Overview

Dataset statistics

Number of variables11
Number of observations768
Missing cells20
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.4 KiB
Average record size in memory91.2 B

Variable types

Numeric3
Text2
Categorical3
DateTime3

Dataset

Description인천광역시 중구에 소재하는 공동주택(다세대주택) 현황에 관한 정보입니다.파일명 인천광역시_중구_주택현황파일내용 단지명, 법정동명, 용도구분 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15006816&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 관할부서High correlation
동수 is highly overall correlated with 연면적 High correlation
연면적 is highly overall correlated with 동수 High correlation
법정동명 is highly overall correlated with 관할부서High correlation
관할부서 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
용도구분 is highly imbalanced (74.0%)Imbalance
단지명 has 16 (2.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:24:25.990904
Analysis finished2024-03-18 05:24:29.273108
Duration3.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct768
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean384.5
Minimum1
Maximum768
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-03-18T14:24:29.338224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile39.35
Q1192.75
median384.5
Q3576.25
95-th percentile729.65
Maximum768
Range767
Interquartile range (IQR)383.5

Descriptive statistics

Standard deviation221.84679
Coefficient of variation (CV)0.57697476
Kurtosis-1.2
Mean384.5
Median Absolute Deviation (MAD)192
Skewness0
Sum295296
Variance49216
MonotonicityStrictly increasing
2024-03-18T14:24:29.462449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
386 1
 
0.1%
508 1
 
0.1%
509 1
 
0.1%
510 1
 
0.1%
511 1
 
0.1%
512 1
 
0.1%
513 1
 
0.1%
514 1
 
0.1%
515 1
 
0.1%
Other values (758) 758
98.7%
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 (%)
768 1
0.1%
767 1
0.1%
766 1
0.1%
765 1
0.1%
764 1
0.1%
763 1
0.1%
762 1
0.1%
761 1
0.1%
760 1
0.1%
759 1
0.1%

단지명
Text

MISSING 

Distinct663
Distinct (%)88.2%
Missing16
Missing (%)2.1%
Memory size6.1 KiB
2024-03-18T14:24:29.677278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length6.9095745
Min length2

Characters and Unicode

Total characters5196
Distinct characters284
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique598 ?
Unique (%)79.5%

Sample

1st row월미맨숀 A동, B동
2nd row우진연립 가동, 나동, 다동
3rd row월미연립
4th row금강빌라
5th row로얄연립 A동, B동
ValueCountFrequency (%)
a동 57
 
4.7%
b동 55
 
4.6%
1동 44
 
3.7%
나동 38
 
3.2%
2동 37
 
3.1%
가동 36
 
3.0%
c동 18
 
1.5%
현대빌라 14
 
1.2%
전동빌리지 10
 
0.8%
3동 10
 
0.8%
Other values (505) 882
73.4%
2024-03-18T14:24:30.036003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 564
 
10.9%
동 484
 
9.3%
449
 
8.6%
라 433
 
8.3%
1 139
 
2.7%
리 80
 
1.5%
, 77
 
1.5%
지 76
 
1.5%
2 74
 
1.4%
성 73
 
1.4%
Other values (274) 2747
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4103
79.0%
Space Separator 449
 
8.6%
Decimal Number 362
 
7.0%
Uppercase Letter 189
 
3.6%
Other Punctuation 77
 
1.5%
Lowercase Letter 12
 
0.2%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 564
 
13.7%
동 484
 
11.8%
라 433
 
10.6%
리 80
 
1.9%
지 76
 
1.9%
성 73
 
1.8%
스 69
 
1.7%
이 61
 
1.5%
트 61
 
1.5%
대 60
 
1.5%
Other values (234) 2142
52.2%
Uppercase Letter
ValueCountFrequency (%)
A 60
31.7%
B 57
30.2%
C 19
 
10.1%
O 9
 
4.8%
D 8
 
4.2%
M 7
 
3.7%
E 4
 
2.1%
R 4
 
2.1%
S 3
 
1.6%
K 3
 
1.6%
Other values (10) 15
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 139
38.4%
2 74
20.4%
0 61
16.9%
3 27
 
7.5%
4 17
 
4.7%
5 15
 
4.1%
6 11
 
3.0%
7 7
 
1.9%
8 6
 
1.7%
9 5
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
c 3
25.0%
e 3
25.0%
y 2
16.7%
k 2
16.7%
i 1
 
