cleanup.py

from decimal import *

# A dict has a key ane a value. In the following, they key is 'name' and the value is 'Homer'.
homer = {'name':'Homer', 'age':'39'}

# I'm using strings for the values so it looks more like the data you get from your CSV.
milhouse = {'name':'Milhouse', 'age':'10'}

unsorted_list = [homer, {'name': 'Marge', 'age': '37'}, milhouse, {'name':'Bart', 'age':'10'}]

### CLEAN UP unsorted_list
# First we need to clean up our list so our numbers are actually numbers
# http://book.pythontips.com/en/latest/map_filter.html#map

# Let's understand map first, but we need to understand functions.

def times_2(x):
    return x * 2

print "The result of times_2(11): ", times_2(11)

# We can apply a function to an entire list via map like so:

junk_list = [4, 5, 6]
print "The result of map(times_2, junk_list): ", map(times_2, junk_list)

# To get back to our original goal, we want to turn our strings into numbers so we can do greater than and less than comparisons.
# Let's write a function that'll convert the age of homer or milhouse.

def converted_number_or_string(value):
    try:
        return Decimal(value)
    except InvalidOperation:
        return value

def convert_values_to_numeric(record):
    result = {}
    for key, value in record.iteritems():
        result[key] = converted_number_or_string(value)
    return result

print convert_values_to_numeric(milhouse)

# Now that we've got something that'll work for a single record, you can use map to clean up the entire unsorted_list at once.


# You should use the map function, unsorted_list and convert_age_to_int to make a new cleaned_unsorted_list now.
# TODO: convert the values in `unsorted_list`
# TODO: Be able to reproduce this file from scratch from memory
# TODO: from an empty file, get to your current point with your csv import and then create a new list called cleaned_unsorted_list
# TODO: Be able to do that last thing from memory

csv_into_list_of_dicts.py

import csv

unsorted_list = []

with open('TechCrunchcontinentalUSA.csv', 'rbU') as csvfile:
  reader = csv.DictReader(csvfile)
  print type(reader)
  for row in reader:
      unsorted_list.append(row)

for datum in unsorted_list:
    print datum

print "done"

python_csv.py

import csv

with open('TechCrunchcontinentalUSA.csv', 'rbU') as csvfile:
  reader = csv.DictReader(csvfile)
  print type(reader)
  for row in reader:
    print row

print "done"

I downloaded the csv file from here: https://support.spatialkey.com/spatialkey-sample-csv-data/