Overview

Dataset statistics

Number of variables8
Number of observations655
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.3 KiB
Average record size in memory66.2 B

Variable types

Numeric2
Categorical2
Text3
DateTime1

Dataset

Description초고층 및 지하연계 복합건출물 재난관리에 관한 특별법 및 화재의 예방 및 안전관리에 관한 특별법에 의거한 예방소방행정통계자료 작성을 위한 인천시 관내 고층건축물 현황을 파악하여 작성, 그 대상을 공공데이터에 개방
Author공공데이터포털
URLhttps://www.data.go.kr/data/15105962/fileData.do

Alerts

처종 is highly overall correlated with 용도High correlation
용도 is highly overall correlated with 처종High correlation
처종 is highly imbalanced (60.5%)Imbalance
용도 is highly imbalanced (69.4%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 15:34:46.152490
Analysis finished2024-04-20 15:34:48.732362
Duration2.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct655
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328
Minimum1
Maximum655
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T00:34:48.885373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33.7
Q1164.5
median328
Q3491.5
95-th percentile622.3
Maximum655
Range654
Interquartile range (IQR)327

Descriptive statistics

Standard deviation189.2265
Coefficient of variation (CV)0.57691005
Kurtosis-1.2
Mean328
Median Absolute Deviation (MAD)164
Skewness0
Sum214840
Variance35806.667
MonotonicityStrictly increasing
2024-04-21T00:34:49.153239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
432 1
 
0.2%
434 1
 
0.2%
435 1
 
0.2%
436 1
 
0.2%
437 1
 
0.2%
438 1
 
0.2%
439 1
 
0.2%
440 1
 
0.2%
441 1
 
0.2%
Other values (645) 645
98.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
655 1
0.2%
654 1
0.2%
653 1
0.2%
652 1
0.2%
651 1
0.2%
650 1
0.2%
649 1
0.2%
648 1
0.2%
647 1
0.2%
646 1
0.2%

처종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
공동주택
562 
복합
89 
업무
 
4

Length

Max length4
Median length4
Mean length3.7160305
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 562
85.8%
복합 89
 
13.6%
업무 4
 
0.6%

Length

2024-04-21T00:34:49.410240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:34:49.599266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 562
85.8%
복합 89
 
13.6%
업무 4
 
0.6%

대상물 명칭
Text

Distinct151
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T00:34:50.323277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length10.717557
Min length3

Characters and Unicode

Total characters7020
Distinct characters207
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

Unique46 ?
Unique (%)7.0%

Sample

1st row동인천역파크푸르지오
2nd row동인천역파크푸르지오
3rd row동인천역파크푸르지오
4th row동인천역파크푸르지오
5th row동인천역파크푸르지오
ValueCountFrequency (%)
더샵 66
 
6.0%
아파트 59
 
5.3%
송도 49
 
4.4%
부평센트럴시티 26
 
2.3%
호반베르디움 25
 
2.3%
이편한세상 23
 
2.1%
sk스카이뷰아파트 21
 
1.9%
힐스테이트 21
 
1.9%
마리나베이 19
 
1.7%
1차 15
 
1.4%
Other values (169) 785
70.8%
2024-04-21T00:34:51.332680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
454
 
6.5%
트 331
 
4.7%
스 230
 
3.3%
파 225
 
3.2%
도 205
 
2.9%
더 203
 
2.9%
이 197
 
2.8%
샵 158
 
2.3%
송 149
 
2.1%
아 149
 
2.1%
Other values (197) 4719
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6036
86.0%
Space Separator 454
 
6.5%
Decimal Number 298
 
4.2%
Uppercase Letter 130
 
1.9%
Lowercase Letter 68
 
1.0%
Open Punctuation 15
 
0.2%
Close Punctuation 15
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 331
 
5.5%
스 230
 
3.8%
파 225
 
3.7%
도 205
 
3.4%
더 203
 
3.4%
이 197
 
3.3%
샵 158
 
2.6%
송 149
 
2.5%
아 149
 
2.5%
지 141
 
2.3%
Other values (158) 4048
67.1%
Uppercase Letter
ValueCountFrequency (%)
S 28
21.5%
K 28
21.5%
L 15
11.5%
B 15
11.5%
I 7
 
5.4%
T 6
 
4.6%
C 6
 
4.6%
W 4
 
3.1%
E 4
 
3.1%
F 4
 
3.1%
Other values (7) 13
10.0%
Decimal Number
ValueCountFrequency (%)
1 122
40.9%
2 54
18.1%
3 32
 
10.7%
0 25
 
8.4%
5 17
 
5.7%
4 15
 
5.0%
6 12
 
4.0%
8 8
 
2.7%
9 7
 
2.3%
7 6
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
s 21
30.9%
k 21
30.9%
e 11
16.2%
l 3
 
