Overview

Dataset statistics

Number of variables6
Number of observations155
Missing cells48
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory48.8 B

Variable types

Text5
Categorical1

Dataset

Description진안군 관내 식품제조가공업소에 대한 데이터로 식품제조가공업소명, 대표자,소재지 도로명주소, 전화번호 등을 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15065106/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지전화번호 has 48 (31.0%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:55:01.586190
Analysis finished2024-03-14 12:55:02.734573
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:55:03.461513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.5354839
Min length2

Characters and Unicode

Total characters1323
Distinct characters245
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)100.0%

Sample

1st row(주)건보
2nd row한국농협김치조합공동사업법인 전북지사
3rd row주식회사 푸른생명
4th row송화수 홍삼 영농조합법인
5th row대성한과
ValueCountFrequency (%)
농업회사법인 15
 
6.0%
주식회사 12
 
4.8%
홍삼 10
 
4.0%
유한회사 7
 
2.8%
영농조합법인 7
 
2.8%
홍삼원 3
 
1.2%
마이 3
 
1.2%
식품 3
 
1.2%
마이산 3
 
1.2%
고려홍삼 2
 
0.8%
Other values (182) 185
74.0%
2024-03-14T21:55:04.811703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
7.2%
삼 53
 
4.0%
사 50
 
3.8%
농 50
 
3.8%
홍 48
 
3.6%
회 43
 
3.3%
인 41
 
3.1%
법 35
 
2.6%
식 32
 
2.4%
주 31
 
2.3%
Other values (235) 845
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1173
88.7%
Space Separator 95
 
7.2%
Close Punctuation 23
 
1.7%
Open Punctuation 23
 
1.7%
Uppercase Letter 4
 
0.3%
Decimal Number 3
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
삼 53
 
4.5%
사 50
 
4.3%
농 50
 
4.3%
홍 48
 
4.1%
회 43
 
3.7%
인 41
 
3.5%
법 35
 
3.0%
식 32
 
2.7%
주 31
 
2.6%
산 27
 
2.3%
Other values (225) 763
65.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
25.0%
C 1
25.0%
M 1
25.0%
O 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1171
88.5%
Common 146
 
11.0%
Latin 4
 
0.3%
Han 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
삼 53
 
4.5%
사 50
 
4.3%
농 50
 
4.3%
홍 48
 
4.1%
회 43
 
3.7%
인 41
 
3.5%
법 35
 
3.0%
식 32
 
2.7%
주 31
 
2.6%
산 27
 
2.3%
Other values (223) 761
65.0%
Common
ValueCountFrequency (%)
95
65.1%
) 23
 
15.8%
( 23
 
15.8%
. 2
 
1.4%
2 2
 
1.4%
1 1
 
0.7%
Latin
ValueCountFrequency (%)
J 1
25.0%
C 1
25.0%
M 1
25.0%
O 1
25.0%
Han
ValueCountFrequency (%)
氣 1
50.0%
家 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1171
88.5%
ASCII 150
 
11.3%
CJK 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
63.3%
) 23
 
15.3%
( 23
 
15.3%
. 2
 
1.3%
2 2
 
1.3%
1 1
 
0.7%
J 1
 
0.7%
C 1
 
0.7%
M 1
 
0.7%
O 1
 
0.7%
Hangul
ValueCountFrequency (%)
삼 53
 
4.5%
사 50
 
4.3%
농 50
 
4.3%
홍 48
 
4.1%
회 43
 
3.7%
인 41
 
3.5%
법 35
 
3.0%
식 32
 
2.7%
주 31
 
2.6%
산 27
 
2.3%
Other values (223) 761
65.0%
CJK
ValueCountFrequency (%)
氣 1
50.0%
家 1
50.0%

대표자
Text

Distinct131
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:55:06.124788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.0709677
Min length2

Characters and Unicode

Total characters476
Distinct characters103
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

Unique112 ?
Unique (%)72.3%

Sample

1st row김*민
2nd row현*성
3rd row최*란
4th row송*생
5th row김*순
ValueCountFrequency (%)
김*술 4
 
2.5%
김*은 3
 
1.9%
김*수 3
 
1.9%
김*숙 3
 
1.9%
김*화 2
 
1.3%
이*순 2
 
1.3%
최*자 2
 
1.3%
송*영 2
 
1.3%
김*상 2
 
1.3%
최*석 2
 
1.3%
Other values (123) 132
84.1%
2024-03-14T21:55:07.860118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 155
32.6%
김 39
 
