并不完美(我没有很长时间使用它)，但是为了让您了解按照您想要的方式定制绘图所需使用的Matplotlib方法，下面有一些代码。在

请注意，要像这样微调绘图，很难将内容和显示分开(您可能需要手动设置刻度标签等，因此如果更改数据，它将不会自动工作)。《经济学人》的绘图人员显然这样做是因为他们似乎把左上角的勾号标签弄错了(280应该是260)。在# -*- coding: utf-8 -*-

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.dates as mdates

import matplotlib.ticker as ticker

from datetime import datetime

# Load in some sample data

bond_yields = np.loadtxt('bond_yields.txt',

converters={0: mdates.strpdate2num('%Y-%m-%d')},

dtype = {'names': ('date', 'bond_yield'),

'formats': (datetime, float)})

bank_deposits = np.loadtxt('bank_deposits.txt',

converters={0: mdates.strpdate2num('%Y-%m-%d')},

dtype = {'names': ('date', 'bank_deposits'),

'formats': (datetime, float)})

# Bond yields line is in light blue, bank deposits line in dark red:

bond_yield_color = (0.424, 0.153, 0.090)

bank_deposits_color = (0.255, 0.627, 0.843)

# Set up a figure, and twin the x-axis so we can have two different y-axes

fig = plt.figure(figsize=(8, 4), frameon=False, facecolor='white')

ax1 = fig.add_subplot(111)

ax2 = ax1.twinx()

# Make sure the gridlines don't end up on top of the plotted data

ax1.set_axisbelow(True)

ax2.set_axisbelow(True)

# The light gray, horizontal gridlines

ax1.yaxis.grid(True, color='0.65', ls='-', lw=1.5, zorder=0)

# Plot the data

l1, = ax1.plot(bank_deposits['date'], bank_deposits['bank_deposits'],

c=bank_deposits_color, lw=3.5)

l2, = ax2.plot(bond_yields['date'], bond_yields['bond_yield'],

c=bond_yield_color, lw=3.5)

# Set the y-tick ranges: chosen so that ax2 labels will match the ax1 gridlines

ax1.set_yticks(range(120,280,20))

ax2.set_yticks(range(0, 40, 5))

# Turn off spines left, top, bottom and right (do it twice because of the twinning)

ax1.spines['left'].set_visible(False)

ax1.spines['right'].set_visible(False)

ax1.spines['top'].set_visible(False)

ax2.spines['left'].set_visible(False)

ax2.spines['right'].set_visible(False)

ax2.spines['top'].set_visible(False)

ax1.spines['bottom'].set_visible(False)

ax2.spines['bottom'].set_visible(False)

# We do want ticks on the bottom x-axis only

ax1.xaxis.set_ticks_position('bottom')

ax2.xaxis.set_ticks_position('bottom')

# Remove ticks from the y-axes

ax1.tick_params(axis='y', length=0)

ax2.tick_params(axis='y', length=0)

# Set tick-labels for the two y-axes in the appropriate colors

for tick_label in ax1.yaxis.get_ticklabels():

tick_label.set_fontsize(12)

tick_label.set_color(bank_deposits_color)

for tick_label in ax2.yaxis.get_ticklabels():

tick_label.set_fontsize(12)

tick_label.set_color(bond_yield_color)

# Set the x-axis tick marks to two-digit years

ax1.xaxis.set_major_locator(mdates.YearLocator())

ax1.xaxis.set_major_formatter(mdates.DateFormatter('%y'))

# Tweak the x-axis tick label sizes

for tick in ax1.xaxis.get_major_ticks():

tick.label.set_fontsize(12)

tick.label.set_horizontalalignment('center')

# Lengthen the bottom x-ticks and set them to dark gray

ax1.tick_params(direction='in', axis='x', length=7, color='0.1')

# Add the line legends as annotations

ax1.annotate(u'private-sector bank deposits, €bn', xy=(0.09, 0.95),

xycoords='figure fraction', size=12, color=bank_deposits_color,

fontstyle='italic')

ax2.annotate(u'ten-year government bond yield, %', xy=(0.6, 0.95),

xycoords='figure fraction', size=12, color=bond_yield_color,

fontstyle='italic')

# Add an annotation at the date of the first bail-out. relpos=(0,0) ensures

# that the label lines up on the right of a vertical line

first_bailout_date = datetime.strptime('2010-05-02', '%Y-%m-%d')

xpos = mdates.date2num(first_bailout_date)

ax1.annotate(u'FIRST BAIL-OUT', xy=(xpos, 120), xytext=(xpos, 250), color='r',

arrowprops=dict(arrowstyle='-', edgecolor='r', ls='dashed',

relpos=(0,0)), fontsize=9, fontstyle='italic')

fig.savefig('fig.png', facecolor=fig.get_facecolor(), edgecolor='none')