标签：val red 1.4 数据可视化 简单的 2.0 x11 params lis
第7章 用matplotlib实现数据可视化 149
7.1 matplotlib库 149
7.2 安装 150
7.3 IPython和IPython QtConsole 150
7.4 matplotlib架构 151
7.4.1 Backend层 152
7.4.2 Artist层 152
7.4.3 Scripting层（pyplot） 153
7.4.4 pylab和pyplot 153
7.5 pyplot 154
7.5.1 生成一幅简单的交互式图表 154
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import matplotlib.pyplot as plt
%matplotlib inline
plt.plot([1,2,3,4])
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[<matplotlib.lines.Line2D at 0xb50aa10>]
7.5.2 设置图形的属性 156
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plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xc78c450>]
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xc7ab610>]
7.5.3 matplotlib和NumPy 158
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import math
import numpy as np
t = np.arange(0,2.5,0.1)
y1 = list(map(math.sin,math.pi*t))
y2 = list(map(math.sin,math.pi*t+math.pi/2))
y3 = list(map(math.sin,math.pi*t-math.pi/2))
plt.plot(t,y1,‘b*‘,t,y2,‘g^‘,t,y3,‘ys‘)
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[<matplotlib.lines.Line2D at 0xc9e7ff0>,
<matplotlib.lines.Line2D at 0xc9f3110>,
<matplotlib.lines.Line2D at 0xc9f3430>]
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plt.plot(t,y1,‘b--‘,t,y2,‘g‘,t,y3,‘r-.‘)
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[<matplotlib.lines.Line2D at 0xca757b0>,
<matplotlib.lines.Line2D at 0xca758b0>,
<matplotlib.lines.Line2D at 0xca75bd0>]
7.6 使用kwargs 160
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plt.plot([1,2,4,2,1,0,1,2,1,4],linewidth=2.0)
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[<matplotlib.lines.Line2D at 0xcaba9d0>]
处理多个Figure和Axes对象
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t = np.arange(0,5,0.1)
y1 = np.sin(2*np.pi*t)
y2 = np.sin(2*np.pi*t)
plt.subplot(211)
plt.plot(t,y1,‘b-.‘)
plt.subplot(212)
plt.plot(t,y2,‘r--‘)
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[<matplotlib.lines.Line2D at 0xcb219b0>]
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t = np.arange(0.,1.,0.05)
y1 = np.sin(2*np.pi*t)
y2 = np.cos(2*np.pi*t)
plt.subplot(121)
plt.plot(t,y1,‘b-.‘)
plt.subplot(122)
plt.plot(t,y2,‘r--‘)
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[<matplotlib.lines.Line2D at 0xcb8c670>]
7.7 为图表添加更多元素 162
7.7.1 添加文本 162
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘)
plt.xlabel(‘Counting‘)
plt.ylabel(‘Square values‘)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xcbdf930>]
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xcc19fb0>]
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(1,1.5,‘First‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xcc5ca50>]
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(1,1.5,‘First‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.text(1.1,12,r‘$y = x^2$‘,fontsize=20,bbox={‘facecolor‘:‘yellow‘,‘alpha‘:0.2})
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xcca15f0>]
7.7.2 添加网格 165
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(1,1.5,‘First‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.text(1.1,12,r‘$y = x^2$‘,fontsize=20,bbox={‘facecolor‘:‘yellow‘,‘alpha‘:0.2})