8.2%
이 15
 
3.2%
전 12
 
2.5%
최 12
 
2.5%
박 10
 
2.1%
원 9
 
1.9%
희 8
 
1.7%
안 7
 
1.5%
임 7
 
1.5%
Other values (93) 202
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
66.8%
Other Punctuation 156
32.8%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 39
 
12.3%
이 15
 
4.7%
전 12
 
3.8%
최 12
 
3.8%
박 10
 
3.1%
원 9
 
2.8%
희 8
 
2.5%
안 7
 
2.2%
임 7
 
2.2%
순 7
 
2.2%
Other values (90) 192
60.4%
Other Punctuation
ValueCountFrequency (%)
* 155
99.4%
, 1
 
0.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
66.8%
Common 158
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 39
 
12.3%
이 15
 
4.7%
전 12
 
3.8%
최 12
 
3.8%
박 10
 
3.1%
원 9
 
2.8%
희 8
 
2.5%
안 7
 
2.2%
임 7
 
2.2%
순 7
 
2.2%
Other values (90) 192
60.4%
Common
ValueCountFrequency (%)
* 155
98.1%
2
 
1.3%
, 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
66.8%
ASCII 158
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 155
98.1%
2
 
1.3%
, 1
 
0.6%
Hangul
ValueCountFrequency (%)
김 39
 
12.3%
이 15
 
4.7%
전 12
 
3.8%
최 12
 
3.8%
박 10
 
3.1%
원 9
 
2.8%
희 8
 
2.5%
안 7
 
2.2%
임 7
 
2.2%
순 7
 
2.2%
Other values (90) 192
60.4%

소재지전화번호
Text

MISSING 

Distinct104
Distinct (%)97.2%
Missing48
Missing (%)31.0%
Memory size1.3 KiB
2024-03-14T21:55:08.765452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1284
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

Unique102 ?
Unique (%)95.3%

Sample

1st row063-433-0133
2nd row063-433-5356
3rd row063-433-4460
4th row063-433-6767
5th row063-433-3569
ValueCountFrequency (%)
063-433-2233 3
 
2.8%
063-432-0367 2
 
1.9%
063-433-0133 1
 
0.9%
063-433-9900 1
 
0.9%
063-432-5604 1
 
0.9%
063-433-5691 1
 
0.9%
063-432-5844 1
 
0.9%
063-432-6822 1
 
0.9%
063-433-1100 1
 
0.9%
063-323-8112 1
 
0.9%
Other values (94) 94
87.9%
2024-03-14T21:55:10.047637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 324
25.2%
- 214
16.7%
6 160
12.5%
0 155
12.1%
4 131
10.2%
2 101
 
7.9%
5 53
 
4.1%
1 43
 
3.3%
8 41
 
3.2%
9 38
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1070
83.3%
Dash Punctuation 214
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 324
30.3%
6 160
15.0%
0 155
14.5%
4 131
12.2%
2 101
 
9.4%
5 53
 
5.0%
1 43
 
4.0%
8 41
 
3.8%
9 38
 
3.6%
7 24
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1284
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 324
25.2%
- 214
16.7%
6 160
12.5%
0 155
12.1%
4 131
10.2%
2 101
 
7.9%
5 53
 
4.1%
1 43
 
3.3%
8 41
 
3.2%
9 38
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 324
25.2%
- 214
16.7%
6 160
12.5%
0 155
12.1%
4 131
10.2%
2 101
 
7.9%
5 53
 
4.1%
1 43
 
3.3%
8 41
 
3.2%
9 38
 
3.0%

소재지 도로명 주소
Text

Distinct150
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:55:11.648826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length24.806452
Min length21

Characters and Unicode

Total characters3845
Distinct characters155
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)94.2%

Sample

1st row전북특별자치도 진안군 진안읍 거북바위로1길 19-6
2nd row전북특별자치도 진안군 부귀면 가정길 6
3rd row전북특별자치도 진안군 성수면 중길로 602
4th row전북특별자치도 진안군 부귀면 전진로 1964
5th row전북특별자치도 진안군 부귀면 전진로 2423
ValueCountFrequency (%)
진안군 156
19.9%
전북특별자치도 155
19.7%
진안읍 63
 
8.0%
주천면 19
 
2.4%
홍삼한방로 16
 
2.0%
부귀면 16
 
2.0%
용담면 13
 
1.7%
정천면 10
 
1.3%
마령면 10
 
1.3%
성수면 8
 
1.0%
Other values (236) 319
40.6%
2024-03-14T21:55:13.826253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
630
 
16.4%
진 236
 
6.1%
안 227
 
5.9%
북 165
 
4.3%
전 163
 
4.2%
자 158
 
4.1%
치 156
 
4.1%
도 156
 
4.1%
군 156
 
4.1%
특 155
 
4.0%
Other values (145) 1643
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2630
68.4%
Space Separator 630
 
