In [3]:
from collections import OrderedDict
import csv
from dateutil.parser import parse
import datetime,time

class DataFrame(object):

    @classmethod
    def from_csv(cls, file_path, delimiting_character=',', quote_character='"'):
        with open(file_path, 'rU') as infile:
            reader = csv.reader(infile, delimiter=delimiting_character, quotechar=quote_character)
            data = []

            for row in reader:
                data.append(row)

            return cls(list_of_lists=data)

    def __init__(self, list_of_lists, header=True):
        if header:
            self.header = list_of_lists[0]
            self.data = list_of_lists[1:]
        else:
            self.header = ['column' + str(index + 1) for index, column in enumerate(list_of_lists[0])]
            self.data = list_of_lists



        ############# HW2 task 1 #############
        if len(self.header) != len(set(self.header)):
            raise Exception('There are duplicates!!!')
        ############# end task 1 #############

        ############# HW2 task 2 #############
        self.data=[[s.strip() for s in row] for row in self.data]
        ############# end task 2 #############

        self.data = [OrderedDict(zip(self.header, row)) for row in self.data]

    def __getitem__(self, item):
        # this is for rows only
        if isinstance(item, (int, slice)):
            return self.data[item]

        # this is for columns only
        elif isinstance(item, str):
            return [row[item] for row in self.data]

        # this is for rows and columns
        elif isinstance(item, tuple):
            if isinstance(item[0], list) or isinstance(item[1], list):

                if isinstance(item[0], list):
                    rowz = [row for index, row in enumerate(self.data) if index in item[0]]
                else:
                    rowz = self.data[item[0]]

                if isinstance(item[1], list):
                    if all([isinstance(thing, int) for thing in item[1]]):
                        return [[column_value for index, column_value in enumerate([value for value in row.itervalues()]) if index in item[1]] for row in rowz]
                    elif all([isinstance(thing,str) for thing in item[1]]):
                        return [[row[column_name] for column_name in item[1]] for row in rowz]
                    else:
                        raise TypeError('What the hell is this?')

                else:
                    return [[value for value in row.itervalues()][item[1]] for row in rowz]
            else:
                if isinstance(item[1], (int, slice)):
                    return [[value for value in row.itervalues()][item[1]] for row in self.data[item[0]]]
                elif isinstance(item[1],str):
                    return [row[item[1]] for row in self.data[item[0]]]
                else:
                    raise TypeError('I don\'t know how to handle this...')

        # only for lists of column names
        elif isinstance(item, list):
            return [[row[column_name] for column_name in item] for row in self.data]

    def get_rows_where_column_has_value(self, column_name, value, index_only=False):
        if index_only:
            return [index for index, row_value in enumerate(self[column_name]) if row_value==value]
        else:
            return [row for row in self.data if row[column_name]==value]

    ############# HW2 task 3 #############
    
    def min(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            print min(nums)
        except ValueError:
            try:
                nums=[datetime.datetime.strptime(row[col_name], '%m/%d/%y %H:%M') for row in self.data]
                nums=[time.mktime(num.timetuple()) for num in nums]
                print time.strftime('%m-%d-%y %H:%M',time.localtime(min(nums)))
            except:    
                print ('Cannot be calculated')

    def max(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            print max(nums)
        except ValueError:
            try:
                nums=[datetime.datetime.strptime(row[col_name], '%m/%d/%y %H:%M') for row in self.data]
                nums=[time.mktime(num.timetuple()) for num in nums]
                print time.strftime('%m-%d-%y %H:%M',time.localtime(max(nums)))
            except:    
                print ('Cannot be calculated')

    def median(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            nums = sorted(nums)
            center = int(len(nums) / 2)
            if len(nums) % 2 == 0:
                print sum(nums[center - 1:center + 1]) / 2.0
            else:
                print nums[center]
        except ValueError:
            try:
                nums=[datetime.datetime.strptime(row[col_name], '%m/%d/%y %H:%M') for row in self.data]
                nums=[time.mktime(num.timetuple()) for num in nums]
                nums = sorted(nums)
                center = int(len(nums) / 2)
                if len(nums) % 2 == 0:
                    print time.strftime('%m-%d-%y %H:%M',time.localtime(sum(nums[center - 1:center + 1]) / 2.0))
                else:
                    print time.strftime('%m-%d-%y %H:%M',time.localtime(nums[center]))
            except:
                print ('Cannot be calculated')


