Overview

Dataset statistics

Number of variables7
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory59.6 B

Variable types

Numeric1
DateTime1
Text3
Categorical2

Dataset

Description국립농산물품질관리원에서 관리하는 안전성 검사기관 지정현황(지정번호, 지정일자, 기관명, 검사기관 소재지, 업무범위, 유해물질항목)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20181019000000000980

Alerts

업무범위 is highly overall correlated with 유해물질항목High correlation
유해물질항목 is highly overall correlated with 업무범위High correlation
업무범위 is highly imbalanced (53.7%)Imbalance
검사기관 소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:24:01.605246
Analysis finished2024-03-23 07:24:03.036210
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Real number (ℝ)

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.529412
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-23T07:24:03.258024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q116.5
median33
Q346.5
95-th percentile57.5
Maximum60
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation18.03813
Coefficient of variation (CV)0.57210486
Kurtosis-1.2354194
Mean31.529412
Median Absolute Deviation (MAD)16
Skewness-0.11204548
Sum1608
Variance325.37412
MonotonicityIncreasing
2024-03-23T07:24:03.602791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
4 3
 
5.9%
26 2
 
3.9%
1 1
 
2.0%
50 1
 
2.0%
40 1
 
2.0%
41 1
 
2.0%
42 1
 
2.0%
43 1
 
2.0%
44 1
 
2.0%
45 1
 
2.0%
Other values (38) 38
74.5%
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
4 3
5.9%
6 1
 
2.0%
7 1
 
2.0%
9 1
 
2.0%
10 1
 
2.0%
11 1
 
2.0%
13 1
 
2.0%
14 1
 
2.0%
ValueCountFrequency (%)
60 1
2.0%
59 1
2.0%
58 1
2.0%
57 1
2.0%
56 1
2.0%
55 1
2.0%
54 1
2.0%
53 1
2.0%
52 1
2.0%
51 1
2.0%

지정일자
Date

Distinct42
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2010-04-23 00:00:00
Maximum2021-03-08 00:00:00
2024-03-23T07:24:03.949254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:24:04.363737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

기관명
Text

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-23T07:24:04.814703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length11.078431
Min length3

Characters and Unicode

Total characters565
Distinct characters126
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)90.2%

Sample

1st row한국에스지에스㈜
2nd row(재)환동해산업연구원
3rd row농협경제지주㈜ 식품알앤디연구소
4th row농협경제지주㈜ 식품알앤디연구소
5th row농협경제지주㈜ 식품알앤디연구소
ValueCountFrequency (%)
농협경제지주㈜ 4
 
6.3%
식품알앤디연구소 3
 
4.8%
서울시농수산식품공사 2
 
3.2%
재)전남바이오산업진흥원 2
 
3.2%
재)구미전자정보기술원 1
 
1.6%
사단법인 1
 
1.6%
kotiti시험연구원 1
 
1.6%
한국에스지에스㈜ 1
 
1.6%
한경대학교산학협력단 1
 
1.6%
한국인터텍테스팅서비스(주 1
 
1.6%
Other values (46) 46
73.0%
2024-03-23T07:24:05.380274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 23
 
4.1%
연 22
 
3.9%
학 20
 
3.5%
㈜ 18
 
3.2%
원 17
 
3.0%
) 16
 
2.8%
( 16
 
2.8%
산 15
 
2.7%
주 14
 
2.5%
농 13
 
2.3%
Other values (116) 391
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
87.6%
Other Symbol 18
 
3.2%
Close Punctuation 16
 
2.8%
Open Punctuation 16
 
2.8%
Space Separator 12
 
2.1%
Uppercase Letter 8
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 23
 
4.6%
연 22
 
4.4%
학 20
 
4.0%
원 17
 
3.4%
산 15
 
3.0%
주 14
 
2.8%
농 13
 
2.6%
한 13
 
2.6%
국 12
 
2.4%
협 11
 
2.2%
Other values (106) 335
67.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
I 2
25.0%
M 1
12.5%
E 1
12.5%
K 1
12.5%
O 1
12.5%
Other Symbol
ValueCountFrequency (%)
㈜ 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
90.8%
Common 44
 
7.8%
Latin 8
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 23
 
4.5%
연 22
 
4.3%
학 20
 
3.9%
㈜ 18
 
3.5%
원 17
 
3.3%
산 15
 
2.9%
주 14
 
2.7%
농 13
 
2.5%
한 13
 
2.5%
국 12
 
2.3%
Other values (107) 346
67.4%
Latin
ValueCountFrequency (%)
T 2
25.0%
I 2
25.0%
M 1
12.5%
E 1
12.5%
K 1
12.5%
O 1
12.5%
Common
ValueCountFrequency (%)
) 16
36.4%
( 16
36.4%
12
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
87.6%
ASCII 52
 