8.3%
t 1
 
8.3%
Space Separator
ValueCountFrequency (%)
449
100.0%
Other Punctuation
ValueCountFrequency (%)
, 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4103
79.0%
Common 892
 
17.2%
Latin 201
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 564
 
13.7%
동 484
 
11.8%
라 433
 
10.6%
리 80
 
1.9%
지 76
 
1.9%
성 73
 
1.8%
스 69
 
1.7%
이 61
 
1.5%
트 61
 
1.5%
대 60
 
1.5%
Other values (234) 2142
52.2%
Latin
ValueCountFrequency (%)
A 60
29.9%
B 57
28.4%
C 19
 
9.5%
O 9
 
4.5%
D 8
 
4.0%
M 7
 
3.5%
E 4
 
2.0%
R 4
 
2.0%
c 3
 
1.5%
S 3
 
1.5%
Other values (16) 27
13.4%
Common
ValueCountFrequency (%)
449
50.3%
1 139
 
15.6%
, 77
 
8.6%
2 74
 
8.3%
0 61
 
6.8%
3 27
 
3.0%
4 17
 
1.9%
5 15
 
1.7%
6 11
 
1.2%
7 7
 
0.8%
Other values (4) 15
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4103
79.0%
ASCII 1093
 
21.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 564
 
13.7%
동 484
 
11.8%
라 433
 
10.6%
리 80
 
1.9%
지 76
 
1.9%
성 73
 
1.8%
스 69
 
1.7%
이 61
 
1.5%
트 61
 
1.5%
대 60
 
1.5%
Other values (234) 2142
52.2%
ASCII
ValueCountFrequency (%)
449
41.1%
1 139
 
12.7%
, 77
 
7.0%
2 74
 
6.8%
0 61
 
5.6%
A 60
 
5.5%
B 57
 
5.2%
3 27
 
2.5%
C 19
 
1.7%
4 17
 
1.6%
Other values (30) 113
 
10.3%

법정동명
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
율목동
138 
도원동
115 
송월동1가
83 
전동
64 
운북동
64 
Other values (36)
304 

Length

Max length6
Median length3
Mean length3.5
Min length2

Unique

Unique12 ?
Unique (%)1.6%

Sample

1st row북성동1가
2nd row북성동1가
3rd row북성동1가
4th row북성동1가
5th row북성동1가

Common Values

ValueCountFrequency (%)
율목동 138
18.0%
도원동 115
15.0%
송월동1가 83
10.8%
전동 64
8.3%
운북동 64
8.3%
운남동 43
 
5.6%
신흥동2가 42
 
5.5%
북성동2가 23
 
3.0%
송월동3가 20
 
2.6%
선화동 19
 
2.5%
Other values (31) 157
20.4%

Length

2024-03-18T14:24:30.168691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
율목동 138
18.0%
도원동 115
15.0%
송월동1가 83
10.8%
운북동 65
8.5%
전동 64
8.3%
운남동 46
 
6.0%
신흥동2가 42
 
5.5%
중산동 26
 
3.4%
북성동2가 24
 
3.1%
송월동3가 21
 
2.7%
Other values (24) 144
18.8%

용도구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
다세대
687 
아파트
 
57
연립
 
20
연립주택
 
3
연립(1동)다세대(2동)
 
1

Length

Max length13
Median length3
Mean length2.9908854
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row연립
2nd row연립
3rd row연립
4th row다세대
5th row연립

Common Values

ValueCountFrequency (%)
다세대 687
89.5%
아파트 57
 
7.4%
연립 20
 
2.6%
연립주택 3
 
0.4%
연립(1동)다세대(2동) 1
 
0.1%

Length

2024-03-18T14:24:30.281913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:24:30.397759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대 687
89.5%
아파트 57
 
7.4%
연립 20
 
2.6%
연립주택 3
 
0.4%
연립(1동)다세대(2동 1
 
0.1%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3255208
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-03-18T14:24:30.483241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum19
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5583479
Coefficient of variation (CV)1.1756495
Kurtosis72.603529
Mean1.3255208
Median Absolute Deviation (MAD)0
Skewness8.0166277
Sum1018
Variance2.4284482
MonotonicityNot monotonic
2024-03-18T14:24:30.571840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 667
86.8%
2 77
 