    def mean(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            count = len(nums)
            print sum(nums) / count
        except ValueError:
            try:
                nums=[datetime.datetime.strptime(row[col_name], '%m/%d/%y %H:%M') for row in self.data]
                nums=[time.mktime(num.timetuple()) for num in nums]
                count = len(nums)
                print time.strftime('%m-%d-%y %H:%M',time.localtime(sum(nums) / count))                
            except:
                print ('Cannot be calculated')

    def sum(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            print sum(nums)
        except ValueError:
            print ('Cannot be calculated')

    def std(self,col_name):
        try:
            nums = [float(row[col_name].replace(',','')) for row in self.data]
            mean = sum(nums)/len(nums)
            print  sum((x-mean)**2/len(nums) for x in nums)**0.5
        except ValueError:
            print ('Cannot be calculated')

    ############# end task 3 #############

    ############# HW2 task 4 #############
    
    def add_rows(self, list_of_lists):
        for new_list in list_of_lists:
            if len(new_list) == len(self.header):
                new_row = [OrderedDict(zip(self.header, row)) for row in list_of_lists]
                self.data = self.data + new_row
                return self
            else:
                print ('Wrong number of len')
    ############# end task 4 #############

    ############# HW2 task 5 #############
    
    def add_column(self, list_of_lists, col_name):
        if len(list_of_lists) == len(self.data):
            self.header=self.header+col_name
            new_col_dict = [OrderedDict(zip(col_name,row)) for row in list_of_lists]
            for l in range(len(self.data)):
                for rowz in self.data:
                    rowz = self.data[l].update(new_col_dict[l]) 
            return self
        else:
            print ("Wrong number of column")
    ############# end task 5 #############

In [413]:
infile = open('SalesJan2009.csv')

In [414]:
lines = infile.readlines()

In [415]:
lines = lines[0].split('\r')

In [416]:
data = [l.split(',') for l in lines]

In [423]:
len(data[0])


Out[423]:
12

In [438]:
for index,row in enumerate(data):
        if len(data[index])!=12:
            print index


559

In [439]:
data[559]


Out[439]:
['1/28/09 18:00',
 'Product1',
 '"13',
 '000"',
 'Visa',
 'sandhya',
 'Centennial                  ',
 'CO',
 'United States',
 '12/2/06 23:24',
 '2/7/09 15:18',
 '39.57917',
 '-104.87639']

In [450]:
things= lines[559].split('"')
things


Out[450]:
['1/28/09 18:00,Product1,',
 '13,000',
 ',Visa,sandhya,Centennial                  ,CO,United States,12/2/06 23:24,2/7/09 15:18,39.57917,-104.87639']

In [458]:
things[0].split(',')[:-1]


Out[458]:
['1/28/09 18:00', 'Product1']

In [459]:
things[1]


Out[459]:
'13,000'

In [462]:
things[2].split(',')[1:]


Out[462]:
['Visa',
 'sandhya',
 'Centennial                  ',
 'CO',
 'United States',
 '12/2/06 23:24',
 '2/7/09 15:18',
 '39.57917',
 '-104.87639']

In [463]:
data[559]=things[0].split(',')[:-1]+[things[1]]+things[2].split(',')[1:]
data[559]


Out[463]:
['1/28/09 18:00',
 'Product1',
 '13,000',
 'Visa',
 'sandhya',
 'Centennial                  ',
 'CO',
 'United States',
 '12/2/06 23:24',
 '2/7/09 15:18',
 '39.57917',
 '-104.87639']

