Overview

Dataset statistics

Number of variables8
Number of observations1994
Missing cells785
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory130.6 KiB
Average record size in memory67.1 B

Variable types

Numeric3
Text2
DateTime2
Categorical1

Dataset

Description인천광역시 중구 소재하는 집합건물에 관한 정보입니다.파일명 인천광역시 중구 집합건물현황내용 소재지 주소, 건물명, 연면적 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15042570&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연면적 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 연면적High correlation
주용도 is highly imbalanced (68.1%)Imbalance
사용승인일자 has 23 (1.2%) missing valuesMissing
건물명칭 has 323 (16.2%) missing valuesMissing
세대수 has 439 (22.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:30:34.465047
Analysis finished2024-03-18 05:30:37.344884
Duration2.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1994
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean997.5
Minimum1
Maximum1994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-03-18T14:30:37.409347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile100.65
Q1499.25
median997.5
Q31495.75
95-th percentile1894.35
Maximum1994
Range1993
Interquartile range (IQR)996.5

Descriptive statistics

Standard deviation575.76254
Coefficient of variation (CV)0.57720555
Kurtosis-1.2
Mean997.5
Median Absolute Deviation (MAD)498.5
Skewness0
Sum1989015
Variance331502.5
MonotonicityStrictly increasing
2024-03-18T14:30:37.530954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1326 1
 
0.1%
1339 1
 
0.1%
1338 1
 
0.1%
1337 1
 
0.1%
1336 1
 
0.1%
1335 1
 
0.1%
1334 1
 
0.1%
1333 1
 
0.1%
1332 1
 
0.1%
Other values (1984) 1984
99.5%
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 (%)
1994 1
0.1%
1993 1
0.1%
1992 1
0.1%
1991 1
0.1%
1990 1
0.1%
1989 1
0.1%
1988 1
0.1%
1987 1
0.1%
1986 1
0.1%
1985 1
0.1%

소재지 주소
Text

Distinct1749
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-03-18T14:30:37.791176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.147944
Min length14

Characters and Unicode

Total characters38181
Distinct characters115
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

Unique1643 ?
Unique (%)82.4%

Sample

1st row인천광역시 중구 우현로49번길 25
2nd row인천광역시 중구 참외전로 117-9
3rd row인천광역시 중구 우현로49번길 25
4th row인천광역시 중구 우현로49번길 25
5th row인천광역시 중구 연안부두로 16
ValueCountFrequency (%)
인천광역시 1994
25.0%
중구 1994
25.0%
율목동 141
 
1.8%
도원동 99
 
1.2%
송월동1가 80
 
1.0%
항동7가 69
 
0.9%
율목로 49
 
0.6%
참외전로244번길 47
 
0.6%
흰바위로 45
 
0.6%
참외전로59번길 42
 
0.5%
Other values (1332) 3416
42.8%
2024-03-18T14:30:38.132028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5982
 
15.7%
중 2109
 
5.5%
시 2072
 
5.4%
인 2053
 
5.4%
광 2002
 
5.2%
구 1995
 
5.2%
역 1994
 
5.2%
천 1994
 
5.2%
1 1583
 
4.1%
2 1357
 
3.6%
Other values (105) 15040
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22951
60.1%
Decimal Number 8104
 
21.2%
Space Separator 5982
 
15.7%
Dash Punctuation 1144
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 2109
 
9.2%
시 2072
 
9.0%
인 2053
 
8.9%
광 2002
 
8.7%
구 1995
 
8.7%
역 1994
 
8.7%
천 1994
 
8.7%
로 1319
 
5.7%
길 903
 
3.9%
번 877
 
3.8%
Other values (93) 5633
24.5%
Decimal Number
ValueCountFrequency (%)
1 1583
19.5%
2 1357
16.7%
4 1063
13.1%
3 838
10.3%
5 649
8.0%
7 576
 
7.1%
6 558
 
6.9%
8 545
 
6.7%
0 471
 
5.8%
9 464
 
5.7%
Space Separator
ValueCountFrequency (%)
5982
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22951
60.1%
Common 15230
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 2109
 
9.2%
시 2072
 
9.0%
인 2053
 
8.9%
광 2002
 
8.7%
구 1995
 
8.7%
역 1994
 
8.7%
천 1994
 
8.7%
로 1319
 
5.7%
길 903
 
3.9%
번 877
 
3.8%
Other values (93) 5633
24.5%
Common
ValueCountFrequency (%)
5982
39.3%
1 1583
 
