Overview

Dataset statistics

Number of variables5
Number of observations187
Missing cells94
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory40.7 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 식품자동판매기영업 현황입니다.
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15084140/fileData.do

Alerts

업종명 has constant value ""Constant
소재지(도로명) has 4 (2.1%) missing valuesMissing
소재지전화 has 90 (48.1%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:52:58.473740
Analysis finished2023-12-12 17:52:59.236296
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
식품자동판매기영업
187 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 187
100.0%

Length

2023-12-13T02:52:59.317822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:59.449696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 187
100.0%

업소명
Text

UNIQUE 

Distinct187
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:52:59.681893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.368984
Min length2

Characters and Unicode

Total characters1752
Distinct characters234
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

Unique187 ?
Unique (%)100.0%

Sample

1st row노인복지회관자판기
2nd row상아하이마트
3rd row이마트24 부평테크시티점
4th row돼지슈퍼
5th row한국마사회
ValueCountFrequency (%)
세븐일레븐 14
 
5.4%
이마트24 11
 
4.2%
씨유 11
 
4.2%
지에스25 6
 
2.3%
나우커피 4
 
1.5%
코레일유통(주 4
 
1.5%
gs25 4
 
1.5%
르하임스터디카페 3
 
1.2%
부개중앙점 2
 
0.8%
무인카페 2
 
0.8%
Other values (196) 198
76.4%
2023-12-13T02:53:00.173463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 99
 
5.7%
부 80
 
4.6%
72
 
4.1%
평 59
 
3.4%
2 49
 
2.8%
븐 44
 
2.5%
동 40
 
2.3%
일 36
 
2.1%
이 36
 
2.1%
자 33
 
1.9%
Other values (224) 1204
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1475
84.2%
Decimal Number 103
 
5.9%
Space Separator 72
 
4.1%
Uppercase Letter 48
 
2.7%
Close Punctuation 27
 
1.5%
Open Punctuation 26
 
1.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 99
 
6.7%
부 80
 
5.4%
평 59
 
4.0%
븐 44
 
3.0%
동 40
 
2.7%
일 36
 
2.4%
이 36
 
2.4%
자 33
 
2.2%
스 32
 
2.2%
인 31
 
2.1%
Other values (203) 985
66.8%
Uppercase Letter
ValueCountFrequency (%)
S 17
35.4%
G 16
33.3%
C 4
 
8.3%
U 3
 
6.2%
O 2
 
4.2%
K 1
 
2.1%
P 1
 
2.1%
L 1
 
2.1%
B 1
 
2.1%
F 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
2 49
47.6%
5 27
26.2%
4 20
19.4%
1 4
 
3.9%
7 2
 
1.9%
3 1
 
1.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1475
84.2%
Common 229
 
13.1%
Latin 48
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 99
 
6.7%
부 80
 
5.4%
평 59
 
4.0%
븐 44
 
3.0%
동 40
 
2.7%
일 36
 
2.4%
이 36
 
2.4%
자 33
 
2.2%
스 32
 
2.2%
인 31
 
2.1%
Other values (203) 985
66.8%
Latin
ValueCountFrequency (%)
S 17
35.4%
G 16
33.3%
C 4
 
8.3%
U 3
 
6.2%
O 2
 
4.2%
K 1
 
2.1%
P 1
 
2.1%
L 1
 
2.1%
B 1
 
2.1%
F 1
 
2.1%
Common
ValueCountFrequency (%)
72
31.4%
2 49
21.4%
) 27
 
11.8%
5 27
 
11.8%
( 26
 
11.4%
4 20
 
8.7%
1 4
 
1.7%
7 2
 
0.9%
- 1
 
0.4%
3 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1475
84.2%
ASCII 277
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 99
 
6.7%
부 80
 
5.4%
평 59
 
4.0%
븐 44
 
3.0%
동 40
 
2.7%
일 36
 
2.4%
이 36
 
2.4%
자 33
 
2.2%
스 32
 
2.2%
인 31
 
2.1%
Other values (203) 985
66.8%
ASCII
ValueCountFrequency (%)
72
26.0%
2 49
17.7%
) 27
 
9.7%
5 27
 
9.7%
( 26
 
9.4%
4 20
 
7.2%
S 17
 
6.1%
G 16
 
5.8%
1 4
 
1.4%
C 4
 
1.4%
Other values (11) 15
 
5.4%

소재지(도로명)
Text

MISSING 

Distinct173
Distinct (%)94.5%
Missing4
Missing (%)2.1%
Memory size1.6 KiB
2023-12-13T02:53:00.559273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length33.234973
Min length22

