《Python数据可视化之matplotlib实践》 源码 第一篇 入门 第三章（利用matplotlib做数据可视化）

《Python数据可视化之matplotlib实践》 源码 第一篇 入门 第三章（利用matplotlib做数据可视化）

图3.1

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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=0.35tick_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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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=0.35tick_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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npx=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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.rcParams['font.sans-serif']=['SimHei']mpl.rcParams['axes.unicode_minus']=False scoresT=np.random.randint(0,100,100)x=scoresTbins=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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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=colormapListinner_colors=colormapListwedges1,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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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*xlower_error=errorupper_error=0.3*xerror_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

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.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

import matplotlibimport matplotlib.pyplot as pltimport 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=0.6colors=['#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

import matplotlibimport matplotlib.pyplot as pltimport 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=0.4tick_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

import matplotlibimport matplotlib.pyplot as pltimport 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=0.6tick_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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