Overview

Dataset statistics

Number of variables7
Number of observations379
Missing cells66
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.9 KiB
Average record size in memory56.3 B

Variable types

Categorical1
Text6

Dataset

Description경쟁력있는 6차사업 주체로 육성하기 위해 인증한 6차산업 예비인증 사업자 현황 정보 제공
Author농림축산식품부
URLhttps://www.data.go.kr/data/15043844/fileData.do

Alerts

연락처 has 66 (17.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 21:55:17.799446
Analysis finished2023-12-12 21:55:18.462512
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct15
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
전북
60 
전남
57 
경기
47 
경남
37 
충북
31 
Other values (10)
147 

Length

Max length4
Median length2
Mean length2.2295515
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row대전
2nd row대전
3rd row울산
4th row 경기
5th row 경기

Common Values

ValueCountFrequency (%)
전북 60
15.8%
전남 57
15.0%
경기 47
12.4%
경남 37
9.8%
충북 31
8.2%
경상북도 29
7.7%
충남 27
7.1%
제주 24
 
6.3%
경북 22
 
5.8%
강원 21
 
5.5%
Other values (5) 24
 
6.3%

Length

2023-12-13T06:55:18.551053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전북 60
15.8%
전남 57
15.0%
경기 51
13.5%
경남 37
9.8%
강원 34
9.0%
충북 31
8.2%
경상북도 29
7.7%
충남 27
7.1%
제주 24
 
6.3%
경북 22
 
5.8%
Other values (3) 7
 
1.8%

시군
Text

Distinct160
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:55:18.991112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.348285
Min length2

Characters and Unicode

Total characters890
Distinct characters95
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)16.9%

Sample

1st row서구
2nd row대덕
3rd row울주군
4th row 김포시
5th row 김포시
ValueCountFrequency (%)
서귀포 10
 
2.6%
영천시 10
 
2.6%
남양주 8
 
2.1%
고흥 8
 
2.1%
제주 7
 
1.8%
문경 7
 
1.8%
제주시 7
 
1.8%
임실군 6
 
1.6%
영광 6
 
1.6%
강진 6
 
1.6%
Other values (146) 304
80.2%
2023-12-13T06:55:19.533145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 71
 
8.0%
시 60
 
6.7%
군 48
 
5.4%
천 47
 
5.3%
양 38
 
4.3%
영 31
 
3.5%
제 25
 
2.8%
산 24
 
2.7%
성 24
 
2.7%
진 19
 
2.1%
Other values (85) 503
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 881
99.0%
Space Separator 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 71
 
8.1%
시 60
 
6.8%
군 48
 
5.4%
천 47
 
5.3%
양 38
 
4.3%
영 31
 
3.5%
제 25
 
2.8%
산 24
 
2.7%
성 24
 
2.7%
진 19
 
2.2%
Other values (84) 494
56.1%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 881
99.0%
Common 9
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 71
 
8.1%
시 60
 
6.8%
군 48
 
5.4%
천 47
 
5.3%
양 38
 
4.3%
영 31
 
3.5%
제 25
 
2.8%
산 24
 
2.7%
성 24
 
2.7%
진 19
 
2.2%
Other values (84) 494
56.1%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 881
99.0%
ASCII 9
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 71
 
8.1%
시 60
 
6.8%
군 48
 
5.4%
천 47
 
5.3%
양 38
 
4.3%
영 31
 
3.5%
제 25
 
2.8%
산 24
 
2.7%
성 24
 
2.7%
진 19
 
2.2%
Other values (84) 494
56.1%
ASCII
ValueCountFrequency (%)
9
100.0%

인증번호
Text

Distinct349
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:55:19.873305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.029024
Min length11

Characters and Unicode

Total characters4180
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

Unique319 ?
Unique (%)84.2%

Sample

1st row2014-06-001
2nd row2014-06-002
3rd row2014-07-001
4th row 2014-09-001
5th row 2014-09-002
ValueCountFrequency (%)
2014-10-015 2
 
