Overview

Dataset statistics

Number of variables35
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory145.1 KiB
Average record size in memory297.3 B

Variable types

Categorical24
Text1
Numeric9
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보증유동화회사보증편입기업마스터에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092850/fileData.do

Alerts

유동화회사업무구분코드 has constant value ""Constant
편입기업고객일련번호 has constant value ""Constant
유동화편입기업계열구분코드 has constant value ""Constant
발행일자 has constant value ""Constant
만기일자 has constant value ""Constant
월별이자납입일자 has constant value ""Constant
한도금액 has constant value ""Constant
기존발행금액 has constant value ""Constant
편입일자 has constant value ""Constant
편입기업업무구분코드 has constant value ""Constant
정상화일자 has constant value ""Constant
삭제여부 has constant value ""Constant
업종차수 is highly imbalanced (93.3%)Imbalance
신용평가기관코드 is highly imbalanced (89.4%)Imbalance
기초자산종류코드 is highly imbalanced (74.0%)Imbalance
부실처리일자 is highly imbalanced (83.7%)Imbalance
대물변제일자 is highly imbalanced (93.3%)Imbalance
신용조사수수료수납기준일자 is highly imbalanced (94.7%)Imbalance
처리시각 is highly imbalanced (53.5%)Imbalance
최초처리시각 is highly imbalanced (53.2%)Imbalance
최초처리직원번호 is highly imbalanced (50.6%)Imbalance
이자금액 has 88 (17.6%) zerosZeros
해지금액 has 257 (51.4%) zerosZeros
잔액 has 238 (47.6%) zerosZeros
부실처리금액 has 488 (97.6%) zerosZeros

Reproduction

Analysis started2023-12-12 14:48:19.468055
Analysis finished2023-12-12 14:48:19.899039
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동화회사업무구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
G
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG
2nd rowG
3rd rowG
4th rowG
5th rowG

Common Values

ValueCountFrequency (%)
G 500
100.0%

Length

2023-12-12T23:48:19.974678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:20.083200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

편입기업고객ID
Text

Distinct310
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T23:48:20.367612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)24.0%

Sample

1st rowaaaaaaqd0k
2nd rowaaaaaaqd0k
3rd row9bQwlyGmWW
4th rowaaaaadabSM
5th rowaaaaaaxqnj
ValueCountFrequency (%)
aaaaaaqd0k 2
 
0.4%
aaaaacdxpk 2
 
0.4%
9bgnoagmov 2
 
0.4%
aaaaacushk 2
 
0.4%
aaaaacr6g5 2
 
0.4%
aaaaacn68u 2
 
0.4%
aaaaacbtng 2
 
0.4%
aaaaaczzsw 2
 
0.4%
aaaaaczyf8 2
 
0.4%
aaaaacvasj 2
 
0.4%
Other values (300) 480
96.0%
2023-12-12T23:48:20.844490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1768
35.4%
9 227
 
4.5%
b 226
 
4.5%
c 166
 
3.3%
d 81
 
1.6%
q 72
 
1.4%
t 64
 
1.3%
w 58
 
1.2%
k 58
 
1.2%
K 57
 
1.1%
Other values (52) 2223
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3286
65.7%
Uppercase Letter 1103
 
22.1%
Decimal Number 611
 
12.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1768
53.8%
b 226
 
6.9%
c 166
 
5.1%
d 81
 
2.5%
q 72
 
2.2%
t 64
 
1.9%
w 58
 
1.8%
k 58
 
1.8%
l 53
 
1.6%
g 52
 
1.6%
Other values (16) 688
 
20.9%
Uppercase Letter
ValueCountFrequency (%)
K 57
 
5.2%
H 52
 
4.7%
F 52
 
4.7%
S 52
 
4.7%
V 51
 
4.6%
A 49
 
4.4%
M 46
 
4.2%
I 46
 
4.2%
O 46
 
4.2%
C 46
 
4.2%
Other values (16) 606
54.9%
Decimal Number
ValueCountFrequency (%)
9 227
37.2%
4 48
 
