Overview

Dataset statistics

Number of variables5
Number of observations6066
Missing cells1134
Missing cells (%)3.7%
Duplicate rows28
Duplicate rows (%)0.5%
Total size in memory248.9 KiB
Average record size in memory42.0 B

Variable types

Text3
Numeric2

Dataset

Description서울특별시 원룸 및 오피스텔에 대한 건축물대장 현황 데이터 정보(대지위치, 건물명, 세부용도, 연면적, 호수 등) ## HTML 미리보기 [![미리보기](http://curate.gimi9.com/linkview/www-data-go-kr-data-filedata-15124246?url=javascript%3Avoid%280%29&version=d7)](https://www.data.go.kr/data/15124246/fileData.do)
Author서울특별시
URLhttps://www.data.go.kr/data/15124246/fileData.do

Alerts

Dataset has 28 (0.5%) duplicate rowsDuplicates
연면적 is highly overall correlated with 호수High correlation
호수 is highly overall correlated with 연면적High correlation
건물명 has 1134 (18.7%) missing valuesMissing
연면적 is highly skewed (γ1 = 76.18392819)Skewed
호수 has 922 (15.2%) zerosZeros

Reproduction

Analysis started2024-03-14 14:46:17.607457
Analysis finished2024-03-14 14:46:20.267574
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대지위치
Text

Distinct5701
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size47.5 KiB
2024-03-14T23:46:21.273283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length19.85938
Min length16

Characters and Unicode

Total characters120467
Distinct characters191
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

Unique5448 ?
Unique (%)89.8%

Sample

1st row서울특별시 강남구 개포동 1194-1
2nd row서울특별시 강남구 개포동 1229-10
3rd row서울특별시 강남구 개포동 1229-6
4th row서울특별시 강남구 개포동 1236-4
5th row서울특별시 강남구 개포동 1237-3
ValueCountFrequency (%)
서울특별시 6066
25.0%
영등포구 690
 
2.8%
관악구 675
 
2.8%
강서구 573
 
2.4%
은평구 421
 
1.7%
금천구 416
 
1.7%
신림동 342
 
1.4%
봉천동 302
 
1.2%
화곡동 280
 
1.2%
동대문구 280
 
1.2%
Other values (5528) 14219
58.6%
2024-03-14T23:46:22.946911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18198
 
15.1%
서 7083
 
5.9%
동 6723
 
5.6%
구 6447
 
5.4%
시 6155
 
5.1%
특 6066
 
5.0%
별 6066
 
5.0%
울 6066
 
5.0%
- 6066
 
5.0%
1 5606
 
4.7%
Other values (181) 45991
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68522
56.9%
Decimal Number 27681
23.0%
Space Separator 18198
 
15.1%
Dash Punctuation 6066
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 7083
 
10.3%
동 6723
 
9.8%
구 6447
 
9.4%
시 6155
 
9.0%
특 6066
 
8.9%
별 6066
 
8.9%
울 6066
 
8.9%
강 1173
 
1.7%
포 1096
 
1.6%
등 994
 
1.5%
Other values (169) 20653
30.1%
Decimal Number
ValueCountFrequency (%)
1 5606
20.3%
2 3640
13.1%
3 2926
10.6%
4 2642
9.5%
0 2452
8.9%
6 2383
8.6%
5 2186
 
7.9%
7 1994
 
7.2%
9 1977
 
7.1%
8 1875
 
6.8%
Space Separator
ValueCountFrequency (%)
18198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6066
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68522
56.9%
Common 51945
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 7083
 
10.3%
동 6723
 
9.8%
구 6447
 
9.4%
시 6155
 
9.0%
특 6066
 
8.9%
별 6066
 
8.9%
울 6066
 
8.9%
강 1173
 
1.7%
포 1096
 
1.6%
등 994
 
1.5%
Other values (169) 20653
30.1%
Common
ValueCountFrequency (%)
18198
35.0%
- 6066
 
11.7%
1 5606
 
10.8%
2 3640
 
7.0%
3 2926
 
5.6%
4 2642
 
5.1%
0 2452
 
4.7%
6 2383
 
4.6%
5 2186
 
4.2%
7 1994
 
3.8%
Other values (2) 3852
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68522
56.9%
ASCII 51945
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18198
35.0%
- 6066
 
