Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory82.7 B

Variable types

Numeric2
Text4
Categorical3

Dataset

Description보성군 관내 보성녹차에 대하여 품질을 군수가 인증한 업체 현황에 대한 공공데이터로 업체명, 대표자, 주소 등의 정보를 제공하고 있습니다.
Author전라남도 보성군
URLhttps://www.data.go.kr/data/3069059/fileData.do

Alerts

세작 is highly overall correlated with 계High correlation
계 is highly overall correlated with 세작High correlation
곡우 is highly imbalanced (74.2%)Imbalance
연번 has unique valuesUnique
업체명 has unique valuesUnique
대표자 has unique valuesUnique
주소 has unique valuesUnique
인증번호 has unique valuesUnique
세작 has 9 (39.1%) zerosZeros

Reproduction

Analysis started2023-12-12 20:28:43.880550
Analysis finished2023-12-12 20:28:45.040868
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T05:28:45.101734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-13T05:28:45.223479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

업체명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:28:45.419866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.8695652
Min length2

Characters and Unicode

Total characters158
Distinct characters60
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row보림제다영농조합법인
2nd row농업회사법인㈜보향다원
3rd row케일리 티 가든
4th row청우다원
5th row몽중산다원영농조합법인
ValueCountFrequency (%)
영농조합법인 2
 
7.4%
보림제다영농조합법인 1
 
3.7%
농)보성녹차선다원 1
 
3.7%
옥수다향 1
 
3.7%
죽림다원 1
 
3.7%
백록다원 1
 
3.7%
춘파다원 1
 
3.7%
신옥로제다 1
 
3.7%
운해다원 1
 
3.7%
소아다원 1
 
3.7%
Other values (16) 16
59.3%
2023-12-13T05:28:45.760190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
다 19
 
12.0%
원 13
 
8.2%
농 8
 
5.1%
보 7
 
4.4%
법 7
 
4.4%
인 7
 
4.4%
영 6
 
3.8%
성 5
 
3.2%
제 5
 
3.2%
조 5
 
3.2%
Other values (50) 76
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
94.3%
Space Separator 4
 
2.5%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 19
 
12.8%
원 13
 
8.7%
농 8
 
5.4%
보 7
 
4.7%
법 7
 
4.7%
인 7
 
4.7%
영 6
 
4.0%
성 5
 
3.4%
제 5
 
3.4%
조 5
 
3.4%
Other values (46) 67
45.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
94.9%
Common 8
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 19
 
12.7%
원 13
 
8.7%
농 8
 
5.3%
보 7
 
4.7%
법 7
 
4.7%
인 7
 
4.7%
영 6
 
4.0%
성 5
 
3.3%
제 5
 
3.3%
조 5
 
3.3%
Other values (47) 68
45.3%
Common
ValueCountFrequency (%)
4
50.0%
( 2
25.0%
) 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
94.3%
ASCII 8
 
5.1%
None 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
다 19
 
12.8%
원 13
 
8.7%
농 8
 
5.4%
보 7
 
4.7%
법 7
 
4.7%
인 7
 
4.7%
영 6
 
4.0%
성 5
 
3.4%
제 5
 
3.4%
조 5
 
3.4%
Other values (46) 67
45.0%
ASCII
ValueCountFrequency (%)
4
50.0%
( 2
25.0%
) 2
25.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:28:45.950748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9565217
Min length2

Characters and Unicode

Total characters68
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row임광철
2nd row최영기
3rd row이수진
4th row안명순
5th row정경완
ValueCountFrequency (%)
임광철 1
 
4.3%
변국섭 1
 
4.3%
손용 1
 
4.3%
장순재 1
 
4.3%
정혜영 1
 
4.3%
김향선 1
 
4.3%
조현부 1
 
4.3%
이순금 1
 
4.3%
최명혜 1
 
4.3%
윤영숙 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T05:28:46.264193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 5
 