9.2%
None 18
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 23
 
4.6%
연 22
 
4.4%
학 20
 
4.0%
원 17
 
3.4%
산 15
 
3.0%
주 14
 
2.8%
농 13
 
2.6%
한 13
 
2.6%
국 12
 
2.4%
협 11
 
2.2%
Other values (106) 335
67.7%
None
ValueCountFrequency (%)
㈜ 18
100.0%
ASCII
ValueCountFrequency (%)
) 16
30.8%
( 16
30.8%
12
23.1%
T 2
 
3.8%
I 2
 
3.8%
M 1
 
1.9%
E 1
 
1.9%
K 1
 
1.9%
O 1
 
1.9%

검사기관 소재지
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-23T07:24:06.106234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length30
Mean length24.941176
Min length15

Characters and Unicode

Total characters1272
Distinct characters174
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row경기도 의왕시 맑은내길 67
2nd row경상북도 울진군 죽변면 해양과학길 22
3rd row(본원)경기도 수원시 영통구 센트럴타운로 114-8
4th row(수도권)경기도 안성시 미양면 강덕1길 161
5th row(중부권)대전광역시 중구 대둔산로 199번길 43번지
ValueCountFrequency (%)
경기도 10
 
3.9%
서울특별시 9
 
3.5%
전라남도 6
 
2.3%
전라북도 3
 
1.2%
대전광역시 3
 
1.2%
유성구 3
 
1.2%
경상남도 3
 
1.2%
충청남도 3
 
1.2%
강서구 2
 
0.8%
군포시 2
 
0.8%
Other values (200) 214
82.9%
2024-03-23T07:24:07.053653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
16.4%
1 55
 
4.3%
로 44
 
3.5%
시 43
 
3.4%
도 33
 
2.6%
2 32
 
2.5%
구 29
 
2.3%
3 24
 
1.9%
경 22
 
1.7%
4 22
 
1.7%
Other values (164) 760
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 772
60.7%
Decimal Number 223
 
17.5%
Space Separator 208
 
16.4%
Close Punctuation 21
 
1.7%
Open Punctuation 21
 
1.7%
Other Punctuation 12
 
0.9%
Dash Punctuation 11
 
0.9%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 44
 
5.7%
시 43
 
5.6%
도 33
 
4.3%
구 29
 
3.8%
경 22
 
2.8%
남 21
 
2.7%
산 20
 
2.6%
동 18
 
2.3%
서 16
 
2.1%
대 16
 
2.1%
Other values (144) 510
66.1%
Decimal Number
ValueCountFrequency (%)
1 55
24.7%
2 32
14.3%
3 24
10.8%
4 22
 
9.9%
0 21
 
9.4%
5 19
 
8.5%
7 16
 
7.2%
6 13
 
5.8%
8 12
 
5.4%
9 9
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
S 1
33.3%
I 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 11
91.7%
. 1
 
8.3%
Space Separator
ValueCountFrequency (%)
208
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 772
60.7%
Common 497
39.1%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 44
 
5.7%
시 43
 
5.6%
도 33
 
4.3%
구 29
 
3.8%
경 22
 
2.8%
남 21
 
2.7%
산 20
 
2.6%
동 18
 
2.3%
서 16
 
2.1%
대 16
 
2.1%
Other values (144) 510
66.1%
Common
ValueCountFrequency (%)
208
41.9%
1 55
 
11.1%
2 32
 
6.4%
3 24
 
4.8%
4 22
 
4.4%
) 21
 
4.2%
( 21
 
4.2%
0 21
 
4.2%
5 19
 
3.8%
7 16
 
3.2%
Other values (7) 58
 
11.7%
Latin
ValueCountFrequency (%)
T 1
33.3%
S 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 772
60.7%
ASCII 500
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
41.6%
1 55
 
11.0%
2 32
 
6.4%
3 24
 
4.8%
4 22
 
4.4%
) 21
 
4.2%
( 21
 
4.2%
0 21
 
4.2%
5 19
 
3.8%
7 16
 
3.2%
Other values (10) 61
 
12.2%
Hangul
ValueCountFrequency (%)
로 44
 
5.7%
시 43
 
5.6%
도 33
 
4.3%
구 29
 
3.8%
경 22
 
2.8%
남 21
 
2.7%
산 20
 
2.6%
동 18
 
2.3%
서 16
 
2.1%
대 16
 
2.1%
Other values (144) 510
66.1%

업무범위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
유해물질분석
46 
유해물질분석, 검사
5 

