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:

最简单的选择是使用mplcursors包。 Mplcursors:读取文档 mplcursors: github 如果使用Anaconda，请按照这些说明安装，否则使用这些说明安装pip。 这必须在交互式窗口中绘制，而不是内联。 对于jupyter，在单元格中执行%matplotlib qt之类的代码将启用交互式绘图。参见如何在IPython笔记本中打开交互式matplotlib窗口? 在python 3.10, pandas 1.4.2, matplotlib 3.5.1, seaborn 0.11.2中测试

import matplotlib.pyplot as plt
import pandas_datareader as web  # only for test data; must be installed with conda or pip
from mplcursors import cursor  # separate package must be installed

# reproducible sample data as a pandas dataframe
df = web.DataReader('aapl', data_source='yahoo', start='2021-03-09', end='2022-06-13')

plt.figure(figsize=(12, 7))
plt.plot(df.index, df.Close)
cursor(hover=True)
plt.show()

熊猫

ax = df.plot(y='Close', figsize=(10, 7))
cursor(hover=True)
plt.show()

Seaborn

工作与轴级别的情节，如sns。Lineplot和像sns.relplot这样的数字级plot。

import seaborn as sns

# load sample data
tips = sns.load_dataset('tips')

sns.relplot(data=tips, x="total_bill", y="tip", hue="day", col="time")
cursor(hover=True)
plt.show()

我做了一个多行注释系统，添加到:https://stackoverflow.com/a/47166787/10302020。 最新版本: https://github.com/AidenBurgess/MultiAnnotationLineGraph

只需更改底部部分中的数据。

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()

这个解决方案适用于悬停一行而不需要单击它:

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()

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:

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()