Overview

Dataset statistics

Number of variables8
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.5 KiB
Average record size in memory68.1 B

Variable types

Categorical7
Numeric1

Dataset

Description한국주택금융공사 유동화자산부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15072810/fileData.do

Alerts

OBJECT_CODE has constant value ""Constant
OFFER_CNT has constant value ""Constant
LOAN_ORG_CD is highly overall correlated with LIQD_PLAN_CD and 1 other fieldsHigh correlation
RCV_DY is highly overall correlated with DWRT_BASIS_DY and 1 other fieldsHigh correlation
HOLD_CD is highly overall correlated with LOAN_ORG_CD and 1 other fieldsHigh correlation
DWRT_BASIS_DY is highly overall correlated with RCV_DY and 1 other fieldsHigh correlation
LIQD_PLAN_CD is highly overall correlated with LOAN_ORG_CD and 3 other fieldsHigh correlation
LOAN_ORG_CD is highly imbalanced (84.3%)Imbalance

Reproduction

Analysis started2023-12-12 20:42:22.201919
Analysis finished2023-12-12 20:42:23.017405
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LOAN_ORG_CD
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
B003
948 
I001
 
35
B004
 
9
B020
 
6
B081
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB081
2nd rowB081
3rd rowB020
4th rowB020
5th rowB020

Common Values

ValueCountFrequency (%)
B003 948
94.8%
I001 35
 
3.5%
B004 9
 
0.9%
B020 6
 
0.6%
B081 2
 
0.2%

Length

2023-12-13T05:42:23.108096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:23.237937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b003 948
94.8%
i001 35
 
3.5%
b004 9
 
0.9%
b020 6
 
0.6%
b081 2
 
0.2%

RCV_DY
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
20161215
447 
20180612
296 
20180913
130 
20170217
127 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20180913
2nd row20180913
3rd row20180913
4th row20180913
5th row20180913

Common Values

ValueCountFrequency (%)
20161215 447
44.7%
20180612 296
29.6%
20180913 130
 
13.0%
20170217 127
 
12.7%

Length

2023-12-13T05:42:23.375389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:23.512301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20161215 447
44.7%
20180612 296
29.6%
20180913 130
 
13.0%
20170217 127
 
12.7%

DWRT_BASIS_DY
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
20161214
447 
20180611
296 
20180912
130 
20170216
127 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20180912
2nd row20180912
3rd row20180912
4th row20180912
5th row20180912

Common Values

ValueCountFrequency (%)
20161214 447
44.7%
20180611 296
29.6%
20180912 130
 
13.0%
20170216 127
 
12.7%

Length

2023-12-13T05:42:23.667439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:23.784998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20161214 447
44.7%
20180611 296
29.6%
20180912 130
 
13.0%
20170216 127
 
12.7%

OBJECT_CODE
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
SD
1000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SD 1000
100.0%

Length

2023-12-13T05:42:23.929166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:24.073281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sd 1000
100.0%

OFFER_CNT
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
1000 

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 1000
100.0%

Length

2023-12-13T05:42:24.218234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:42:24.323181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1000
100.0%

SEQ
Real number (ℝ)

Distinct478
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.003
Minimum1
Maximum478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T05:42:24.460614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q167
median137.5
Q3262.25
95-th percentile428.05
Maximum478
Range477
Interquartile range (IQR)195.25

Descriptive statistics

Standard deviation128.78147
Coefficient of variation (CV)0.74438867
Kurtosis-0.60733613
Mean173.003
Median Absolute Deviation (MAD)91.5
Skewness0.65267663
Sum173003
Variance16584.668
MonotonicityNot monotonic
2023-12-13T05:42:24.660223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 4
 
0.4%
1 4
 
0.4%
25 4
 
0.4%
23 4
 
0.4%
22 4
 
0.4%
21 4
 
0.4%
20 4
 
0.4%
19 4
 
0.4%
18 4
 
0.4%
17 4
 
0.4%
Other values (468) 960
96.0%
ValueCountFrequency (%)
1 4
0.4%
2 4
0.4%
3 4
0.4%
4 4
0.4%
5 4
0.4%
6 4
0.4%
7 4
0.4%
8 4
0.4%
9 4
0.4%
10 4
0.4%
ValueCountFrequency (%)
478 1
0.1%
477 1
0.1%
476 1
0.1%
475 1
0.1%
474 1
0.1%
473 1
0.1%
472 1
0.1%
471 1
0.1%
470 1
0.1%
469 1
0.1%

LIQD_PLAN_CD
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
KHFCMB2016L-04
296 
KHFCMB2013L-A1
199 
KHFCMB2012L-A3
139 
KHFCMB2013L-A5
109 
KHFCMB2015L-05
88 
Other values (6)
169 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKHFCMB2015L-A4
2nd rowKHFCMB2015L-A4
3rd rowKHFCMB2014L-A1
4th rowKHFCMB2015L-A4
5th rowKHFCMB2014L-A1

Common Values

ValueCountFrequency (%)
KHFCMB2016L-04 296
29.6%
KHFCMB2013L-A1 199
19.9%
KHFCMB2012L-A3 139
13.9%
KHFCMB2013L-A5 109
 
10.9%
KHFCMB2015L-05 88
 
8.8%
KHFCMB2015L-A4 68
 
6.8%
KHFCMB2014L-A4 49
 
4.9%
KHFCMB2014L-05 36
 
3.6%
KHFCMB2014L-A1 8
 
0.8%
KHFCMB2015L-A3 5
 
0.5%

Length

2023-12-13T05:42:24.828873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
khfcmb2016l-04 296
29.6%
khfcmb2013l-a1 199
19.9%
khfcmb2012l-a3 139
13.9%
khfcmb2013l-a5 109
 