Length

Max length10
Median length6
Mean length6.3921569
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유해물질분석
2nd row유해물질분석
3rd row유해물질분석
4th row유해물질분석
5th row유해물질분석, 검사

Common Values

ValueCountFrequency (%)
유해물질분석 46
90.2%
유해물질분석, 검사 5
 
9.8%

Length

2024-03-23T07:24:07.480105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:24:07.809793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유해물질분석 51
91.1%
검사 5
 
8.9%

유해물질항목
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
농산물(잔류농약)
16 
농산물(잔류농약, 중금속), 농지(중금속)
6 
농산물(중금속)
3 
농산물(잔류농약,중금속), 농지(중금속,기타유해물질)
 
2
농지(중금속)
 
2
Other values (20)
22 

Length

Max length56
Median length35
Mean length18.607843
Min length7

Unique

Unique18 ?
Unique (%)35.3%

Sample

1st row농산물(잔류농약,중금속, 병원성미생물)농지(중금속,기타유해물질)용수(중금속,기타유해물질)자재(중금속)
2nd row농산물(잔류농약)
3rd row농산물(중금속, 무기비소), 농지(중금속)
4th row농산물(잔류농약)
5th row농산물(잔류농약), 농지(유기인),용수(유기인)

Common Values

ValueCountFrequency (%)
농산물(잔류농약) 16
31.4%
농산물(잔류농약, 중금속), 농지(중금속) 6
 
11.8%
농산물(중금속) 3
 
5.9%
농산물(잔류농약,중금속), 농지(중금속,기타유해물질) 2
 
3.9%
농지(중금속) 2
 
3.9%
농산물(잔류농약, 중금속, 병원성미생물) 2
 
3.9%
농산물(잔류농약,중금속, 병원성미생물) 2
 
3.9%
농산물(잔류농약,중금속(무기비소 포함)), 농지(중금속, 기타성분) 1
 
2.0%
농산물(중금속, 무기비소), 농지(중금속) 1
 
2.0%
농산물(잔류농약), 농지(유기인),용수(유기인) 1
 
2.0%
Other values (15) 15
29.4%

Length

2024-03-23T07:24:08.154628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농산물(잔류농약 29
29.0%
농지(중금속 20
20.0%
농산물(잔류농약,중금속 12
12.0%
중금속 10
 
10.0%
농산물(중금속 5
 
5.0%
병원성미생물 4
 
4.0%
용수(중금속 4
 
4.0%
농지(중금속,기타유해물질 2
 
2.0%
곰팡이독소 2
 
2.0%
자재(중금속 2
 
2.0%
Other values (10) 10
 
10.0%

전화번호
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-23T07:24:08.660491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.960784
Min length9

Characters and Unicode

Total characters610
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

Unique51 ?
Unique (%)100.0%

Sample

1st row031-689-8614
2nd row054-780-3401
3rd row031-8021-7052
4th row031-8046-8780
5th row042-585-1147
ValueCountFrequency (%)
031-689-8614 1
 
2.0%
061-811-3370 1
 
2.0%
055-372-2994 1
 
2.0%
061-433-2675 1
 
2.0%
02-6090-9600 1
 
2.0%
031-702-3155 1
 
2.0%
02-2026-1252 1
 
2.0%
02-6393-2725 1
 
2.0%
062-530-5312 1
 
2.0%
02-929-4326 1
 
2.0%
Other values (41) 41
80.4%
2024-03-23T07:24:09.368616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 104
17.0%
- 101
16.6%
2 66
10.8%
3 63
10.3%
1 58
9.5%
6 47
7.7%
4 46
7.5%
5 44
7.2%
8 31
 
5.1%
7 30
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 509
83.4%
Dash Punctuation 101
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 104
20.4%
2 66
13.0%
3 63
12.4%
1 58
11.4%
6 47
9.2%
4 46
9.0%
5 44
8.6%
8 31
 
6.1%
7 30
 
5.9%
9 20
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 104
17.0%
- 101
16.6%
2 66
10.8%
3 63
10.3%
1 58
9.5%
6 47
7.7%
4 46
7.5%
5 44
7.2%
8 31
 
5.1%
7 30
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 104
17.0%
- 101
16.6%
2 66
10.8%
3 63
10.3%
1 58
9.5%
6 47
7.7%
4 46
7.5%
5 44
7.2%
8 31
 