7.9%
3 48
 
7.9%
7 48
 
7.9%
8 47
 
7.7%
0 47
 
7.7%
5 42
 
6.9%
1 38
 
6.2%
6 37
 
6.1%
2 29
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 4389
87.8%
Common 611
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1768
40.3%
b 226
 
5.1%
c 166
 
3.8%
d 81
 
1.8%
q 72
 
1.6%
t 64
 
1.5%
w 58
 
1.3%
k 58
 
1.3%
K 57
 
1.3%
l 53
 
1.2%
Other values (42) 1786
40.7%
Common
ValueCountFrequency (%)
9 227
37.2%
4 48
 
7.9%
3 48
 
7.9%
7 48
 
7.9%
8 47
 
7.7%
0 47
 
7.7%
5 42
 
6.9%
1 38
 
6.2%
6 37
 
6.1%
2 29
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1768
35.4%
9 227
 
4.5%
b 226
 
4.5%
c 166
 
3.3%
d 81
 
1.6%
q 72
 
1.4%
t 64
 
1.3%
w 58
 
1.2%
k 58
 
1.2%
K 57
 
1.1%
Other values (52) 2223
44.5%

편입기업고객일련번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-12T23:48:21.040646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:21.167333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

유동화편입기업계열구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
ZZ
500 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowZZ
2nd rowZZ
3rd rowZZ
4th rowZZ
5th rowZZ

Common Values

ValueCountFrequency (%)
ZZ 500
100.0%

Length

2023-12-12T23:48:21.296546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:21.411016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
zz 500
100.0%

업종차수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
496 
8
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 496
99.2%
8 4
 
0.8%

Length

2023-12-12T23:48:21.543114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:21.671550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 496
99.2%
8 4
 
0.8%

업종대분류코드
Categorical

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
C
249 
G
167 
F
40 
H
 
15
N
 
6
Other values (7)
 
23

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG
2nd rowG
3rd rowG
4th rowC
5th rowC

Common Values

ValueCountFrequency (%)
C 249
49.8%
G 167
33.4%
F 40
 
8.0%
H 15
 
3.0%
N 6
 
1.2%
M 6
 
1.2%
Q 5
 
1.0%
E 3
 
0.6%
J 3
 
0.6%
D 2
 
0.4%
Other values (2) 4
 
0.8%

Length

2023-12-12T23:48:21.824472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c 249
49.8%
g 167
33.4%
f 40
 
8.0%
h 15
 
3.0%
n 6
 
1.2%
m 6
 
1.2%
q 5
 
1.0%
e 3
 
0.6%
j 3
 
0.6%
d 2
 
0.4%
Other values (2) 4
 
0.8%

기업규모코드
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
3
311 
4
170 
2
 
16
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row4
4th row2
5th row2

Common Values

ValueCountFrequency (%)
3 311
62.2%
4 170
34.0%
2 16
 
3.2%
5 3
 
0.6%

Length

2023-12-12T23:48:21.983031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:22.121204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 311
62.2%
4 170
34.0%
2 16
 
3.2%
5 3
 
0.6%

신용평가기관코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
493 
2
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 493
98.6%
2 7
 
1.4%

Length

2023-12-12T23:48:22.274483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:22.426244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 493
98.6%
2 7
 
1.4%

기업신용등급코드값
Categorical

Distinct22
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
KS8
75 
KS9
73 
KS6
70 
KS10
53 
KS7
53 
Other values (17)
176 

Length

Max length4
Median length3
Mean length3.278
Min length1

Unique

Unique6 ?
Unique (%)1.2%

Sample

1st rowKS11
2nd rowKS11
3rd rowKS4
4th rowBB+
5th rowBB

Common Values

ValueCountFrequency (%)
KS8 75
15.0%
KS9 73
14.6%
KS6 70
14.0%
KS10 53
10.6%
KS7 53
10.6%
KS11 36
7.2%
KS5 31
6.2%
KS12 27
 
5.4%
KS4 27
 
5.4%
KS13 17
 
3.4%
Other values (12) 38
7.6%

Length

2023-12-12T23:48:22.586570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ks8 75
15.0%
ks9 73
14.6%
ks6 70
14.0%
ks10 53
10.6%
ks7 53
10.6%
ks11 36
7.2%
ks5 31
6.2%
ks12 27
 
