Overview

Dataset statistics

Number of variables6
Number of observations366
Missing cells3
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description창원시 관내에 위치한 석면조사대상 건축물 현황 자료로, 석면건축물명, 소재지, 위해성 평가의 항목을 제공합니다.
Author경상남도 창원시
URLhttps://www.data.go.kr/data/3068544/fileData.do

Alerts

번호 is highly overall correlated with 위해성 평가High correlation
위해성 평가 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:45:36.282673
Analysis finished2024-04-21 02:45:38.221076
Duration1.94 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.5
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-04-21T11:45:38.296835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.25
Q192.25
median183.5
Q3274.75
95-th percentile347.75
Maximum366
Range365
Interquartile range (IQR)182.5

Descriptive statistics

Standard deviation105.79934
Coefficient of variation (CV)0.57656315
Kurtosis-1.2
Mean183.5
Median Absolute Deviation (MAD)91.5
Skewness0
Sum67161
Variance11193.5
MonotonicityStrictly increasing
2024-04-21T11:45:38.437220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
253 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
244 1
 
0.3%
Other values (356) 356
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%
358 1
0.3%
357 1
0.3%

건축물 분류
Categorical

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
공공건축물
166 
불특정다수이용
82 
대학교
52 
어린이집
49 
기타
17 

Length

Max length7
Median length5
Mean length4.8907104
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불특정다수이용
2nd row어린이집
3rd row불특정다수이용
4th row불특정다수이용
5th row불특정다수이용

Common Values

ValueCountFrequency (%)
공공건축물 166
45.4%
불특정다수이용 82
22.4%
대학교 52
 
14.2%
어린이집 49
 
13.4%
기타 17
 
4.6%

Length

2024-04-21T11:45:38.570573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:45:38.676556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공건축물 166
45.4%
불특정다수이용 82
22.4%
대학교 52
 
14.2%
어린이집 49
 
13.4%
기타 17
 
4.6%

건축물명
Text

Distinct295
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-04-21T11:45:38.862096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.3114754
Min length3

Characters and Unicode

Total characters3042
Distinct characters314
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)73.8%

Sample

1st row대동훼미리상가
2nd row덕산이든어린이집
3rd row경창종합상가
4th row복음요양병원
5th row새롬오피스텔(주차장)
ValueCountFrequency (%)
경남대학교 18
 
4.0%
마산대학 9
 
2.0%
창원문성대학 9
 
2.0%
한국전력공사 8
 
1.8%
한국전기연구원 7
 
1.5%
창원대학교 6
 
1.3%
청아의료재단 6
 
1.3%
동창원농협 5
 
1.1%
본점 5
 
1.1%
창원시(농산물도매시장 4
 
0.9%
Other values (319) 376
83.0%
2024-04-21T11:45:39.175888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 146
 
4.8%
89
 
2.9%
창 86
 
2.8%
동 83
 
2.7%
산 74
 
2.4%
대 62
 
2.0%
마 58
 
1.9%
이 57
 
1.9%
) 54
 
1.8%
( 54
 
1.8%
Other values (304) 2279
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2814
92.5%
Space Separator 89
 
2.9%
Close Punctuation 54
 
1.8%
Open Punctuation 54
 
1.8%
Decimal Number 18
 
0.6%
Uppercase Letter 7
 
0.2%
Other Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 146
 
5.2%
창 86
 
3.1%
동 83
 
2.9%
산 74
 
2.6%
대 62
 
2.2%
마 58
 
2.1%
이 57
 
2.0%
학 53
 
1.9%
장 53
 
1.9%
린 52
 
1.8%
Other values (289) 2090
74.3%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
5 2
 
11.1%
3 2
 
11.1%
2 2
 
11.1%
4 2
 
11.1%
9 1
 
5.6%
6 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
71.4%
S 1
 
14.3%
K 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2814
92.5%
Common 221
 
7.3%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 146
 
5.2%
창 86
 
3.1%
동 83
 
2.9%
산 74
 
2.6%
대 62
 
2.2%
마 58
 
2.1%
이 57
 
2.0%
학 53
 
1.9%
장 53
 
1.9%
린 52
 
1.8%
Other values (289) 2090
74.3%
Common
ValueCountFrequency (%)
89
40.3%
) 54
24.4%
( 54
24.4%
1 8
 