Characters and Unicode

Total characters6082
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

Unique170 ?
Unique (%)92.9%

Sample

1st row인천광역시 부평구 굴포로 114 3층 (삼산동 노인복지회관)
2nd row인천광역시 부평구 아트센터로74번길 91 (십정동)
3rd row인천광역시 부평구 부평대로 293 부평테크시티 107-1호 (청천동)
4th row인천광역시 부평구 평천로306번길 7 (갈산동)
5th row인천광역시 부평구 장제로 54 (부평동)
ValueCountFrequency (%)
인천광역시 183
 
14.7%
부평구 183
 
14.7%
1층 97
 
7.8%
부평동 58
 
4.7%
청천동 31
 
2.5%
일부호 31
 
2.5%
십정동 27
 
2.2%
삼산동 22
 
1.8%
부개동 22
 
1.8%
부평대로 19
 
1.5%
Other values (352) 568
45.8%
2023-12-13T02:53:01.136620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1220
20.1%
부 367
 
6.0%
1 308
 
5.1%
평 287
 
4.7%
천 227
 
3.7%
동 225
 
3.7%
인 200
 
3.3%
광 195
 
3.2%
시 190
 
3.1%
역 189
 
3.1%
Other values (197) 2674
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3567
58.6%
Space Separator 1220
 
20.1%
Decimal Number 892
 
14.7%
Open Punctuation 185
 
3.0%
Close Punctuation 185
 
3.0%
Dash Punctuation 21
 
0.3%
Uppercase Letter 11
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 367
 
10.3%
평 287
 
8.0%
천 227
 
6.4%
동 225
 
6.3%
인 200
 
5.6%
광 195
 
5.5%
시 190
 
5.3%
역 189
 
5.3%
구 188
 
5.3%
로 185
 
5.2%
Other values (175) 1314
36.8%
Decimal Number
ValueCountFrequency (%)
1 308
34.5%
2 104
 
11.7%
0 97
 
10.9%
3 90
 
10.1%
4 68
 
7.6%
5 52
 
5.8%
7 51
 
5.7%
6 47
 
5.3%
8 42
 
4.7%
9 33
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
B 3
27.3%
P 1
 
9.1%
T 1
 
9.1%
S 1
 
9.1%
D 1
 
9.1%
C 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1220
100.0%
Open Punctuation
ValueCountFrequency (%)
( 185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3567
58.6%
Common 2504
41.2%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 367
 
10.3%
평 287
 
8.0%
천 227
 
6.4%
동 225
 
6.3%
인 200
 
5.6%
광 195
 
5.5%
시 190
 
5.3%
역 189
 
5.3%
구 188
 
5.3%
로 185
 
5.2%
Other values (175) 1314
36.8%
Common
ValueCountFrequency (%)
1220
48.7%
1 308
 
12.3%
( 185
 
7.4%
) 185
 
7.4%
2 104
 
4.2%
0 97
 
3.9%
3 90
 
3.6%
4 68
 
2.7%
5 52
 
2.1%
7 51
 
2.0%
Other values (5) 144
 
5.8%
Latin
ValueCountFrequency (%)
A 3
27.3%
B 3
27.3%
P 1
 
9.1%
T 1
 
9.1%
S 1
 
9.1%
D 1
 
9.1%
C 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3567
58.6%
ASCII 2515
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1220
48.5%
1 308
 
12.2%
( 185
 
7.4%
) 185
 
7.4%
2 104
 
4.1%
0 97
 
3.9%
3 90
 
3.6%
4 68
 
2.7%
5 52
 
2.1%
7 51
 
2.0%
Other values (12) 155
 
6.2%
Hangul
ValueCountFrequency (%)
부 367
 
10.3%
평 287
 
8.0%
천 227
 
6.4%
동 225
 
6.3%
인 200
 
5.6%
광 195
 
5.5%
시 190
 
5.3%
역 189
 
5.3%
구 188
 
5.3%
로 185
 
5.2%
Other values (175) 1314
36.8%

소재지(지번)
Text

Distinct176
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:53:01.576153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length25.02139
Min length17

Characters and Unicode

Total characters4679
Distinct characters172
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

Unique172 ?
Unique (%)92.0%

Sample

1st row인천광역시 부평구 삼산동 441-2 노인복지회관 3층
2nd row인천광역시 부평구 십정동 584-7
3rd row인천광역시 부평구 청천동 425-4 부평테크시티 107-1호
4th row인천광역시 부평구 갈산동 172-1
5th row인천광역시 부평구 부평동 161-3
ValueCountFrequency (%)
인천광역시 187
19.0%
부평구 187
19.0%
부평동 60
 
