Overview

Dataset statistics

Number of variables9
Number of observations53
Missing cells9
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory74.5 B

Variable types

Categorical3
Text4
Boolean2

Dataset

Description2011년말 기준으로 조사된 시도별 농축산물 공동브랜드 현황
Author농림축산식품부
URLhttps://www.data.go.kr/data/15055114/fileData.do

Alerts

브랜드소유자 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 브랜드소유자 and 1 other fieldsHigh correlation
신규여부 is highly overall correlated with 시군High correlation
신규여부 is highly imbalanced (86.5%)Imbalance
등록번호 has 9 (17.0%) missing valuesMissing
브랜드명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:59:32.203460
Analysis finished2023-12-12 10:59:33.530504
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
괴산군
16 
음성군
10 
청주시
5 
진천군
4 
충주시
3 
Other values (8)
15 

Length

Max length4
Median length3
Mean length3.0188679
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
괴산군 16
30.2%
음성군 10
18.9%
청주시 5
 
9.4%
진천군 4
 
7.5%
충주시 3
 
5.7%
청원군 3
 
5.7%
제천시 2
 
3.8%
보은군 2
 
3.8%
옥천군 2
 
3.8%
영동군 2
 
3.8%
Other values (3) 4
 
7.5%

Length

2023-12-12T19:59:33.669216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
괴산군 16
30.2%
음성군 10
18.9%
청주시 5
 
9.4%
진천군 4
 
7.5%
충주시 3
 
5.7%
청원군 3
 
5.7%
제천시 2
 
3.8%
보은군 2
 
3.8%
옥천군 2
 
3.8%
영동군 2
 
3.8%
Other values (3) 4
 
7.5%

브랜드명
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T19:59:34.004529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.7735849
Min length2

Characters and Unicode

Total characters253
Distinct characters121
Distinct categories4 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st row용바위골
2nd row뻘국산
3rd row부모산
4th row매봉산
5th row원마루
ValueCountFrequency (%)
괴산 2
 
3.5%
임꺽정 2
 
3.5%
괴산군자산농특산물 1
 
1.8%
괴산청결고추 1
 
1.8%
괴산고추 1
 
1.8%
고추잠자리 1
 
1.8%
문광꿀배 1
 
1.8%
연풍사과 1
 
1.8%
장연사과 1
 
1.8%
화양계곡 1
 
1.8%
Other values (45) 45
78.9%
2023-12-12T19:59:34.521705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 17
 
6.7%
괴 9
 
3.6%
고 8
 
3.2%
진 8
 
3.2%
성 8
 
3.2%
미 7
 
2.8%
추 6
 
2.4%
청 6
 
2.4%
자 5
 
2.0%
5
 
2.0%
Other values (111) 174
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
96.0%
Space Separator 5
 
2.0%
Lowercase Letter 3
 
1.2%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 17
 
7.0%
괴 9
 
3.7%
고 8
 
3.3%
진 8
 
3.3%
성 8
 
3.3%
미 7
 
2.9%
추 6
 
2.5%
청 6
 
2.5%
자 5
 
2.1%
음 5
 
2.1%
Other values (105) 164
67.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
e 1
33.3%
y 1
33.3%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 241
95.3%
Common 7
 
2.8%
Latin 3
 
1.2%
Han 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 17
 
7.1%
괴 9
 
3.7%
고 8
 
3.3%
진 8
 
3.3%
성 8
 
3.3%
미 7
 
2.9%
추 6
 
2.5%
청 6
 
2.5%
자 5
 
2.1%
음 5
 
2.1%
Other values (104) 162
67.2%
Common
ValueCountFrequency (%)
5
71.4%
0 1
 
14.3%
3 1
 
14.3%
Latin
ValueCountFrequency (%)
s 1
33.3%
e 1
33.3%
y 1
33.3%
Han
ValueCountFrequency (%)
米 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 241
95.3%
ASCII 10
 
4.0%
CJK 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 17
 
7.1%
괴 9
 
3.7%
고 8
 
3.3%
진 8
 
3.3%
성 8
 
3.3%
미 7
 
2.9%
추 6
 
2.5%
청 6
 
2.5%
자 5
 
2.1%
음 5
 
2.1%
Other values (104) 162
67.2%
ASCII
ValueCountFrequency (%)
5
50.0%
s 1
 
10.0%
e 1
 
10.0%
y 1
 
10.0%
0 1
 
10.0%
3 1
 
10.0%
CJK
ValueCountFrequency (%)
米 2
100.0%

브랜드소유자
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)37.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
괴산군수
11 
음성군수
9 
청주시장
5 
진천군수
4 
청원군수
3 
Other values (15)
21 