3.6%
. 5
 
2.3%
5 2
 
0.9%
3 2
 
0.9%
2 2
 
0.9%
4 2
 
0.9%
9 1
 
0.5%
Other values (2) 2
 
0.9%
Latin
ValueCountFrequency (%)
B 5
71.4%
S 1
 
14.3%
K 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2814
92.5%
ASCII 228
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 146
 
5.2%
창 86
 
3.1%
동 83
 
2.9%
산 74
 
2.6%
대 62
 
2.2%
마 58
 
2.1%
이 57
 
2.0%
학 53
 
1.9%
장 53
 
1.9%
린 52
 
1.8%
Other values (289) 2090
74.3%
ASCII
ValueCountFrequency (%)
89
39.0%
) 54
23.7%
( 54
23.7%
1 8
 
3.5%
B 5
 
2.2%
. 5
 
2.2%
5 2
 
0.9%
3 2
 
0.9%
2 2
 
0.9%
4 2
 
0.9%
Other values (5) 5
 
2.2%

동명
Text

Distinct350
Distinct (%)96.2%
Missing2
Missing (%)0.5%
Memory size3.0 KiB
2024-04-21T11:45:39.389878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.8928571
Min length2

Characters and Unicode

Total characters2873
Distinct characters325
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique342 ?
Unique (%)94.0%

Sample

1st row대동훼미리상가
2nd row덕산이든어린이집
3rd row경창종합상가
4th row복음요양병원
5th row새롬오피스텔(주차장)
ValueCountFrequency (%)
본관 10
 
2.2%
한국전기연구원 7
 
1.6%
본관동 6
 
1.3%
동창원농협 5
 
1.1%
한국전력공사 5
 
1.1%
롯데백화점 4
 
0.9%
본점 4
 
0.9%
마산수협 4
 
0.9%
지하주차장 3
 
0.7%
별관 3
 
0.7%
Other values (377) 398
88.6%
2024-04-21T11:45:39.731992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 115
 
4.0%
동 111
 
3.9%
원 98
 
3.4%
87
 
3.0%
) 61
 
2.1%
( 61
 
2.1%
이 57
 
2.0%
집 52
 
1.8%
어 52
 
1.8%
린 52
 
1.8%
Other values (315) 2127
74.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2571
89.5%
Space Separator 87
 
3.0%
Decimal Number 62
 
2.2%
Close Punctuation 61
 
2.1%
Open Punctuation 61
 
2.1%
Uppercase Letter 19
 
0.7%
Other Punctuation 7
 
0.2%
Lowercase Letter 2
 
0.1%
Dash Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 115
 
4.5%
동 111
 
4.3%
원 98
 
3.8%
이 57
 
2.2%
집 52
 
2.0%
어 52
 
2.0%
린 52
 
2.0%
산 51
 
2.0%
창 50
 
1.9%
지 48
 
1.9%
Other values (285) 1885
73.3%
Uppercase Letter
ValueCountFrequency (%)
A 4
21.1%
C 3
15.8%
B 3
15.8%
D 1
 
5.3%
F 1
 
5.3%
S 1
 
5.3%
K 1
 
5.3%
V 1
 
5.3%
G 1
 
5.3%
R 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 21
33.9%
2 10
16.1%
3 7
 
11.3%
4 6
 
9.7%
5 5
 
8.1%
0 3
 
4.8%
9 3
 
4.8%
8 3
 
4.8%
6 2
 
3.2%
7 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2571
89.5%
Common 281
 
9.8%
Latin 21
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 115
 
4.5%
동 111
 
4.3%
원 98
 
3.8%
이 57
 
2.2%
집 52
 
2.0%
어 52
 
2.0%
린 52
 
2.0%
산 51
 
2.0%
창 50
 
1.9%
지 48
 
1.9%
Other values (285) 1885
73.3%
Common
ValueCountFrequency (%)
87
31.0%
) 61
21.7%
( 61
21.7%
1 21
 
7.5%
2 10
 
3.6%
3 7
 
2.5%
4 6
 
2.1%
, 6
 
2.1%
5 5
 
1.8%
0 3
 
1.1%
Other values (7) 14
 
5.0%
Latin
ValueCountFrequency (%)
A 4
19.0%
C 3
14.3%
B 3
14.3%
m 2
9.5%
D 1
 
4.8%
F 1
 
4.8%
S 1
 
4.8%
K 1
 
4.8%
V 1
 
4.8%
G 1
 
4.8%
Other values (3) 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2571
89.5%
ASCII 302
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 115
 
