Overview

Dataset statistics

Number of variables6
Number of observations188
Missing cells60
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory48.7 B

Variable types

Categorical2
Text4

Dataset

Description경상북도 포항시 식품유통업 현황에 관한 데이터로 식품유통업 업체명, 주소, 전화번호 등에 관한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15113385/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지도로명주소 has 3 (1.6%) missing valuesMissing
전화번호 has 57 (30.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:04:34.072983
Analysis finished2023-12-12 23:04:34.648155
Duration0.58 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
식품소분업
188 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 188
100.0%

Length

2023-12-13T08:04:34.703736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:04:34.805860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 188
100.0%

업소명
Text

Distinct187
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:04:35.026510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.6117021
Min length2

Characters and Unicode

Total characters1243
Distinct characters284
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

Unique186 ?
Unique (%)98.9%

Sample

1st row(주)정화식품상사
2nd row노승사
3rd row동아스파우현점
4th row정화식품
5th row한성수산식품(주)
ValueCountFrequency (%)
탑마트 4
 
1.8%
주)서원유통 4
 
1.8%
건어물 3
 
1.4%
포항점 2
 
0.9%
빅마트 2
 
0.9%
포항 2
 
0.9%
그린스토아 2
 
0.9%
세남자떡볶이 1
 
0.5%
띵크건어물 1
 
0.5%
올바른 1
 
0.5%
Other values (196) 196
89.9%
2023-12-13T08:04:35.527515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 36
 
2.9%
) 35
 
2.8%
( 35
 
2.8%
산 33
 
2.7%
30
 
2.4%
물 29
 
2.3%
주 29
 
2.3%
수 28
 
2.3%
마 27
 
2.2%
회 26
 
2.1%
Other values (274) 935
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1116
89.8%
Close Punctuation 35
 
2.8%
Open Punctuation 35
 
2.8%
Space Separator 30
 
2.4%
Lowercase Letter 10
 
0.8%
Uppercase Letter 9
 
0.7%
Decimal Number 4
 
0.3%
Dash Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 36
 
3.2%
산 33
 
3.0%
물 29
 
2.6%
주 29
 
2.6%
수 28
 
2.5%
마 27
 
2.4%
회 26
 
2.3%
상 26
 
2.3%
건 26
 
2.3%
포 25
 
2.2%
Other values (253) 831
74.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
30.0%
c 2
20.0%
o 2
20.0%
t 1
 
10.0%
h 1
 
10.0%
s 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
R 3
33.3%
E 2
22.2%
H 1
 
11.1%
T 1
 
11.1%
I 1
 
11.1%
P 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
8 1
25.0%
4 1
25.0%
0 1
25.0%
9 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1116
89.8%
Common 108
 
8.7%
Latin 19
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 36
 
3.2%
산 33
 
3.0%
물 29
 
2.6%
주 29
 
2.6%
수 28
 
2.5%
마 27
 
2.4%
회 26
 
2.3%
상 26
 
2.3%
건 26
 
2.3%
포 25
 
2.2%
Other values (253) 831
74.5%
Latin
ValueCountFrequency (%)
e 3
15.8%
R 3
15.8%
E 2
10.5%
c 2
10.5%
o 2
10.5%
H 1
 
5.3%
T 1
 
5.3%
t 1
 
5.3%
h 1
 
5.3%
s 1
 
5.3%
Other values (2) 2
10.5%
Common
ValueCountFrequency (%)
) 35
32.4%
( 35
32.4%
30
27.8%
- 2
 
1.9%
, 2
 
1.9%
8 1
 
0.9%
4 1
 
0.9%
0 1
 
0.9%
9 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1116
89.8%
ASCII 127
 
10.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 36
 
3.2%
산 33
 
3.0%
물 29
 
2.6%
주 29
 
2.6%
수 28
 
2.5%
마 27
 
2.4%
회 26
 
2.3%
상 26
 
2.3%
건 26
 
2.3%
포 25
 
2.2%
Other values (253) 831
74.5%
ASCII
ValueCountFrequency (%)
) 35
27.6%
( 35
27.6%
30
23.6%
e 3
 
2.4%
R 3
 
2.4%
E 2
 
1.6%
c 2
 
1.6%
- 2
 
1.6%
, 2
 
1.6%
o 2
 
1.6%
Other values (11) 11
 
8.7%

소재지도로명주소
Text

MISSING 

Distinct182
Distinct (%)98.4%
Missing3
Missing (%)1.6%
Memory size1.6 KiB
2023-12-13T08:04:35.865312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length29.497297
Min length22

Characters and Unicode

Total characters5457
Distinct characters156
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

