3.1散點圖

import matplotlib.pyplot as plt
import numpy as npn = 1024
X = np.random.normal(0,1,n)
Y = np.random.normal(0,1,n)
T = np.arctan2(Y,X) #用于計算顏色plt.scatter(X,Y,s=75,c=T,alpha=0.5)#alpha是透明度
#plt.scatter(np.arange(5),np.arange(5))  #一條線的散點圖plt.xlim((-1.5,1.5))
plt.ylim((-1.5,1.5))
plt.xticks(())  #把x坐標刻度去掉
plt.yticks(())
plt.show()

3.2柱狀圖

import matplotlib.pyplot as plt
import numpy as npn = 12  #柱狀圖個數
X = np.arange(n)
Y1 = (1-X/float(n))*np.random.uniform(0.5,1.0,n)
Y2 = (1-X/float(n))*np.random.uniform(0.5,1.0,n)plt.bar(X,+Y1,facecolor = '#9999ff',edgecolor = 'white')
plt.bar(X,-Y2,facecolor = '#ff9999',edgecolor = 'white')for x,y in zip(X,Y1):plt.text(x+0.4,y+0.05,'%.2f'%y,ha = 'center',va = 'bottom')#+0.4,+0.05是為了標注不太擁擠,ha是橫向對齊，va是縱向對齊for x,y in zip(X,-Y2):plt.text(x+0.4,y-0.05,'-%.2f'%y,ha = 'center',va = 'top')plt.xlim(-.5,n)
plt.xticks(())
plt.ylim(-1.25,1.25)
plt.yticks(())plt.show()

3.3Contours等高線圖

import matplotlib.pyplot as plt
import numpy as npdef f(x,y):return  (1 + x /2 + x**5 + y**3)*np.exp(-x**2-y**2) #隨機高度公式n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
X,Y = np.meshgrid(x,y)  #網格的輸入（）等高線地圖是個網格plt.contourf(X,Y,f(X,Y),8,alpha = 0.75,cmap = plt.cm.hot)   #plt.cm.hot是將數值轉換為顏色，8代表背景分成n+2類
C = plt.contour(X,Y,f(X,Y),8,colors='black',linewidths=.5)  #等高線的繪制，8代表分成n+2類（多少個等高線）
plt.clabel(C,inline=True,fontsize = 10) #標簽plt.xticks(())
plt.yticks(())
plt.show()

3.4 image圖片

import matplotlib.pyplot as plt
import numpy as np# image data
a = np.array([0.313660827978, 0.365348418405, 0.423733120134,0.365348418405, 0.439599930621, 0.525083754405,0.423733120134, 0.525083754405, 0.651536351379]).reshape(3,3)plt.imshow(a, interpolation='nearest', cmap='bone', origin='lower') #lower是遞增，upper是遞減
plt.colorbar(shrink=.92)    #壓縮了到原來的0.92plt.xticks(())
plt.yticks(())
plt.show()

3.5 3D數據

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3Dfig = plt.figure()
ax = Axes3D(fig)    #3D坐標軸X = np.arange(-4,4,0.25)
Y = np.arange(-4,4,0.25)
X,Y = np.meshgrid(X,Y)
R = np.sqrt(X**2+Y**2)
Z = np.sin(R)ax.plot_surface(X,Y,Z,rstride=1,cstride=1,cmap=plt.get_cmap('rainbow'))
"""
============= ================================================Argument      Description============= ================================================*X*, *Y*, *Z* Data values as 2D arrays*rstride*     Array row stride (step size), defaults to 10*cstride*     Array column stride (step size), defaults to 10*color*       Color of the surface patches*cmap*        A colormap for the surface patches.*facecolors*  Face colors for the individual patches*norm*        An instance of Normalize to map values to colors*vmin*        Minimum value to map*vmax*        Maximum value to map*shade*       Whether to shade the facecolors============= ================================================
"""
ax.contourf(X,Y,Z,zdir='z',offset=-2,cmap = 'rainbow') #等高線
ax.set_zlim(-2,2)plt.show()