4.4%
a 3
 
4.4%
r 3
 
4.4%
t 3
 
4.4%
n 3
 
4.4%
Space Separator
ValueCountFrequency (%)
454
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6036
86.0%
Common 786
 
11.2%
Latin 198
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 331
 
5.5%
스 230
 
3.8%
파 225
 
3.7%
도 205
 
3.4%
더 203
 
3.4%
이 197
 
3.3%
샵 158
 
2.6%
송 149
 
2.5%
아 149
 
2.5%
지 141
 
2.3%
Other values (158) 4048
67.1%
Latin
ValueCountFrequency (%)
S 28
14.1%
K 28
14.1%
s 21
10.6%
k 21
10.6%
L 15
 
7.6%
B 15
 
7.6%
e 11
 
5.6%
I 7
 
3.5%
T 6
 
3.0%
C 6
 
3.0%
Other values (15) 40
20.2%
Common
ValueCountFrequency (%)
454
57.8%
1 122
 
15.5%
2 54
 
6.9%
3 32
 
4.1%
0 25
 
3.2%
5 17
 
2.2%
4 15
 
1.9%
( 15
 
1.9%
) 15
 
1.9%
6 12
 
1.5%
Other values (4) 25
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6036
86.0%
ASCII 984
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
454
46.1%
1 122
 
12.4%
2 54
 
5.5%
3 32
 
3.3%
S 28
 
2.8%
K 28
 
2.8%
0 25
 
2.5%
s 21
 
2.1%
k 21
 
2.1%
5 17
 
1.7%
Other values (29) 182
18.5%
Hangul
ValueCountFrequency (%)
트 331
 
5.5%
스 230
 
3.8%
파 225
 
3.7%
도 205
 
3.4%
더 203
 
3.4%
이 197
 
3.3%
샵 158
 
2.6%
송 149
 
2.5%
아 149
 
2.5%
지 141
 
2.3%
Other values (158) 4048
67.1%

동 명칭
Text

Distinct302
Distinct (%)46.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T00:34:52.014842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length4
Mean length4.6
Min length2

Characters and Unicode

Total characters3013
Distinct characters82
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

Unique231 ?
Unique (%)35.3%

Sample

1st row동인천역파크푸르지오 101동
2nd row동인천역파크푸르지오 102동
3rd row동인천역파크푸르지오 103동
4th row동인천역파크푸르지오 104동
5th row동인천역파크푸르지오 105동
ValueCountFrequency (%)
102동 41
 
5.8%
101동 40
 
5.7%
103동 37
 
5.3%
104동 28
 
4.0%
105동 26
 
3.7%
106동 22
 
3.1%
107동 18
 
2.6%
108동 15
 
2.1%
109동 13
 
1.9%
201동 12
 
1.7%
Other values (276) 450
64.1%
2024-04-21T00:34:52.928943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 663
22.0%
1 576
19.1%
0 468
15.5%
2 227
 
7.5%
3 134
 
4.4%
5 134
 
4.4%
4 118
 
3.9%
6 93
 
3.1%
7 93
 
3.1%
9 70
 
2.3%
Other values (72) 437
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1975
65.5%
Other Letter 955
31.7%
Space Separator 48
 
1.6%
Uppercase Letter 28
 
0.9%
Dash Punctuation 4
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 663
69.4%
지 25
 
2.6%
오 18
 
1.9%
푸 15
 
1.6%
르 15
 
1.6%
트 13
 
1.4%
크 13
 
1.4%
스 12
 
1.3%
역 12
 
1.3%
파 12
 
1.3%
Other values (45) 157
 
16.4%
Uppercase Letter
ValueCountFrequency (%)
T 5
17.9%
C 4
14.3%
I 4
14.3%
Y 3
10.7%
N 3
10.7%
B 2
 
7.1%
A 2
 
7.1%
R 1
 
3.6%
E 1
 
3.6%
W 1
 
3.6%
Other values (2) 2
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 576
29.2%
0 468
23.7%
2 227
 
11.5%
3 134
 
6.8%
5 134
 
6.8%
4 118
 
6.0%
6 93
 
4.7%
7 93
 
4.7%
9 70
 
3.5%
8 62
 
3.1%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2030
67.4%
Hangul 955
31.7%
Latin 28
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 663
69.4%
지 25
 
2.6%
오 18
 
1.9%
푸 15
 
1.6%
르 15
 
1.6%
트 13
 
1.4%
크 13
 
1.4%
스 12
 
1.3%
역 12
 
1.3%
파 12
 
1.3%
Other values (45) 157
 
16.4%
Common
ValueCountFrequency (%)
1 576
28.4%
0 468
23.1%
2 227
 
11.2%
3 134
 
6.6%
5 134
 
6.6%
4 118
 
5.8%
6 93
 
4.6%
7 93
 
4.6%
9 70
 
3.4%
8 62
 
3.1%
Other values (5) 55
 
2.7%
Latin
ValueCountFrequency (%)
T 5
17.9%
C 4
14.3%
I 4
14.3%
Y 3
10.7%
N 3
10.7%
B 2
 