In [465]:
data


Out[465]:
[['Transaction_date',
  'Product',
  'Price',
  'Payment_Type',
  'Name',
  'City',
  'State',
  'Country',
  'Account_Created',
  'Last_Login',
  'Latitude',
  'Longitude'],
 ['1/2/09 6:17',
  'Product1',
  '1200',
  'Mastercard',
  'carolina',
  'Basildon',
  'England',
  'United Kingdom',
  '1/2/09 6:00',
  '1/2/09 6:08',
  '51.5',
  '-1.1166667'],
 ['1/2/09 4:53',
  'Product1',
  '1200',
  'Visa',
  'Betina',
  'Parkville                   ',
  'MO',
  'United States',
  '1/2/09 4:42',
  '1/2/09 7:49',
  '39.195',
  '-94.68194'],
 ['1/2/09 13:08',
  'Product1',
  '1200',
  'Mastercard',
  'Federica e Andrea',
  'Astoria                     ',
  'OR',
  'United States',
  '1/1/09 16:21',
  '1/3/09 12:32',
  '46.18806',
  '-123.83'],
 ['1/3/09 14:44',
  'Product1',
  '1200',
  'Visa',
  'Gouya',
  'Echuca',
  'Victoria',
  'Australia',
  '9/25/05 21:13',
  '1/3/09 14:22',
  '-36.1333333',
  '144.75'],
 ['1/4/09 12:56',
  'Product2',
  '3600',
  'Visa',
  'Gerd W ',
  'Cahaba Heights              ',
  'AL',
  'United States',
  '11/15/08 15:47',
  '1/4/09 12:45',
  '33.52056',
  '-86.8025'],
 ['1/4/09 13:19',
  'Product1',
  '1200',
  'Visa',
  'LAURENCE',
  'Mickleton                   ',
  'NJ',
  'United States',
  '9/24/08 15:19',
  '1/4/09 13:04',
  '39.79',
  '-75.23806'],
 ['1/4/09 20:11',
  'Product1',
  '1200',
  'Mastercard',
  'Fleur',
  'Peoria                      ',
  'IL',
  'United States',
  '1/3/09 9:38',
  '1/4/09 19:45',
  '40.69361',
  '-89.58889'],
 ['1/2/09 20:09',
  'Product1',
  '1200',
  'Mastercard',
  'adam',
  'Martin                      ',
  'TN',
  'United States',
  '1/2/09 17:43',
  '1/4/09 20:01',
  '36.34333',
  '-88.85028'],
 ['1/4/09 13:17',
  'Product1',
  '1200',
  'Mastercard',
  'Renee Elisabeth',
  'Tel Aviv',
  'Tel Aviv',
  'Israel',
  '1/4/09 13:03',
  '1/4/09 22:10',
  '32.0666667',
  '34.7666667'],
 ['1/4/09 14:11',
  'Product1',
  '1200',
  'Visa',
  'Aidan',
  'Chatou',
  'Ile-de-France',
  'France',
  '6/3/08 4:22',
  '1/5/09 1:17',
  '48.8833333',
  '2.15'],
 ['1/5/09 2:42',
  'Product1',
  '1200',
  'Diners',
  'Stacy',
  'New York                    ',
  'NY',
  'United States',
  '1/5/09 2:23',
  '1/5/09 4:59',
  '40.71417',
  '-74.00639'],
 ['1/5/09 5:39',
  'Product1',
  '1200',
  'Amex',
  'Heidi',
  'Eindhoven',
  'Noord-Brabant',
  'Netherlands',
  '1/5/09 4:55',
  '1/5/09 8:15',
  '51.45',
  '5.4666667'],
 ['1/2/09 9:16',
  'Product1',
  '1200',
  'Mastercard',
  'Sean ',
  'Shavano Park                ',
  'TX',
  'United States',
  '1/2/09 8:32',
  '1/5/09 9:05',
  '29.42389',
  '-98.49333'],
 ['1/5/09 10:08',
  'Product1',
  '1200',
  'Visa',
  'Georgia',