plt.grid(True)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
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[<matplotlib.lines.Line2D at 0xcd2e6b0>]
7.7.3 添加图例 166
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.text(1.1,12,‘$y = x^2$‘,fontsize=20,bbox={‘facecolor‘:‘yellow‘,‘alpha‘:0.2})
plt.grid(True)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
plt.legend([‘First series‘])
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<matplotlib.legend.Legend at 0xcd71750>
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import matplotlib.pyplot as plt
plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(1,1.5,‘First‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.text(1.1,12,‘$y = x^2$‘,fontsize=20,bbox={‘facecolor‘:‘yellow‘,‘alpha‘:0.2})
plt.grid(True)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
plt.plot([1,2,3,4],[0.8,3.5,8,15],‘g^‘)
plt.plot([1,2,3,4],[0.5,2.5,4,12],‘b*‘)
plt.legend([‘First series‘,‘Second series‘,‘Third series‘],loc=2)
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<matplotlib.legend.Legend at 0xcdca450>
Location Code Location String
0 best
1 upper-right
2 upper-left
3 lower-right
4 lower-left
5 right
6 center-left
7 center-right
8 lower-center
9 upper-center
10 centerChapter
7.8 保存图表 168
7.8.1 保存代码 169
7.8.2 将会话转换为HTML文件 170
7.8.3 将图表直接保存为图片 171
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plt.axis([0,5,0,20])
plt.title(‘My first plot‘,fontsize=20,fontname=‘Times New Roman‘)
plt.xlabel(‘Counting‘,color=‘gray‘)
plt.ylabel(‘Square values‘,color=‘gray‘)
plt.text(1,1.5,‘First‘)
plt.text(2,4.5,‘Second‘)
plt.text(3,9.5,‘Third‘)
plt.text(4,16.5,‘Fourth‘)
plt.text(1.1,12,‘$y = x^2$‘,fontsize=20,bbox={‘facecolor‘:‘yellow‘,‘alpha‘:0.2})
plt.grid(True)
plt.plot([1,2,3,4],[1,4,9,16],‘ro‘)
plt.plot([1,2,3,4],[0.8,3.5,8,15],‘g^‘)
plt.plot([1,2,3,4],[0.5,2.5,4,12],‘b*‘)
plt.legend([‘First series‘,‘Second series‘,‘Third series‘],loc=2)
plt.savefig(‘my_chart.png‘)
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7.9 处理日期值 171
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import datetime
import numpy as np
import matplotlib.pyplot as plt
events = [datetime.date(2015,1,23),datetime.date(2015,1,28),datetime.
date(2015,2,3),datetime.date(2015,2,21),datetime.date(2015,3,15),datetime.
date(2015,3,24),datetime.date(2015,4,8),datetime.date(2015,4,24)]
readings = [12,22,25,20,18,15,17,14]
plt.plot(events,readings)
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[<matplotlib.lines.Line2D at 0xcdfa2d0>]
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import datetime
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
months = mdates.MonthLocator()
days = mdates.DayLocator()
timeFmt = mdates.DateFormatter(‘%Y-%m‘)
events = [datetime.date(2015,1,23),datetime.date(2015,1,28),datetime.
date(2015,2,3),datetime.date(2015,2,21),datetime.date(2015,3,15),datetime.
date(2015,3,24),datetime.date(2015,4,8),datetime.date(2015,4,24)]
readings = [12,22,25,20,18,15,17,14]
fig, ax = plt.subplots()
plt.plot(events,readings)
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(timeFmt)