7.1%
A 2
 
7.1%
R 1
 
3.6%
E 1
 
3.6%
W 1
 
3.6%
Other values (2) 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2058
68.3%
Hangul 955
31.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 663
69.4%
지 25
 
2.6%
오 18
 
1.9%
푸 15
 
1.6%
르 15
 
1.6%
트 13
 
1.4%
크 13
 
1.4%
스 12
 
1.3%
역 12
 
1.3%
파 12
 
1.3%
Other values (45) 157
 
16.4%
ASCII
ValueCountFrequency (%)
1 576
28.0%
0 468
22.7%
2 227
 
11.0%
3 134
 
6.5%
5 134
 
6.5%
4 118
 
5.7%
6 93
 
4.5%
7 93
 
4.5%
9 70
 
3.4%
8 62
 
3.0%
Other values (17) 83
 
4.0%

주소
Text

Distinct136
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T00:34:53.707950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length14.992366
Min length5

Characters and Unicode

Total characters9820
Distinct characters128
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)4.6%

Sample

1st row중구 서해대로567번길 15
2nd row중구 서해대로567번길 15
3rd row중구 서해대로567번길 15
4th row중구 서해대로567번길 15
5th row중구 서해대로567번길 15
ValueCountFrequency (%)
서구 101
 
5.6%
랜드마크로 67
 
3.7%
중산동 57
 
3.2%
90열우물로 52
 
2.9%
남동구 48
 
2.7%
부평구 37
 
2.1%
90 26
 
1.4%
열우물로 26
 
1.4%
송도문화로28번길 26
 
1.4%
송도과학로 25
 
1.4%
Other values (209) 1336
74.2%
2024-04-21T00:34:54.765582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1180
 
12.0%
로 855
 
8.7%
1 631
 
6.4%
2 424
 
4.3%
3 384
 
3.9%
0 314
 
3.2%
길 304
 
3.1%
번 298
 
3.0%
8 286
 
2.9%
구 272
 
2.8%
Other values (118) 4872
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5410
55.1%
Decimal Number 3161
32.2%
Space Separator 1180
 
12.0%
Dash Punctuation 69
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 855
 
15.8%
길 304
 
5.6%
번 298
 
5.5%
구 272
 
5.0%
라 165
 
3.0%
청 142
 
2.6%
대 132
 
2.4%
서 127
 
2.3%
동 125
 
2.3%
크 103
 
1.9%
Other values (106) 2887
53.4%
Decimal Number
ValueCountFrequency (%)
1 631
20.0%
2 424
13.4%
3 384
12.1%
0 314
9.9%
8 286
9.0%
6 246
 
7.8%
7 234
 
7.4%
4 231
 
7.3%
9 212
 
6.7%
5 199
 
6.3%
Space Separator
ValueCountFrequency (%)
1180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5410
55.1%
Common 4410
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 855
 
15.8%
길 304
 
5.6%
번 298
 
5.5%
구 272
 
5.0%
라 165
 
3.0%
청 142
 
2.6%
대 132
 
2.4%
서 127
 
2.3%
동 125
 
2.3%
크 103
 
1.9%
Other values (106) 2887
53.4%
Common
ValueCountFrequency (%)
1180
26.8%
1 631
14.3%
2 424
 
9.6%
3 384
 
8.7%
0 314
 
7.1%
8 286
 
6.5%
6 246
 
5.6%
7 234
 
5.3%
4 231
 
5.2%
9 212
 
4.8%
Other values (2) 268
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5410
55.1%
ASCII 4410
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1180
26.8%
1 631
14.3%
2 424
 
9.6%
3 384
 
8.7%
0 314
 
7.1%
8 286
 
6.5%
6 246
 
5.6%
7 234
 
5.3%
4 231
 
5.2%
9 212
 
4.8%
Other values (2) 268
 
6.1%
Hangul
ValueCountFrequency (%)
로 855
 
15.8%
길 304
 
5.6%
번 298
 
5.5%
구 272
 
5.0%
라 165
 
3.0%
청 142
 
2.6%
대 132
 
2.4%
서 127
 
2.3%
동 125
 
2.3%
크 103
 
1.9%
Other values (106) 2887
53.4%

용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
공동주택
595 
복합
 
54
업무시설
 
6

Length

Max length4
Median length4
Mean length3.8351145
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 595
90.8%
복합 54
 
8.2%
업무시설 6
 
0.9%

Length

2024-04-21T00:34:55.006627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:34:55.203541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 595
90.8%
복합 54
 
8.2%
업무시설 6
 
0.9%

동 지상 층수
Real number (ℝ)