10.4%
2 1357
 
8.9%
- 1144
 
7.5%
4 1063
 
7.0%
3 838
 
5.5%
5 649
 
4.3%
7 576
 
3.8%
6 558
 
3.7%
8 545
 
3.6%
Other values (2) 935
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22951
60.1%
ASCII 15230
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5982
39.3%
1 1583
 
10.4%
2 1357
 
8.9%
- 1144
 
7.5%
4 1063
 
7.0%
3 838
 
5.5%
5 649
 
4.3%
7 576
 
3.8%
6 558
 
3.7%
8 545
 
3.6%
Other values (2) 935
 
6.1%
Hangul
ValueCountFrequency (%)
중 2109
 
9.2%
시 2072
 
9.0%
인 2053
 
8.9%
광 2002
 
8.7%
구 1995
 
8.7%
역 1994
 
8.7%
천 1994
 
8.7%
로 1319
 
5.7%
길 903
 
3.9%
번 877
 
3.8%
Other values (93) 5633
24.5%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct1288
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5253.6727
Minimum11.38
Maximum272145.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-03-18T14:30:38.256171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.38
5-th percentile247.02
Q1399.75
median602.825
Q31457.8125
95-th percentile20721.29
Maximum272145.74
Range272134.36
Interquartile range (IQR)1058.0625

Descriptive statistics

Standard deviation21061.674
Coefficient of variation (CV)4.0089429
Kurtosis81.291827
Mean5253.6727
Median Absolute Deviation (MAD)255.975
Skewness8.3745776
Sum10475823
Variance4.4359409 × 108
MonotonicityNot monotonic
2024-03-18T14:30:38.385975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
329.76 14
 
0.7%
20721.29 11
 
0.6%
2988.05 10
 
0.5%
592.4 8
 
0.4%
656.96 8
 
0.4%
658.8 8
 
0.4%
2951.3 8
 
0.4%
435.6 7
 
0.4%
651.25 6
 
0.3%
520.8 6
 
0.3%
Other values (1278) 1908
95.7%
ValueCountFrequency (%)
11.38 1
0.1%
12.16 2
0.1%
15.84 1
0.1%
20.95 1
0.1%
38.88 1
0.1%
43.0 1
0.1%
45.0 1
0.1%
45.97 1
0.1%
49.32 2
0.1%
73.08 1
0.1%
ValueCountFrequency (%)
272145.74 1
0.1%
262699.77 1
0.1%
256975.84 1
0.1%
233747.28 1
0.1%
228049.26 1
0.1%
227934.19 1
0.1%
219166.37 1
0.1%
216901.76 1
0.1%
203166.91 1
0.1%
203119.09 1
0.1%

사용승인일자
Date

MISSING 

Distinct957
Distinct (%)48.6%
Missing23
Missing (%)1.2%
Memory size15.7 KiB
Minimum1771-04-07 00:00:00
Maximum2023-06-01 00:00:00
2024-03-18T14:30:38.508857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:38.668743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건물명칭
Text

MISSING 

Distinct754
Distinct (%)45.1%
Missing323
Missing (%)16.2%
Memory size15.7 KiB
2024-03-18T14:30:38.959707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length5.8994614
Min length1

Characters and Unicode

Total characters9858
Distinct characters356
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)25.2%

Sample

1st row해양센타
2nd row홍예문아파트
3rd row연안상가
4th row우진연립
5th row우진연립
ValueCountFrequency (%)
현대빌라 30
 
1.5%
라이프아파트 24
 
1.2%
연안아파트 22
 
1.1%
동원베네스트영종타운하우스 22
 
1.1%
장미빌라 20
 
1.0%
항운아파트 19
 
1.0%
영종 18
 
0.9%
영진빌라 16
 
0.8%
동국빌리지 16
 
0.8%
뉴월드그린빌라 14
 
0.7%
Other values (791) 1736
89.6%
2024-03-18T14:30:39.373232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 1015
 
10.3%
라 887
 
9.0%
트 283
 
2.9%
268
 
2.7%
아 260
 
2.6%
파 238
 
2.4%
동 237
 
2.4%
스 222
 
2.3%
이 213
 
2.2%
영 211
 
2.1%
Other values (346) 6024
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9077
92.1%
Decimal Number 322
 
3.3%
Space Separator 268
 
2.7%
Uppercase Letter 128
 
1.3%
Lowercase Letter 41
 
0.4%
Dash Punctuation 8
 
0.1%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Letter Number 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 1015
 