0.5%
2014-10-018 2
 
0.5%
2014-10-019 2
 
0.5%
2014-10-016 2
 
0.5%
2014-10-030 2
 
0.5%
2014-10-014 2
 
0.5%
2014-10-029 2
 
0.5%
2014-10-013 2
 
0.5%
2014-10-009 2
 
0.5%
2014-10-010 2
 
0.5%
Other values (340) 360
94.7%
2023-12-13T06:55:20.496598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1012
24.2%
1 876
21.0%
- 757
18.1%
2 532
12.7%
4 507
12.1%
3 146
 
3.5%
9 84
 
2.0%
6 79
 
1.9%
5 77
 
1.8%
7 62
 
1.5%
Other values (2) 48
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3411
81.6%
Dash Punctuation 757
 
18.1%
Space Separator 12
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1012
29.7%
1 876
25.7%
2 532
15.6%
4 507
14.9%
3 146
 
4.3%
9 84
 
2.5%
6 79
 
2.3%
5 77
 
2.3%
7 62
 
1.8%
8 36
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 757
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1012
24.2%
1 876
21.0%
- 757
18.1%
2 532
12.7%
4 507
12.1%
3 146
 
3.5%
9 84
 
2.0%
6 79
 
1.9%
5 77
 
1.8%
7 62
 
1.5%
Other values (2) 48
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1012
24.2%
1 876
21.0%
- 757
18.1%
2 532
12.7%
4 507
12.1%
3 146
 
3.5%
9 84
 
2.0%
6 79
 
1.9%
5 77
 
1.8%
7 62
 
1.5%
Other values (2) 48
 
1.1%

법인명
Text

Distinct378
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:55:20.776462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17
Mean length9.2796834
Min length2

Characters and Unicode

Total characters3517
Distinct characters409
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique377 ?
Unique (%)99.5%

Sample

1st row베리팜
2nd row신탄진주조
3rd row신우에프티
4th row 김포파주인삼농협
5th row 김포농식품가공영농조합
ValueCountFrequency (%)
영농조합법인 55
 
10.4%
농업회사법인 32
 
6.0%
주식회사 14
 
2.6%
와이너리 7
 
1.3%
자연그대로영농조합법인 2
 
0.4%
마을 2
 
0.4%
영농법인 2
 
0.4%
㈜ 2
 
0.4%
베리팜 2
 
0.4%
디자인농부 1
 
0.2%
Other values (411) 411
77.5%
2023-12-13T06:55:21.227921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 250
 
7.1%
인 205
 
5.8%
법 193
 
5.5%
영 167
 
4.7%
159
 
4.5%
조 155
 
4.4%
합 143
 
4.1%
사 96
 
2.7%
회 77
 
2.2%
업 62
 
1.8%
Other values (399) 2010
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3260
92.7%
Space Separator 159
 
4.5%
Other Symbol 44
 
1.3%
Close Punctuation 23
 
0.7%
Open Punctuation 22
 
0.6%
Uppercase Letter 3
 
0.1%
Lowercase Letter 2
 
0.1%
Decimal Number 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 250
 
7.7%
인 205
 
6.3%
법 193
 
5.9%
영 167
 
5.1%
조 155
 
4.8%
합 143
 
4.4%
사 96
 
2.9%
회 77
 
2.4%
업 62
 
1.9%
주 61
 
1.9%
Other values (388) 1851
56.8%
Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
F 1
33.3%
B 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
159
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3304
93.9%
Common 208
 
5.9%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 250
 
7.6%
인 205
 
6.2%
법 193
 
5.8%
영 167
 
5.1%
조 155
 
4.7%
합 143
 
4.3%
사 96
 
2.9%
회 77
 
2.3%
업 62
 
1.9%
주 61
 
1.8%
Other values (389) 1895
57.4%
Common
ValueCountFrequency (%)
159
76.4%
) 23
 
11.1%
( 22
 
10.6%
2 2
 
1.0%
, 1
 
0.5%
& 1
 
0.5%
Latin
ValueCountFrequency (%)
e 2
40.0%
W 1
20.0%
F 1
20.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3260
92.7%
ASCII 213
 
