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In [1]:



    


import time
import random

import pandas as pd
import numpy as np


from faker import Factory



    











In [2]:



    


fake = Factory.create()



    











In [3]:



    


companies = pd.read_csv('label.csv')
companies



    


















    
Out[3]:











  
    

      
      label
      name
    

  
  
    

      0
      Beauty
      Bobbi Brown Inc.
    

    

      1
      Beauty
      Dior Beauty
    

    

      2
      Beauty
      Derma Skincare Centre
    

    

      3
      Beauty
      KIKO Asia Ltd.
    

    

      4
      Beauty
      Vichy Laboratories
    

    

      5
      Beauty
      Colourmix Cosmetics Company Limited
    

    

      6
      Beauty
      Sa Sa Cosmetic Co. Ltd.
    

    

      7
      Beauty
      Clinique Laboratories, llc.
    

    

      8
      Beauty
      Shiseido Company, Limited
    

    

      9
      Beauty
      Sephora USA, Inc.
    

    

      10
      Beauty
      MAKE-UP ART COSMETICS.
    

    

      11
      Beauty
      Clarins.
    

    

      12
      Beauty
      L'Oreal SA
    

    

      13
      Beauty
      Laura Mercier Cosmetics.
    

    

      14
      Beauty
      FANCL International, Inc.
    

    

      15
      Education
      Memrise Inc.
    

    

      16
      Education
      Coursera Inc.
    

    

      17
      Education
      Udacity, Inc.
    

    

      18
      Education
      Code School LLC.
    

    

      19
      Education
      edX Inc.
    

    

      20
      Education
      Open Learning Global Pty Ltd.
    

    

      21
      Education
      New Oriental Education & Tech Grp
    

    

      22
      Education
      Chinese TAL Education Group
    

    

      23
      Education
      Tarena International, Inc.
    

    

      24
      Education
      Chegg Inc
    

    

      25
      Education
      2U, Inc.
    

    

      26
      Education
      McGraw-Hill Education
    

    

      27
      Education
      Pearson plc
    

    

      28
      Education
      China Distance Education Hldgs Ltd
    

    

      29
      Education
      Udemy, Inc.
    

    

      ...
      ...
      ...
    

    

      120
      Entertainment
      Broadway Cinematheque
    

    

      121
      Entertainment
      UA Cinema Circuit Limited
    

    

      122
      Entertainment
      Neway Karaoke Box Limited
    

    

      123
      Entertainment
      Red MR Limited
    

    

      124
      Entertainment
      Walt Disney Company
    

    

      125
      Entertainment
      AMC Entertainment Inc
    

    

      126
      Entertainment
      Nintendo
    

    

      127
      Entertainment
      Xbox
    

    

      128
      Entertainment
      LEGO
    

    

      129
      Entertainment
      Ocean Park Hong Kong
    

    

      130
      Entertainment
      Ryze Ultimate Trampoline Park Hong Kong
    

    

      131
      Entertainment
      Ball Room
    

    

      132
      Entertainment
      Ikari Area
    

    

      133
      Entertainment
      VR Arena
    

    

      134
      Entertainment
      HA cube
    

    

      135
      Clothing
      American Eagle Outfitters Inc
    

    

      136
      Clothing
      Holister Co.
    

    

      137
      Clothing
      Zara
    

    

      138
      Clothing
      H&M Hennes & Mauritz AB
    

    

      139
      Clothing
      GAP
    

    

      140
      Clothing
      Levi Strauss & Co.
    

    

      141
      Clothing
      G2000
    

    

      142
      Clothing
      Louis Vuitton
    

    

      143
      Clothing
      Longchamp
    

    

      144
      Clothing
      J. Crew
    

    

      145
      Clothing
      Nike
    

    

      146
      Clothing
      Adidas
    

    

      147
      Clothing
      Converse
    

    

      148
      Clothing
      Superdry
    

    

      149
      Clothing
      Balenciaga
    

  



150 rows × 2 columns



















In [9]:



    


#companies = pd.Series(companies.name.values)



    











In [8]:



    


# random.shuffle(companies)



    











In [8]:



    


def generate_people(n):
    """ Generates n-people, and returns a data frame.
        Each person has a:
            - id
            - age
            - name
            - address
            
        Two of them may be unexpected:
            - compromised: 0 or 1
            - compromised: if compromised, when
            
