python-realization of Chart drawing summary

NumPy is a python open-source numerical extension that can be used to store and manipulate large matrices, which is more efficient than Python's own data structures;

Matplotlib is a python image frame that uses its drawing effect to resemble a graphic drawn under Matlab.

Before using Python to draw a chart, we need to install two library files NumPy and matplotlib

Pip Install Numpypip Install Matplotlib

Generate histograms

 import   NumPy as NP  from  pylab num  =100sigma  =20x  =num+sigma*np.random.randn (20000)   #样本数量   plt.hist (x,bins  =100,color= " green  " , Normed=true)   #bins显示有几个直方, normed whether the data is normalized   plt.show ()   #显示图像   
 Plt.savefig ()   #保存图片    

Operation Result:

generate a bar chart

Import NumPy as NP  from Import *value=[22,13,34]index=["root","  Admin","lyshark"]
#index =np.arange (5) Plt.bar (left =index,height=value,color="green", width= 0.5) plt.show ()

Operation Result:

generate a line chart

Import NumPy as NP  from Import *x=np.linspace ( -10,10,100) y=x**3plt.plot (x,y,linestyle=" -- ", color="green", marker="< " ) plt.show ()

Operation Result:

Generating Scatter plots

Import NumPy as NP  from Import *x=np.random.randn (+) y=x+np.random.randn (+) *0.5plt.scatter (x,y,s =5,marker="<")            #s represents the area  marker represents the graph  Plt.show ()

Operation Result:

Generate pie chart

ImportNumPy as NP fromPylabImport*Labels="Cangjingkong","Jizemingbu","Boduoyejieyi","Xiaozemaliya"Fracs=[45,10,30,15]plt.axes (Aspect=1) Explode=[0,0.05, 0,0]plt.pie (x=fracs,labels=labels,autopct="%0f%%", explode=explode) plt.show ()

Operation Result:

Create a Box chart

Mainly used to show the dispersion of data. The graph is divided into top edge, top four, median, bottom four, bottom edge. Outliers at the point outside

Import NumPy as NP  from Import *np.random.seed (+) data=np.random.normal (size= (1000,4), loc=0,scale=1) Labels=["A","B","C  ","D"]plt.boxplot (data,labels=labels) plt.show ()

Operation Result:

Generate multiple Legends

Import NumPy as NP  from Import *x=np.arange (1,11,1)          plt.plot (x,x)          plt.plot (x,x)          Plt.plot (x,x)      plt.legend (["boduoyejieyi","  cangjingkong","jiatengying"])          plt.show ( )

Operation Result:

python-realization of Chart drawing summary