Overview

Dataset statistics

Number of variables4
Number of observations154
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory35.9 B

Variable types

Numeric3
Categorical1

Dataset

Description최근 5개년동안의 연도별 상품별(분양보증,하자보수보증, 전세보증금반환보증 등) 보증사고 건수 및 금액 데이터를 제공합니다.
Author주택도시보증공사
URLhttps://www.data.go.kr/data/15002597/fileData.do

Alerts

건수 is highly overall correlated with 금액(억원)High correlation
금액(억원) is highly overall correlated with 건수High correlation
건수 has 70 (45.5%) zerosZeros
금액(억원) has 70 (45.5%) zerosZeros

Reproduction

Analysis started2023-10-09 17:05:05.303722
Analysis finished2023-10-09 17:05:07.803173
Duration2.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct7
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.0779
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-10-10T02:05:07.888325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2019
Q32021
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0050018
Coefficient of variation (CV)0.00099302845
Kurtosis-1.2460628
Mean2019.0779
Median Absolute Deviation (MAD)2
Skewness-0.059032885
Sum310938
Variance4.0200323
MonotonicityIncreasing
2023-10-10T02:05:08.097772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2020 23
14.9%
2021 23
14.9%
2022 23
14.9%
2019 22
14.3%
2016 21
13.6%
2017 21
13.6%
2018 21
13.6%
ValueCountFrequency (%)
2016 21
13.6%
2017 21
13.6%
2018 21
13.6%
2019 22
14.3%
2020 23
14.9%
2021 23
14.9%
2022 23
14.9%
ValueCountFrequency (%)
2022 23
14.9%
2021 23
14.9%
2020 23
14.9%
2019 22
14.3%
2018 21
13.6%
2017 21
13.6%
2016 21
13.6%

보증종류
Categorical

Distinct28
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
주택분양보증
 
7
전세보증금반환보증
 
7
기금전세자금대출
 
7
임대주택매입자금보증
 
7
전세임대사업 임차료지급보증
 
7
Other values (23)
119 

Length

Max length17
Median length15
Mean length7.7857143
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row주택분양보증
2nd row주택임대보증
3rd row주상복합분양보증
4th row조합주택시공보증
5th row하자보수보증

Common Values

ValueCountFrequency (%)
주택분양보증 7
 
4.5%
전세보증금반환보증 7
 
4.5%
기금전세자금대출 7
 
4.5%
임대주택매입자금보증 7
 
4.5%
전세임대사업 임차료지급보증 7
 
4.5%
하자보수보증 7
 
4.5%
인허가보증 7
 
4.5%
감리비예치보증 7
 
4.5%
임대보증금보증 7
 
4.5%
조합주택시공보증 7
 
4.5%
Other values (18) 84
54.5%

Length

2023-10-10T02:05:08.396249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pf보증 10
 
6.0%
주택분양보증 7
 
4.2%
조합주택시공보증 7
 
4.2%
전세임대주택반환 7
 
4.2%
주택임대보증 7
 
4.2%
전세보증금반환보증 7
 
4.2%
주택임차자금보증 7
 
4.2%
주택구입자금보증 7
 
4.2%
모기지보증 7
 
4.2%
전세대출특약보증 7
 
4.2%
Other values (20) 95
56.5%

건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150.3961
Minimum0
Maximum5443
Zeros70
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-10-10T02:05:08.687787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q322.75
95-th percentile891.6
Maximum5443
Range5443
Interquartile range (IQR)22.75

Descriptive statistics

Standard deviation569.04516
Coefficient of variation (CV)3.783643
Kurtosis53.163564
Mean150.3961
Median Absolute Deviation (MAD)1
Skewness6.6299996
Sum23161
Variance323812.4
MonotonicityNot monotonic
2023-10-10T02:05:08.935884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 70
45.5%
1 13
 
8.4%
2 10
 
6.5%
4 8
 
5.2%
5 4
 
2.6%
3 3
 
1.9%
8 3
 
1.9%
31 2
 
1.3%
86 2
 
1.3%
53 2
 
1.3%
Other values (37) 37
24.0%
ValueCountFrequency (%)
0 70
45.5%
1 13
 
8.4%
2 10
 
6.5%
3 3
 
1.9%
4 8
 
5.2%
5 4
 
2.6%
8 3
 
1.9%
11 1
 
0.6%
19 1
 
0.6%
20 1
 
0.6%
ValueCountFrequency (%)
5443 1
0.6%
2799 1
0.6%
2408 1
0.6%
1630 1
0.6%
1109 1
0.6%
954 1
0.6%
939 1
0.6%
902 1
0.6%
886 1
0.6%
852 1
0.6%

금액(억원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)46.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.12727
Minimum0
Maximum11726
Zeros70
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-10-10T02:05:09.255123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.2
Q3113
95-th percentile1408.9
Maximum11726
Range11726
Interquartile range (IQR)113

Descriptive statistics

Standard deviation1178.8338
Coefficient of variation (CV)3.7172261
Kurtosis61.422137
Mean317.12727
Median Absolute Deviation (MAD)1.2
Skewness7.1727603
Sum48837.6
Variance1389649.1
MonotonicityNot monotonic
2023-10-10T02:05:09.654037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 70
45.5%
2.0 6
 
3.9%
1.0 4
 
2.6%
4.0 3
 
1.9%
13.0 2
 
1.3%
9.0 2
 
1.3%
3.0 2
 
1.3%
23.0 2
 
1.3%
517.0 1
 
0.6%
5.0 1
 
0.6%
Other values (61) 61
39.6%
ValueCountFrequency (%)
0.0 70
45.5%
0.1 1
 
0.6%
0.4 1
 
0.6%
0.7 1
 
0.6%
1.0 4
 
2.6%
1.4 1
 
0.6%
2.0 6
 
3.9%
3.0 2
 
1.3%
4.0 3
 
1.9%
5.0 1
 
0.6%
ValueCountFrequency (%)
11726.0 1
0.6%
5790.0 1
0.6%
4682.0 1
0.6%
3442.0 1
0.6%
2022.0 1
0.6%
1806.0 1
0.6%
1485.0 1
0.6%
1444.0 1
0.6%
1390.0 1
0.6%
1257.0 1
0.6%

Interactions

2023-10-10T02:05:06.853174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:05.598869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:06.271641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:07.096465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:05.805139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:06.493022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:07.274637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:06.022739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-10T02:05:06.672560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-10-10T02:05:10.004499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도보증종류건수금액(억원)
연도1.0000.0000.0000.000
보증종류0.0001.0000.0000.221
건수0.0000.0001.0000.996
금액(억원)0.0000.2210.9961.000
2023-10-10T02:05:10.247719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도건수금액(억원)보증종류
연도1.0000.0830.0620.000
건수0.0831.0000.9120.000
금액(억원)0.0620.9121.0000.086
보증종류0.0000.0000.0861.000

Missing values

2023-10-10T02:05:07.541778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-10T02:05:07.739056image/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

연도보증종류건수금액(억원)
02016주택분양보증2517.0
12016주택임대보증00.0
22016주상복합분양보증00.0
32016조합주택시공보증3502.0
42016하자보수보증1113.0
52016인허가보증00.0
62016감리비예치보증00.0
72016임대보증금보증00.0
82016PF보증00.0
92016하도급보증00.0
연도보증종류건수금액(억원)
1442022주택구입자금보증5991224.0
1452022주택임차자금보증21.0
1462022정비사업자급대출보증193283.0
1472022리모델링자금보증14.0
1482022전세임대주택반환53.0
1492022기금전세자금대출00.0
1502022전세보증금반환보증544311726.0
1512022전세대출특약보증11091485.0
1522022전세임대사업 임차료지급보증862.0
1532022임대주택매입자금보증00.0