Overview

Dataset statistics

Number of variables4
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory36.9 B

Variable types

Categorical4

Dataset

Description2022년 12월말 기준 지역별, 공사 신용평가등급별 PF대출보증 및 정비사업대출보증의 승인현황(건수)에 대한 데이터
URLhttps://www.data.go.kr/data/15113716/fileData.do

Reproduction

Analysis started2023-12-12 00:17:05.753801
Analysis finished2023-12-12 00:17:06.036800
Duration0.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
정비사업대출보증(사업비)
24 
PF보증
10 

Length

Max length13
Median length13
Mean length10.352941
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정비사업대출보증(사업비) 24
70.6%
PF보증 10
29.4%

Length

2023-12-12T09:17:06.094700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:06.184236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정비사업대출보증(사업비 24
70.6%
pf보증 10
29.4%

신용평가등급
Categorical

Distinct7
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
AAA
13 
AA
6 
A+
5 
BBB+
4 
BBB-
3 
Other values (2)
3 

Length

Max length4
Median length3
Mean length2.8235294
Min length2

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st rowAAA
2nd rowAAA
3rd rowAAA
4th rowAA
5th rowA+

Common Values

ValueCountFrequency (%)
AAA 13
38.2%
AA 6
17.6%
A+ 5
 
14.7%
BBB+ 4
 
11.8%
BBB- 3
 
8.8%
A- 2
 
5.9%
BB+ 1
 
2.9%

Length

2023-12-12T09:17:06.297466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:06.414512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aaa 13
38.2%
a 7
20.6%
bbb 7
20.6%
aa 6
17.6%
bb 1
 
2.9%

시도
Categorical

Distinct12
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size404.0 B
경기도
8 
서울특별시
5 
인천광역시
4 
경상남도
4 
충청남도
2 
Other values (7)
11 

Length

Max length5
Median length5
Mean length4.2941176
Min length3

Unique

Unique3 ?
Unique (%)8.8%

Sample

1st row인천광역시
2nd row경기도
3rd row경상남도
4th row서울특별시
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 8
23.5%
서울특별시 5
14.7%
인천광역시 4
11.8%
경상남도 4
11.8%
충청남도 2
 
5.9%
부산광역시 2
 
5.9%
대구광역시 2
 
5.9%
대전광역시 2
 
5.9%
광주광역시 2
 
5.9%
울산광역시 1
 
2.9%
Other values (2) 2
 
5.9%

Length

2023-12-12T09:17:06.553945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 8
23.5%
서울특별시 5
14.7%
인천광역시 4
11.8%
경상남도 4
11.8%
충청남도 2
 
5.9%
부산광역시 2
 
5.9%
대구광역시 2
 
5.9%
대전광역시 2
 
5.9%
광주광역시 2
 
5.9%
울산광역시 1
 
2.9%
Other values (2) 2
 
5.9%

건수
Categorical

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
1
22 
2
7 
4
3 
3
 
1
10
 
1

Length

Max length2
Median length1
Mean length1.0294118
Min length1

Unique

Unique2 ?
Unique (%)5.9%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 22
64.7%
2 7
 
20.6%
4 3
 
8.8%
3 1
 
2.9%
10 1
 
2.9%

Length

2023-12-12T09:17:06.689223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:06.793415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
64.7%
2 7
 
20.6%
4 3
 
8.8%
3 1
 
2.9%
10 1
 
2.9%

Correlations

2023-12-12T09:17:06.873100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분신용평가등급시도건수
구분1.0000.0000.0000.174
신용평가등급0.0001.0000.0000.000
시도0.0000.0001.0000.000
건수0.1740.0000.0001.000
2023-12-12T09:17:07.198222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도구분건수신용평가등급
시도1.0000.0000.0000.000
구분0.0001.0000.1930.000
건수0.0000.1931.0000.000
신용평가등급0.0000.0000.0001.000
2023-12-12T09:17:07.281742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분신용평가등급시도건수
구분1.0000.0000.0000.193
신용평가등급0.0001.0000.0000.000
시도0.0000.0001.0000.000
건수0.1930.0000.0001.000

Missing values

2023-12-12T09:17:05.935696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:17:06.008349image/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

구분신용평가등급시도건수
0PF보증AAA인천광역시2
1PF보증AAA경기도1
2PF보증AAA경상남도1
3PF보증AA서울특별시1
4PF보증A+경기도3
5PF보증A+경상남도1
6PF보증A-경기도1
7PF보증BBB+울산광역시1
8PF보증BBB+충청남도1
9PF보증BBB-경기도1
구분신용평가등급시도건수
24정비사업대출보증(사업비)AA경상남도1
25정비사업대출보증(사업비)A+서울특별시1
26정비사업대출보증(사업비)A+부산광역시1
27정비사업대출보증(사업비)A+대구광역시1
28정비사업대출보증(사업비)A-서울특별시1
29정비사업대출보증(사업비)BBB+인천광역시1
30정비사업대출보증(사업비)BBB+경기도2
31정비사업대출보증(사업비)BBB-광주광역시1
32정비사업대출보증(사업비)BBB-경기도1
33정비사업대출보증(사업비)BB+서울특별시1