10.9%
khfcmb2015l-05 88
 
8.8%
khfcmb2015l-a4 68
 
6.8%
khfcmb2014l-a4 49
 
4.9%
khfcmb2014l-05 36
 
3.6%
khfcmb2014l-a1 8
 
0.8%
khfcmb2015l-a3 5
 
0.5%

HOLD_CD
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
B003-2010-0003
254 
B003-2010-0008
157 
B003-2010-0011
108 
B003-2010-0014
94 
B003-2010-0006
75 
Other values (42)
312 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st rowB081-2012-0025
2nd rowB081-2012-0008
3rd rowB020-2012-0002
4th rowB020-2011-0010
5th rowB020-2012-0002

Common Values

ValueCountFrequency (%)
B003-2010-0003 254
25.4%
B003-2010-0008 157
15.7%
B003-2010-0011 108
10.8%
B003-2010-0014 94
 
9.4%
B003-2010-0006 75
 
7.5%
B003-2010-0018 63
 
6.3%
B003-2010-0020 40
 
4.0%
B003-2011-0001 36
 
3.6%
I001-2010-0006 15
 
1.5%
B003-2012-0002 15
 
1.5%
Other values (37) 143
14.3%

Length

2023-12-13T05:42:24.995523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
b003-2010-0003 254
25.4%
b003-2010-0008 157
15.7%
b003-2010-0011 108
10.8%
b003-2010-0014 94
 
9.4%
b003-2010-0006 75
 
7.5%
b003-2010-0018 63
 
6.3%
b003-2010-0020 40
 
4.0%
b003-2011-0001 36
 
3.6%
i001-2010-0006 15
 
1.5%
b003-2012-0002 15
 
1.5%
Other values (37) 143
14.3%

Interactions

2023-12-13T05:42:22.653616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:42:25.105061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LOAN_ORG_CDRCV_DYDWRT_BASIS_DYSEQLIQD_PLAN_CDHOLD_CD
LOAN_ORG_CD1.0000.3860.3860.4210.7441.000
RCV_DY0.3861.0001.0000.6071.0000.664
DWRT_BASIS_DY0.3861.0001.0000.6071.0000.664
SEQ0.4210.6070.6071.0000.5650.407
LIQD_PLAN_CD0.7441.0001.0000.5651.0000.879
HOLD_CD1.0000.6640.6640.4070.8791.000
2023-12-13T05:42:25.262326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LOAN_ORG_CDRCV_DYHOLD_CDDWRT_BASIS_DYLIQD_PLAN_CD
LOAN_ORG_CD1.0000.3230.9790.3230.529
RCV_DY0.3231.0000.3901.0000.996
HOLD_CD0.9790.3901.0000.3900.516
DWRT_BASIS_DY0.3231.0000.3901.0000.996
LIQD_PLAN_CD0.5290.9960.5160.9961.000
2023-12-13T05:42:25.390925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQLOAN_ORG_CDRCV_DYDWRT_BASIS_DYLIQD_PLAN_CDHOLD_CD
SEQ1.0000.1870.4100.4100.2810.148
LOAN_ORG_CD0.1871.0000.3230.3230.5290.979
RCV_DY0.4100.3231.0001.0000.9960.390
DWRT_BASIS_DY0.4100.3231.0001.0000.9960.390
LIQD_PLAN_CD0.2810.5290.9960.9961.0000.516
HOLD_CD0.1480.9790.3900.3900.5161.000

Missing values

2023-12-13T05:42:22.804380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:42:22.955671image/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

LOAN_ORG_CDRCV_DYDWRT_BASIS_DYOBJECT_CODEOFFER_CNTSEQLIQD_PLAN_CDHOLD_CD
0B0812018091320180912SD1130KHFCMB2015L-A4B081-2012-0025
1B0812018091320180912SD1129KHFCMB2015L-A4B081-2012-0008
2B0202018091320180912SD1128KHFCMB2014L-A1B020-2012-0002
3B0202018091320180912SD1127KHFCMB2015L-A4B020-2011-0010
4B0202018091320180912SD1126KHFCMB2014L-A1B020-2012-0002
5B0042018091320180912SD1125KHFCMB2015L-A4B004-2011-0022
6B0032018091320180912SD1124KHFCMB2015L-A4B003-2012-0002
7B0032018091320180912SD1123KHFCMB2014L-A1B003-2010-0003
8B0032018091320180912SD1122KHFCMB2015L-A3B003-2010-0003
9B0032018091320180912SD1121KHFCMB2014L-A4B003-2010-0006
LOAN_ORG_CDRCV_DYDWRT_BASIS_DYOBJECT_CODEOFFER_CNTSEQLIQD_PLAN_CDHOLD_CD
990B0032016121520161214SD192KHFCMB2013L-A5B003-2010-0003
991B0032016121520161214SD191KHFCMB2013L-A5B003-2010-0003
992B0032016121520161214SD190KHFCMB2013L-A5B003-2010-0003
993B0032016121520161214SD189KHFCMB2012L-A3B003-2010-0006
994B0032016121520161214SD188KHFCMB2012L-A3B003-2010-0006
995B0032016121520161214SD187KHFCMB2013L-A1B003-2010-0014
996B0032016121520161214SD186KHFCMB2013L-A1B003-2011-0004
997B0032016121520161214SD185KHFCMB2013L-A5B003-2010-0003
998B0032016121520161214SD184KHFCMB2012L-A3B003-2010-0008
999B0032016121520161214SD183KHFCMB2013L-A1B003-2011-0001