way you approach any problems in general. Big or small, always start with a plan, use other strategies mentioned here till you are confident and ready to code the solution.
In this post, my aim is to share an overview the topic about Possible to make labels appear when hovering over a point in matplotlib?, which can be followed any time. Take easy to follow this discuss.

Possible to make labels appear when hovering over a point in matplotlib?

I am using matplotlib to make scatter plots. Each point on the scatter plot is associated with a named object. I would like to be able to see the name of an object when I hover my cursor over the point on the scatter plot associated with that object. In particular, it would be nice to be able to quickly see the names of the points that are outliers. The closest thing I have been able to find while searching here is the annotate command, but that appears to create a fixed label on the plot. Unfortunately, with the number of points that I have, the scatter plot would be unreadable if I labeled each point. Does anyone know of a way to create labels that only appear when the cursor hovers in the vicinity of that point?

Asked By: jdmcbr

||

Answer #1:

It seems none of the other answers here actually answer the question. So here is a code that uses a scatter and shows an annotation upon hovering over the scatter points.

import matplotlib.pyplot as plt
import numpy as np; np.random.seed(1)
x = np.random.rand(15)
y = np.random.rand(15)
names = np.array(list("ABCDEFGHIJKLMNO"))
c = np.random.randint(1,5,size=15)
norm = plt.Normalize(1,4)
cmap = plt.cm.RdYlGn
fig,ax = plt.subplots()
sc = plt.scatter(x,y,c=c, s=100, cmap=cmap, norm=norm)
annot = ax.annotate("", xy=(0,0), xytext=(20,20),textcoords="offset points",
                    bbox=dict(boxstyle="round", fc="w"),
                    arrowprops=dict(arrowstyle="->"))
annot.set_visible(False)
def update_annot(ind):
    pos = sc.get_offsets()[ind["ind"][0]]
    annot.xy = pos
    text = "{}, {}".format(" ".join(list(map(str,ind["ind"]))),
                           " ".join([names[n] for n in ind["ind"]]))
    annot.set_text(text)
    annot.get_bbox_patch().set_facecolor(cmap(norm(c[ind["ind"][0]])))
    annot.get_bbox_patch().set_alpha(0.4)
def hover(event):
    vis = annot.get_visible()
    if event.inaxes == ax:
        cont, ind = sc.contains(event)
        if cont:
            update_annot(ind)
            annot.set_visible(True)
            fig.canvas.draw_idle()
        else:
            if vis:
                annot.set_visible(False)
                fig.canvas.draw_idle()
fig.canvas.mpl_connect("motion_notify_event", hover)
plt.show()

enter image description here

Because people also want to use this solution for a line plot instead of a scatter, the following would be the same solution for plot (which works slightly differently).

In case someone is looking for a solution for lines in twin axes, refer to How to make labels appear when hovering over a point in multiple axis?

In case someone is looking for a solution for bar plots, please refer to e.g. this answer.

Answer #2:

This solution works when hovering a line without the need to click it:

import matplotlib.pyplot as plt
# Need to create as global variable so our callback(on_plot_hover) can access
fig = plt.figure()
plot = fig.add_subplot(111)
# create some curves
for i in range(4):
    # Giving unique ids to each data member
    plot.plot(
        [i*1,i*2,i*3,i*4],
        gid=i)
def on_plot_hover(event):
    # Iterating over each data member plotted
    for curve in plot.get_lines():
        # Searching which data member corresponds to current mouse position
        if curve.contains(event)[0]:
            print "over %s" % curve.get_gid()
fig.canvas.mpl_connect('motion_notify_event', on_plot_hover)
plt.show()
Answered By: mbernasocchi

Answer #3:

From http://matplotlib.sourceforge.net/examples/event_handling/pick_event_demo.html :

from matplotlib.pyplot import figure, show
import numpy as npy
from numpy.random import rand
if 1: # picking on a scatter plot (matplotlib.collections.RegularPolyCollection)
    x, y, c, s = rand(4, 100)
    def onpick3(event):
        ind = event.ind
        print('onpick3 scatter:', ind, npy.take(x, ind), npy.take(y, ind))
    fig = figure()
    ax1 = fig.add_subplot(111)
    col = ax1.scatter(x, y, 100*s, c, picker=True)
    #fig.savefig('pscoll.eps')
    fig.canvas.mpl_connect('pick_event', onpick3)
show()
Answered By: cyborg

Answer #4:

A slight edit on an example provided in http://matplotlib.org/users/shell.html:

import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_title('click on points')
line, = ax.plot(np.random.rand(100), '-', picker=5)  # 5 points tolerance
def onpick(event):
    thisline = event.artist
    xdata = thisline.get_xdata()
    ydata = thisline.get_ydata()
    ind = event.ind
    print('onpick points:', *zip(xdata[ind], ydata[ind]))
fig.canvas.mpl_connect('pick_event', onpick)
plt.show()

This plots a straight line plot, as Sohaib was asking

Answered By: texasflood

Answer #5:

The other answers did not address my need for properly showing tooltips in a recent version of Jupyter inline matplotlib figure. This one works though:

import matplotlib.pyplot as plt
import numpy as np
import mplcursors
np.random.seed(42)
fig, ax = plt.subplots()
ax.scatter(*np.random.random((2, 26)))
ax.set_title("Mouse over a point")
crs = mplcursors.cursor(ax,hover=True)
crs.connect("add", lambda sel: sel.annotation.set_text(
    'Point {},{}'.format(sel.target[0], sel.target[1])))
plt.show()

Leading to something like the following picture when going over a point with mouse:
enter image description here

Answered By: Farzad Vertigo

Answer #6:

If you use jupyter notebook, my solution is as simple as:

%pylab
import matplotlib.pyplot as plt
import mplcursors
plt.plot(...)
mplcursors.cursor(hover=True)
plt.show()

YOu can get something like
enter image description here

Answered By: Yuchao Jiang

Answer #7:

mpld3 solve it for me.
EDIT (CODE ADDED):

import matplotlib.pyplot as plt
import numpy as np
import mpld3
fig, ax = plt.subplots(subplot_kw=dict(axisbg='#EEEEEE'))
N = 100
scatter = ax.scatter(np.random.normal(size=N),
                 np.random.normal(size=N),
                 c=np.random.random(size=N),
                 s=1000 * np.random.random(size=N),
                 alpha=0.3,
                 cmap=plt.cm.jet)
ax.grid(color='white', linestyle='solid')
ax.set_title("Scatter Plot (with tooltips!)", size=20)
labels = ['point {0}'.format(i + 1) for i in range(N)]
tooltip = mpld3.plugins.PointLabelTooltip(scatter, labels=labels)
mpld3.plugins.connect(fig, tooltip)
mpld3.show()

You can check this example

Answered By: Julian

Answer #8:

mplcursors worked for me. mplcursors provides clickable annotation for matplotlib. It is heavily inspired from mpldatacursor (https://github.com/joferkington/mpldatacursor), with a much simplified API

import matplotlib.pyplot as plt
import numpy as np
import mplcursors
data = np.outer(range(10), range(1, 5))
fig, ax = plt.subplots()
lines = ax.plot(data)
ax.set_title("Click somewhere on a line.nRight-click to deselect.n"
             "Annotations can be dragged.")
mplcursors.cursor(lines) # or just mplcursors.cursor()
plt.show()
Answered By: Enayat

Leave a Reply

Your email address will not be published.