使用Python生成“The Economist”风格的图表

Question

使用python和marplotlib和类似seaborn的工具，我想创建一个类似《经济学人》的图表（因为我认为这种风格很棒）

这是一个时间序列图，我想重现的关键是水平网格线，标签与带有刻度线的下横轴相匹配。网格线两端的不同颜色的标签将是一个额外的奖励，相应的标题（左对齐和右对齐）。注释将是双倍的奖励。在

我试着用seaborn做类似的东西，但没能走到第一步。在

Answer 1

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')