2 Read Files

data

data

2.1 Accounts

Relation account (4500 objects in the file ACCOUNT.ASC) each record describes static characteristics of an account:

Table 2.1: accounts frame
account_id district_id frequency date
576 55 monthly 1993-01-01
3818 74 monthly 1993-01-01
704 55 monthly 1993-01-01
2378 16 monthly 1993-01-01
2632 24 monthly 1993-01-02
1972 77 monthly 1993-01-02
1539 1 after transaction 1993-01-03
793 47 monthly 1993-01-03
2484 74 monthly 1993-01-03
1695 76 monthly 1993-01-03

2.2 Clients

Relation client (5369 objects in the file CLIENT.ASC) each record describes characteristics of a client:

Table 2.2: clients frame
client_id birth_number district_id gender_code gender birth_date
1 706213 18 1 W 1970-12-13
2 450204 1 0 M 1945-02-04
3 406009 1 1 W 1940-10-09
4 561201 5 0 M 1956-12-01
5 605703 5 1 W 1960-07-03
6 190922 12 0 M 1919-09-22
7 290125 15 0 M 1929-01-25
8 385221 51 1 W 1938-02-21
9 351016 60 0 M 1935-10-16
10 430501 57 0 M 1943-05-01

2.3 Disposition

Relation disposition (5369 objects in the file DISP.ASC) each record relates together a client with an account i.e. this relation describes the rights of clients to operate accounts:

Table 2.3: disposition frame
disp_id client_id account_id type
1 1 1 OWNER
2 2 2 OWNER
3 3 2 DISPONENT
4 4 3 OWNER
5 5 3 DISPONENT
6 6 4 OWNER
7 7 5 OWNER
8 8 6 OWNER
9 9 7 OWNER
10 10 8 OWNER

2.4 Order

Relation permanent order (6471 objects in the file ORDER.ASC) each record describes characteristics of a payment order:

Table 2.4: order frame
order_id account_id bank_to account_to amount k_symbol
29401 1 YZ 87144583 2452.0 household
29402 2 ST 89597016 3372.7 loan
29403 2 QR 13943797 7266.0 household
29404 3 WX 83084338 1135.0 household
29405 3 CD 24485939 327.0
29406 3 AB 59972357 3539.0 insurrance
29407 4 UV 26693541 2078.0 household
29408 4 UV 5848086 1285.0 household
29409 5 GH 37390208 2668.0 household
29410 6 AB 44486999 3954.0 household

2.5 Transactions

Relation transaction (1056320 objects in the file TRANS.ASC) each record describes one transaction on an account:

Table 2.5: transaction frame
trans_id account_id date type operation amount balance k_symbol bank account
695247 2378 1993-01-01 credit credit in cash 700 700 NA
171812 576 1993-01-01 credit credit in cash 900 900 NA
207264 704 1993-01-01 credit credit in cash 1000 1000 NA
1117247 3818 1993-01-01 credit credit in cash 600 600 NA
579373 1972 1993-01-02 credit credit in cash 400 400 NA
771035 2632 1993-01-02 credit credit in cash 1100 1100 NA
452728 1539 1993-01-03 credit credit in cash 600 600 NA
725751 2484 1993-01-03 credit credit in cash 1100 1100 NA
497211 1695 1993-01-03 credit credit in cash 200 200 NA
232960 793 1993-01-03 credit credit in cash 800 800 NA

2.6 Loans

Relation loan (682 objects in the file LOAN.ASC) each record describes a loan granted for a given account:

Table 2.6: loan frame
loan_id account_id date amount duration payments status
5314 1787 1993-07-05 96396 12 8033 B
5316 1801 1993-07-11 165960 36 4610 A
6863 9188 1993-07-28 127080 60 2118 A
5325 1843 1993-08-03 105804 36 2939 A
7240 11013 1993-09-06 274740 60 4579 A
6687 8261 1993-09-13 87840 24 3660 A
7284 11265 1993-09-15 52788 12 4399 A
6111 5428 1993-09-24 174744 24 7281 B
7235 10973 1993-10-13 154416 48 3217 A
5997 4894 1993-11-04 117024 24 4876 A

2.7 Credit Card

Relation credit card (892 objects in the file CARD.ASC) each record describes a credit card issued to an account:

Table 2.7: card frame
card_id disp_id type issued
1005 9285 classic 1993-11-07
104 588 classic 1994-01-19
747 4915 classic 1994-02-05
70 439 classic 1994-02-08
577 3687 classic 1994-02-15
377 2429 classic 1994-03-03
721 4680 junior 1994-04-05
437 2762 classic 1994-06-01
188 1146 classic 1994-06-19
13 87 classic 1994-06-29

2.8 Demographic data

Relation demographic data (77 objects in the file DISTRICT.ASC) each record describes demographic characteristics of a district:

Table 2.8: demographic frame
district_id district_name region inhabitants n_size_1 n_size_2 n_size_3 n_size_4 n_cities ratio of urban inhabitants average salary unemploymant rate ’95 unemploymant rate ’96 enterpreneurs per 1000 inhabitants commited crimes ’95 commited crimes ’96
1 Hl.m. Praha Prague 1204953 0 0 0 1 1 100.0 12541 0.29 0.43 167 85677 99107
2 Benesov central Bohemia 88884 80 26 6 2 5 46.7 8507 1.67 1.85 132 2159 2674
3 Beroun central Bohemia 75232 55 26 4 1 5 41.7 8980 1.95 2.21 111 2824 2813
4 Kladno central Bohemia 149893 63 29 6 2 6 67.4 9753 4.64 5.05 109 5244 5892
5 Kolin central Bohemia 95616 65 30 4 1 6 51.4 9307 3.85 4.43 118 2616 3040
6 Kutna Hora central Bohemia 77963 60 23 4 2 4 51.5 8546 2.95 4.02 126 2640 3120
7 Melnik central Bohemia 94725 38 28 1 3 6 63.4 9920 2.26 2.87 130 4289 4846
8 Mlada Boleslav central Bohemia 112065 95 19 7 1 8 69.4 11277 1.25 1.44 127 5179 4987
9 Nymburk central Bohemia 81344 61 23 4 2 6 55.3 8899 3.39 3.97 149 2987 2487
10 Praha - vychod central Bohemia 92084 55 29 4 3 5 46.7 10124 0.56 0.54 141 3810 4316