        These values get set by other functions."""
#     namePool = np.load('names.npy')
#     ids = [i for i in range(n)]
#     names = [fake.name() for n in range(n)]
#     uuids = [fake.uuid4() for n in range(n)]
#     ages = [random.randint(18, 80) for n in range(n)]
#     addresses = [fake.address().replace('\n', ', ') for n in range(n)]
#     compromised = list(np.zeros(n))
#     compromised_time = list(np.zeros(n))
    #generate names
    names = set()
    while len(names) < n:
        nextName = fake.name()
        if nextName not in names:
            names.add(nextName)
    names = list(names)
    names = np.array(names)
    genders = np.random.choice(['male', 'female'], n)
    ids = np.arange(n)
    ages = [random.randint(18, 50) for _ in range(n)]
    addresses = [fake.address().replace('\n', ', ') for _ in range(n)]
    compromised = list(np.zeros(n))
    compromised_time = list(np.zeros(n))
    df = pd.DataFrame([ids, names, genders, ages, addresses, compromised, compromised_time]).T
    df.columns = ['id', 'name', 'gender', 'age', 'address', 'compromised', 'compromised_time']
    return df



    











In [12]:



    


def generate_business(n, fraudster_likelihood=0.01):
    """ Generates n-businesses, and returns a data frame.
        Each person has a:
            - id
            - name
            - address
            
        The one weird one is "frauders_present" which is controlled by the fraudster_likelihood option.
            
        These values get set by other functions."""
    
    ids = [i for i in range(n)]
#     names = list(companies[:n])
    coms = companies.sample(n, replace=True)
    addresses = [fake.address().replace('\n', ', ') for n in range(n)]
    fraudsters = [1 if random.random() < fraudster_likelihood else 0 for n in range(n) ]
    
    df = pd.DataFrame([ids, list(coms['name']), list(coms['label']), addresses]).T
    df.columns = ['id', 'name', 'label', 'address']
    return df



    











In [15]:



    


def generate_normal_transactions(people, businesses, max_transactions=40, fraud_likelihood=1, earliest="-30d", latest="now", amin=9, amax=300):
    """ Generates normal transactions. Returns a list."""
    transactions = []
    amounts = []
    companyNameList = []
    companyLabelList = []
    times = []
    users = []
    ageList = []
    genderList = []
    # For each person
    for p in range(len(people)):
        
        person = people.ix[p]
        
        number_of_transactions = random.randint(1, max_transactions)
        
        # Generate soem transactions
        for i in range(number_of_transactions):

            # random time and business
            time = fake.date_time_between(start_date=earliest, end_date=latest, tzinfo=None)
#             time = fake.date_time_this_month()
            business = businesses.sample(1)
            companyName = business['name']
            companyLabel = business['label']
            amount = random.randint(amin, amax) + round(random.random(), 2)

            
            times.append(time)
            companyNameList.append(companyName)
            companyLabelList.append(companyLabel)
            amounts.append(amount)
            users.append(person['name'])
            ageList.append(person.age)
            genderList.append(person.gender)
#             transactions.append(transaction)
    companyList= companies.sample(len(times), replace=True)
    companyNameList = list(companyList['name'])
    companyLabelList = list(companyList['label'])
    
    df = pd.DataFrame([times, users, genderList, ageList, companyNameList, companyLabelList, amounts]).T
    df.columns = ['time', 'name', 'gender' ,'age', 'company name', 'company label', 'amount']
    return df
# generate_normal_transactions(p,b)



    











In [9]:



    


def generate_fradulent_transactions(people, businesses, max_transactions=40, user_fraud_detection_likelihood=0.10, latest="+10d", amin=1, amax=3000):
    """ Genereates fradulent transactions. Returns a list."""
    transactions = []
    compromised = people[people.compromised == 1]
    
    for i in range(len(compromised)):
        
        person = compromised.iloc[i]
        earliest = person.compromised_time
        time = fake.date_time_between(start_date=earliest, end_date=latest, tzinfo=None)
#         number_of_transactions = random.randint(5, max_transactions)
        number_of_transactions = max_transactions
        for j in range(number_of_transactions):
    
            def fraud():        

                business = businesses.sample(1)
                amount = random.randint(amin, amax) + round(random.random(), 2)

                transaction = '{time} uuid={uuid} user="{user}" business="{business}" amount={amount} disputed=true'.format(
                    time = time,
                    uuid = person['uuid'],
                    user = person['name'],
                    business = business.name.values[0],
                    amount = amount)

                transactions.append(transaction)

            if j == 1:
                fraud()

            # Each fradulent transaction has +1% chance of being cause from the user
            # Imaginging they are maybe monitoring their transaction history
            # Or happen to be checking one thing or another
            if random.random() < j/100:
                fraud()
            
    return transactions



    











In [10]:



    


generate_people(3)



    


















    
Out[10]:











  
    

      
      id
      name
      age
      address
      compromised
      compromised_time
    

  
  
    

      0
      0
      Erin Burton
      51
      00076 Warren Inlet, North Justinchester, IN 97410
      0
      0
    

    

      1
      1
      Robert Bush
      56
      528 Duran Port, Ericland, TX 14494-3816
      0
      0
    

    

      2
      2
      Scott Hansen
      63
      49906 Rivera Rest Suite 699, East Daniel, AS 5...
      0
      0
    

