Overview

Dataset statistics

Number of variables18
Number of observations530
Missing cells36
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.2 KiB
Average record size in memory147.2 B

Variable types

Text3
DateTime11
Categorical4

Dataset

Description한국주택금융공사에서 발행한 유동화대상코드정보(유동화대상코드, 유동화대상명, 계획시작일자 등)에 관한 데이터 입니다. 유동화대상코드,유동화대상명,계획시작일자,예상종료일자,유동화계획코드,양수심사순번,적격심사순번,실사후심사순번,심사예상시작일자,심사예상종료일자,실사예상시작일자,실사예상종료일자,통지예상시작일자,통지예상종료일자,양수예정일자,자산확정예상일자,발행예정일자,보유목적코드에 관한 정보가 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073162/fileData.do

Alerts

적격심사순번 is highly overall correlated with 양수심사순번 and 2 other fieldsHigh correlation
양수심사순번 is highly overall correlated with 적격심사순번 and 2 other fieldsHigh correlation
실사후심사순번 is highly overall correlated with 양수심사순번 and 2 other fieldsHigh correlation
보유목적코드 is highly overall correlated with 양수심사순번 and 2 other fieldsHigh correlation
발행예정일자 has 36 (6.8%) missing valuesMissing
유동화대상코드 has unique valuesUnique
유동화대상명 has unique valuesUnique
유동화계획코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:47:49.607196
Analysis finished2023-12-12 22:47:50.363592
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동화대상코드
Text

UNIQUE 

Distinct530
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T07:47:50.505607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters7420
Distinct characters18
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

Unique530 ?
Unique (%)100.0%

Sample

1st rowKHFCMB2005M-16
2nd rowKHFCMB2005M-17
3rd rowKHFCMB2005M-18
4th rowKHFCMB2006M-01
5th rowKHFCMB2006M-02
ValueCountFrequency (%)
khfcmb2005m-16 1
 
0.2%
khfcmb2017m-05 1
 
0.2%
khfcmb2016m-04 1
 
0.2%
khfcmb2016m-03 1
 
0.2%
khfcmb2016m-02 1
 
0.2%
khfcpb2016m-01 1
 
0.2%
khfcmb2016m-01 1
 
0.2%
khfcmb2015m-34 1
 
0.2%
khfcmb2015m-37 1
 
0.2%
khfcmb2015m-36 1
 
0.2%
Other values (520) 520
98.1%
2023-12-13T07:47:50.806419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1018
13.7%
0 862
11.6%
2 769
10.4%
1 695
9.4%
K 530
7.1%
H 530
7.1%
- 530
7.1%
B 530
7.1%
C 530
7.1%
F 530
7.1%
Other values (8) 896
12.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3710
50.0%
Decimal Number 3180
42.9%
Dash Punctuation 530
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 862
27.1%
2 769
24.2%
1 695
21.9%
3 187
 
5.9%
4 129
 
4.1%
9 123
 
3.9%
8 108
 
3.4%
5 106
 
3.3%
7 103
 
3.2%
6 98
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
M 1018
27.4%
K 530
14.3%
H 530
14.3%
B 530
14.3%
C 530
14.3%
F 530
14.3%
P 42
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 530
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3710
50.0%
Common 3710
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 862
23.2%
2 769
20.7%
1 695
18.7%
- 530
14.3%
3 187
 
5.0%
4 129
 
3.5%
9 123
 
3.3%
8 108
 
2.9%
5 106
 
2.9%
7 103
 
2.8%
Latin
ValueCountFrequency (%)
M 1018
27.4%
K 530
14.3%
H 530
14.3%
B 530
14.3%
C 530
14.3%
F 530
14.3%
P 42
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 1018
13.7%
0 862
11.6%
2 769
10.4%
1 695
9.4%
K 530
7.1%
H 530
7.1%
- 530
7.1%
B 530
7.1%
C 530
7.1%
F 530
7.1%
Other values (8) 896
12.1%

유동화대상명
Text

UNIQUE 

Distinct530
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T07:47:51.060951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5300
Distinct characters15
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

Unique530 ?
Unique (%)100.0%

Sample

1st rowMBS2005-16
2nd rowMBS2005-17
3rd rowMBM2005-18
4th rowMBM2006-01
5th rowMBM2006-02
ValueCountFrequency (%)
mbs2005-16 1
 
0.2%
mbm2017-05 1
 
0.2%
mbm2016-04 1
 
0.2%
mbm2016-03 1
 
0.2%
mbm2016-02 1
 
0.2%
pbm2016-01 1
 
0.2%
mbm2016-01 1
 
0.2%
mbm2015-34 1
 
0.2%
mbm2015-37 1
 
0.2%
mbm2015-36 1
 
0.2%
Other values (520) 520
98.1%
2023-12-13T07:47:51.397235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1016
19.2%
0 862
16.3%
2 769
14.5%
1 695
13.1%
B 530
10.0%
- 530
10.0%
3 187
 
