库importmatplotlib.pyplotaspltimportnumpyasnp # % matplotlibinline生成数据# definesomedatax=NP.linspace (0，10，100 ) 0.1 # meanandstandarddeviationy=NP.random.normal (mu，sigma，100 ) creatingdataofnormaldistribution折线asjdlz图PLT.PLL y )图像PLT.savefig(plota.png ) ) # saving images on local machine自定义轴、标题#plot ) time series (fig )， ax=plt.subplots ) )的color='red'(ax.grid ) ) ax.set_xlabel ) (time ) inminute ) ) ax.set_ylabel piechartimportnumpyasnpimportmatplotlib.pyplotaspltn=6z=NP.random.uniform (0，1， n ) PLT.pie(z ) plt.show ) )直方图创建N1=NP.random.randn ) 1000 ) N2=NP.random.uniform (-1，5，800 ) fig axes twocolumnsforpositionofplotsaxes[0].hist (n1 ) axes [0] . set _ title (histogram 3360正常分布' ) axes[ max(N1 ) axes(1).hist (N2 ) axes )1).set _ title 箱型绘图# box plots # createdatanp.random.seed (10 ) client_1=NP.random.normal ) 40、8、50 ) client _2=NP.ran 50 ) client_4=NP.random.normal ) 60、25、50 ) # combinethesedifferentcollectionsintoalistdata _ to _ plot=[ clined client _4] # createafigureinstancefig=PLT.figure (1，figsize=(9) 9，6 ) # createanaxesinstanceax=fig.add _ ax savethefigurefig.save fig (client _ comparison.png )，bbox_inches='tight ' ) ax.set_xticklabels ) )客户端' client4' )多根asjdlz制# multipleplotsinasinglediagramt=NP.arange (0，50 ) fig，ax=plt.subplots ) ) plt.plot(t aseparatelyPLT.plot(t，client_2，' b ' ) # plotting t，bseparatelyPLT.plot(t，client_3，' g ' ) # plotting t