  




















In [12]:



    


generate_business(3)



    


















    






---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-12-44df4dda289a> in <module>()
----> 1 generate_business(3)

<ipython-input-11-1768d55b910a> in generate_business(n, fraudster_likelihood)
     16     fraudsters = [1 if random.random() < fraudster_likelihood else 0 for n in range(n) ]
     17 
---> 18     df = pd.DataFrame([ids, names.name, addresses]).T
     19     df.columns = ['id', 'name', 'address']
     20     return df

/usr/local/lib/python3.6/site-packages/pandas/core/generic.py in __getattr__(self, name)
   3079             if name in self._info_axis:
   3080                 return self[name]
-> 3081             return object.__getattribute__(self, name)
   3082 
   3083     def __setattr__(self, name, value):

AttributeError: 'DataFrame' object has no attribute 'name'
















In [13]:



    


p = generate_people(100)
b = generate_business(3000)
b



    


















    
Out[13]:











  
    

      
      id
      name
      label
      address
    

  
  
    

      0
      0
      Rifle Paper Co.
      Stationery
      Unit 0267 Box 4738, DPO AA 00004-9305
    

    

      1
      1
      Parker Pen Company
      Stationery
      5644 Rachel Mills, North Sandyfort, WY 55999-3065
    

    

      2
      2
      FANCL International, Inc.
      Beauty
      USNV Sutton, FPO AA 70850-3992
    

    

      3
      3
      McGraw-Hill Education
      Education
      177 Fleming Knolls Suite 937, Geoffreyborough,...
    

    

      4
      4
      Chinese TAL Education Group
      Education
      0935 Kimberly Pike, Michaelstad, KY 21575
    

    

      5
      5
      Netflix, Inc.
      Media
      12856 Joseph Island, South Joshua, OK 89872
    

    

      6
      6
      Balenciaga
      Clothing
      USCGC Hall, FPO AA 46989
    

    

      7
      7
      Netflix, Inc.
      Media
      674 Henry Passage, Gardnerchester, PR 67737
    

    

      8
      8
      Broadway Cinematheque
      Entertainment
      4147 Andrea Rue, Lake Sarah, MD 11984-4336
    

    

      9
      9
      J. Crew
      Clothing
      05383 Robertson Lock Suite 509, Nguyenton, PW ...
    

    

      10
      10
      Clarins.
      Beauty
      4199 Bethany Freeway, Carlyhaven, NY 89876-0476
    

    

      11
      11
      Shiseido Company, Limited
      Beauty
      62465 Christian Hills Apt. 994, East Davidside...
    

    

      12
      12
      Café de Coral
      Dining
      064 Barry Road, Sullivanborough, OR 69414
    

    

      13
      13
      Citybus Limited
      Transport
      700 Oneal Expressway, Harrisonbury, TX 24317-1515
    

    

      14
      14
      Sa Sa Cosmetic Co. Ltd.
      Beauty
      0067 Amy Skyway Apt. 213, Millerstad, VT 70538...
    

    

      15
      15
      Hong Kong Dragon Airlines Ltd
      Transport
      USS Kelly, FPO AA 17443
    

    

      16
      16
      Neway Karaoke Box Limited
      Entertainment
      Unit 3861 Box 5262, DPO AP 24658
    

    

      17
      17
      VR Arena
      Entertainment
      8760 Deborah Stravenue, Juliehaven, LA 01159
    

    

      18
      18
      Liberty Stationery Corp.
      Stationery
      161 Mary Mews, Lake Angelica, TX 95569-7355
    

    

      19
      19
      G2000
      Clothing
      Unit 6164 Box 1429, DPO AP 46897-2124
    

    

      20
      20
      Tesco PLC
      Grocery
      9359 Cheyenne Haven, Rebeccashire, MS 18285
    

    

      21
      21
      Ryze Ultimate Trampoline Park Hong Kong
      Entertainment
      PSC 1586, Box 7570, APO AP 19954-0216
    

    

      22
      22
      Louis Vuitton
      Clothing
      305 Leslie Canyon Suite 216, Lake Tyler, WI 12880
    

    

      23
      23
      Rainbow Department Store Company Limited
      Grocery
      PSC 1409, Box 7654, APO AP 60702
    

    

      24
      24
      The Dairy Farm Company, Limited
      Grocery
      8287 Dyer Curve Suite 275, Lake Benjaminview, ...
    

    

      25
      25
      Udemy, Inc.
      Education
      PSC 5336, Box 3428, APO AP 48005-1288
    

    

      26
      26
      J. Crew
      Clothing
      6366 Sara Garden Apt. 220, Donaldfurt, NJ 3431...
    

    

      27
      27
      Xiami.com
      Media
      6223 Amanda Squares, Westhaven, AK 80593
    

    

      28
      28
      Spotify AB
      Media
      9584 Brandon Underpass Apt. 562, New Audreymou...
    

