《Python数据可视化之matplotlib实践》 源码 第一篇 入门 第三章
图3.1
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=[1,2,3,4,5] y=[6,10,4,5,1] plt.grid(True, axis='y',ls=':',color='r',alpha=0.3) plt.bar(x,y,align='center', color='b', tick_label=['A','B','C','D','E'], alpha=0.6, edgecolor="black") plt.xlabel('测试难度') plt.ylabel('试卷份数') plt.show()
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图3.2
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=[1,2,3,4,5] y=[6,10,4,5,1] plt.grid(True, axis='x',ls=':',color='r',alpha=0.3) plt.barh(x,y,align='center', color='c', tick_label=['A','B','C','D','E'], alpha=0.6, edgecolor="black") plt.ylabel('测试难度') plt.xlabel('试卷份数') plt.show()
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图 3.3
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=[1,2,3,4,5] y=[6,10,4,5,1] y1=[2,6,3,8,5] plt.bar(x,y,align='center',color='#66c2a5', tick_label=['A','B','C','D','E'], label='班级A', edgecolor='black') plt.bar(x,y1,align='center',color='#8da0cb', bottom=y, label='班级B', edgecolor='black') plt.xlabel("测试难度") plt.ylabel("测试份数") plt.legend() plt.show()
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图 3.4
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=[1,2,3,4,5] y=[6,10,4,5,1] y1=[2,6,3,8,5] plt.barh(x,y,align='center',color='#66c2a5', tick_label=['A','B','C','D','E'], label='班级A', edgecolor='black') plt.barh(x,y1,align='center',color='#8da0cb', left=y, label='班级B', edgecolor='black') plt.ylabel("测试难度") plt.xlabel("测试份数") plt.legend() plt.show()
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图 3.5
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.array([1,2,3,4,5]) y=[6,10,4,5,1] y1=[2,6,3,8,5] bar_width=0.35 tick_label=['A','B','C','D','E'] plt.bar(x, y, bar_width, align='center',color='c', label='班级A', alpha=0.5) plt.bar(x+bar_width,y1,bar_width, align='center',color='b', label='班级B', alpha=0.5) plt.xticks(x+bar_width/2, tick_label) plt.xlabel("测试难度") plt.ylabel("试卷份数") plt.legend() plt.show()
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图 3.6
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.array([1,2,3,4,5]) y=[6,10,4,5,1] y1=[2,6,3,8,5] bar_width=0.35 tick_label=['A','B','C','D','E'] plt.barh(x, y, bar_width, align='center',color='c', label='班级A', alpha=0.5) plt.barh(x+bar_width,y1,bar_width, align='center',color='b', label='班级B', alpha=0.5) plt.yticks(x+bar_width/2, tick_label) plt.ylabel("测试难度") plt.xlabel("试卷份数") plt.legend() plt.show()
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图 3.7
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=[1,2,3,4,5] y=[6,10,4,5,1] plt.bar(x,y, align='center', color='c', tick_label=['A','B','C','D','E'], hatch='///') plt.xlabel("测试难度") plt.ylabel("试卷份数") plt.show()
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图 3.8
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np x=np.arange(1,6,1) y=[0,4,3,5,6] y1=[1,3,4,2,7] y2=[1,1,1,1,1] labels=['BluePlanet', 'BrownPlanet', 'GreenPlanet'] colors=['#8da0cb','#fc8d62','#66c2a5'] plt.stackplot(x, y, y1, y2, labels=labels, colors=colors) plt.legend(loc='upper left') plt.show()
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图 3.9
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False plt.broken_barh([(30,100),(180,50),(260,70)], (20,8), facecolors='#1f78b4') plt.broken_barh([(60,90),(190,20),(230,30),(280,60)], (10,8), facecolors=['#7fc97f','#beaed4','#fdc086','#ffff99']) plt.xticks(np.arange(0,361,60)) plt.yticks([15,25],['歌剧院A','歌剧院B']) plt.xlim(0, 360) plt.ylim(5, 35) plt.xlabel("演出时间(分)") plt.grid(ls='-', lw=1, color='gray') plt.title("不同地区的歌剧院的演出时间比较") plt.show()
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图 3.10
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.linspace(1,10,10) y=np.sin(x) plt.step(x,y,color='#8dd3c7', where='pre', lw=2) plt.xlim(0, 11) plt.ylim(-1.2, 1.2) plt.xticks(np.arange(1, 11, 1)) plt.show()
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图 3.11
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.linspace(1,10,10) y=np.sin(x) plt.step(x,y,color='#8dd3c7', where='post', lw=2) plt.xlim(0, 11) plt.ylim(-1.2, 1.2) plt.xticks(np.arange(1, 11, 1)) plt.show()
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图 3.12
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False scoresT=np.random.randint(0,100,100) x=scoresT bins=range(0,101,10) plt.hist(x, bins, color='#377eb8', histtype='bar',rwidth=1.0, edgecolor="black") plt.xlabel("测试成绩") plt.ylabel("学生人数") plt.show()
