Overview

Dataset statistics

Number of variables10
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory83.1 KiB
Average record size in memory85.1 B

Variable types

Categorical7
Numeric3

Dataset

Description한국주택금융공사 신탁자산부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15072800/fileData.do

Alerts

LIQD_PLAN_CD is highly overall correlated with FEE_RAT and 8 other fieldsHigh correlation
REG_DT is highly overall correlated with FEE_RAT and 8 other fieldsHigh correlation
LOAN_ORG_CD is highly overall correlated with FEE_RAT and 8 other fieldsHigh correlation
MNG_FEE_CD is highly overall correlated with FEE_RAT and 6 other fieldsHigh correlation
DEMND_DY is highly overall correlated with FEE_RAT and 8 other fieldsHigh correlation
REG_ENO is highly overall correlated with FEE_RAT and 8 other fieldsHigh correlation
FEE_RAT is highly overall correlated with LIQD_PLAN_CD and 5 other fieldsHigh correlation
BASIS_DY is highly overall correlated with DY_LOAN_RAMT and 7 other fieldsHigh correlation
DY_LOAN_RAMT is highly overall correlated with BASIS_DY and 6 other fieldsHigh correlation
HOLD_CD is highly overall correlated with BASIS_DY and 6 other fieldsHigh correlation
FEE_RAT has 156 (15.6%) zerosZeros

Reproduction

Analysis started2023-12-12 22:59:16.291251
Analysis finished2023-12-12 22:59:18.007378
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LIQD_PLAN_CD
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
KHFCMB2013S-32
124 
KHFCMB2013S-29
124 
KHFCMB2013S-26
124 
KHFCMB2010S-04
120 
KHFCMB2013S-19
117 
Other values (8)
391 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKHFCMB2010S-04
2nd rowKHFCMB2010S-04
3rd rowKHFCMB2010S-04
4th rowKHFCMB2010S-04
5th rowKHFCMB2010S-04

Common Values

ValueCountFrequency (%)
KHFCMB2013S-32 124
12.4%
KHFCMB2013S-29 124
12.4%
KHFCMB2013S-26 124
12.4%
KHFCMB2010S-04 120
12.0%
KHFCMB2013S-19 117
11.7%
KHFCMB2014S-02 99
9.9%
KHFCMB2009S-08 90
9.0%
KHFCMB2008S-01 60
6.0%
KHFCMB2010S-16 30
 
3.0%
KHFCMB2013S-38 28
 
2.8%
Other values (3) 84
8.4%

Length

2023-12-13T07:59:18.064563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
khfcmb2013s-32 124
12.4%
khfcmb2013s-29 124
12.4%
khfcmb2013s-26 124
12.4%
khfcmb2010s-04 120
12.0%
khfcmb2013s-19 117
11.7%
khfcmb2014s-02 99
9.9%
khfcmb2009s-08 90
9.0%
khfcmb2008s-01 60
6.0%
khfcmb2010s-16 30
 
3.0%
khfcmb2013s-38 28
 
2.8%
Other values (3) 84
8.4%

LOAN_ORG_CD
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
B088
588 
B035
300 
I004
112 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB035
2nd rowB035
3rd rowB035
4th rowB035
5th rowB035

Common Values

ValueCountFrequency (%)
B088 588
58.8%
B035 300
30.0%
I004 112
 
11.2%

Length

2023-12-13T07:59:18.160979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:18.239982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b088 588
58.8%
b035 300
30.0%
i004 112
 
11.2%

MNG_FEE_CD
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
C1
293 
CL
292 
PB
112 
S2
90 
SB
90 
Other values (4)
123 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
C1 293
29.3%
CL 292
29.2%
PB 112
 
11.2%
S2 90
 
9.0%
SB 90
 
9.0%
S1 60
 
6.0%
BB 30
 
3.0%
TB 30
 
3.0%
5C 3
 
0.3%

Length

2023-12-13T07:59:18.328201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:18.419410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c1 293
29.3%
cl 292
29.2%
pb 112
 
11.2%
s2 90
 
9.0%
sb 90
 
9.0%
s1 60
 
6.0%
bb 30
 
3.0%
tb 30
 
3.0%
5c 3
 
0.3%

FEE_RAT
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.16494
Minimum0
Maximum1.2
Zeros156
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T07:59:18.526023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.1
Q30.2
95-th percentile0.5
Maximum1.2
Range1.2
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.15885223
Coefficient of variation (CV)0.96309099
Kurtosis4.0787221
Mean0.16494
Median Absolute Deviation (MAD)0.1
Skewness1.6961805
Sum164.94
Variance0.02523403
MonotonicityNot monotonic
2023-12-13T07:59:18.629503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.1 352
35.2%
0.0 156
15.6%
0.2 143
14.3%
0.05 90
 