11.2%
라 887
 
9.8%
트 283
 
3.1%
아 260
 
2.9%
파 238
 
2.6%
동 237
 
2.6%
스 222
 
2.4%
이 213
 
2.3%
영 211
 
2.3%
지 153
 
1.7%
Other values (300) 5358
59.0%
Uppercase Letter
ValueCountFrequency (%)
O 18
14.1%
E 14
10.9%
M 12
 
9.4%
K 10
 
7.8%
S 10
 
7.8%
R 7
 
5.5%
A 7
 
5.5%
C 6
 
4.7%
V 6
 
4.7%
I 6
 
4.7%
Other values (12) 32
25.0%
Decimal Number
ValueCountFrequency (%)
1 101
31.4%
2 64
19.9%
0 60
18.6%
3 21
 
6.5%
7 18
 
5.6%
5 18
 
5.6%
6 15
 
4.7%
4 12
 
3.7%
9 9
 
2.8%
8 4
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
y 10
24.4%
e 6
14.6%
i 6
14.6%
k 5
12.2%
c 5
12.2%
t 5
12.2%
s 3
 
7.3%
l 1
 
2.4%
Space Separator
ValueCountFrequency (%)
268
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9077
92.1%
Common 609
 
6.2%
Latin 172
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 1015
 
11.2%
라 887
 
9.8%
트 283
 
3.1%
아 260
 
2.9%
파 238
 
2.6%
동 237
 
2.6%
스 222
 
2.4%
이 213
 
2.3%
영 211
 
2.3%
지 153
 
1.7%
Other values (300) 5358
59.0%
Latin
ValueCountFrequency (%)
O 18
 
10.5%
E 14
 
8.1%
M 12
 
7.0%
K 10
 
5.8%
y 10
 
5.8%
S 10
 
5.8%
R 7
 
4.1%
A 7
 
4.1%
C 6
 
3.5%
V 6
 
3.5%
Other values (21) 72
41.9%
Common
ValueCountFrequency (%)
268
44.0%
1 101
 
16.6%
2 64
 
10.5%
0 60
 
9.9%
3 21
 
3.4%
7 18
 
3.0%
5 18
 
3.0%
6 15
 
2.5%
4 12
 
2.0%
9 9
 
1.5%
Other values (5) 23
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9077
92.1%
ASCII 778
 
7.9%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 1015
 
11.2%
라 887
 
9.8%
트 283
 
3.1%
아 260
 
2.9%
파 238
 
2.6%
동 237
 
2.6%
스 222
 
2.4%
이 213
 
2.3%
영 211
 
2.3%
지 153
 
1.7%
Other values (300) 5358
59.0%
ASCII
ValueCountFrequency (%)
268
34.4%
1 101
 
13.0%
2 64
 
8.2%
0 60
 
7.7%
3 21
 
2.7%
7 18
 
2.3%
O 18
 
2.3%
5 18
 
2.3%
6 15
 
1.9%
E 14
 
1.8%
Other values (35) 181
23.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

주용도
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
공동주택
1559 
제1종근린생활시설
 
131
제2종근린생활시설
 
125
업무시설
 
89
숙박시설
 
57
Other values (11)
 
33

Length

Max length9
Median length4
Mean length4.6584754
Min length2

Unique

Unique6 ?
Unique (%)0.3%

Sample

1st row제2종근린생활시설
2nd row제1종근린생활시설
3rd row업무시설
4th row업무시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
공동주택 1559
78.2%
제1종근린생활시설 131
 
6.6%
제2종근린생활시설 125
 
6.3%
업무시설 89
 
4.5%
숙박시설 57
 
2.9%
판매시설 11
 
0.6%
자동차관련시설 8
 
0.4%
노유자시설 4
 
0.2%
교육연구시설 2
 
0.1%
위락시설 2
 
0.1%
Other values (6) 6
 
0.3%

Length

2024-03-18T14:30:39.501645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 1559
78.2%
제1종근린생활시설 131
 
6.6%
제2종근린생활시설 125
 
6.3%
업무시설 89
 
4.5%
숙박시설 57
 
2.9%
판매시설 11
 
0.6%
자동차관련시설 8
 
0.4%
노유자시설 4
 
0.2%
교육연구시설 2
 
0.1%
위락시설 2
 
0.1%
Other values (6) 6
 
0.3%

세대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct120
Distinct (%)7.7%
Missing439
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean39.064309
Minimum1
Maximum1680
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-03-18T14:30:39.613175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median10
Q314
95-th percentile126
Maximum1680
Range1679
Interquartile range (IQR)6

