python散点图
python scatter散点图用循环分类法加图例本文实例为大家分享了python scatter散点图用循环分类法加图例,供大家参考,具体内容如下
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import matplotlib.pyplot as plt import knn plt.rcparams[ 'font.sans-serif' ] = [ 'simhei' ] plt.rcparams[ 'axes.unicode_minus' ] = false datingdatamat, datinglabels = knn.file2matrix( 'datingtestset2.txt' ) plt.figure() type1_x = [] #一共有3类,所以定义3个空列表准备接受数据 type1_y = [] type2_x = [] type2_y = [] type3_x = [] type3_y = [] for i in range ( len (datinglabels)): #1000组数据,i循环1000次 if datinglabels[i] = = '1' : #根据标签进行数据分类,注意标签此时是字符串 type1_x.append(datingdatamat[i][ 0 ]) #取的是样本数据的第一列特征和第二列特征 type1_y.append(datingdatamat[i][ 1 ]) if datinglabels[i] = = '2' : type2_x.append(datingdatamat[i][ 0 ]) type2_y.append(datingdatamat[i][ 1 ]) if datinglabels[i] = = '3' : type3_x.append(datingdatamat[i][ 0 ]) type3_y.append(datingdatamat[i][ 1 ]) plt.scatter(type1_x, type1_y, s = 20 , c = 'r' , label = '不喜欢' ) plt.scatter(type2_x, type2_y, s = 40 , c = 'b' , label = '魅力一般' ) plt.scatter(type3_x, type3_y, s = 60 , c = 'k' , label = '极具魅力' ) plt.legend() plt.show() |
用面向对象的写法:
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import matplotlib.pyplot as plt import knn plt.rcparams[ 'font.sans-serif' ] = [ 'simhei' ] plt.rcparams[ 'axes.unicode_minus' ] = false datingdatamat, datinglabels = knn.file2matrix( 'datingtestset2.txt' ) plt.figure() axes = plt.subplot( 111 ) type1_x = [] type1_y = [] type2_x = [] type2_y = [] type3_x = [] type3_y = [] for i in range ( len (datinglabels)): if datinglabels[i] = = '1' : type1_x.append(datingdatamat[i][ 0 ]) type1_y.append(datingdatamat[i][ 1 ]) if datinglabels[i] = = '2' : type2_x.append(datingdatamat[i][ 0 ]) type2_y.append(datingdatamat[i][ 1 ]) if datinglabels[i] = = '3' : type3_x.append(datingdatamat[i][ 0 ]) type3_y.append(datingdatamat[i][ 1 ]) type1 = axes.scatter(type1_x, type1_y, s = 20 , c = 'r' ) type2 = axes.scatter(type2_x, type2_y, s = 40 , c = 'b' ) type3 = axes.scatter(type3_x, type3_y, s = 60 , c = 'k' ) plt.legend((type1, type2, type3), ( '不喜欢' , '魅力一般' , '极具魅力' )) plt.show() |
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持开心学习网。
原文链接:https://blog.csdn.net/xiaobaicai4552/article/details/79069207