Overview

Dataset statistics

Number of variables5
Number of observations410
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Text4

Dataset

Description부산광역시 영도구 담배소매인 지정현황인 연번, 업소명, 업소지번주소, 업소도로명 주소, 지정일자 등 데이터를 제공합니다. (상호명, 주소 등)
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/15021212/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:19:02.167410
Analysis finished2023-12-12 06:19:03.067854
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205.5
Minimum1
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-12T15:19:03.249314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.45
Q1103.25
median205.5
Q3307.75
95-th percentile389.55
Maximum410
Range409
Interquartile range (IQR)204.5

Descriptive statistics

Standard deviation118.50105
Coefficient of variation (CV)0.57664747
Kurtosis-1.2
Mean205.5
Median Absolute Deviation (MAD)102.5
Skewness0
Sum84255
Variance14042.5
MonotonicityStrictly increasing
2023-12-12T15:19:03.607348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
271 1
 
0.2%
281 1
 
0.2%
280 1
 
0.2%
279 1
 
0.2%
278 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
Other values (400) 400
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
410 1
0.2%
409 1
0.2%
408 1
0.2%
407 1
0.2%
406 1
0.2%
405 1
0.2%
404 1
0.2%
403 1
0.2%
402 1
0.2%
401 1
0.2%

업소명
Text

Distinct291
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-12T15:19:04.037994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length5.8341463
Min length2

Characters and Unicode

Total characters2392
Distinct characters321
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique281 ?
Unique (%)68.5%

Sample

1st row햇님이네
2nd row헤니츠
3rd row소셜컴바인
4th row지에스(GS)25 영도남항점
5th row카페슈가
ValueCountFrequency (%)
없 103
 
16.7%
음 103
 
16.7%
씨유 21
 
3.4%
없음 10
 
1.6%
gs25 7
 
1.1%
세븐일레븐 7
 
1.1%
지에스(gs)25 6
 
1.0%
이마트24 4
 
0.6%
주)코리아세븐 3
 
0.5%
한국해양대학교 3
 
0.5%
Other values (324) 349
56.7%
2023-12-12T15:19:04.626257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
206
 
8.6%
음 115
 
4.8%
없 114
 
4.8%
점 89
 
3.7%
영 81
 
3.4%
트 71
 
3.0%
마 70
 
2.9%
도 68
 
2.8%
회 39
 
1.6%
상 37
 
1.5%
Other values (311) 1502
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1996
83.4%
Space Separator 206
 
8.6%
Decimal Number 65
 
2.7%
Uppercase Letter 64
 
2.7%
Open Punctuation 25
 
1.0%
Close Punctuation 25
 
1.0%
Lowercase Letter 8
 
0.3%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 115
 
5.8%
없 114
 
5.7%
점 89
 
4.5%
영 81
 
4.1%
트 71
 
3.6%
마 70
 
3.5%
도 68
 
3.4%
회 39
 
2.0%
상 37
 
1.9%
퍼 34
 
1.7%
Other values (274) 1278
64.0%
Uppercase Letter
ValueCountFrequency (%)
G 18
28.1%
S 18
28.1%
C 6
 
9.4%
U 3
 
4.7%
I 2
 
3.1%
L 2
 
3.1%
D 2
 
3.1%
O 2
 
3.1%
A 1
 
1.6%
N 1
 
1.6%
Other values (9) 9
14.1%
Decimal Number
ValueCountFrequency (%)
2 30
46.2%
5 25
38.5%
4 4
 
6.2%
1 3
 
4.6%
8 2
 
3.1%
3 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
e 2
25.0%
h 1
12.5%
a 1
12.5%
m 1
12.5%
f 1
12.5%
Space Separator
ValueCountFrequency (%)
206
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1997
83.5%
Common 323
 
13.5%
Latin 72
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 115
 
5.8%
없 114
 
5.7%
점 89
 
4.5%
영 81
 
4.1%
트 71
 
3.6%
마 70
 
3.5%
도 68
 
3.4%
회 39
 
2.0%
상 37
 
1.9%
퍼 34
 
1.7%
Other values (275) 1279
64.0%
Latin
ValueCountFrequency (%)
G 18
25.0%
S 18
25.0%
C 6
 
