设置坐标轴

import matplotlib.pyplot as plt 
import numpy as np 
x=np.linspace(-3,3,50)
y1=2*x+1
y2=x**3

##plt.figure()
##plt.plot(x,y1)

plt.figure(num=3,figsize=(8,5))
plt.plot(x,y2)
plt.plot(x,y1,'r--')

plt.xlim((-1,2))
plt.ylim((-2,3))    #设置x,y坐标轴范围
plt.xlabel('I am x')
plt.ylabel('I am y')    #设置x,y坐标轴标签 

new_ticks=np.linspace(-1,2,5)    
plt.xticks(new_ticks)    #给横轴分段显示
plt.yticks([-2,-1.8,-1,1.22,3],
    [r'$really\ bad$',r'$bad$',r'$normal$',r'$good$',r'$good\ \alpha$']
    )        #纵轴设置文字节点

plt.show()

运行结果

移动坐标轴

import matplotlib.pyplot as plt 
import numpy as np 
x=np.linspace(-3,3,50)
y1=2*x+1
y2=x**3

##plt.figure()
##plt.plot(x,y1)

plt.figure(num=3,figsize=(8,5))
plt.plot(x,y2)
plt.plot(x,y1,'r--')

plt.xlim((-1,2))
plt.ylim((-2,3))    #设置x,y坐标轴范围
plt.xlabel('I am x')
plt.ylabel('I am y')    #设置x,y坐标轴标签 

new_ticks=np.linspace(-1,2,5)
print(new_ticks)
plt.xticks(new_ticks)
plt.yticks([-2,-1.8,-1,1.22,3],
    [r'$really\ bad$',r'$bad$',r'$normal$',r'$good$',r'$good\ \alpha$',]
    )

ax=plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data',-1))
ax.spines['left'].set_position(('data',0))

plt.show()

运行结果

关于legend图例

import matplotlib.pyplot as plt 
import numpy as np 
x=np.linspace(-3,3,50)
y1=2*x+1
y2=x**3

##plt.figure()
##plt.plot(x,y1)

plt.figure(num=3,figsize=(8,5))
l2,=plt.plot(x,y2,label='up')
l1,=plt.plot(x,y1,'r--',label='down')

plt.xlim((-1,2))
plt.ylim((-2,3))    #设置x,y坐标轴范围
plt.xlabel('I am x')
plt.ylabel('I am y')    #设置x,y坐标轴标签 

new_ticks=np.linspace(-1,2,5)
print(new_ticks)
plt.xticks(new_ticks)
plt.yticks([-2,-1.8,-1,1.22,3],
    [r'$really\ bad$',r'$bad$',r'$normal$',r'$good$',r'$good\ \alpha$',]
    )

ax=plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data',-1))
ax.spines['left'].set_position(('data',0))

plt.legend(handles=[l1,l2,],labels=['aaa','bbb'],loc='best')
plt.show()

运行结果

关于annotation标注

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-3, 3, 50)
y = 2*x + 1

plt.figure(num=1, figsize=(8, 5),)
plt.plot(x, y,)

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))

x0 = 1
y0 = 2*x0 + 1
plt.plot([x0, x0,], [0, y0,], 'k--', linewidth=2.5)
plt.scatter([x0, ], [y0, ], s=50, color='b')

# method 1:
#####################
plt.annotate(r'$2x+1=%s$' % y0, xy=(x0, y0), xycoords='data', xytext=(+30, -30),
             textcoords='offset points', fontsize=16,
             arrowprops=dict(arrowstyle='->', connectionstyle="arc3,rad=.2"))

# method 2:
########################
plt.text(-3.7, 3, r'$This\ is\ the\ some\ text. \mu\ \sigma_i\ \alpha_t$',
         fontdict={'size': 16, 'color': 'r'})

plt.show()

运行结果