[python] 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?

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()

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

I have made a multi-line annotation system to add to: https://stackoverflow.com/a/47166787/10302020. for the most up to date version: https://github.com/AidenBurgess/MultiAnnotationLineGraph

Simply change the data in the bottom section.

import matplotlib.pyplot as plt


def update_annot(ind, line, annot, ydata):
    x, y = line.get_data()
    annot.xy = (x[ind["ind"][0]], y[ind["ind"][0]])
    # Get x and y values, then format them to be displayed
    x_values = " ".join(list(map(str, ind["ind"])))
    y_values = " ".join(str(ydata[n]) for n in ind["ind"])
    text = "{}, {}".format(x_values, y_values)
    annot.set_text(text)
    annot.get_bbox_patch().set_alpha(0.4)


def hover(event, line_info):
    line, annot, ydata = line_info
    vis = annot.get_visible()
    if event.inaxes == ax:
        # Draw annotations if cursor in right position
        cont, ind = line.contains(event)
        if cont:
            update_annot(ind, line, annot, ydata)
            annot.set_visible(True)
            fig.canvas.draw_idle()
        else:
            # Don't draw annotations
            if vis:
                annot.set_visible(False)
                fig.canvas.draw_idle()


def plot_line(x, y):
    line, = plt.plot(x, y, marker="o")
    # Annotation style may be changed here
    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)
    line_info = [line, annot, y]
    fig.canvas.mpl_connect("motion_notify_event",
                           lambda event: hover(event, line_info))


# Your data values to plot
x1 = range(21)
y1 = range(0, 21)
x2 = range(21)
y2 = range(0, 42, 2)
# Plot line graphs
fig, ax = plt.subplots()
plot_line(x1, y1)
plot_line(x2, y2)
plt.show()

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:

showing object information in matplotlib statusbar

Features

• no extra libraries needed
• clean plot
• no overlap of labels and artists
• supports multi artist labeling
• can handle artists from different plotting calls (like scatter, plot, add_patch)
• code in library style

Code

### imports
import matplotlib as mpl
import matplotlib.pylab as plt
import numpy as np


# https://stackoverflow.com/a/47166787/7128154
# https://matplotlib.org/3.3.3/api/collections_api.html#matplotlib.collections.PathCollection
# https://matplotlib.org/3.3.3/api/path_api.html#matplotlib.path.Path
# https://stackoverflow.com/questions/15876011/add-information-to-matplotlib-navigation-toolbar-status-bar
# https://stackoverflow.com/questions/36730261/matplotlib-path-contains-point
# https://stackoverflow.com/a/36335048/7128154
class StatusbarHoverManager:
    """
    Manage hover information for mpl.axes.Axes object based on appearing
    artists.

    Attributes
    ----------
    ax : mpl.axes.Axes
        subplot to show status information
    artists : list of mpl.artist.Artist
        elements on the subplot, which react to mouse over
    labels : list (list of strings) or strings
        each element on the top level corresponds to an artist.
        if the artist has items
        (i.e. second return value of contains() has key 'ind'),
        the element has to be of type list.
        otherwise the element if of type string
    cid : to reconnect motion_notify_event
    """
    def __init__(self, ax):
        assert isinstance(ax, mpl.axes.Axes)


        def hover(event):
            if event.inaxes != ax:
                return
            info = 'x={:.2f}, y={:.2f}'.format(event.xdata, event.ydata)
            ax.format_coord = lambda x, y: info
        cid = ax.figure.canvas.mpl_connect("motion_notify_event", hover)

        self.ax = ax
        self.cid = cid
        self.artists = []
        self.labels = []

    def add_artist_labels(self, artist, label):
        if isinstance(artist, list):
            assert len(artist) == 1
            artist = artist[0]

        self.artists += [artist]
        self.labels += [label]

        def hover(event):
            if event.inaxes != self.ax:
                return
            info = 'x={:.2f}, y={:.2f}'.format(event.xdata, event.ydata)
            for aa, artist in enumerate(self.artists):
                cont, dct = artist.contains(event)
                if not cont:
                    continue
                inds = dct.get('ind')
                if inds is not None:  # artist contains items
                    for ii in inds:
                        lbl = self.labels[aa][ii]
                        info += ';   artist [{:d}, {:d}]: {:}'.format(
                            aa, ii, lbl)
                else:
                    lbl = self.labels[aa]
                    info += ';   artist [{:d}]: {:}'.format(aa, lbl)
            self.ax.format_coord = lambda x, y: info

        self.ax.figure.canvas.mpl_disconnect(self.cid)
        self.cid = self.ax.figure.canvas.mpl_connect(
            "motion_notify_event", hover)



def demo_StatusbarHoverManager():
    fig, ax = plt.subplots()
    shm = StatusbarHoverManager(ax)

    poly = mpl.patches.Polygon(
        [[0,0], [3, 5], [5, 4], [6,1]], closed=True, color='green', zorder=0)
    artist = ax.add_patch(poly)
    shm.add_artist_labels(artist, 'polygon')

    artist = ax.scatter([2.5, 1, 2, 3], [6, 1, 1, 7], c='blue', s=10**2)
    lbls = ['point ' + str(ii) for ii in range(4)]
    shm.add_artist_labels(artist, lbls)

    artist = ax.plot(
        [0, 0, 1, 5, 3], [0, 1, 1, 0, 2], marker='o', color='red')
    lbls = ['segment ' + str(ii) for ii in range(5)]
    shm.add_artist_labels(artist, lbls)

    plt.show()


# --- main
if __name__== "__main__":
    demo_StatusbarHoverManager()

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

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()

• This recipe draws an annotation on picking a data point: http://scipy-cookbook.readthedocs.io/items/Matplotlib_Interactive_Plotting.html .
• This recipe draws a tooltip, but it requires wxPython: Point and line tooltips in matplotlib?

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

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()