11.7%
1 5606
 
10.8%
2 3640
 
7.0%
3 2926
 
5.6%
4 2642
 
5.1%
0 2452
 
4.7%
6 2383
 
4.6%
5 2186
 
4.2%
7 1994
 
3.8%
Other values (2) 3852
 
7.4%
Hangul
ValueCountFrequency (%)
서 7083
 
10.3%
동 6723
 
9.8%
구 6447
 
9.4%
시 6155
 
9.0%
특 6066
 
8.9%
별 6066
 
8.9%
울 6066
 
8.9%
강 1173
 
1.7%
포 1096
 
1.6%
등 994
 
1.5%
Other values (169) 20653
30.1%

건물명
Text

MISSING 

Distinct4187
Distinct (%)84.9%
Missing1134
Missing (%)18.7%
Memory size47.5 KiB
2024-03-14T23:46:23.868334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length6.7370235
Min length1

Characters and Unicode

Total characters33227
Distinct characters641
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3742 ?
Unique (%)75.9%

Sample

1st row런던빌 개포
2nd row하우징허브럭스
3rd rowCCRU오피스텔
4th row디오빌
5th row한별2
ValueCountFrequency (%)
오피스텔 212
 
3.1%
더 69
 
1.0%
여의도 25
 
0.4%
강남 23
 
0.3%
투웨니퍼스트 22
 
0.3%
아파트 21
 
0.3%
tower 20
 
0.3%
잠실 19
 
0.3%
성우스타팰리스 17
 
0.3%
the 16
 
0.2%
Other values (4497) 6302
93.4%
2024-03-14T23:46:25.069512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 2128
 
6.4%
1819
 
5.5%
리 900
 
2.7%
빌 858
 
2.6%
오 838
 
2.5%
텔 760
 
2.3%
피 746
 
2.2%
이 742
 
2.2%
트 649
 
2.0%
아 522
 
1.6%
Other values (631) 23265
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28463
85.7%
Space Separator 1819
 
5.5%
Uppercase Letter 1296
 
3.9%
Decimal Number 1000
 
3.0%
Lowercase Letter 328
 
1.0%
Dash Punctuation 78
 
0.2%
Other Punctuation 67
 
0.2%
Close Punctuation 58
 
0.2%
Open Punctuation 58
 
0.2%
Letter Number 58
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 2128
 
7.5%
리 900
 
3.2%
빌 858
 
3.0%
오 838
 
2.9%
텔 760
 
2.7%
피 746
 
2.6%
이 742
 
2.6%
트 649
 
2.3%
아 522
 
1.8%
타 484
 
1.7%
Other values (549) 19836
69.7%
Uppercase Letter
ValueCountFrequency (%)
E 120
 
9.3%
S 119
 
9.2%
I 89
 
6.9%
A 80
 
6.2%
T 79
 
6.1%
C 70
 
5.4%
K 65
 
5.0%
R 64
 
4.9%
L 58
 
4.5%
O 55
 
4.2%
Other values (16) 497
38.3%
Lowercase Letter
ValueCountFrequency (%)
e 63
19.2%
l 36
11.0%
s 27
8.2%
o 26
 
7.9%
t 24
 
7.3%
a 22
 
6.7%
i 20
 
6.1%
r 18
 
5.5%
u 14
 
4.3%
h 12
 
3.7%
Other values (15) 66
20.1%
Decimal Number
ValueCountFrequency (%)
1 262
26.2%
2 241
24.1%
3 113
11.3%
0 85
 
8.5%
5 77
 
7.7%
6 53
 
5.3%
7 50
 
5.0%
4 47
 
4.7%
8 38
 
3.8%
9 34
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 30
44.8%
# 11
 
16.4%
& 9
 
13.4%
' 6
 
9.0%
/ 3
 
4.5%
? 3
 
4.5%
, 2
 
3.0%
· 2
 
3.0%
？ 1
 
1.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 36
62.1%
Ⅰ 12
 
20.7%
Ⅲ 6
 
10.3%
Ⅳ 3
 
5.2%
Ⅴ 1
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 57
98.3%
] 1
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 57
98.3%
[ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1819
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28454
85.6%
Common 3082
 
9.3%
Latin 1682
 
5.1%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 2128
 
7.5%
리 900
 
3.2%
빌 858
 
3.0%
오 838
 
2.9%
텔 760
 
2.7%
피 746
 
2.6%
이 742
 
2.6%
트 649
 
2.3%
아 522
 
1.8%
타 484
 
1.7%
Other values (542) 19827
69.7%
Latin
ValueCountFrequency (%)
E 120
 
7.1%
S 119
 
7.1%
I 89
 
5.3%
A 80
 
4.8%
T 79
 
4.7%
C 70
 
4.2%
K 65
 
3.9%
R 64
 
3.8%
e 63
 
3.7%
L 58
 
3.4%
Other values (46) 875
52.0%
Common
ValueCountFrequency (%)
1819
59.0%
1 262
 
8.5%
2 241
 
7.8%
3 113
 
3.7%
0 85
 
2.8%
- 78
 
2.5%
5 77
 
2.5%
) 57
 
1.8%
( 57
 
1.8%
6 53
 
1.7%
Other values (16) 240
 
7.8%
Han
ValueCountFrequency (%)
塘 2
22.2%
金 2
22.2%
美 1
11.1%
巖 1
11.1%
鳳 1
11.1%
家 1
11.1%
笑 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28454
85.6%
ASCII 4703
 
