Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells7
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory63.5 B

Variable types

Text4
Numeric2
Categorical1

Dataset

Description제주특별자치도 서귀포시 관내 비료생산업체현황에 관한 데이터로 업체명, 소재지, 생산비종, 전화번호 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/3083691/fileData.do

Alerts

위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
데이터기준일자 is highly imbalanced (75.0%)Imbalance
업체명 has 1 (4.2%) missing valuesMissing
소재지 has 1 (4.2%) missing valuesMissing
생산비종 has 1 (4.2%) missing valuesMissing
전화번호 has 2 (8.3%) missing valuesMissing
위도 has 1 (4.2%) missing valuesMissing
경도 has 1 (4.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 01:27:12.530952
Analysis finished2023-12-12 01:27:13.889391
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing1
Missing (%)4.2%
Memory size324.0 B
2023-12-12T10:27:14.031741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length9.7826087
Min length5

Characters and Unicode

Total characters225
Distinct characters81
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 row세미영농조합
2nd row주식회사 한라자원 농업회사법인
3rd row(주)화송산업
4th row자농영농조합
5th row서귀포시청
ValueCountFrequency (%)
농업회사법인 4
 
12.5%
주식회사 2
 
6.2%
세미영농조합 1
 
3.1%
칠성영농조합법인 1
 
3.1%
유한회사 1
 
3.1%
농업회사법인㈜그린바이오 1
 
3.1%
제주비오투 1
 
3.1%
사람과자연 1
 
3.1%
㈜인성산업 1
 
3.1%
축산물종합유통센터 1
 
3.1%
Other values (18) 18
56.2%
2023-12-12T10:27:14.430376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 14
 
6.2%
사 11
 
4.9%
인 10
 
4.4%
법 9
 
4.0%
업 9
 
4.0%
9
 
4.0%
합 9
 
4.0%
회 8
 
3.6%
주 8
 
3.6%
조 8
 
3.6%
Other values (71) 130
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
90.2%
Space Separator 9
 
4.0%
Close Punctuation 5
 
2.2%
Open Punctuation 4
 
1.8%
Other Symbol 4
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 14
 
6.9%
사 11
 
5.4%
인 10
 
4.9%
법 9
 
4.4%
업 9
 
4.4%
합 9
 
4.4%
회 8
 
3.9%
주 8
 
3.9%
조 8
 
3.9%
산 7
 
3.4%
Other values (67) 110
54.2%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
92.0%
Common 18
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 14
 
6.8%
사 11
 
5.3%
인 10
 
4.8%
법 9
 
4.3%
업 9
 
4.3%
합 9
 
4.3%
회 8
 
3.9%
주 8
 
3.9%
조 8
 
3.9%
산 7
 
3.4%
Other values (68) 114
55.1%
Common
ValueCountFrequency (%)
9
50.0%
) 5
27.8%
( 4
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
90.2%
ASCII 18
 
8.0%
None 4
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 14
 
6.9%
사 11
 
5.4%
인 10
 
4.9%
법 9
 
4.4%
업 9
 
4.4%
합 9
 
4.4%
회 8
 
3.9%
주 8
 
3.9%
조 8
 
3.9%
산 7
 
3.4%
Other values (67) 110
54.2%
ASCII
ValueCountFrequency (%)
9
50.0%
) 5
27.8%
( 4
22.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

소재지
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing1
Missing (%)4.2%
Memory size324.0 B
2023-12-12T10:27:14.690326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length27.217391
Min length20

Characters and Unicode

Total characters626
Distinct characters58
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

Unique21 ?
Unique (%)91.3%

Sample

1st row제주특별자치도 서귀포시 대정읍 대한로 389-25
2nd row제주특별자치도 서귀포시 남원읍 위미항구로 395-31
3rd row제주특별자치도 서귀포시 대정읍 일주서로3000번길 155-13
4th row제주특별자치도 서귀포시 동홍로262번길 74
5th row제주특별자치도 서귀포시 산록남로1241번길 163
ValueCountFrequency (%)
제주특별자치도 23
21.1%
서귀포시 23
21.1%
대정읍 7
 
6.4%
안덕면 4
 
3.7%
남원읍 3
 
2.8%
일주서로3000번길 3
 
2.8%
한창로 3
 
2.8%
대한로 2
 
1.8%
389-25 2
 
1.8%
1100로 2
 
1.8%
Other values (37) 37
33.9%
2023-12-12T10:27:15.141235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
13.7%
서 29
 
4.6%
주 28
 
4.5%
1 25
 
4.0%
도 24
 
3.8%
시 23
 
3.7%
포 23
 
3.7%
귀 23
 
3.7%
제 23
 
3.7%
치 23
 
3.7%
Other values (48) 319
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 399
63.7%
Decimal Number 129
 