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图 3.14
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False scoresT1=np.random.randint(0,100,100) scoresT2=np.random.randint(0,100,100) x=[scoresT1,scoresT2] colors=['#8dd3c7','#bebada'] labels=['班级A','班级B'] bins=range(0,101,10) plt.hist(x,bins=bins, color=colors, histtype='bar', edgecolor="black", rwidth=1.0, stacked=True, label=labels) plt.xlabel("测试成绩(分)") plt.ylabel("学生人数") plt.title("不同班级的测试成绩直方图") plt.legend(loc="upper left") plt.show()
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图 3.15
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False scoresT1=np.random.randint(0,100,100) scoresT2=np.random.randint(0,100,100) x=[scoresT1,scoresT2] colors=['#8dd3c7','#bebada'] labels=['班级A','班级B'] bins=range(0,101,10) plt.hist(x,bins=bins, color=colors, histtype='bar', edgecolor="black", rwidth=0.8, stacked=False, label=labels) plt.xlabel("测试成绩(分)") plt.ylabel("学生人数") plt.title("不同班级的测试成绩直方图") plt.legend(loc="upper left") plt.show()
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图 3.16
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False scoresT1=np.random.randint(0,100,100) scoresT2=np.random.randint(0,100,100) x=[scoresT1,scoresT2] colors=['#8dd3c7','#bebada'] labels=['班级A','班级B'] bins=range(0,101,10) plt.hist(x, bins=bins, color=colors, histtype='stepfilled', edgecolor="black", rwidth=1.0, stacked=True, label=labels) plt.xlabel("测试成绩(分)") plt.ylabel("学生人数") plt.title("不同班级的测试成绩的直方图") plt.legend() plt.show()
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图 3.17
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False labels=['A 难度水平','B 难度水平','C 难度水平','D 难度水平'] students=[0.35, 0.15, 0.2, 0.3] colors=['#377eb8','#4daf4a','#984ea3','#ff7f00'] explode=[0.1, 0.1, 0.1, 0.1] plt.pie(students, explode=explode, labels=labels, autopct="%3.1f%%", startangle=45, shadow=True, colors=colors) plt.title("选择不同难度测试试卷的学生占比") plt.show()
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图 3.18
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False labels=['A 难度水平','B 难度水平','C 难度水平','D 难度水平'] students=[0.35, 0.15, 0.2, 0.3] colors=['#377eb8','#4daf4a','#984ea3','#ff7f00'] explode=[0.1, 0.1, 0.1, 0.1] #百分比数值pctdistance=0.7, 标签值labeldistance=1.2 以半径长度比例值作为显示依据 plt.pie(students, labels=labels, pctdistance=0.7, labeldistance=1.2, autopct="%3.1f%%", startangle=45, colors=colors) plt.title("选择不同难度测试试卷的学生占比") plt.show()
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图 3.19
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False elements=['面粉','砂糖','奶油','草莓酱','坚果'] weight1=[40,15,20,10,15] weight2=[30,25,15,20,10] colormapList=['#e41a1c','#377eb8','#4daf4a','#984ea3','#ff7f00'] outer_colors=colormapList inner_colors=colormapList wedges1,texts1,autotexts1=plt.pie(weight1,autopct='%3.1f%%',radius=1.0, labels=elements, pctdistance=0.80,labeldistance=1.1, colors=outer_colors,textprops=dict(color='black'), wedgeprops=dict(width=0.4, edgecolor='w')) wedges2,texts2,autotexts2=plt.pie(weight2,autopct='%3.1f%%',radius=0.6, pctdistance=0.65,colors=inner_colors,textprops=dict(color='black'), wedgeprops=dict(width=0.4, edgecolor='w')) plt.legend(wedges1,elements, fontsize=12, title='配料表', loc="upper right", bbox_to_anchor=(1.31, 1.0)) #设置百分比数值大小、粗细 plt.setp(autotexts1,size=13,weight='bold') plt.setp(autotexts2,size=13,weight='bold') #设置标签字体 plt.setp(texts1, size=13) # plt.setp(texts2,size=12) plt.title("不同果酱面包配料比例表") plt.show()
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图 3.20
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False plt.grid(axis='y', ls=':', lw=1, color='gray', alpha=0.4) testA=np.random.randn(5000) testB=np.random.randn(5000) testList=[testA, testB] labels=['随机数生成器AlphaRM','随机数生成器BetaRM'] colors=['#1b9e77','#d95f02'] #四分位间距的倍数,确定箱须包含数据的范围 whis=1.6 #箱体宽度 width=0.35 #patch_artist 是否给箱体加颜色, sym离群点形式 bplot=plt.boxplot(testList, whis=whis, widths=width, sym='o', labels=labels, patch_artist=True) for patch, color in zip(bplot['boxes'], colors): patch.set_facecolor(color) plt.ylabel("随机数值") plt.title("生成器抗干扰能力的稳定性比较") plt.show()
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图 3.21