5.4%
ks4 27
 
5.4%
ks13 17
 
3.4%
Other values (9) 38
7.6%

기초자산종류코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
478 
4
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 478
95.6%
4 22
 
4.4%

Length

2023-12-12T23:48:22.768736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:22.882859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 478
95.6%
4 22
 
4.4%

유동화회사보증용도코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
432 
1
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 432
86.4%
1 68
 
13.6%

Length

2023-12-12T23:48:23.017128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:23.154377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 432
86.4%
1 68
 
13.6%

발행일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T23:48:23.324548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:23.478112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

만기일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T23:48:23.646403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:23.811038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

표면이자율
Real number (ℝ)

Distinct112
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.266948
Minimum2.624
Maximum6.148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:23.962140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.624
5-th percentile2.994
Q13.524
median4.198
Q34.867
95-th percentile5.624
Maximum6.148
Range3.524
Interquartile range (IQR)1.343

Descriptive statistics

Standard deviation0.81540478
Coefficient of variation (CV)0.19109789
Kurtosis-0.83748232
Mean4.266948
Median Absolute Deviation (MAD)0.674
Skewness0.12879996
Sum2133.474
Variance0.66488495
MonotonicityNot monotonic
2023-12-12T23:48:24.171196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.324 17
 
3.4%
3.524 17
 
3.4%
3.394 17
 
3.4%
4.174 17
 
3.4%
4.288 16
 
3.2%
4.474 16
 
3.2%
3.824 15
 
3.0%
4.124 13
 
2.6%
4.724 13
 
2.6%
4.768 13
 
2.6%
Other values (102) 346
69.2%
ValueCountFrequency (%)
2.624 2
 
0.4%
2.654 1
 
0.2%
2.724 1
 
0.2%
2.794 8
1.6%
2.924 1
 
0.2%
2.928 1
 
0.2%
2.968 2
 
0.4%
2.994 11
2.2%
2.998 2
 
0.4%
3.024 2
 
0.4%
ValueCountFrequency (%)
6.148 2
 
0.4%
6.048 3
0.6%
5.968 3
0.6%
5.888 6
1.2%
5.798 7
1.4%
5.748 1
 
0.2%
5.728 1
 
0.2%
5.624 3
0.6%
5.574 1
 
0.2%
5.568 4
0.8%

월별이자납입일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-12T23:48:24.399332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:24.536006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

이자금액
Real number (ℝ)

ZEROS 

Distinct303
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7069411.9
Minimum0
Maximum1.927 × 108
Zeros88
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:24.662553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12573858.8
median5362000
Q38488750
95-th percentile16483360
Maximum1.927 × 108
Range1.927 × 108
Interquartile range (IQR)5914891.2

Descriptive statistics

Standard deviation12193048
Coefficient of variation (CV)1.7247614
Kurtosis135.67878
Mean7069411.9
Median Absolute Deviation (MAD)3035900
Skewness10.302368
Sum3.5347059 × 109
Variance1.4867043 × 1014
MonotonicityNot monotonic
2023-12-12T23:48:24.871339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 88
 
17.6%
7000000 14
 
2.8%
8000000 8
 
1.6%
8485000 8
 
1.6%
3500000 6
 
1.2%
12727500 5
 
1.0%
4900000 5
 
1.0%
4000000 5
 
1.0%
7985000 5
 
1.0%
7485000 4
 
0.8%
Other values (293) 352
70.4%
ValueCountFrequency (%)
0 88
17.6%
1034550 1
 
0.2%
1222080 1
 
0.2%
1332000 1
 
0.2%
1400000 1
 
0.2%
1540000 1
 
0.2%
1600000 1
 
0.2%
1609300 1
 
0.2%
1619400 1
 
0.2%
1800000 2
 
0.4%
ValueCountFrequency (%)
192700000 1
0.2%
132700000 1
0.2%
97965000 1
0.2%
54425000 1
0.2%
33717600 1
0.2%
29283750 1
0.2%
25600000 1
0.2%
23205000 1
0.2%
22466560 1
0.2%
20955000 1
0.2%