ax.xaxis.set_minor_locator(days)
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7.10 图表类型 173
7.11 线性图 173
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(3*x)/x
plt.plot(x,y)
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[<matplotlib.lines.Line2D at 0xcf9eab0>]
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(x)/x
y2 = np.sin(2*x)/x
y3 = np.sin(3*x)/x
plt.plot(x,y)
plt.plot(x,y2)
plt.plot(x,y3)
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[<matplotlib.lines.Line2D at 0xcdc4ff0>]
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(x)/x
y2 = np.sin(2*x)/x
y3 = np.sin(3*x)/x
plt.plot(x,y,‘k--‘,linewidth=3)
plt.plot(x,y2,‘m-.‘)
plt.plot(x,y3,color=‘#87a3cc‘,linestyle=‘--‘)
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[<matplotlib.lines.Line2D at 0xe00f2d0>]
Code Color
b blue
g green
r red
c cyan
m magenta
y yellow
k black
w white
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(3*x)/x
y2 = np.sin(2*x)/x
y3 = np.sin(x)/x
plt.plot(x,y,color=‘b‘)
plt.plot(x,y2,color=‘r‘)
plt.plot(x,y3,color=‘g‘)
plt.xticks([-2*np.pi, -np.pi, 0, np.pi, 2*np.pi],
[r‘$-2\pi$‘,r‘$-\pi$‘,r‘$0$‘,r‘$+\pi$‘,r‘$+2\pi$‘])
plt.yticks([-1,0,+1,+2,+3],
[r‘$-1$‘,r‘$0$‘,r‘$+1$‘,r‘$+2$‘,r‘$+3$‘])
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([<matplotlib.axis.YTick at 0xe0358f0>,
<matplotlib.axis.YTick at 0xe00f7f0>,
<matplotlib.axis.YTick at 0xe035eb0>,
<matplotlib.axis.YTick at 0xe05b430>,
<matplotlib.axis.YTick at 0xe05b8b0>],
<a list of 5 Text yticklabel objects>)
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(3*x)/x
y2 = np.sin(2*x)/x
y3 = np.sin(x)/x
plt.plot(x,y,color=‘b‘)
plt.plot(x,y2,color=‘r‘)
plt.plot(x,y3,color=‘g‘)
plt.xticks([-2*np.pi, -np.pi, 0, np.pi, 2*np.pi],
[r‘$-2\pi$‘,r‘$-\pi$‘,r‘$0$‘,r‘$+\pi$‘,r‘$+2\pi$‘])
plt.yticks([-1,0,+1,+2,+3],
[r‘$-1$‘,r‘$0$‘,r‘$+1$‘,r‘$+2$‘,r‘$+3$‘])
ax = plt.gca()
ax.spines[‘right‘].set_color(‘none‘)
ax.spines[‘top‘].set_color(‘none‘)
ax.xaxis.set_ticks_position(‘bottom‘)
ax.spines[‘bottom‘].set_position((‘data‘,0))
ax.yaxis.set_ticks_position(‘left‘)
ax.spines[‘left‘].set_position((‘data‘,0))
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import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-2*np.pi,2*np.pi,0.01)
y = np.sin(3*x)/x
y2 = np.sin(2*x)/x
y3 = np.sin(x)/x
plt.plot(x,y,color=‘b‘)
plt.plot(x,y2,color=‘r‘)
plt.plot(x,y3,color=‘g‘)
plt.xticks([-2*np.pi, -np.pi, 0, np.pi, 2*np.pi],
[r‘$-2\pi$‘,r‘$-\pi$‘,r‘$0$‘,r‘$+\pi$‘,r‘$+2\pi$‘])
plt.yticks([-1,0,+1,+2,+3],
[r‘$-1$‘,r‘$0$‘,r‘$+1$‘,r‘$+2$‘,r‘$+3$‘])
plt.annotate(r‘$\lim_{x\to 0}\frac{\sin(x)}{x}= 1$‘, xy=[0,1],xycoords=‘data‘,
xytext=[30,30],fontsize=16,textcoords=‘offset points‘,arrowprops=dict(arrowstyle="->",
connectionstyle="arc3,rad=.2"))
ax = plt.gca()
ax.spines[‘right‘].set_color(‘none‘)
ax.spines[‘top‘].set_color(‘none‘)
ax.xaxis.set_ticks_position(‘bottom‘)
ax.spines[‘bottom‘].set_position((‘data‘,0))
ax.yaxis.set_ticks_position(‘left‘)
ax.spines[‘left‘].set_position((‘data‘,0))
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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
data = {‘series1‘:[1,3,4,3,5],