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False plt.grid(axis='y', ls=':', lw=1, color='gray', alpha=0.4) testA=np.random.randn(5000) testB=np.random.randn(5000) testList=[testA, testB] labels=['随机数生成器AlphaRM','随机数生成器BetaRM'] colors=['#1b9e77','#d95f02'] #四分位间距的倍数,确定箱须包含数据的范围 whis=1.6 #箱体宽度 width=0.35 #patch_artist 是否给箱体加颜色, sym离群点形式 bplot=plt.boxplot(testList, whis=whis, widths=width, sym='o', labels=labels, patch_artist=True, notch=True) for patch, color in zip(bplot['boxes'], colors): patch.set_facecolor(color) plt.ylabel("随机数值") plt.title("生成器抗干扰能力的稳定性比较") plt.show()
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图 3.23
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.random.randn(1000) plt.boxplot(x,vert=False) plt.xlabel("随机数值") plt.yticks([1],[""], rotation=90) plt.ylabel('随机数生成器AlphaRM') plt.grid(axis='x',ls=':', lw=1,color='gray', alpha=0.4) plt.title("随机数生成器抗干扰能力的稳定性") plt.show()
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图 3.24
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.random.randn(1000) plt.boxplot(x, vert=False, showfliers=False) plt.xlabel("随机数值") plt.yticks([1],[""], rotation=90) plt.ylabel('随机数生成器AlphaRM') plt.grid(axis='x',ls=':', lw=1,color='gray', alpha=0.4) plt.title("随机数生成器抗干扰能力的稳定性") plt.show()
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图 3.25
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.linspace(0.1, 0.6, 10) y=np.exp(x) error=0.05+0.15*x lower_error=error upper_error=0.3*x error_limit=[lower_error, upper_error] plt.errorbar(x, y, yerr=error_limit, fmt=":o", ecolor='y', elinewidth=4, ms=5, mfc='c', mec='r', capthick=1, capsize=4) plt.xlim(0, 0.7) plt.show()
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图 3.26
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import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False x=np.arange(5) y=[100,68,79,91,82] std_err=[7,2,6,10,5] error_attri=dict(elinewidth=2, ecolor='black', capsize=3) plt.bar(x, y, color='c',width=0.6, align='center', yerr=std_err, error_kw=error_attri, tick_label=['园区1', '园区2', '园区3', '园区4', '园区5']) plt.xlabel("芒果种植区") plt.ylabel("收割量") plt.title("不同芒果种植区的单次收割量") plt.grid(True, axis='y', ls=":", color="gray", alpha=0.2) plt.show()
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图 3.27
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import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.arange(5) y=[1200, 2400, 1800, 2200, 1600] std_err=[150,100,180,130,80] bar_width=0.6 colors=['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00'] plt.barh(x, y, bar_width, color=colors, align='center', xerr=std_err, tick_label=['家庭', '小说', '心理', '科技', '儿童']) plt.xlabel("订购数量") plt.ylabel("图书种类") plt.title("大型图书展销会的不同图书种类的采购情况") plt.grid(True, axis='x', ls=':', color='gray', alpha=0.2) plt.xlim(0, 2600) plt.show()
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图 3.28
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.arange(5) y1=[100, 68, 79, 91, 82] y2=[120, 75, 70, 78, 85] std_err1=[7, 2, 6, 10, 5] std_err2=[5, 1, 4, 8, 9] error_attri=dict(elinewidth=2, ecolor='black', capsize=3) bar_width=0.4 tick_label=['园区1', '园区2', '园区3', '园区4', '园区5'] plt.bar(x, y1, bar_width, color='#87CEEB', align='center', yerr=std_err1, error_kw=error_attri, label='2010') plt.bar(x+bar_width, y2, bar_width, color='#CD5C5C', align='center', yerr=std_err2, error_kw=error_attri, label='2013') plt.xticks(x+bar_width/2, tick_label) plt.grid(True, axis='y', ls=':', color='gray', alpha=0.2) plt.legend() plt.xlabel("芒果种植区") plt.ylabel("收割量") plt.title("不同芒果种植区的单次收割量") plt.grid(True, axis='y', ls=":", color="gray", alpha=0.2) plt.show()
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图 3.29
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import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.arange(5) y1=[1200, 2400, 1800, 2200, 1600] y2=[1050, 2100, 1300, 1600, 1340] std_err1=[150, 100, 180, 130, 80] std_err2=[120, 110, 170, 150, 120] error_attri=dict(elinewidth=2, ecolor='black', capsize=0) bar_width=0.6 tick_label=['家庭', '小说', '心理', '科技', '儿童'] plt.bar(x, y1, bar_width, color='#6495ED', align='center', yerr=std_err1, error_kw=error_attri, label='地区1') plt.bar(x, y2, bar_width, bottom=y1, color='#FFA500', align='center', yerr=std_err2, error_kw=error_attri, label='地区2') plt.xlabel("图书种类") plt.ylabel("订购数量") plt.xticks(x, tick_label) plt.title("大型图书展销会的不同图书种类的采购情况") plt.grid(True, axis='y', ls=':', color='gray', alpha=0.2) plt.legend() plt.show()
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posted on 2020-05-14 18:11 Angry_Panda 阅读(781) 评论(0) 编辑 收藏 举报