3.5%
4 129
 
2.4%
9 123
 
2.3%
8 108
 
2.0%
Other values (5) 351
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3180
60.0%
Uppercase Letter 1590
30.0%
Dash Punctuation 530
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 862
27.1%
2 769
24.2%
1 695
21.9%
3 187
 
5.9%
4 129
 
4.1%
9 123
 
3.9%
8 108
 
3.4%
5 106
 
3.3%
7 103
 
3.2%
6 98
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
M 1016
63.9%
B 530
33.3%
P 42
 
2.6%
S 2
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 530
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3710
70.0%
Latin 1590
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 862
23.2%
2 769
20.7%
1 695
18.7%
- 530
14.3%
3 187
 
5.0%
4 129
 
3.5%
9 123
 
3.3%
8 108
 
2.9%
5 106
 
2.9%
7 103
 
2.8%
Latin
ValueCountFrequency (%)
M 1016
63.9%
B 530
33.3%
P 42
 
2.6%
S 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 1016
19.2%
0 862
16.3%
2 769
14.5%
1 695
13.1%
B 530
10.0%
- 530
10.0%
3 187
 
3.5%
4 129
 
2.4%
9 123
 
2.3%
8 108
 
2.0%
Other values (5) 351
 
6.6%

계획시작일자
Date

Distinct461
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-17 00:00:00
Maximum2020-02-05 00:00:00
2023-12-13T07:47:51.536195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:51.667193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예상종료일자
Date

Distinct481
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-11-10 00:00:00
Maximum2054-11-25 00:00:00
2023-12-13T07:47:51.778681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:51.938176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

유동화계획코드
Text

UNIQUE 

Distinct530
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T07:47:52.160267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters7420
Distinct characters20
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

Unique530 ?
Unique (%)100.0%

Sample

1st rowKHFCMB2005S-09
2nd rowKHFCMB2005L-09
3rd rowKHFCMB2005L-10
4th rowKHFCMB2006S-01
5th rowKHFCMB2006L-01
ValueCountFrequency (%)
khfcmb2005s-09 1
 
0.2%
khfcmb2017s-04 1
 
0.2%
khfcmb2016s-05 1
 
0.2%
khfcmb2016s-04 1
 
0.2%
khfcmb2016s-03 1
 
0.2%
khfcmb2016s-02 1
 
0.2%
khfcmb2016s-01 1
 
0.2%
khfcmb2015l-a4 1
 
0.2%
khfcmb2015l-05 1
 
0.2%
khfcmb2015l-04 1
 
0.2%
Other values (520) 520
98.1%
2023-12-13T07:47:52.563748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 920
12.4%
2 747
10.1%
1 728
9.8%
B 544
7.3%
K 530
7.1%
H 530
7.1%
- 530
7.1%
M 530
7.1%
C 530
7.1%
F 530
7.1%
Other values (10) 1301
17.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3752
50.6%
Decimal Number 3138
42.3%
Dash Punctuation 530
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 920
29.3%
2 747
23.8%
1 728
23.2%
3 142
 
4.5%
9 119
 
3.8%
8 103
 
3.3%
7 99
 
3.2%
4 94
 
3.0%
5 93
 
3.0%
6 93
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 544
14.5%
K 530
14.1%
H 530
14.1%
M 530
14.1%
C 530
14.1%
F 530
14.1%
S 324
8.6%
L 192
 
5.1%
A 42
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 530
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3752
50.6%
Common 3668
49.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 920
25.1%
2 747
20.4%
1 728
19.8%
- 530
14.4%
3 142
 
3.9%
9 119
 
3.2%
8 103
 
2.8%
7 99
 
2.7%
4 94
 
2.6%
5 93
 
2.5%
Latin
ValueCountFrequency (%)
B 544
14.5%
K 530
14.1%
H 530
14.1%
M 530
14.1%
C 530
14.1%
F 530
14.1%
S 324
8.6%
L 192
 
5.1%
A 42
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 920
12.4%
2 747
10.1%
1 728
9.8%
B 544
7.3%
K 530
7.1%
H 530
7.1%
- 530
7.1%
M 530
7.1%
C 530
7.1%
F 530
7.1%
Other values (10) 1301
17.5%

양수심사순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2
457 
<NA>
73 

Length

Max length4
Median length1
Mean length1.4132075
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
2 457
86.2%
<NA> 73
 