6.1%
None 44
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 250
 
7.7%
인 205
 
6.3%
법 193
 
5.9%
영 167
 
5.1%
조 155
 
4.8%
합 143
 
4.4%
사 96
 
2.9%
회 77
 
2.4%
업 62
 
1.9%
주 61
 
1.9%
Other values (388) 1851
56.8%
ASCII
ValueCountFrequency (%)
159
74.6%
) 23
 
10.8%
( 22
 
10.3%
e 2
 
0.9%
2 2
 
0.9%
W 1
 
0.5%
, 1
 
0.5%
F 1
 
0.5%
& 1
 
0.5%
B 1
 
0.5%
None
ValueCountFrequency (%)
㈜ 44
100.0%

성명
Text

Distinct372
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:55:21.606561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.055409
Min length2

Characters and Unicode

Total characters1158
Distinct characters173
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

Unique365 ?
Unique (%)96.3%

Sample

1st row박미숙
2nd row유황철
3rd row김종화
4th row 조재열
5th row 배효원
ValueCountFrequency (%)
김금순 2
 
0.5%
김재식 2
 
0.5%
권윤주 2
 
0.5%
김정숙 2
 
0.5%
이정희 2
 
0.5%
서광복 2
 
0.5%
김숙희 2
 
0.5%
김영숙 2
 
0.5%
박재숙 1
 
0.3%
신병용 1
 
0.3%
Other values (366) 366
95.3%
2023-12-13T06:55:22.166866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 78
 
6.7%
이 47
 
4.1%
정 46
 
4.0%
영 32
 
2.8%
순 22
 
1.9%
박 22
 
1.9%
수 22
 
1.9%
재 22
 
1.9%
숙 19
 
1.6%
조 19
 
1.6%
Other values (163) 829
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1141
98.5%
Space Separator 14
 
1.2%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 78
 
6.8%
이 47
 
4.1%
정 46
 
4.0%
영 32
 
2.8%
순 22
 
1.9%
박 22
 
1.9%
수 22
 
1.9%
재 22
 
1.9%
숙 19
 
1.7%
조 19
 
1.7%
Other values (160) 812
71.2%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1141
98.5%
Common 17
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 78
 
6.8%
이 47
 
4.1%
정 46
 
4.0%
영 32
 
2.8%
순 22
 
1.9%
박 22
 
1.9%
수 22
 
1.9%
재 22
 
1.9%
숙 19
 
1.7%
조 19
 
1.7%
Other values (160) 812
71.2%
Common
ValueCountFrequency (%)
14
82.4%
, 2
 
11.8%
/ 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1141
98.5%
ASCII 17
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 78
 
6.8%
이 47
 
4.1%
정 46
 
4.0%
영 32
 
2.8%
순 22
 
1.9%
박 22
 
1.9%
수 22
 
1.9%
재 22
 
1.9%
숙 19
 
1.7%
조 19
 
1.7%
Other values (160) 812
71.2%
ASCII
ValueCountFrequency (%)
14
82.4%
, 2
 
11.8%
/ 1
 
5.9%

연락처
Text

MISSING 

Distinct312
Distinct (%)99.7%
Missing66
Missing (%)17.4%
Memory size3.1 KiB
2023-12-13T06:55:22.404688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.054313
Min length12

Characters and Unicode

Total characters3773
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

Unique311 ?
Unique (%)99.4%

Sample

1st row052-264-9332
2nd row031-996-0021
3rd row070-4406-7974
4th row070-4118-5352
5th row031-356-8144
ValueCountFrequency (%)
063-243-7009 2
 
