两个条形图合二为一

Question

我有两个关于推文情绪的工作条形图（中性、积极、消极）。如何将它们并排合并为一个？

第一小节：

plt.figure(figsize=(6,5))
plt.title('Classification of All tweets into sentiment categories',fontsize=15)
plt.ylabel('Percentage [%]',fontsize=18)
ax = (df_navalny.sentiment.value_counts()/len(df_navalny)*100).plot(kind="bar", rot=0,color=['#04407F','#0656AC','#0A73E1'])
ax.set_yticks(np.arange(0, 110, 10))
plt.grid(color='#95a5a6', linestyle='-.', linewidth=1, axis='y', alpha=0.7)
ax2 = ax.twinx()
ax2.set_yticks(np.arange(0, 110, 10)*len(df_navalny)/100)
for p in ax.patches:
    ax.annotate('{:.2f}%'.format(p.get_height()), (p.get_x()+0.15, p.get_height()+1)) 

第二栏：

plt.figure(figsize=(6,5))
plt.title('Classification of All tweets into sentiment categories',fontsize=15)
plt.ylabel('Percentage [%]',fontsize=18)
ax = (df_putin.sentiment.value_counts()/len(df_putin)*100).plot(kind="bar", rot=0,color=['#04407F','#0656AC','#0A73E1'])
ax.set_yticks(np.arange(0, 110, 10))
plt.grid(color='#95a5a6', linestyle='-.', linewidth=1, axis='y', alpha=0.7)
ax2 = ax.twinx()
ax2.set_yticks(np.arange(0, 110, 10)*len(df_putin)/100)
for p in ax.patches:
    ax.annotate('{:.2f}%'.format(p.get_height()), (p.get_x()+0.15, p.get_height()+1))

Answer 1

这有点复杂，但 Matplotlib 网站提供了一个 demo，当你复制并过去时，你会得到以下内容

这是代码

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot
from mpl_toolkits import axisartist

# fake data
a = [2341, 5670, 4822]
b = [4290, 5205, 3966]
pca, pcb = [[round(100*x/sum(l),2) for x in l] for l in (a, b)]

# prepare all the vertical axes
ax = host_subplot(111, axes_class=axisartist.Axes)
plt.subplots_adjust(right=0.67)
axa = ax.twinx() ; axb = ax.twinx()
axb.axis['right'] = axb.new_fixed_axis(loc="right", offset=(60, 0))
axa.axis['right'].toggle(all=True)
axb.axis['right'].toggle(all=True)

# plot the bars PLUS invisible lines to represent the samples numerosities
x, w = np.array((1,2,3)), 0.30
ax.bar(x-w, pca, width=w, align='edge', label='a', zorder=1)
ax.bar(x-0, pcb, width=w, align='edge', label='b', zorder=1)
axa.plot((1,1),(0,sum(a)),lw=0)
axb.plot((1,1),(0,sum(b)),lw=0)

# fix xtics, xlabels, 'regular' yticks
plt.xticks((1,2,3)) ; ax.set_xticklabels('NO == YES'.split())
ax.set_yticks(range(0, 101, 10))

# all the ylabels
ax.set_ylabel('Percentages')
axa.set_ylabel('Numerosity of a')
axb.set_ylabel('Numerosity of b')
axa.set_ylim(bottom=0.0)
axb.set_ylim(bottom=0.0)
plt.legend()
plt.grid(zorder=0)
plt.show()