Python 绘制 matplotlib 子图时删除 for 循环

我使用matplotlib在python中生成了一个基于子图的大图.该图总共有500多个单独的图，每个图有for0个数据点.这可以使用基于for个循环的方法绘制，该方法以下面给出的最小示例为模型

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec

# define main plot names and subplot names
mains = ['A','B','C','D']
subs = list(range(9))

# generate mimic data in pd dataframe
col = [letter+str(number) for letter in mains for number in subs]
col.insert(0,'Time')

df = pd.DataFrame(columns=col)

for title in df.columns:
    df[title] = [i for i in range(100)]

# although alphabet and mains are the same in this minimal example this may not always be true
alphabet = ['A', 'B', 'C', 'D']
column_names = [column for column in df.columns if column != 'Time']

# define figure size and main gridshape
fig = plt.figure(figsize=(15, 15))
outer = gridspec.GridSpec(2, 2, wspace=0.2, hspace=0.2)

for i, letter in enumerate(alphabet):
    # define inner grid size and shape
    inner = gridspec.GridSpecFromSubplotSpec(3, 3,
                    subplot_spec=outer[i], wspace=0.1, hspace=0.1)

    # select only columns with correct letter
    plot_array = [col for col in column_names if col.startswith(letter)]      
        
    # set title for each letter plot
    ax = plt.Subplot(fig, outer[i])
    ax.set_title(f'Letter {letter}')
    ax.axis('off')
    fig.add_subplot(ax)
    
    # create each subplot
    for j, col in enumerate(plot_array):
        ax = plt.Subplot(fig, inner[j])   
        
        X = df['Time']
        Y = df[col]
    
        # plot waveform
        ax.plot(X, Y)

        # hide all axis ticks
        ax.axis('off')
        
        # set y_axis limits so all plots share same y_axis  
        ax.set_ylim(df[column_names].min().min(),df[column_names].max().max())
        
        fig.add_subplot(ax)  

然而，这很慢，需要几分钟来绘制图形.是否有更有效的方法(可能没有for个循环)来实现相同的结果