5.1%
7 30
 
4.9%

Interactions

2024-03-23T07:24:02.409905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:24:09.691573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자기관명검사기관 소재지업무범위유해물질항목전화번호
지정번호1.0001.0001.0001.0000.1180.8251.000
지정일자1.0001.0001.0001.0000.0000.0001.000
기관명1.0001.0001.0001.0000.0000.0001.000
검사기관 소재지1.0001.0001.0001.0001.0001.0001.000
업무범위0.1180.0000.0001.0001.0000.8771.000
유해물질항목0.8250.0000.0001.0000.8771.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
2024-03-23T07:24:09.972814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무범위유해물질항목
업무범위1.0000.585
유해물질항목0.5851.000
2024-03-23T07:24:10.233136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호업무범위유해물질항목
지정번호1.0000.0580.357
업무범위0.0581.0000.585
유해물질항목0.3570.5851.000

Missing values

2024-03-23T07:24:02.738346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:24:02.955952image/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

지정번호지정일자기관명검사기관 소재지업무범위유해물질항목전화번호
012010-04-23한국에스지에스㈜경기도 의왕시 맑은내길 67유해물질분석농산물(잔류농약,중금속, 병원성미생물)농지(중금속,기타유해물질)용수(중금속,기타유해물질)자재(중금속)031-689-8614
122010-04-23(재)환동해산업연구원경상북도 울진군 죽변면 해양과학길 22유해물질분석농산물(잔류농약)054-780-3401
242010-06-04농협경제지주㈜ 식품알앤디연구소(본원)경기도 수원시 영통구 센트럴타운로 114-8유해물질분석농산물(중금속, 무기비소), 농지(중금속)031-8021-7052
342010-06-04농협경제지주㈜ 식품알앤디연구소(수도권)경기도 안성시 미양면 강덕1길 161유해물질분석농산물(잔류농약)031-8046-8780
442010-06-04농협경제지주㈜ 식품알앤디연구소(중부권)대전광역시 중구 대둔산로 199번길 43번지유해물질분석, 검사농산물(잔류농약), 농지(유기인),용수(유기인)042-585-1147
562010-09-17전북대학교산학협력단전라북도 정읍시 첨단과학로 241, 401호유해물질분석, 검사농산물(잔류농약,중금속) 농지(중금속), 자재(중금속)063-532-4828
672010-11-08전주대학교(농생명EM환경연구센터)전라북도 전주시 완산구 천참로 330번지유해물질분석농산물(잔류농약,중금속), 농지(중금속), 용수(중금속)063-220-2950
792010-11-08(주)한국분석기술연구원부산광역시 동구 대영로 267(초량동) 해광빌딩 301호유해물질분석농산물(잔류농약,중금속, 병원성미생물)051-466-1231
8102010-11-29㈜한국유로핀즈 분석서비스경기도 군포시 산본로 101번길 13(당정동)유해물질분석농산물(잔류농약,중금속) 농지(중금속), 용수(중금속)031-460-9121
9112010-12-30수원여자대학 식품분석연구센터경기도 화성시 봉담읍 주석로 1078유해물질분석농산물(잔류농약,중금속, 병원성미생물)031-290-8217
지정번호지정일자기관명검사기관 소재지업무범위유해물질항목전화번호
41512017-09-12(재)전남바이오산업진흥원 나노바이오연구센터전라남도 장성군 남면 나노산단로 123유해물질분석농산물(잔류농약)061-393-0313
42522018-04-05동명생명과학원(주)광주광역시 남구 대남대로 385유해물질분석농산물(잔류농약)062-351-1005
43532018-08-27㈜수호분석전라북도 덕진구 신복로 88, 3층유해물질분석농지(중금속)063-717-2441
44542019-07-05워터스생활환경연구소경기도 군포시 공단로 140번길 46 12층유해물질분석농지(중금속)1544-7712
45552019-09-18주식회사 네이처앤바이오텍경기도 오산시 가장산업서로 12-24유해물질분석농산물(잔류농약, 중금속)031-831-3536
46562019-12-16한국농수산식품유통공사경기도 성남시 분당구 운중로 229, 4층유해물질분석농산물(중금속)031-8060-6084
47572020-02-06(주)피켐코리아대전광역시 유성구 테크노 11로 12유해물질분석농산물(잔류농약, 중금속), 농지(중금속)042-823-8678
48582020-12-03안동대학교 산학협력단경상북도 안동시 경동로 1375, 공동실험실습실 416유해물질분석농산물(잔류농약)054-820-6992
49592020-12-24한울생명과학㈜대전광역시 유성구 가정북로 26-18유해물질분석농산물(잔류농약)042-826-4033
50602021-03-08한라분석연구원㈜제주시 첨단로 213-3, 124, 125호(영평동)유해물질분석농산물(잔류농약)064-725-1151