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

Posted 2021-02-19 Hello_BeautifulWorld

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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