9.0%
0.25 76
 
7.6%
0.4 60
 
6.0%
0.13 31
 
3.1%
0.61 31
 
3.1%
0.5 30
 
3.0%
0.45 28
 
2.8%
Other values (2) 3
 
0.3%
ValueCountFrequency (%)
0.0 156
15.6%
0.05 90
 
9.0%
0.1 352
35.2%
0.13 31
 
3.1%
0.2 143
14.3%
0.25 76
 
7.6%
0.4 60
 
6.0%
0.45 28
 
2.8%
0.5 30
 
3.0%
0.61 31
 
3.1%
ValueCountFrequency (%)
1.2 2
 
0.2%
0.7 1
 
0.1%
0.61 31
 
3.1%
0.5 30
 
3.0%
0.45 28
 
2.8%
0.4 60
 
6.0%
0.25 76
 
7.6%
0.2 143
14.3%
0.13 31
 
3.1%
0.1 352
35.2%

DEMND_DY
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
20140203
588 
20141202
300 
20140307
112 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20141202
2nd row20141202
3rd row20141202
4th row20141202
5th row20141202

Common Values

ValueCountFrequency (%)
20140203 588
58.8%
20141202 300
30.0%
20140307 112
 
11.2%

Length

2023-12-13T07:59:18.729642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:18.809333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20140203 588
58.8%
20141202 300
30.0%
20140307 112
 
11.2%

BASIS_DY
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20140428
Minimum20140101
Maximum20141130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T07:59:18.907465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20140101
5-th percentile20140104
Q120140116
median20140128
Q320141105
95-th percentile20141125
Maximum20141130
Range1029
Interquartile range (IQR)989.25

Descriptive statistics

Standard deviation451.53424
Coefficient of variation (CV)2.2419297 × 10-5
Kurtosis-1.2430844
Mean20140428
Median Absolute Deviation (MAD)22
Skewness0.86010215
Sum2.0140428 × 1010
Variance203883.17
MonotonicityNot monotonic
2023-12-13T07:59:19.024310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140131 25
 
2.5%
20140129 22
 
2.2%
20140122 22
 
2.2%
20140128 22
 
2.2%
20140117 22
 
2.2%
20140118 22
 
2.2%
20140119 22
 
2.2%
20140120 22
 
2.2%
20140121 22
 
2.2%
20140116 22
 
2.2%
Other values (79) 777
77.7%
ValueCountFrequency (%)
20140101 14
1.4%
20140102 14
1.4%
20140103 14
1.4%
20140104 15
1.5%
20140105 16
1.6%
20140106 16
1.6%
20140107 16
1.6%
20140108 16
1.6%
20140109 16
1.6%
20140110 16
1.6%
ValueCountFrequency (%)
20141130 10
1.0%
20141129 10
1.0%
20141128 10
1.0%
20141127 10
1.0%
20141126 10
1.0%
20141125 10
1.0%
20141124 10
1.0%
20141123 10
1.0%
20141122 10
1.0%
20141121 10
1.0%

DY_LOAN_RAMT
Real number (ℝ)

HIGH CORRELATION 

Distinct275
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0363949 × 1010
Minimum8836000
Maximum2.6235649 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T07:59:19.153212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8836000
5-th percentile25077610
Q11.0938765 × 108
median3.5689469 × 109
Q37.5467419 × 1010
95-th percentile2.5979541 × 1011
Maximum2.6235649 × 1011
Range2.6234766 × 1011
Interquartile range (IQR)7.5358031 × 1010

Descriptive statistics

Standard deviation8.4290306 × 1010
Coefficient of variation (CV)1.6736238
Kurtosis1.2768668
Mean5.0363949 × 1010
Median Absolute Deviation (MAD)3.5438693 × 109
Skewness1.6520935
Sum5.0363949 × 1013
Variance7.1048556 × 1021
MonotonicityNot monotonic
2023-12-13T07:59:19.284653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59352798 81
 
8.1%
25077610 46
 
4.6%
710400018 34
 
3.4%
71467504 32
 
3.2%
59570000 26
 
2.6%
8904000 26
 
2.6%
710650018 16
 
1.6%
220298891 16
 
1.6%
131401907 16
 
1.6%
24772864 14
 
1.4%
Other values (265) 693
69.3%
ValueCountFrequency (%)
8836000 4
 
0.4%
8904000 26
 
2.6%
24772864 14
 
1.4%
25077610 46
4.6%
59200000 4
 
0.4%
59250368 9
 
0.9%
59352798 81
8.1%
59570000 26
 
2.6%
71467504 32
 
3.2%
71772920 1
 
0.1%
ValueCountFrequency (%)
262356491048 2
 
0.2%
262162115626 2
 
0.2%
262095804249 6
0.6%
262003870790 2
 
0.2%
261921839175 2
 
0.2%
261873642017 2
 
0.2%
261658025663 2
 
0.2%
261293363901 6
0.6%
261120268068 2
 
0.2%
261089619224 2
 
0.2%

REG_ENO
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1452
588 
1298
300 
1498
112 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1298
2nd row1298
3rd row1298
4th row1298
5th row1298