10.0%
3 6
 
0.8%
6 4
 
0.5%
5 3
 
0.4%
8 2
 
0.3%
12 2
 
0.3%
10 1
 
0.1%
18 1
 
0.1%
19 1
 
0.1%
Other values (4) 4
 
0.5%
ValueCountFrequency (%)
1 667
86.8%
2 77
 
10.0%
3 6
 
0.8%
5 3
 
0.4%
6 4
 
0.5%
7 1
 
0.1%
8 2
 
0.3%
10 1
 
0.1%
12 2
 
0.3%
13 1
 
0.1%
ValueCountFrequency (%)
19 1
 
0.1%
18 1
 
0.1%
17 1
 
0.1%
16 1
 
0.1%
13 1
 
0.1%
12 2
0.3%
10 1
 
0.1%
8 2
0.3%
7 1
 
0.1%
6 4
0.5%

세대수
Text

Distinct52
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-03-18T14:24:30.721816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.6132812
Min length1

Characters and Unicode

Total characters1239
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)3.8%

Sample

1st row28
2nd row16
3rd row8
4th row10
5th row8
ValueCountFrequency (%)
8 172
22.4%
10 131
17.1%
12 64
 
8.3%
16 48
 
6.2%
15 42
 
5.5%
9 42
 
5.5%
19 41
 
5.3%
14 37
 
4.8%
6 35
 
4.6%
4 22
 
2.9%
Other values (42) 134
17.4%
2024-03-18T14:24:30.986413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 416
33.6%
8 186
15.0%
0 146
 
11.8%
2 94
 
7.6%
9 93
 
7.5%
6 89
 
7.2%
4 81
 
6.5%
5 71
 
5.7%
3 31
 
2.5%
7 29
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1236
99.8%
Other Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 416
33.7%
8 186
15.0%
0 146
 
11.8%
2 94
 
7.6%
9 93
 
7.5%
6 89
 
7.2%
4 81
 
6.6%
5 71
 
5.7%
3 31
 
2.5%
7 29
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1239
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 416
33.6%
8 186
15.0%
0 146
 
11.8%
2 94
 
7.6%
9 93
 
7.5%
6 89
 
7.2%
4 81
 
6.5%
5 71
 
5.7%
3 31
 
2.5%
7 29
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 416
33.6%
8 186
15.0%
0 146
 
11.8%
2 94
 
7.6%
9 93
 
7.5%
6 89
 
7.2%
4 81
 
6.5%
5 71
 
5.7%
3 31
 
2.5%
7 29
 
2.3%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct685
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3673.3557
Minimum117.96
Maximum235474.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-03-18T14:24:31.106616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum117.96
5-th percentile270.8505
Q1397.665
median568.175
Q3658.125
95-th percentile1819.106
Maximum235474.57
Range235356.61
Interquartile range (IQR)260.46

Descriptive statistics

Standard deviation21377.681
Coefficient of variation (CV)5.8196599
Kurtosis76.043353
Mean3673.3557
Median Absolute Deviation (MAD)129.33
Skewness8.4143547
Sum2821137.2
Variance4.5700524 × 108
MonotonicityNot monotonic
2024-03-18T14:24:31.222671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
656.96 8
 
1.0%
604.45 6
 
0.8%
329.76 5
 
0.7%
1302.5 4
 
0.5%
666.11 4
 
0.5%
649.36 4
 
0.5%
585.9 4
 
0.5%
569.8 4
 
0.5%
617.1 3
 
0.4%
601.2 3
 
0.4%
Other values (675) 723
94.1%
ValueCountFrequency (%)
117.96 1
0.1%
121.66 1
0.1%
125.05 1
0.1%
146.88 1
0.1%
165.94 1
0.1%
166.2 1
0.1%
168.35 1
0.1%
170.67 1
0.1%
179.82 1
0.1%
180.86 1
0.1%
ValueCountFrequency (%)
235474.5717 1
0.1%
229547.9489 1
0.1%
219861.4241 1
0.1%
218897.21 1
0.1%
182954.6627 1
0.1%
175962.1862 1
0.1%
139442.343 1
0.1%
117020.848 1
0.1%
100638.4622 1
0.1%
97651.4473 1
0.1%

건축허가일
Date

Distinct482
Distinct (%)63.1%
Missing4
Missing (%)0.5%
Memory size6.1 KiB
Minimum1978-04-27 00:00:00
Maximum2022-03-12 00:00:00
2024-03-18T14:24:31.348290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:31.493706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

