Creating a colorbar in matplotlib given the code below - matplotlib

Question

I'm having a really hard time creating a colourbar given the code below. I had the idea of colouring the lines one by one as my code adds the plot lines for each cycle iteration. What matters is that for each main cycle iteration (i in stim_strength_list) a new line is added for each of the subplots. And the colour values for such line get continuously updated.
Now the issue of such a code is that I'm having an extremely hard time creating a colourbar sitting to the right of all the subplot. Most importantly because I have no ScalarMappable object that can be fed into the plt.colorbar() function. And I don't know of any other function that could get the job done properly.
I see a lot of tutorials on-line where no parameters are given at all to the function and everything works just fine but I don't know why it isn't the case for me. I just began programming recently so I'm really sure that there is something really simple flyin over my head, but despite having searched all over stack overflow I haven't managed to find anything that could fix my specific problem.
stim_strength_list = [int(x)*10 for x in range(0,81)]
stp_list = [int(x) for x in range(51,71)]
area_list = ['V1', 'TO', 'AT', 'PFL', 'PML', 'M1L', 'A1', 'AB', 'PB', 'PFI', 'PMI', 'M1I']
# CREATE THE FIGURE
fig, axis = plt.subplots(2, 6, sharey=True, sharex=True, squeeze=True, figsize=(30, 22.5))
fig.suptitle("Activation plots for each area at different levels of strength, spiking architecture", fontsize=25.0, y=0.99)
# COLOURS
red = 0.0
blue = 1.0
for i in stim_strength_list:
# CREATING VALUES TO BE PLOTTED
a = df_s.drop(df_s[df_s['stim_strength'] != i].index)
b = a.groupby('stp').mean()
for j in area_list: # here a create an empty list for each of the 12 areas
globals()[j]=[] # i.e.: V1 = [], TO = [], AT = [], ...
for j in stp_list: # here I cycle through the time steps..
for k in area_list:
globals()[k].append(b.loc[j, k]) # to append values to each area called upon
# PLOTTING
for row in range(0, 2): # given the plt.subplots() methods refers to the subplots via a matrix coordinate system...
for col in range (0, 6): # ...I use this nested loop to plot values in each list in its respective subplot
if row == 0:
axis[row, col].plot(stp_list, globals()[area_list[col]], color=(red, 0, blue), linewidth=1)
else: # about the col + 6 indexing, if I'm in the second row of the subplots I just add 6 to the current value of col to fetch the appropriate brain area this is just
axis[row, col].plot(stp_list, globals()[area_list[col + 6]], color=(red, 0, blue), linewidth=1)
blue -= 1/len(stim_strength_list) # this is to make it that the first line is fully blue...
red += 1/len(stim_strength_list) # ... and the final one is fully red
# TITLING
for row in range(0, 2): #same logic as above, I did an external nested loop simply because the titling would be done for len(stp_list)*12 times
for col in range (0, 6):
if row == 0:
axis[row, col].set_title(area_list[col], fontsize=25)
else:
axis[row, col].set_title(area_list[col + 6], fontsize=25)
# LABELLING
axis[0, 0].set_ylabel('Amount of cells', fontsize=20)
axis[1, 0].set_ylabel('Amount of cells', fontsize=20)
for i in range(0, 6):
axis[1, i].set_xlabel('Time step', fontsize=20)
fig.tight_layout()
plt.show()
This is the code which creates everything. What is missing is the dataframe from which data is taken but i think that you can get an idea by looking at the result.
Final plot
What I would love to achieve is to have a colorbar which displays the colors employed to color the different lines within each subplot. Such transition is determined by progressively increasing and decreasing the red and blue values within the color attribute in .plot() method.
If I just add plt.colorbar() I will get the following error:
Traceback (most recent call last):
  at block x, line y
  at /opt/python/envs/default/lib/python3.8/site-packages/matplotlib/pyplot.py, line 2084, in colorbar(mappable, cax, ax, **kw)
RuntimeError: No mappable was found to use for colorbar creation. First define a mappable such as an image (with imshow) or a contour set (with contourf).
What would you do with the code available to achieve the result I described above?