한도금액
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:48:25.064150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:25.175778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

기존발행금액
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:48:25.292614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:25.404556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

편입금액
Real number (ℝ)

Distinct172
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.580334 × 108
Minimum90000000
Maximum2 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:25.889317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90000000
5-th percentile2.1 × 108
Q13.9 × 108
median6.15 × 108
Q31 × 109
95-th percentile1.693 × 109
Maximum2 × 1010
Range1.991 × 1010
Interquartile range (IQR)6.1 × 108

Descriptive statistics

Standard deviation1.4399557 × 109
Coefficient of variation (CV)1.6782047
Kurtosis129.31304
Mean8.580334 × 108
Median Absolute Deviation (MAD)2.65 × 108
Skewness10.442719
Sum4.290167 × 1011
Variance2.0734724 × 1018
MonotonicityNot monotonic
2023-12-12T23:48:26.086381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
700000000 32
 
6.4%
1000000000 29
 
5.8%
350000000 21
 
4.2%
1500000000 18
 
3.6%
500000000 15
 
3.0%
400000000 13
 
2.6%
490000000 13
 
2.6%
800000000 13
 
2.6%
440000000 9
 
1.8%
390000000 9
 
1.8%
Other values (162) 328
65.6%
ValueCountFrequency (%)
90000000 1
0.2%
100000000 2
0.4%
114000000 1
0.2%
120000000 1
0.2%
140000000 2
0.4%
153000000 1
0.2%
154000000 1
0.2%
160000000 2
0.4%
165000000 1
0.2%
176000000 1
0.2%
ValueCountFrequency (%)
20000000000 2
0.4%
10000000000 1
0.2%
9000000000 1
0.2%
5000000000 1
0.2%
4200000000 1
0.2%
3780000000 1
0.2%
3000000000 2
0.4%
2560000000 1
0.2%
2500000000 1
0.2%
2380000000 1
0.2%

해지금액
Real number (ℝ)

ZEROS 

Distinct110
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6860199 × 108
Minimum0
Maximum1 × 1010
Zeros257
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:26.292559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.885 × 108
95-th percentile1.32405 × 109
Maximum1 × 1010
Range1 × 1010
Interquartile range (IQR)5.885 × 108

Descriptive statistics

Standard deviation6.5419378 × 108
Coefficient of variation (CV)1.7747972
Kurtosis95.916027
Mean3.6860199 × 108
Median Absolute Deviation (MAD)0
Skewness7.3005085
Sum1.8430099 × 1011
Variance4.2796951 × 1017
MonotonicityNot monotonic
2023-12-12T23:48:26.485981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 257
51.4%
700000000 28
 
5.6%
350000000 15
 
3.0%
500000000 8
 
1.6%
390000000 8
 
1.6%
800000000 7
 
1.4%
400000000 6
 
1.2%
490000000 6
 
1.2%
750000000 6
 
1.2%
448000000 4
 
0.8%
Other values (100) 155
31.0%
ValueCountFrequency (%)
0 257
51.4%
51691000 1
 
0.2%
100000000 1
 
0.2%
140000000 1
 
0.2%
154000000 1
 
0.2%
160000000 1
 
0.2%
180000000 3
 
0.6%
196000000 1
 
0.2%
200000000 2
 
0.4%
210000000 3
 
0.6%
ValueCountFrequency (%)
10000000000 1
0.2%
4200000000 1
0.2%
2560000000 1
0.2%
2380000000 1
0.2%
2010625000 1
0.2%
2000000000 1
0.2%
1990000000 1
0.2%
1940000000 1
0.2%
1680000000 2
0.4%
1610000000 1
0.2%

후순위인수채권금액
Real number (ℝ)

Distinct242
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25783556
Minimum2000000
Maximum6.6 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:26.679230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000000
5-th percentile5595400
Q110745000
median16800000
Q330000000
95-th percentile54009000
Maximum6.6 × 108
Range6.58 × 108
Interquartile range (IQR)19255000

