Python Matplotlib:将一个大图拆分成几个 Sub-Graphs(子图)

Python Matplotlib: Splitting one Large Graph into several Sub-Graphs (Subplot)

简单地说,假设我有 2 个列表:
A -> 有名称列表 ['A','B','C','D','E','F', 'G','H']
B -> 具有值列表 [5,7,3,8,2,9,1,3]
A 将是 X-Axis 标签的名称,B 中的相应值将是图形的高度(即 Y-Axis )。

%matplotlib inline
import pandas as pd
from matplotlib import rcParams
import matplotlib.pyplot as plt
from operator import itemgetter

rcParams.update({'figure.autolayout': True})
plt.figure(figsize=(14,9), dpi=600)

reso_names = ['A','B','C','D','E','F','G','H']
reso_values = [5,7,3,8,2,9,1,3]
plt.bar(range(len(reso_values)), reso_values, align='center')
plt.xticks(range(len(reso_names)), list(reso_names), rotation='vertical')

plt.margins(0.075)
plt.xlabel('X-Axis')
plt.ylabel('Y-Axis')
plt.title('Graph', {'family' : 'Arial Black',
        'weight' : 'bold',
        'size'   : 22})
plt.show()

此代码给出以下输出:

但是我希望它为每 2 个值创建子图。在这种情况下应该有 4 个子图:

这种拆分应该是动态完成的(不是 4 个不同的循环,它应该根据输入的大小将图形分成 2 个单元,如果列表 A 有 10 个值,那么它应该给出 5 个子图)。



我想出了如何将图形分成两半,但我需要使用每个图形 N 的步骤来实现它(本例中的 N 为 2)。
我将图分成 2 个相等子图的代码是:

%matplotlib inline
import pandas as pd
from matplotlib import rcParams
import matplotlib.pyplot as plt
from operator import itemgetter

rcParams.update({'figure.autolayout': True})
plt.figure(figsize=(14,9), dpi=600)

reso_names = ['A','B','C','D','E','F','G','H']
reso_values = [5,7,3,8,2,9,1,3]

fig, axs = plt.subplots(nrows=2, sharey=True, figsize=(14,18), dpi=50)
size = int(len(reso_values))
half = int( size/2 )

fig.suptitle('Graph', 
          **{'family': 'Arial Black', 'size': 22, 'weight': 'bold'})

for ax, start, end in zip(axs, (0, half), (half, size)):
    names, values = list(reso_names[start:end]), reso_values[start:end]
    ax.bar(range(len(values)), values, align='center')
    ax.set_xlabel('X-Axis')
    ax.set_ylabel('Y-Axis')
    ax.set_xticks(range(len(names)))
    ax.set_xticklabels(names, rotation='vertical')
    ax.set_xlim(0, len(names))
fig.subplots_adjust(bottom=0.05, top=0.95)
plt.show()


这给了我:


我只是想让程序根据拆分数N将图动态拆分成子图。

您可以使用以下代码将包含 size 个元素的列表 values/names 直接拆分为包含 N 个元素的 size//N + 1 个列表:

N=3
sublists_names = [reso_names[x:x+N] for x in range(0, len(reso_names), N)]
sublists_values = [reso_values[x:x+N] for x in range(0, len(reso_values), N)]

注意,如果N不分大小,最后一个子列表的元素会少

然后您只需执行压缩并在不同的图表中绘制每个子列表:

import pandas as pd
from matplotlib import rcParams
import matplotlib.pyplot as plt
from operator import itemgetter

rcParams.update({'figure.autolayout': True})
plt.figure(figsize=(14,9), dpi=600)

reso_names = ['A','B','C','D','E','F','G','H']
reso_values = [5,7,3,8,2,9,1,3]

N=3
sublists_names = [reso_names[x:x+N] for x in range(0, len(reso_names), N)]
sublists_values = [reso_values[x:x+N] for x in range(0, len(reso_values), N)]

size = int(len(reso_values))
fig, axs = plt.subplots(nrows=size//N+1, sharey=True, figsize=(14,18), dpi=50)

fig.suptitle('Graph', 
          **{'family': 'Arial Black', 'size': 22, 'weight': 'bold'})

for ax, names, values in zip(axs, sublists_names, sublists_values):
    ax.bar(range(len(values)), values, align='center')
    ax.set_xlabel('X-Axis')
    ax.set_ylabel('Y-Axis')
    ax.set_xticks(range(len(names)))
    ax.set_xticklabels(names, rotation='vertical')
    ax.set_xlim(0, len(names))
    #ax.set_xlim(0, N)

fig.subplots_adjust(bottom=0.05, top=0.95)
plt.show()

如果列表不能被 N 整除,您可以取消注释最后注释的行,以便条形图在最后一个子图上保持对齐:(ax.set_xlim(0, N)):