Overview

Dataset statistics

Number of variables7
Number of observations73
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory61.8 B

Variable types

Numeric4
Categorical1
Text2

Dataset

Descriptionㅁ 기계설비 성능점검 대상 건축물 현황(연면적 1m²2이상 일반건축물과 500세대 이상 공동주택)- 용도, 건물명, 도로명주소, 우편번호, 연면적, 세대수 필드로 구성되어 있습니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15124663/fileData.do

Alerts

순번 is highly overall correlated with 세대수High correlation
연면적(제곱미터) is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
건물명 has unique valuesUnique
연면적(제곱미터) has 15 (20.5%) zerosZeros
세대수 has 58 (79.5%) zerosZeros

Reproduction

Analysis started2023-12-12 11:13:42.723313
Analysis finished2023-12-12 11:13:46.375144
Duration3.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37
Minimum1
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T20:13:46.483154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.6
Q119
median37
Q355
95-th percentile69.4
Maximum73
Range72
Interquartile range (IQR)36

Descriptive statistics

Standard deviation21.217131
Coefficient of variation (CV)0.57343598
Kurtosis-1.2
Mean37
Median Absolute Deviation (MAD)18
Skewness0
Sum2701
Variance450.16667
MonotonicityStrictly increasing
2023-12-12T20:13:46.686390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
56 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%

용도
Categorical

Distinct11
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
업무시설
39 
공동주택
15 
교육연구시설
8 
의료시설
 
2
종교시설
 
2
Other values (6)
7 

Length

Max length6
Median length4
Mean length4.2465753
Min length4

Unique

Unique5 ?
Unique (%)6.8%

Sample

1st row오피스텔
2nd row의료시설
3rd row업무시설
4th row교육연구시설
5th row업무시설

Common Values

ValueCountFrequency (%)
업무시설 39
53.4%
공동주택 15
 
20.5%
교육연구시설 8
 
11.0%
의료시설 2
 
2.7%
종교시설 2
 
2.7%
판매시설 2
 
2.7%
오피스텔 1
 
1.4%
근린생활시설 1
 
1.4%
전시시설 1
 
1.4%
운수시설 1
 
1.4%

Length

2023-12-12T20:13:46.858599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 39
53.4%
공동주택 15
 
20.5%
교육연구시설 8
 
11.0%
의료시설 2
 
2.7%
종교시설 2
 
2.7%
판매시설 2
 
2.7%
오피스텔 1
 
1.4%
근린생활시설 1
 
1.4%
전시시설 1
 
1.4%
운수시설 1
 
1.4%

건물명
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T20:13:47.135614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.9041096
Min length4

Characters and Unicode

Total characters577
Distinct characters184
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)100.0%

Sample

1st row이튼타워리버3차
2nd row혜민병원
3rd row구의아크로리버
4th row서울구남초등학교
5th row군자비채온오피스텔
ValueCountFrequency (%)
현대프라임아파트 2
 
2.3%
더샵스타시티 2
 
2.3%
이튼타워리버3차 1
 
1.1%
국립정신건강센터 1
 
1.1%
건국대학교병원 1
 
1.1%
동서울우편집중국청사 1
 
1.1%
펜트하우스 1
 
1.1%
더라움 1
 
1.1%
상가동(이마트 1
 
1.1%
보건복지행정타운 1
 
1.1%
Other values (76) 76
86.4%
2023-12-12T20:13:47.665904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 22
 
3.8%
파 20
 
3.5%
대 18
 
3.1%
아 18
 
3.1%
15
 
2.6%
스 14
 
2.4%
광 14
 
2.4%
타 11
 
1.9%
교 11
 
1.9%
학 11
 
1.9%
Other values (174) 423
73.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 528
91.5%
Space Separator 15
 
2.6%
Decimal Number 12
 
2.1%
Uppercase Letter 10
 
1.7%
Open Punctuation 4
 
0.7%
Close Punctuation 4
 
0.7%
Lowercase Letter 3
 
0.5%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 22
 
4.2%
파 20
 
3.8%
대 18
 
3.4%
아 18
 
3.4%
스 14
 
2.7%
광 14
 
2.7%
타 11
 
2.1%
교 11
 
2.1%
학 11
 
2.1%
크 11
 
2.1%
Other values (153) 378
71.6%
Decimal Number
ValueCountFrequency (%)
3 3
25.0%
5 2
16.7%
0 2
16.7%
2 2
16.7%
1 1
 