  'Eagle                       ',
  'ID',
  'United States',
  '11/11/08 15:53',
  '1/5/09 10:05',
  '43.69556',
  '-116.35306'],
 ['1/2/09 14:18',
  'Product1',
  '1200',
  'Visa',
  'Richard',
  'Riverside                   ',
  'NJ',
  'United States',
  '12/9/08 12:07',
  '1/5/09 11:01',
  '40.03222',
  '-74.95778'],
 ['1/4/09 1:05',
  'Product1',
  '1200',
  'Diners',
  'Leanne',
  'Julianstown',
  'Meath',
  'Ireland',
  '1/4/09 0:00',
  '1/5/09 13:36',
  '53.6772222',
  '-6.3191667'],
 ['1/5/09 11:37',
  'Product1',
  '1200',
  'Visa',
  'Janet',
  'Ottawa',
  'Ontario',
  'Canada',
  '1/5/09 9:35',
  '1/5/09 19:24',
  '45.4166667',
  '-75.7'],
 ['1/6/09 5:02',
  'Product1',
  '1200',
  'Diners',
  'barbara',
  'Hyderabad',
  'Andhra Pradesh',
  'India',
  '1/6/09 2:41',
  '1/6/09 7:52',
  '17.3833333',
  '78.4666667'],
 ['1/6/09 7:45',
  'Product2',
  '3600',
  'Visa',
  'Sabine',
  'London',
  'England',
  'United Kingdom',
  '1/6/09 7:00',
  '1/6/09 9:17',
  '51.52721',
  '0.14559'],
 ['1/2/09 7:35',
  'Product1',
  '1200',
  'Diners',
  'Hani',
  'Salt Lake City              ',
  'UT',
  'United States',
  '12/30/08 5:44',
  '1/6/09 10:52',
  '40.76083',
  '-111.89028'],
 ['1/6/09 12:56',
  'Product1',
  '1200',
  'Visa',
  'Jeremy',
  'Manchester',
  'England',
  'United Kingdom',
  '1/6/09 10:58',
  '1/6/09 13:31',
  '53.5',
  '-2.2166667'],
 ['1/1/09 11:05',
  'Product1',
  '1200',
  'Diners',
  'Janis',
  'Ballynora',
  'Cork',
  'Ireland',
  '12/10/07 12:37',
  '1/7/09 1:52',
  '51.8630556',
  '-8.58'],
 ['1/5/09 4:10',
  'Product1',
  '1200',
  'Mastercard',
  'Nicola',
  'Roodepoort',
  'Gauteng',
  'South Africa',
  '1/5/09 2:33',
  '1/7/09 5:13',
  '-26.1666667',
  '27.8666667'],
 ['1/6/09 7:18',
  'Product1',
  '1200',
  'Visa',
  'asuman',
  'Chula Vista                 ',
  'CA',
  'United States',
  '1/6/09 7:07',
  '1/7/09 7:08',
  '32.64',
  '-117.08333'],
 ['1/2/09 1:11',
  'Product1',
  '1200',
  'Mastercard',
  'Lena',
  'Kuopio',
  'Ita-Suomen Laani',
  'Finland',
  '12/31/08 2:48',
  '1/7/09 10:20',
  '62.9',
  '27.6833333'],
 ['1/1/09 2:24',
  'Product1',
  '1200',
  'Visa',
  'Lisa',
  'Sugar Land                  ',
  'TX',
  'United States',
  '1/1/09 1:56',
  '1/7/09 10:52',
  '29.61944',
  '-95.63472'],
 ['1/7/09 8:08',
  'Product1',
  '1200',
  'Diners',
  'Bryan Kerrene',
  'New York                    ',
  'NY',
  'United States',
  '1/7/09 7:39',
  '1/7/09 12:38',
  '40.71417',
  '-74.00639'],
 ['1/2/09 2:57',
  'Product1',
  '1200',
  'Visa',
  'chris',
  'London',
  'England',
  'United Kingdom',
  '1/3/08 7:23',
  '1/7/09 13:14',
  '51.52721',
  '0.14559'],
 ['1/1/09 20:21',
  'Product1',
  '1200',
  'Visa',
  'Maxine',
