As mentionned by others, PIL is the right library. Here is a function that open an image and look for the main color.

def get_main_color(file):
    img = Image.open(file)
    colors = img.getcolors(256) #put a higher value if there are many colors in your image
    max_occurence, most_present = 0, 0
    try:
        for c in colors:
            if c[0] > max_occurence:
                (max_occurence, most_present) = c
        return most_present
    except TypeError:
        raise Exception("Too many colors in the image")

I hope it helps

Update : passing 256 to getcolors is ok for very small images but may not work in most cases. This value must be increased for bigger images. for example, 1024*1024 is ok for 400 pixels * 300 pixel image.

I have used something like the following a few times to analyze graphs:

>>> from PIL import Image
>>> im = Image.open('polar-bear-cub.jpg')
>>> from collections import defaultdict
>>> by_color = defaultdict(int)
>>> for pixel in im.getdata():
...     by_color[pixel] += 1
>>> by_color
defaultdict(<type 'int'>, {(11, 24, 41): 8, (53, 52, 58): 8, (142, 147, 117): 1, (121, 111, 119): 1, (234, 228, 216): 4

Ie, there are 8 pixels with rbg value (11, 24, 41), and so on.