Python数据可视化编程指南

1、 Python 数据可视化编程指南01 前言Python 数据可视化利器，Bokeh、pyecharts 的用法，本文增加了 Plotly 的部分教程。02 推荐数据可视化的库有挺多的，这里推荐几个比较常用的：MatplotlibPlotlySeabornGgplotBokehPyechartPygal03 PlotlyPlotly 文档地址：https:/plot.ly/python/#financial-charts使用方式：Plotly 有 online 和 offline 两种方式，这里只介绍 offline 的。这是 Plotly 官方教程的一部分importplotly.plotl

2、yaspyimportnumpyasnpdata=dict(visible=False,line=dict(color=#00CED1,width=6),#配置线宽和颜色name=+str(step),x=np.arange(0,10,0.01),#x轴参数y=np.sin(step*np.arange(0,10,0.01)forstepinnp.arange(0,5,0.1)#y轴参数data10visible=Truepy.iplot(data,filename=SingleSineWave)只要将最后一行中的py.iplot替换为下面代码py.offline.plot便可以运行。漏斗图这

3、个图代码太长了，就不 po 出来了。Basic Box Plotimportplotly.plotlyimportplotly.graph_objsasgoimportnumpyasnpy0=np.random.randn(50)-1y1=np.random.randn(50)+1trace0=go.Box(y=y0)trace1=go.Box(y=y1)data=trace0,trace1plotly.offline.plot(data)Wind Rose Chartimportplotly.graph_objsasgotrace1=go.Barpolar(r=77.5,72.5,70.0,

4、45.0,22.5,42.5,40.0,62.5,text=North,N-E,East,S-E,South,S-W,West,N-W,name=11-14m/s,marker=dict(color=rgb(106,81,163)trace2=go.Barpolar(r=57.49999999999999,50.0,45.0,35.0,20.0,22.5,37.5,55.00000000000001,text=North,N-E,East,S-E,South,S-W,West,N-W,#鼠标浮动标签文字描述name=8-11m/s,marker=dict(color=rgb(158,154,2

5、00)trace3=go.Barpolar(r=40.0,30.0,30.0,35.0,7.5,7.5,32.5,40.0,text=North,N-E,East,S-E,South,S-W,West,N-W,name=5-8m/s,marker=dict(color=rgb(203,201,226)trace4=go.Barpolar(r=20.0,7.5,15.0,22.5,2.5,2.5,12.5,22.5,text=North,N-E,East,S-E,South,S-W,West,N-W,name=5m/s,marker=dict(color=rgb(242,240,247)data

6、=trace1,trace2,trace3,trace4layout=go.Layout(title=WindSpeedDistributioninLaurel,NE,font=dict(size=16),legend=dict(font=dict(size=16),radialaxis=dict(ticksuffix=%),orientation=270)fig=go.Figure(data=data,layout=layout)plotly.offline.plot(fig,filename=polar-area-chart)Basic Ternary Plot with Markers篇

7、幅有点长，这里就不 po 代码了。04 Bokeh这里展示一下常用的图表和比较抢眼的图表，详细的文档可查看。条形图这配色看着还挺舒服的，比 pyecharts 条形图的配色好看一点。frombokeh.ioimportshow,output_filefrombokeh.modelsimportColumnDataSourcefrombokeh.palettesimportSpectral6frombokeh.plottingimportfigureoutput_file(colormapped_bars.html)#配置输出文件名fruits=Apples,魅族,OPPO,VIVO,小米,华为

8、#数据counts=5,3,4,2,4,6#数据source=ColumnDataSource(data=dict(fruits=fruits,counts=counts,color=Spectral6)p=figure(x_range=fruits,y_range=(0,9),plot_height=250,title=FruitCounts,toolbar_location=None,tools=)#条形图配置项p.vbar(x=fruits,top=counts,width=0.9,color=color,legend=fruits,source=source)p.xgrid.grid_