    

      29
      29
      Nike
      Clothing
      PSC 1292, Box 2093, APO AP 75747-9304
    

    

      ...
      ...
      ...
      ...
      ...
    

    

      2970
      2970
      Code School LLC.
      Education
      USS Tran, FPO AE 69030-1549
    

    

      2971
      2971
      Tarena International, Inc.
      Education
      4586 Harrell Lodge, North Danielborough, WI 14238
    

    

      2972
      2972
      Dior Beauty
      Beauty
      34261 Thomas Track Apt. 653, Tinaborough, MD 4...
    

    

      2973
      2973
      HA cube
      Entertainment
      43089 Dalton Squares, East Alyssaland, ND 08344
    

    

      2974
      2974
      PILOT CORPORATION
      Stationery
      275 Theresa Knolls, South Bryan, OR 64085
    

    

      2975
      2975
      The Dairy Farm Company, Limited
      Grocery
      9276 Amanda Island, Jessicaton, MP 07156-3929
    

    

      2976
      2976
      Memrise Inc.
      Education
      6711 West Cliffs, Port Thomas, OH 24506
    

    

      2977
      2977
      Sun Life Financial Inc.
      Investment
      42711 Andrew Ridge, North Meghan, MP 39941
    

    

      2978
      2978
      Sun Life Financial Inc.
      Investment
      PSC 0884, Box 0782, APO AP 90531
    

    

      2979
      2979
      Voya Financial, Inc.
      Investment
      561 Moreno Manor Apt. 041, Henryville, VA 2779...
    

    

      2980
      2980
      Carrefour SA
      Grocery
      186 Anthony Manor, Bakermouth, IA 34596
    

    

      2981
      2981
      Walt Disney Company
      Entertainment
      0182 David Mount Suite 087, Daniellemouth, CT ...
    

    

      2982
      2982
      Xiami.com
      Media
      2127 Amber Crossroad, New Joelbury, RI 38726
    

    

      2983
      2983
      Pacific Coffee Company
      Dining
      986 Williams Coves, Derrickton, WV 04542
    

    

      2984
      2984
      HA cube
      Entertainment
      523 Jenkins Ford, Joelhaven, WV 26193-3040
    

    

      2985
      2985
      Uber
      Transport
      USNV Walker, FPO AA 89517
    

    

      2986
      2986
      Publix Super Markets
      Grocery
      2052 Hector Rapid Apt. 438, Washingtonburgh, N...
    

    

      2987
      2987
      McGraw-Hill Education
      Education
      USNV Moran, FPO AA 84580
    

    

      2988
      2988
      Dior Beauty
      Beauty
      0656 Jones Flat, Hawkinsstad, PA 73585
    

    

      2989
      2989
      PILOT CORPORATION
      Stationery
      2558 Robert Mall, West Samuelstad, LA 64925-6151
    

    

      2990
      2990
      KKBOX
      Media
      8550 Johnson Street, Joyside, GU 09637-3351
    

    

      2991
      2991
      The PNC Financial Services Group, Inc.
      Investment
      812 Audrey Mission, Andreaburgh, NV 19390
    

    

      2992
      2992
      Superdry
      Clothing
      819 Rebecca Landing Apt. 442, New Jennifer, SD...
    

    

      2993
      2993
      Nike
      Clothing
      915 Garcia Neck Apt. 290, Jonesbury, MH 83434
    

    

      2994
      2994
      Air China Airlines
      Transport
      7296 Rios Forks Suite 882, Loribury, DC 15051-...
    

    

      2995
      2995
      Converse
      Clothing
      278 George Courts, East Tomstad, OH 52807-5075
    

    

      2996
      2996
      Hong Kong Express Airways Limited
      Transport
      PSC 0780, Box 2684, APO AE 36278-5969
    

    

      2997
      2997
      Din Tai Fung
      Dining
      237 Richardson Lake, Bradleyshire, PW 97352-0681
    

    

      2998
      2998
      Broadway Cinematheque
      Entertainment
      3537 Hernandez Springs Suite 347, Smithchester...
    

