Is there a simple way to add in to my original code so that I can add another title to both column of my subplot? for example like somewhere in the pink region shown in the picture below.

Someone refer me to look at this post for solution but I am looking to see if there is a method without using the for loop

My code:

import cv2
import numpy as np
import matplotlib.pyplot as pltpath = 'R:\\Temp\\xx\\'
path1 = 'R:\\Temp\\xx\\'def Hue(im_file):im = cv2.imread(im_file)im = cv2.cvtColor(im, cv2.COLOR_BGR2HSV_FULL) # Get Hue value= range[0,360]im1 = im[776, 402]Hue = im1[0]return Huedef Saturation(im_file):im = cv2.imread(im_file)im = cv2.cvtColor(im, cv2.COLOR_BGR2HSV_FULL) #return Saturation value = range[0,255]im1 = im[776, 402]Saturation = im1[1]return Saturationdef Value(im_file):im = cv2.imread(im_file)im = cv2.cvtColor(im, cv2.COLOR_BGR2HSV_FULL) #return Value(Brightness) value = range[0,255]im1 = im[776, 402]Value = im1[2]return Value   def BlueComponent(im_file):im = cv2.imread(im_file) #return blue valueim1 = im[776, 402]b = im1[0]return bdef GreenComponent(im_file):im = cv2.imread(im_file) #return green value im1 = im[776, 402]g = im1[1]return gdef RedComponent(im_file): #return red value im = cv2.imread(im_file)im1 = im[776, 402]r = im1[2]return rmyHueList = []
mySaturationList = []
myValueList = []
myBlueList = []
myGreenList = []
myRedList = []
myList = []
num_images = 99 # number of imagesdotPos = 0
for i in range(1770, 1869): # loop to auto-generate image names and run prior function image_name = path + 'Cropped_Aligned_IMG_' + str(i) + '.png' # for loop runs from image number 1770 to 1868myHueList.append(Hue(image_name))mySaturationList.append(Saturation(image_name))myValueList.append(Value(image_name))myBlueList.append(BlueComponent(image_name))myGreenList.append(GreenComponent(image_name))myRedList.append(RedComponent(image_name))myList.append(dotPos)dotPos = dotPos + 0.5print(myBlueList)
print(myGreenList)
print(myRedList)
print(myHueList)
print(mySaturationList)
print(myValueList)
print(myList)for k in range(1770,1869):a = 'Cropped_Aligned_IMG_' + str(k)image_name = path + a + '.png'img_file = cv2.imread(image_name)x = myList
y = myBlueList
y1 = myGreenList
y2 = myRedList
y3 = myHueList
y4 = mySaturationList
y5 = myValueListplt.axes([0.1, 0.1, 1, 1])
plt.suptitle('BGR & HSV Color Decimal Code Against Function of Time(Hours)', fontsize=14, fontweight='bold')
plt.subplot(3,2,1)
plt.plot(x, y, 'b.-')
plt.title('Blue Component Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')plt.subplot(3,2,3)
plt.plot(x, y1, 'g.-')
plt.title('Green Component Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')plt.subplot(3,2,5)
plt.plot(x, y2, 'r.-')
plt.title('Red Component Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')plt.subplot(3,2,2)
plt.plot(x, y3, 'b.-')
plt.title('Hue Component HSV Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')plt.subplot(3,2,4)
plt.plot(x, y4, 'g.-')
plt.title('Saturation Component HSV Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')plt.subplot(3,2,6)
plt.plot(x, y5, 'r.-')
plt.title('Value Component HSV Color Decimal Code')
plt.xlabel('Time(Hours)')
plt.ylabel('Colour Code')
plt.subplots_adjust(hspace = 0.5)
plt.show()

I could imagine creating an empty row of subplots at the top, with each of the subplots having its own title would act as a column title.

import matplotlib.pyplot as plt
import numpy as np
plt.rcParams["figure.figsize"] = 6,8
colors = plt.rcParams["axes.prop_cycle"].by_key()["color"]x = np.linspace(-3,3)
y = np.random.randn(len(x),6)fig, axes = plt.subplots(ncols=2, nrows=3+1, gridspec_kw={"height_ratios":[0.02,1,1,1]})
fig.suptitle('Some long super title for the complete figure', fontsize=14, fontweight='bold')
for i, ax in enumerate(axes.flatten()[2:]):ax.plot(x,y[:,i], color=colors[i%6])ax.set_title("Title {}".format(i+1))for i, ax in enumerate(axes.flatten()[:2]):ax.axis("off")ax.set_title("Columntitle {}".format(i+1), fontweight='bold')fig.subplots_adjust(hspace=0.5, bottom=0.1)
plt.show()

Note that I'm using loops here in order to simplify things. Of course you can type in the commands for each subplots individually, if that is desireable for any reason.