4.5%
동 111
 
4.3%
원 98
 
3.8%
이 57
 
2.2%
집 52
 
2.0%
어 52
 
2.0%
린 52
 
2.0%
산 51
 
2.0%
창 50
 
1.9%
지 48
 
1.9%
Other values (285) 1885
73.3%
ASCII
ValueCountFrequency (%)
87
28.8%
) 61
20.2%
( 61
20.2%
1 21
 
7.0%
2 10
 
3.3%
3 7
 
2.3%
4 6
 
2.0%
, 6
 
2.0%
5 5
 
1.7%
A 4
 
1.3%
Other values (20) 34
 
11.3%

건축물 주소
Text

Distinct264
Distinct (%)72.3%
Missing1
Missing (%)0.3%
Memory size3.0 KiB
2024-04-21T11:45:39.978359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length44
Mean length29.443836
Min length23

Characters and Unicode

Total characters10747
Distinct characters206
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

Unique225 ?
Unique (%)61.6%

Sample

1st row경상남도 창원시 성산구 대정로 138 (대방동)
2nd row경상남도 창원시 성산구 대정로 131, 복리관 1층 (대방동, 대방덕산타운)
3rd row경상남도 창원시 성산구 상남로 67 (상남동)
4th row경상남도 창원시 마산회원구 3·15대로 850 (합성동)
5th row경상남도 창원시 성산구 상남로 35 (상남동)
ValueCountFrequency (%)
경상남도 365
 
16.4%
창원시 365
 
16.4%
성산구 112
 
5.0%
마산합포구 81
 
3.6%
마산회원구 69
 
3.1%
의창구 66
 
3.0%
진해구 37
 
1.7%
내서읍 29
 
1.3%
상남동 24
 
1.1%
팔용동 22
 
1.0%
Other values (510) 1051
47.3%
2024-04-21T11:45:40.343352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1856
 
17.3%
원 504
 
4.7%
창 468
 
4.4%
남 436
 
4.1%
상 410
 
3.8%
경 385
 
3.6%
동 383
 
3.6%
구 378
 
3.5%
도 369
 
3.4%
시 366
 
3.4%
Other values (196) 5192
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6919
64.4%
Space Separator 1856
 
17.3%
Decimal Number 1225
 
11.4%
Close Punctuation 318
 
3.0%
Open Punctuation 318
 
3.0%
Other Punctuation 71
 
0.7%
Dash Punctuation 39
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 504
 
7.3%
창 468
 
6.8%
남 436
 
6.3%
상 410
 
5.9%
경 385
 
5.6%
동 383
 
5.5%
구 378
 
5.5%
도 369
 
5.3%
시 366
 
5.3%
로 326
 
4.7%
Other values (178) 2894
41.8%
Decimal Number
ValueCountFrequency (%)
1 281
22.9%
2 166
13.6%
3 136
11.1%
7 116
9.5%
6 108
 
8.8%
0 105
 
8.6%
5 99
 
8.1%
4 83
 
6.8%
9 76
 
6.2%
8 55
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 57
80.3%
· 13
 
18.3%
? 1
 
1.4%
Space Separator
ValueCountFrequency (%)
1856
100.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 318
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6919
64.4%
Common 3827
35.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 504
 
7.3%
창 468
 
6.8%
남 436
 
6.3%
상 410
 
5.9%
경 385
 
5.6%
동 383
 
5.5%
구 378
 
5.5%
도 369
 
5.3%
시 366
 
5.3%
로 326
 
4.7%
Other values (178) 2894
41.8%
Common
ValueCountFrequency (%)
1856
48.5%
) 318
 
8.3%
( 318
 
8.3%
1 281
 
7.3%
2 166
 
4.3%
3 136
 
3.6%
7 116
 
3.0%
6 108
 
2.8%
0 105
 
2.7%
5 99
 
2.6%
Other values (7) 324
 
8.5%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6919
64.4%
ASCII 3815
35.5%
None 13
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1856
48.7%
) 318
 