6.1%
1층 50
 
5.1%
청천동 32
 
3.3%
십정동 27
 
2.7%
부개동 22
 
2.2%
삼산동 22
 
2.2%
일부 17
 
1.7%
산곡동 13
 
1.3%
Other values (302) 367
37.3%
2023-12-13T02:53:02.198633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
808
17.3%
부 303
 
6.5%
1 276
 
5.9%
평 257
 
5.5%
천 222
 
4.7%
동 209
 
4.5%
인 194
 
4.1%
역 193
 
4.1%
구 193
 
4.1%
시 191
 
4.1%
Other values (162) 1833
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2705
57.8%
Decimal Number 996
 
21.3%
Space Separator 808
 
17.3%
Dash Punctuation 154
 
3.3%
Uppercase Letter 9
 
0.2%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 303
11.2%
평 257
 
9.5%
천 222
 
8.2%
동 209
 
7.7%
인 194
 
7.2%
역 193
 
7.1%
구 193
 
7.1%
시 191
 
7.1%
광 188
 
7.0%
산 57
 
2.1%
Other values (140) 698
25.8%
Decimal Number
ValueCountFrequency (%)
1 276
27.7%
4 110
 
11.0%
2 98
 
9.8%
0 90
 
9.0%
3 86
 
8.6%
5 69
 
6.9%
7 68
 
6.8%
6 68
 
6.8%
8 66
 
6.6%
9 65
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
33.3%
T 1
 
11.1%
P 1
 
11.1%
B 1
 
11.1%
C 1
 
11.1%
S 1
 
11.1%
D 1
 
11.1%
Space Separator
ValueCountFrequency (%)
808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2705
57.8%
Common 1965
42.0%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 303
11.2%
평 257
 
9.5%
천 222
 
8.2%
동 209
 
7.7%
인 194
 
7.2%
역 193
 
7.1%
구 193
 
7.1%
시 191
 
7.1%
광 188
 
7.0%
산 57
 
2.1%
Other values (140) 698
25.8%
Common
ValueCountFrequency (%)
808
41.1%
1 276
 
14.0%
- 154
 
7.8%
4 110
 
5.6%
2 98
 
5.0%
0 90
 
4.6%
3 86
 
4.4%
5 69
 
3.5%
7 68
 
3.5%
6 68
 
3.5%
Other values (5) 138
 
7.0%
Latin
ValueCountFrequency (%)
A 3
33.3%
T 1
 
11.1%
P 1
 
11.1%
B 1
 
11.1%
C 1
 
11.1%
S 1
 
11.1%
D 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2705
57.8%
ASCII 1974
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
808
40.9%
1 276
 
14.0%
- 154
 
7.8%
4 110
 
5.6%
2 98
 
5.0%
0 90
 
4.6%
3 86
 
4.4%
5 69
 
3.5%
7 68
 
3.4%
6 68
 
3.4%
Other values (12) 147
 
7.4%
Hangul
ValueCountFrequency (%)
부 303
11.2%
평 257
 
9.5%
천 222
 
8.2%
동 209
 
7.7%
인 194
 
7.2%
역 193
 
7.1%
구 193
 
7.1%
시 191
 
7.1%
광 188
 
7.0%
산 57
 
2.1%
Other values (140) 698
25.8%

소재지전화
Text

MISSING 

Distinct86
Distinct (%)88.7%
Missing90
Missing (%)48.1%
Memory size1.6 KiB
2023-12-13T02:53:02.535113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.051546
Min length12

Characters and Unicode

Total characters1169
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)85.6%

Sample

1st row032-511-3311
2nd row032-435-4387
3rd row032-501-6094
4th row032-270-3600
5th row032-525-7076
ValueCountFrequency (%)
032-517-6720 9
 
9.3%
070-7092-7037 3
 
3.1%
032-519-6441 2
 
2.1%
032-433-4555 1
 
1.0%
032-506-7989 1
 
1.0%
032-524-5909 1
 
1.0%
032-504-1840 1
 
1.0%
032-527-7104 1
 
1.0%
032-571-1121 1
 
1.0%
032-505-0576 1
 
1.0%
Other values (76) 76
78.4%
2023-12-13T02:53:02.954154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 194
16.6%
0 189
16.2%
2 176
15.1%
3 143
12.2%
5 110
9.4%
7 85
7.3%
1 81
6.9%
6 60
 
5.1%
4 54
 
4.6%
8 40
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 975
83.4%
Dash Punctuation 194
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 189
19.4%
2 176
18.1%
3 143
14.7%
5 110
11.3%
7 85
8.7%
1 81
8.3%
6 60
 