7.4%
최 4
 
5.9%
순 4
 
5.9%
수 3
 
4.4%
정 3
 
4.4%
조 2
 
2.9%
현 2
 
2.9%
섭 2
 
2.9%
이 2
 
2.9%
혜 2
 
2.9%
Other values (37) 39
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 5
 
7.4%
최 4
 
5.9%
순 4
 
5.9%
수 3
 
4.4%
정 3
 
4.4%
조 2
 
2.9%
현 2
 
2.9%
섭 2
 
2.9%
이 2
 
2.9%
혜 2
 
2.9%
Other values (37) 39
57.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 5
 
7.4%
최 4
 
5.9%
순 4
 
5.9%
수 3
 
4.4%
정 3
 
4.4%
조 2
 
2.9%
현 2
 
2.9%
섭 2
 
2.9%
이 2
 
2.9%
혜 2
 
2.9%
Other values (37) 39
57.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 5
 
7.4%
최 4
 
5.9%
순 4
 
5.9%
수 3
 
4.4%
정 3
 
4.4%
조 2
 
2.9%
현 2
 
2.9%
섭 2
 
2.9%
이 2
 
2.9%
혜 2
 
2.9%
Other values (37) 39
57.4%

주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:28:46.459806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.565217
Min length19

Characters and Unicode

Total characters496
Distinct characters63
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

Unique23 ?
Unique (%)100.0%

Sample

1st row전라남도 보성군 보성읍 자세길 36-41
2nd row전라남도 보성군 보성읍 동암1길 144
3rd row전라남도 보성군 보성읍 사동길 35
4th row전라남도 보성군 보성읍 사동길 52-2
5th row전라남도 보성군 보성읍 녹차로 831
ValueCountFrequency (%)
전라남도 23
20.0%
보성군 23
20.0%
회천면 11
 
9.6%
보성읍 6
 
5.2%
녹차로 5
 
4.3%
사동길 2
 
1.7%
미력면 2
 
1.7%
영천길 2
 
1.7%
노동면 2
 
1.7%
588-66 1
 
0.9%
Other values (38) 38
33.0%
2023-12-13T05:28:46.785645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
18.5%
보 29
 
5.8%
성 29
 
5.8%
전 23
 
4.6%
남 23
 
4.6%
도 23
 
4.6%
군 23
 
4.6%
라 23
 
4.6%
면 17
 
3.4%
- 17
 
3.4%
Other values (53) 197
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
61.9%
Space Separator 92
 
18.5%
Decimal Number 80
 
16.1%
Dash Punctuation 17
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 29
 
9.4%
성 29
 
9.4%
전 23
 
7.5%
남 23
 
7.5%
도 23
 
7.5%
군 23
 
7.5%
라 23
 
7.5%
면 17
 
5.5%
길 16
 
5.2%
천 14
 
4.6%
Other values (41) 87
28.3%
Decimal Number
ValueCountFrequency (%)
1 13
16.2%
6 12
15.0%
2 12
15.0%
3 10
12.5%
8 8
10.0%
4 7
8.8%
5 7
8.8%
7 5
 
6.2%
9 3
 
3.8%
0 3
 
3.8%
Space Separator
ValueCountFrequency (%)
92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
61.9%
Common 189
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 29
 
9.4%
성 29
 
9.4%
전 23
 
7.5%
남 23
 
7.5%
도 23
 
7.5%
군 23
 
7.5%
라 23
 
7.5%
면 17
 
5.5%
길 16
 
5.2%
천 14
 
4.6%
Other values (41) 87
28.3%
Common
ValueCountFrequency (%)
92
48.7%
- 17
 
9.0%
1 13
 
6.9%
6 12
 
6.3%
2 12
 
6.3%
3 10
 
5.3%
8 8
 
4.2%
4 7
 
3.7%
5 7
 
3.7%
7 5
 
2.6%
Other values (2) 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
61.9%
ASCII 189
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
48.7%
- 17
 
