Python data analytics drawing experience

For numpy functions, pands and so on, is not very familiar, I will copy the code, tap, look for feelings.

The default import Package
Import NumPy as NP
Import Matplotlib.pyplot as Plt

DefPrint_line_draw(): "" "Draw Straight Return:" "X=Np.Arange(0,9,1)Y=X+8Plt.Plot(X,Y,color= "red" linestyle=,= "*" ,label=< span class= "str" > ' y=x+8 ' )  Plt. ( "1.png" ,dpi= 60)  Plt. ()  Plt. ()               

DefPrint_pie_draw(): "" "Draw Pie Return:" " #指定切片大小比例Sclice=[2,3,5,8] #指定标签Activite=["Sleep","Eating","Study","Work"] #颜色Color=[' B ',' m ',' R ',' W ']Plt.Pie(Sclice,Labels=Activite,Colors=Color,StartAngle=0, Shadow=true, Explode= (0,0.2 ,0,0),  Autopct= '%1.1f%% ' ) . Title ( "Activite Analys"  PLT savefig ()  plt< Span class= "pun". show ()             

DefPrint_scatter_draw():    "" "Draw scatter Plot return:" "X=Np.Random.Rand(1000)Y=Np.Random.Rand(Len(X)) #绘图Plt.Scatter(X,Y,Color= ' B ' ,label=  "scatter draw" , Alpha= 0.3,marker= "P"  Plt. ()  Plt. ( "3.png" ,dpi= 60)  Plt. () print_scatter_draw ()      

DefPrint_hist_draw():    "" "Picture Histogram" ""X=Np.Random.Randint(1,800,300)Axit=Plt.Gca() #得到当前绘图对象Axit.hist(X,Bins=35,Facecolor=' R ',Normed=True,histtype= "bar" ,< Span class= "PLN" >alpha=0.5)  Axitset_xlabel ( "values" ) . Set_title)  Plt . savefig (,dpi< Span class= "pun" >=150)  Plt. Show ()               

This one's not written as a function.

ImportNumPyAsNpImportMatplotlib.PyplotAsPltx=Np.Linspace(0,10,1200)Y=Np.Sin(X)+1Z=Np.Cos(X**2)+1#设置图像大小Plt.Figure(Figsize=(8,6))Plt.Plot(X,Y,Label=' $\cosx+1$ ',Color="Red",LineWidth=2)Plt.Plot(X,Z,Label=' $\cos x^2+1$ ')#设置x轴Plt.Xlabel("Time (s)")Plt.ylabel (plt< Span class= "pun". title () plt< Span class= "pun". ylim (0,2 plt. () plt. ( "5.png" ,dpi= 120) plt. ()               

Copy of the article
Introduction to Matplotlib Data mining

Find Python code pasted in the past, because indentation, need to be re-modified, a little trouble
Baidu Cloud source sharing, download down, experience running it.

Axis, no calibration, with my MMA, take a look at the last image.

The most favorite MMA, is still very powerful, several to solve a problem.

Python data analytics drawing experience
In MU class network, as if the picture shows a problem, I modify MARKD also not,
To see the modified image, click on the link forklift rental

Python data analytics drawing experience