‘series2‘:[2,4,5,2,4],
‘series3‘:[3,2,3,1,3]}
df = pd.DataFrame(data)
x = np.arange(5)
plt.axis([0,5,0,7])
plt.plot(x,df)
plt.legend(data, loc=2)
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<matplotlib.legend.Legend at 0xf047270>
7.12 直方图 180
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import matplotlib.pyplot as plt
import numpy as np
pop = np.random.randint(0,100,100)
pop
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array([32, 29, 53, 8, 43, 91, 54, 31, 81, 54, 28, 56, 43, 39, 96, 44, 6,
71, 29, 26, 34, 41, 78, 45, 1, 22, 94, 89, 19, 6, 95, 3, 86, 10,
1, 54, 51, 5, 20, 18, 87, 12, 92, 50, 82, 3, 56, 23, 57, 92, 25,
2, 86, 32, 75, 13, 85, 90, 8, 77, 91, 5, 31, 34, 44, 67, 30, 15,
42, 63, 15, 38, 56, 83, 2, 18, 94, 49, 31, 47, 25, 5, 20, 70, 47,
65, 29, 44, 23, 35, 73, 96, 34, 27, 11, 70, 96, 21, 71, 69])
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n,bins,patches = plt.hist(pop,bins=20)
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7.13 条状图 181
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import matplotlib.pyplot as plt
index = [0,1,2,3,4]
values = [5,7,3,4,6]
plt.bar(index,values)
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<Container object of 5 artists>
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import numpy as np
index = np.arange(5)
values1 = [5,7,3,4,6]
plt.bar(index,values1)
plt.xticks(index+0.4,[‘A‘,‘B‘,‘C‘,‘D‘,‘E‘])
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([<matplotlib.axis.XTick at 0xf3246f0>,
<matplotlib.axis.XTick at 0xf261bd0>,
<matplotlib.axis.XTick at 0xf31c310>,
<matplotlib.axis.XTick at 0xf3423f0>,
<matplotlib.axis.XTick at 0xf342790>],
<a list of 5 Text xticklabel objects>)
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import numpy as np
index = np.arange(5)
values1 = [5,7,3,4,6]
std1 = [0.8,1,0.4,0.9,1.3]
plt.title(‘A Bar Chart‘)
plt.bar(index,values1,yerr=std1,error_kw={‘ecolor‘:‘0.1‘,
‘capsize‘:6},alpha=0.7,label=‘First‘)
plt.xticks(index+0.4,[‘A‘,‘B‘,‘C‘,‘D‘,‘E‘])
plt.legend(loc=2)
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<matplotlib.legend.Legend at 0xf389970>
7.13.1 水平条状图 183
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import matplotlib.pyplot as plt
import numpy as np
index = np.arange(5)
values1 = [5,7,3,4,6]
std1 = [0.8,1,0.4,0.9,1.3]
plt.title(‘A Horizontal Bar Chart‘)
plt.barh(index,values1,xerr=std1,error_kw={‘ecolor‘:‘0.1‘,‘capsize‘:6},alpha=0.7,
label=‘First‘)
plt.yticks(index+0.4,[‘A‘,‘B‘,‘C‘,‘D‘,‘E‘])
plt.legend(loc=5)
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<matplotlib.legend.Legend at 0xf3c9630>
7.13.2 多序列条状图 184
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import matplotlib.pyplot as plt
import numpy as np
index = np.arange(5)
values1 = [5,7,3,4,6]
values2 = [6,6,4,5,7]
values3 = [5,6,5,4,6]
bw = 0.3
plt.axis([0,5,0,8])
plt.title(‘A Multiseries Bar Chart‘,fontsize=20)
plt.bar(index,values1,bw,color=‘b‘)
plt.bar(index+bw,values2,bw,color=‘g‘)
plt.bar(index+2*bw,values3,bw,color=‘r‘)
plt.xticks(index+1.5*bw,[‘A‘,‘B‘,‘C‘,‘D‘,‘E‘])
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([<matplotlib.axis.XTick at 0xf39dcd0>,