    

      2999
      2999
      SOGO Limited.
      Grocery
      37840 Meyer Throughway, Marcomouth, MA 22015
    

  



3000 rows × 4 columns



















In [16]:



    


transactionDf = generate_normal_transactions(p,b)
transactionDf



    


















    
Out[16]:











  
    

      
      time
      name
      gender
      age
      company name
      company label
      amount
    

  
  
    

      0
      2017-06-12 08:30:36
      Kathryn King
      female
      26
      Sa Sa Cosmetic Co. Ltd.
      Beauty
      263.48
    

    

      1
      2017-06-22 04:35:23
      Kathryn King
      female
      26
      Sizzler
      Dining
      262.65
    

    

      2
      2017-07-03 07:45:55
      Kathryn King
      female
      26
      Nintendo
      Entertainment
      287.86
    

    

      3
      2017-06-30 09:52:34
      Kathryn King
      female
      26
      Zara
      Clothing
      89.23
    

    

      4
      2017-06-09 15:30:12
      Kathryn King
      female
      26
      Pearson plc
      Education
      104.38
    

    

      5
      2017-06-16 12:42:59
      Kathryn King
      female
      26
      UA Cinema Circuit Limited
      Entertainment
      50.31
    

    

      6
      2017-06-22 00:13:27
      Kathryn King
      female
      26
      Sephora USA, Inc.
      Beauty
      40.1
    

    

      7
      2017-06-22 07:12:50
      Kathryn King
      female
      26
      Tim Ho Wan
      Dining
      197.74
    

    

      8
      2017-06-25 21:26:56
      Kathryn King
      female
      26
      Rainbow Department Store Company Limited
      Grocery
      94.67
    

    

      9
      2017-06-23 22:09:02
      Kathryn King
      female
      26
      Voya Financial, Inc.
      Investment
      165.27
    

    

      10
      2017-06-27 08:04:20
      Kathryn King
      female
      26
      Longchamp
      Clothing
      187.36
    

    

      11
      2017-06-12 02:35:57
      Kathryn King
      female
      26
      L'Oreal SA
      Beauty
      29.54
    

    

      12
      2017-07-05 17:18:49
      Kathryn King
      female
      26
      Mass Transit Railway (MTR)
      Transport
      169.79
    

    

      13
      2017-07-03 16:09:22
      Kathryn King
      female
      26
      Parker Pen Company
      Stationery
      50.86
    

    

      14
      2017-06-09 13:18:41
      Kathryn King
      female
      26
      Udemy, Inc.
      Education
      106.89
    

    

      15
      2017-06-14 04:22:33
      Kathryn King
      female
      26
      The Kowloon Motor Bus Company Limited
      Transport
      238.05
    

    

      16
      2017-06-18 21:01:31
      Kathryn King
      female
      26
      Udacity, Inc.
      Education
      108.45
    

    

      17
      2017-06-14 10:57:38
      Kathryn King
      female
      26
      A.S. Watson Group (Hong Kong) Ltd.
      Grocery
      249.53
    

    

      18
      2017-06-07 17:24:06
      Kathryn King
      female
      26
      2U, Inc.
      Education
      81.53
    

    

      19
      2017-06-10 06:13:31
      Tracy Wilkerson
      female
      36
      Mannings.
      Grocery
      132.75
    

    

      20
      2017-06-15 14:21:44
      Tracy Wilkerson
      female
      36
      Colourmix Cosmetics Company Limited
      Beauty
      300.48
    

    

      21
      2017-07-05 22:23:16
      Tracy Wilkerson
      female
      36
      Air China Airlines
      Transport
      93.7
    

    

      22
      2017-06-10 04:22:02
      Tracy Wilkerson
      female
      36
      KIKO Asia Ltd.
      Beauty
      285.06
    

    

      23
      2017-06-27 06:30:12
      Tracy Wilkerson
      female
      36
      Burger King
      Dining
      199.24
    

    

      24
      2017-07-01 09:24:00
      Tracy Wilkerson
      female
      36
      Laura Mercier Cosmetics.
      Beauty
      114.03
    

    

      25
      2017-06-15 22:06:22
      Tracy Wilkerson
      female
      36
      Uber
      Transport
      146.56
    

    

      26
      2017-06-13 22:14:19
      Tracy Wilkerson
      female
      36
      Best Buy Co Inc
      Grocery
      290.2
    

    

      27
      2017-06-22 17:30:50
      Tracy Wilkerson
      female
      36
      Louis Vuitton
      Clothing
      243.57
    

    

      28
      2017-06-30 10:38:54
      Tracy Wilkerson
      female
      36
      Converse
      Clothing
      151.39
    

    

      29
      2017-06-08 04:26:50
      Tracy Wilkerson
      female
      36
      TCF Financial Corporation
      Investment
      29.33
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      2193
      2017-06-30 16:14:03
      Jason Martinez
      male
      28
      Pearson plc
      Education
      244.28
    

    

      2194
      2017-06-17 02:29:34
      Jason Martinez
      male
      28
      Parker Pen Company
      Stationery
      149.44
    

    

      2195
      2017-06-09 07:57:31
      Jason Martinez
      male
      28
      Longchamp
      Clothing
      262.6
    

    

      2196
      2017-06-30 22:20:48
      Jason Martinez
      male
      28
      Liberty Stationery Corp.
      Stationery
      161.36
    

    

      2197
      2017-06-12 11:06:04
      Jason Martinez
      male
      28
      Shiseido Company, Limited
      Beauty
      178.98
    