8.3%
7 1
 
8.3%
8 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
30.0%
A 2
20.0%
Z 1
 
10.0%
L 1
 
10.0%
P 1
 
10.0%
S 1
 
10.0%
K 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
k 1
33.3%
s 1
33.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 529
91.7%
Common 35
 
6.1%
Latin 13
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 22
 
4.2%
파 20
 
3.8%
대 18
 
3.4%
아 18
 
3.4%
스 14
 
2.6%
광 14
 
2.6%
타 11
 
2.1%
교 11
 
2.1%
학 11
 
2.1%
크 11
 
2.1%
Other values (154) 379
71.6%
Common
ValueCountFrequency (%)
15
42.9%
( 4
 
11.4%
) 4
 
11.4%
3 3
 
8.6%
5 2
 
5.7%
0 2
 
5.7%
2 2
 
5.7%
1 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
Latin
ValueCountFrequency (%)
C 3
23.1%
A 2
15.4%
e 1
 
7.7%
Z 1
 
7.7%
L 1
 
7.7%
P 1
 
7.7%
S 1
 
7.7%
K 1
 
7.7%
k 1
 
7.7%
s 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 528
91.5%
ASCII 48
 
8.3%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 22
 
4.2%
파 20
 
3.8%
대 18
 
3.4%
아 18
 
3.4%
스 14
 
2.7%
광 14
 
2.7%
타 11
 
2.1%
교 11
 
2.1%
학 11
 
2.1%
크 11
 
2.1%
Other values (153) 378
71.6%
ASCII
ValueCountFrequency (%)
15
31.2%
( 4
 
8.3%
) 4
 
8.3%
3 3
 
6.2%
C 3
 
6.2%
A 2
 
4.2%
5 2
 
4.2%
0 2
 
4.2%
2 2
 
4.2%
1 1
 
2.1%
Other values (10) 10
20.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

Distinct69
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T20:13:48.089541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length23.849315
Min length15

Characters and Unicode

Total characters1741
Distinct characters56
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)90.4%

Sample

1st row서울특별시 광진구 능동로 18 (자양동)
2nd row서울특별시 광진구 자양로 85 (자양동)
3rd row서울특별시 광진구 구의강변로 64 (구의동)
4th row서울특별시 광진구 구의강변로 69 (구의동)
5th row서울특별시 광진구 천호대로 530 (군자동)
ValueCountFrequency (%)
서울특별시 73
20.2%
광진구 73
20.2%
구의동 18
 
5.0%
광장동 16
 
4.4%
아차산로 15
 
4.1%
자양동 15
 
4.1%
능동로 14
 
3.9%
화양동 12
 
3.3%
광나루로 7
 
1.9%
중곡동 5
 
1.4%
Other values (85) 114
31.5%
2023-12-12T20:13:48.795924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
289
 
16.6%
광 101
 
5.8%
구 94
 
5.4%
동 89
 
5.1%
서 73
 
4.2%
특 73
 
4.2%
별 73
 
4.2%
시 73
 
4.2%
진 73
 
4.2%
울 73
 
4.2%
Other values (46) 730
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1080
62.0%
Space Separator 289
 
16.6%
Decimal Number 226
 
13.0%
Close Punctuation 71
 
4.1%
Open Punctuation 71
 
4.1%
Dash Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 101
 
9.4%
구 94
 
8.7%
동 89
 
8.2%
서 73
 
6.8%
특 73
 
6.8%
별 73
 
6.8%
시 73
 
6.8%
진 73
 
6.8%
울 73
 
6.8%
로 73
 
6.8%
Other values (31) 285
26.4%
Decimal Number
ValueCountFrequency (%)
1 30
13.3%
5 30
13.3%
6 28
12.4%
2 27
11.9%
4 26
11.5%
7 22
9.7%
3 19
8.4%
0 18
8.0%
8 14
6.2%
9 12
 
5.3%
Space Separator
ValueCountFrequency (%)
289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1080
62.0%
Common 661
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 101
 
9.4%
구 94
 
8.7%
동 89
 
8.2%
서 73
 
6.8%
특 73
 
6.8%
별 73
 
6.8%
시 73
 
6.8%
진 73
 
6.8%
울 73
 
6.8%
로 73
 
6.8%
Other values (31) 285
26.4%
Common
ValueCountFrequency (%)
289
43.7%
) 71
 
10.7%
( 71
 
10.7%
1 30
 
4.5%
5 30
 
4.5%
6 28
 
4.2%
2 27
 
4.1%
4 26
 
3.9%
7 22
 
3.3%
3 19
 
2.9%
Other values (5) 48
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1080
62.0%
ASCII 661
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
289
43.7%
) 71
 