Descriptive statistics

Standard deviation43080944
Coefficient of variation (CV)1.670869
Kurtosis114.18777
Mean25783556
Median Absolute Deviation (MAD)8120000
Skewness9.4397868
Sum1.2891778 × 1010
Variance1.8559678 × 1015
MonotonicityNot monotonic
2023-12-12T23:48:26.884756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16800000 28
 
5.6%
8400000 20
 
4.0%
30000000 11
 
2.2%
33600000 10
 
2.0%
45000000 9
 
1.8%
11760000 9
 
1.8%
36000000 9
 
1.8%
24000000 8
 
1.6%
15680000 8
 
1.6%
27000000 8
 
1.6%
Other values (232) 380
76.0%
ValueCountFrequency (%)
2000000 1
0.2%
2160000 1
0.2%
2880000 1
0.2%
3000000 1
0.2%
3192000 1
0.2%
3360000 1
0.2%
3920000 1
0.2%
4312000 1
0.2%
4480000 2
0.4%
4560000 1
0.2%
ValueCountFrequency (%)
660000000 1
0.2%
390000000 1
0.2%
351000000 1
0.2%
300000000 1
0.2%
218400000 1
0.2%
195000000 1
0.2%
173880000 1
0.2%
100880000 1
0.2%
95200000 1
0.2%
90000000 1
0.2%

잔액
Real number (ℝ)

ZEROS 

Distinct126
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8943141 × 108
Minimum0
Maximum2 × 1010
Zeros238
Zeros (%)47.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:27.089619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.97 × 108
Q36.2475 × 108
95-th percentile1.5 × 109
Maximum2 × 1010
Range2 × 1010
Interquartile range (IQR)6.2475 × 108

Descriptive statistics

Standard deviation1.4150315 × 109
Coefficient of variation (CV)2.8911743
Kurtosis146.60651
Mean4.8943141 × 108
Median Absolute Deviation (MAD)1.97 × 108
Skewness11.125463
Sum2.4471571 × 1011
Variance2.0023142 × 1018
MonotonicityNot monotonic
2023-12-12T23:48:27.331786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 238
47.6%
1000000000 28
 
5.6%
1500000000 14
 
2.8%
560000000 8
 
1.6%
2000000000 8
 
1.6%
500000000 7
 
1.4%
400000000 7
 
1.4%
490000000 7
 
1.4%
350000000 6
 
1.2%
440000000 6
 
1.2%
Other values (116) 171
34.2%
ValueCountFrequency (%)
0 238
47.6%
18893926 1
 
0.2%
90000000 1
 
0.2%
100000000 1
 
0.2%
114000000 1
 
0.2%
120000000 1
 
0.2%
140000000 1
 
0.2%
153000000 1
 
0.2%
160000000 1
 
0.2%
165000000 1
 
0.2%
ValueCountFrequency (%)
20000000000 2
 
0.4%
9000000000 1
 
0.2%
5000000000 1
 
0.2%
3780000000 1
 
0.2%
3000000000 2
 
0.4%
2500000000 1
 
0.2%
2048000000 1
 
0.2%
2000000000 8
1.6%
1500000000 14
2.8%
1400000000 1
 
0.2%

편입일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T23:48:27.547555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:27.659586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

편입기업업무구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
G
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG
2nd rowG
3rd rowG
4th rowG
5th rowG

Common Values

ValueCountFrequency (%)
G 500
100.0%

Length

2023-12-12T23:48:27.796636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:27.900384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

부실처리일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
488 
00:00.0
 
12

Length

Max length26
Median length26
Mean length25.544
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 488
97.6%
00:00.0 12
 
2.4%

Length

2023-12-12T23:48:28.018016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:28.134299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 488
49.4%
00:00:00.000000 488
49.4%
00:00.0 12
 
1.2%

부실처리금액
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20779038
Minimum0
Maximum2.25 × 109
Zeros488
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:28.239669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2.25 × 109
Range2.25 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.605414 × 108
Coefficient of variation (CV)7.726123
Kurtosis104.54113
Mean20779038
Median Absolute Deviation (MAD)0
Skewness9.5617476
Sum1.0389519 × 1010
Variance2.5773541 × 1016
MonotonicityNot monotonic
2023-12-12T23:48:28.371622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 488
97.6%
800000000 2
 