<matplotlib.axis.XTick at 0xf39ded0>,
<matplotlib.axis.XTick at 0xf3ef4b0>,
<matplotlib.axis.XTick at 0xf42d230>,
<matplotlib.axis.XTick at 0xf42d5d0>],
<a list of 5 Text xticklabel objects>)
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import matplotlib.pyplot as plt
import numpy as np
index = np.arange(5)
values1 = [5,7,3,4,6]
values2 = [6,6,4,5,7]
values3 = [5,6,5,4,6]
bw = 0.3
plt.axis([0,8,0,5])
plt.title(‘A Multiseries Horizontal Bar Chart‘,fontsize=20)
plt.barh(index,values1,bw,color=‘b‘)
plt.barh(index+bw,values2,bw,color=‘g‘)
plt.barh(index+2*bw,values3,bw,color=‘r‘)
plt.yticks(index+0.4,[‘A‘,‘B‘,‘C‘,‘D‘,‘E‘])
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([<matplotlib.axis.YTick at 0xf43e810>,
<matplotlib.axis.YTick at 0xf43e0f0>,
<matplotlib.axis.YTick at 0xf44f330>,
<matplotlib.axis.YTick at 0xf473f50>,
<matplotlib.axis.YTick at 0xf47d310>],
<a list of 5 Text yticklabel objects>)
7.13.3 为pandas DataFrame生成多序列条状图 185
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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
data = {‘series1‘:[1,3,4,3,5],
‘series2‘:[2,4,5,2,4],
‘series3‘:[3,2,3,1,3]}
df = pd.DataFrame(data)
df.plot(kind=‘bar‘)
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<matplotlib.axes._subplots.AxesSubplot at 0xf3a3330>
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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
data = {‘series1‘:[1,3,4,3,5],
‘series2‘:[2,4,5,2,4],
‘series3‘:[3,2,3,1,3]}
df = pd.DataFrame(data)
df.plot(kind=‘barh‘)
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<matplotlib.axes._subplots.AxesSubplot at 0xf3bf030>
7.13.4 多序列堆积条状图 186
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import matplotlib.pyplot as plt
import numpy as np
series1 = np.array([3,4,5,3])
series2 = np.array([1,2,2,5])
series3 = np.array([2,3,3,4])
index = np.arange(4)
plt.axis([0,4,0,15])
plt.bar(index,series1,color=‘r‘)
plt.bar(index,series2,color=‘b‘,bottom=series1)
plt.bar(index,series3,color=‘g‘,bottom=(series2+series1))
plt.xticks(index+0.4,[‘Jan15‘,‘Feb15‘,‘Mar15‘,‘Apr15‘])
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([<matplotlib.axis.XTick at 0xf53e9f0>,
<matplotlib.axis.XTick at 0xf549250>,
<matplotlib.axis.XTick at 0xf53ef70>,
<matplotlib.axis.XTick at 0xf5790b0>],
<a list of 4 Text xticklabel objects>)
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import matplotlib.pyplot as plt
import numpy as np
index = np.arange(4)
series1 = np.array([3,4,5,3])
series2 = np.array([1,2,2,5])
series3 = np.array([2,3,3,4])
plt.axis([0,15,0,4])
plt.title(‘A Multiseries Horizontal Stacked Bar Chart‘)
plt.barh(index,series1,color=‘r‘)
plt.barh(index,series2,color=‘g‘,left=series1)
plt.barh(index,series3,color=‘b‘,left=(series1+series2))
plt.yticks(index+0.4,[‘Jan15‘,‘Feb15‘,‘Mar15‘,‘Apr15‘])
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([<matplotlib.axis.YTick at 0xf58b1d0>,
<matplotlib.axis.YTick at 0xf549ff0>,
<matplotlib.axis.YTick at 0xf58bcf0>,
<matplotlib.axis.YTick at 0xf5bf2b0>],
<a list of 4 Text yticklabel objects>)