20.6%
Space Separator 86
 
13.7%
Dash Punctuation 12
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 29
 
7.3%
주 28
 
7.0%
도 24
 
6.0%
시 23
 
5.8%
포 23
 
5.8%
귀 23
 
5.8%
제 23
 
5.8%
치 23
 
5.8%
특 23
 
5.8%
별 23
 
5.8%
Other values (36) 157
39.3%
Decimal Number
ValueCountFrequency (%)
1 25
19.4%
0 22
17.1%
3 15
11.6%
7 14
10.9%
2 12
9.3%
4 10
 
7.8%
5 9
 
7.0%
9 9
 
7.0%
8 7
 
5.4%
6 6
 
4.7%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 399
63.7%
Common 227
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 29
 
7.3%
주 28
 
7.0%
도 24
 
6.0%
시 23
 
5.8%
포 23
 
5.8%
귀 23
 
5.8%
제 23
 
5.8%
치 23
 
5.8%
특 23
 
5.8%
별 23
 
5.8%
Other values (36) 157
39.3%
Common
ValueCountFrequency (%)
86
37.9%
1 25
 
11.0%
0 22
 
9.7%
3 15
 
6.6%
7 14
 
6.2%
- 12
 
5.3%
2 12
 
5.3%
4 10
 
4.4%
5 9
 
4.0%
9 9
 
4.0%
Other values (2) 13
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 399
63.7%
ASCII 227
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
37.9%
1 25
 
11.0%
0 22
 
9.7%
3 15
 
6.6%
7 14
 
6.2%
- 12
 
5.3%
2 12
 
5.3%
4 10
 
4.4%
5 9
 
4.0%
9 9
 
4.0%
Other values (2) 13
 
5.7%
Hangul
ValueCountFrequency (%)
서 29
 
7.3%
주 28
 
7.0%
도 24
 
6.0%
시 23
 
5.8%
포 23
 
5.8%
귀 23
 
5.8%
제 23
 
5.8%
치 23
 
5.8%
특 23
 
5.8%
별 23
 
5.8%
Other values (36) 157
39.3%

생산비종
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing1
Missing (%)4.2%
Memory size324.0 B
2023-12-12T10:27:15.369962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length6.9565217
Min length2

Characters and Unicode

Total characters160
Distinct characters41
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

Unique6 ?
Unique (%)26.1%

Sample

1st row퇴비
2nd row퇴비+가축분퇴비+가축분뇨발효액
3rd row골분
4th row유기질 등
5th row퇴비
ValueCountFrequency (%)
부숙유기질 4
14.3%
퇴비 3
10.7%
토양미생물제제 3
10.7%
퇴비+가축분퇴비+가축분뇨발효액 2
 
7.1%
유기질 2
 
7.1%
등 2
 
7.1%
미생물비료 2
 
7.1%
가축분뇨발효액 2
 
7.1%
골분 1
 
3.6%
미량요소비료 1
 
3.6%
Other values (6) 6
21.4%
2023-12-12T10:27:15.808081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 14
 
8.8%
분 9
 
5.6%
퇴 8
 
5.0%
가 7
 
4.4%
축 7
 
4.4%
제 7
 
4.4%
미 7
 
4.4%
유 6
 
3.8%
기 6
 
3.8%
질 6
 
3.8%
Other values (31) 83
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
91.9%
Space Separator 5
 
3.1%
Math Symbol 5
 
3.1%
Decimal Number 1
 
0.6%
Close Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 14
 
9.5%
분 9
 
6.1%
퇴 8
 
5.4%
가 7
 
4.8%
축 7
 
4.8%
제 7
 
4.8%
미 7
 
4.8%
유 6
 
4.1%
기 6
 
4.1%
질 6
 
4.1%
Other values (26) 70
47.6%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
91.9%
Common 13
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 14
 
9.5%
분 9
 
6.1%
퇴 8
 
5.4%
가 7
 
4.8%
축 7
 
4.8%
제 7
 
4.8%
미 7
 
4.8%
유 6
 
4.1%
기 6
 
4.1%
질 6
 
4.1%
Other values (26) 70
47.6%
Common
ValueCountFrequency (%)
5
38.5%
+ 5
38.5%
4 1
 
7.7%
) 1
 
7.7%
( 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
91.9%
ASCII 13
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 14
 
9.5%
분 9
 
6.1%
퇴 8
 
5.4%
가 7
 
4.8%
축 7
 
4.8%
제 7
 
4.8%
미 7
 
4.8%
유 6
 
4.1%
기 6
 
4.1%
질 6
 
4.1%
Other values (26) 70
47.6%
ASCII
ValueCountFrequency (%)
5
38.5%
+ 5
38.5%
4 1
 