Unique180 ?
Unique (%)97.3%

Sample

1st row경상북도 포항시 북구 송라면 해안로 2763
2nd row경상북도 포항시 북구 두호로37번길 8 (두호동)
3rd row경상북도 포항시 북구 아치로 57 (우현동)
4th row경상북도 포항시 북구 중앙로419번길 12-1 (우현동)
5th row경상북도 포항시 남구 구룡포읍 병포길 130
ValueCountFrequency (%)
경상북도 185
 
15.2%
포항시 185
 
15.2%
북구 119
 
9.8%
남구 66
 
5.4%
죽도동 43
 
3.5%
1층 42
 
3.5%
구룡포읍 14
 
1.2%
흥해읍 13
 
1.1%
장성동 12
 
1.0%
양덕동 11
 
0.9%
Other values (337) 525
43.2%
2023-12-13T08:04:36.303438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1030
18.9%
북 304
 
5.6%
도 285
 
5.2%
1 236
 
4.3%
시 217
 
4.0%
포 209
 
3.8%
구 200
 
3.7%
상 195
 
3.6%
항 188
 
3.4%
경 185
 
3.4%
Other values (146) 2408
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3222
59.0%
Space Separator 1030
 
18.9%
Decimal Number 800
 
14.7%
Open Punctuation 133
 
2.4%
Close Punctuation 133
 
2.4%
Other Punctuation 76
 
1.4%
Dash Punctuation 55
 
1.0%
Uppercase Letter 7
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 304
 
9.4%
도 285
 
8.8%
시 217
 
6.7%
포 209
 
6.5%
구 200
 
6.2%
상 195
 
6.1%
항 188
 
5.8%
경 185
 
5.7%
동 159
 
4.9%
로 139
 
4.3%
Other values (128) 1141
35.4%
Decimal Number
ValueCountFrequency (%)
1 236
29.5%
2 123
15.4%
3 86
 
10.8%
7 63
 
7.9%
4 62
 
7.8%
0 59
 
7.4%
5 55
 
6.9%
8 41
 
5.1%
6 39
 
4.9%
9 36
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
57.1%
D 3
42.9%
Space Separator
ValueCountFrequency (%)
1030
100.0%
Open Punctuation
ValueCountFrequency (%)
( 133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 133
100.0%
Other Punctuation
ValueCountFrequency (%)
, 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3222
59.0%
Common 2227
40.8%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 304
 
9.4%
도 285
 
8.8%
시 217
 
6.7%
포 209
 
6.5%
구 200
 
6.2%
상 195
 
6.1%
항 188
 
5.8%
경 185
 
5.7%
동 159
 
4.9%
로 139
 
4.3%
Other values (128) 1141
35.4%
Common
ValueCountFrequency (%)
1030
46.3%
1 236
 
10.6%
( 133
 
6.0%
) 133
 
6.0%
2 123
 
5.5%
3 86
 
3.9%
, 76
 
3.4%
7 63
 
2.8%
4 62
 
2.8%
0 59
 
2.6%
Other values (5) 226
 
10.1%
Latin
ValueCountFrequency (%)
A 4
50.0%
D 3
37.5%
c 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3222
59.0%
ASCII 2235
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1030
46.1%
1 236
 
10.6%
( 133
 
6.0%
) 133
 
6.0%
2 123
 
5.5%
3 86
 
3.8%
, 76
 
3.4%
7 63
 
2.8%
4 62
 
2.8%
0 59
 
2.6%
Other values (8) 234
 
10.5%
Hangul
ValueCountFrequency (%)
북 304
 
9.4%
도 285
 
8.8%
시 217
 
6.7%
포 209
 
6.5%
구 200
 
6.2%
상 195
 
6.1%
항 188
 
5.8%
경 185
 
5.7%
동 159
 
4.9%
로 139
 
4.3%
Other values (128) 1141
35.4%

소재지지번주소
Text

Distinct186
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:04:36.668152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length25.058511
Min length20

Characters and Unicode

Total characters4711
Distinct characters141
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

Unique184 ?
Unique (%)97.9%

Sample

1st row경상북도 포항시 북구 송라면 조사리 357
2nd row경상북도 포항시 북구 두호동 1055-2
3rd row경상북도 포항시 북구 우현동 335-4
4th row경상북도 포항시 북구 우현동 92-6
5th row경상북도 포항시 남구 구룡포읍 병포리 181
ValueCountFrequency (%)
경상북도 188
17.4%
포항시 188
17.4%
북구 121
 
