Overview

Dataset statistics

Number of variables6
Number of observations96
Missing cells39
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory49.4 B

Variable types

Text5
DateTime1

Dataset

Description부산광역시_동래구_옥외광고업현황_20220825
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3079382

Alerts

영업장전화번호 has 39 (40.6%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:13:03.845416
Analysis finished2023-12-10 17:13:05.763070
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T02:13:06.193641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.5625
Min length2

Characters and Unicode

Total characters534
Distinct characters163
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

Unique96 ?
Unique (%)100.0%

Sample

1st row(주)가포
2nd row(주)대경에이앤아이
3rd row(주)대풍애드
4th row(주)더블비젼
5th row(주)마이스테이션
ValueCountFrequency (%)
주식회사 3
 
2.8%
디자인 2
 
1.9%
주)가포 1
 
0.9%
유림광고사 1
 
0.9%
우리광고 1
 
0.9%
오케이디자인광고자재 1
 
0.9%
오케이광고 1
 
0.9%
영진광고 1
 
0.9%
애드케이 1
 
0.9%
애드스타 1
 
0.9%
Other values (93) 93
87.7%
2023-12-11T02:13:07.756051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 34
 
6.4%
고 33
 
6.2%
자 18
 
3.4%
디 18
 
3.4%
인 17
 
3.2%
사 17
 
3.2%
드 17
 
3.2%
애 16
 
3.0%
주 13
 
2.4%
이 13
 
2.4%
Other values (153) 338
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 469
87.8%
Uppercase Letter 25
 
4.7%
Open Punctuation 12
 
2.2%
Close Punctuation 12
 
2.2%
Space Separator 10
 
1.9%
Lowercase Letter 4
 
0.7%
Other Punctuation 1
 
0.2%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 34
 
7.2%
고 33
 
7.0%
자 18
 
3.8%
디 18
 
3.8%
인 17
 
3.6%
사 17
 
3.6%
드 17
 
3.6%
애 16
 
3.4%
주 13
 
2.8%
이 13
 
2.8%
Other values (131) 273
58.2%
Uppercase Letter
ValueCountFrequency (%)
D 4
16.0%
E 3
12.0%
N 3
12.0%
P 2
8.0%
S 2
8.0%
G 2
8.0%
L 2
8.0%
I 2
8.0%
T 1
 
4.0%
O 1
 
4.0%
Other values (3) 3
12.0%
Lowercase Letter
ValueCountFrequency (%)
p 1
25.0%
o 1
25.0%
h 1
25.0%
s 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 469
87.8%
Common 36
 
6.7%
Latin 29
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 34
 
7.2%
고 33
 
7.0%
자 18
 
3.8%
디 18
 
3.8%
인 17
 
3.6%
사 17
 
3.6%
드 17
 
3.6%
애 16
 
3.4%
주 13
 
2.8%
이 13
 
2.8%
Other values (131) 273
58.2%
Latin
ValueCountFrequency (%)
D 4
13.8%
E 3
10.3%
N 3
10.3%
P 2
 
6.9%
S 2
 
6.9%
G 2
 
6.9%
L 2
 
6.9%
I 2
 
6.9%
T 1
 
3.4%
O 1
 
3.4%
Other values (7) 7
24.1%
Common
ValueCountFrequency (%)
( 12
33.3%
) 12
33.3%
10
27.8%
: 1
 
2.8%
+ 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 469
87.8%
ASCII 65
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 34
 
7.2%
고 33
 
7.0%
자 18
 
3.8%
디 18
 
3.8%
인 17
 
3.6%
사 17
 
3.6%
드 17
 
3.6%
애 16
 
3.4%
주 13
 
2.8%
이 13
 
2.8%
Other values (131) 273
58.2%
ASCII
ValueCountFrequency (%)
( 12
18.5%
) 12
18.5%
10
15.4%
D 4
 
6.2%
E 3
 
4.6%
N 3
 
4.6%
P 2
 
3.1%
S 2
 
3.1%
G 2
 
3.1%
L 2
 
3.1%
Other values (12) 13
20.0%

대표자명
Text

Distinct95
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T02:13:08.529972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9791667
Min length2

Characters and Unicode

Total characters286
Distinct characters106
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)97.9%

Sample

1st row김인규
2nd row김봉구
3rd row강명석
4th row문원주
5th row허재호
ValueCountFrequency (%)
이종진 2
 
2.1%
변희대 1
 
1.0%
최경완 1
 
1.0%
유영욱 1
 
1.0%
홍석열 1
 
1.0%
차장길 1
 
1.0%
박균배 1
 
1.0%
황원규 1
 
1.0%
배용국 1
 
1.0%
김창대 1
 
1.0%
Other values (85) 85
88.5%
2023-12-11T02:13:09.356180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 25
 
