The three color channels of the image are red, green and blue or "RGB" for short. The combination of intensity values across the three channels determines what color we see in the image. You can look at each of the color channels in isolation by zeroing out the others and lining them up side by side like this:
	
# Note: we use the np.copy() function rather than just saying red_channel = image
# because in Python, such a statement would set those two arrays equal to each other
# forever, meaning any changes made to one would also be made to the other!
red_channel = np.copy(image)
# Note: here instead of extracting individual channels from the image
# I'll keep all 3 color channels in each case but set the ones I'm not interested 
# in to zero.  
red_channel[:,:,[1, 2]] = 0 # Zero out the green and blue channels
green_channel = np.copy(image)
green_channel[:,:,[0, 2]] = 0 # Zero out the red and blue channels
blue_channel = np.copy(image)
blue_channel[:,:,[0, 1]] = 0 # Zero out the red and green channels
fig = plt.figure(figsize=(12,3)) # Create a figure for plotting
plt.subplot(131) # Initialize subplot number 1 in a figure that is 3 columns 1 row
plt.imshow(red_channel) # Plot the red channel
plt.subplot(132) # Initialize subplot number 2 in a figure that is 3 columns 1 row
plt.imshow(green_channel)  # Plot the green channel
plt.subplot(133) # Initialize subplot number 3 in a figure that is 3 columns 1 row
plt.imshow(blue_channel)  # Plot the blue channel
plt.show() 