10.7%
( 71
 
10.7%
1 30
 
4.5%
5 30
 
4.5%
6 28
 
4.2%
2 27
 
4.1%
4 26
 
3.9%
7 22
 
3.3%
3 19
 
2.9%
Other values (5) 48
 
7.3%
Hangul
ValueCountFrequency (%)
광 101
 
9.4%
구 94
 
8.7%
동 89
 
8.2%
서 73
 
6.8%
특 73
 
6.8%
별 73
 
6.8%
시 73
 
6.8%
진 73
 
6.8%
울 73
 
6.8%
로 73
 
6.8%
Other values (31) 285
26.4%

우편번호
Real number (ℝ)

Distinct51
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5021.1781
Minimum4904
Maximum5119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T20:13:49.072690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4904
5-th percentile4933
Q14980
median5023
Q35056
95-th percentile5116
Maximum5119
Range215
Interquartile range (IQR)76

Descriptive statistics

Standard deviation52.176608
Coefficient of variation (CV)0.010391308
Kurtosis-0.43263443
Mean5021.1781
Median Absolute Deviation (MAD)42
Skewness0.057549313
Sum366546
Variance2722.3984
MonotonicityNot monotonic
2023-12-12T20:13:49.356273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5116 4
 
5.5%
5065 4
 
5.5%
4969 3
 
4.1%
5025 3
 
4.1%
5119 2
 
2.7%
4971 2
 
2.7%
4983 2
 
2.7%
5073 2
 
2.7%
5030 2
 
2.7%
4933 2
 
2.7%
Other values (41) 47
64.4%
ValueCountFrequency (%)
4904 1
 
1.4%
4918 1
 
1.4%
4919 1
 
1.4%
4933 2
2.7%
4963 1
 
1.4%
4964 1
 
1.4%
4965 1
 
1.4%
4967 1
 
1.4%
4969 3
4.1%
4971 2
2.7%
ValueCountFrequency (%)
5119 2
2.7%
5118 1
 
1.4%
5116 4
5.5%
5096 1
 
1.4%
5074 1
 
1.4%
5073 2
2.7%
5072 1
 
1.4%
5068 1
 
1.4%
5066 1
 
1.4%
5065 4
5.5%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37221.595
Minimum0
Maximum434581.12
Zeros15
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T20:13:49.704103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110252.42
median14777.2
Q329895.39
95-th percentile214372.04
Maximum434581.12
Range434581.12
Interquartile range (IQR)19642.97

Descriptive statistics

Standard deviation73281.544
Coefficient of variation (CV)1.9687911
Kurtosis14.790389
Mean37221.595
Median Absolute Deviation (MAD)11117.23
Skewness3.7169717
Sum2717176.4
Variance5.3701847 × 109
MonotonicityNot monotonic
2023-12-12T20:13:49.982285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 15
 
20.5%
10011.95 1
 
1.4%
44996.71 1
 
1.4%
20428.33 1
 
1.4%
22162.72 1
 
1.4%
22330.49 1
 
1.4%
24945.96 1
 
1.4%
25894.43 1
 
1.4%
28515.35 1
 
1.4%
28839.04 1
 
1.4%
Other values (49) 49
67.1%
ValueCountFrequency (%)
0.0 15
20.5%
10011.95 1
 
1.4%
10033.12 1
 
1.4%
10059.73 1
 
1.4%
10252.42 1
 
1.4%
10269.15 1
 
1.4%
10541.2 1
 
1.4%
10773.34 1
 
1.4%
11280.89 1
 
1.4%
11284.43 1
 
1.4%
ValueCountFrequency (%)
434581.12 1
1.4%
292903.671 1
1.4%
259730.9 1
1.4%
247344.58 1
1.4%
192390.35 1
1.4%
85686.68 1
1.4%
71491.25 1
1.4%
65548.28 1
1.4%
54117.39 1
1.4%
52252.83 1
1.4%

세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169.61644
Minimum0
Maximum1606
Zeros58
Zeros (%)79.5%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T20:13:50.185216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile960
Maximum1606
Range1606
Interquartile range (IQR)0

Descriptive statistics

Standard deviation374.93587
Coefficient of variation (CV)2.2104925
Kurtosis5.1551306
Mean169.61644
Median Absolute Deviation (MAD)0
Skewness2.3491167
Sum12382
Variance140576.91
MonotonicityNot monotonic
2023-12-12T20:13:50.439220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 58
79.5%
656 1
 
