来自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()

这个食谱绘制了一个关于选择数据点的注释:http://scipy-cookbook.readthedocs.io/items/Matplotlib_Interactive_Plotting.html。 这个配方绘制了一个工具提示，但它需要wxPython: matplotlib中的点和线工具提示?

Mplcursors对我很有用。Mplcursors为matplotlib提供了可单击的注释。它很大程度上受到mpldatacursor (https://github.com/joferkington/mpldatacursor)的启发，具有非常简化的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()

似乎这里的其他答案都不能回答这个问题。这是一个代码，它使用散点并在悬停在散点上时显示注释。

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()

因为人们还想将这个解决方案用于线状图而不是散点图，所以下面的解决方案将用于图形(其工作方式略有不同)。

import matplotlib.pyplot as plt import numpy as np; np.random.seed(1) x = np.sort(np.random.rand(15)) y = np.sort(np.random.rand(15)) names = np.array(list("ABCDEFGHIJKLMNO")) norm = plt.Normalize(1,4) cmap = plt.cm.RdYlGn fig,ax = plt.subplots() line, = plt.plot(x,y, marker="o") 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): x,y = line.get_data() annot.xy = (x[ind["ind"][0]], y[ind["ind"][0]]) 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_alpha(0.4) def hover(event): vis = annot.get_visible() if event.inaxes == ax: cont, ind = line.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()

如果有人正在寻找双轴线的解决方案，请参阅如何使标签出现时悬停在多个轴上的点?

如果有人正在寻找条形图的解决方案，请参考例如这个答案。

在matplotlib状态栏中显示对象信息

特性

不需要额外的库 干净的情节 没有厂牌和艺人的重叠 支持多艺术家标签 可以处理来自不同绘图调用的艺术家(如scatter, plot, add_patch) 库风格的代码

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()

其他答案没有解决我在最新版本的Jupyter内联matplotlib图中正确显示工具提示的需求。这条是可行的:

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()

当用鼠标浏览一个点时，会导致如下图所示:

基于Markus Dutschke”和“ImportanceOfBeingErnest”，我简化了代码，使其更加模块化。

此外，这也不需要安装额外的包。

import matplotlib.pylab as plt
import numpy as np

plt.close('all')
fh, ax = plt.subplots()

#Generate some data
y,x = np.histogram(np.random.randn(10000), bins=500)
x = x[:-1]
colors = ['#0000ff', '#00ff00','#ff0000']
x2, y2 = x,y/10
x3, y3 = x, np.random.randn(500)*10+40

#Plot
h1 = ax.plot(x, y, color=colors[0])
h2 = ax.plot(x2, y2, color=colors[1])
h3 = ax.scatter(x3, y3, color=colors[2], s=1)

artists = h1 + h2 + [h3] #concatenating lists
labels = [list('ABCDE'*100),list('FGHIJ'*100),list('klmno'*100)] #define labels shown

#___ Initialize annotation arrow
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 on_plot_hover(event):
    if event.inaxes != ax: #exit if mouse is not on figure
        return
    is_vis = annot.get_visible() #check if an annotation is visible
    # x,y = event.xdata,event.ydata #coordinates of mouse in graph
    for ii, artist in enumerate(artists):
        is_contained, dct = artist.contains(event)

        if(is_contained):
            if('get_data' in dir(artist)): #for plot
                data = list(zip(*artist.get_data()))
            elif('get_offsets' in dir(artist)): #for scatter
                data = artist.get_offsets().data

            inds = dct['ind'] #get which data-index is under the mouse
            #___ Set Annotation settings
            xy = data[inds[0]] #get 1st position only
            annot.xy = xy
            annot.set_text(f'pos={xy},text={labels[ii][inds[0]]}')
            annot.get_bbox_patch().set_edgecolor(colors[ii])
            annot.get_bbox_patch().set_alpha(0.7)
            annot.set_visible(True)
            fh.canvas.draw_idle()
        else:
             if is_vis:
                 annot.set_visible(False) #disable when not hovering
                 fh.canvas.draw_idle()

fh.canvas.mpl_connect('motion_notify_event', on_plot_hover)

给出以下结果: