Overview

Dataset statistics

Number of variables6
Number of observations522
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.1 KiB
Average record size in memory53.3 B

Variable types

Numeric4
Categorical2

Dataset

Description주택재개발 주택재건축 등 도시 및 주거환경정비법에 따른 정비사업에 대하여 주택도시보증공사가 발급한 정비사업대출보증 현황(시군구별)
Author주택도시보증공사
URLhttps://www.data.go.kr/data/15012531/fileData.do

Alerts

이주비대출보증 대출금총액(원) is highly overall correlated with 부담금대출보증 대출금총액(원) and 1 other fieldsHigh correlation
부담금대출보증 대출금총액(원) is highly overall correlated with 이주비대출보증 대출금총액(원) and 1 other fieldsHigh correlation
사업비대출보증 대출금총액(원) is highly overall correlated with 이주비대출보증 대출금총액(원) and 1 other fieldsHigh correlation
이주비대출보증 대출금총액(원) has 66 (12.6%) zerosZeros
부담금대출보증 대출금총액(원) has 111 (21.3%) zerosZeros
사업비대출보증 대출금총액(원) has 74 (14.2%) zerosZeros

Reproduction

Analysis started2023-12-12 00:46:09.942447
Analysis finished2023-12-12 00:46:12.308519
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct12
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.2893
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:46:12.372535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12016
median2018
Q32021
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9104748
Coefficient of variation (CV)0.0014420504
Kurtosis-0.9612204
Mean2018.2893
Median Absolute Deviation (MAD)2
Skewness-0.18628103
Sum1053547
Variance8.4708636
MonotonicityIncreasing
2023-12-12T09:46:12.518160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2022 59
11.3%
2019 58
11.1%
2018 57
10.9%
2021 56
10.7%
2020 54
10.3%
2017 52
10.0%
2015 48
9.2%
2016 48
9.2%
2014 31
5.9%
2023 30
5.7%
Other values (2) 29
5.6%
ValueCountFrequency (%)
2012 8
 
1.5%
2013 21
 
4.0%
2014 31
5.9%
2015 48
9.2%
2016 48
9.2%
2017 52
10.0%
2018 57
10.9%
2019 58
11.1%
2020 54
10.3%
2021 56
10.7%
ValueCountFrequency (%)
2023 30
5.7%
2022 59
11.3%
2021 56
10.7%
2020 54
10.3%
2019 58
11.1%
2018 57
10.9%
2017 52
10.0%
2016 48
9.2%
2015 48
9.2%
2014 31
5.9%

분기
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2
139 
4
130 
3
127 
1
126 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
2 139
26.6%
4 130
24.9%
3 127
24.3%
1 126
24.1%

Length

2023-12-12T09:46:12.698268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:46:12.841313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 139
26.6%
4 130
24.9%
3 127
24.3%
1 126
24.1%

지역명
Categorical

Distinct16
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
서울특별시
45 
부산광역시
44 
경상남도
43 
광주광역시
42 
경기도
39 
Other values (11)
309 

Length

Max length7
Median length5
Mean length4.4444444
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row서울특별시
2nd row광주광역시
3rd row부산광역시
4th row서울특별시
5th row경기도

Common Values

ValueCountFrequency (%)
서울특별시 45
 
8.6%
부산광역시 44
 
8.4%
경상남도 43
 
8.2%
광주광역시 42
 
8.0%
경기도 39
 
7.5%
충청남도 39
 
7.5%
대구광역시 38
 
7.3%
대전광역시 38
 
7.3%
전라북도 35
 
6.7%
인천광역시 34
 
6.5%
Other values (6) 125
23.9%

Length

2023-12-12T09:46:12.979803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 45
 
8.6%
부산광역시 44
 
8.4%
경상남도 43
 
8.2%
광주광역시 42
 
8.0%
경기도 39
 
7.5%
충청남도 39
 
7.5%
대구광역시 38
 
7.3%
대전광역시 38
 
7.3%
전라북도 35
 
6.7%
인천광역시 34
 
6.5%
Other values (6) 125
23.9%

이주비대출보증 대출금총액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct455
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7164001 × 1010
Minimum0
Maximum5.70773 × 1011
Zeros66
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:46:13.161658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.9075 × 108
median7.308 × 109
Q34.7131354 × 1010
95-th percentile2.4363745 × 1011
Maximum5.70773 × 1011
Range5.70773 × 1011
Interquartile range (IQR)4.6740604 × 1010

Descriptive statistics

Standard deviation8.8235717 × 1010
Coefficient of variation (CV)1.8708276
Kurtosis8.76418
Mean4.7164001 × 1010
Median Absolute Deviation (MAD)7.308 × 109
Skewness2.81628
Sum2.4619609 × 1013
Variance7.7855418 × 1021
MonotonicityNot monotonic
2023-12-12T09:46:13.356547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
 
12.6%
40000000 2
 
0.4%
210000000 2
 
0.4%
33612597772 1
 
0.2%
11220600000 1
 
0.2%
204320000 1
 
0.2%
465043000000 1
 
0.2%
8909300000 1
 
0.2%
43900000 1
 
0.2%
123600000 1
 
0.2%
Other values (445) 445
85.2%
ValueCountFrequency (%)
0 66
12.6%
20000000 1
 
0.2%
30000000 1
 
0.2%
40000000 2
 
0.4%
43900000 1
 
0.2%
50000000 1
 
0.2%
52300000 1
 
0.2%
55000000 1
 
0.2%
56000000 1
 
0.2%
62900000 1
 
0.2%
ValueCountFrequency (%)
570773000000 1
0.2%
516349000000 1
0.2%
481017000000 1
0.2%
465856000000 1
0.2%
465043000000 1
0.2%
415507000000 1
0.2%
379237000000 1
0.2%
363578000000 1
0.2%
361250000000 1
0.2%
357580000000 1
0.2%

부담금대출보증 대출금총액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct403
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4847215 × 1010
Minimum0
Maximum2.2375 × 1011
Zeros111
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:46:13.510111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.6808 × 108
median6.8378079 × 109
Q32.3590421 × 1010
95-th percentile1.2778825 × 1011
Maximum2.2375 × 1011
Range2.2375 × 1011
Interquartile range (IQR)2.2822341 × 1010

Descriptive statistics

Standard deviation4.2776889 × 1010
Coefficient of variation (CV)1.721597
Kurtosis6.0459329
Mean2.4847215 × 1010
Median Absolute Deviation (MAD)6.8378079 × 109
Skewness2.4847167
Sum1.2970246 × 1013
Variance1.8298622 × 1021
MonotonicityNot monotonic
2023-12-12T09:46:13.669161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 111
 
21.3%
3130470839 3
 
0.6%
747440000 3
 
0.6%
768080000 3
 
0.6%
2254459384 2
 
0.4%
874963000 2
 
0.4%
754841000 2
 
0.4%
4347870000 1
 
0.2%
3423957444 1
 
0.2%
11397399290 1
 
0.2%
Other values (393) 393
75.3%
ValueCountFrequency (%)
0 111
21.3%
11190000 1
 
0.2%
14180000 1
 
0.2%
29302725 1
 
0.2%
48753000 1
 
0.2%
60930000 1
 
0.2%
67000000 1
 
0.2%
72360000 1
 
0.2%
82000000 1
 
0.2%
324772000 1
 
0.2%
ValueCountFrequency (%)
223750000000 1
0.2%
219506000000 1
0.2%
212187000000 1
0.2%
200031000000 1
0.2%
199242000000 1
0.2%
193391000000 1
0.2%
193024000000 1
0.2%
191029000000 1
0.2%
190133000000 1
0.2%
180648000000 1
0.2%

사업비대출보증 대출금총액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct446
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4240319 × 1010
Minimum0
Maximum9.43666 × 1011
Zeros74
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:46:13.830702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.1898279 × 109
median1.6142333 × 1010
Q38.257024 × 1010
95-th percentile4.5590915 × 1011
Maximum9.43666 × 1011
Range9.43666 × 1011
Interquartile range (IQR)8.0380412 × 1010

Descriptive statistics

Standard deviation1.5314401 × 1011
Coefficient of variation (CV)1.817942
Kurtosis7.1054567
Mean8.4240319 × 1010
Median Absolute Deviation (MAD)1.6142333 × 1010
Skewness2.6216727
Sum4.3973447 × 1013
Variance2.3453089 × 1022
MonotonicityNot monotonic
2023-12-12T09:46:13.969552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 74
 
14.2%
1500000000 3
 
0.6%
100000000 2
 
0.4%
139105000000 1
 
0.2%
77830414088 1
 
0.2%
43681897050 1
 
0.2%
114421000000 1
 
0.2%
80733108616 1
 
0.2%
7286014806 1
 
0.2%
10542190971 1
 
0.2%
Other values (436) 436
83.5%
ValueCountFrequency (%)
0 74
14.2%
22762450 1
 
0.2%
100000000 2
 
0.4%
110373965 1
 
0.2%
196369703 1
 
0.2%
246333147 1
 
0.2%
280679000 1
 
0.2%
323444400 1
 
0.2%
342458204 1
 
0.2%
365713926 1
 
0.2%
ValueCountFrequency (%)
943666000000 1
0.2%
885015000000 1
0.2%
766951000000 1
0.2%
739032000000 1
0.2%
688450000000 1
0.2%
685662000000 1
0.2%
656864000000 1
0.2%
646091000000 1
0.2%
641913000000 1
0.2%
609909000000 1
0.2%

Interactions

2023-12-12T09:46:11.615490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.189981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.552314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.885426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:11.729128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.276557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.636354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.972558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:11.846987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.382040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.716168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:11.420430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:11.943063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.475553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:10.802381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:11.518612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:46:14.061448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도분기지역명이주비대출보증 대출금총액(원)부담금대출보증 대출금총액(원)사업비대출보증 대출금총액(원)
연도1.0000.0000.0000.1620.3190.053
분기0.0001.0000.0000.0670.0000.000
지역명0.0000.0001.0000.5120.6310.582
이주비대출보증 대출금총액(원)0.1620.0670.5121.0000.7800.782
부담금대출보증 대출금총액(원)0.3190.0000.6310.7801.0000.836
사업비대출보증 대출금총액(원)0.0530.0000.5820.7820.8361.000
2023-12-12T09:46:14.168120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명분기
지역명1.0000.000
분기0.0001.000
2023-12-12T09:46:14.281323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도이주비대출보증 대출금총액(원)부담금대출보증 대출금총액(원)사업비대출보증 대출금총액(원)분기지역명
연도1.0000.1470.2190.2920.0000.000
이주비대출보증 대출금총액(원)0.1471.0000.5840.7920.0390.227
부담금대출보증 대출금총액(원)0.2190.5841.0000.6190.0000.305
사업비대출보증 대출금총액(원)0.2920.7920.6191.0000.0000.270
분기0.0000.0390.0000.0001.0000.000
지역명0.0000.2270.3050.2700.0001.000

Missing values

2023-12-12T09:46:12.099252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:46:12.252416image/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

연도분기지역명이주비대출보증 대출금총액(원)부담금대출보증 대출금총액(원)사업비대출보증 대출금총액(원)
020122서울특별시259000000005849000000
120123광주광역시0143879500000
220123부산광역시6646400000146993921000
320123서울특별시1346790000007484802949
420124경기도099430390000
520124경상남도538390000006423424486
620124부산광역시163280000025323276000
720124서울특별시1035730000000256074000000
820131경상남도467510000003634015644
920131광주광역시0187790400000
연도분기지역명이주비대출보증 대출금총액(원)부담금대출보증 대출금총액(원)사업비대출보증 대출금총액(원)
51220232대전광역시44237000002027637400034094545778
51320232부산광역시4717146000022113780530163044000000
51420232서울특별시23516300000077393855941126675000000
51520232세종특별자치시0028042348001
51620232울산광역시78000000012236415352
51720232인천광역시323891200004378388600048024973323
51820232전라북도252659000005083675907
51920232제주특별자치도053640660000
52020232충청남도0060620180851
52120232충청북도30122280000031642665623