金融学图表 matplotlib.finance

quant001

1.烛柱图 candlestick

1. #!/etc/bin/python
   
2. #coding=utf-8
   
3. import matplotlib.pyplot as plt
   
4. import matplotlib.finance as mpf
   
5. start = (2014, 5,1)
   
6. end = (2014, 7,1)
   
7. quotes = mpf.quotes_historical_yahoo('^GDAXI',start,end)
   
8. # print quotes[:2]
   
9. 
   
10. fig, ax = plt.subplots(figsize=(8,5))
    
11. fig.subplots_adjust(bottom = 0.2)
    
12. mpf.candlestick(ax, quotes, width=0.6, colorup='b',colordown='r')
    
13. plt.grid(True)
    
14. ax.xaxis_date() #x轴上的日期
    
15. ax.autoscale_view()
    
16. plt.setp(plt.gca().get_xticklabels(),rotation=30) #日期倾斜
    
17. plt.show()

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2. plot_day_summary

该函数提供了一个相当类似的图标类型,使用方法和 candlestick 函数相同,使用类似的参数. 这里开盘价和收盘价不是由彩色矩形表示,而是由两条短水平线表示.

1. #!/etc/bin/python
   
2. #coding=utf-8
   
3. import matplotlib.pyplot as plt
   
4. import matplotlib.finance as mpf
   
5. start = (2014, 5,1)
   
6. end = (2014, 7,1)
   
7. quotes = mpf.quotes_historical_yahoo('^GDAXI',start,end)
   
8. # print quotes[:2]
   
9. 
   
10. fig, ax = plt.subplots(figsize=(8,5))
    
11. fig.subplots_adjust(bottom = 0.2)
    
12. mpf.plot_day_summary(ax, quotes,  colorup='b',colordown='r')
    
13. plt.grid(True)
    
14. ax.xaxis_date() #x轴上的日期
    
15. ax.autoscale_view()
    
16. plt.setp(plt.gca().get_xticklabels(),rotation=30) #日期倾斜
    
17. plt.show()

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3.股价数据和成交量

1. #!/etc/bin/python
   
2. #coding=utf-8
   
3. import matplotlib.pyplot as plt
   
4. import numpy as np
   
5. import matplotlib.finance as mpf
   
6. start = (2014, 5,1)
   
7. end = (2014, 7,1)
   
8. quotes = mpf.quotes_historical_yahoo('^GDAXI',start,end)
   
9. # print quotes[:2]
   
10. 
    
11. quotes = np.array(quotes)
    
12. fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(8,6))
    
13. mpf.candlestick(ax1, quotes, width=0.6,colorup='b',colordown='r')
    
14. ax1.set_title('Yahoo Inc.')
    
15. ax1.set_ylabel('index level')
    
16. ax1.grid(True)
    
17. ax1.xaxis_date()
    
18. plt.bar(quotes[:,0] - 0.25, quotes[:, 5], width=0.5)
    
19. 
    
20. ax2.set_ylabel('volume')
    
21. ax2.grid(True)
    
22. ax2.autoscale_view()
    
23. plt.setp(plt.gca().get_xticklabels(),rotation=30)
    
24. plt.show()

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3.3D 绘图

1. #!/etc/bin/python
   
2. #coding=utf-8
   
3. import numpy as np
   
4. import matplotlib.pyplot as plt
   
5. 
   
6. stike = np.linspace(50, 150, 24)
   
7. ttm = np.linspace(0.5, 2.5, 24)
   
8. stike, ttm = np.meshgrid(stike, ttm)
   
9. print  stike[:2]
   
10. 
    
11. iv = (stike - 100) ** 2 / (100 * stike) /ttm
    
12. from mpl_toolkits.mplot3d import Axes3D
    
13. fig = plt.figure(figsize=(9,6))
    
14. ax = fig.gca(projection='3d')
    
15. surf = ax.plot_surface(stike, ttm, iv, rstride=2, cstride=2, cmap=plt.cm.coolwarm, linewidth=0.5, antialiased=True)
    
16. ax.set_xlabel('strike')
    
17. ax.set_ylabel('time-to-maturity')
    
18. ax.set_zlabel('implied volatility')
    
19. 
    
20. plt.show()
    

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