  'Morton                      ',
  'IL',
  'United States',
  '10/24/08 6:48',
  '1/7/09 20:49',
  '40.61278',
  '-89.45917'],
 ['1/8/09 0:42',
  'Product1',
  '1200',
  'Visa',
  'Family',
  'Los Gatos                   ',
  'CA',
  'United States',
  '1/8/09 0:28',
  '1/8/09 3:39',
  '37.22667',
  '-121.97361'],
 ['1/8/09 3:56',
  'Product1',
  '1200',
  'Mastercard',
  'Katherine',
  'New York                    ',
  'NY',
  'United States',
  '1/8/09 3:33',
  '1/8/09 6:19',
  '40.71417',
  '-74.00639'],
 ['1/8/09 3:16',
  'Product1',
  '1200',
  'Mastercard',
  'Linda',
  'Miami                       ',
  'FL',
  'United States',
  '1/8/09 3:06',
  '1/8/09 6:34',
  '25.77389',
  '-80.19389'],
 ['1/8/09 1:59',
  'Product1',
  '1200',
  'Mastercard',
  'SYLVIA',
  'Vesenaz',
  'Geneve',
  'Switzerland',
  '11/28/07 11:56',
  '1/8/09 7:20',
  '46.2333333',
  '6.2'],
 ['1/3/09 9:03',
  'Product1',
  '1200',
  'Diners',
  'Sheila',
  'Brooklyn                    ',
  'NY',
  'United States',
  '1/3/09 8:47',
  '1/8/09 10:38',
  '40.65',
  '-73.95'],
 ['1/5/09 13:17',
  'Product1',
  '1200',
  'Mastercard',
  'Stephanie',
  'Badhoevedorp',
  'Noord-Holland',
  'Netherlands',
  '1/5/09 12:45',
  '1/8/09 11:45',
  '52.3333333',
  '4.7833333'],
 ['1/6/09 7:46',
  'Product1',
  '1200',
  'Amex',
  'Kelly',
  'Reston                      ',
  'VA',
  'United States',
  '1/6/09 7:30',
  '1/8/09 12:40',
  '38.96861',
  '-77.34139'],
 ['1/5/09 20:00',
  'Product2',
  '3600',
  'Visa',
  'James',
  'Burpengary',
  'Queensland',
  'Australia',
  '12/10/08 19:53',
  '1/8/09 17:58',
  '-27.1666667',
  '152.95'],
 ['1/8/09 16:24',
  'Product1',
  '1200',
  'Visa',
  'jennifer',
  'Phoenix                     ',
  'AZ',
  'United States',
  '1/8/09 15:57',
  '1/8/09 18:30',
  '33.44833',
  '-112.07333'],
 ['1/9/09 6:39',
  'Product1',
  '1200',
  'Mastercard',
  'Anneli',
  'Houston                     ',
  'TX',
  'United States',
  '1/9/09 5:09',
  '1/9/09 7:11',
  '29.76306',
  '-95.36306'],
 ['1/6/09 22:19',
  'Product2',
  '3600',
  'Amex',
  'Ritz',
  'Pittsfield                  ',
  'VT',
  'United States',
  '1/6/09 12:00',
  '1/9/09 10:05',
  '43.77222',
  '-72.81333'],
 ['1/6/09 23:00',
  'Product2',
  '3600',
  'Amex',
  'Sylvia',
  'Pittsfield                  ',
  'VT',
  'United States',
  '1/6/09 12:00',
  '1/9/09 10:05',
  '43.77222',
  '-72.81333'],
 ['1/7/09 7:44',
  'Product1',
  '1200',
  'Mastercard',
  'Marie',
  'Ball Ground                 ',
  'GA',
  'United States',
  '1/7/09 5:35',
  '1/9/09 10:52',
  '34.33806',
  '-84.37667'],
 ['1/3/09 13:24',
  'Product1',
  '1200',
  'Visa',
  'Mehmet Fatih',
  'Helsingor',
  'Frederiksborg',
  'Denmark',