0.4%
760000000 1
 
0.2%
1400000000 1
 
0.2%
630000000 1
 
0.2%
440000000 1
 
0.2%
490000000 1
 
0.2%
2250000000 1
 
0.2%
1050000000 1
 
0.2%
19518750 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
0 488
97.6%
19518750 1
 
0.2%
270000000 1
 
0.2%
440000000 1
 
0.2%
490000000 1
 
0.2%
630000000 1
 
0.2%
760000000 1
 
0.2%
800000000 2
 
0.4%
1050000000 1
 
0.2%
1400000000 1
 
0.2%
ValueCountFrequency (%)
2250000000 1
0.2%
1480000000 1
0.2%
1400000000 1
0.2%
1050000000 1
0.2%
800000000 2
0.4%
760000000 1
0.2%
630000000 1
0.2%
490000000 1
0.2%
440000000 1
0.2%
270000000 1
0.2%

정상화일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-12T23:48:28.517115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:28.618326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

대물변제일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
496 
00:00.0
 
4

Length

Max length26
Median length26
Mean length25.848
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 496
99.2%
00:00.0 4
 
0.8%

Length

2023-12-12T23:48:28.749872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:28.890732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 496
49.8%
00:00:00.000000 496
49.8%
00:00.0 4
 
0.4%

신용조사수수료수납기준일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
497 
0001-01-01 00:00:00.000000
 
3

Length

Max length26
Median length7
Mean length7.114
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 497
99.4%
0001-01-01 00:00:00.000000 3
 
0.6%

Length

2023-12-12T23:48:29.057752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:29.237066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 497
98.8%
0001-01-01 3
 
0.6%
00:00:00.000000 3
 
0.6%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T23:48:29.362572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.258
Minimum2
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:29.494655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median5
Q36
95-th percentile7
Maximum89
Range87
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.8833524
Coefficient of variation (CV)0.92874712
Kurtosis207.64629
Mean5.258
Median Absolute Deviation (MAD)1
Skewness13.291873
Sum2629
Variance23.84713
MonotonicityNot monotonic
2023-12-12T23:48:29.667919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4 111
22.2%
6 109
21.8%
5 98
19.6%
7 89
17.8%
2 50
10.0%
3 37
 
7.4%
89 1
 
0.2%
27 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
2 50
10.0%
3 37
 
7.4%
4 111
22.2%
5 98
19.6%
6 109
21.8%
7 89
17.8%
8 1
 
0.2%
10 1
 
0.2%
12 1
 
0.2%
27 1
 
0.2%
ValueCountFrequency (%)
89 1
 
0.2%
61 1
 
0.2%
27 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
8 1
 
0.2%
7 89
17.8%
6 109
21.8%
5 98
19.6%
4 111
22.2%

처리시각
Categorical

IMBALANCE 

Distinct26
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
28:33.2
185 
28:01.8
181 
27:22.3
63 
12:26.0
46 
26:50.4
 
4
Other values (21)
21 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique21 ?
Unique (%)4.2%

Sample

1st row51:46.0
2nd row51:24.2
3rd row31:48.3
4th row28:59.6
5th row26:56.2

Common Values

ValueCountFrequency (%)
28:33.2 185
37.0%
28:01.8 181
36.2%
27:22.3 63
 
12.6%
12:26.0 46
 
9.2%
26:50.4 4
 
0.8%
07:48.0 1
 
0.2%
31:48.3 1
 
0.2%
28:59.6 1
 
0.2%
26:56.2 1
 
0.2%
55:08.3 1
 
0.2%
Other values (16) 16
 
3.2%

Length

2023-12-12T23:48:29.857131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
28:33.2 185
37.0%
28:01.8 181
36.2%
27:22.3 63
 
12.6%
12:26.0 46
 
9.2%
26:50.4 4
 
0.8%
51:46.0 1
 
0.2%
51:24.2 1
 
0.2%
35:59.4 1
 
0.2%
41:52.7 1
 
0.2%
18:08.8 1
 
0.2%
Other values (16) 16
 
3.2%

처리직원번호
Real number (ℝ)