13.8%

Length

2023-12-13T07:47:52.704198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:47:52.802521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 457
86.2%
na 73
 
13.8%

적격심사순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2
446 
<NA>
84 

Length

Max length4
Median length1
Mean length1.4754717
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
2 446
84.2%
<NA> 84
 
15.8%

Length

2023-12-13T07:47:53.236217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:47:53.353334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 446
84.2%
na 84
 
15.8%

실사후심사순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2
446 
<NA>
84 

Length

Max length4
Median length1
Mean length1.4754717
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
2 446
84.2%
<NA> 84
 
15.8%

Length

2023-12-13T07:47:53.486795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:47:53.603869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 446
84.2%
na 84
 
15.8%

심사예상시작일자
Date

Distinct459
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-24 00:00:00
Maximum2020-01-21 00:00:00
2023-12-13T07:47:53.760276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:53.922528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

심사예상종료일자
Date

Distinct470
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-31 00:00:00
Maximum2020-02-03 00:00:00
2023-12-13T07:47:54.050389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:54.189487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실사예상시작일자
Date

Distinct461
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-24 00:00:00
Maximum2020-01-22 00:00:00
2023-12-13T07:47:54.334807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:54.466186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실사예상종료일자
Date

Distinct469
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-31 00:00:00
Maximum2020-02-03 00:00:00
2023-12-13T07:47:54.604236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:54.716787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

통지예상시작일자
Date

Distinct461
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-24 00:00:00
Maximum2020-01-22 00:00:00
2023-12-13T07:47:54.826672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:54.943993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

통지예상종료일자
Date

Distinct471
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-31 00:00:00
Maximum2020-02-03 00:00:00
2023-12-13T07:47:55.055207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:55.180937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

양수예정일자
Date

Distinct457
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-11-10 00:00:00
Maximum2020-02-05 00:00:00
2023-12-13T07:47:55.330819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:55.440796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

자산확정예상일자
Date

Distinct443
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2005-10-17 00:00:00
Maximum2020-01-21 00:00:00
2023-12-13T07:47:55.544840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:55.663177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발행예정일자
Date

MISSING 

Distinct457
Distinct (%)92.5%
Missing36
Missing (%)6.8%
Memory size4.3 KiB
Minimum2005-11-10 00:00:00
Maximum2042-10-31 00:00:00
2023-12-13T07:47:55.776566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:47:55.915655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보유목적코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
신탁유동화
328 
매입보유
146 
고유유동화
56 

Length

Max length5
Median length5
Mean length4.7245283
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신탁유동화
2nd row매입보유
3rd row매입보유
4th row신탁유동화
5th row매입보유

Common Values

ValueCountFrequency (%)
신탁유동화 328
61.9%
매입보유 146
27.5%
고유유동화 56
 
10.6%

Length

2023-12-13T07:47:56.031204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:47:56.113539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신탁유동화 328
61.9%
매입보유 146
27.5%
고유유동화 56
 
10.6%

Correlations

2023-12-13T07:47:56.172486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보유목적코드
보유목적코드1.000
2023-12-13T07:47:56.256549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적격심사순번양수심사순번실사후심사순번보유목적코드
적격심사순번1.0001.0001.0001.000
양수심사순번1.0001.0001.0001.000
실사후심사순번1.0001.0001.0001.000
보유목적코드1.0001.0001.0001.000
2023-12-13T07:47:56.347637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
양수심사순번적격심사순번실사후심사순번보유목적코드
양수심사순번1.0001.0001.0001.000
적격심사순번1.0001.0001.0001.000
실사후심사순번1.0001.0001.0001.000
보유목적코드1.0001.0001.0001.000

Missing values

2023-12-13T07:47:50.034502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:47:50.266014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