  '1/3/09 12:47',
  '1/9/09 11:14',
  '56.0333333',
  '12.6166667'],
 ['1/7/09 15:12',
  'Product2',
  '3600',
  'Visa',
  'Anabela',
  'Flossmoor                   ',
  'IL',
  'United States',
  '1/5/09 19:55',
  '1/9/09 16:03',
  '41.54278',
  '-87.68472'],
 ['1/7/09 20:15',
  'Product1',
  '1200',
  'Amex',
  'Nicole',
  'Houston                     ',
  'TX',
  'United States',
  '1/7/09 17:17',
  '1/9/09 20:02',
  '29.76306',
  '-95.36306'],
 ['1/3/09 10:11',
  'Product2',
  '3600',
  'Visa',
  'Christiane ',
  'Delray Beach                ',
  'FL',
  'United States',
  '1/3/09 9:27',
  '1/10/09 9:46',
  '26.46111',
  '-80.07306'],
 ['1/9/09 15:58',
  'Product1',
  '1200',
  'Mastercard',
  'Sari',
  'Newbury',
  'England',
  'United Kingdom',
  '1/9/09 14:53',
  '1/10/09 13:16',
  '51.4',
  '-1.3166667'],
 ['1/3/09 13:11',
  'Product1',
  '1200',
  'Mastercard',
  'simone',
  'Kobenhavn',
  'Kobenhavn',
  'Denmark',
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  '51.75',
  '-0.3333333'],
 ['1/22/09 11:10',
  'Product1',
  '1200',
  'Mastercard',
  'Gustavo',
  'Voluntari',
  'Bucuresti',
  'Romania',
  '7/28/08 11:12',
  '2/28/09 7:52',
  '44.4666667',
  '26.1333333'],
 ['1/7/09 12:06',
  'Product1',
  '1200',
  'Visa',
  'Erica',
  'Nadur',
  ' ',
  'Malta',
  '3/30/06 2:02',
  '2/28/09 7:59',
  '36.0377778',
  '14.2941667'],
 ['1/29/09 13:25',
  'Product1',
  '1200',
  'Diners',
  'Hale',
  'Morrison                    ',
  'CO',
  'United States',
  '11/3/05 18:14',
  '2/28/09 8:27',
  '39.65361',
  '-105.19056'],
 ['1/27/09 2:57',
  'Product1',
  '1200',
  'Visa',
  'Rosemary',
  'Cobham',
  'England',
  'United Kingdom',
  '1/27/09 2:50',
  '2/28/09 9:22',
  '51.3833333',
  '0.4'],
 ['1/7/09 13:19',
  'Product1',
  '1200',
  'Visa',
  'Darian',
  'Izmir',
  'Izmir',
  'Turkey',
  '8/26/08 7:33',
  '2/28/09 9:54',
  '38.4072222',
  '27.1502778'],
 ['1/23/09 10:04',
  'Product1',
  '1200',
  'Mastercard',
  'Kevin',
  'Hollywood                   ',
  'CA',
  'United States',
  '5/30/06 20:25',
  '2/28/09 9:59',
  '34.09833',
  '-118.32583'],
 ['1/19/09 4:55',
  'Product1',
  '1200',
  'Visa',
  'Alyssa',
  'Brighton',
  'England',
  'United Kingdom',
  '2/19/08 9:27',
  '2/28/09 10:06',
  '50.8333333',
  '-0.15'],
 ['1/28/09 22:02',
  'Product1',
  '1200',
  'Visa',
  'Hale',
  'Hawera',
  'Taranaki',
  'New Zealand',
  '1/23/09 22:31',
  '2/28/09 12:43',
  '-39.5916667',
  '174.2833333'],
 ['1/4/09 18:57',
  'Product1',
  '1200',
  'Mastercard',
  'KELI',
  'Worongary',
  'Queensland',
  'Australia',
  '12/23/08 15:17',
  '2/28/09 14:00',
  '-28.05',
  '153.35'],
 ['1/12/09 20:31',
  'Product1',
  '1200',
  'Visa',
  'Glen',
  'Atlantida',
