在matplotlib中排除日期范围

Question

因此，我使用修改过的教程，使用matplotlib绘制了大约5k的时间日期。我想删除所有年份的year-01和year-07之间的范围，以使数据更有趣。

这是我的代码：

import matplotlib.pyplot as plt 

def plotTimes(data):
    x = data["x"]
    y = data["y"]
    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.grid()

    plt.plot(x,y)
    plt.xlabel('Date')
    plt.ylabel('5k Time')
    plt.title(data['name'])
    plt.show()

• 如何从情节中排除日期范围？
• （附带问题）pyplot是使用matplotlib的最佳方法吗？

所有代码： https://pastebin.com/raw/MQVa5QLZ

这是数据：

{'x': [datetime.datetime(2015, 8, 28, 0, 0), datetime.datetime(2015, 
9, 3, 0, 0), datetime.datetime(2015, 9, 10, 0, 0), datetime.datetime(2015, 9, 12, 0, 0), datetime.datetime(2015, 9, 17, 0, 0), datetime.datetime(2015, 9, 26, 0, 0), datetime.datetime(2015, 9, 29, 0,
 0), datetime.datetime(2015, 10, 3, 0, 0), datetime.datetime(2015, 10, 16,
 0, 0), datetime.datetime(2015, 10, 22, 0, 0), datetime.datetime(2015, 10,
 23, 0, 0), datetime.datetime(2015, 10, 27, 0, 0), datetime.datetime(2015,
 10, 30, 0, 0), datetime.datetime(2015, 11, 4, 0, 0), 
datetime.datetime(2016, 8, 26, 0, 0), datetime.datetime(2016, 9, 1, 0, 0),
 datetime.datetime(2016, 9, 10, 0, 0), datetime.datetime(2016, 9, 13, 0, 
0), datetime.datetime(2016, 9, 15, 0, 0), datetime.datetime(2016, 9, 24, 0, 0), datetime.datetime(2016, 9, 27, 0, 0), datetime.datetime(2016, 10, 
14, 0, 0), datetime.datetime(2016, 10, 20, 0, 0), datetime.datetime(2016, 
10, 21, 0, 0), datetime.datetime(2016, 10, 25, 0, 0), datetime.datetime(2016, 10, 29, 0, 0), datetime.datetime(2016, 11, 2, 0,
 0), datetime.datetime(2017, 8, 25, 0, 0), datetime.datetime(2017, 9, 9, 
0, 0), datetime.datetime(2017, 9, 12, 0, 0), datetime.datetime(2017, 9, 
14, 0, 0), datetime.datetime(2017, 9, 23, 0, 0), datetime.datetime(2017,
 9, 27, 0, 0), datetime.datetime(2017, 10, 7, 0, 0), 
datetime.datetime(2017, 10, 28, 0, 0), datetime.datetime(2017, 11, 1, 0, 
0)], 'y': [datetime.datetime(1900, 1, 1, 0, 20, 4, 100000), 
datetime.datetime(1900, 1, 1, 0, 19, 59, 700000), datetime.datetime(1900, 1, 1, 0, 18, 48, 100000), datetime.datetime(1900, 1, 1, 0, 18, 26),
 datetime.datetime(1900, 1, 1, 0, 18, 49, 600000), datetime.datetime(1900,
 1, 1, 0, 17, 57), datetime.datetime(1900, 1, 1, 0, 18, 28, 200000), 
datetime.datetime(1900, 1, 1, 0, 17, 34, 800000), datetime.datetime(1900,
 1, 1, 0, 17, 46), datetime.datetime(1900, 1, 1, 0, 17, 57, 700000), 
datetime.datetime(1900, 1, 1, 0, 17, 43, 200000), datetime.datetime(1900,
 1, 1, 0, 17, 54, 700000), datetime.datetime(1900, 1, 1, 0, 17, 40, 
700000), datetime.datetime(1900, 1, 1, 0, 17, 55, 600000), 
datetime.datetime(1900, 1, 1, 0, 18, 29, 200000), datetime.datetime(1900,
 1, 1, 0, 17, 43, 300000), datetime.datetime(1900, 1, 1, 0, 17, 51), 
datetime.datetime(1900, 1, 1, 0, 18, 12, 500000), datetime.datetime(1900,
 1, 1, 0, 17, 30, 100000), datetime.datetime(1900, 1, 1, 0, 17, 9, 
800000), datetime.datetime(1900, 1, 1, 0, 17, 58), datetime.datetime(1900,
 1, 1, 0, 17, 16, 800000), datetime.datetime(1900, 1, 1, 0, 17, 43, 
600000), datetime.datetime(1900, 1, 1, 0, 17, 12, 400000), 
datetime.datetime(1900, 1, 1, 0, 17, 31, 600000), datetime.datetime(1900,
 1, 1, 0, 17, 36, 700000), datetime.datetime(1900, 1, 1, 0, 17, 13, 
900000), datetime.datetime(1900, 1, 1, 0, 17, 17,
700000), datetime.datetime(1900, 1, 1, 0, 16, 42), datetime.datetime(1900, 1, 1, 0,
     16, 56, 200000), datetime.datetime(1900, 1, 1, 0, 17, 11, 700000),
 datetime.datetime(1900, 1, 1, 0, 16, 51, 900000),
 datetime.datetime(1900, 1, 1, 0, 17, 15, 200000), datetime.datetime(1900, 1, 1, 0, 17, 9, 
700000),
 datetime.datetime(1900, 1, 1, 0, 16, 55, 600000), 
datetime.datetime(1900, 1, 1, 0, 17, 2, 400000)], 'name': 'Jack Santinga'}