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import matplotlib.pyplot as plt
import numpy as np
index = np.arange(4)
series1 = np.array([3,4,5,3])
series2 = np.array([1,2,2,5])
series3 = np.array([2,3,3,4])
plt.axis([0,15,0,4])
plt.title(‘A Multiseries Horizontal Stacked Bar Chart‘)
plt.barh(index,series1,color=‘w‘,hatch=‘xx‘)
plt.barh(index,series2,color=‘w‘,hatch=‘///‘, left=series1)
plt.barh(index,series3,color=‘w‘,hatch=‘\\\\\\‘,left=(series1+series2))
plt.yticks(index+0.4,[‘Jan15‘,‘Feb15‘,‘Mar15‘,‘Apr15‘])
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([<matplotlib.axis.YTick at 0xf5d0c10>,
<matplotlib.axis.YTick at 0xf5b6790>,
<matplotlib.axis.YTick at 0xf5dc170>,
<matplotlib.axis.YTick at 0xf6066b0>],
<a list of 4 Text yticklabel objects>)
7.13.5 为pandas DataFrame绘制堆积条状图 189
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import matplotlib.pyplot as plt
import pandas as pd
data = {‘series1‘:[1,3,4,3,5],
‘series2‘:[2,4,5,2,4],
‘series3‘:[3,2,3,1,3]}
df = pd.DataFrame(data)
df.plot(kind=‘bar‘, stacked=True)
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<matplotlib.axes._subplots.AxesSubplot at 0xf5e74f0>
7.13.6 其他条状图 190
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import matplotlib.pyplot as plt
x0 = np.arange(8)
y1 = np.array([1,3,4,6,4,3,2,1])
y2 = np.array([1,2,5,4,3,3,2,1])
plt.ylim(-7,7)
plt.bar(x0,y1,0.9,facecolor=‘r‘,edgecolor=‘w‘)
plt.bar(x0,-y2,0.9,facecolor=‘b‘,edgecolor=‘w‘)
plt.xticks(())
plt.grid(True)
for x, y in zip(x0, y1):
plt.text(x + 0.4, y + 0.05, ‘%d‘ % y, ha=‘center‘, va= ‘bottom‘)
for x, y in zip(x0, y2):
plt.text(x + 0.4, (-y) - 0.05, ‘%d‘ % y, ha=‘center‘, va= ‘top‘)
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7.14 饼图 190
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import matplotlib.pyplot as plt
labels = [‘Nokia‘,‘Samsung‘,‘Apple‘,‘Lumia‘]
values = [10,30,45,15]
colors = [‘yellow‘,‘green‘,‘red‘,‘blue‘]
plt.pie(values,labels=labels,colors=colors)
plt.axis(‘equal‘)
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(-1.11637372803214,
1.1007797090739162,
-1.1163737124158366,
1.1007797083302826)
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import matplotlib.pyplot as plt
labels = [‘Nokia‘,‘Samsung‘,‘Apple‘,‘Lumia‘]
values = [10,30,45,15]
colors = [‘yellow‘,‘green‘,‘red‘,‘blue‘]
explode = [0.3,0,0,0]
plt.title(‘A Pie Chart‘)
plt.pie(values,labels=labels,colors=colors,explode=explode,startangle=180)
plt.axis(‘equal‘)
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(-1.4003625034945653,
1.130639575385504,
-1.1007797083302826,
1.1163737124158366)
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import matplotlib.pyplot as plt
labels = [‘Nokia‘,‘Samsung‘,‘Apple‘,‘Lumia‘]
values = [10,30,45,15]
colors = [‘yellow‘,‘green‘,‘red‘,‘blue‘]
explode = [0.3,0,0,0]
plt.title(‘A Pie Chart‘)
plt.pie(values,labels=labels,colors=colors,explode=explode,
shadow=True,autopct=‘%1.1f%%‘,startangle=180)
plt.axis(‘equal‘)
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(-1.4003625034945653,
1.130639575385504,
-1.1007797083302826,
1.1163737124158366)
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import matplotlib.pyplot as plt