7.7%
) 1
 
7.7%
( 1
 
7.7%

전화번호
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing2
Missing (%)8.3%
Memory size324.0 B
2023-12-12T10:27:16.030984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters264
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

Unique22 ?
Unique (%)100.0%

Sample

1st row064-792-3200
2nd row064-764-0058
3rd row064-794-5336
4th row064-762-0700
5th row064-735-3567
ValueCountFrequency (%)
064-764-0058 1
 
4.5%
064-794-5336 1
 
4.5%
064-742-2001 1
 
4.5%
064-762-7802 1
 
4.5%
064-797-4251 1
 
4.5%
064-729-7878 1
 
4.5%
064-738-8337 1
 
4.5%
064-764-0055 1
 
4.5%
064-738-4322 1
 
4.5%
064-794-2334 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T10:27:16.489555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 44
16.7%
0 41
15.5%
4 34
12.9%
7 31
11.7%
6 30
11.4%
3 23
8.7%
2 20
7.6%
8 14
 
5.3%
9 12
 
4.5%
5 9
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
83.3%
Dash Punctuation 44
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
18.6%
4 34
15.5%
7 31
14.1%
6 30
13.6%
3 23
10.5%
2 20
9.1%
8 14
 
6.4%
9 12
 
5.5%
5 9
 
4.1%
1 6
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 44
16.7%
0 41
15.5%
4 34
12.9%
7 31
11.7%
6 30
11.4%
3 23
8.7%
2 20
7.6%
8 14
 
5.3%
9 12
 
4.5%
5 9
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 44
16.7%
0 41
15.5%
4 34
12.9%
7 31
11.7%
6 30
11.4%
3 23
8.7%
2 20
7.6%
8 14
 
5.3%
9 12
 
4.5%
5 9
 
3.4%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean33.295522
Minimum33.24601
Maximum33.446253
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:27:16.668394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.24601
5-th percentile33.256443
Q133.261402
median33.291066
Q333.31855
95-th percentile33.349443
Maximum33.446253
Range0.20024317
Interquartile range (IQR)0.05714878

Descriptive statistics

Standard deviation0.044491105
Coefficient of variation (CV)0.0013362489
Kurtosis4.9057342
Mean33.295522
Median Absolute Deviation (MAD)0.0296644
Skewness1.8164179
Sum765.79701
Variance0.0019794584
MonotonicityNot monotonic
2023-12-12T10:27:17.177723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
33.2614017 2
 
8.3%
33.35200755 1
 
4.2%
33.26914077 1
 
4.2%
33.26510534 1
 
4.2%
33.26845118 1
 
4.2%
33.25825926 1
 
4.2%
33.32380733 1
 
4.2%
33.30247921 1
 
4.2%
33.32635988 1
 
4.2%
33.3020891 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
33.24601033 1
4.2%
33.25629584 1
4.2%
33.2577645 1
4.2%
33.25825926 1
4.2%
33.25857159 1
4.2%
33.2614017 2
8.3%
33.26510534 1
4.2%
33.26845118 1
4.2%
33.26914077 1
4.2%
33.27047493 1
4.2%
ValueCountFrequency (%)
33.4462535 1
4.2%
33.35200755 1
4.2%
33.32635988 1
4.2%
33.32465241 1
4.2%
33.32380733 1
4.2%
33.32125783 1
4.2%
33.31584313 1
4.2%
33.30917722 1
4.2%
33.30913992 1
4.2%
33.30247921 1
4.2%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean126.44486
Minimum126.22791
Maximum126.91156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:27:17.321654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.22791
5-th percentile126.22868
Q1126.25528
median126.4195
Q3126.57767
95-th percentile126.7442
Maximum126.91156
Range0.6836469
Interquartile range (IQR)0.32239625

Descriptive statistics

Standard deviation0.19949434
Coefficient of variation (CV)0.0015777181
Kurtosis-0.44644811
Mean126.44486
Median Absolute Deviation (MAD)0.1615944
Skewness0.67621786
Sum2908.2318
Variance0.039797991
MonotonicityNot monotonic
2023-12-12T10:27:17.480247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
126.2424329 2
 
8.3%
126.7493094 1
 
4.2%
126.268123 1
 
4.2%
126.57394 1
 
4.2%
126.3324768 1
 
4.2%
126.2297062 1
 
4.2%
126.3364235 1
 
4.2%
126.4518842 1
 
4.2%
126.698195 1
 
4.2%
126.4517449 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
126.2279125 1
4.2%
126.2286293 1
4.2%
126.2290901 1
4.2%
126.2297062 1
4.2%
126.2424329 2
8.3%
126.268123 1
4.2%
126.3324768 1
4.2%
126.3357941 1
4.2%
126.3364235 1
4.2%
126.3373192 1
4.2%
ValueCountFrequency (%)
126.9115594 1
4.2%
126.7493094 1
4.2%
126.698195 1
4.2%
126.6893395 1
4.2%
126.6441001 1
4.2%
126.5810983 1
4.2%
126.5742501 1
4.2%
126.57394 1
4.2%
126.4764915 1
4.2%
126.4518842 1
4.2%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-10-06
23 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.75
Min length4

