Python 2.7 Interactive Visualisation

Question

I'm a new programmer who has for a few days trying to create a dropdown list whose input then creates a graph. For my graph, I'm using Bokeh to create a html file graph, plotting per-capita income of a few places as well as it's percentage of Diabetes. However I have been trying to get it to work for 2 weeks now with a dropdown list and I simply cannot make it work. I can create the file, but only when the user enters the input by typing. How Can I make this work with a person selecting a place from a dropdown list and the file showing that places graph as output. Here's my code.

Edit: I want the selected value from the dropdown list to be sent as the value aaa to the program. I know I should turn my graph creating part of the program into a function. But how do I get the value of a dropdown list as the variable aaa?

import csv
from bokeh.plotting import figure, curdoc
from bokeh.io import output_file, show
from bokeh.layouts import widgetbox
from bokeh.models.widgets import Dropdown

aaa = raw_input("Write State, not Puerto Rico, Hawaii, or DC: ")
from collections import defaultdict
columns = defaultdict(list) # each value in each column is appended to a list
columns1 = defaultdict(list)
with open('my_data.csv') as f:
        for row in f:
         row = row.strip()# read a row as {column1: value1, column2: value2,...}
         row  = row.split(',')
         columns[row[0]].append(row[1])
         columns[row[0]].append(row[2])
         columns[row[0]].append(row[3])
         columns[row[0]].append(row[4])
         columns[row[0]].append(row[5])

xy = (columns[aaa])
xy = [float(i) for i in xy]
myInt = 10000
xy = [x / myInt for x in xy]
print xy

with open('my_data1.csv') as f:
        for row in f:
         row = row.strip()# read a row as {column1: value1, column2: value2,...}
         row  = row.split(',')
         columns1[row[0]].append(row[1])
         columns1[row[0]].append(row[2])
         columns1[row[0]].append(row[3])
         columns1[row[0]].append(row[4])
         columns1[row[0]].append(row[5])
omega = (columns1[aaa])
omega = [float(i) for i in omega]
print omega
import numpy
corr123 = numpy.corrcoef(omega,xy)
print corr123
a = [2004, 2005, 2006, 2007, 2008]
output_file("lines.html")
p = figure(tools="pan,box_zoom,reset,save", title="Diabetes and Stats",
          x_axis_label='Years', y_axis_label='percents')
# add some renderers
per = "Diabetes% " + aaa
p.line(a, omega, legend=per)
p.circle(a, omega, legend=per, fill_color="white",line_color="green",   size=8)
p.line(a, xy, legend="Per Capita Income/10000")
p.circle(a, xy, legend="Per Capita Income/10000", fill_color="red",    line_color="red", size=8)
p.legend.location="top_left"
show(p)