Python中的 Matplotlib.pyplot.tick_params()

Matplotlib 是Python中用于数组二维图的可视化库。 Matplotlib 是一个基于 NumPy 数组构建的多平台数据可视化库，旨在与更广泛的 SciPy 堆栈配合使用。

matplotlib.pyplot.tick_params()

matplotlib.pyplot.tick_params()用于更改刻度、刻度标签和网格线的外观。

句法：

matplotlib.pyplot.tick_params(axis='both', **kwargs)

参数：

Parameter	Value	Use
axis	{‘x’, ‘y’, ‘both’}, optional	Which axis to apply the parameters to. Default is ‘both’.
reset	bool, default: False	If True, set all parameters to defaults before processing other keyword arguments..
which	{‘major’, ‘minor’, ‘both’}	Default is ‘major’; apply arguments to which ticks.
direction	{‘in’, ‘out’, ‘inout’}	Puts ticks inside the axes, outside the axes, or both.
length	float	Tick length in points.
width	float	Default is ‘major’; apply arguments to which ticks.
color	color	Tick color.
pad	float	Distance in points between tick and label.	labelsize	float or str	Tick label font size in points or as a string (e.g., ‘large’).	labelcolor	color	Tick label color.	colors	color	Tick color and label color.	zorder	float	Tick and label zorder.	bottom, top, left, right	bool	Whether to draw the respective ticks.	labelbottom, labeltop, labelleft, labelright	bool	Whether to draw the respective tick labels.	labelrotation	float	Tick label rotation	grid_color	color	Gridline color	grid_alpha	float	Transparency of gridlines: 0 (transparent) to 1 (opaque).	grid_linewidth	float	Width of gridlines in points.	grid_linestyle	str	Any valid Line2D line style spec.

示例 #1：默认绘图

# importing libraries
import matplotlib.pyplot as plt 
    
# values of x and y axes 
x = [i for i in range(5, 55, 5)]
y = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5] 
    
plt.plot(x, y) 
plt.xlabel('x') 
plt.ylabel('y') 
    
plt.show() 

输出 ：
示例 #2：

# importing libraries
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, ScalarFormatter
  
fig, ax = plt.subplots()
ax.plot([0, 10, 20, 30], [0, 2, 1, 2])
  
ax.xaxis.set_minor_locator(MultipleLocator(1))
ax.xaxis.set_minor_formatter(ScalarFormatter())
  
ax.tick_params(axis ='both', which ='major', 
               labelsize = 16, pad = 12, 
               colors ='r')
  
ax.tick_params(axis ='both', which ='minor',
               labelsize = 8, colors ='b')
  
plt.show()

输出：