14.2%
Number Forms 58
 
0.2%
CJK 7
 
< 0.1%
None 3
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 2128
 
7.5%
리 900
 
3.2%
빌 858
 
3.0%
오 838
 
2.9%
텔 760
 
2.7%
피 746
 
2.6%
이 742
 
2.6%
트 649
 
2.3%
아 522
 
1.8%
타 484
 
1.7%
Other values (542) 19827
69.7%
ASCII
ValueCountFrequency (%)
1819
38.7%
1 262
 
5.6%
2 241
 
5.1%
E 120
 
2.6%
S 119
 
2.5%
3 113
 
2.4%
I 89
 
1.9%
0 85
 
1.8%
A 80
 
1.7%
T 79
 
1.7%
Other values (65) 1696
36.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 36
62.1%
Ⅰ 12
 
20.7%
Ⅲ 6
 
10.3%
Ⅳ 3
 
5.2%
Ⅴ 1
 
1.7%
CJK
ValueCountFrequency (%)
塘 2
28.6%
美 1
14.3%
巖 1
14.3%
鳳 1
14.3%
家 1
14.3%
笑 1
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
金 2
100.0%
None
ValueCountFrequency (%)
· 2
66.7%
？ 1
33.3%

동_세부용도
Text

Distinct2074
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size47.5 KiB
2024-03-14T23:46:25.922504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length52
Mean length15.10633
Min length3

Characters and Unicode

Total characters91635
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1581 ?
Unique (%)26.1%

Sample

1st row단지형다세대주택,오피스텔
2nd row오피스텔
3rd row업무시설(오피스텔 15호실), 다세대주택(20세대), 근린생활시설
4th row업무시설 (오피스텔)
5th row오피스텔,근린생활시설
ValueCountFrequency (%)
업무시설 1207
 
13.0%
업무시설(오피스텔 1046
 
11.3%
근린생활시설 653
 
7.0%
오피스텔 631
 
6.8%
및 566
 
6.1%
공동주택 357
 
3.8%
다세대주택 284
 
3.1%
업무시설(오피스텔),근린생활시설 170
 
1.8%
외 118
 
1.3%
도시형생활주택 92
 
1.0%
Other values (1620) 4169
44.9%
2024-03-14T23:46:27.117127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7968
 
8.7%
설 7046
 
7.7%
, 4429
 
4.8%
무 4387
 
4.8%
업 4280
 
4.7%
) 3745
 
4.1%
( 3744
 
4.1%
주 3590
 
3.9%
택 3494
 
3.8%
생 3443
 
3.8%
Other values (165) 45509
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73114
79.8%
Other Punctuation 4998
 
5.5%
Open Punctuation 3763
 
4.1%
Close Punctuation 3761
 
4.1%
Space Separator 3235
 
3.5%
Decimal Number 2464
 
2.7%
Dash Punctuation 295
 
0.3%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7968
 
10.9%
설 7046
 
9.6%
무 4387
 
6.0%
업 4280
 
5.9%
주 3590
 
4.9%
택 3494
 
4.8%
생 3443
 
4.7%
텔 3386
 
4.6%
스 3380
 
4.6%
오 3379
 
4.6%
Other values (137) 28761
39.3%
Decimal Number
ValueCountFrequency (%)
2 915
37.1%
1 853
34.6%
3 136
 
5.5%
8 112
 
4.5%
6 109
 
4.4%
4 107
 
4.3%
5 68
 
2.8%
9 60
 
2.4%
0 57
 
2.3%
7 47
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 4429
88.6%
/ 463
 
9.3%
: 50
 
1.0%
. 47
 
0.9%
· 6
 
0.1%
& 2
 
< 0.1%
; 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
E 1
20.0%
A 1
20.0%
P 1
20.0%
L 1
20.0%
T 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 3745
99.6%
] 16
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 3744
99.5%
[ 19
 
0.5%
Space Separator
ValueCountFrequency (%)
3235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 295
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73114
79.8%
Common 18516
 
