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不懂Python数据可视化图实现过程分析?其实想解决这个问题也不难,下面让小编带着大家一起学习怎么去解决,希望大家阅读完这篇文章后大所收获。
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# encoding=utf-8 import matplotlib.pyplot as plt from pylab import * # 支持中文 mpl.rcParams['font.sans-serif'] = ['SimHei'] # 'mentioned0cluster', names = ['mentioned1cluster','mentioned2cluster', 'mentioned3cluster', 'mentioned4cluster', 'mentioned5cluster', 'mentioned6cluster', 'mentioned7cluster', 'mentioned8cluster', 'mentioned9cluster', 'mentioned10cluster'] x = range(len(names)) # y_0625 = [39266,56796,42996,24872,13849,8609,5331,1971,554,169,26] y_0626_1=[4793,100,0,0,0,0,0,0,0,0] # y_0626_2=[2622,203,0,0,0,0,0,0,0,0,0] # plt.plot(x, y, 'ro-') # plt.plot(x, y1, 'bo-') # pl.xlim(-1, 11) # 限定横轴的范围 # pl.ylim(-1, 110) # 限定纵轴的范围 plt.plot(x, y_0626_1, marker='o', mec='r', mfc='w', label='HighRating:MentionedClusterNum Distribution') # plt.plot(x, y_0626_2, marker='o', mec='r', mfc='w', label='LowRating:MentionedClusterNum Distribution') # plt.plot(x, y1, marker='*', ms=10, label=u'y=x^3曲线图') plt.legend() # 让图例生效 plt.xticks(x, names, rotation=45) plt.margins(0) plt.subplots_adjust(bottom=0.15) # plt.xlabel(u"time(s)邻居") # X轴标签 plt.xlabel("clusters") plt.ylabel("number of reviews") # Y轴标签 plt.title("A simple plot") # 标题 plt.show()