11.2%
남구 67
 
6.2%
죽도동 46
 
4.2%
1층 25
 
2.3%
구룡포읍 14
 
1.3%
흥해읍 13
 
1.2%
장성동 12
 
1.1%
양덕동 11
 
1.0%
Other values (294) 398
36.7%
2023-12-13T08:04:37.170360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1078
22.9%
북 309
 
6.6%
도 257
 
5.5%
포 216
 
4.6%
구 211
 
4.5%
1 206
 
4.4%
상 195
 
4.1%
시 190
 
4.0%
항 189
 
4.0%
경 188
 
4.0%
Other values (131) 1672
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2651
56.3%
Space Separator 1078
22.9%
Decimal Number 799
 
17.0%
Dash Punctuation 146
 
3.1%
Other Punctuation 15
 
0.3%
Uppercase Letter 10
 
0.2%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 309
11.7%
도 257
 
9.7%
포 216
 
8.1%
구 211
 
8.0%
상 195
 
7.4%
시 190
 
7.2%
항 189
 
7.1%
경 188
 
7.1%
동 139
 
5.2%
남 69
 
2.6%
Other values (111) 688
26.0%
Decimal Number
ValueCountFrequency (%)
1 206
25.8%
2 96
12.0%
5 88
11.0%
6 84
10.5%
4 83
10.4%
8 66
 
8.3%
3 58
 
7.3%
0 48
 
6.0%
7 42
 
5.3%
9 28
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
D 3
30.0%
L 2
20.0%
A 1
 
10.0%
F 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1078
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2651
56.3%
Common 2050
43.5%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 309
11.7%
도 257
 
9.7%
포 216
 
8.1%
구 211
 
8.0%
상 195
 
7.4%
시 190
 
7.2%
항 189
 
7.1%
경 188
 
7.1%
동 139
 
5.2%
남 69
 
2.6%
Other values (111) 688
26.0%
Common
ValueCountFrequency (%)
1078
52.6%
1 206
 
10.0%
- 146
 
7.1%
2 96
 
4.7%
5 88
 
4.3%
6 84
 
4.1%
4 83
 
4.0%
8 66
 
3.2%
3 58
 
2.8%
0 48
 
2.3%
Other values (5) 97
 
4.7%
Latin
ValueCountFrequency (%)
B 3
30.0%
D 3
30.0%
L 2
20.0%
A 1
 
10.0%
F 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2651
56.3%
ASCII 2060
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1078
52.3%
1 206
 
10.0%
- 146
 
7.1%
2 96
 
4.7%
5 88
 
4.3%
6 84
 
4.1%
4 83
 
4.0%
8 66
 
3.2%
3 58
 
2.8%
0 48
 
2.3%
Other values (10) 107
 
5.2%
Hangul
ValueCountFrequency (%)
북 309
11.7%
도 257
 
9.7%
포 216
 
8.1%
구 211
 
8.0%
상 195
 
7.4%
시 190
 
7.2%
항 189
 
7.1%
경 188
 
7.1%
동 139
 
5.2%
남 69
 
2.6%
Other values (111) 688
26.0%

전화번호
Text

MISSING 

Distinct128
Distinct (%)97.7%
Missing57
Missing (%)30.3%
Memory size1.6 KiB
2023-12-13T08:04:37.432583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.068702
Min length12

Characters and Unicode

Total characters1581
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

Unique125 ?
Unique (%)95.4%

Sample

1st row054-247-0958
2nd row054-247-0295
3rd row054-248-3068
4th row054-247-7021
5th row054-276-6792
ValueCountFrequency (%)
054-272-8300 2
 
1.5%
070-8770-5424 2
 
1.5%
054-262-2438 2
 
1.5%
070-7585-9060 1
 
0.8%
054-241-3181 1
 
0.8%
054-246-6205 1
 
0.8%
054-292-1785 1
 
0.8%
054-247-0958 1
 
0.8%
070-7677-9285 1
 
0.8%
054-281-4800 1
 
0.8%
Other values (118) 118
90.1%
2023-12-13T08:04:37.817246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 262
16.6%
2 225
14.2%
4 224
14.2%
0 216
13.7%
5 198
12.5%
8 99
 
6.3%
7 93
 
5.9%
3 82
 
5.2%
1 72
 
4.6%
6 68
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1319
83.4%
Dash Punctuation 262
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 225
17.1%
4 224
17.0%
0 216
16.4%
5 198
15.0%
8 99
7.5%
7 93
7.1%
3 82
 
6.2%
1 72
 
5.5%
6 68
 
5.2%
9 42
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1581
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 262
16.6%
2 225
14.2%
4 224
14.2%
0 216
13.7%
5 198
12.5%
8 99
 