0.6%
063-244-0684 1
 
0.3%
063-351-5847 1
 
0.3%
063-351-3500 1
 
0.3%
063-351-8300 1
 
0.3%
063-644-8821 1
 
0.3%
063-246-8848 1
 
0.3%
063-247-0243 1
 
0.3%
061-363-5060 1
 
0.3%
063-653-6610 1
 
0.3%
Other values (302) 302
96.5%
2023-12-13T06:55:22.779438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 626
16.6%
0 541
14.3%
3 477
12.6%
5 365
9.7%
4 345
9.1%
6 330
8.7%
1 271
7.2%
2 239
 
6.3%
8 230
 
6.1%
7 209
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3147
83.4%
Dash Punctuation 626
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 541
17.2%
3 477
15.2%
5 365
11.6%
4 345
11.0%
6 330
10.5%
1 271
8.6%
2 239
7.6%
8 230
7.3%
7 209
 
6.6%
9 140
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 626
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 626
16.6%
0 541
14.3%
3 477
12.6%
5 365
9.7%
4 345
9.1%
6 330
8.7%
1 271
7.2%
2 239
 
6.3%
8 230
 
6.1%
7 209
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 626
16.6%
0 541
14.3%
3 477
12.6%
5 365
9.7%
4 345
9.1%
6 330
8.7%
1 271
7.2%
2 239
 
6.3%
8 230
 
6.1%
7 209
 
5.5%

소재지(전체 주소 작성)
Text

Distinct378
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:55:23.088507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length23.538259
Min length12

Characters and Unicode

Total characters8921
Distinct characters290
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique377 ?
Unique (%)99.5%

Sample

1st row대전광역시 서구 계백로 776번길 154
2nd row대전광역시 대덕구 신탄진로 583번길 41
3rd row울산시 울주군 두서면 미호리 825-4 신우목장내 신우에프티
4th row 경기도 김포시 대곶면 대명리 391
5th row 경기도 김포시 월곶명 오리정로 13 푸드센터 내
ValueCountFrequency (%)
전북 60
 
2.9%
경북 46
 
2.3%
경남 34
 
1.7%
경기도 27
 
1.3%
강원도 27
 
1.3%
충남 25
 
1.2%
충청북도 20
 
1.0%
제주특별자치도 19
 
0.9%
문경시 15
 
0.7%
제주시 14
 
0.7%
Other values (1247) 1755
85.9%
2023-12-13T06:55:23.530201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1678
 
18.8%
1 355
 
4.0%
면 314
 
3.5%
군 245
 
2.7%
2 223
 
2.5%
시 214
 
2.4%
- 202
 
2.3%
북 202
 
2.3%
3 200
 
2.2%
길 180
 
2.0%
Other values (280) 5108
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5233
58.7%
Space Separator 1678
 
18.8%
Decimal Number 1654
 
18.5%
Dash Punctuation 202
 
2.3%
Close Punctuation 77
 
0.9%
Open Punctuation 77
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 314
 
6.0%
군 245
 
4.7%
시 214
 
4.1%
북 202
 
3.9%
길 180
 
3.4%
로 173
 
3.3%
경 168
 
3.2%
리 139
 
2.7%
주 125
 
2.4%
남 122
 
2.3%
Other values (266) 3351
64.0%
Decimal Number
ValueCountFrequency (%)
1 355
21.5%
2 223
13.5%
3 200
12.1%
5 159
9.6%
4 156
9.4%
7 131
 
7.9%
6 121
 
7.3%
0 113
 
6.8%
8 112
 
6.8%
9 84
 
5.1%
Space Separator
ValueCountFrequency (%)
1678
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5233
58.7%
Common 3688
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 314
 
6.0%
군 245
 
4.7%
시 214
 
4.1%
북 202
 
3.9%
길 180
 
3.4%
로 173
 
3.3%
경 168
 
3.2%
리 139
 
2.7%
주 125
 
2.4%
남 122
 
2.3%
Other values (266) 3351
64.0%
Common
ValueCountFrequency (%)
1678
45.5%
1 355
 
