Overview

Dataset statistics

Number of variables10
Number of observations2219
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory175.7 KiB
Average record size in memory81.1 B

Variable types

Numeric1
Text1
Categorical5
DateTime3

Dataset

Description한국주택금융공사에서 발행한 MBS 채권의 신용등급 공시 자료입니다. 발행회차, 신용평가사, 발행일, 평가등급 등의 정보가 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15113096/fileData.do

Alerts

평가구분 has constant value ""Constant
현재평가등급 has constant value ""Constant
등급변동여부 has constant value ""Constant
직전평가등급 is highly imbalanced (52.5%)Imbalance
번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:06:57.143607
Analysis finished2024-04-06 08:06:58.599137
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1110
Minimum1
Maximum2219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2024-04-06T17:06:58.833848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile111.9
Q1555.5
median1110
Q31664.5
95-th percentile2108.1
Maximum2219
Range2218
Interquartile range (IQR)1109

Descriptive statistics

Standard deviation640.71444
Coefficient of variation (CV)0.57722022
Kurtosis-1.2
Mean1110
Median Absolute Deviation (MAD)555
Skewness0
Sum2463090
Variance410515
MonotonicityStrictly increasing
2024-04-06T17:06:59.172317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1483 1
 
< 0.1%
1477 1
 
< 0.1%
1478 1
 
< 0.1%
1479 1
 
< 0.1%
1480 1
 
< 0.1%
1481 1
 
< 0.1%
1482 1
 
< 0.1%
1484 1
 
< 0.1%
1492 1
 
< 0.1%
Other values (2209) 2209
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2219 1
< 0.1%
2218 1
< 0.1%
2217 1
< 0.1%
2216 1
< 0.1%
2215 1
< 0.1%
2214 1
< 0.1%
2213 1
< 0.1%
2212 1
< 0.1%
2211 1
< 0.1%
2210 1
< 0.1%

발행회차
Text

Distinct395
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
2024-04-06T17:06:59.675507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.064443
Min length11

Characters and Unicode

Total characters24552
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)1.2%

Sample

1st rowMBS 2004-06
2nd rowMBS 2005-08
3rd rowMBS 2006-01
4th rowMBS 2006-02
5th rowMBS 2006-02
ValueCountFrequency (%)
mbs 2073
46.7%
slbs 143
 
3.2%
2009-02 26
 
0.6%
2009-03 25
 
0.6%
2009-04 22
 
0.5%
2009-01 18
 
0.4%
2008-04 17
 
0.4%
2009-13 17
 
0.4%
2009-11 16
 
0.4%
2008-02 16
 
0.4%
Other values (373) 2065
46.5%
2024-04-06T17:07:00.417916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3793
15.4%
2 3392
13.8%
1 2891
11.8%
S 2359
9.6%
B 2222
9.1%
2219
9.0%
- 2219
9.0%
M 2076
8.5%
3 751
 
3.1%
4 450
 
1.8%
Other values (6) 2180
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13314
54.2%
Uppercase Letter 6800
27.7%
Space Separator 2219
 
9.0%
Dash Punctuation 2219
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3793
28.5%
2 3392
25.5%
1 2891
21.7%
3 751
 
5.6%
4 450
 
3.4%
9 441
 
3.3%
5 411
 
3.1%
8 406
 
3.0%
6 400
 
3.0%
7 379
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
S 2359
34.7%
B 2222
32.7%
M 2076
30.5%
L 143
 
2.1%
Space Separator
ValueCountFrequency (%)
2219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17752
72.3%
Latin 6800
 
27.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3793
21.4%
2 3392
19.1%
1 2891
16.3%
2219
12.5%
- 2219
12.5%
3 751
 
4.2%
4 450
 
2.5%
9 441
 
2.5%
5 411
 
2.3%
8 406
 
2.3%
Other values (2) 779
 
4.4%
Latin
ValueCountFrequency (%)
S 2359
34.7%
B 2222
32.7%
M 2076
30.5%
L 143
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3793
15.4%
2 3392
13.8%
1 2891
11.8%
S 2359
9.6%
B 2222
9.1%
2219
9.0%
- 2219
9.0%
M 2076
8.5%
3 751
 
3.1%
4 450
 
1.8%
Other values (6) 2180
8.9%

신용평가사
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
한국신용평가
796 
나이스신용평가
735 
한국기업평가
688 

Length

Max length7
Median length6
Mean length6.3312303
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row나이스신용평가
2nd row한국기업평가
3rd row나이스신용평가
4th row한국신용평가
5th row한국기업평가

Common Values

ValueCountFrequency (%)
한국신용평가 796
35.9%
나이스신용평가 735
33.1%
한국기업평가 688
31.0%

Length

2024-04-06T17:07:00.894378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:07:01.271584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국신용평가 796
35.9%
나이스신용평가 735
33.1%
한국기업평가 688
31.0%

발행일
Date

Distinct388
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
Minimum2004-11-30 00:00:00
Maximum2022-01-21 00:00:00
2024-04-06T17:07:01.512057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:07:01.805526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

