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

图3.1

 

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

 

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

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

 

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

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

 

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

 

 

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

 

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

 

 

 

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

 

 

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

 

 

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

 

 

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

 

 

 

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

 

 

 

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

 

 

 

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

 

 

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

 

 

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

 

 

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

 

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

 

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

 

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

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

 

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

 

 

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

 

 

 

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

 

 

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

 

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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