9.6%
2 223
 
6.0%
- 202
 
5.5%
3 200
 
5.4%
5 159
 
4.3%
4 156
 
4.2%
7 131
 
3.6%
6 121
 
3.3%
0 113
 
3.1%
Other values (4) 350
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5233
58.7%
ASCII 3688
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1678
45.5%
1 355
 
9.6%
2 223
 
6.0%
- 202
 
5.5%
3 200
 
5.4%
5 159
 
4.3%
4 156
 
4.2%
7 131
 
3.6%
6 121
 
3.3%
0 113
 
3.1%
Other values (4) 350
 
9.5%
Hangul
ValueCountFrequency (%)
면 314
 
6.0%
군 245
 
4.7%
시 214
 
4.1%
북 202
 
3.9%
길 180
 
3.4%
로 173
 
3.3%
경 168
 
3.2%
리 139
 
2.7%
주 125
 
2.4%
남 122
 
2.3%
Other values (266) 3351
64.0%

Missing values

2023-12-13T06:55:18.303411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:55:18.415477image/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

시도시군인증번호법인명성명연락처소재지(전체 주소 작성)
0대전서구2014-06-001베리팜박미숙<NA>대전광역시 서구 계백로 776번길 154
1대전대덕2014-06-002신탄진주조유황철<NA>대전광역시 대덕구 신탄진로 583번길 41
2울산울주군2014-07-001신우에프티김종화052-264-9332울산시 울주군 두서면 미호리 825-4 신우목장내 신우에프티
3경기김포시2014-09-001김포파주인삼농협조재열031-996-0021경기도 김포시 대곶면 대명리 391
4경기김포시2014-09-002김포농식품가공영농조합배효원070-4406-7974경기도 김포시 월곶명 오리정로 13 푸드센터 내
5경기김포시2014-09-003꿈목장이윤재070-4118-5352경기도 김포시 통진읍 귀전로 56번길 187
6경기화성시2014-09-004호트팜이영자031-356-8144경기도 화성시 서신면 은수포길 102
7경기화성시2014-09-005또나따목장양의주031-356-1602경기도 화성시 마도면 백곡리 563-5
8경기고양시2014-09-006한국상황버섯김현수070-7556-8565경기도 고양시 일산서구 덕이로 132-27
9경기파주시2014-09-007장단콩청정식품이완배070-4178-2680경기도 파주시 군내면 통일촌길 217(백연리 480-44)
시도시군인증번호법인명성명연락처소재지(전체 주소 작성)
369제주제주2014-17-015농업회사법인 주식회사 오제주최우식064-712-2429제주특별자치도 제주시 애월읍 평화로 2507
370제주제주2014-17-016㈜제주아가최창권064-751-8880제주특별자치도 제주시 죽성서길 7-10
371제주서귀포2014-17-017농업회사법인 주식회사 갈중이김두경064-794-1686제주특별자치도 서귀포시 안덕면 사계리 216번길 24-61
372제주서귀포2014-17-018농업회사법인 ㈜태반의땅 제주김명수064-732-8885제주특별자치도 서귀포시 토평로 50번길 31
373제주서귀포2014-17-019더푸른채영농조합법인황영호064-783-1380제주특별자치도 서귀포시 성산읍 시흥상동로 53번길 415
374제주서귀포2014-17-020휴럼백순옥070-8896-4660제주특별자치도 서귀포시 남원읍 신례동로 121-17
375제주서귀포2014-17-021귤향영농조합법인오화자<NA>제주특별자치도 서귀포시 신효로7
376제주서귀포2014-17-022영농조합법인 한라산청정촌박영희064-738-7778제주특별자치도 서귀포시 중산간서로 740
377제주서귀포2014-17-023양춘선식품양춘선064-794-9466제주특별시 서귀포시 안덕면 감산리 1430
378제주서귀포2014-17-024최남단체험감귤농장오창학064-764-7759제주특별시 서귀포시 남원읍 남원리 2019