9、line_color=None#配置网格线颜色p.legend.orientation=horizontal#图表方向为水平方向p.legend.location=top_centershow(p)#展示图表年度条形图可以对比不同时间点的量。frombokeh.ioimportshow,output_filefrombokeh.modelsimportColumnDataSource,FactorRangefrombokeh.plottingimportfigureoutput_file(bars.html)#输出文件名fruits=Apple,魅族,OPPO,VIVO,小米,华为#参数yea

10、rs=2015,2016,2017#参数data=fruits:fruits,2015:2,1,4,3,2,4,2016:5,3,3,2,4,6,2017:3,2,4,4,5,3x=(fruit,year)forfruitinfruitsforyearinyearscounts=sum(zip(data2015,data2016,data2017),()source=ColumnDataSource(data=dict(x=x,counts=counts)p=figure(x_range=FactorRange(*x),plot_height=250,title=FruitCountsbyYe

11、ar,toolbar_location=None,tools=)p.vbar(x=x,top=counts,width=0.9,source=source)p.y_range.start=0p.x_range.range_padding=0.1p.xaxis.major_label_orientation=1p.xgrid.grid_line_color=Noneshow(p)饼图fromcollectionsimportCounterfrommathimportpiimportpandasaspdfrombokeh.ioimportoutput_file,showfrombokeh.pale

12、ttesimportCategory20cfrombokeh.plottingimportfigurefrombokeh.transformimportcumsumoutput_file(pie.html)x=Counter(中国:157,美国:93,日本:89,巴西:63,德国:44,印度:42,意大利:40,澳大利亚:35,法国:31,西班牙:29)data=pd.DataFrame.from_dict(dict(x),orient=index).reset_index().rename(index=str,columns=0:value,index:country)dataangle=d

13、atavalue/sum(x.values()*2*pidatacolor=Category20clen(x)p=figure(plot_height=350,title=PieChart,toolbar_location=None,tools=hover,tooltips=country:value)p.wedge(x=0,y=1,radius=0.4,start_angle=cumsum(angle,include_zero=True),end_angle=cumsum(angle),line_color=white,fill_color=color,legend=country,sour

14、ce=data)p.axis.axis_label=Nonep.axis.visible=Falsep.grid.grid_line_color=Noneshow(p)条形图年度水果进出口frombokeh.ioimportoutput_file,showfrombokeh.modelsimportColumnDataSourcefrombokeh.palettesimportGnBu3,OrRd3frombokeh.plottingimportfigureoutput_file(stacked_split.html)fruits=Apples,Pears,Nectarines,Plums,G

15、rapes,Strawberriesyears=2015,2016,2017exports=fruits:fruits,2015:2,1,4,3,2,4,2016:5,3,4,2,4,6,2017:3,2,4,4,5,3imports=fruits:fruits,2015:-1,0,-1,-3,-2,-1,2016:-2,-1,-3,-1,-2,-2,2017:-1,-2,-1,0,-2,-2p=figure(y_range=fruits,plot_height=250,x_range=(-16,16),title=Fruitimport/export,byyear,toolbar_locat

16、ion=None)p.hbar_stack(years,y=fruits,height=0.9,color=GnBu3,source=ColumnDataSource(exports),legend=%sexports%xforxinyears)p.hbar_stack(years,y=fruits,height=0.9,color=OrRd3,source=ColumnDataSource(imports),legend=%simports%xforxinyears)p.y_range.range_padding=0.1p.ygrid.grid_line_color=Nonep.legend

17、.location=top_leftp.axis.minor_tick_line_color=Nonep.outline_line_color=Noneshow(p)散点图frombokeh.plottingimportfigure,output_file,showoutput_file(line.html)p=figure(plot_width=400,plot_height=400)p.circle(1,2,3,4,5,6,7,2,4,5,size=20,color=navy,alpha=0.5)show(p)六边形图这两天，马蜂窝刚被发现数据造假，这不，与马蜂窝应应景。importnum

