python可视化之散点图的绘制

我们仍然以Iris数据集为例进行散点图的绘制，为了对不同的cell进行区分，我们需要使用plt.sca(cell)指明cell所在的位置。此外，如果使每个cell的横纵坐标的比例尺相等，可以在plt.subplots中添加额外的参数 sharex=True, sharey=True，在本例中不同的属性具有不同的scale，所以我们不需要设置相同的比例尺。实现的方法如下，欢迎各位指教。

#divide the data set to blocksdata_s0 = [x.split(',')[0] for x in content[0:50]]      #sepal length of setosa#remove the none datawhile '' in data_s0:    data_s0.remove('')#plot 16 subplotsfig, axes2d = plt.subplots(nrows=4, ncols=4,                           figsize=(15,15))for i, row in enumerate(axes2d):    for j, cell in enumerate(row):        if i==0 and j==0:            plt.sca(cell)             cell.set_ylabel("sepal length")            plt.xlim(4,8)            cell.set_xbound(lower=4.0, upper=8.0)        if i==0 and j==1:            plt.sca(cell)             l1=plt.scatter(data_s1, data_s0, marker = 'x', color = 'm')              l2=plt.scatter(data_ve1, data_ve0, marker = '+', color = 'c')              l3=plt.scatter(data_vi1, data_vi0, marker = 'o', color = 'r')         elif i==0 and j==2:            plt.sca(cell)             l1=plt.scatter(data_s2, data_s0, marker = 'x', color = 'm')              l2=plt.scatter(data_ve2, data_ve0, marker = '+', color = 'c')              l3=plt.scatter(data_vi2, data_vi0, marker = 'o', color = 'r')             cell.set_autoscaley_on(False)        elif i==0 and j==3:            plt.sca(cell)             l1=plt.scatter(data_s3, data_s0, marker = 'x', color = 'm')              l2=plt.scatter(data_ve3, data_ve0, marker = '+', color = 'c')              l3=plt.scatter(data_vi3, data_vi0, marker = 'o', color = 'r')         elif i==1 and j==0:            plt.sca(cell)             cell.set_ylabel("sepal width")            l1=plt.scatter(data_s0, data_s1, marker = 'x', color = 'm')              l2=plt.scatter(data_ve0, data_ve1, marker = '+', color = 'c')              l3=plt.scatter(data_vi0, data_vi1, marker = 'o', color = 'r')         elif i==1 and j==1:            plt.sca(cell)         elif i==1 and j==2:            plt.sca(cell)             l1=plt.scatter(data_s2, data_s1, marker = 'x', color = 'm' )              l2=plt.scatter(data_ve2, data_ve1, marker = '+', color = 'c')              l3=plt.scatter(data_vi2, data_vi1, marker = 'o', color = 'r')        elif i==1 and j==3:            plt.sca(cell)             l1=plt.scatter(data_s3, data_s1, marker = 'x', color = 'm')              l2=plt.scatter(data_ve3, data_ve1, marker = '+', color = 'c')              l3=plt.scatter(data_vi3, data_vi1, marker = 'o', color = 'r')         elif i==2 and j==0:            plt.sca(cell)             cell.set_ylabel("petal length")            l1=plt.scatter(data_s0, data_s2, marker = 'x', color = 'm')              l2=plt.scatter(data_ve0, data_ve2, marker = '+', color = 'c')              l3=plt.scatter(data_vi0, data_vi2, marker = 'o', color = 'r')         elif i==2 and j==1:            plt.sca(cell)             l1=plt.scatter(data_s1, data_s2, marker = 'x', color = 'm')              l2=plt.scatter(data_ve1, data_ve2, marker = '+', color = 'c')              l3=plt.scatter(data_vi1, data_vi2, marker = 'o', color = 'r')         elif i==2 and j==2:            plt.sca(cell)         elif i==2 and j==3:            plt.sca(cell)             l1=plt.scatter(data_s3, data_s2, marker = 'x', color = 'm')              l2=plt.scatter(data_ve3, data_ve2, marker = '+', color = 'c')              l3=plt.scatter(data_vi3, data_vi2, marker = 'o', color = 'r')         elif i==3 and j==0:            plt.sca(cell)             cell.set_ylabel("petal width")            cell.set_xlabel("sepal length")            l1=plt.scatter(data_s0, data_s3, marker = 'x', color = 'm')              l2=plt.scatter(data_ve0, data_ve3, marker = '+', color = 'c')              l3=plt.scatter(data_vi0, data_vi3, marker = 'o', color = 'r')         elif i==3 and j==1:            plt.sca(cell)             cell.set_xlabel("sepal width")            l1=plt.scatter(data_s1, data_s3, marker = 'x', color = 'm' )              l2=plt.scatter(data_ve1, data_ve3, marker = '+', color = 'c')              l3=plt.scatter(data_vi1, data_vi3, marker = 'o', color = 'r')         elif i==3 and j==2:            plt.sca(cell)             cell.set_xlabel("petal length")            l1=plt.scatter(data_s2, data_s3, marker = 'x', color = 'm')              l2=plt.scatter(data_ve2, data_ve3, marker = '+', color = 'c')              l3=plt.scatter(data_vi2, data_vi3, marker = 'o', color = 'r')         elif i==3 and j==3:            plt.sca(cell)             cell.set_xlabel("petal width")        else:            passplt.legend((l1, l2, l3),           ('Setosa', 'Versicolour', 'Virginica'),           scatterpoints=1,           loc='center',           ncol=1,           fontsize=10)#save the imagefig.savefig("../image/matrix_of_scatte_ plots_for_the_Iris_data_set.png")#show the imageplt.show()

效果图如下：