Length

Max length12
Median length4
Mean length4.8490566
Min length3

Unique

Unique9 ?
Unique (%)17.0%

Sample

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

Common Values

ValueCountFrequency (%)
괴산군수 11
20.8%
음성군수 9
17.0%
청주시장 5
9.4%
진천군수 4
 
7.5%
청원군수 3
 
5.7%
영동군수 2
 
3.8%
증평군수 2
 
3.8%
괴산고추생산자협의회 2
 
3.8%
옥천군수 2
 
3.8%
보은군 2
 
3.8%
Other values (10) 11
20.8%

Length

2023-12-12T19:59:34.751950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
괴산군수 11
20.8%
음성군수 9
17.0%
청주시장 5
9.4%
진천군수 4
 
7.5%
청원군수 3
 
5.7%
옥천군수 2
 
3.8%
보은군 2
 
3.8%
제천시장 2
 
3.8%
괴산고추생산자협의회 2
 
3.8%
증평군수 2
 
3.8%
Other values (10) 11
20.8%

브랜드사용자
Text

Distinct38
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T19:59:35.004723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length9.6415094
Min length3

Characters and Unicode

Total characters511
Distinct characters115
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)62.3%

Sample

1st row용암포도작목반
2nd row뻘국산작목반
3rd row부모산작목반
4th row매봉산작목반
5th row원마루작목반
ValueCountFrequency (%)
생산자단체 8
 
9.9%
음성군 6
 
7.4%
농협 5
 
6.2%
rpc 5
 
6.2%
등 5
 
6.2%
진천농협통합 3
 
3.7%
및 3
 
3.7%
작목반 3
 
3.7%
생산자 2
 
2.5%
영농조합법인 2
 
2.5%
Other values (38) 39
48.1%
2023-12-12T19:59:35.453300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 29
 
5.7%
29
 
5.7%
협 27
 
5.3%
농 24
 
4.7%
생 21
 
4.1%
자 19
 
3.7%
단 15
 
2.9%
, 14
 
2.7%
합 14
 
2.7%
회 12
 
2.3%
Other values (105) 307
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 452
88.5%
Space Separator 29
 
5.7%
Uppercase Letter 15
 
2.9%
Other Punctuation 14
 
2.7%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 29
 
6.4%
협 27
 
6.0%
농 24
 
5.3%
생 21
 
4.6%
자 19
 
4.2%
단 15
 
3.3%
합 14
 
3.1%
회 12
 
2.7%
작 10
 
2.2%
인 10
 
2.2%
Other values (99) 271
60.0%
Uppercase Letter
ValueCountFrequency (%)
C 5
33.3%
P 5
33.3%
R 5
33.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 452
88.5%
Common 44
 
8.6%
Latin 15
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 29
 
6.4%
협 27
 
6.0%
농 24
 
5.3%
생 21
 
4.6%
자 19
 
4.2%
단 15
 
3.3%
합 14
 
3.1%
회 12
 
2.7%
작 10
 
2.2%
인 10
 
2.2%
Other values (99) 271
60.0%
Common
ValueCountFrequency (%)
29
65.9%
, 14
31.8%
) 1
 
2.3%
Latin
ValueCountFrequency (%)
C 5
33.3%
P 5
33.3%
R 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 452
88.5%
ASCII 59
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 29
 
6.4%
협 27
 
6.0%
농 24
 
5.3%
생 21
 
4.6%
자 19
 
4.2%
단 15
 
3.3%
합 14
 
3.1%
회 12
 
2.7%
작 10
 
2.2%
인 10
 
2.2%
Other values (99) 271
60.0%
ASCII
ValueCountFrequency (%)
29
49.2%
, 14
23.7%
C 5
 
8.5%
P 5
 
8.5%
R 5
 
8.5%
) 1
 
1.7%

부류명
Categorical

Distinct9
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
공통
13 
식량작물
12 
과실류
7 
과채류
7 
축산물
5 
Other values (4)
9 

Length

Max length4
Median length3
Mean length3.0566038
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row과실류
2nd row식량작물
3rd row과채류
4th row과채류
5th row채소류

Common Values

ValueCountFrequency (%)
공통 13
24.5%
식량작물 12
22.6%
과실류 7
13.2%
과채류 7
13.2%
축산물 5
 
9.4%
농산가공 4
 
7.5%
채소류 2
 
3.8%
임산물 2
 
3.8%
특작류 1
 
1.9%

Length

2023-12-12T19:59:35.654768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:59:35.857445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공통 13
24.5%
식량작물 12
22.6%
과실류 7
13.2%
과채류 7
13.2%
축산물 5
 
9.4%
농산가공 4
 
7.5%
채소류 2
 
3.8%
임산물 2
 
3.8%
특작류 1
 
1.9%

주품목
Text

Distinct29
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T19:59:36.070687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length2.2830189
Min length1