  'Guatemala',
  'Guatemala',
  '1/6/09 16:53',
  '2/28/09 14:39',
  '14.65',
  '-90.4833333'],
 ['1/24/09 12:00',
  'Product1',
  '1200',
  'Visa',
  'T',
  'El Escorial',
  'Madrid',
  'Spain',
  '12/30/08 15:19',
  '2/28/09 15:17',
  '40.5833333',
  '-4.1166667'],
 ['1/28/09 11:19',
  'Product1',
  '1200',
  'Visa',
  'christal',
  'Morrison                    ',
  'CO',
  'United States',
  '6/20/04 17:16',
  '2/28/09 17:18',
  '39.65361',
  '-105.19056'],
 ['1/7/09 17:48',
  'Product1',
  '1200',
  'Mastercard',
  'Alex',
  'Augusta                     ',
  'GA',
  'United States',
  '6/10/05 20:25',
  '2/28/09 19:57',
  '33.51722',
  '-82.07583'],
 ['1/23/09 12:42',
  'Product2',
  '3600',
  'Mastercard',
  'Anke',
  'Avalon',
  'New South Wales',
  'Australia',
  '3/3/08 17:38',
  '2/28/09 22:26',
  '-33.6333333',
  '151.3333333'],
 ['1/7/09 19:48',
  'Product2',
  '3600',
  'Mastercard',
  'TRICIA',
  'Sydney',
  'New South Wales',
  'Australia',
  '9/21/08 20:49',
  '3/1/09 0:14',
  '-33.8833333',
  '151.2166667'],
 ['1/26/09 11:19',
  'Product1',
  '1200',
  'Mastercard',
  'smith',
  'Lahti',
  'Etela-Suomen Laani',
  'Finland',
  '1/4/09 5:25',
  '3/1/09 0:39',
  '60.9666667',
  '25.6666667'],
 ['1/5/09 13:23',
  'Product1',
  '1200',
  'Visa',
  'Macy',
  'Inner City',
  'Vienna',
  'Austria',
  '1/5/09 11:28',
  '3/1/09 2:28',
  '48.2166667',
  '16.3666667'],
 ['1/26/09 13:41',
  'Product1',
  '1200',
  'Mastercard',
  'Lesleigh',
  'Baden',
  'Aargau',
  'Switzerland',
  '10/23/05 9:23',
  '3/1/09 3:11',
  '47.4666667',
  '8.3'],
 ['1/20/09 10:42',
  'Product2',
  '3600',
  'Diners',
  'esther',
  'Huddersfield',
  'England',
  'United Kingdom',
  '1/20/09 9:15',
  '3/1/09 3:29',
  '53.65',
  '-1.7833333'],
 ['1/22/09 14:25',
  'Product1',
  '1200',
  'Visa',
  'Hans-Joerg',
  'Belfast',
  'Northern Ireland',
  'United Kingdom',
  '11/10/08 12:15',
  '3/1/09 3:37',
  '54.5833333',
  '-5.9333333'],
 ['1/28/09 5:36',
  'Product2',
  '3600',
  'Visa',
  'Christiane',
  'Black River',
  'Black River',
  'Mauritius',
  '1/9/09 8:10',
  '3/1/09 4:40',
  '-20.3602778',
  '57.3661111'],
 ['1/1/09 4:24',
  'Product3',
  '7500',
  'Amex',
  'Pamela',
  'Skaneateles                 ',
  'NY',
  'United States',
  '12/28/08 17:28',
  '3/1/09 7:21',
  '42.94694',
  '-76.42944'],
 ['1/8/09 11:55',
  'Product1',
  '1200',
  'Diners',
  'julie',
  'Haverhill',
  'England',
  'United Kingdom',
  '11/29/06 13:31',
  '3/1/09 7:28',
  '52.0833333',
  '0.4333333'],
 ['1/12/09 21:30',
  'Product1',
  '1200',
  'Visa',
  'Julia ',
  'Madison                     ',
  'WI',
  'United States',
  '11/17/08 22:24',
  '3/1/09 10:14',
  '43.07306',
  '-89.40111']]

