可视化传播PythonCheatSheet (4).pdf
Python For Data Science Cheat SheetMatplotlibLearn Python Interactively at www.DataCMatplotlibDataCampLearn Python for Data Science Interactively Prepare The DataAlso see Lists&NumPy Matplotlib is a Python 2D plotting library which produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.1 import numpy as np x=np.linspace(0,10,100)y=np.cos(x)z=np.sin(x)Show Plot plt.show()Save Plot Save figures plt.savefig(foo.png)Save transparent figures plt.savefig(foo.png,transparent=True)65 fig=plt.figure()fig2=plt.figure(figsize=plt.figaspect(2.0)Create Plot2Plot Anatomy&WorkflowAll plotting is done with respect to an Axes.In most cases,a subplot will fit your needs.A subplot is an axes on a grid system.fig.add_axes()ax1=fig.add_subplot(221)#row-col-num ax3=fig.add_subplot(212)fig3,axes=plt.subplots(nrows=2,ncols=2)fig4,axes2=plt.subplots(ncols=3)Customize PlotColors,Color Bars&Color MapsMarkersLinestylesMathtextText&AnnotationsLimits,Legends&Layouts The basic steps to creating plots with matplotlib are:1 Prepare data 2 Create plot 3 Plot 4 Customize plot 5 Save plot 6 Show plot import matplotlib.pyplot as plt x=1,2,3,4 y=10,20,25,30 fig=plt.figure()ax=fig.add_subplot(111)ax.plot(x,y,color=lightblue,linewidth=3)ax.scatter(2,4,6,5,15,25,color=darkgreen,marker=)ax.set_xlim(1,6.5)plt.savefig(foo.png)plt.show()Step 3,4Step 2Step 1Step 3Step 6Plot AnatomyWorkflow4 Limits&Autoscaling ax.margins(x=0.0,y=0.1)Add padding to a plot ax.axis(equal)Set the aspect ratio of the plot to 1 ax.set(xlim=0,10.5,ylim=-1.5,1.5)Set limits for x-and y-axis ax.set_xlim(0,10.5)Set limits for x-axis Legends ax.set(title=An Example Axes,Set a title and x-and y-axis labels ylabel=Y-Axis,xlabel=X-Axis)ax.legend(loc=best)No overlapping plot elements Ticks ax.xaxis.set(ticks=range(1,5),Manually set x-ticks ticklabels=3,100,-12,foo)ax.tick_params(axis=y,Make y-ticks longer and go in and out direction=inout,length=10)Subplot Spacing fig3.subplots_adjust(wspace=0.5,Adjust the spacing between subplots hspace=0.3,left=0.125,right=0.9,top=0.9,bottom=0.1)fig.tight_layout()Fit subplot(s)in to the figure area Axis Spines ax1.spinestop.set_visible(False)Make the top axis line for a plot invisible ax1.spinesbottom.set_position(outward,10)Move the bottom axis line outwardFigureAxes data=2*np.random.random(10,10)data2=3*np.random.random(10,10)Y,X=np.mgrid-3:3:100j,-3:3:100j U=-1-X*2+Y V=1+X-Y*2 from matplotlib.cbook import get_sample_data img=np.load(get_sample_data(axes_grid/bivariate_normal.npy)lines=ax.plot(x,y)Draw points with lines or markers connecting them ax.scatter(x,y)Draw unconnected points,scaled or colored axes0,0.bar(1,2,3,3,4,5)Plot vertical rectangles(constant width)axes1,0.barh(0.5,1,2.5,0,1,2)Plot horiontal rectangles(constant height)axes1,1.axhline(0.45)Draw a horizontal line across axes axes0,1.axvline(0.65)Draw a vertical line across axes ax.fill(x,y,color=blue)Draw filled polygons ax.fill_between(x,y,color=yellow)Fill between y-values and 0 Plotting Routines31D Data fig,ax=plt.subplots()im=ax.imshow(img,Colormapped or RGB arrays cmap=gist_earth,interpolation=nearest,vmin=-2,vmax=2)2D Data or ImagesVector Fields axes0,1.arrow(0,0,0.5,0.5)Add an arrow to the axes axes1,1.quiver(y,z)Plot a 2D field of arrows axes0,1.streamplot(X,Y,U,V)Plot 2D vector fieldsData Distributions ax1.hist(y)Plot a histogram ax3.boxplot(y)Make a box and whisker plot ax3.violinplot(z)Make a violin plot axes20.pcolor(data2)Pseudocolor plot of 2D array axes20.pcolormesh(data)Pseudocolor plot of 2D array CS=plt.contour(Y,X,U)Plot contours axes22.contourf(data1)Plot filled contours axes22=ax.clabel(CS)Label a contour plotFigureAxes/SubplotY-axisX-axis1D Data2D Data or Images plt.plot(x,x,x,x*2,x,x*3)ax.plot(x,y,alpha=0.4)ax.plot(x,y,c=k)fig.colorbar(im,orientation=horizontal)im=ax.imshow(img,cmap=seismic)fig,ax=plt.subplots()ax.scatter(x,y,marker=.)ax.plot(x,y,marker=o)plt.title(r$sigma_i=15$,fontsize=20)ax.text(1,-2.1,Example Graph,style=italic)ax.annotate(Sine,xy=(8,0),xycoords=data,xytext=(10.5,0),textcoords=data,arrowprops=dict(arrowstyle=-,connectionstyle=arc3),)plt.plot(x,y,linewidth=4.0)plt.plot(x,y,ls=solid)plt.plot(x,y,ls=-)plt.plot(x,y,-,x*2,y*2,-.)plt.setp(lines,color=r,linewidth=4.0)import matplotlib.pyplot as pltClose&Clear plt.cla()Clear an axis plt.clf()Clear the entire figure plt.close()Close a window