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5803.132
Minimum4662
Maximum5814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:48:30.034138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4662
5-th percentile5814
Q15814
median5814
Q35814
95-th percentile5814
Maximum5814
Range1152
Interquartile range (IQR)0

Descriptive statistics

Standard deviation81.267111
Coefficient of variation (CV)0.014004009
Kurtosis109.23501
Mean5803.132
Median Absolute Deviation (MAD)0
Skewness-9.7093975
Sum2901566
Variance6604.3433
MonotonicityNot monotonic
2023-12-12T23:48:30.185777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5814 487
97.4%
5449 6
 
1.2%
5692 3
 
0.6%
5588 1
 
0.2%
5125 1
 
0.2%
4662 1
 
0.2%
5003 1
 
0.2%
ValueCountFrequency (%)
4662 1
 
0.2%
5003 1
 
0.2%
5125 1
 
0.2%
5449 6
 
1.2%
5588 1
 
0.2%
5692 3
 
0.6%
5814 487
97.4%
ValueCountFrequency (%)
5814 487
97.4%
5692 3
 
0.6%
5588 1
 
0.2%
5449 6
 
1.2%
5125 1
 
0.2%
5003 1
 
0.2%
4662 1
 
0.2%

최초처리시각
Categorical

IMBALANCE 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
54:47.6
232 
20:29.3
185 
19:05.6
63 
0001-01-01 00:00:00.000000
 
4
18:26.6
 
4
Other values (8)
 
12

Length

Max length26
Median length7
Mean length7.152
Min length7

Unique

Unique5 ?
Unique (%)1.0%

Sample

1st row55:03.7
2nd row09:08.9
3rd row09:08.9
4th row20:29.3
5th row20:29.3

Common Values

ValueCountFrequency (%)
54:47.6 232
46.4%
20:29.3 185
37.0%
19:05.6 63
 
12.6%
0001-01-01 00:00:00.000000 4
 
0.8%
18:26.6 4
 
0.8%
09:08.9 3
 
0.6%
55:03.7 2
 
0.4%
27:50.1 2
 
0.4%
16:55.3 1
 
0.2%
54:10.9 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2023-12-12T23:48:30.355948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
54:47.6 232
46.0%
20:29.3 185
36.7%
19:05.6 63
 
12.5%
0001-01-01 4
 
0.8%
00:00:00.000000 4
 
0.8%
18:26.6 4
 
0.8%
09:08.9 3
 
0.6%
55:03.7 2
 
0.4%
27:50.1 2
 
0.4%
16:55.3 1
 
0.2%
Other values (4) 4
 
0.8%

최초처리직원번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5814
253 
5449
237 
5588
 
5
BATCH
 
4
5447
 
1

Length

Max length5
Median length4
Mean length4.008
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row5449
2nd row5449
3rd row5449
4th row5814
5th row5814

Common Values

ValueCountFrequency (%)
5814 253
50.6%
5449 237
47.4%
5588 5
 
1.0%
BATCH 4
 
0.8%
5447 1
 
0.2%

Length

2023-12-12T23:48:30.569573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:48:30.691961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5814 253
50.6%
5449 237
47.4%
5588 5
 
