Overview

Dataset statistics

Number of variables5
Number of observations406
Missing cells188
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory40.3 B

Variable types

Categorical1
Text4

Dataset

Description부산광역시 북구 관내에 존재하는 즉석판매제조가공업 현황 데이터로 업소명, 도로명주소, 지번주소, 전화번호 등의 항목을 제공합니다.
Author부산광역시 북구
URLhttps://www.data.go.kr/data/3069439/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 186 (45.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 15:07:30.826229
Analysis finished2023-12-12 15:07:31.680660
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
즉석판매제조가공업
406 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 406
100.0%

Length

2023-12-13T00:07:31.729650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:07:31.805929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 406
100.0%

업소명
Text

Distinct393
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T00:07:32.024304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length5.8842365
Min length2

Characters and Unicode

Total characters2389
Distinct characters406
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)93.8%

Sample

1st row창녕상회
2nd row구포떡방앗간
3rd row제일떡방앗간
4th row밀양상회
5th row우리상회
ValueCountFrequency (%)
푸름유통 3
 
0.7%
주식회사 3
 
0.7%
롯데쇼핑(주)롯데마트화명점 2
 
0.5%
다원푸드 2
 
0.5%
남동수산 2
 
0.5%
만덕점 2
 
0.5%
의성상회 2
 
0.5%
신마트 2
 
0.5%
롯데쇼핑(주 2
 
0.5%
제일상회 2
 
0.5%
Other values (416) 422
95.0%
2023-12-13T00:07:32.381357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
떡 59
 
2.5%
원 50
 
2.1%
방 47
 
2.0%
간 44
 
1.8%
앗 43
 
1.8%
점 41
 
1.7%
38
 
1.6%
산 38
 
1.6%
) 36
 
1.5%
회 36
 
1.5%
Other values (396) 1957
81.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2181
91.3%
Lowercase Letter 53
 
2.2%
Space Separator 38
 
1.6%
Close Punctuation 36
 
1.5%
Open Punctuation 35
 
1.5%
Uppercase Letter 23
 
1.0%
Decimal Number 12
 
0.5%
Other Punctuation 10
 
0.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
떡 59
 
2.7%
원 50
 
2.3%
방 47
 
2.2%
간 44
 
2.0%
앗 43
 
2.0%
점 41
 
1.9%
산 38
 
1.7%
회 36
 
1.7%
강 32
 
1.5%
상 32
 
1.5%
Other values (350) 1759
80.7%
Lowercase Letter
ValueCountFrequency (%)
e 15
28.3%
a 5
 
9.4%
r 4
 
7.5%
s 4
 
7.5%
t 4
 
7.5%
l 4
 
7.5%
o 3
 
5.7%
h 2
 
3.8%
b 2
 
3.8%
n 2
 
3.8%
Other values (7) 8
15.1%
Uppercase Letter
ValueCountFrequency (%)
A 3
13.0%
S 3
13.0%
D 3
13.0%
J 2
8.7%
T 2
8.7%
B 2
8.7%
L 2
8.7%
V 1
 
4.3%
E 1
 
4.3%
Y 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
1 2
16.7%
3 2
16.7%
6 2
16.7%
5 2
16.7%
2 1
8.3%
4 1
8.3%
9 1
8.3%
8 1
8.3%
Other Punctuation
ValueCountFrequency (%)
: 3
30.0%
. 3
30.0%
' 3
30.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2180
91.3%
Common 132
 
5.5%
Latin 76
 
3.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
떡 59
 
2.7%
원 50
 
2.3%
방 47
 
2.2%
간 44
 
2.0%
앗 43
 
2.0%
점 41
 
1.9%
산 38
 
1.7%
회 36
 
1.7%
강 32
 
1.5%
상 32
 
1.5%
Other values (349) 1758
80.6%
Latin
ValueCountFrequency (%)
e 15
19.7%
a 5
 
6.6%
r 4
 
5.3%
s 4
 
5.3%
t 4
 
5.3%
l 4
 
5.3%
A 3
 
3.9%
S 3
 
3.9%
o 3
 
3.9%
D 3
 
3.9%
Other values (20) 28
36.8%
Common
ValueCountFrequency (%)
38
28.8%
) 36
27.3%
( 35
26.5%
: 3
 
2.3%
. 3
 
2.3%
' 3
 
2.3%
1 2
 
1.5%
3 2
 
1.5%
6 2
 
1.5%
5 2
 
1.5%
Other values (6) 6
 
4.5%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2180
91.3%
ASCII 208
 
8.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
떡 59
 
2.7%
원 50
 
2.3%
방 47
 
2.2%
간 44
 
2.0%
앗 43
 
2.0%
점 41
 
1.9%
산 38
 
1.7%
회 36
 
1.7%
강 32
 
1.5%
상 32
 
1.5%
Other values (349) 1758
80.6%
ASCII
ValueCountFrequency (%)
38
18.3%
) 36
17.3%
( 35
16.8%
e 15
 
7.2%
a 5
 
2.4%
r 4
 
1.9%
s 4
 
1.9%
t 4
 
1.9%
l 4
 
1.9%
A 3
 
1.4%
Other values (36) 60
28.8%
CJK
ValueCountFrequency (%)
內 1
100.0%

소재지(도로명)
Text

Distinct382
Distinct (%)94.6%
Missing2
Missing (%)0.5%
Memory size3.3 KiB
2023-12-13T00:07:32.632727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length31.457921
Min length20

Characters and Unicode

Total characters12709
Distinct characters210
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique367 ?
Unique (%)90.8%

Sample

1st row부산광역시 북구 낙동대로1776번길 53 (구포동)
2nd row부산광역시 북구 낙동대로1762번가길 35 (구포동)
3rd row부산광역시 북구 구포시장4길 7-1 (구포동)
4th row부산광역시 북구 구포시장5길 14 (구포동)
5th row부산광역시 북구 만덕대로78번길 22 (덕천동)
ValueCountFrequency (%)
부산광역시 404
 
16.0%
북구 404
 
16.0%
1층 135
 
5.4%
구포동 131
 
5.2%
화명동 91
 
3.6%
만덕동 63
 
2.5%
덕천동 56
 
2.2%
금곡동 50
 
2.0%
금곡대로 49
 
1.9%
상가동 22
 
0.9%
Other values (504) 1113
44.2%
2023-12-13T00:07:33.043078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2114
 
16.6%
1 609
 
4.8%
구 576
 
4.5%
동 523
 
4.1%
시 477
 
3.8%
산 428
 
3.4%
부 421
 
3.3%
( 411
 
3.2%
) 411
 
3.2%
북 409
 
3.2%
Other values (200) 6330
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7303
57.5%
Space Separator 2114
 
16.6%
Decimal Number 2058
 
16.2%
Open Punctuation 411
 
3.2%
Close Punctuation 411
 
3.2%
Other Punctuation 343
 
2.7%
Dash Punctuation 47
 
0.4%
Uppercase Letter 20
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 576
 
7.9%
동 523
 
7.2%
시 477
 
6.5%
산 428
 
5.9%
부 421
 
5.8%
북 409
 
5.6%
광 405
 
5.5%
역 404
 
5.5%
로 376
 
5.1%
길 218
 
3.0%
Other values (178) 3066
42.0%
Decimal Number
ValueCountFrequency (%)
1 609
29.6%
2 301
14.6%
0 202
 
9.8%
4 170
 
8.3%
7 164
 
8.0%
3 148
 
7.2%
6 141
 
6.9%
5 121
 
5.9%
8 110
 
5.3%
9 92
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 9
45.0%
A 4
20.0%
S 2
 
10.0%
D 2
 
10.0%
G 2
 
10.0%
E 1
 
5.0%
Space Separator
ValueCountFrequency (%)
2114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 411
100.0%
Close Punctuation
ValueCountFrequency (%)
) 411
100.0%
Other Punctuation
ValueCountFrequency (%)
, 343
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7303
57.5%
Common 5386
42.4%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 576
 
7.9%
동 523
 
7.2%
시 477
 
6.5%
산 428
 
5.9%
부 421
 
5.8%
북 409
 
5.6%
광 405
 
5.5%
역 404
 
5.5%
로 376
 
5.1%
길 218
 
3.0%
Other values (178) 3066
42.0%
Common
ValueCountFrequency (%)
2114
39.2%
1 609
 
11.3%
( 411
 
7.6%
) 411
 
7.6%
, 343
 
6.4%
2 301
 
5.6%
0 202
 
3.8%
4 170
 
3.2%
7 164
 
3.0%
3 148
 
2.7%
Other values (6) 513
 
9.5%
Latin
ValueCountFrequency (%)
B 9
45.0%
A 4
20.0%
S 2
 
10.0%
D 2
 
10.0%
G 2
 
10.0%
E 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7303
57.5%
ASCII 5406
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2114
39.1%
1 609
 
11.3%
( 411
 
7.6%
) 411
 
7.6%
, 343
 
6.3%
2 301
 
5.6%
0 202
 
3.7%
4 170
 
3.1%
7 164
 
3.0%
3 148
 
2.7%
Other values (12) 533
 
9.9%
Hangul
ValueCountFrequency (%)
구 576
 
7.9%
동 523
 
7.2%
시 477
 
6.5%
산 428
 
5.9%
부 421
 
5.8%
북 409
 
5.6%
광 405
 
5.5%
역 404
 
5.5%
로 376
 
5.1%
길 218
 
3.0%
Other values (178) 3066
42.0%

소재지(지번)
Text

Distinct374
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T00:07:33.300716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length23.332512
Min length17

Characters and Unicode

Total characters9473
Distinct characters184
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)86.9%

Sample

1st row부산광역시 북구 구포동 609-6
2nd row부산광역시 북구 구포동 산 590-1
3rd row부산광역시 북구 구포동 589-77
4th row부산광역시 북구 구포동 592-4
5th row부산광역시 북구 덕천동 411-5
ValueCountFrequency (%)
부산광역시 406
21.1%
북구 406
21.1%
구포동 134
 
7.0%
화명동 99
 
5.2%
만덕동 64
 
3.3%
덕천동 56
 
2.9%
금곡동 53
 
2.8%
1층 22
 
1.1%
1874-3 19
 
1.0%
산 16
 
0.8%
Other values (479) 647
33.7%
2023-12-13T00:07:33.685380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1891
20.0%
구 541
 
5.7%
동 457
 
4.8%
1 448
 
4.7%
산 435
 
4.6%
부 415
 
4.4%
시 411
 
4.3%
광 407
 
4.3%
북 406
 
4.3%
역 406
 
4.3%
Other values (174) 3656
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5124
54.1%
Decimal Number 2079
21.9%
Space Separator 1891
 
20.0%
Dash Punctuation 352
 
3.7%
Uppercase Letter 11
 
0.1%
Close Punctuation 5
 
0.1%
Other Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 541
 
10.6%
동 457
 
8.9%
산 435
 
8.5%
부 415
 
8.1%
시 411
 
8.0%
광 407
 
7.9%
북 406
 
7.9%
역 406
 
7.9%
포 137
 
2.7%
덕 127
 
2.5%
Other values (154) 1382
27.0%
Decimal Number
ValueCountFrequency (%)
1 448
21.5%
2 274
13.2%
3 195
9.4%
9 194
9.3%
4 190
9.1%
8 176
 
8.5%
0 167
 
8.0%
5 160
 
7.7%
7 152
 
7.3%
6 123
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 7
63.6%
A 2
 
18.2%
G 1
 
9.1%
S 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1891
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5124
54.1%
Common 4338
45.8%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 541
 
10.6%
동 457
 
8.9%
산 435
 
8.5%
부 415
 
8.1%
시 411
 
8.0%
광 407
 
7.9%
북 406
 
7.9%
역 406
 
7.9%
포 137
 
2.7%
덕 127
 
2.5%
Other values (154) 1382
27.0%
Common
ValueCountFrequency (%)
1891
43.6%
1 448
 
10.3%
- 352
 
8.1%
2 274
 
6.3%
3 195
 
4.5%
9 194
 
4.5%
4 190
 
4.4%
8 176
 
4.1%
0 167
 
3.8%
5 160
 
3.7%
Other values (6) 291
 
6.7%
Latin
ValueCountFrequency (%)
B 7
63.6%
A 2
 
18.2%
G 1
 
9.1%
S 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5124
54.1%
ASCII 4349
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1891
43.5%
1 448
 
10.3%
- 352
 
8.1%
2 274
 
6.3%
3 195
 
4.5%
9 194
 
4.5%
4 190
 
4.4%
8 176
 
4.0%
0 167
 
3.8%
5 160
 
3.7%
Other values (10) 302
 
6.9%
Hangul
ValueCountFrequency (%)
구 541
 
10.6%
동 457
 
8.9%
산 435
 
8.5%
부 415
 
8.1%
시 411
 
8.0%
광 407
 
7.9%
북 406
 
7.9%
역 406
 
7.9%
포 137
 
2.7%
덕 127
 
2.5%
Other values (154) 1382
27.0%

소재지전화
Text

MISSING 

Distinct217
Distinct (%)98.6%
Missing186
Missing (%)45.8%
Memory size3.3 KiB
2023-12-13T00:07:33.969319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.413636
Min length12

Characters and Unicode

Total characters2731
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)97.3%

Sample

1st row051-332-4359
2nd row 051-332-0981
3rd row 051-333-7313
4th row051-332-9396
5th row 051-335-1552
ValueCountFrequency (%)
051-604-2500 2
 
0.9%
051-333-1413 2
 
0.9%
051-717-2950 2
 
0.9%
051-330-9000 2
 
0.9%
051-334-9292 1
 
0.5%
051-365-1211 1
 
0.5%
051-330-9088 1
 
0.5%
051-902-8585 1
 
0.5%
051-333-9175 1
 
0.5%
051-332-4359 1
 
0.5%
Other values (206) 206
93.6%
2023-12-13T00:07:34.476647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 457
16.7%
- 440
16.1%
1 351
12.9%
5 346
12.7%
0 340
12.4%
2 147
 
5.4%
4 132
 
4.8%
7 119
 
4.4%
6 116
 
4.2%
8 112
 
4.1%
Other values (2) 171
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2200
80.6%
Dash Punctuation 440
 
16.1%
Space Separator 91
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 457
20.8%
1 351
16.0%
5 346
15.7%
0 340
15.5%
2 147
 
6.7%
4 132
 
6.0%
7 119
 
5.4%
6 116
 
5.3%
8 112
 
5.1%
9 80
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 440
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2731
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 457
16.7%
- 440
16.1%
1 351
12.9%
5 346
12.7%
0 340
12.4%
2 147
 
5.4%
4 132
 
4.8%
7 119
 
4.4%
6 116
 
4.2%
8 112
 
4.1%
Other values (2) 171
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 457
16.7%
- 440
16.1%
1 351
12.9%
5 346
12.7%
0 340
12.4%
2 147
 
5.4%
4 132
 
4.8%
7 119
 
4.4%
6 116
 
4.2%
8 112
 
4.1%
Other values (2) 171
 
6.3%

Missing values

2023-12-13T00:07:31.217654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:07:31.563633image/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.
2023-12-13T00:07:31.639504image/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
0즉석판매제조가공업창녕상회부산광역시 북구 낙동대로1776번길 53 (구포동)부산광역시 북구 구포동 609-6051-332-4359
1즉석판매제조가공업구포떡방앗간부산광역시 북구 낙동대로1762번가길 35 (구포동)부산광역시 북구 구포동 산 590-1051-332-0981
2즉석판매제조가공업제일떡방앗간부산광역시 북구 구포시장4길 7-1 (구포동)부산광역시 북구 구포동 589-77051-333-7313
3즉석판매제조가공업밀양상회부산광역시 북구 구포시장5길 14 (구포동)부산광역시 북구 구포동 592-4051-332-9396
4즉석판매제조가공업우리상회부산광역시 북구 만덕대로78번길 22 (덕천동)부산광역시 북구 덕천동 411-5051-335-1552
5즉석판매제조가공업합천상회부산광역시 북구 구포시장5길 14 (구포동)부산광역시 북구 구포동 592-4051-332-3403
6즉석판매제조가공업우리상회부산광역시 북구 만덕1로 24 (만덕동)부산광역시 북구 만덕동 829-2051-332-9854
7즉석판매제조가공업대동제분소부산광역시 북구 만덕1로24번길 8 (만덕동)부산광역시 북구 만덕동 산 829051-332-3686
8즉석판매제조가공업경북상회부산광역시 북구 은행나무로 11, B동동 125호 (만덕동)부산광역시 북구 만덕동 848 B동동 125호051-334-9988
9즉석판매제조가공업대진제분소부산광역시 북구 기찰로 155 (덕천동)부산광역시 북구 덕천동 364-7051-335-1257
업종명업소명소재지(도로명)소재지(지번)소재지전화
396즉석판매제조가공업주식회사 주경에프엔비부산광역시 북구 기찰로 164 (덕천동)부산광역시 북구 덕천동 370<NA>
397즉석판매제조가공업동림유통부산광역시 북구 금곡대로 469, 농협하나로클럽 (금곡동)부산광역시 북구 금곡동 1874-3 농협하나로클럽<NA>
398즉석판매제조가공업주식회사 세연미트부산광역시 북구 금곡대로 469, 농협하나로클럽 (금곡동)부산광역시 북구 금곡동 1874-3 농협하나로클럽<NA>
399즉석판매제조가공업초코키부산광역시 북구 금곡대로 224, 동원로얄듀크 주상가동 203호 (화명동)부산광역시 북구 화명동 1150 동원로얄듀크<NA>
400즉석판매제조가공업푸름유통부산광역시 북구 금곡대로 469, 농협하나로클럽 1층 (금곡동)부산광역시 북구 금곡동 1874-3 농협하나로클럽<NA>
401즉석판매제조가공업온새미로부산광역시 북구 덕천로 188, GS슈퍼마켓 내 (만덕동)부산광역시 북구 만덕동 774-7 벽산라인아파트<NA>
402즉석판매제조가공업(주)미트벨리(지에스슈퍼-화명점 內)부산광역시 북구 대천천길 15 (화명동)부산광역시 북구 화명동 194-2055-544-0792
403즉석판매제조가공업금산인삼농업협동조합 유통사업본부부산광역시 북구 금곡대로 469, 농협하나로클럽 (금곡동)부산광역시 북구 금곡동 1874-3 농협하나로클럽041-753-3731
404즉석판매제조가공업호떡집부산광역시 북구 낙동대로1766번길 46, 1층 (구포동)부산광역시 북구 구포동 433-5<NA>
405즉석판매제조가공업코안도르제과부산광역시 북구 효열로275번길 40, 1층 (금곡동)부산광역시 북구 금곡동 66-3<NA>