유동화대상코드유동화대상명계획시작일자예상종료일자유동화계획코드양수심사순번적격심사순번실사후심사순번심사예상시작일자심사예상종료일자실사예상시작일자실사예상종료일자통지예상시작일자통지예상종료일자양수예정일자자산확정예상일자발행예정일자보유목적코드
0KHFCMB2005M-16MBS2005-162005-10-172005-11-10KHFCMB2005S-09<NA><NA><NA>2005-10-242005-10-312005-10-242005-10-312005-10-242005-10-312005-11-102005-10-172005-11-10신탁유동화
1KHFCMB2005M-17MBS2005-172005-10-172005-11-10KHFCMB2005L-09<NA><NA><NA>2005-10-242005-10-312005-10-242005-10-312005-10-242005-10-312005-11-102005-10-172005-11-10매입보유
2KHFCMB2005M-18MBM2005-182005-11-252006-02-25KHFCMB2005L-10<NA><NA><NA>2005-11-252005-12-212005-11-252005-12-212005-11-252005-12-212005-12-212005-11-25<NA>매입보유
3KHFCMB2006M-01MBM2006-012006-01-062006-01-26KHFCMB2006S-01<NA><NA><NA>2006-01-062006-01-262006-01-062006-01-262006-01-062006-01-262006-01-262006-01-062006-01-26신탁유동화
4KHFCMB2006M-02MBM2006-022006-01-062006-03-29KHFCMB2006L-01<NA><NA><NA>2006-01-062006-01-262006-01-062006-01-262006-01-062006-01-262006-01-262006-01-06<NA>매입보유
5KHFCMB2006M-03MBM2006-032006-02-282006-03-30KHFCMB2006S-022222006-02-282006-03-302006-02-282006-03-302006-02-282006-03-302006-03-302006-02-282006-03-30신탁유동화
6KHFCMB2006M-04MBM2006-042006-05-022006-05-26KHFCMB2006L-02<NA><NA><NA>2006-05-022006-05-262006-05-022006-05-262006-05-022006-05-262006-05-262006-05-02<NA>매입보유
7KHFCMB2006M-05MBM2006-052006-06-232006-07-14KHFCMB2006S-03<NA><NA><NA>2006-06-232006-07-142006-06-232006-07-142006-06-232006-07-142006-07-142006-06-232006-07-14신탁유동화
8KHFCMB2006M-06MBM2006-062006-07-282006-09-30KHFCMB2006L-03<NA><NA><NA>2006-07-282006-08-142006-07-282006-08-142006-07-282006-08-142006-08-212006-07-28<NA>매입보유
9KHFCMB2006M-07MBM2006-072006-09-052027-09-27KHFCMB2006S-04<NA><NA><NA>2006-09-042006-09-262006-09-042006-09-262006-09-042006-09-262006-09-262006-09-042006-09-26신탁유동화
유동화대상코드유동화대상명계획시작일자예상종료일자유동화계획코드양수심사순번적격심사순번실사후심사순번심사예상시작일자심사예상종료일자실사예상시작일자실사예상종료일자통지예상시작일자통지예상종료일자양수예정일자자산확정예상일자발행예정일자보유목적코드
520KHFCMB2019M-49MBM2019-492019-12-182049-12-18KHFCMB2019L-14<NA><NA><NA>2019-12-172019-12-182019-12-182019-12-182019-12-182019-12-182019-12-182019-12-172019-12-18매입보유
521KHFCMB2019M-46MBM2019-462019-12-202040-12-20KHFCMB2019S-262222019-11-302019-12-182019-11-302019-12-182019-11-302019-12-182019-12-202019-11-302019-12-20신탁유동화
522KHFCMB2019M-47MBM2019-472019-12-242040-12-24KHFCMB2019S-272222019-12-052019-12-202019-12-052019-12-202019-12-052019-12-202019-12-242019-12-052019-12-24신탁유동화
523KHFCMB2019M-50MBM2019-502019-12-272040-12-27KHFCMB2019S-28<NA><NA><NA>2019-12-162019-12-242019-12-162019-12-242019-12-162019-12-242019-12-272019-12-162019-12-27신탁유동화
524KHFCMB2020M-02MBM2020-022020-01-082050-01-08KHFCMB2020L-01<NA><NA><NA>2020-01-072020-01-082020-01-082020-01-082020-01-082020-01-082020-01-082020-01-072020-10-08매입보유
525KHFCMB2020M-04MBM2020-042020-01-102041-01-10KHFCMB2020S-012222019-12-192020-01-082019-12-192020-01-082019-12-192020-01-082020-01-102019-12-192020-01-10신탁유동화
526KHFCMB2020M-05MBM2020-052020-01-172041-01-17KHFCMB2020S-022222019-12-302020-01-152019-12-302020-01-152019-12-302020-01-152020-01-172019-12-302020-01-17신탁유동화
527KHFCMB2020M-06MBM2020-062020-01-212041-01-21KHFCMB2020S-032222019-12-312020-01-172019-12-312020-01-172019-12-312020-01-172020-01-212019-12-312020-01-21신탁유동화
528KHFCMB2020M-03MBM2020-032020-01-222050-01-22KHFCMB2020L-02<NA><NA><NA>2020-01-212020-01-222020-01-222020-01-222020-01-222020-01-222020-01-222020-01-212020-01-22매입보유
529KHFCMB2020M-01MBM2020-012020-02-052025-02-05KHFCMB2020B-012222019-12-162020-02-032019-12-162020-02-032019-12-162020-02-032020-02-052019-12-162025-02-05고유유동화