Characters and Unicode

Total characters121
Distinct characters61
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

Unique22 ?
Unique (%)41.5%

Sample

1st row포도
2nd row고구마
3rd row토마토
4th row토마토
5th row열무
ValueCountFrequency (%)
쌀 14
25.9%
고추 5
 
9.3%
포도 3
 
5.6%
사과 3
 
5.6%
토마토 2
 
3.7%
한우 2
 
3.7%
복숭아 2
 
3.7%
혼합곡 1
 
1.9%
절임배추 1
 
1.9%
배 1
 
1.9%
Other values (20) 20
37.0%
2023-12-12T19:59:36.935328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
쌀 14
 
11.6%
추 9
 
7.4%
고 9
 
7.4%
과 5
 
4.1%
포 4
 
3.3%
토 4
 
3.3%
마 4
 
3.3%
도 3
 
2.5%
사 3
 
2.5%
한 3
 
2.5%
Other values (51) 63
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
96.7%
Open Punctuation 1
 
0.8%
Other Punctuation 1
 
0.8%
Space Separator 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 14
 
12.0%
추 9
 
7.7%
고 9
 
7.7%
과 5
 
4.3%
포 4
 
3.4%
토 4
 
3.4%
마 4
 
3.4%
도 3
 
2.6%
사 3
 
2.6%
한 3
 
2.6%
Other values (47) 59
50.4%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
96.7%
Common 4
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 14
 
12.0%
추 9
 
7.7%
고 9
 
7.7%
과 5
 
4.3%
포 4
 
3.4%
토 4
 
3.4%
마 4
 
3.4%
도 3
 
2.6%
사 3
 
2.6%
한 3
 
2.6%
Other values (47) 59
50.4%
Common
ValueCountFrequency (%)
( 1
25.0%
, 1
25.0%
1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
96.7%
ASCII 4
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
쌀 14
 
12.0%
추 9
 
7.7%
고 9
 
7.7%
과 5
 
4.3%
포 4
 
3.4%
토 4
 
3.4%
마 4
 
3.4%
도 3
 
2.6%
사 3
 
2.6%
한 3
 
2.6%
Other values (47) 59
50.4%
ASCII
ValueCountFrequency (%)
( 1
25.0%
, 1
25.0%
1
25.0%
) 1
25.0%

등록여부
Boolean

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size185.0 B
True
44 
False
9 
ValueCountFrequency (%)
True 44
83.0%
False 9
 
17.0%
2023-12-12T19:59:37.100324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록번호
Text

MISSING 

Distinct43
Distinct (%)97.7%
Missing9
Missing (%)17.0%
Memory size556.0 B
2023-12-12T19:59:37.434448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length11.5
Min length10

Characters and Unicode

Total characters506
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st row40-0478667
2nd row40-0478671
3rd row40-0478669
4th row40-0478670
5th row40-0478668
ValueCountFrequency (%)
외 5
 
9.1%
2건 3
 
5.5%
40-0518149 2
 
3.6%
40-0529483 1
 
1.8%
40-0592070 1
 
1.8%
40-1998-0031965 1
 
1.8%
40-1998-0031961 1
 
1.8%
40-1998-0031960 1
 
1.8%
50-2010-0004074 1
 
1.8%
40-1798-0031959 1
 
1.8%
Other values (38) 38
69.1%
2023-12-12T19:59:38.052451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 113
22.3%
4 71
14.0%
- 52
10.3%
9 40
 
7.9%
1 36
 
7.1%
2 33
 
6.5%
8 30
 
5.9%
7 29
 
5.7%
6 25
 
4.9%
5 25
 
4.9%
Other values (11) 52
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 425
84.0%
Dash Punctuation 52
 
10.3%
Other Letter 18
 
3.6%
Space Separator 11
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 113
26.6%
4 71
16.7%
9 40
 
9.4%
1 36
 
8.5%
2 33
 
7.8%
8 30
 
7.1%
7 29
 
6.8%
6 25
 
5.9%
5 25
 
5.9%
3 23
 
5.4%
Other Letter
ValueCountFrequency (%)
외 5
27.8%
건 5
27.8%
제 2
 
11.1%
지 1
 
5.6%
리 1
 
5.6%
적 1
 
5.6%
표 1
 
5.6%
시 1
 
5.6%
호 1
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488
96.4%
Hangul 18
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 113
23.2%
4 71
14.5%
- 52
10.7%
9 40
 