Distinct28
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.236641
Minimum30
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T00:34:55.382963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile30
Q132
median36
Q341
95-th percentile49
Maximum68
Range38
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.577731
Coefficient of variation (CV)0.17664673
Kurtosis1.7853354
Mean37.236641
Median Absolute Deviation (MAD)4
Skewness1.1903931
Sum24390
Variance43.266545
MonotonicityNot monotonic
2024-04-21T00:34:55.609268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
30 100
15.3%
33 55
 
8.4%
31 47
 
7.2%
35 45
 
6.9%
32 39
 
6.0%
38 37
 
5.6%
40 36
 
5.5%
34 34
 
5.2%
37 34
 
5.2%
36 30
 
4.6%
Other values (18) 198
30.2%
ValueCountFrequency (%)
30 100
15.3%
31 47
7.2%
32 39
 
6.0%
33 55
8.4%
34 34
 
5.2%
35 45
6.9%
36 30
 
4.6%
37 34
 
5.2%
38 37
 
5.6%
39 30
 
4.6%
ValueCountFrequency (%)
68 1
 
0.2%
64 4
 
0.6%
60 2
 
0.3%
58 2
 
0.3%
55 3
 
0.5%
53 2
 
0.3%
51 2
 
0.3%
50 3
 
0.5%
49 28
4.3%
48 12
1.8%

사용승인
Date

Distinct112
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum1905-07-03 00:00:00
Maximum2022-09-30 00:00:00
2024-04-21T00:34:55.858736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:34:56.109016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-21T00:34:47.282300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:34:46.744971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:34:47.765937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:34:47.006267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T00:34:56.278162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번처종용도동 지상 층수
연번1.0000.2710.2830.556
처종0.2711.0000.9700.366
용도0.2830.9701.0000.351
동 지상 층수0.5560.3660.3511.000
2024-04-21T00:34:56.431163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도처종
용도1.0000.789
처종0.7891.000
2024-04-21T00:34:56.570489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동 지상 층수처종용도
연번1.0000.2480.1670.176
동 지상 층수0.2481.0000.2350.224
처종0.1670.2351.0000.789
용도0.1760.2240.7891.000

Missing values

2024-04-21T00:34:48.157726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T00:34:48.570572image/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

연번처종대상물 명칭동 명칭주소용도동 지상 층수사용승인
01공동주택동인천역파크푸르지오동인천역파크푸르지오 101동중구 서해대로567번길 15공동주택482022-08-22
12공동주택동인천역파크푸르지오동인천역파크푸르지오 102동중구 서해대로567번길 15공동주택422022-08-22
23공동주택동인천역파크푸르지오동인천역파크푸르지오 103동중구 서해대로567번길 15공동주택482022-08-22
34공동주택동인천역파크푸르지오동인천역파크푸르지오 104동중구 서해대로567번길 15공동주택442022-08-22
45공동주택동인천역파크푸르지오동인천역파크푸르지오 105동중구 서해대로567번길 15공동주택452022-08-22
56공동주택동인천역파크푸르지오동인천역파크푸르지오 106동중구 서해대로567번길 15공동주택442022-08-22
67공동주택동인천역파크푸르지오동인천역파크푸르지오 107동중구 서해대로567번길 15공동주택482022-08-22
78공동주택동인천역파크푸르지오동인천역파크푸르지오 108동중구 서해대로567번길 15공동주택482022-08-22
89공동주택동인천역파크푸르지오동인천역파크푸르지오 109동중구 서해대로567번길 15공동주택442022-08-22
910공동주택동인천역파크푸르지오동인천역파크푸르지오 110동중구 서해대로567번길 15공동주택402022-08-22
연번처종대상물 명칭동 명칭주소용도동 지상 층수사용승인
645646복합힐스테이트 송도 더테라스107동센트럴로415복합492020-09-24
646647복합힐스테이트 송도 더테라스108동센트럴로415복합492020-09-24
647648복합랜드마크푸르지오시티1동아트센터대로168번길 101복합362021-03-10
648649복합한라웨스턴파크 송도1동아트센터대로168번길 100복합372021-01-28
649650복합인천테크노파크 AT센터1동송도과학로 70복합332022-04-27
650651공동주택더샵 송도프라임뷰 20BL2001동인천타워대로231번길 97공동주택322022-07-28
651652공동주택더샵 송도프라임뷰 20BL2002동인천타워대로231번길 97공동주택372022-07-28
652653공동주택더샵 송도프라임뷰 20BL2003동인천타워대로231번길 97공동주택352022-07-28
653654공동주택더샵 송도프라임뷰 20BL2004동인천타워대로231번길 97공동주택372022-07-28
654655공동주택더샵 송도프라임뷰 20BL2005동인천타워대로231번길 97공동주택362022-07-28