Common Values

ValueCountFrequency (%)
1452 588
58.8%
1298 300
30.0%
1498 112
 
11.2%

Length

2023-12-13T07:59:19.397059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:19.475596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1452 588
58.8%
1298 300
30.0%
1498 112
 
11.2%

REG_DT
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2014/02/05 12:42:13
588 
2015/01/22 17:51:38
300 
2014/03/13 11:38:28
112 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015/01/22 17:51:38
2nd row2015/01/22 17:51:38
3rd row2015/01/22 17:51:38
4th row2015/01/22 17:51:38
5th row2015/01/22 17:51:38

Common Values

ValueCountFrequency (%)
2014/02/05 12:42:13 588
58.8%
2015/01/22 17:51:38 300
30.0%
2014/03/13 11:38:28 112
 
11.2%

Length

2023-12-13T07:59:19.572026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:19.662230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2014/02/05 588
29.4%
12:42:13 588
29.4%
2015/01/22 300
15.0%
17:51:38 300
15.0%
2014/03/13 112
 
5.6%
11:38:28 112
 
5.6%

HOLD_CD
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0000-0000-0000
412 
B088-2013-0028
62 
B088-2013-0027
62 
B088-2013-0025
62 
B088-2013-0024
62 
Other values (7)
340 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0000-0000-0000
2nd row0000-0000-0000
3rd row0000-0000-0000
4th row0000-0000-0000
5th row0000-0000-0000

Common Values

ValueCountFrequency (%)
0000-0000-0000 412
41.2%
B088-2013-0028 62
 
6.2%
B088-2013-0027 62
 
6.2%
B088-2013-0025 62
 
6.2%
B088-2013-0024 62
 
6.2%
B088-2013-0022 62
 
6.2%
B088-2013-0021 62
 
6.2%
B088-2013-0017 62
 
6.2%
B088-2013-0016 55
 
5.5%
B088-2014-0003 33
 
3.3%
Other values (2) 66
 
6.6%

Length

2023-12-13T07:59:19.773037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0000-0000-0000 412
41.2%
b088-2013-0028 62
 