16.4%
Decimal Number 501
 
13.0%
Dash Punctuation 77
 
2.0%
Other Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 236
 
9.0%
안 227
 
8.6%
북 165
 
6.3%
전 163
 
6.2%
자 158
 
6.0%
치 156
 
5.9%
도 156
 
5.9%
군 156
 
5.9%
특 155
 
5.9%
별 155
 
5.9%
Other values (132) 903
34.3%
Decimal Number
ValueCountFrequency (%)
1 118
23.6%
2 108
21.6%
3 60
12.0%
6 41
 
8.2%
7 35
 
7.0%
4 34
 
6.8%
0 32
 
6.4%
5 30
 
6.0%
8 24
 
4.8%
9 19
 
3.8%
Space Separator
ValueCountFrequency (%)
630
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2630
68.4%
Common 1215
31.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 236
 
9.0%
안 227
 
8.6%
북 165
 
6.3%
전 163
 
6.2%
자 158
 
6.0%
치 156
 
5.9%
도 156
 
5.9%
군 156
 
5.9%
특 155
 
5.9%
별 155
 
5.9%
Other values (132) 903
34.3%
Common
ValueCountFrequency (%)
630
51.9%
1 118
 
9.7%
2 108
 
8.9%
- 77
 
6.3%
3 60
 
4.9%
6 41
 
3.4%
7 35
 
2.9%
4 34
 
2.8%
0 32
 
2.6%
5 30
 
2.5%
Other values (3) 50
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2630
68.4%
ASCII 1215
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
630
51.9%
1 118
 
9.7%
2 108
 
8.9%
- 77
 
6.3%
3 60
 
4.9%
6 41
 
3.4%
7 35
 
2.9%
4 34
 
2.8%
0 32
 
2.6%
5 30
 
2.5%
Other values (3) 50
 
4.1%
Hangul
ValueCountFrequency (%)
진 236
 
9.0%
안 227
 
8.6%
북 165
 
6.3%
전 163
 
6.2%
자 158
 
6.0%
치 156
 
5.9%
도 156
 
5.9%
군 156
 
5.9%
특 155
 
5.9%
별 155
 
5.9%
Other values (132) 903
34.3%

식품유형
Text

Distinct84
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:55:14.976378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length65
Mean length14.6
Min length2

Characters and Unicode

Total characters2263
Distinct characters93
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

Unique73 ?
Unique (%)47.1%

Sample

1st row인삼제품류, 다류, 음료류, 절임식품, 규격외일반가공식품, 농산가공식품류, 기타식품류
2nd row김치류, 절임식품, 기타김치, 절임류 또는 조림류, 즉석식품류, 기타식품류
3rd row영양보충용제품, 특수용도식품, 기타식품류, 규격외일반가공식품, 특수용도식품, 곡류효소함유제품, 코코아가공품류 또는 초콜릿류, 농산가공식품류
4th row다류, 절임식품, 규격외일반가공식품, 음료류, 인삼 및 홍삼음료, 농산가공식품류, 기타식품류
5th row과자류, 빵류 또는 떡류
ValueCountFrequency (%)
다류 86
18.7%
음료류 78
17.0%
기타식품류 30
 
6.5%
규격외일반가공식품 29
 
6.3%
또는 23
 
5.0%
절임식품 22
 
4.8%
조미식품 21
 
4.6%
농산가공식품류 21
 
4.6%
과자류 15
 
3.3%
장류 14
 
3.0%
Other values (46) 121
26.3%
2024-03-14T21:55:16.846858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 323
14.3%
316
14.0%
, 253
 
11.2%
품 153
 
6.8%
식 149
 
6.6%
다 86
 
3.8%
료 84
 
3.7%
음 83
 
3.7%
공 67
 
3.0%
가 67
 
3.0%
Other values (83) 682
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1694
74.9%
Space Separator 316
 
14.0%
Other Punctuation 253
 
11.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 323
19.1%
품 153
 
9.0%
식 149
 
8.8%
다 86
 
5.1%
료 84
 
5.0%
음 83
 
4.9%
공 67
 
4.0%
가 67
 
4.0%
기 39
 
2.3%
타 39
 
2.3%
Other values (81) 604
35.7%
Space Separator
ValueCountFrequency (%)
316
100.0%
Other Punctuation
ValueCountFrequency (%)
, 253
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1694
74.9%
Common 569
 