1.0%
batch 4
 
0.8%
5447 1
 
0.2%

Sample

유동화회사업무구분코드편입기업고객ID편입기업고객일련번호유동화편입기업계열구분코드업종차수업종대분류코드기업규모코드신용평가기관코드기업신용등급코드값기초자산종류코드유동화회사보증용도코드발행일자만기일자표면이자율월별이자납입일자이자금액한도금액기존발행금액편입금액해지금액후순위인수채권금액잔액편입일자편입기업업무구분코드부실처리일자부실처리금액정상화일자대물변제일자신용조사수수료수납기준일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
0Gaaaaaaqd0k1ZZ0G21KS111200:00.000:00.05.4770001-01-01 00:00:00.00000015000000001500000000150000000054000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N551:46.0581455:03.75449
1Gaaaaaaqd0k1ZZ0G21KS111200:00.000:00.05.3890001-01-01 00:00:00.00000015000000001500000000150000000054000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N551:24.2581409:08.95449
2G9bQwlyGmWW1ZZ0G41KS41200:00.000:00.03.1390001-01-01 00:00:00.0000000002450000002450000006860000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N531:48.3581409:08.95449
3GaaaaadabSM1ZZ0C21BB+1200:00.000:00.03.6880001-01-01 00:00:00.00000082058000089000000003382000089000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N528:59.6581420:29.35814
4Gaaaaaaxqnj1ZZ0C21BB1200:00.000:00.03.9980001-01-01 00:00:00.00000083958000084000000002856000084000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N526:56.2581420:29.35814
5GaaaaaawO6X1ZZ0C21BBB-1200:00.000:00.03.5680001-01-01 00:00:00.000000337176000037800000000173880000378000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N555:08.3581420:29.35814
6Gaaaaaat5n51ZZ0F31KS71200:00.000:00.03.9770001-01-01 00:00:00.0000000003100000003100000009300000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N625:41.7544955:03.75449
7GaaaaaceVic1ZZ0C31KS81200:00.000:00.04.4390001-01-01 00:00:00.00000076000000076000000003344000076000000000:00.0G00:00.07600000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N724:38.2558809:08.95449
8GaaaaaayCXY1ZZ8D31C1200:00.000:00.05.3690001-01-01 00:00:00.000000187915000014000000005218070503360000087819295000:00.0G00:00.014000000000001-01-01 00:00:00.00000000:00.00001-01-01 00:00:00.000000N8947:40.151250001-01-01 00:00:00.000000BATCH
9GaaaaacNej51ZZ0C41KS111200:00.000:00.05.5680001-01-01 00:00:00.00000087696000063000000002268000063000000000:00.0G00:00.06300000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N519:23.1581420:29.35814
유동화회사업무구분코드편입기업고객ID편입기업고객일련번호유동화편입기업계열구분코드업종차수업종대분류코드기업규모코드신용평가기관코드기업신용등급코드값기초자산종류코드유동화회사보증용도코드발행일자만기일자표면이자율월별이자납입일자이자금액한도금액기존발행금액편입금액해지금액후순위인수채권금액잔액편입일자편입기업업무구분코드부실처리일자부실처리금액정상화일자대물변제일자신용조사수수료수납기준일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
490G9cf8zmrNRi1ZZ0G31KS81100:00.000:00.04.1940001-01-01 00:00:00.00000010485000001000000000042000000100000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N227:22.3581419:05.65814
491GaaaaabIDN71ZZ0G41KS54100:00.000:00.03.1940001-01-01 00:00:00.0000007985000001000000000027000000100000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N427:22.3581419:05.65814
492GaaaaaaA85O1ZZ0G31KS91100:00.000:00.04.5940001-01-01 00:00:00.00000080395000070000000003360000070000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N527:22.3581419:05.65814
493G9cffRsBL2v1ZZ0G31KS61100:00.000:00.03.3940001-01-01 00:00:00.0000008485000001000000000030000000100000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N327:22.3581419:05.65814
494G9btjGJ7Ou11ZZ0G31KS41100:00.000:00.02.9940001-01-01 00:00:00.00000011227500001500000000036000000150000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N327:22.3581419:05.65814
495G9czfqNdy6E1ZZ0Q31KS94100:00.000:00.04.5940001-01-01 00:00:00.00000057425000050000000002400000050000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N227:22.3581419:05.65814
496Gaaaaaaaz2T1ZZ0C22BBB1100:00.000:00.02.6540001-01-01 00:00:00.000000132700000002000000000003000000002000000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N226:50.4581418:26.65814
497GaaaaaasqZu1ZZ0C22BB-1100:00.000:00.04.3540001-01-01 00:00:00.000000544250000050000000000195000000500000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N226:50.4581418:26.65814
498GaaaaaasbND1ZZ0C22BB1100:00.000:00.03.8540001-01-01 00:00:00.000000192700000002000000000006600000002000000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N426:50.4581418:26.65814
499Gaaaaaam9VG1ZZ0C22BB-1100:00.000:00.04.3540001-01-01 00:00:00.000000979650000090000000000351000000900000000000:00.0G0001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.0N226:50.4581418:26.65814