Descriptive statistics

Standard deviation149.03783
Coefficient of variation (CV)3.8151917
Kurtosis62.885163
Mean39.064309
Median Absolute Deviation (MAD)2
Skewness7.4869383
Sum60745
Variance22212.274
MonotonicityNot monotonic
2024-03-18T14:30:39.739196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 366
18.4%
10 240
12.0%
12 107
 
5.4%
9 89
 
4.5%
6 85
 
4.3%
14 72
 
3.6%
15 64
 
3.2%
4 57
 
2.9%
3 41
 
2.1%
19 40
 
2.0%
Other values (110) 394
19.8%
(Missing) 439
22.0%
ValueCountFrequency (%)
1 8
 
0.4%
2 14
 
0.7%
3 41
 
2.1%
4 57
 
2.9%
5 38
 
1.9%
6 85
 
4.3%
7 29
 
1.5%
8 366
18.4%
9 89
 
4.5%
10 240
12.0%
ValueCountFrequency (%)
1680 1
0.1%
1628 1
0.1%
1604 1
0.1%
1520 1
0.1%
1445 1
0.1%
1409 1
0.1%
1365 1
0.1%
1330 1
0.1%
1304 1
0.1%
1287 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
Minimum2023-08-04 00:00:00
Maximum2023-08-04 00:00:00
2024-03-18T14:30:39.837060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:39.934761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T14:30:36.723399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.134267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.482063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.811164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.282799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.565957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.914799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.378803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:30:36.641171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:30:40.012786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적주용도세대수
연번1.0000.2120.4300.385
연면적0.2121.0000.5750.955
주용도0.4300.5751.0000.104
세대수0.3850.9550.1041.000
2024-03-18T14:30:40.337166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적세대수주용도
연번1.0000.0790.0570.183
연면적0.0791.0000.8070.267
세대수0.0570.8071.0000.062
주용도0.1830.2670.0621.000

Missing values

2024-03-18T14:30:37.053947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:30:37.171465image/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.
2024-03-18T14:30:37.287893image/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

연번소재지 주소연면적사용승인일자건물명칭주용도세대수데이터기준일자
01인천광역시 중구 우현로49번길 25807.661771-04-07<NA>제2종근린생활시설<NA>2023-08-04
12인천광역시 중구 참외전로 117-9714.041962-10-18<NA>제1종근린생활시설<NA>2023-08-04
23인천광역시 중구 우현로49번길 252669.931971-04-07<NA>업무시설<NA>2023-08-04
34인천광역시 중구 우현로49번길 25807.661971-04-07<NA>업무시설<NA>2023-08-04
45인천광역시 중구 연안부두로 168581.541974-12-07해양센타제2종근린생활시설<NA>2023-08-04
56인천광역시 중구 연안부두로 1094373.981976-09-22<NA>제1종근린생활시설<NA>2023-08-04
67인천광역시 중구 연안부두로33번길 362414.051976-12-22<NA>제1종근린생활시설<NA>2023-08-04
78인천광역시 중구 연안부두로 41-11606.741977-01-27<NA>판매시설<NA>2023-08-04
89인천광역시 중구 송학로 511464.881977-02-04홍예문아파트공동주택232023-08-04
910인천광역시 중구 연안부두로33번길 3349.111977-03-23연안상가공동주택<NA>2023-08-04
연번소재지 주소연면적사용승인일자건물명칭주용도세대수데이터기준일자
19841985인천광역시 중구 신포동 7-18807.66<NA><NA>제2종근린생활시설<NA>2023-08-04
19851986인천광역시 중구 신흥동2가 54-51940.32<NA>삼익아파트제1종근린생활시설<NA>2023-08-04
19861987인천광역시 중구 북성동3가 5-2756.09<NA><NA>공동주택122023-08-04
19871988인천광역시 중구 인현동 1-17295.88<NA>엔조이쇼핑몰판매시설<NA>2023-08-04
19881989인천광역시 중구 신생동 38-5248.816<NA>삼성아파트공동주택<NA>2023-08-04
19891990인천광역시 중구 신생동 38-515.84<NA>삼성아파트공동주택<NA>2023-08-04
19901991인천광역시 중구 신생동 38-512673.42<NA>삼성아파트공동주택<NA>2023-08-04
19911992인천광역시 중구 항동7가 58-40694.06<NA><NA>숙박시설<NA>2023-08-04
19921993인천광역시 중구 항동7가 27-126689.92<NA><NA>숙박시설<NA>2023-08-04
19931994인천광역시 중구 신포동 7-4849.32<NA><NA>제2종근린생활시설<NA>2023-08-04