您可以使用numpy数组，并在您想要的范围内（在本例中为一年）使用掩码。为了使用示例中的内置YearLocator函数，您需要首先绘制图表并设置刻度，然后从示例中删除并替换为每年的范围。

import matplotlib.pyplot as plt
from matplotlib.finance import quotes_historical_yahoo_ochl
from matplotlib.dates import YearLocator, MonthLocator, DateFormatter
import datetime
import numpy 

date1 = datetime.date(1995, 1, 1)
date2 = datetime.date(2004, 4, 12)

years = YearLocator()   # every year
months = MonthLocator()  # every month
yearsFmt = DateFormatter('%Y')

quotes = quotes_historical_yahoo_ochl('INTC', date1, date2)
if len(quotes) == 0:
    raise SystemExit

dates = np.array([q[0] for q in quotes])
opens = np.array([q[1] for q in quotes])

fig, ax = plt.subplots()
l = ax.plot_date(dates, opens, '-')

# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
ax.autoscale_view()

l[0].remove()
py = years()[0]
for year in years()[1:]:
    mask = (py < dates) & (dates < year)
    ax.plot_date(dates[mask], opens[mask], '-')
    py = year

# format the coords message box
def price(x):
   return '$%1.2f' % x
ax.fmt_xdata = DateFormatter('%Y-%m-%d')
ax.fmt_ydata = price
ax.grid(True)

fig.autofmt_xdate()
plt.show()

其给出，

我通常使用的方法是使用for循环绘制数据的不同部分，并在绘制时对每个部分进行着色。在您的示例中，此部分：

fig, ax = plt.subplots()
ax.plot_date(dates, opens, '-')

变成：

# import the colormaps
from maplotlib import cm

fig, ax = plt.subplots()

for y in years:
    y_indices = [i for i in range(len(dates)) if dates[i].year==y]

    # subset the data, there are better ways to do this
    sub_dates = [dates[i] for i in y_indices]
    sub_opens = [opens[i] for i in y_indices]

    # plot each section of data, using a colormap to change the color for
    # each iteration.
    ax.plot_date(sub_dates, sub_opens, '-', linecolor=cm.spring((y-2000)/10.0)