8.7%
이 11
 
3.8%
영 10
 
3.5%
호 10
 
3.5%
박 9
 
3.1%
진 8
 
2.8%
강 6
 
2.1%
경 6
 
2.1%
규 6
 
2.1%
성 5
 
1.7%
Other values (96) 190
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 25
 
8.7%
이 11
 
3.8%
영 10
 
3.5%
호 10
 
3.5%
박 9
 
3.1%
진 8
 
2.8%
강 6
 
2.1%
경 6
 
2.1%
규 6
 
2.1%
성 5
 
1.7%
Other values (96) 190
66.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 25
 
8.7%
이 11
 
3.8%
영 10
 
3.5%
호 10
 
3.5%
박 9
 
3.1%
진 8
 
2.8%
강 6
 
2.1%
경 6
 
2.1%
규 6
 
2.1%
성 5
 
1.7%
Other values (96) 190
66.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 25
 
8.7%
이 11
 
3.8%
영 10
 
3.5%
호 10
 
3.5%
박 9
 
3.1%
진 8
 
2.8%
강 6
 
2.1%
경 6
 
2.1%
규 6
 
2.1%
성 5
 
1.7%
Other values (96) 190
66.4%

영업장전화번호
Text

MISSING 

Distinct57
Distinct (%)100.0%
Missing39
Missing (%)40.6%
Memory size900.0 B
2023-12-11T02:13:09.828012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters684
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

Unique57 ?
Unique (%)100.0%

Sample

1st row051-505-6191
2nd row051-634-0393
3rd row051-751-0583
4th row051-851-1515
5th row051-506-1222
ValueCountFrequency (%)
051-502-2202 1
 
1.8%
051-558-3410 1
 
1.8%
051-553-2567 1
 
1.8%
051-505-3806 1
 
1.8%
051-501-8453 1
 
1.8%
051-502-1537 1
 
1.8%
051-552-2323 1
 
1.8%
051-526-3305 1
 
1.8%
051-554-3868 1
 
1.8%
051-553-1805 1
 
1.8%
Other values (47) 47
82.5%
2023-12-11T02:13:10.582312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 152
22.2%
- 114
16.7%
0 98
14.3%
1 87
12.7%
3 54
 
7.9%
2 48
 
7.0%
7 32
 
4.7%
4 30
 
4.4%
6 28
 
4.1%
8 25
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570
83.3%
Dash Punctuation 114
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 152
26.7%
0 98
17.2%
1 87
15.3%
3 54
 
9.5%
2 48
 
8.4%
7 32
 
5.6%
4 30
 
5.3%
6 28
 
4.9%
8 25
 
4.4%
9 16
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 684
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 152
22.2%
- 114
16.7%
0 98
14.3%
1 87
12.7%
3 54
 
7.9%
2 48
 
7.0%
7 32
 
4.7%
4 30
 
4.4%
6 28
 
4.1%
8 25
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 152
22.2%
- 114
16.7%
0 98
14.3%
1 87
12.7%
3 54
 
7.9%
2 48
 
7.0%
7 32
 
4.7%
4 30
 
4.4%
6 28
 
4.1%
8 25
 
3.7%

영업장도로명주소
Text

Distinct93
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T02:13:11.367242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length28.78125
Min length22

Characters and Unicode

Total characters2763
Distinct characters106
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

Unique90 ?
Unique (%)93.8%

Sample

1st row부산광역시 동래구 미남로132번길 104 (온천동)
2nd row부산광역시 동래구 연안로64번길 34 (안락동)
3rd row부산광역시 동래구 온천천로531번길 58 (안락동)
4th row부산광역시 동래구 중앙대로 1291-1, 상주빌딩 3층 (사직동)
5th row부산광역시 동래구 온천천로 551, 3층 (안락동)
ValueCountFrequency (%)
부산광역시 96
 
17.9%
동래구 96
 
17.9%
안락동 24
 
4.5%
사직동 24
 
4.5%
온천동 17
 
3.2%
명장동 10
 
1.9%
수안동 8
 
1.5%
명륜동 7
 
1.3%
2층 6
 
1.1%
중앙대로1267번길 5
 
0.9%
Other values (179) 242
45.2%
2023-12-11T02:13:12.464553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
 
16.0%
동 202
 
7.3%
시 100
 
3.6%
래 98
 
3.5%
산 97
 
3.5%
부 96
 
3.5%
로 96
 
3.5%
) 96
 
3.5%
( 96
 
3.5%
역 96
 
3.5%
Other values (96) 1344
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1623
58.7%
Decimal Number 443
 