18、pyasnpfrombokeh.ioimportoutput_file,showfrombokeh.plottingimportfigurefrombokeh.util.heximportaxial_to_cartesianoutput_file(hex_coords.html)q=np.array(0,0,0,-1,-1,1,1)r=np.array(0,-1,1,0,1,-1,0)p=figure(plot_width=400,plot_height=400,toolbar_location=None)#p.grid.visible=False#配置网格是否可见p.hex_tile(q,r

19、,size=1,fill_color=firebrick*3+navy*4,line_color=white,alpha=0.5)x,y=axial_to_cartesian(q,r,1,pointytop)p.text(x,y,text=(%d,%d)%(q,r)for(q,r)inzip(q,r),text_baseline=middle,text_align=center)show(p)环比条形图这个实现挺厉害的，看了一眼就吸引了我。我在代码中都做了一些注释，希望对你理解有帮助。注：圆心为正中央，即直角坐标系中标签为（0，0）的地方。fromcollectionsimportOrdere

20、dDictfrommathimportlog,sqrtimportnumpyasnpimportpandasaspdfromsix.movesimportcStringIOasStringIOfrombokeh.plottingimportfigure,show,output_fileantibiotics=bacteria,penicillin,streptomycin,neomycin,gram结核分枝杆菌,800,5,2,negative沙门氏菌,10,0.8,0.09,negative变形杆菌,3,0.1,0.1,negative肺炎克雷伯氏菌,850,1.2,1,negative布鲁

21、氏菌,1,2,0.02,negative铜绿假单胞菌,850,2,0.4,negative大肠杆菌,100,0.4,0.1,negative产气杆菌,870,1,1.6,negative白色葡萄球菌,0.007,0.1,0.001,positive溶血性链球菌,0.001,14,10,positive草绿色链球菌,0.005,10,40,positive肺炎双球菌,0.005,11,10,positivedrug_color=OrderedDict(#配置中间标签名称与颜色(盘尼西林,#0d3362),(链霉素,#c64737),(新霉素,black),)gram_color=positive

22、:#aeaeb8,negative:#e69584,#读取数据df=pd.read_csv(StringIO(antibiotics),skiprows=1,skipinitialspace=True,engine=python)width=800height=800inner_radius=90outer_radius=300-10minr=sqrt(log(.001*1E4)maxr=sqrt(log(1000*1E4)a=(outer_radius-inner_radius)/(minr-maxr)b=inner_radius-a*maxrdefrad(mic):returna*np.s

23、qrt(np.log(mic*1E4)+bbig_angle=2.0*np.pi/(len(df)+1)small_angle=big_angle/7#整体配置p=figure(plot_width=width,plot_height=height,title=,x_axis_type=None,y_axis_type=None,x_range=(-420,420),y_range=(-420,420),min_border=0,outline_line_color=black,background_fill_color=#f0e1d2)p.xgrid.grid_line_color=None

24、p.ygrid.grid_line_color=None#annularwedgesangles=np.pi/2-big_angle/2-df.index.to_series()*big_angle#计算角度colors=gram_colorgramforgramindf.gram#配置颜色p.annular_wedge(0,0,inner_radius,outer_radius,-big_angle+angles,angles,color=colors,)#smallwedgesp.annular_wedge(0,0,inner_radius,rad(df.penicillin),-big_

25、angle+angles+5*small_angle,-big_angle+angles+6*small_angle,color=drug_color盘尼西林)p.annular_wedge(0,0,inner_radius,rad(df.streptomycin),-big_angle+angles+3*small_angle,-big_angle+angles+4*small_angle,color=drug_color链霉素)p.annular_wedge(0,0,inner_radius,rad(df.neomycin),-big_angle+angles+1*small_angle,