import pandas as pd
data = {‘series1‘:[1,3,4,3,5],
‘series2‘:[2,4,5,2,4],
‘series3‘:[3,2,3,1,3]}
df = pd.DataFrame(data)
df[‘series1‘].plot(kind=‘pie‘,figsize=(6,6))
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<matplotlib.axes._subplots.AxesSubplot at 0xf7d2ed0>
7.15 高级图表 193
7.15.1 等值线图 193
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import matplotlib.pyplot as plt
import numpy as np
dx = 0.01; dy = 0.01
x = np.arange(-2.0,2.0,dx)
y = np.arange(-2.0,2.0,dy)
X,Y = np.meshgrid(x,y)
def f(x,y):
return (1 - y**5 + x**5)*np.exp(-x**2-y**2)
C = plt.contour(X,Y,f(X,Y),8,colors=‘black‘)
plt.contourf(X,Y,f(X,Y),8)
plt.clabel(C, inline=1, fontsize=10)
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<a list of 16 text.Text objects>
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import matplotlib.pyplot as plt
import numpy as np
dx = 0.01; dy = 0.01
x = np.arange(-2.0,2.0,dx)
y = np.arange(-2.0,2.0,dy)
X,Y = np.meshgrid(x,y)
C = plt.contour(X,Y,f(X,Y),8,colors=‘black‘)
plt.contourf(X,Y,f(X,Y),8,cmap=plt.cm.hot)
plt.clabel(C, inline=1, fontsize=10)
plt.colorbar()
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<matplotlib.colorbar.Colorbar at 0x1100f0b0>
7.15.2 极区图 195
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import matplotlib.pyplot as plt
import numpy as np
N = 8
theta = np.arange(0.,2 * np.pi, 2 * np.pi / N)
radii = np.array([4,7,5,3,1,5,6,7])
plt.axes([0.025, 0.025, 0.95, 0.95], polar=True)
colors = np.array([‘#4bb2c5‘, ‘#c5b47f‘, ‘#EAA228‘, ‘#579575‘, ‘#839557‘, ‘#958c12‘,
‘#953579‘, ‘#4b5de4‘])
bars = plt.bar(theta, radii, width=(2*np.pi/N), bottom=0.0, color=colors)
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import matplotlib.pyplot as plt
import numpy as np
N = 8
theta = np.arange(0.,2 * np.pi, 2 * np.pi / N)
radii = np.array([4,7,5,3,1,5,6,7])
plt.axes([0.025, 0.025, 0.95, 0.95], polar=True)
colors = np.array([‘lightgreen‘, ‘darkred‘, ‘navy‘, ‘brown‘, ‘violet‘, ‘plum‘,
‘yellow‘, ‘darkgreen‘])
bars = plt.bar(theta, radii, width=(2*np.pi/N), bottom=0.0, color=colors)
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7.16 mplot3d 197
7.16.1 3D曲面 197
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from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-2,2,0.1)
Y = np.arange(-2,2,0.1)
X,Y = np.meshgrid(X,Y)
def f(x,y):
return (1 - y**5 + x**5)*np.exp(-x**2-y**2)
ax.plot_surface(X,Y,f(X,Y), rstride=1, cstride=1)
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<mpl_toolkits.mplot3d.art3d.Poly3DCollection at 0x11eade50>
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from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-2,2,0.1)
Y = np.arange(-2,2,0.1)
X,Y = np.meshgrid(X,Y)
def f(x,y):
return (1 - y**5 + x**5)*np.exp(-x**2-y**2)
ax.plot_surface(X,Y,f(X,Y), rstride=1, cstride=1, cmap=plt.cm.hot)
ax.view_init(elev=30,azim=125)
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7.16.2 3D散点图 198
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import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
xs = np.random.randint(30,40,100)