    

      2198
      2017-06-07 08:39:30
      Jason Martinez
      male
      28
      Yadkin Financial Corporation
      Investment
      107.68
    

    

      2199
      2017-06-25 04:58:03
      Jason Martinez
      male
      28
      Burger King
      Dining
      246.93
    

    

      2200
      2017-06-26 06:12:23
      Jason Martinez
      male
      28
      Principal Financial Group Inc
      Investment
      231.46
    

    

      2201
      2017-06-19 15:35:18
      Jason Martinez
      male
      28
      Zara
      Clothing
      211.81
    

    

      2202
      2017-06-08 22:54:53
      Jason Martinez
      male
      28
      Costco Wholesale Corporation
      Grocery
      225.86
    

    

      2203
      2017-06-28 19:11:05
      Jason Martinez
      male
      28
      Subway
      Dining
      247.58
    

    

      2204
      2017-06-08 09:49:45
      Stephanie Reynolds
      female
      32
      Vudu, Inc.
      Media
      225.06
    

    

      2205
      2017-07-05 02:25:37
      Stephanie Reynolds
      female
      32
      Din Tai Fung
      Dining
      247.2
    

    

      2206
      2017-06-22 18:21:15
      Stephanie Reynolds
      female
      32
      A.S. Watson Group (Hong Kong) Ltd.
      Grocery
      130.56
    

    

      2207
      2017-06-28 14:58:55
      Stephanie Reynolds
      female
      32
      HA cube
      Entertainment
      163.83
    

    

      2208
      2017-06-28 03:04:31
      Stephanie Reynolds
      female
      32
      Peak Tramways Company Limited
      Transport
      283.41
    

    

      2209
      2017-06-26 05:27:48
      Stephanie Reynolds
      female
      32
      Maped SAS
      Stationery
      88.2
    

    

      2210
      2017-06-14 06:02:26
      Stephanie Reynolds
      female
      32
      Webster Financial Corporation
      Investment
      191.24
    

    

      2211
      2017-07-02 11:55:44
      Stephanie Reynolds
      female
      32
      Faber-Castell
      Stationery
      108.65
    

    

      2212
      2017-07-05 06:12:44
      Stephanie Reynolds
      female
      32
      Balenciaga
      Clothing
      264.47
    

    

      2213
      2017-06-19 06:13:19
      Stephanie Reynolds
      female
      32
      China Distance Education Hldgs Ltd
      Education
      147.92
    

    

      2214
      2017-06-20 09:50:12
      Stephanie Reynolds
      female
      32
      Citybus Limited
      Transport
      19.32
    

    

      2215
      2017-06-21 13:28:16
      Stephanie Reynolds
      female
      32
      Mannings.
      Grocery
      274.92
    

    

      2216
      2017-06-13 20:01:15
      Stephanie Reynolds
      female
      32
      Spotify AB
      Media
      216.02
    

    

      2217
      2017-06-25 15:28:02
      Stephanie Reynolds
      female
      32
      Walt Disney Company
      Entertainment
      177.13
    

    

      2218
      2017-06-11 20:45:42
      Stephanie Reynolds
      female
      32
      HA cube
      Entertainment
      83.83
    

    

      2219
      2017-06-24 20:58:47
      Stephanie Reynolds
      female
      32
      Pearson plc
      Education
      191.7
    

    

      2220
      2017-06-11 18:16:08
      Stephanie Reynolds
      female
      32
      Nike
      Clothing
      179.19
    

    

      2221
      2017-06-22 08:47:39
      Stephanie Reynolds
      female
      32
      ZAIS Financial Corp.
      Investment
      289.62
    

    

      2222
      2017-06-20 13:27:43
      Stephanie Reynolds
      female
      32
      Synovus Financial Corp.
      Investment
      125.98
    

  



2223 rows × 7 columns



















In [79]:



    


np.mean(list(transactionDf.age))
transactionDf = transactionDf[['time','name','age','company name', 'company label', 'amount']]
transactionDf.to_csv('transaction.csv', index=False)



    











In [80]:



    


df = pd.read_csv('transaction.csv')
df



    


















    
Out[80]:











  
    

      
      time
      name
      age
      company name
      company label
      amount
    

  
  
    

      0
      2017-06-14 10:01:38
      Jennifer Strickland
      50
      Shiseido Company, Limited
      Beauty
      206.13
    

    

      1
      2017-07-02 07:20:13
      Jennifer Strickland
      50
      Yoshinoya
      Dining
      200.84
    

    

      2
      2017-06-30 18:11:29
      Jennifer Strickland
      50
      Converse
      Clothing
      188.42
    

    

      3
      2017-06-06 20:59:09
      Jennifer Strickland
      50
      The Dairy Farm Company, Limited
      Grocery
      275.78
    