9.0%
1 13
 
6.9%
6 12
 
6.3%
2 12
 
6.3%
3 10
 
5.3%
8 8
 
4.2%
4 7
 
3.7%
5 7
 
3.7%
7 5
 
2.6%
Other values (2) 6
 
3.2%
Hangul
ValueCountFrequency (%)
보 29
 
9.4%
성 29
 
9.4%
전 23
 
7.5%
남 23
 
7.5%
도 23
 
7.5%
군 23
 
7.5%
라 23
 
7.5%
면 17
 
5.5%
길 16
 
5.2%
천 14
 
4.6%
Other values (41) 87
28.3%

우전
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
12 
50
7 
100
4 

Length

Max length3
Median length1
Mean length1.6521739
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row100
4th row50
5th row0

Common Values

ValueCountFrequency (%)
0 12
52.2%
50 7
30.4%
100 4
 
17.4%

Length

2023-12-13T05:28:47.224438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:47.335555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 12
52.2%
50 7
30.4%
100 4
 
17.4%

곡우
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
22 
50
 
1

Length

Max length2
Median length1
Mean length1.0434783
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
95.7%
50 1
 
4.3%

Length

2023-12-13T05:28:47.449313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:47.551731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
95.7%
50 1
 
4.3%

세작
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.521739
Minimum0
Maximum200
Zeros9
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T05:28:47.648025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q3100
95-th percentile190
Maximum200
Range200
Interquartile range (IQR)100

Descriptive statistics

Standard deviation61.458685
Coefficient of variation (CV)1.21648
Kurtosis1.1195124
Mean50.521739
Median Absolute Deviation (MAD)30
Skewness1.2853011
Sum1162
Variance3777.17
MonotonicityNot monotonic
2023-12-13T05:28:47.763480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9
39.1%
100 5
21.7%
50 4
17.4%
30 2
 
8.7%
200 2
 
8.7%
2 1
 
4.3%
ValueCountFrequency (%)
0 9
39.1%
2 1
 
4.3%
30 2
 
8.7%
50 4
17.4%
100 5
21.7%
200 2
 
8.7%
ValueCountFrequency (%)
200 2
 
8.7%
100 5
21.7%
50 4
17.4%
30 2
 
8.7%
2 1
 
4.3%
0 9
39.1%

계
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
100
12 
50
6 
30
2 
200
2 
2
 
1

Length

Max length3
Median length3
Mean length2.5652174
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row30
2nd row100
3rd row100
4th row50
5th row200

Common Values

ValueCountFrequency (%)
100 12
52.2%
50 6
26.1%
30 2
 
8.7%
200 2
 
8.7%
2 1
 
4.3%

Length

2023-12-13T05:28:47.916983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:48.051142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 12
52.2%
50 6
26.1%
30 2
 
8.7%
200 2
 
8.7%
2 1
 
4.3%

인증번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T05:28:48.286585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7
Min length6

Characters and Unicode

Total characters161
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

Unique23 ?
Unique (%)100.0%

Sample

1st row2023-1
2nd row2023-2
3rd row2023-3
4th row2023-4
5th row2023-5
ValueCountFrequency (%)
2023-1 1
 
4.3%
2023-14 1
 
4.3%
2023-25 1
 
4.3%
2023-23,24 1
 
4.3%
2023-22 1
 
4.3%
2023-21 1
 
4.3%
2023-20 1
 
4.3%
2023-18,19 1
 
4.3%
2023-17 1
 
4.3%
2023-16 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T05:28:48.750887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 56
34.8%
3 26
16.1%
0 25
15.5%
- 23
14.3%
1 13
 
8.1%
4 3
 
1.9%
5 3
 
1.9%
6 3
 
1.9%
, 3
 
1.9%
7 2
 
1.2%
Other values (2) 4
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
83.9%
Dash Punctuation 23
 
14.3%
Other Punctuation 3
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 56
41.5%
3 26
19.3%
0 25
18.5%
1 13
 