25.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 323
19.1%
품 153
 
9.0%
식 149
 
8.8%
다 86
 
5.1%
료 84
 
5.0%
음 83
 
4.9%
공 67
 
4.0%
가 67
 
4.0%
기 39
 
2.3%
타 39
 
2.3%
Other values (81) 604
35.7%
Common
ValueCountFrequency (%)
316
55.5%
, 253
44.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1694
74.9%
ASCII 569
 
25.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 323
19.1%
품 153
 
9.0%
식 149
 
8.8%
다 86
 
5.1%
료 84
 
5.0%
음 83
 
4.9%
공 67
 
4.0%
가 67
 
4.0%
기 39
 
2.3%
타 39
 
2.3%
Other values (81) 604
35.7%
ASCII
ValueCountFrequency (%)
316
55.5%
, 253
44.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-11-30
155 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 155
100.0%

Length

2024-03-14T21:55:17.358962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:55:17.643988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 155
100.0%

Missing values

2024-03-14T21:55:02.241700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:55:02.594985image/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

업소명대표자소재지전화번호소재지 도로명 주소식품유형데이터기준일자
0(주)건보김*민063-433-0133전북특별자치도 진안군 진안읍 거북바위로1길 19-6인삼제품류, 다류, 음료류, 절임식품, 규격외일반가공식품, 농산가공식품류, 기타식품류2023-11-30
1한국농협김치조합공동사업법인 전북지사현*성063-433-5356전북특별자치도 진안군 부귀면 가정길 6김치류, 절임식품, 기타김치, 절임류 또는 조림류, 즉석식품류, 기타식품류2023-11-30
2주식회사 푸른생명최*란063-433-4460전북특별자치도 진안군 성수면 중길로 602영양보충용제품, 특수용도식품, 기타식품류, 규격외일반가공식품, 특수용도식품, 곡류효소함유제품, 코코아가공품류 또는 초콜릿류, 농산가공식품류2023-11-30
3송화수 홍삼 영농조합법인송*생063-433-6767전북특별자치도 진안군 부귀면 전진로 1964다류, 절임식품, 규격외일반가공식품, 음료류, 인삼 및 홍삼음료, 농산가공식품류, 기타식품류2023-11-30
4대성한과김*순063-433-3569전북특별자치도 진안군 부귀면 전진로 2423과자류, 빵류 또는 떡류2023-11-30
5마이산 인진쑥안*철063-432-2680전북특별자치도 진안군 마령면 석교길 30다류2023-11-30
6마이산약초협동조합김*숙063-432-3311전북특별자치도 진안군 마령면 서평로 187-25기타식품류, 다류, 음료류2023-11-30
7단양선교관 선교식품송*례<NA>전북특별자치도 진안군 진안읍 홍삼한방로 17과자류, 빵류 또는 떡류2023-11-30
8양지원전*성<NA>전북특별자치도 진안군 진안읍 원양지길 67-3다류2023-11-30
9진안고원농산김*은063-432-0367전북특별자치도 진안군 동향면 능금로 231-3다류, 규격외일반가공식품, 음료류2023-11-30
업소명대표자소재지전화번호소재지 도로명 주소식품유형데이터기준일자
145고원반찬2호점(진안시니어클럽)김*술063-433-2233전북특별자치도 진안군 진안읍 진장로 35수산가공식품류2023-11-30
146마이산 정과마을김*서<NA>전북특별자치도 진안군 진안읍 진용로 317-22절임류 또는 조림류2023-11-30
147(주)진앤삼생명공학연구소강*원<NA>전북특별자치도 진안군 진안읍 거북바위로1길 19-6음료류, 농산가공식품류2023-11-30
148(주)동선식품오*훈<NA>전북특별자치도 진안군 백운면 백장로 25농산가공식품류2023-11-30
149청아람영농조합법인이*원063-432-2255전북특별자치도 진안군 주천면 봉소길 19-7음료류2023-11-30
150(주)뉴트롬홍*기<NA>전북특별자치도 진안군 진안읍 홍삼한방로 21-55조미식품, 농산가공식품류, 기타식품류, 특수의료용도식품2023-11-30
151굿스팜이*홍<NA>전북특별자치도 진안군 동향면 천동로 548음료류2023-11-30
152단야푸드앤바이오황*연<NA>전북특별자치도 진안군 성수면 원좌산2길 24당류, 잼류, 음료류, 장류, 조미식품, 절임류 또는 조림류2023-11-30
153농업회사법인(주)초록앤푸드조*익<NA>전북특별자치도 진안군 진안읍 홍삼한방로 22-22음료류, 농산가공식품류2023-11-30
154농업회사법인한시골유한회사박*민<NA>전북특별자치도 진안군 진안읍 외기길 31-22음료류2023-11-30