6.2%
b088-2013-0027 62
 
6.2%
b088-2013-0025 62
 
6.2%
b088-2013-0024 62
 
6.2%
b088-2013-0022 62
 
6.2%
b088-2013-0021 62
 
6.2%
b088-2013-0017 62
 
6.2%
b088-2013-0016 55
 
5.5%
b088-2014-0003 33
 
3.3%
Other values (2) 66
 
6.6%

Interactions

2023-12-13T07:59:17.506381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:16.923848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.215416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.589958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.024828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.315557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.672731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.116361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:59:17.406339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:59:19.846764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LIQD_PLAN_CDLOAN_ORG_CDMNG_FEE_CDFEE_RATDEMND_DYBASIS_DYDY_LOAN_RAMTREG_ENOREG_DTHOLD_CD
LIQD_PLAN_CD1.0001.0000.8770.8251.0000.9740.9441.0001.0000.916
LOAN_ORG_CD1.0001.0001.0000.7271.0000.9990.7681.0001.0000.930
MNG_FEE_CD0.8771.0001.0000.8491.0000.9990.6341.0001.0000.650
FEE_RAT0.8250.7270.8491.0000.7270.7080.7100.7270.7270.689
DEMND_DY1.0001.0001.0000.7271.0000.9990.7681.0001.0000.930
BASIS_DY0.9740.9990.9990.7080.9991.0000.7420.9990.9990.920
DY_LOAN_RAMT0.9440.7680.6340.7100.7680.7421.0000.7680.7680.863
REG_ENO1.0001.0001.0000.7271.0000.9990.7681.0001.0000.930
REG_DT1.0001.0001.0000.7271.0000.9990.7681.0001.0000.930
HOLD_CD0.9160.9300.6500.6890.9300.9200.8630.9300.9301.000
2023-12-13T07:59:19.967093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LIQD_PLAN_CDREG_DTHOLD_CDLOAN_ORG_CDMNG_FEE_CDDEMND_DYREG_ENO
LIQD_PLAN_CD1.0000.9950.6690.9950.6340.9950.995
REG_DT0.9951.0000.7001.0000.9971.0001.000
HOLD_CD0.6690.7001.0000.7000.3440.7000.700
LOAN_ORG_CD0.9951.0000.7001.0000.9971.0001.000
MNG_FEE_CD0.6340.9970.3440.9971.0000.9970.997
DEMND_DY0.9951.0000.7001.0000.9971.0001.000
REG_ENO0.9951.0000.7001.0000.9971.0001.000
2023-12-13T07:59:20.084203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FEE_RATBASIS_DYDY_LOAN_RAMTLIQD_PLAN_CDLOAN_ORG_CDMNG_FEE_CDDEMND_DYREG_ENOREG_DTHOLD_CD
FEE_RAT1.0000.259-0.2300.5710.6480.6710.6480.6480.6480.425
BASIS_DY0.2591.000-0.5710.9630.9680.9650.9680.9680.9680.682
DY_LOAN_RAMT-0.230-0.5711.0000.8140.7060.4020.7060.7060.7060.659
LIQD_PLAN_CD0.5710.9630.8141.0000.9950.6340.9950.9950.9950.669
LOAN_ORG_CD0.6480.9680.7060.9951.0000.9971.0001.0001.0000.700
MNG_FEE_CD0.6710.9650.4020.6340.9971.0000.9970.9970.9970.344
DEMND_DY0.6480.9680.7060.9951.0000.9971.0001.0001.0000.700
REG_ENO0.6480.9680.7060.9951.0000.9971.0001.0001.0000.700
REG_DT0.6480.9680.7060.9951.0000.9971.0001.0001.0000.700
HOLD_CD0.4250.6820.6590.6690.7000.3440.7000.7000.7001.000

Missing values

2023-12-13T07:59:17.804923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:59:17.941347image/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

LIQD_PLAN_CDLOAN_ORG_CDMNG_FEE_CDFEE_RATDEMND_DYBASIS_DYDY_LOAN_RAMTREG_ENOREG_DTHOLD_CD
0KHFCMB2010S-04B035BB0.2520141202201411305920000012982015/01/22 17:51:380000-0000-0000
1KHFCMB2010S-04B035BB0.2520141202201411295920000012982015/01/22 17:51:380000-0000-0000
2KHFCMB2010S-04B035BB0.2520141202201411285920000012982015/01/22 17:51:380000-0000-0000
3KHFCMB2010S-04B035BB0.2520141202201411275920000012982015/01/22 17:51:380000-0000-0000
4KHFCMB2010S-04B035BB0.2520141202201411265957000012982015/01/22 17:51:380000-0000-0000
5KHFCMB2010S-04B035BB0.2520141202201411255957000012982015/01/22 17:51:380000-0000-0000
6KHFCMB2010S-04B035BB0.2520141202201411245957000012982015/01/22 17:51:380000-0000-0000
7KHFCMB2010S-04B035BB0.2520141202201411235957000012982015/01/22 17:51:380000-0000-0000
8KHFCMB2010S-04B035BB0.2520141202201411225957000012982015/01/22 17:51:380000-0000-0000
9KHFCMB2010S-04B035BB0.2520141202201411215957000012982015/01/22 17:51:380000-0000-0000
LIQD_PLAN_CDLOAN_ORG_CDMNG_FEE_CDFEE_RATDEMND_DYBASIS_DYDY_LOAN_RAMTREG_ENOREG_DTHOLD_CD
990KHFCMB2013S-19B088CL0.120140203201401091181948288014522014/02/05 12:42:13B088-2013-0016
991KHFCMB2013S-19B088C10.4520140203201401081181993676814522014/02/05 12:42:13B088-2013-0016
992KHFCMB2013S-19B088CL0.120140203201401081181993676814522014/02/05 12:42:13B088-2013-0016
993KHFCMB2013S-19B088C10.4520140203201401071182850535114522014/02/05 12:42:13B088-2013-0016
994KHFCMB2013S-19B088CL0.120140203201401071182850535114522014/02/05 12:42:13B088-2013-0016
995KHFCMB2013S-19B088C10.4520140203201401061183071090414522014/02/05 12:42:13B088-2013-0016
996KHFCMB2013S-19B088CL0.120140203201401061183071090414522014/02/05 12:42:13B088-2013-0016
997KHFCMB2013S-19B088C10.4520140203201401051183857298414522014/02/05 12:42:13B088-2013-0016
998KHFCMB2013S-19B088CL0.120140203201401051183857298414522014/02/05 12:42:13B088-2013-0016
999KHFCMB2013S-19B088C10.4520140203201401041183857298414522014/02/05 12:42:13B088-2013-0016