20.2%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7968
 
10.9%
설 7046
 
9.6%
무 4387
 
6.0%
업 4280
 
5.9%
주 3590
 
4.9%
택 3494
 
4.8%
생 3443
 
4.7%
텔 3386
 
4.6%
스 3380
 
4.6%
오 3379
 
4.6%
Other values (137) 28761
39.3%
Common
ValueCountFrequency (%)
, 4429
23.9%
) 3745
20.2%
( 3744
20.2%
3235
17.5%
2 915
 
4.9%
1 853
 
4.6%
/ 463
 
2.5%
- 295
 
1.6%
3 136
 
0.7%
8 112
 
0.6%
Other values (13) 589
 
3.2%
Latin
ValueCountFrequency (%)
E 1
20.0%
A 1
20.0%
P 1
20.0%
L 1
20.0%
T 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73113
79.8%
ASCII 18515
 
20.2%
None 6
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7968
 
10.9%
설 7046
 
9.6%
무 4387
 
6.0%
업 4280
 
5.9%
주 3590
 
4.9%
택 3494
 
4.8%
생 3443
 
4.7%
텔 3386
 
4.6%
스 3380
 
4.6%
오 3379
 
4.6%
Other values (136) 28760
39.3%
ASCII
ValueCountFrequency (%)
, 4429
23.9%
) 3745
20.2%
( 3744
20.2%
3235
17.5%
2 915
 
4.9%
1 853
 
4.6%
/ 463
 
2.5%
- 295
 
1.6%
3 136
 
0.7%
8 112
 
0.6%
Other values (17) 588
 
3.2%
None
ValueCountFrequency (%)
· 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5963
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8733.7498
Minimum0
Maximum15297327
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size53.4 KiB
2024-03-14T23:46:27.361898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile483.91
Q1933.7325
median1782.74
Q34388.04
95-th percentile24899.529
Maximum15297327
Range15297327
Interquartile range (IQR)3454.3075

Descriptive statistics

Standard deviation197842.35
Coefficient of variation (CV)22.652624
Kurtosis5883.1134
Mean8733.7498
Median Absolute Deviation (MAD)1074.55
Skewness76.183928
Sum52978926
Variance3.9141596 × 1010
MonotonicityNot monotonic
2024-03-14T23:46:27.631155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
934.22 6
 
0.1%
1999.83 3
 
< 0.1%
3246.63 3
 
< 0.1%
2190.72 3
 
< 0.1%
677.73 3
 
< 0.1%
2506.4 3
 
< 0.1%
2313.44 3
 
< 0.1%
786.1 3
 
< 0.1%
1998.38 2
 
< 0.1%
548.81 2
 
< 0.1%
Other values (5953) 6035
99.5%
ValueCountFrequency (%)
0.0 1
< 0.1%
112.32 1
< 0.1%
123.14 1
< 0.1%
176.31 1
< 0.1%
184.71 1
< 0.1%
198.24 1
< 0.1%
213.18 1
< 0.1%
218.82 1
< 0.1%
220.92 1
< 0.1%
222.6 1
< 0.1%
ValueCountFrequency (%)
15297327.0 1
< 0.1%
1471845.0 1
< 0.1%
420309.54 1
< 0.1%
265791.63 1
< 0.1%
258427.5 1
< 0.1%
243460.86 1
< 0.1%
226180.46 1
< 0.1%
205876.98 1
< 0.1%
203903.56 1
< 0.1%
197404.78 1
< 0.1%

호수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct469
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.967359
Minimum0
Maximum1629
Zeros922
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size53.4 KiB
2024-03-14T23:46:27.980493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median20
Q357
95-th percentile255
Maximum1629
Range1629
Interquartile range (IQR)52

Descriptive statistics

Standard deviation120.38883
Coefficient of variation (CV)2.0075726
Kurtosis41.427207
Mean59.967359
Median Absolute Deviation (MAD)20
Skewness5.307556
Sum363762
Variance14493.47
MonotonicityNot monotonic
2024-03-14T23:46:28.400261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 922
 
15.2%
4 240
 
4.0%
6 194
 
3.2%
2 168
 
2.8%
8 160
 
2.6%
12 149
 
2.5%
16 113
 
1.9%
9 107
 
1.8%
20 97
 
1.6%
10 95
 
1.6%
Other values (459) 3821
63.0%
ValueCountFrequency (%)
0 922
15.2%
1 37
 
0.6%
2 168
 
2.8%
3 88
 
1.5%
4 240
 
4.0%
5 76
 
1.3%
6 194
 
3.2%
7 80
 
1.3%
8 160
 
2.6%
9 107
 
1.8%
ValueCountFrequency (%)
1629 1
< 0.1%
1570 1
< 0.1%
1546 1
< 0.1%
1491 1
< 0.1%
1417 1
< 0.1%
1403 1
< 0.1%
1384 1
< 0.1%
1376 1
< 0.1%
1296 1
< 0.1%
1191 1
< 0.1%