9.6%
4 3
 
2.2%
5 3
 
2.2%
6 3
 
2.2%
7 2
 
1.5%
8 2
 
1.5%
9 2
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 56
34.8%
3 26
16.1%
0 25
15.5%
- 23
14.3%
1 13
 
8.1%
4 3
 
1.9%
5 3
 
1.9%
6 3
 
1.9%
, 3
 
1.9%
7 2
 
1.2%
Other values (2) 4
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 56
34.8%
3 26
16.1%
0 25
15.5%
- 23
14.3%
1 13
 
8.1%
4 3
 
1.9%
5 3
 
1.9%
6 3
 
1.9%
, 3
 
1.9%
7 2
 
1.2%
Other values (2) 4
 
2.5%

Interactions

2023-12-13T05:28:44.576500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:44.336498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:44.664063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:44.432728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:28:48.858345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명대표자주소우전곡우세작계인증번호
연번1.0001.0001.0001.0000.3050.4880.0000.0001.000
업체명1.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
우전0.3051.0001.0001.0001.0000.0820.5460.3351.000
곡우0.4881.0001.0001.0000.0821.0000.0000.0001.000
세작0.0001.0001.0001.0000.5460.0001.0000.9501.000
계0.0001.0001.0001.0000.3350.0000.9501.0001.000
인증번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T05:28:49.002239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우전곡우계
우전1.0000.1170.239
곡우0.1171.0000.000
계0.2390.0001.000
2023-12-13T05:28:49.112055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번세작우전곡우계
연번1.0000.1110.0000.2670.000
세작0.1111.0000.4560.0000.680
우전0.0000.4561.0000.1170.239
곡우0.2670.0000.1171.0000.000
계0.0000.6800.2390.0001.000

Missing values

2023-12-13T05:28:44.822890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:28:44.969729image/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

연번업체명대표자주소우전곡우세작계인증번호
01보림제다영농조합법인임광철전라남도 보성군 보성읍 자세길 36-410030302023-1
12농업회사법인㈜보향다원최영기전라남도 보성군 보성읍 동암1길 144001001002023-2
23케일리 티 가든이수진전라남도 보성군 보성읍 사동길 35100001002023-3
34청우다원안명순전라남도 보성군 보성읍 사동길 52-25000502023-4
45몽중산다원영농조합법인정경완전라남도 보성군 보성읍 녹차로 831002002002023-5
56청룡다원최면희전라남도 보성군 보성읍 대련로 60-60050502023-6
67백연골발효차문정자전라남도 보성군 노동면 돈다길 71-400222023-7
78다채최수수전라남도 보성군 노동면 갱맹골길 73-440050502023-8
89영농조합법인 보성제다서찬식전라남도 보성군 미력면 농공길 28-18505001002023-9,10
910보성원당제다원김영옥전라남도 보성군 미력면 미력원당길 51100001002023-11
연번업체명대표자주소우전곡우세작계인증번호
1314녹차마을 영농조합법인양승천전라남도 보성군 회천면 녹차로 256-65000502023-15
1415영천다원윤영숙전라남도 보성군 회천면 영천길 378-155000502023-16
1516소아다원최명혜전라남도 보성군 회천면 녹차로 588-66001001002023-17
1617운해다원이순금전라남도 보성군 회천면 녹차로 273-10500501002023-18,19
1718신옥로제다조현부전라남도 보성군 회천면 녹차로 646-2100001002023-20
1819춘파다원김향선전라남도 보성군 회천면 화동분매길 126-255000502023-21
1920백록다원정혜영전라남도 보성군 회천면 봉서동길 81-7002002002023-22
2021죽림다원장순재전라남도 보성군 회천면 이문길 23-9500501002023-23,24
2122옥수다향손용전라남도 보성군 회천면 만수상율길 96-30030302023-25
2223농업회사법인(주)다도락조현곤전라남도 보성군 회천면 영천길 213001001002023-26