Distinct566
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
Minimum1978-09-26 00:00:00
Maximum2023-03-23 00:00:00
2024-03-18T14:24:31.608546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:31.732851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관할부서
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
건축과
610 
허가민원과
117 
건축허가과
 
41

Length

Max length5
Median length3
Mean length3.4114583
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건축과 610
79.4%
허가민원과 117
 
15.2%
건축허가과 41
 
5.3%

Length

2024-03-18T14:24:31.851817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:24:32.232130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축과 610
79.4%
허가민원과 117
 
15.2%
건축허가과 41
 
5.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
Minimum2023-08-30 00:00:00
Maximum2023-08-30 00:00:00
2024-03-18T14:24:32.307235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:32.384416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T14:24:28.705289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.151488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.463761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.786489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.286356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.552325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.863654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.388404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:24:28.629939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:24:32.451696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법정동명용도구분동수세대수연면적관할부서
연번1.0000.8500.5990.3020.5770.2950.860
법정동명0.8501.0000.7680.7700.9040.7710.938
용도구분0.5990.7681.0000.4180.7810.4090.352
동수0.3020.7700.4181.0000.9960.9630.603
세대수0.5770.9040.7810.9961.0000.9980.816
연면적0.2950.7710.4090.9630.9981.0000.598
관할부서0.8600.9380.3520.6030.8160.5981.000
2024-03-18T14:24:32.555307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명용도구분관할부서
법정동명1.0000.4700.786
용도구분0.4701.0000.284
관할부서0.7860.2841.000
2024-03-18T14:24:32.635809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수연면적법정동명용도구분관할부서
연번1.0000.3650.2110.4830.2890.780
동수0.3651.0000.5090.4120.2720.471
연면적0.2110.5091.0000.4130.2650.465
법정동명0.4830.4120.4131.0000.4700.786
용도구분0.2890.2720.2650.4701.0000.284
관할부서0.7800.4710.4650.7860.2841.000

Missing values

2024-03-18T14:24:28.962481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:24:29.094289image/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.
2024-03-18T14:24:29.220552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번단지명법정동명용도구분동수세대수연면적건축허가일사용승인일관할부서데이터기준일자
01월미맨숀 A동, B동북성동1가연립2282302.141978-04-271978-09-26건축과2023-08-30
12우진연립 가동, 나동, 다동북성동1가연립3161260.081978-06-211978-12-18건축과2023-08-30
23월미연립북성동1가연립18653.881978-05-271978-12-20건축과2023-08-30
34금강빌라북성동1가다세대1101386.51978-08-041979-03-13건축과2023-08-30
45로얄연립 A동, B동북성동1가연립28451.961980-07-041980-11-24건축과2023-08-30
56정건빌라유동다세대16328.771986-08-011987-06-20건축과2023-08-30
67우진빌라송월동3가다세대16326.881987-03-121987-11-26건축과2023-08-30
78삼형빌라 나동북성동2가다세대19323.371988-06-201988-11-07건축과2023-08-30
89삼형빌라 나동북성동2가다세대18287.281988-06-201988-11-07건축과2023-08-30
910진흥빌라율목동다세대16248.41988-10-101989-02-03건축과2023-08-30
연번단지명법정동명용도구분동수세대수연면적건축허가일사용승인일관할부서데이터기준일자
758759운서역 반도유보라 퍼스티지운서동아파트645097651.44732019-03-062022-02-03건축허가과2023-08-30
759760영종엘에이치67단지중산동아파트345734119.242018-12-312022-03-16건축허가과2023-08-30
760761영종호반써밋1차(호반써밋스카이센트럴)중산동아파트653481184.72482019-05-152022-07-01건축허가과2023-08-30
761762희망꿈터북성동2가연립주택112810.892022-03-112022-07-27건축과2023-08-30
762763운서 SK뷰 스카이시티 2차운남동아파트12909139442.3432020-01-102022-08-25건축허가과2023-08-30
763764웨스턴휴신흥동3가아파트1459622.222022-03-122022-09-06건축과2023-08-30
764765화성파크드림2차운남동아파트849968704.4562018-07-052022-09-08건축허가과2023-08-30
765766동원로얄듀크마리나포레중산동아파트641269130.5732017-06-282022-10-27건축허가과2023-08-30
766767e편한세상영종국제도시센텀베뉴중산동아파트161409235474.57172020-11-242023-03-23건축허가과2023-08-30
767768연넥스운남동다세대3241894.82021-08-032022-11-09건축허가과2023-08-30