Interactions

2024-03-14T23:46:19.143449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:46:18.560109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:46:19.438286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:46:18.851234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:46:28.673918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적호수
연면적1.0000.000
호수0.0001.000
2024-03-14T23:46:28.896438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적호수
연면적1.0000.667
호수0.6671.000

Missing values

2024-03-14T23:46:19.804002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:46:20.128277image/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

대지위치건물명동_세부용도연면적호수
0서울특별시 강남구 개포동 1194-1런던빌 개포단지형다세대주택,오피스텔1038.756
1서울특별시 강남구 개포동 1229-10하우징허브럭스오피스텔1723.220
2서울특별시 강남구 개포동 1229-6CCRU오피스텔업무시설(오피스텔 15호실), 다세대주택(20세대), 근린생활시설2100.4115
3서울특별시 강남구 개포동 1236-4디오빌업무시설 (오피스텔)1123.7622
4서울특별시 강남구 개포동 1237-3<NA>오피스텔,근린생활시설936.1521
5서울특별시 강남구 개포동 1237-7한별2도시형생활주택 및 오피스텔753.554
6서울특별시 강남구 개포동 1237-8YH빌리지공동주택(다세대주택)906.375
7서울특별시 강남구 개포동 1246-3골든빌오피스텔업무시설,오피스텔948.4435
8서울특별시 강남구 개포동 157-9개포동 157-9 공동주택 (김해옥)공동주택, 업무시설, 근린생활시설1440.058
9서울특별시 강남구 개포동 186-13메트하임근린생활시설,업무시설(오피스텔)10846.626141
대지위치건물명동_세부용도연면적호수
6056서울특별시 중랑구 중화동 208-16더샤이닝업무시설,도시형생활주택,근린생활시설4541.6598
6057서울특별시 중랑구 중화동 208-4중화동 범양프레체공동주택(도시형생활주택 원룸형),업무시설(오피스텔),제2종 근린생활시설10970.98118
6058서울특별시 중랑구 중화동 286-33알파인 오피스텔오피스텔 및 다세대주택1129.9518
6059서울특별시 중랑구 중화동 301-110천수빌딩근린생활시설, 업무시설(오피스텔), 단독주택(다가구주택)2736.2621
6060서울특별시 중랑구 중화동 305-34그라티아스토리공동주택(도시형생활주택-단지형다세대), 업무시설(오피스텔), 근린생활시설1117.247
6061서울특별시 중랑구 중화동 305-48아가페하우스도시형생활주택,업무시설,근린생활시설560.224
6062서울특별시 중랑구 중화동 305-59탑클래스2차도시형생활주택,업무시설,근린생활시설995.5110
6063서울특별시 중랑구 중화동 307-4화인하우스도시형생활주택(단지형다세대)및오피스텔1008.34
6064서울특별시 중랑구 중화동 307-4화인하우스도시형생활주택(단지형다세대)및오피스텔1024.544
6065서울특별시 중랑구 중화동 307-4화인하우스도시형생활주택(단지형다세대)및오피스텔1079.574

Duplicate rows

Most frequently occurring

대지위치건물명동_세부용도연면적호수# duplicates
26서울특별시 중랑구 면목동 1550-0봄작시티 50공동주택(도시형생활주택-단지형다세대)/업무시설(오피스텔)934.2264
0서울특별시 강서구 가양동 257-1마곡보타닉투웨니퍼스트오피스텔2313.44523
7서울특별시 도봉구 도봉동 62-43도봉 투웨니퍼스트 2단지업무시설(오피스텔)2506.4523
23서울특별시 영등포구 양평동5가 51-0에듀시티에비앙업무시설2190.72483
1서울특별시 강서구 가양동 257-1마곡보타닉투웨니퍼스트오피스텔2390.45532
2서울특별시 강서구 등촌동 633-17등촌투웨니퍼스트2차업무시설(오피스텔)2348.68522
3서울특별시 강서구 등촌동 633-17등촌투웨니퍼스트2차업무시설(오피스텔)2449.91542
4서울특별시 강서구 등촌동 634-10투웨니퍼스트1차업무시설(오피스텔)2141.9522
5서울특별시 강서구 염창동 266-12한빛어반뉴스토리업무시설(오피스텔)2220.74562
6서울특별시 도봉구 도봉동 62-3도봉 투웨니퍼스트 1단지업무시설(오피스텔)2568.8522