Adding timestamp on the top of the plot using Matplotlib

Is there a way to add timestamp t=0 on the top of the plot at the specific location as shown in the expected output? In general, does Python have a time counter which appears on every frame and is split according to the number of frames? I present the current and expected outputs.

import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from matplotlib.colors import Normalize
from matplotlib import cm
import math
from  numpy import nan

fig,aPe = plt.subplots(1)
n=3
arMax=[]
arMin=[]

N=2*n*(n-1)

J = np.array([[]])

Pe=np.array([[394.20560747663563, 408.7929050665396 , 419.132709901089  ,
        398.95097406721044, 403.81198021076113, 430.00914784982064,
        424.50127213826016, 453.54817733128607, 441.4651085668709 ,
        447.42507960635163, 413.8982415602072 , 390.3025816600353 ]])
            

C1 = nan
for i in J[0]:
    Pe = np.insert(Pe, i, [C1], axis=1)
print("Pe =", [Pe])

for i in range(0,len(Pe)):
    Max=max(max(Pe[i]), max(Pe[i]))
    Min=min(min(Pe[i]), min(Pe[i]))
    
    arMax.append(Max)
    Max=np.array(arMax)
    
    arMin.append(Min)
    Min=np.array(arMin)

a=min(Min)
b=max(Max)

print("a =",a)
print("b =",b)


Amax= math.ceil(b)
Amin= math.floor(a)
print(Amax, Amin)

color = cm.get_cmap('Dark2')
norm = Normalize(vmin=Amin, vmax=Amax)
color_list = []
for i in range(len(Pe[0])):   
    color_list.append(color(((Pe[0,i])-Amin)/(Amax-Amin)))
    
id = 0
for j in range(0, n):
    for k in range(n-1):
        aPe.hlines(200+200*(n-j-1)+5*n, 200*(k+1)+5*n, 200*(k+2)+5*n, zorder=0, colors=color_list[id])
        id += 1

    for i in range(0, n):
        rect = mpl.patches.Rectangle((200+200*i, 200+200*j), 10*n, 10*n, linewidth=1, edgecolor='black', facecolor='black')
        aPe.add_patch(rect)
        if j < n-1:
            aPe.vlines(200+200*i+5*n, 200*(n-1-j)+5*n, 200*(n-j)+5*n, zorder=0, colors=color_list[id])
            id += 1

cb = fig.colorbar(cm.ScalarMappable(cmap=color, norm=norm), ticks=np.arange(Amin, Amax+len(color.colors), len(color.colors)))
cb.set_ticks(np.arange(Amin, Amax+1, (Amax-Amin)/8).astype(np.int64))
cb.set_label("Entry pressure (N/m$^{2}$)")
aPe.set_xlim(left = 0, right = 220*n)
aPe.set_ylim(bottom = 0, top = 220*n)
plt.axis('off')
plt.show()

The current output is

The expected output is