8.3%
U 3
 
4.2%
o 2
 
2.8%
e 2
 
2.8%
I 2
 
2.8%
L 2
 
2.8%
D 2
 
2.8%
O 2
 
2.8%
Other values (15) 15
20.8%
Common
ValueCountFrequency (%)
206
63.8%
2 30
 
9.3%
( 25
 
7.7%
5 25
 
7.7%
) 25
 
7.7%
4 4
 
1.2%
1 3
 
0.9%
8 2
 
0.6%
3 1
 
0.3%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1996
83.4%
ASCII 395
 
16.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
206
52.2%
2 30
 
7.6%
( 25
 
6.3%
5 25
 
6.3%
) 25
 
6.3%
G 18
 
4.6%
S 18
 
4.6%
C 6
 
1.5%
4 4
 
1.0%
U 3
 
0.8%
Other values (26) 35
 
8.9%
Hangul
ValueCountFrequency (%)
음 115
 
5.8%
없 114
 
5.7%
점 89
 
4.5%
영 81
 
4.1%
트 71
 
3.6%
마 70
 
3.5%
도 68
 
3.4%
회 39
 
2.0%
상 37
 
1.9%
퍼 34
 
1.7%
Other values (274) 1278
64.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업소지번주소
Text

Distinct381
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-12T15:19:05.274700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length23.12439
Min length1

Characters and Unicode

Total characters9481
Distinct characters184
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

Unique373 ?
Unique (%)91.0%

Sample

1st row부산광역시 영도구 봉래동4가 158-27
2nd row부산광역시 영도구 봉래동3가 61-1
3rd row부산광역시 영도구 대교동1가 29-2
4th row부산광역시 영도구 영선동3가 56-6
5th row부산광역시 영도구 봉래동3가 181-2
ValueCountFrequency (%)
부산광역시 389
20.4%
영도구 389
20.4%
동삼동 88
 
4.6%
청학동 61
 
3.2%
1호 27
 
1.4%
호 20
 
1.1%
남항동1가 18
 
0.9%
남항동2가 16
 
0.8%
봉래동4가 16
 
0.8%
영선동3가 15
 
0.8%
Other values (523) 864
45.4%
2023-12-12T15:19:05.763689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1726
18.2%
동 506
 
5.3%
1 476
 
5.0%
영 443
 
4.7%
산 399
 
4.2%
도 397
 
4.2%
부 393
 
4.1%
구 391
 
4.1%
시 389
 
4.1%
역 389
 
4.1%
Other values (174) 3972
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5771
60.9%
Decimal Number 1825
 
19.2%
Space Separator 1726
 
18.2%
Dash Punctuation 139
 
1.5%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Uppercase Letter 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 506
 
8.8%
영 443
 
7.7%
산 399
 
6.9%
도 397
 
6.9%
부 393
 
6.8%
구 391
 
6.8%
시 389
 
6.7%
역 389
 
6.7%
광 389
 
6.7%
호 347
 
6.0%
Other values (154) 1728
29.9%
Decimal Number
ValueCountFrequency (%)
1 476
26.1%
2 327
17.9%
3 200
11.0%
4 159
 
8.7%
5 132
 
7.2%
6 129
 
7.1%
0 118
 
6.5%
9 103
 
5.6%
7 95
 
5.2%
8 86
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
S 1
 
16.7%
D 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
1726
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5771
60.9%
Common 3704
39.1%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 506
 
8.8%
영 443
 
7.7%
산 399
 
6.9%
도 397
 
6.9%
부 393
 
6.8%
구 391
 
6.8%
시 389
 
6.7%
역 389
 
6.7%
광 389
 
6.7%
호 347
 
6.0%
Other values (154) 1728
29.9%
Common
ValueCountFrequency (%)
1726
46.6%
1 476
 
12.9%
2 327
 
8.8%
3 200
 
5.4%
4 159
 
4.3%
- 139
 
3.8%
5 132
 
3.6%
6 129
 
3.5%
0 118
 
3.2%
9 103
 
2.8%
Other values (6) 195
 
5.3%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
S 1
 
16.7%
D 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5771
60.9%
ASCII 3710
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1726
46.5%
1 476
 
12.8%
2 327
 
8.8%
3 200
 
5.4%
4 159
 
4.3%
- 139
 
3.7%
5 132
 
3.6%
6 129
 
3.5%
0 118
 
3.2%
9 103
 
2.8%
Other values (10) 201
 
5.4%
Hangul
ValueCountFrequency (%)
동 506
 
8.8%
영 443
 
7.7%
산 399
 
6.9%
도 397
 
6.9%
부 393
 
6.8%
구 391
 
6.8%
시 389
 
6.7%
역 389
 
6.7%
광 389
 
6.7%
호 347
 
6.0%
Other values (154) 1728
29.9%

업소도로명주소
Text

Distinct343
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-12T15:19:06.132735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length24.268293
Min length1

Characters and Unicode

Total characters9950
Distinct characters212
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

Unique335 ?
Unique (%)81.7%

Sample

1st row부산광역시 영도구 하나길 734 (봉래동4가)
2nd row부산광역시 영도구 한결길 21 (봉래동3가)
3rd row부산광역시 영도구 태종로 54-3. 1층 (대교동1가)
4th row부산광역시 영도구 남항서로70번길 101. 1층 (영선동3가)
5th row부산광역시 영도구 대교로14번길 50 (봉래동3가)
ValueCountFrequency (%)
부산광역시 349
 
18.1%
영도구 349
 
18.1%
동삼동 85
 
4.4%
청학동 66
 
3.4%
태종로 52
 
2.7%
1층 35
 
1.8%
절영로 17
 
0.9%
남항동1가 15
 
0.8%
봉래동3가 14
 
0.7%
봉래동4가 14
 
0.7%
Other values (467) 931
48.3%
2023-12-12T15:19:06.632036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1711
 
17.2%
동 497
 
5.0%
영 436
 
4.4%
산 363
 
3.6%
도 356
 
3.6%
( 353
 
3.5%
) 353
 
3.5%
광 352
 
3.5%
부 352
 
3.5%
구 351
 
3.5%
Other values (202) 4826
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5942
59.7%
Space Separator 1711
 
17.2%
Decimal Number 1415
 
14.2%
Open Punctuation 353
 
3.5%
Close Punctuation 353
 
3.5%
Other Punctuation 128
 
1.3%
Dash Punctuation 42
 
0.4%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 497
 
8.4%
영 436
 
7.3%
산 363
 
6.1%
도 356
 
6.0%
광 352
 
5.9%
부 352
 
5.9%
구 351
 
5.9%
시 350
 
5.9%
역 349
 
5.9%
로 282
 
4.7%
Other values (183) 2254
37.9%
Decimal Number
ValueCountFrequency (%)
1 348
24.6%
2 228
16.1%
3 194
13.7%
0 120
 
8.5%
4 120
 
8.5%
5 95
 
6.7%
7 89
 
6.3%
9 78
 
5.5%
6 75
 
5.3%
8 68
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
S 1
 
16.7%
D 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1711
100.0%
Open Punctuation
ValueCountFrequency (%)
( 353
100.0%
Close Punctuation
ValueCountFrequency (%)
) 353
100.0%
Other Punctuation
ValueCountFrequency (%)
. 128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5942
59.7%
Common 4002
40.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 497
 
8.4%
영 436
 
7.3%
산 363
 
6.1%
도 356
 
6.0%
광 352
 
5.9%
부 352
 
5.9%
구 351
 
5.9%
시 350
 
5.9%
역 349
 
5.9%
로 282
 
4.7%
Other values (183) 2254
37.9%
Common
ValueCountFrequency (%)
1711
42.8%
( 353
 
8.8%
) 353
 
8.8%
1 348
 
8.7%
2 228
 
5.7%
3 194
 
4.8%
. 128
 
3.2%
0 120
 
3.0%
4 120
 
3.0%
5 95
 
2.4%
Other values (5) 352
 
8.8%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
S 1
 
16.7%
D 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5942
59.7%
ASCII 4008
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1711
42.7%
( 353
 
8.8%
) 353
 
8.8%
1 348
 
8.7%
2 228
 
5.7%
3 194
 
4.8%
. 128
 
3.2%
0 120
 
3.0%
4 120
 
3.0%
5 95
 
2.4%
Other values (9) 358
 
8.9%
Hangul
ValueCountFrequency (%)
동 497
 
8.4%
영 436
 
7.3%
산 363
 
6.1%
도 356
 
6.0%
광 352
 
5.9%
부 352
 
5.9%
구 351
 
5.9%
시 350
 
5.9%
역 349
 
5.9%
로 282
 
4.7%
Other values (183) 2254
37.9%

지정일자
Text

Distinct356
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-12T15:19:06.983318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.4731707
Min length2

Characters and Unicode

Total characters3884
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique329 ?
Unique (%)80.2%

Sample

1st row2021-12-29
2nd row2021-11-11
3rd row2021-11-08
4th row2021-11-02
5th row2021-11-02
ValueCountFrequency (%)
없음 27
 
6.6%
2010-09-14 3
 
0.7%
1992-10-14 3
 
0.7%
2018-04-04 2
 
0.5%
2009-04-15 2
 
0.5%
2018-01-22 2
 
0.5%
1994-03-25 2
 
0.5%
1996-02-03 2
 
0.5%
2001-02-26 2
 
0.5%
2017-06-14 2
 
0.5%
Other values (346) 363
88.5%
2023-12-12T15:19:07.548134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 867
22.3%
- 766
19.7%
1 622
16.0%
2 591
15.2%
9 322
 
8.3%
8 136
 
3.5%
3 134
 
3.5%
4 121
 
3.1%
5 113
 
2.9%
6 92
 
2.4%
Other values (3) 120
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3064
78.9%
Dash Punctuation 766
 
19.7%
Other Letter 54
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 867
28.3%
1 622
20.3%
2 591
19.3%
9 322
 
10.5%
8 136
 
4.4%
3 134
 
4.4%
4 121
 
3.9%
5 113
 
3.7%
6 92
 
3.0%
7 66
 
2.2%
Other Letter
ValueCountFrequency (%)
없 27
50.0%
음 27
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 766
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3830
98.6%
Hangul 54
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 867
22.6%
- 766
20.0%
1 622
16.2%
2 591
15.4%
9 322
 
8.4%
8 136
 
3.6%
3 134
 
3.5%
4 121
 
3.2%
5 113
 
3.0%
6 92
 
2.4%
Hangul
ValueCountFrequency (%)
없 27
50.0%
음 27
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3830
98.6%
Hangul 54
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 867
22.6%
- 766
20.0%
1 622
16.2%
2 591
15.4%
9 322
 
8.4%
8 136
 
3.6%
3 134
 
3.5%
4 121
 
3.2%
5 113
 
3.0%
6 92
 
2.4%
Hangul
ValueCountFrequency (%)
없 27
50.0%
음 27
50.0%

Interactions

2023-12-12T15:19:02.632847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T15:19:02.781028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:19:02.984043image/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

순번업소명업소지번주소업소도로명주소지정일자
01햇님이네부산광역시 영도구 봉래동4가 158-27부산광역시 영도구 하나길 734 (봉래동4가)2021-12-29
12헤니츠부산광역시 영도구 봉래동3가 61-1부산광역시 영도구 한결길 21 (봉래동3가)2021-11-11
23소셜컴바인부산광역시 영도구 대교동1가 29-2부산광역시 영도구 태종로 54-3. 1층 (대교동1가)2021-11-08
34지에스(GS)25 영도남항점부산광역시 영도구 영선동3가 56-6부산광역시 영도구 남항서로70번길 101. 1층 (영선동3가)2021-11-02
45카페슈가부산광역시 영도구 봉래동3가 181-2부산광역시 영도구 대교로14번길 50 (봉래동3가)2021-11-02
56더좋은할인마트부산광역시 영도구 대평동1가 96부산광역시 영도구 대평로 17-1 (대평동1가)2021-08-31
67킹덤 전자담배부산광역시 영도구 대교동1가 36-4부산광역시 영도구 태종로 53-1 (대교동1가)2021-08-26
78오 맘마미야부산광역시 영도구 동삼동 231-48부산광역시 영도구 웃서발로 65-1 (동삼동)2021-08-25
89세븐일레븐 부산영선로터리점부산광역시 영도구 영선동3가 123-1부산광역시 영도구 절영로 118-2. 1층 (영선동3가)2021-08-23
910씨유 영도에뜰태양점부산광역시 영도구 봉래동4가 69-1 봉래에일린의뜰 119동 106호부산광역시 영도구 태종로 172. 봉래에일린의뜰 119동 106호 (봉래동4가)2021-07-29
순번업소명업소지번주소업소도로명주소지정일자
400401없 음부산광역시 영도구 청학동 279-2호부산광역시 영도구 청학북로15번길 17 (청학동)없음
401402없 음부산광역시 영도구 청학동 253-96호부산광역시 영도구 청학북로34번길 2 (청학동)없음
402403없 음부산광역시 영도구 봉래동5가 80-13호부산광역시 영도구 외나무길 102 (봉래동5가)없음
403404없 음부산광역시 영도구 봉래동4가 156-5호없음
404405없 음부산광역시 영도구 봉래동3가 23호없음
405406부영갈비부산광역시 영도구 봉래동3가 7-5호부산광역시 영도구 태종로113번길 23 (봉래동3가)1989-04-06
406407없 음부산광역시 영도구 봉래동2가 65호없음
407408없 음부산광역시 영도구 봉래동2가 97-13호부산광역시 영도구 대교로 32 (봉래동2가)없음
408409없 음부산광역시 영도구 봉래동1가 73-2호부산광역시 영도구 대교로 41 (봉래동1가)없음
409410없 음부산광역시 영도구 신선동3가 56호없음