1.4%
1606 1
 
1.4%
1592 1
 
1.4%
1170 1
 
1.4%
1056 1
 
1.4%
730 1
 
1.4%
854 1
 
1.4%
654 1
 
1.4%
545 1
 
1.4%
Other values (6) 6
 
8.2%
ValueCountFrequency (%)
0 58
79.5%
432 1
 
1.4%
448 1
 
1.4%
537 1
 
1.4%
545 1
 
1.4%
581 1
 
1.4%
625 1
 
1.4%
654 1
 
1.4%
656 1
 
1.4%
730 1
 
1.4%
ValueCountFrequency (%)
1606 1
1.4%
1592 1
1.4%
1170 1
1.4%
1056 1
1.4%
896 1
1.4%
854 1
1.4%
730 1
1.4%
656 1
1.4%
654 1
1.4%
625 1
1.4%

Interactions

2023-12-12T20:13:44.903977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:43.312171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:43.993931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.483469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:45.011971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:43.497051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.150701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.598151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:45.111286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:43.653775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.260922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.702395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:45.748992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:43.832591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.362751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:44.793271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:13:50.633758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번용도건물명도로명주소우편번호연면적(제곱미터)세대수
순번1.0000.6401.0000.8910.1800.6990.674
용도0.6401.0001.0000.9380.7130.7470.174
건물명1.0001.0001.0001.0001.0001.0001.000
도로명주소0.8910.9381.0001.0001.0000.0000.000
우편번호0.1800.7131.0001.0001.0000.3150.000
연면적(제곱미터)0.6990.7471.0000.0000.3151.0000.000
세대수0.6740.1741.0000.0000.0000.0001.000
2023-12-12T20:13:50.890128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호연면적(제곱미터)세대수용도
순번1.000-0.0380.0120.7040.331
우편번호-0.0381.0000.097-0.0830.424
연면적(제곱미터)0.0120.0971.000-0.6970.486
세대수0.704-0.083-0.6971.0000.066
용도0.3310.4240.4860.0661.000

Missing values

2023-12-12T20:13:46.043043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:13:46.269007image/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

순번용도건물명도로명주소우편번호연면적(제곱미터)세대수
01오피스텔이튼타워리버3차서울특별시 광진구 능동로 18 (자양동)509610011.950
12의료시설혜민병원서울특별시 광진구 자양로 85 (자양동)505610033.120
23업무시설구의아크로리버서울특별시 광진구 구의강변로 64 (구의동)511610059.730
34교육연구시설서울구남초등학교서울특별시 광진구 구의강변로 69 (구의동)504810252.420
45업무시설군자비채온오피스텔서울특별시 광진구 천호대로 530 (군자동)499610269.150
56업무시설인성빌딩서울특별시 광진구 아차산로 627 (광장동)496710541.20
67종교시설한국천주교서울특별시 광진구 면목로 74 (중곡동)491810773.340
78교육연구시설서울자양초등학교서울특별시 광진구 아차산로44길 26 (자양동)505411280.890
89업무시설CS PLAZA서울특별시 광진구 아차산로 471 (구의동)503511284.430
910교육연구시설서울양진초등학교서울특별시 광진구 워커힐로 32 (광장동)498211447.010
순번용도건물명도로명주소우편번호연면적(제곱미터)세대수
6364공동주택광장현대8단지아파트서울특별시 광진구 아차산로 522, 508 (광장동)49740.0537
6465공동주택자양7차우성아파트서울특별시 광진구 아차산로36길 39 (자양동)50660.0625
6566공동주택청구아파트서울특별시 광진구 아차산로 503-23 (광장동)49840.0654
6667공동주택우성아파트서울특별시 광진구 뚝섬로 569 (자양동)50680.0656
6768공동주택래미안파크스위트서울특별시 광진구 광나루로 545 (구의동)49780.0854
6869공동주택e편한세상광진그랜드파크아파트서울특별시 광진구 광나루로 458 (구의동)50220.0730
6970공동주택광장현대3단지아파트서울특별시 광진구 아차산로70길 62 (광장동)49740.01056
7071공동주택광장현대파크빌서울특별시 광진구 아차산로 549 (광장동)49830.01170
7172공동주택현대프라임아파트서울특별시 광진구 광나루로56길 29 (구의동)51190.01592
7273공동주택구의현대2단지아파트서울특별시 광진구 광나루로56길 32 (구의동)51180.01606