In [4]:
df = DataFrame.from_csv('SalesJan2009.csv')

In [472]:
value=df['Price']
value= [l.replace(',','') for l in value]

In [475]:
[int(l) for l in value]


Out[475]:
[1200,
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 1200,
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 1200,
 3600,
 3600,
 1200,
 1200,
 1200,
 3600,
 1200,
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 7500,
 1200,
 1200]

In [519]:
header = ['a','b','c']
new_row = [[1,2,3],[4,5,6]]
new_data=[OrderedDict(zip(header,l))for l in new_row]
data


Out[519]:
[OrderedDict([('a', 1), ('b', 2), ('c', 3)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6)])]

In [520]:
header = ['a','b','c']
new_row = [1,2,3]
yy=OrderedDict(zip(header,new_row))
yy


Out[520]:
OrderedDict([('a', 1), ('b', 2), ('c', 3)])

In [522]:
data=[OrderedDict([('a', 1), ('b', 2), ('c', 3)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6)])]
data=data +new_data
data


Out[522]:
[OrderedDict([('a', 1), ('b', 2), ('c', 3)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6)]),
 OrderedDict([('a', 1), ('b', 2), ('c', 3)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6)])]

In [542]:
new_col=[['d','e'],[1,1],[2,2],[3,3],[4,4]]
new_col_head=new_col[0]
new_col_data=new_col[1:]
print new_col_head
print new_col_data


['d', 'e']
[[1, 1], [2, 2], [3, 3], [4, 4]]

In [562]:
len(data)== len(new_col_data)
len(data)


Out[562]:
4

In [598]:
header = ['a','b','c']
header_new = header+new_col_head
header_new

In [591]:
new_col_dict = [OrderedDict(zip(new_col_head,row)) for row in new_col_data]
new_col_dict


Out[591]:
[OrderedDict([('d', 1), ('e', 1)]),
 OrderedDict([('d', 2), ('e', 2)]),
 OrderedDict([('d', 3), ('e', 3)]),
 OrderedDict([('d', 4), ('e', 4)])]

In [596]:
for l in range(len(data)):
    for rowz in data:
        rowz = data[l].update(new_col_dict[l]) 
data


Out[596]:
[OrderedDict([('a', 1), ('b', 2), ('c', 3), ('d', 1), ('e', 1)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6), ('d', 2), ('e', 2)]),
 OrderedDict([('a', 1), ('b', 2), ('c', 3), ('d', 3), ('e', 3)]),
 OrderedDict([('a', 4), ('b', 5), ('c', 6), ('d', 4), ('e', 4)])]

In [587]:
data[3]


Out[587]:
OrderedDict([('a', 4), ('b', 5), ('c', 6)])

In [589]:
new_col_dict[1]


---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-589-f582518922c6> in <module>()
----> 1 new_col_dict(1)

TypeError: 'OrderedDict' object is not callable

In [18]:
dt = DataFrame.from_csv('test_hw2_task5.csv')

In [19]:
dt[:]


Out[19]:
[OrderedDict([('A', '1'), ('B', '4'), ('C', '7')]),
 OrderedDict([('A', '2'), ('B', '5'), ('C', '8')]),
 OrderedDict([('A', '3'), ('B', '6'), ('C', '9')])]

In [20]:
add=[['D','E'],[1,2,3],[4,5,6],[7,8,9]]
add


Out[20]:
[['D', 'E'], [1, 2, 3], [4, 5, 6], [7, 8, 9]]

In [21]:
new=dt.add_column(add[1:],add[0])
print new


<__main__.DataFrame object at 0x7f73d05b5890>

In [22]:
dt[:]


Out[22]:
[OrderedDict([('A', '1'), ('B', '4'), ('C', '7'), ('D', 1), ('E', 2)]),
 OrderedDict([('A', '2'), ('B', '5'), ('C', '8'), ('D', 4), ('E', 5)]),
 OrderedDict([('A', '3'), ('B', '6'), ('C', '9'), ('D', 7), ('E', 8)])]

In [ ]: