Overview

Dataset statistics

Number of variables5
Number of observations254
Missing cells169
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory40.5 B

Variable types

Categorical1
Text4

Dataset

Description부산광역시_중구_건강기능식품판매업소현황_20230711
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026350

Alerts

업종명 is highly imbalanced (88.3%)Imbalance
소재지(도로명) has 12 (4.7%) missing valuesMissing
소재지전화 has 157 (61.8%) missing valuesMissing

Reproduction

Analysis started2023-12-10 17:03:29.872421
Analysis finished2023-12-10 17:03:31.114042
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
건강기능식품일반판매업
250 
건강기능식품유통전문판매업
 
4

Length

Max length13
Median length11
Mean length11.031496
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품일반판매업 250
98.4%
건강기능식품유통전문판매업 4
 
1.6%

Length

2023-12-11T02:03:31.262272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:03:31.473759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품일반판매업 250
98.4%
건강기능식품유통전문판매업 4
 
1.6%

업소명
Text

Distinct247
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T02:03:32.001705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length7.1889764
Min length2

Characters and Unicode

Total characters1826
Distinct characters380
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

Unique240 ?
Unique (%)94.5%

Sample

1st row(주)나눔의사람들
2nd row(주)태양트레이드
3rd row한국인삼공사 남포동전시판매장
4th row아모레 중구제일특약점
5th row시민자연건강
ValueCountFrequency (%)
주식회사 6
 
1.9%
광복점 3
 
0.9%
고려인삼총판 2
 
0.6%
애터미 2
 
0.6%
모닝클럽 2
 
0.6%
에스테틱 2
 
0.6%
주)에치와이 2
 
0.6%
정관장홍삼 2
 
0.6%
에이스패밀리 2
 
0.6%
부산 2
 
0.6%
Other values (290) 296
92.2%
2023-12-11T02:03:32.769030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
3.7%
이 51
 
2.8%
주 49
 
2.7%
) 48
 
2.6%
( 48
 
2.6%
스 42
 
2.3%
점 39
 
2.1%
사 32
 
1.8%
산 30
 
1.6%
리 26
 
1.4%
Other values (370) 1394
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1562
85.5%
Space Separator 67
 
3.7%
Close Punctuation 49
 
2.7%
Open Punctuation 49
 
2.7%
Uppercase Letter 48
 
2.6%
Lowercase Letter 39
 
2.1%
Decimal Number 8
 
0.4%
Other Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 51
 
3.3%
주 49
 
3.1%
스 42
 
2.7%
점 39
 
2.5%
사 32
 
2.0%
산 30
 
1.9%
리 26
 
1.7%
부 26
 
1.7%
아 25
 
1.6%
삼 19
 
1.2%
Other values (323) 1223
78.3%
Uppercase Letter
ValueCountFrequency (%)
R 5
 
10.4%
A 4
 
8.3%
K 4
 
8.3%
E 4
 
8.3%
S 4
 
8.3%
N 3
 
6.2%
M 3
 
6.2%
G 3
 
6.2%
H 3
 
6.2%
D 2
 
4.2%
Other values (8) 13
27.1%
Lowercase Letter
ValueCountFrequency (%)
o 5
12.8%
u 3
 
7.7%
a 3
 
7.7%
t 3
 
7.7%
r 3
 
7.7%
e 3
 
7.7%
l 3
 
7.7%
n 3
 
7.7%
g 2
 
5.1%
y 2
 
5.1%
Other values (7) 9
23.1%
Decimal Number
ValueCountFrequency (%)
3 4
50.0%
1 2
25.0%
2 1
 
12.5%
5 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 48
98.0%
] 1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 48
98.0%
[ 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1562
85.5%
Common 177
 
9.7%
Latin 87
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 51
 
3.3%
주 49
 
3.1%
스 42
 
2.7%
점 39
 
2.5%
사 32
 
2.0%
산 30
 
1.9%
리 26
 
1.7%
부 26
 
1.7%
아 25
 
1.6%
삼 19
 
1.2%
Other values (323) 1223
78.3%
Latin
ValueCountFrequency (%)
R 5
 
5.7%
o 5
 
5.7%
A 4
 
4.6%
K 4
 
4.6%
E 4
 
4.6%
S 4
 
4.6%
u 3
 
3.4%
N 3
 
3.4%
a 3
 
3.4%
t 3
 
3.4%
Other values (25) 49
56.3%
Common
ValueCountFrequency (%)
67
37.9%
) 48
27.1%
( 48
27.1%
3 4
 
2.3%
1 2
 
1.1%
. 2
 
1.1%
: 1
 
0.6%
2 1
 
0.6%
5 1
 
0.6%
[ 1
 
0.6%
Other values (2) 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1562
85.5%
ASCII 264
 
14.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
25.4%
) 48
18.2%
( 48
18.2%
R 5
 
1.9%
o 5
 
1.9%
A 4
 
1.5%
K 4
 
1.5%
E 4
 
1.5%
3 4
 
1.5%
S 4
 
1.5%
Other values (37) 71
26.9%
Hangul
ValueCountFrequency (%)
이 51
 
3.3%
주 49
 
3.1%
스 42
 
2.7%
점 39
 
2.5%
사 32
 
2.0%
산 30
 
1.9%
리 26
 
1.7%
부 26
 
1.7%
아 25
 
1.6%
삼 19
 
1.2%
Other values (323) 1223
78.3%

소재지(도로명)
Text

MISSING 

Distinct228
Distinct (%)94.2%
Missing12
Missing (%)4.7%
Memory size2.1 KiB
2023-12-11T02:03:33.208768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length32.512397
Min length22

Characters and Unicode

Total characters7868
Distinct characters197
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

Unique221 ?
Unique (%)91.3%

Sample

1st row부산광역시 중구 중앙대로 137, 5층 (대창동2가)
2nd row부산광역시 중구 구덕로 51 (남포동5가)
3rd row부산광역시 중구 충장대로9번길 31, 201호 (중앙동4가)
4th row부산광역시 중구 흑교로 11 (부평동3가)
5th row부산광역시 중구 대청로 133-1 (동광동4가)
ValueCountFrequency (%)
부산광역시 242
 
15.4%
중구 242
 
15.4%
중앙대로 48
 
3.1%
1층 33
 
2.1%
3층 28
 
1.8%
중앙동4가 25
 
1.6%
대청로 24
 
1.5%
2 22
 
1.4%
구덕로 22
 
1.4%
중앙동7가 21
 
1.3%
Other values (391) 865
55.0%
2023-12-11T02:03:33.927057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1330
 
16.9%
중 395
 
5.0%
광 322
 
4.1%
1 316
 
4.0%
부 296
 
3.8%
동 284
 
3.6%
구 280
 
3.6%
산 252
 
3.2%
시 248
 
3.2%
) 244
 
3.1%
Other values (187) 3901
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4458
56.7%
Space Separator 1330
 
16.9%
Decimal Number 1283
 
16.3%
Close Punctuation 244
 
3.1%
Open Punctuation 244
 
3.1%
Other Punctuation 233
 
3.0%
Dash Punctuation 58
 
0.7%
Uppercase Letter 15
 
0.2%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 395
 
8.9%
광 322
 
7.2%
부 296
 
6.6%
동 284
 
6.4%
구 280
 
6.3%
산 252
 
5.7%
시 248
 
5.6%
역 243
 
5.5%
가 239
 
5.4%
로 220
 
4.9%
Other values (160) 1679
37.7%
Decimal Number
ValueCountFrequency (%)
1 316
24.6%
2 236
18.4%
3 158
12.3%
4 115
 
9.0%
5 103
 
8.0%
6 95
 
7.4%
7 83
 
6.5%
0 76
 
5.9%
9 52
 
4.1%
8 49
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 5
33.3%
B 3
20.0%
G 2
 
13.3%
C 1
 
6.7%
F 1
 
6.7%
N 1
 
6.7%
P 1
 
6.7%
D 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 232
99.6%
/ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
1330
100.0%
Close Punctuation
ValueCountFrequency (%)
) 244
100.0%
Open Punctuation
ValueCountFrequency (%)
( 244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4458
56.7%
Common 3393
43.1%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 395
 
8.9%
광 322
 
7.2%
부 296
 
6.6%
동 284
 
6.4%
구 280
 
6.3%
산 252
 
5.7%
시 248
 
5.6%
역 243
 
5.5%
가 239
 
5.4%
로 220
 
4.9%
Other values (160) 1679
37.7%
Common
ValueCountFrequency (%)
1330
39.2%
1 316
 
9.3%
) 244
 
7.2%
( 244
 
7.2%
2 236
 
7.0%
, 232
 
6.8%
3 158
 
4.7%
4 115
 
3.4%
5 103
 
3.0%
6 95
 
2.8%
Other values (7) 320
 
9.4%
Latin
ValueCountFrequency (%)
A 5
29.4%
B 3
17.6%
G 2
 
11.8%
C 1
 
5.9%
F 1
 
5.9%
N 1
 
5.9%
P 1
 
5.9%
D 1
 
5.9%
c 1
 
5.9%
s 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4458
56.7%
ASCII 3410
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1330
39.0%
1 316
 
9.3%
) 244
 
7.2%
( 244
 
7.2%
2 236
 
6.9%
, 232
 
6.8%
3 158
 
4.6%
4 115
 
3.4%
5 103
 
3.0%
6 95
 
2.8%
Other values (17) 337
 
9.9%
Hangul
ValueCountFrequency (%)
중 395
 
8.9%
광 322
 
7.2%
부 296
 
6.6%
동 284
 
6.4%
구 280
 
6.3%
산 252
 
5.7%
시 248
 
5.6%
역 243
 
5.5%
가 239
 
5.4%
로 220
 
4.9%
Other values (160) 1679
37.7%

소재지(지번)
Text

Distinct196
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T02:03:34.402759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length22.374016
Min length17

Characters and Unicode

Total characters5683
Distinct characters143
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

Unique173 ?
Unique (%)68.1%

Sample

1st row부산광역시 중구 대창동2가 35-4
2nd row부산광역시 중구 중앙동5가 65
3rd row부산광역시 중구 남포동5가 60-1
4th row부산광역시 중구 중앙동4가 81-21
5th row부산광역시 중구 부평동3가 49-4
ValueCountFrequency (%)
부산광역시 254
22.0%
중구 254
22.0%
중앙동4가 26
 
2.3%
중앙동7가 21
 
1.8%
20-1 21
 
1.8%
영주동 16
 
1.4%
남포동6가 16
 
1.4%
부평동1가 14
 
1.2%
부평동2가 14
 
1.2%
대청동2가 12
 
1.0%
Other values (271) 506
43.8%
2023-12-11T02:03:35.093419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1144
20.1%
중 329
 
5.8%
부 302
 
5.3%
광 293
 
5.2%
1 279
 
4.9%
동 276
 
4.9%
산 262
 
4.6%
시 257
 
4.5%
구 254
 
4.5%
역 254
 
4.5%
Other values (133) 2033
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3288
57.9%
Space Separator 1144
 
20.1%
Decimal Number 1028
 
18.1%
Dash Punctuation 199
 
3.5%
Uppercase Letter 8
 
0.1%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 329
10.0%
부 302
9.2%
광 293
 
8.9%
동 276
 
8.4%
산 262
 
8.0%
시 257
 
7.8%
구 254
 
7.7%
역 254
 
7.7%
가 252
 
7.7%
앙 74
 
2.3%
Other values (112) 735
22.4%
Decimal Number
ValueCountFrequency (%)
1 279
27.1%
2 181
17.6%
3 120
11.7%
4 107
 
10.4%
6 74
 
7.2%
7 65
 
6.3%
0 64
 
6.2%
5 64
 
6.2%
8 39
 
3.8%
9 35
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
50.0%
F 1
 
12.5%
N 1
 
12.5%
P 1
 
12.5%
A 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3288
57.9%
Common 2387
42.0%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 329
10.0%
부 302
9.2%
광 293
 
8.9%
동 276
 
8.4%
산 262
 
8.0%
시 257
 
7.8%
구 254
 
7.7%
역 254
 
7.7%
가 252
 
7.7%
앙 74
 
2.3%
Other values (112) 735
22.4%
Common
ValueCountFrequency (%)
1144
47.9%
1 279
 
11.7%
- 199
 
8.3%
2 181
 
7.6%
3 120
 
5.0%
4 107
 
4.5%
6 74
 
3.1%
7 65
 
2.7%
0 64
 
2.7%
5 64
 
2.7%
Other values (6) 90
 
3.8%
Latin
ValueCountFrequency (%)
B 4
50.0%
F 1
 
12.5%
N 1
 
12.5%
P 1
 
12.5%
A 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3288
57.9%
ASCII 2395
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1144
47.8%
1 279
 
11.6%
- 199
 
8.3%
2 181
 
7.6%
3 120
 
5.0%
4 107
 
4.5%
6 74
 
3.1%
7 65
 
2.7%
0 64
 
2.7%
5 64
 
2.7%
Other values (11) 98
 
4.1%
Hangul
ValueCountFrequency (%)
중 329
10.0%
부 302
9.2%
광 293
 
8.9%
동 276
 
8.4%
산 262
 
8.0%
시 257
 
7.8%
구 254
 
7.7%
역 254
 
7.7%
가 252
 
7.7%
앙 74
 
2.3%
Other values (112) 735
22.4%

소재지전화
Text

MISSING 

Distinct89
Distinct (%)91.8%
Missing157
Missing (%)61.8%
Memory size2.1 KiB
2023-12-11T02:03:35.485349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1164
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

Unique86 ?
Unique (%)88.7%

Sample

1st row051-242-0761
2nd row051-442-3673
3rd row051-231-2304
4th row051-468-5881
5th row051-244-0797
ValueCountFrequency (%)
051-678-3005 6
 
6.2%
051-250-7700 3
 
3.1%
051-441-2500 2
 
2.1%
051-248-8507 1
 
1.0%
051-441-4365 1
 
1.0%
051-467-2215 1
 
1.0%
051-245-5688 1
 
1.0%
051-469-6637 1
 
1.0%
051-256-7582 1
 
1.0%
051-465-6761 1
 
1.0%
Other values (79) 79
81.4%
2023-12-11T02:03:36.031654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 194
16.7%
5 178
15.3%
0 165
14.2%
1 134
11.5%
2 112
9.6%
4 102
8.8%
6 78
6.7%
7 63
 
5.4%
3 59
 
5.1%
8 46
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 970
83.3%
Dash Punctuation 194
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 178
18.4%
0 165
17.0%
1 134
13.8%
2 112
11.5%
4 102
10.5%
6 78
8.0%
7 63
 
6.5%
3 59
 
6.1%
8 46
 
4.7%
9 33
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 194
16.7%
5 178
15.3%
0 165
14.2%
1 134
11.5%
2 112
9.6%
4 102
8.8%
6 78
6.7%
7 63
 
5.4%
3 59
 
5.1%
8 46
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 194
16.7%
5 178
15.3%
0 165
14.2%
1 134
11.5%
2 112
9.6%
4 102
8.8%
6 78
6.7%
7 63
 
5.4%
3 59
 
5.1%
8 46
 
4.0%

Correlations

2023-12-11T02:03:36.214301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명소재지전화
업종명1.0001.000
소재지전화1.0001.000

Missing values

2023-12-11T02:03:30.669148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:03:30.840231image/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.
2023-12-11T02:03:31.013855image/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
0건강기능식품일반판매업(주)나눔의사람들부산광역시 중구 중앙대로 137, 5층 (대창동2가)부산광역시 중구 대창동2가 35-4051-242-0761
1건강기능식품일반판매업(주)태양트레이드<NA>부산광역시 중구 중앙동5가 65051-442-3673
2건강기능식품일반판매업한국인삼공사 남포동전시판매장부산광역시 중구 구덕로 51 (남포동5가)부산광역시 중구 남포동5가 60-1051-231-2304
3건강기능식품일반판매업아모레 중구제일특약점부산광역시 중구 충장대로9번길 31, 201호 (중앙동4가)부산광역시 중구 중앙동4가 81-21051-468-5881
4건강기능식품일반판매업시민자연건강부산광역시 중구 흑교로 11 (부평동3가)부산광역시 중구 부평동3가 49-4051-244-0797
5건강기능식품일반판매업정관장홍삼 동광점부산광역시 중구 대청로 133-1 (동광동4가)부산광역시 중구 동광동4가 1-2051-442-2304
6건강기능식품일반판매업영림수부산광역시 중구 중구로33번길 13-1 (부평동1가)부산광역시 중구 부평동1가 29-3051-231-0606
7건강기능식품일반판매업인산건강식품부산광역시 중구 자갈치로 33 (남포동6가)부산광역시 중구 남포동6가 3051-242-7708
8건강기능식품일반판매업(주)준영부산광역시 중구 중앙대로 70, 10층 (중앙동4가)부산광역시 중구 중앙동4가 25 10층051-464-7175
9건강기능식품일반판매업(주)코리아나화장품<NA>부산광역시 중구 중앙동4가 73-21051-442-1043
업종명업소명소재지(도로명)소재지(지번)소재지전화
244건강기능식품일반판매업달성상회부산광역시 중구 용미길 5, 지상1층 (남포동1가)부산광역시 중구 남포동1가 57-1<NA>
245건강기능식품일반판매업꿀영자부산광역시 중구 대청로 91-6, 1004호 (대청동2가, 그린시티)부산광역시 중구 대청동2가 19-2 그린시티<NA>
246건강기능식품일반판매업신우유통부산광역시 중구 대청로 83-20, 지상4층 (대청동3가)부산광역시 중구 대청동3가 4-1<NA>
247건강기능식품일반판매업대양컴퓨터부산광역시 중구 중앙대로 지하 17, 광복지하도상가 A28호 (중앙동6가)부산광역시 중구 중앙동6가 9-1 광복지하도상가<NA>
248건강기능식품일반판매업녹돌에이부산광역시 중구 광복중앙로 28-1, 지상6층 640호 (대청동2가)부산광역시 중구 대청동2가 34-1<NA>
249건강기능식품일반판매업엠3(M3)부산광역시 중구 중앙대로 지하 17, 광복지하도상가 A-17호 (중앙동6가)부산광역시 중구 중앙동6가 9-1 광복지하도상가<NA>
250건강기능식품유통전문판매업(주)청운플러스부산광역시 중구 대청로155번길 6, 2층 (중앙동4가)부산광역시 중구 중앙동4가 17-7051-466-5168
251건강기능식품유통전문판매업주식회사 바이오맥스부산광역시 중구 중앙대로 131, 센트렐오피스텔 3층 (대창동1가)부산광역시 중구 대창동1가 54-1 센트렐오피스텔<NA>
252건강기능식품유통전문판매업(주)네이처온팜부산광역시 중구 중앙대로81번길 2, 팔성빌딩 6층 (중앙동4가)부산광역시 중구 중앙동4가 53-6<NA>
253건강기능식품유통전문판매업(주)곰솔부산광역시 중구 보수대로124번길 66, 206호 (보수동2가)부산광역시 중구 보수동2가 93-1 206호<NA>