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row2023-10-06
2nd row2023-10-06
3rd row2023-10-06
4th row2023-10-06
5th row2023-10-06

Common Values

ValueCountFrequency (%)
2023-10-06 23
95.8%
<NA> 1
 
4.2%

Length

2023-12-12T10:27:17.660449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:27:17.796941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-06 23
95.8%
na 1
 
4.2%

Interactions

2023-12-12T10:27:13.171138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:27:12.915577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:27:13.330710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:27:13.046338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:27:17.893697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명소재지생산비종전화번호위도경도
업체명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
생산비종1.0001.0001.0001.0000.0000.000
전화번호1.0001.0001.0001.0001.0001.000
위도1.0001.0000.0001.0001.0000.842
경도1.0001.0000.0001.0000.8421.000
2023-12-12T10:27:18.038723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도데이터기준일자
위도1.0000.6871.000
경도0.6871.0001.000
데이터기준일자1.0001.0001.000

Missing values

2023-12-12T10:27:13.490898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:27:13.630961image/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.
2023-12-12T10:27:13.780042image/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

업체명소재지생산비종전화번호위도경도데이터기준일자
0세미영농조합제주특별자치도 서귀포시 대정읍 대한로 389-25퇴비064-792-320033.261402126.2424332023-10-06
1주식회사 한라자원 농업회사법인제주특별자치도 서귀포시 남원읍 위미항구로 395-31퇴비+가축분퇴비+가축분뇨발효액064-764-005833.30914126.64412023-10-06
2(주)화송산업제주특별자치도 서귀포시 대정읍 일주서로3000번길 155-13골분064-794-533633.258572126.229092023-10-06
3자농영농조합제주특별자치도 서귀포시 동홍로262번길 74유기질 등064-762-070033.270475126.574252023-10-06
4서귀포시청제주특별자치도 서귀포시 산록남로1241번길 163퇴비064-735-356733.309177126.4195042023-10-06
5고원(주)제주특별자치도 서귀포시 도순남로 97토양미생물제제 미량요소비료064-739-089233.24601126.4764912023-10-06
6(주)풍농제주특별자치도 서귀포시 대정읍 일주서로3000번길 124유기질 등064-794-670933.256296126.2279132023-10-06
7농업회사법인 금강에코너지(주)제주특별자치도 서귀포시 안덕면 한창로 748-49퇴비+가축분퇴비+가축분뇨발효액064-794-088133.324652126.3373192023-10-06
8맛미유기비료제주특별자치도 서귀포시 대정읍 대한로 389-25퇴비064-794-510033.261402126.2424332023-10-06
9주식회사 케이에스앤바이오제주특별자치도 서귀포시 토평공단로115번길 28제4종복합비료064-732-353033.291066126.5810982023-10-06
업체명소재지생산비종전화번호위도경도데이터기준일자
14㈜지에스엘바이오제주특별자치도 서귀포시 대정읍 일주서로 3000번길 137-10미생물비료064-794-233433.257765126.2286292023-10-06
15윤창영농조합법인제주특별자치도 서귀포시 1100로 777부숙유기질064-738-432233.302089126.4517452023-10-06
16길갈영농조합법인제주특별자치도 서귀포시 남원읍 서성로914번길 125-36가축분뇨발효액064-764-005533.32636126.6981952023-10-06
17서흥축산영농조합법인제주특별자치도 서귀포시 1100로 779가축분뇨발효액064-738-833733.302479126.4518842023-10-06
18제주양돈축산업협동조합 축산물종합유통센터제주특별자치도 서귀포시 안덕면 한창로 746-31가축분퇴비064-729-787833.323807126.3364232023-10-06
19농업회사법인 ㈜인성산업제주특별자치도 서귀포시 대정읍 일주서로3000번길 151(부산물비료)그 밖의 비료+동애등에분064-797-425133.258259126.2297062023-10-06
20사람과자연 제주비오투제주특별자치도 서귀포시 안덕면 상창로 40-10토양미생물제제064-762-780233.268451126.3324772023-10-06
21농업회사법인㈜그린바이오제주특별자치도 서귀포시 동홍동 790번지미생물비료<NA>33.265105126.573942023-10-06
22유한회사 한라무역제주특별자치도 서귀포시 대정읍 보성리 601번지부숙유기질064-763-289433.269141126.2681232023-10-06
23<NA><NA><NA><NA><NA><NA><NA>