6.2%
4 54
 
5.5%
8 40
 
4.1%
9 37
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1169
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 194
16.6%
0 189
16.2%
2 176
15.1%
3 143
12.2%
5 110
9.4%
7 85
7.3%
1 81
6.9%
6 60
 
5.1%
4 54
 
4.6%
8 40
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 194
16.6%
0 189
16.2%
2 176
15.1%
3 143
12.2%
5 110
9.4%
7 85
7.3%
1 81
6.9%
6 60
 
5.1%
4 54
 
4.6%
8 40
 
3.4%

Missing values

2023-12-13T02:52:58.938890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:52:59.068344image/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.
2023-12-13T02:52:59.169164image/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

업종명업소명소재지(도로명)소재지(지번)소재지전화
0식품자동판매기영업노인복지회관자판기인천광역시 부평구 굴포로 114 3층 (삼산동 노인복지회관)인천광역시 부평구 삼산동 441-2 노인복지회관 3층032-511-3311
1식품자동판매기영업상아하이마트인천광역시 부평구 아트센터로74번길 91 (십정동)인천광역시 부평구 십정동 584-7032-435-4387
2식품자동판매기영업이마트24 부평테크시티점인천광역시 부평구 부평대로 293 부평테크시티 107-1호 (청천동)인천광역시 부평구 청천동 425-4 부평테크시티 107-1호<NA>
3식품자동판매기영업돼지슈퍼인천광역시 부평구 평천로306번길 7 (갈산동)인천광역시 부평구 갈산동 172-1032-501-6094
4식품자동판매기영업한국마사회인천광역시 부평구 장제로 54 (부평동)인천광역시 부평구 부평동 161-3032-270-3600
5식품자동판매기영업세븐일레븐 동암대우빌점B인천광역시 부평구 열우물로 18 (십정동 동암역 대우마이빌 108호 일부)인천광역시 부평구 십정동 408-48 동암역 대우마이빌 108호 일부<NA>
6식품자동판매기영업GS25부평공원점<NA>인천광역시 부평구 부평동 773-51 1층032-525-7076
7식품자동판매기영업세븐일레븐 부평동암점인천광역시 부평구 동암남로 7-1 1층 일부호 (십정동)인천광역시 부평구 십정동 516-4 1층 일부<NA>
8식품자동판매기영업재일설비인천광역시 부평구 충선로 191 (부개동)인천광역시 부평구 부개동 477-3032-362-9000
9식품자동판매기영업카페 포스트인천광역시 부평구 체육관로 27 B동 1층 101-1호 (삼산동 삼산타운)인천광역시 부평구 삼산동 453-1 삼산타운<NA>
업종명업소명소재지(도로명)소재지(지번)소재지전화
177식품자동판매기영업씨유 부개중앙점인천광역시 부평구 마분로19번길 3 1층 일부호 (부개동)인천광역시 부평구 부개동 387-2<NA>
178식품자동판매기영업세븐일레븐제이와이팰리스점인천광역시 부평구 장제로 104 101호 일부호 (부평동)인천광역시 부평구 부평동 134-13<NA>
179식품자동판매기영업세븐일레븐 인천부평로터리점인천광역시 부평구 시장로 46-1 1층 (부평동)인천광역시 부평구 부평동 150-21<NA>
180식품자동판매기영업신화슈퍼인천광역시 부평구 부흥로376번길 26 (부평동 신화슈퍼)인천광역시 부평구 부평동 167-22 신화슈퍼032-527-7963
181식품자동판매기영업씨유부평에코파인점인천광역시 부평구 광장로24번길 34 1층 102호 (부평동 에코파인)인천광역시 부평구 부평동 738-45 외3필지 에코파인 102호<NA>
182식품자동판매기영업씨유삼산해피점인천광역시 부평구 부평북로 467 삼산주공미래타운아파트 상가동 1층 101호 (삼산동)인천광역시 부평구 삼산동 390-9 삼산주공미래타운아파트 상가동 101호<NA>
183식품자동판매기영업우리슈퍼인천광역시 부평구 세월천로40번길 45 (청천동)인천광역시 부평구 청천동 178-22032-527-1284
184식품자동판매기영업편의점씨유인천광역시 부평구 길주로 510 1층 (청천동)인천광역시 부평구 청천동 302 1층<NA>
185식품자동판매기영업인천세븐일레븐부평대로점인천광역시 부평구 부평대로 128 1층 101호 (부평동)인천광역시 부평구 부평동 431-42 1층 101호<NA>
186식품자동판매기영업GS25동암북부점인천광역시 부평구 동암광장로14번길 7 1층 (십정동)인천광역시 부평구 십정동 402-58 1층032-423-1688