ys = np.random.randint(20,30,100)
zs = np.random.randint(10,20,100)
xs2 = np.random.randint(50,60,100)
ys2 = np.random.randint(30,40,100)
zs2 = np.random.randint(50,70,100)
xs3 = np.random.randint(10,30,100)
ys3 = np.random.randint(40,50,100)
zs3 = np.random.randint(40,50,100)
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(xs,ys,zs)
ax.scatter(xs2,ys2,zs2,c=‘r‘,marker=‘^‘)
ax.scatter(xs3,ys3,zs3,c=‘g‘,marker=‘*‘)
ax.set_xlabel(‘X Label‘)
ax.set_ylabel(‘Y Label‘)
ax.set_zlabel(‘Z Label‘)
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Text(0.5,0,‘Z Label‘)
7.16.3 3D条状图 199
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import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
x = np.arange(8)
y = np.random.randint(0,10,8)
y2 = y + np.random.randint(0,3,8)
y3 = y2 + np.random.randint(0,3,8)
y4 = y3 + np.random.randint(0,3,8)
y5 = y4 + np.random.randint(0,3,8)
clr = [‘#4bb2c5‘, ‘#c5b47f‘, ‘#EAA228‘, ‘#579575‘, ‘#839557‘, ‘#958c12‘, ‘#953579‘,
‘#4b5de4‘]
fig = plt.figure()
ax = Axes3D(fig)
ax.bar(x,y,0,zdir=‘y‘,color=clr)
ax.bar(x,y2,10,zdir=‘y‘,color=clr)
ax.bar(x,y3,20,zdir=‘y‘,color=clr)
ax.bar(x,y4,30,zdir=‘y‘,color=clr)
ax.bar(x,y5,40,zdir=‘y‘,color=clr)
ax.set_xlabel(‘X Axis‘)
ax.set_ylabel(‘Y Axis‘)
ax.set_zlabel(‘Z Axis‘)
ax.view_init(elev=40)
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7.17 多面板图形 200
7.17.1 在其他子图中显示子图 200
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import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
inner_ax = fig.add_axes([0.6,0.6,0.25,0.25])
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import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
inner_ax = fig.add_axes([0.6,0.6,0.25,0.25])
x1 = np.arange(10)
y1 = np.array([1,2,7,1,5,2,4,2,3,1])
x2 = np.arange(10)
y2 = np.array([1,3,4,5,4,5,2,6,4,3])
ax.plot(x1,y1)
inner_ax.plot(x2,y2)
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[<matplotlib.lines.Line2D at 0x12144fd0>]
7.17.2 子图网格 202
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import matplotlib.pyplot as plt
gs = plt.GridSpec(3,3)
fig = plt.figure(figsize=(6,6))
fig.add_subplot(gs[1,:2])
fig.add_subplot(gs[0,:2])
fig.add_subplot(gs[2,0])
fig.add_subplot(gs[:2,2])
fig.add_subplot(gs[2,1:])
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<matplotlib.axes._subplots.AxesSubplot at 0x12177a70>
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import matplotlib.pyplot as plt
import numpy as np
gs = plt.GridSpec(3,3)
fig = plt.figure(figsize=(6,6))
x1 = np.array([1,3,2,5])
y1 = np.array([4,3,7,2])
x2 = np.arange(5)
y2 = np.array([3,2,4,6,4])
s1 = fig.add_subplot(gs[1,:2])
s1.plot(x,y,‘r‘)
s2 = fig.add_subplot(gs[0,:2])
s2.bar(x2,y2)
s3 = fig.add_subplot(gs[2,0])
s3.barh(x2,y2,color=‘g‘)
s4 = fig.add_subplot(gs[:2,2])
s4.plot(x2,y2,‘k‘)
s5 = fig.add_subplot(gs[2,1:])
s5.plot(x1,y1,‘b^‘,x2,y2,‘yo‘)
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[<matplotlib.lines.Line2D at 0x1238a410>,
<matplotlib.lines.Line2D at 0x1238a4d0>]
7.18 小结 204
python数据分析实战-第7章-用matplotlib实现数据可视化
标签：val red 1.4 数据可视化 简单的 2.0 x11 params lis
原文地址：https://www.cnblogs.com/LearnFromNow/p/9349930.html
