Datasets:
MinaMila
/
GermanCredit_train_lr_42

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status of existing checking account_0 to less than 200 DM
int64
0
1
status of existing checking account_200 DM or more
int64
0
1
status of existing checking account_less than 0 DM
int64
0
1
status of existing checking account_no checking account
int64
0
1
purpose of credit_for business
int64
0
1
purpose of credit_for education
int64
0
1
purpose of credit_for other reasons
int64
0
1
purpose of credit_for repairs
int64
0
1
purpose of credit_for retraining
int64
0
1
purpose of credit_to buy a new car
int64
0
1
purpose of credit_to buy a radio or television
int64
0
1
purpose of credit_to buy a used car
int64
0
1
purpose of credit_to buy domestic appliances
int64
0
1
purpose of credit_to buy furniture or equipment
int64
0
1
sex_Male
int64
0
1
housing_owned
int64
0
1
housing_provided for free
int64
0
1
housing_rented
int64
0
1
job status_manager, self-employed, or highly qualified
int64
0
1
job status_skilled worker or official
int64
0
1
job status_unemployed or unskilled (non-resident)
int64
0
1
job status_unskilled worker (resident)
int64
0
1
marital status_divorced / separated
int64
0
1
marital status_divorced / separated / married
int64
0
1
marital status_married / widowed
int64
0
1
marital status_single
int64
0
1
duration in months
int64
4
72
credit amount
int64
250
18.4k
age
int64
20
75
label
int64
0
1
1
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0
0
0
0
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1
42
9,283
55
1
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18
3,190
24
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1
1
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1
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1
30
1,867
58
1
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1
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0
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1
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1
24
6,579
29
1
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1
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1
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0
1
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1
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1
45
11,816
29
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1
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1
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1
0
0
33
4,281
23
0
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3,386
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15
2,788
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1
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0
1
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0
0
0
0
1
0
0
0
0
1
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1
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0
0
1
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9
1,236
23
1
1
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1
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1
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12
1,158
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1
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1
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6
1,554
24
1
1
0
0
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0
0
0
0
1
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0
0
0
1
0
0
0
1
0
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1
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12
2,930
27
1
0
0
0
1
0
0
0
0
0
0
1
0
0
0
1
1
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1
18
1,800
24
1
0
0
1
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0
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0
1
1
1
0
0
0
1
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0
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1
36
3,620
37
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
1
1
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0
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1
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1
36
5,800
34
1
0
0
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1
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0
1
1
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12
1,413
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1
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0
1
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1
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1
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1
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1
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15
2,186
33
1
0
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1
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1
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1
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1
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1
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30
3,622
57
1
0
1
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1
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1
1
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1
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1
12
3,399
37
1
1
0
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0
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0
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0
0
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0
1
1
1
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0
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1
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0
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1
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30
3,832
22
1
0
0
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1
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1
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1
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1
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1
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36
3,349
28
0
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1
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1
10
1,038
49
1
0
0
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1
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1
1
0
1
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1
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1
15
3,343
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1
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1
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1
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1
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1
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1
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12
1,200
23
1
1
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1
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1
1
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0
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1
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1
15
1,308
38
1
1
0
0
0
0
0
0
0
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1
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1
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1
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12
836
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0
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1
1
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1
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1
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1
6
1,872
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1
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1
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1
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1
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1
18
2,775
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1
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24
1,024
48
0
1
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1,237
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30
6,187
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1
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1
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6
1,198
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11,328
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12,749
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1
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7,119
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1
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4
1,544
42
1
0
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1
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1
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1
1
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1
54
9,436
39
1
0
0
0
1
1
0
0
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0
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0
0
0
0
1
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0
1
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12
1,412
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1
1
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12
2,969
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1
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1
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1
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30
5,234
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7,685
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6,468
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1
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1,473
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10,127
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1,240
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1,318
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3,186
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3,160
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1
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24
1,597
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3,104
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976
35
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1
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4,280
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1,893
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1
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9
1,206
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1
1
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6,078
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1
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2,223
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1
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1,559
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1
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18
1,530
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7,511
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15
1,360
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1
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1
1
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9
1,126
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1
1
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24
1,216
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1
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18
1,042
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683
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24
1,837
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9
276
22
1
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24
2,910
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18
2,169
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13
2,101
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1
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9
3,074
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1
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18
1,961
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24
947
38
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18
6,204
44
1
1
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1
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24
1,967
20
1
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3,632
22
1
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1
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1
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1
9
1,224
30
1
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1
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24
8,648
27
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12
1,282
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9
1,082
27
1
1
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48
10,961
27
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21
1,835
25
0
0
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1
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0
0
0
0
0
1
0
0
0
0
1
1
0
0
0
1
0
0
0
0
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1
24
2,325
32
1
0
0
0
1
1
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
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1
0
0
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1
24
4,139
27
1
0
0
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1
0
0
0
0
0
0
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0
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1
1
1
0
0
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1
24
3,777
50
1
0
0
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1
0
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0
0
0
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1
0
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1
1
0
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0
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24
4,042
43
1
1
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0
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0
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0
0
0
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1
1
0
0
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18
1,913
36
1
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0
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0
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1
0
0
0
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1
1
0
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1
36
10,875
45
1
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1
0
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0
0
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0
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6
1,382
28
1
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60
9,157
27
1
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6
343
27
1
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1,313
20
1
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24
1,553
23
1
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1
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15
2,708
27
1
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12
2,762
25
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26
7,966
30
1
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2,030
24
1
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1,300
45
1
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18
1,216
23
0
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12
1,995
27
1