    

      4
      2017-06-13 02:26:17
      Jennifer Strickland
      50
      Waddell & Reed Financial, Inc.
      Investment
      51.27
    

    

      5
      2017-06-21 06:57:14
      Jennifer Strickland
      50
      Maped SAS
      Stationery
      56.14
    

    

      6
      2017-06-15 22:56:50
      Jennifer Strickland
      50
      Waddell & Reed Financial, Inc.
      Investment
      240.68
    

    

      7
      2017-06-13 09:41:39
      Jennifer Strickland
      50
      Long Win Bus Company Limited
      Transport
      197.07
    

    

      8
      2017-06-20 13:28:07
      Jennifer Strickland
      50
      Sakura Color Products Corporation
      Stationery
      51.86
    

    

      9
      2017-06-09 07:21:32
      Jennifer Strickland
      50
      HA cube
      Entertainment
      124.35
    

    

      10
      2017-06-21 13:31:27
      Jennifer Strickland
      50
      Derma Skincare Centre
      Beauty
      126.00
    

    

      11
      2017-06-23 09:55:13
      Jennifer Strickland
      50
      New World First Bus Services Limited
      Transport
      16.03
    

    

      12
      2017-06-25 08:26:21
      Jennifer Strickland
      50
      Xbox
      Entertainment
      137.61
    

    

      13
      2017-06-22 10:22:37
      Jennifer Strickland
      50
      McGraw-Hill Education
      Education
      245.85
    

    

      14
      2017-06-15 08:50:57
      Jennifer Strickland
      50
      Pearson plc
      Education
      234.29
    

    

      15
      2017-06-14 16:32:38
      Jennifer Strickland
      50
      Societe B I C SA
      Stationery
      104.60
    

    

      16
      2017-06-09 15:39:00
      Jennifer Strickland
      50
      Nintendo
      Entertainment
      195.11
    

    

      17
      2017-06-30 06:29:43
      Jennifer Strickland
      50
      H&M Hennes & Mauritz AB
      Clothing
      206.60
    

    

      18
      2017-06-08 21:43:40
      Jennifer Strickland
      50
      Sephora USA, Inc.
      Beauty
      208.17
    

    

      19
      2017-06-29 23:11:08
      Jennifer Strickland
      50
      3M Company
      Stationery
      212.72
    

    

      20
      2017-06-06 17:08:35
      Jennifer Strickland
      50
      Yoshinoya
      Dining
      45.49
    

    

      21
      2017-06-25 03:01:08
      Jennifer Strickland
      50
      Rainbow Department Store Company Limited
      Grocery
      112.65
    

    

      22
      2017-06-15 04:15:29
      Jennifer Strickland
      50
      City Super Limited
      Grocery
      299.08
    

    

      23
      2017-06-27 13:08:19
      Jennifer Strickland
      50
      Ikari Area
      Entertainment
      162.76
    

    

      24
      2017-07-04 17:52:11
      Jennifer Strickland
      50
      Wal-Mart Stores Inc
      Grocery
      37.47
    

    

      25
      2017-06-10 03:06:25
      Jennifer Strickland
      50
      Webster Financial Corporation
      Investment
      27.00
    

    

      26
      2017-06-28 18:40:06
      Jennifer Strickland
      50
      New Oriental Education & Tech Grp
      Education
      273.95
    

    

      27
      2017-07-01 20:30:44
      Jennifer Strickland
      50
      Superdry
      Clothing
      281.21
    

    

      28
      2017-06-26 18:53:31
      Jennifer Strickland
      50
      FANCL International, Inc.
      Beauty
      225.08
    

    

      29
      2017-06-14 08:16:39
      Jennifer Strickland
      50
      Ikari Area
      Entertainment
      111.45
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      2016
      2017-06-26 02:55:05
      Reginald Lee
      32
      Dior Beauty
      Beauty
      63.55
    

    

      2017
      2017-06-13 15:45:33
      Reginald Lee
      32
      McGraw-Hill Education
      Education
      248.55
    

    

      2018
      2017-06-17 11:53:37
      Reginald Lee
      32
      Wing Wah
      Dining
      260.77
    

    

      2019
      2017-06-22 04:22:25
      Reginald Lee
      32
      J. Crew
      Clothing
      26.41
    

    

      2020
      2017-06-27 15:16:45
      Reginald Lee
      32
      iQIYI.COM
      Media
      101.52
    

    

      2021
      2017-06-25 19:20:32
      Reginald Lee
      32
      Liberty Stationery Corp.
      Stationery
      62.75
    

    

      2022
      2017-06-17 20:57:28
      Reginald Lee
      32
      Stifel Financial Corporation
      Investment
      84.47
    

    

      2023
      2017-07-05 08:46:49
      Reginald Lee
      32
      edX Inc.
      Education
      237.93
    

    

