你可以:

for k in ax.get_xmajorticklabels():
    if some-condition:
        k.set_color(any_colour_you_like)

draw()

在matplotlib的新版本中，如果您没有使用一堆str值来设置tick标签，那么默认情况下它们是“(并且当绘制绘图时，标签只是tick值)。要得到你想要的输出，需要这样做:

>>> from pylab import *
>>> axes = figure().add_subplot(111)
>>> a=axes.get_xticks().tolist()
>>> a[1]='change'
>>> axes.set_xticklabels(a)
[<matplotlib.text.Text object at 0x539aa50>, <matplotlib.text.Text object at 0x53a0c90>, 
<matplotlib.text.Text object at 0x53a73d0>, <matplotlib.text.Text object at 0x53a7a50>, 
<matplotlib.text.Text object at 0x53aa110>, <matplotlib.text.Text object at 0x53aa790>]
>>> plt.show()

结果是:

现在如果检查_xticklabels，它们不再是一堆“。

>>> [item.get_text() for item in axes.get_xticklabels()]
['0.0', 'change', '1.0', '1.5', '2.0']

它适用于从1.1.1rc1到当前版本2.0的版本。

matplotlib.axes.Axes.set_xticks, or matplotlib.axes.Axes.set_yticks for the y-axis, can be used to change the ticks and labels beginning with matplotlib 3.5.0. These are for the object oriented interface. If using the pyplot state-based interface, use plt.xticks or plt.yticks, as shown in other answers. In general terms, pass a list / array of numbers to the ticks parameter, and a list / array strings to the labels parameter. In this case, the x-axis is comprised of continuous numeric values, so there are no set Text labels, as thoroughly explained in this answer. This is not the case when plots have discrete ticks (e.g. boxplot, barplot). [Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, '')] is returned by ax.get_xticklabels() [-0.25 0. 0.25 0.5 0.75 1. 1.25 1.5 1.75 2. 2.25] is returned by ax.get_xticks() type(ax.get_xticks()) is <class 'numpy.ndarray'> type(ax.get_xticks()[0]) is <class 'numpy.float64'> Since the OP is trying to replace a numeric label with a str, all of the values in the ndarray must be converted to str type, and the value to be changed can be updated. Tested in python 3.10 and matplotlib 3.5.2

import numpy as np
import matplotlib.pyplot as plt

# create figure and axes
fig, ax = plt.subplots(figsize=(8, 6))

# plot data
t = np.arange(0.0, 2.0, 0.01)
s = np.sin(2*np.pi*t)

# plot
ax.plot(t, s)

# get the xticks, which are the numeric location of the ticks
xticks = ax.get_xticks()

# get the xticks and convert the values in the array to str type
xticklabels = list(map(str, ax.get_xticks()))

# update the string to be changed
xticklabels[1] = 'Test'

# set the xticks and the labels
_ = ax.set_xticks(xticks, xticklabels)

注意，更改xticklabels时，x轴偏移量不会保留。但是，正确的值没有偏移量。

# create figure and axes
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 6), sharex=False)

# plot data
t = np.linspace(0, 1500000, 100)
s = t**2

# plot
ax1.plot(t, s)
ax2.plot(t, s)

# get the xticks, which are the numeric location of the ticks
xticks = ax2.get_xticks()

# get the xticks and convert the values in the array to str type
xticklabels = list(map(str, ax2.get_xticks()))

# update the string to be changed
xticklabels[1] = 'Test'

# set the xticks and the labels
_ = ax2.set_xticks(xticks, xticklabels, rotation=90)

在这里，我们打算修改Matplotlib中的一些tick标签，但没有副作用，这可以干净地工作，并保留偏移的科学符号。本解决方案中没有遇到其他一些答案中讨论的问题。

import matplotlib
import matplotlib.pyplot as plt
import numpy as np

from matplotlib import rcParams
rcParams['axes.formatter.use_mathtext'] = True

class CustomScalarFormatter(matplotlib.ticker.ScalarFormatter):
    def __init__(self, useOffset=None, useMathText=None, useLocale=None, replace_values=([],[])):
        super().__init__(useOffset=None, useMathText=None, useLocale=None)
        self.replace_values = replace_values

    def __call__(self, x, pos=None):
        """
        Return the format for tick value *x* at position *pos*.
        """
        if len(self.locs) == 0:
            return ''
        elif x in self.replace_values[0]:
            idx = self.replace_values[0].index(x)
            return str(self.replace_values[1][idx])
        else:
            xp = (x - self.offset) / (10. ** self.orderOfMagnitude)
            if abs(xp) < 1e-8:
                xp = 0
            return self._format_maybe_minus_and_locale(self.format, xp)


z = np.linspace(0, 5000, 100)
fig, ax = plt.subplots()

xmajorformatter = CustomScalarFormatter(replace_values=([2000,0],['$x_0$','']))
ymajorformatter = CustomScalarFormatter(replace_values=([1E7,0],['$y_0$','']))
ax.xaxis.set_major_formatter(xmajorformatter)
ax.yaxis.set_major_formatter(ymajorformatter)

ax.plot(z,z**2)
plt.show()

我们在这里所做的是创建matplotlib.ticker. scalarformatter类的派生类，matplotlib默认使用它来格式化标签。代码从matplotlib源复制，但只有__call__函数被复制和修改。后

        elif x in self.replace_values[0]:
            idx = self.replace_values[0].index(x)
            return str(self.replace_values[1][idx])

是添加到__call__函数中执行替换工作的新行。派生类的优点是它继承了基类的所有特性，比如偏移量标记法、科学标记法，如果值很大的话就标记。结果是:

这也适用于matplotlib 3:

x1 = [0,1,2,3]
squad = ['Fultz','Embiid','Dario','Simmons']

plt.xticks(x1, squad, rotation=45)

注意:除非ticklabels已经设置为字符串(通常在箱线图中是这样)，否则这将不适用于任何更新于1.1.0的matplotlib版本。如果你正在从当前的github master工作，这将不起作用。我还不确定是什么问题……这可能是一个无意的变化，也可能不是……

通常情况下，你会这样做:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()

# We need to draw the canvas, otherwise the labels won't be positioned and 
# won't have values yet.
fig.canvas.draw()

labels = [item.get_text() for item in ax.get_xticklabels()]
labels[1] = 'Testing'

ax.set_xticklabels(labels)

plt.show()

要理解为什么需要跳过这么多步骤，您需要更多地了解matplotlib的结构。

Matplotlib故意避免对刻度等进行“静态”定位，除非明确地告诉它这样做。假设您希望与图形交互，因此图形的边界、刻度、刻度标签等将动态变化。

因此，不能只设置给定标记标签的文本。默认情况下，每次绘制图形时，它都会被轴的Locator和Formatter重新设置。

但是，如果Locators和Formatters被设置为静态(分别为FixedLocator和FixedFormatter)，则标记标签保持不变。

这就是set_*ticklabels或ax.*axis。set_ticklabels。

希望这能让您更清楚地了解为什么更改单个标记有点复杂。

通常，你真正想做的只是注释一个特定的位置。在这种情况下，请查看注释。