8.2%
1 36
 
7.4%
2 33
 
6.8%
8 30
 
6.1%
7 29
 
5.9%
6 25
 
5.1%
5 25
 
5.1%
Other values (2) 34
 
7.0%
Hangul
ValueCountFrequency (%)
외 5
27.8%
건 5
27.8%
제 2
 
11.1%
지 1
 
5.6%
리 1
 
5.6%
적 1
 
5.6%
표 1
 
5.6%
시 1
 
5.6%
호 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488
96.4%
Hangul 18
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 113
23.2%
4 71
14.5%
- 52
10.7%
9 40
 
8.2%
1 36
 
7.4%
2 33
 
6.8%
8 30
 
6.1%
7 29
 
5.9%
6 25
 
5.1%
5 25
 
5.1%
Other values (2) 34
 
7.0%
Hangul
ValueCountFrequency (%)
외 5
27.8%
건 5
27.8%
제 2
 
11.1%
지 1
 
5.6%
리 1
 
5.6%
적 1
 
5.6%
표 1
 
5.6%
시 1
 
5.6%
호 1
 
5.6%

신규여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size185.0 B
False
52 
True
 
1
ValueCountFrequency (%)
False 52
98.1%
True 1
 
1.9%
2023-12-12T19:59:38.259694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:59:38.390688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군브랜드명브랜드소유자브랜드사용자부류명주품목등록여부등록번호신규여부
시군1.0001.0001.0001.0000.0000.7540.3041.0000.620
브랜드명1.0001.0001.0001.0001.0001.0001.0001.0001.000
브랜드소유자1.0001.0001.0001.0000.4910.8260.7431.0000.569
브랜드사용자1.0001.0001.0001.0000.0000.5770.6210.9891.000
부류명0.0001.0000.4910.0001.0000.9740.2071.0000.000
주품목0.7541.0000.8260.5770.9741.0000.5061.0000.000
등록여부0.3041.0000.7430.6210.2070.5061.000NaN0.000
등록번호1.0001.0001.0000.9891.0001.000NaN1.0001.000
신규여부0.6201.0000.5691.0000.0000.0000.0001.0001.000
2023-12-12T19:59:38.586918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
브랜드소유자부류명신규여부등록여부시군
브랜드소유자1.0000.1670.3570.4810.908
부류명0.1671.0000.0000.1840.000
신규여부0.3570.0001.0000.0000.514
등록여부0.4810.1840.0001.0000.242
시군0.9080.0000.5140.2421.000
2023-12-12T19:59:38.751811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군브랜드소유자부류명등록여부신규여부
시군1.0000.9080.0000.2420.514
브랜드소유자0.9081.0000.1670.4810.357
부류명0.0000.1671.0000.1840.000
등록여부0.2420.4810.1841.0000.000
신규여부0.5140.3570.0000.0001.000

Missing values

2023-12-12T19:59:33.172442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:59:33.429003image/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

시군브랜드명브랜드소유자브랜드사용자부류명주품목등록여부등록번호신규여부
0청주시용바위골청주시장용암포도작목반과실류포도Y40-0478667N
1청주시뻘국산청주시장뻘국산작목반식량작물고구마Y40-0478671N
2청주시부모산청주시장부모산작목반과채류토마토Y40-0478669N
3청주시매봉산청주시장매봉산작목반과채류토마토Y40-0478670N
4청주시원마루청주시장원마루작목반채소류열무Y40-0478668N
5충주시충주밤충주시장충주밤생산자협회임산물밤N<NA>N
6충주시하늘작농협중앙회앙성농협, 앙성복숭아작목반과실류복숭아Y40-0039222N
7충주시충주미소진쌀충주시농협쌀조합공동법인충주시농협쌀조합공동사업법인식량작물쌀Y40-0055993N
8제천시맛달재제천시장영농조합법인 및 작목반 등공통사과Y40-0554711N
9제천시자연인제천시장영농조합법인 및 작목반 등임산물약초Y40-0729268N
시군브랜드명브랜드소유자브랜드사용자부류명주품목등록여부등록번호신규여부
43음성군감곡미백쌀음성군수감곡농협식량작물쌀Y40-0463238N
44음성군음성고추계란음성군수음성군축산물건조란Y40-2003-54523N
45음성군다올찬음성군수농협중앙회음성군지부공통쌀Y40-2003-28271N
46음성군햇사레햇사레과일조합공동법인햇사레연합단과실류복숭아Y40-0592164N
47음성군음성진미전통고추장음성군수음성군농산가공고추장Y40-0289130N
48음성군한금령벌꿀음성군수음성군축산물벌꿀Y40-0592070N
49음성군음성청결고춧가루음성군수음성군농산가공고춧가루Y40-0529483N
50음성군음성청결한우음성군수음성군축산물한우N<NA>N
51단양군단고을단양군수농협,단고을연합사업단,친환경단체공통마늘Y40-0701286N
52충청북도청풍명월한우도지사청풍명월한우클러스터사업단축산물한우Y40-0732458 외 1건N