평가구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
정기
2219 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 2219
100.0%

Length

2024-04-06T17:07:02.030616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:07:02.217495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 2219
100.0%

직전평가등급
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
AAA(sf)
1763 
<NA>
450 
AA(sf)
 
6

Length

Max length7
Median length7
Mean length6.3889139
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAA(sf)
2nd rowAA(sf)
3rd rowAA(sf)
4th rowAA(sf)
5th rowAA(sf)

Common Values

ValueCountFrequency (%)
AAA(sf) 1763
79.5%
<NA> 450
 
20.3%
AA(sf) 6
 
0.3%

Length

2024-04-06T17:07:02.418337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:07:02.619032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aaa(sf 1763
79.5%
na 450
 
20.3%
aa(sf 6
 
0.3%

현재평가등급
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
AAA(sf)
2219 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAAA(sf)
2nd rowAAA(sf)
3rd rowAAA(sf)
4th rowAAA(sf)
5th rowAAA(sf)

Common Values

ValueCountFrequency (%)
AAA(sf) 2219
100.0%

Length

2024-04-06T17:07:02.828077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:07:03.101896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aaa(sf 2219
100.0%

등급변동여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
부
2219 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부 2219
100.0%

Length

2024-04-06T17:07:03.317180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:07:03.482090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 2219
100.0%

평가일
Date

Distinct288
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
Minimum2014-10-21 00:00:00
Maximum2023-03-24 00:00:00
2024-04-06T17:07:03.689673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:07:03.988894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

공시일
Date

Distinct241
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
Minimum2014-10-21 00:00:00
Maximum2023-03-27 00:00:00
2024-04-06T17:07:04.259823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:07:04.550628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-06T17:06:57.633159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:07:04.721045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호신용평가사직전평가등급
번호1.0000.1050.177
신용평가사0.1051.0000.000
직전평가등급0.1770.0001.000
2024-04-06T17:07:04.910936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직전평가등급신용평가사
직전평가등급1.0000.000
신용평가사0.0001.000
2024-04-06T17:07:05.072723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호신용평가사직전평가등급
번호1.0000.0620.136
신용평가사0.0621.0000.000
직전평가등급0.1360.0001.000

Missing values

2024-04-06T17:06:57.885046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:06:58.292833image/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

번호발행회차신용평가사발행일평가구분직전평가등급현재평가등급등급변동여부평가일공시일
01MBS 2004-06나이스신용평가2004-11-30정기AA(sf)AAA(sf)부2014-10-212014-10-21
12MBS 2005-08한국기업평가2005-09-29정기AA(sf)AAA(sf)부2014-11-252014-11-26
23MBS 2006-01나이스신용평가2006-01-26정기AA(sf)AAA(sf)부2015-01-282015-01-28
34MBS 2006-02한국신용평가2006-03-30정기AA(sf)AAA(sf)부2015-05-282015-05-28
45MBS 2006-02한국기업평가2006-03-30정기AA(sf)AAA(sf)부2015-05-212015-05-22
56MBS 2006-05한국신용평가2006-12-15정기<NA>AAA(sf)부2015-02-262015-02-26
67MBS 2006-05나이스신용평가2006-12-15정기<NA>AAA(sf)부2015-01-272015-01-27
78MBS 2007-01나이스신용평가2007-02-21정기<NA>AAA(sf)부2015-04-302015-04-30
89MBS 2007-01한국신용평가2007-02-21정기<NA>AAA(sf)부2015-04-272015-04-27
910MBS 2007-02한국신용평가2007-04-24정기<NA>AAA(sf)부2015-06-302015-06-30
번호발행회차신용평가사발행일평가구분직전평가등급현재평가등급등급변동여부평가일공시일
22092210SLBS 2009-04한국신용평가2009-08-25정기AAA(sf)AAA(sf)부2019-10-312019-11-01
22102211SLBS 2009-04나이스신용평가2009-08-25정기AAA(sf)AAA(sf)부2019-09-162019-09-16
22112212SLBS 2009-04한국신용평가2009-08-25정기AAA(sf)AAA(sf)부2018-11-012018-11-01
22122213SLBS 2009-04나이스신용평가2009-08-25정기AAA(sf)AAA(sf)부2018-09-182018-09-18
22132214SLBS 2009-04한국신용평가2009-08-25정기AAA(sf)AAA(sf)부2017-10-312017-11-01
22142215SLBS 2009-04나이스신용평가2009-08-25정기AAA(sf)AAA(sf)부2017-10-132017-10-13
22152216SLBS 2009-04나이스신용평가2009-08-25정기AAA(sf)AAA(sf)부2016-11-222016-11-22
22162217SLBS 2009-04한국신용평가2009-08-25정기<NA>AAA(sf)부2016-10-242016-10-24
22172218SLBS 2009-04나이스신용평가2009-08-25정기AAA(sf)AAA(sf)부2015-10-302015-10-30
22182219SLBS 2009-04나이스신용평가2009-08-25정기<NA>AAA(sf)부2014-10-212014-10-21