26、-big_angle+angles+2*small_angle,color=drug_color新霉素)#绘制大圆和标签labels=np.power(10.0,np.arange(-3,4)radii=a*np.sqrt(np.log(labels*1E4)+bp.circle(0,0,radius=radii,fill_color=None,line_color=white)p.text(0,radii:-1,str(r)forrinlabels:-1,text_font_size=8pt,text_align=center,text_baseline=middle)#半径p.annula

27、r_wedge(0,0,inner_radius-10,outer_radius+10,-big_angle+angles,-big_angle+angles,color=black)#细菌标签xr=radii0*np.cos(np.array(-big_angle/2+angles)yr=radii0*np.sin(np.array(-big_angle/2+angles)label_angle=np.array(-big_angle/2+angles)label_anglelabel_angle-np.pi/2+=np.pi#easiertoreadlabelsontheleftside#

28、绘制各个细菌的名字p.text(xr,yr,df.bacteria,angle=label_angle,text_font_size=9pt,text_align=center,text_baseline=middle)#绘制圆形，其中数字分别为x轴与y轴标签p.circle(-40,-40,-370,-390,color=list(gram_color.values(),radius=5)#绘制文字p.text(-30,-30,-370,-390,text=Gram-+grforgringram_color.keys(),text_font_size=7pt,text_align=left,

29、text_baseline=middle)#绘制矩形，中间标签部分。其中-40，-40，-40为三个矩形的x轴坐标。18，0，-18为三个矩形的y轴坐标p.rect(-40,-40,-40,18,0,-18,width=30,height=13,color=list(drug_color.values()#配置中间标签文字、文字大小、文字对齐方式p.text(-15,-15,-15,18,0,-18,text=list(drug_color),text_font_size=9pt,text_align=left,text_baseline=middle)output_file(burtin.h

30、tml,title=burtin.pyexample)show(p)元素周期表元素周期表，这个实现好牛逼啊，距离初三刚开始学化学已经很遥远了，想当年我还是化学课代表呢！由于基本用不到化学了，这里就不实现了。真实状态05 Pyechartspyecharts 也是一个比较常用的数据可视化库，用得也是比较多的了，是百度 Echarts 库的 Python 支持。这里也展示一下常用的图表。文档地址为：/#/zh-cn/prepare?id=%E5%AE%89%E8%A3%85-pyecharts条形图frompyechartsimportBarbar=Bar(我的第一个图表,这里是副标题)bar.a

31、dd(服装,衬衫,羊毛衫,雪纺衫,裤子,高跟鞋,袜子,5,20,36,10,75,90)#bar.print_echarts_options()#该行只为了打印配置项，方便调试时使用bar.render()#生成本地HTML文件散点图frompyechartsimportPolarimportrandomdata_1=(10,random.randint(1,100)foriinrange(300)data_2=(11,random.randint(1,100)foriinrange(300)polar=Polar(极坐标系-散点图示例,width=1200,height=600)polar.

32、add(,data_1,type=scatter)polar.add(,data_2,type=scatter)polar.render()饼图importrandomfrompyechartsimportPieattr=A,B,C,D,E,Fpie=Pie(饼图示例,width=1000,height=600)pie.add(,attr,random.randint(0,100)for_inrange(6),radius=50,55,center=25,50,is_random=True,)pie.add(,attr,random.randint(20,100)for_inrange(6),

33、radius=0,45,center=25,50,rosetype=area,)pie.add(,attr,random.randint(0,100)for_inrange(6),radius=50,55,center=65,50,is_random=True,)pie.add(,attr,random.randint(20,100)for_inrange(6),radius=0,45,center=65,50,rosetype=radius,)pie.render()词云这个是我在前面的文章中用到的图片实例，这里就不 po 具体数据了。frompyechartsimportWordCloudname=SamSClub#词条value=10000#权重wordcloud=WordCloud(width=1300,height=620)wordcloud.add(,name,value,word_size_range=20,100)wordcloud.r