6.3%
7 93
 
5.9%
3 82
 
5.2%
1 72
 
4.6%
6 68
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1581
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 262
16.6%
2 225
14.2%
4 224
14.2%
0 216
13.7%
5 198
12.5%
8 99
 
6.3%
7 93
 
5.9%
3 82
 
5.2%
1 72
 
4.6%
6 68
 
4.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-04-14
188 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-14
2nd row2023-04-14
3rd row2023-04-14
4th row2023-04-14
5th row2023-04-14

Common Values

ValueCountFrequency (%)
2023-04-14 188
100.0%

Length

2023-12-13T08:04:37.954452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:04:38.042351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-14 188
100.0%

Missing values

2023-12-13T08:04:34.415409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:04:34.507988image/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.
2023-12-13T08:04:34.600357image/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

업종명업소명소재지도로명주소소재지지번주소전화번호데이터기준일자
0식품소분업(주)정화식품상사경상북도 포항시 북구 송라면 해안로 2763경상북도 포항시 북구 송라면 조사리 357054-247-09582023-04-14
1식품소분업노승사경상북도 포항시 북구 두호로37번길 8 (두호동)경상북도 포항시 북구 두호동 1055-2054-247-02952023-04-14
2식품소분업동아스파우현점경상북도 포항시 북구 아치로 57 (우현동)경상북도 포항시 북구 우현동 335-4054-248-30682023-04-14
3식품소분업정화식품경상북도 포항시 북구 중앙로419번길 12-1 (우현동)경상북도 포항시 북구 우현동 92-6054-247-70212023-04-14
4식품소분업한성수산식품(주)경상북도 포항시 남구 구룡포읍 병포길 130경상북도 포항시 남구 구룡포읍 병포리 181054-276-67922023-04-14
5식품소분업새시대식품경상북도 포항시 남구 오천읍 해병로337번길 24-6경상북도 포항시 남구 오천읍 문덕리 10-302054-276-49222023-04-14
6식품소분업용현상회경상북도 포항시 북구 죽도시장11길 12-7 (죽도동)경상북도 포항시 북구 죽도동 2-31054-242-14952023-04-14
7식품소분업부일수산경상북도 포항시 남구 구룡포읍 하정로 200경상북도 포항시 남구 구룡포읍 병포리 235-1054-276-51362023-04-14
8식품소분업이레마트경상북도 포항시 북구 새마을로 94 (용흥동)경상북도 포항시 북구 용흥동 355-1054-243-82892023-04-14
9식품소분업하니마트경상북도 포항시 북구 삼흥로100번길 56 (두호동)경상북도 포항시 북구 두호동 1076-1<NA>2023-04-14
업종명업소명소재지도로명주소소재지지번주소전화번호데이터기준일자
178식품소분업(주)인터내셔널크루경상북도 포항시 남구 오천읍 하원로26번길 16-10경상북도 포항시 남구 오천읍 원리 1342<NA>2023-04-14
179식품소분업정아스토어경상북도 포항시 남구 구정길17번길 43-22, A동 1층 110호 (인덕동)경상북도 포항시 남구 인덕동 5-2070-8879-40002023-04-14
180식품소분업별이네건어물경상북도 포항시 북구 장량로174번길 6, 1층 (양덕동)경상북도 포항시 북구 양덕동 1498-1<NA>2023-04-14
181식품소분업(주)푸드사이언스경상북도 포항시 북구 흥해읍 성곡길 214, 2층경상북도 포항시 북구 흥해읍 성곡리 70-6054-233-24022023-04-14
182식품소분업아린수산경상북도 포항시 남구 연일읍 철강로107번길 82, 1층 102호경상북도 포항시 남구 연일읍 오천리 181-28<NA>2023-04-14
183식품소분업모든건어물경상북도 포항시 남구 오천읍 원동로 50, 1층 102-1호경상북도 포항시 남구 오천읍 원리 933<NA>2023-04-14
184식품소분업진우푸드(주)경상북도 포항시 남구 구룡포읍 병포길129번길 25-8경상북도 포항시 남구 구룡포읍 병포리 65-2054-275-98262023-04-14
185식품소분업더이로움경상북도 포항시 북구 장량로 218, 1층 (양덕동)경상북도 포항시 북구 양덕동 1840054-274-55252023-04-14
186식품소분업호야네씨푸드경상북도 포항시 남구 대이로95번길 5-4, 1층 (대잠동)경상북도 포항시 남구 대잠동 464-3<NA>2023-04-14
187식품소분업건어물해 달포차경상북도 포항시 북구 새천년대로1249번길 6-7, 1층 101호 (장성동)경상북도 포항시 북구 장성동 1572-21<NA>2023-04-14