16.0%
Space Separator 442
 
16.0%
Close Punctuation 96
 
3.5%
Open Punctuation 96
 
3.5%
Other Punctuation 40
 
1.4%
Dash Punctuation 19
 
0.7%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 202
 
12.4%
시 100
 
6.2%
래 98
 
6.0%
산 97
 
6.0%
부 96
 
5.9%
로 96
 
5.9%
역 96
 
5.9%
구 96
 
5.9%
광 96
 
5.9%
길 52
 
3.2%
Other values (80) 594
36.6%
Decimal Number
ValueCountFrequency (%)
1 94
21.2%
2 79
17.8%
3 51
11.5%
5 46
10.4%
4 42
9.5%
6 33
 
7.4%
8 28
 
6.3%
0 24
 
5.4%
7 24
 
5.4%
9 22
 
5.0%
Space Separator
ValueCountFrequency (%)
442
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Other Punctuation
ValueCountFrequency (%)
, 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1623
58.7%
Common 1136
41.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 202
 
12.4%
시 100
 
6.2%
래 98
 
6.0%
산 97
 
6.0%
부 96
 
5.9%
로 96
 
5.9%
역 96
 
5.9%
구 96
 
5.9%
광 96
 
5.9%
길 52
 
3.2%
Other values (80) 594
36.6%
Common
ValueCountFrequency (%)
442
38.9%
) 96
 
8.5%
( 96
 
8.5%
1 94
 
8.3%
2 79
 
7.0%
3 51
 
4.5%
5 46
 
4.0%
4 42
 
3.7%
, 40
 
3.5%
6 33
 
2.9%
Other values (5) 117
 
10.3%
Latin
ValueCountFrequency (%)
A 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1623
58.7%
ASCII 1140
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
38.8%
) 96
 
8.4%
( 96
 
8.4%
1 94
 
8.2%
2 79
 
6.9%
3 51
 
4.5%
5 46
 
4.0%
4 42
 
3.7%
, 40
 
3.5%
6 33
 
2.9%
Other values (6) 121
 
10.6%
Hangul
ValueCountFrequency (%)
동 202
 
12.4%
시 100
 
6.2%
래 98
 
6.0%
산 97
 
6.0%
부 96
 
5.9%
로 96
 
5.9%
역 96
 
5.9%
구 96
 
5.9%
광 96
 
5.9%
길 52
 
3.2%
Other values (80) 594
36.6%

영업내용
Text

Distinct50
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T02:13:12.970001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length8.2083333
Min length2

Characters and Unicode

Total characters788
Distinct characters64
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)37.5%

Sample

1st row광고물제작
2nd row광고대행, 인테리어
3rd row옥외광고물제작
4th row광고물 제작, 디자인
5th row전시·기획, 옥외광고, 인테리어, 편집, 인쇄, 제조
ValueCountFrequency (%)
제작 22
 
12.4%
광고물제작 17
 
9.6%
및 12
 
6.7%
옥외광고물등제작 12
 
6.7%
간판 10
 
5.6%
간판제작 9
 
5.1%
옥외광고물 8
 
4.5%
광고물 8
 
4.5%
옥외광고 7
 
3.9%
옥외광고물제작 7
 
3.9%
Other values (43) 66
37.1%
2023-12-11T02:13:13.731359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 83
10.5%
고 82
10.4%
82
10.4%
제 78
9.9%
작 73
 
9.3%
물 59
 
7.5%
옥 43
 
5.5%
외 43
 
5.5%
판 27
 
3.4%
간 24
 
3.0%
Other values (54) 194
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 678
86.0%
Space Separator 82
 
10.4%
Other Punctuation 22
 
2.8%
Uppercase Letter 6
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 83
12.2%
고 82
12.1%
제 78
11.5%
작 73
10.8%
물 59
 
8.7%
옥 43
 
6.3%
외 43
 
6.3%
판 27
 
4.0%
간 24
 
3.5%
등 15
 
2.2%
Other values (48) 151
22.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
33.3%
E 2
33.3%
L 2
33.3%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
· 1
 
4.5%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 678
86.0%
Common 104
 
13.2%
Latin 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 83
12.2%
고 82
12.1%
제 78
11.5%
작 73
10.8%
물 59
 
8.7%
옥 43
 
6.3%
외 43
 
6.3%
판 27
 
4.0%
간 24
 
3.5%
등 15
 
2.2%
Other values (48) 151
22.3%
Common
ValueCountFrequency (%)
82
78.8%
, 21
 
20.2%
· 1
 
1.0%
Latin
ValueCountFrequency (%)
D 2
33.3%
E 2
33.3%
L 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 678
86.0%
ASCII 109
 
13.8%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 83
12.2%
고 82
12.1%
제 78
11.5%
작 73
10.8%
물 59
 
8.7%
옥 43
 
6.3%
외 43
 
6.3%
판 27
 
4.0%
간 24
 
3.5%
등 15
 
2.2%
Other values (48) 151
22.3%
ASCII
ValueCountFrequency (%)
82
75.2%
, 21
 
19.3%
D 2
 
1.8%
E 2
 
1.8%
L 2
 
1.8%
None
ValueCountFrequency (%)
· 1
100.0%

등록일
Date

Distinct92
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size900.0 B
Minimum1988-03-10 00:00:00
Maximum2022-08-05 00:00:00
2023-12-11T02:13:14.062435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:13:14.414980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-11T02:13:14.645052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명대표자명영업장전화번호영업장도로명주소영업내용등록일
업소명1.0001.0001.0001.0001.0001.000
대표자명1.0001.0001.0000.9970.9980.997
영업장전화번호1.0001.0001.0001.0001.0001.000
영업장도로명주소1.0000.9971.0001.0000.0000.982
영업내용1.0000.9981.0000.0001.0000.977
등록일1.0000.9971.0000.9820.9771.000

Missing values

2023-12-11T02:13:05.497896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:13:05.691230image/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

업소명대표자명영업장전화번호영업장도로명주소영업내용등록일
0(주)가포김인규051-505-6191부산광역시 동래구 미남로132번길 104 (온천동)광고물제작2007-07-25
1(주)대경에이앤아이김봉구<NA>부산광역시 동래구 연안로64번길 34 (안락동)광고대행, 인테리어2022-04-01
2(주)대풍애드강명석051-634-0393부산광역시 동래구 온천천로531번길 58 (안락동)옥외광고물제작2020-11-06
3(주)더블비젼문원주<NA>부산광역시 동래구 중앙대로 1291-1, 상주빌딩 3층 (사직동)광고물 제작, 디자인2021-02-02
4(주)마이스테이션허재호<NA>부산광역시 동래구 온천천로 551, 3층 (안락동)전시·기획, 옥외광고, 인테리어, 편집, 인쇄, 제조2022-03-04
5(주)애드앤서번국051-751-0583부산광역시 동래구 온천천로531번길 58, A동 1호 (안락동)옥외광고물제작및설치2011-09-28
6(주)어반플레닝김창균<NA>부산광역시 동래구 충렬대로 312, 2층 (낙민동)옥외광고업2021-04-19
7(주)온오프디자인송원영<NA>부산광역시 동래구 중앙대로1267번길 80, 2층 (사직동)옥외간판 제조업2019-11-05
8(주)지앤비조기범051-851-1515부산광역시 동래구 여고로 50 (사직동)광고물 제작 및 광고 대행2009-08-27
9(주)하이플랜권지성051-506-1222부산광역시 동래구 아시아드대로 258-1, 5층 5호 (온천동)미술디자인,디자인제품,도시환경디자인2016-07-14
업소명대표자명영업장전화번호영업장도로명주소영업내용등록일
86피앤비김태관<NA>부산광역시 동래구 명안로26번길 90, 2층 (안락동)옥외광고물 제작2021-05-03
87필광고기획한영순051-554-8333부산광역시 동래구 충렬대로446번길 27 (안락동)인쇄 및 간판광고물제작2013-10-14
88하나광고허남구051-557-4343부산광역시 동래구 충렬대로245번길 15 (수안동)광고물제작2021-01-10
89한국비젼윤진오051-503-2394부산광역시 동래구 미남로 95-1 (온천동)옥외광고물등제작1997-08-28
90한애드컴한성희051-752-6258부산광역시 동래구 연안로59번길 35 (안락동)간판제작2005-11-15
91한양광고김재규051-557-6013부산광역시 동래구 중앙대로1267번길 63 (사직동)간판 제작1996-04-19
92현대애드기획김태균<NA>부산광역시 동래구 연안로58번길 39 (안락동)옥외광고업 제작 및 시공2015-09-21
93현대예공사이향구051-512-5943부산광역시 동래구 충렬대로237번길 135 (명륜동)광고물제작1988-03-14
94호:아라이영주<NA>부산광역시 동래구 충렬대로 245, 4층 (수안동)광고대행업, 전문디자인2022-02-10
95효성광고공사박훈051-556-4033부산광역시 동래구 명륜로 144 (명륜동)간판 및 광고물2005-07-20