你可以:

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

draw()

你可以:

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

draw()

试试这个:

  fig,axis = plt.subplots(nrows=1,ncols=1,figsize=(13,6),sharex=True)
  axis.set_xticklabels(['0', 'testing', '10000', '20000', '30000'],fontsize=22)

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:

也可以使用pylab和xticks来实现这一点

import matplotlib
import matplotlib.pyplot as plt
x = [0,1,2]
y = [90,40,65]
labels = ['high', 'low', 37337]
plt.plot(x,y, 'r')
plt.xticks(x, labels, rotation='vertical')
plt.show()

https://matplotlib.org/stable/gallery/ticks_and_spines/ticklabels_rotation.html