数据可视化之matplotlib(01)--基本参数

引入matplotlib.pyplot包与全局中文字体设置

导入语句：

import matplotlib.pyplot as plt

pyplot包并不默认支持中文显示，需要.rcParams()方法修改字体来实现。
使用下面的语句：

plt.rcParams['font.sans-serif'] = ['SimHei'] #用来显示中文标签
plt.rcParams['axes.unicode_minus'] = False #用来正常显示负号

Plot快速绘图

举例：

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0.05,10,1000)  #在0.05~10之间间隔取1000个数
y = np.sin(x)

plt.plot(x,y)
plt.show()  #显示所绘图像

import matplotlib.pyplot as plt
%matplotlib inline  #使用notebook显示图像
import numpy as np
x = np.linspace(1,10,10)
y = x ** 2
plt.plot(x,y,color='#ff3456',marker='*',linestyle='--')   #plt.plot(x,y,'r*--')

import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
x = np.linspace(1,10,10)
y = np.cos(x)
plt.plot(x,y,'b*')

plt.plot()其他常用参数

1. linewidth #定义线条的宽度，可取任意实数
2. alpha #定义线条的透明度，一般取值**[0,1]**
3. drawstyle #定义描点方式

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

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'b*-', drawstyle = 'steps')

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

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'b*-', linewidth = 10, drawstyle = 'steps')

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

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'b*-', linewidth = 10, alpha = 0.3, drawstyle = 'steps')

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

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'b*-', linewidth = 10, alpha = 0.3, drawstyle = 'steps')

常用的图像设置命令

plt.title()设置图像标题

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'r*-',linewidth = 10, alpha = 0.6, drawstyle = 'steps')
plt.title("我的matplotlib图")

plt.xlim() 设置x轴显示范围

plt.xlabel() 设置x轴名称

plt.ylabel() 设置y轴名称

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'r*-',linewidth = 10, alpha = 0.6, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.xlim(2,6)
plt.xlabel("x轴")
plt.ylabel("y轴")

plt.grid() 显示坐标网格线

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'r*-',linewidth = 10, alpha = 0.6, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.xlim(2,6)
plt.xlabel("x轴")
plt.ylabel("y轴")
plt.grid()

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'r*-',linewidth = 10, alpha = 0.6, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.xlim(2,6)
plt.xlabel("x轴")
plt.ylabel("y轴")
plt.grid(linestyle=':', color = 'r')

plt.axhline() 绘制平行于x轴的水平参考线

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhline(y=0.25,color='blue',linewidth=6)

plt.axvline() 绘制平行于y轴的水平参考线

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhline(y=0.25,color='blue',linewidth=6)
plt.axvline(6,c='r',lw=5)

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhline(y=0.25,color='blue',linewidth=6)
plt.axvline(6,c='r',lw=5, ls='-.')

plt.axhspan() 绘制垂直于y轴的参考区域

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25)
plt.axvline(6,c='r',lw=5,ls='-.')

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25,facecolor = 'yellow',alpha=0.9)
plt.axvline(6,c='r',lw=5,ls='-.')

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25,facecolor = 'yellow',alpha=0.9)
plt.axvline(6,c='r',lw=5,ls='-.')
plt.axvspan(4,8,facecolor='c',alpha=0.3)

plt.axvspan() 绘制垂直于x轴的参考区域

plt.legend() 标示不同图形的文本标签图例

plt.xticks()设置x轴标签名称

plt.yticks()设置y轴标签名称

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps',label='y=sin(x)')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25,facecolor = 'yellow',alpha=0.9)
plt.axvline(6,c='r',lw=5,ls='-.')
plt.axvspan(4,8,facecolor='c',alpha=0.3)
plt.legend(loc='upper right')
plt.yticks([-1,-0.5,0,0.5,1],['甲','乙','丙','丁','戌'])

plt.text()添加图形内容细节的无指向型注释文本

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps',label='y=sin(x)')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25,facecolor = 'yellow',alpha=0.9)
plt.axvline(6,c='r',lw=5,ls='-.')
plt.axvspan(4,8,facecolor='c',alpha=0.3)
plt.legend(loc='upper right')
plt.text(1.5,0,'y=cos(x)',weight='bold',color='b')

plt.annotate()添加图形内容细节的指向型注释文本

x = np.linspace(0,10,10)
y = np.cos(x)
plt.plot(x,y,'g*-',linewidth = 10, alpha = 0.9, drawstyle = 'steps',label='y=sin(x)')
plt.title("我的matplotlib图")
plt.grid(ls=':',c='b')
plt.axhspan(-0.25,0.25,facecolor = 'yellow',alpha=0.9)
plt.axvline(6,c='r',lw=5,ls='-.')
plt.axvspan(4,8,facecolor='c',alpha=0.3)
plt.legend(loc='upper right')
plt.text(1.5,0,'y=cos(x)',weight='bold',color='b')
plt.annotate("最大值",xy=(0,1),xytext=(0.8,1),arrowprops=dict(arrowstyle='->'))