8.3%
( 318
 
8.3%
1 281
 
7.4%
2 166
 
4.4%
3 136
 
3.6%
7 116
 
3.0%
6 108
 
2.8%
0 105
 
2.8%
5 99
 
2.6%
Other values (7) 312
 
8.2%
Hangul
ValueCountFrequency (%)
원 504
 
7.3%
창 468
 
6.8%
남 436
 
6.3%
상 410
 
5.9%
경 385
 
5.6%
동 383
 
5.5%
구 378
 
5.5%
도 369
 
5.3%
시 366
 
5.3%
로 326
 
4.7%
Other values (178) 2894
41.8%
None
ValueCountFrequency (%)
· 13
100.0%

위해성 평가
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
낮음
318 
중간
48 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
낮음 318
86.9%
중간 48
 
13.1%

Length

2024-04-21T11:45:40.466838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:45:40.556224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낮음 318
86.9%
중간 48
 
13.1%

Interactions

2024-04-21T11:45:37.799071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:45:40.618150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호건축물 분류위해성 평가
번호1.0000.5370.987
건축물 분류0.5371.0000.270
위해성 평가0.9870.2701.000
2024-04-21T11:45:40.694013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물 분류위해성 평가
건축물 분류1.0000.329
위해성 평가0.3291.000
2024-04-21T11:45:40.773830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호건축물 분류위해성 평가
번호1.0000.2490.890
건축물 분류0.2491.0000.329
위해성 평가0.8900.3291.000

Missing values

2024-04-21T11:45:37.969628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:45:38.079597image/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.
2024-04-21T11:45:38.171661image/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

번호건축물 분류건축물명동명건축물 주소위해성 평가
01불특정다수이용대동훼미리상가대동훼미리상가경상남도 창원시 성산구 대정로 138 (대방동)중간
12어린이집덕산이든어린이집덕산이든어린이집경상남도 창원시 성산구 대정로 131, 복리관 1층 (대방동, 대방덕산타운)중간
23불특정다수이용경창종합상가경창종합상가경상남도 창원시 성산구 상남로 67 (상남동)중간
34불특정다수이용복음요양병원복음요양병원경상남도 창원시 마산회원구 3·15대로 850 (합성동)중간
45불특정다수이용새롬오피스텔(주차장)새롬오피스텔(주차장)경상남도 창원시 성산구 상남로 35 (상남동)중간
56공공건축물한국전력공사진해지사한국전력공사진해지사경상남도 창원시 진해구 여좌천로 122(여좌동)중간
67공공건축물마산자유무역지역 관리원청사마산자유무역지역 관리원청사경상남도 창원시 마산회원구 무역로 27 (양덕동)중간
78대학교마산대학1,2호관경상남도 창원시 마산회원구 내서읍 함마대로 2640중간
89공공건축물북창원농협 본점북창원농협경상남도 창원시 의창구 북면 천주로 1154중간
910공공건축물마산세관 본관마산세관 본관경상남도 창원시 마산합포구 해안대로 148 (월포동)중간
번호건축물 분류건축물명동명건축물 주소위해성 평가
356357공공건축물마산수협 제빙공장 가동.나동.라동마산수협 제빙공장 나동경상남도 창원시 마산합포구 수산1길 214 (오동동)낮음
357358공공건축물마산수협 신용부마산수협 신용부경상남도 창원시 마산합포구 복요리로 12 (오동동)낮음
358359불특정다수이용스카이웰빙파크스카이웰빙파크경상남도 창원시 성산구 동산로 122 (상남동)낮음
359360공공건축물창원노인대학창원노인대학경상남도 창원시 성산구 창원대로 716 (내동)낮음
360361어린이집코끼리어린이집코끼리어린이집경상남도 창원시 진해구 여좌남로49번길 9, 코끼리어린이집 1층 (여좌동)낮음
361362불특정다수이용롯데백화점 영플라자롯데백화점 영플라자경상남도 창원시 성산구 상남로 121 (상남동)낮음
362363불특정다수이용롯데백화점롯데백화점경상남도 창원시 성산구 중앙대로 124 (상남동)낮음
363364어린이집하늘날다어린이집하늘날다어린이집경상남도 창원시 성산구 대정로 149, 관리동 1층 (대방동, 대방개나리1차아파트)낮음
364365공공건축물산림조합중앙회 경남지역본부산림조합중앙회 경남지역본부경상남도 창원시 성산구 중앙대로162번길 11(신월동)낮음
365366어린이집큰별예나어린이집큰별예나어린이집경상남도 창원시 의창구 의안로32번길 7 (소답동)낮음