      2024
      2017-06-27 02:31:05
      Reginald Lee
      32
      Crackle, Inc.
      Media
      208.93
    

    

      2025
      2017-06-27 20:13:06
      Reginald Lee
      32
      QQ Music
      Media
      147.62
    

    

      2026
      2017-06-25 11:41:44
      Reginald Lee
      32
      Ikari Area
      Entertainment
      110.86
    

    

      2027
      2017-06-29 07:07:24
      Reginald Lee
      32
      The Dairy Farm Company, Limited
      Grocery
      86.13
    

    

      2028
      2017-06-20 00:04:37
      Reginald Lee
      32
      Neway Karaoke Box Limited
      Entertainment
      200.52
    

    

      2029
      2017-06-11 21:46:17
      Reginald Lee
      32
      KFC
      Dining
      149.41
    

    

      2030
      2017-07-02 15:35:32
      Reginald Lee
      32
      SOGO Limited.
      Grocery
      49.76
    

    

      2031
      2017-06-25 14:58:33
      Reginald Lee
      32
      New Oriental Education & Tech Grp
      Education
      124.48
    

    

      2032
      2017-07-05 04:17:01
      Reginald Lee
      32
      Red MR Limited
      Entertainment
      57.59
    

    

      2033
      2017-06-06 18:44:13
      Reginald Lee
      32
      Home Box Office Inc.
      Media
      37.66
    

    

      2034
      2017-06-16 15:54:56
      Reginald Lee
      32
      Sa Sa Cosmetic Co. Ltd.
      Beauty
      290.76
    

    

      2035
      2017-06-30 16:16:37
      Reginald Lee
      32
      Tarena International, Inc.
      Education
      30.53
    

    

      2036
      2017-06-28 02:14:28
      Reginald Lee
      32
      Citybus Limited
      Transport
      262.21
    

    

      2037
      2017-06-11 04:01:11
      Reginald Lee
      32
      Nintendo
      Entertainment
      248.80
    

    

      2038
      2017-06-15 09:46:17
      Reginald Lee
      32
      KFC
      Dining
      77.76
    

    

      2039
      2017-06-23 17:03:10
      Reginald Lee
      32
      RAIT Financial Trust
      Investment
      249.50
    

    

      2040
      2017-06-29 22:41:56
      Reginald Lee
      32
      Rifle Paper Co.
      Stationery
      125.41
    

    

      2041
      2017-06-27 00:11:35
      Reginald Lee
      32
      Walt Disney Company
      Entertainment
      50.92
    

    

      2042
      2017-07-04 09:45:34
      Reginald Lee
      32
      Adidas
      Clothing
      62.26
    

    

      2043
      2017-07-05 23:19:20
      Reginald Lee
      32
      Shiseido Company, Limited
      Beauty
      76.30
    

    

      2044
      2017-06-21 04:35:56
      Reginald Lee
      32
      Pizza Hut
      Dining
      73.11
    

    

      2045
      2017-06-27 10:24:09
      Reginald Lee
      32
      Hong Kong Dragon Airlines Ltd
      Transport
      187.64
    

  



2046 rows × 6 columns



















In [18]:



    


len(t) + len(f)



    


















    
Out[18]:








1927

















In [19]:



    


t.extend(f)
len(t)



    


















    
Out[19]:








1927

















In [20]:



    


with open('output.log', 'w') as f:
    for line in t:
        f.write(line)
        f.write('\n')



    











In [21]:



    


! ls



    


















    






LICENSE                                credit-card-fraud-data-generator.ipynb
README.md                              output.log
companies.csv                          requirements.txt

















In [22]:



    


! head output.log



    


















    






2017-07-02 12:17:52 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Emergent Biosolutions, Inc." amount=267.69 disputed=false
2017-07-02 12:18:03 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Blackrock Core Bond Trust" amount=245.13 disputed=false
2017-07-02 12:18:03 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Phillips 66 Partners LP" amount=160.64 disputed=false
2017-07-02 12:17:40 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Kimberly-Clark Corporation" amount=148.37 disputed=false
2017-07-02 12:17:37 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Seaspan Corporation" amount=233.69 disputed=false
2017-07-02 12:17:56 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Time Warner Inc." amount=164.46 disputed=false
2017-07-02 12:18:13 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Flaherty & Crumrine Preferred Income Opportunity Fund Inc" amount=232.47 disputed=false
2017-07-02 12:17:32 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="Stone Energy Corporation" amount=165.0 disputed=false
2017-07-02 12:17:36 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="TELUS Corporation" amount=123.96 disputed=false
2017-07-02 12:17:28 uuid=6a8d3fa6-e47e-4c59-a469-c2a4a4ac4247 user="Lisa Henderson" business="SunCoke Energy, Inc." amount=111.38 disputed=false

Content source: FinHackChamp/FinHack

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