Overview

Dataset statistics

Number of variables7
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory60.2 B

Variable types

Numeric1
DateTime1
Text4
Categorical1

Dataset

Description농식품부에서 지정한 농산물 안전성 검정기관 현황정보
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20150108000000000416

Alerts

업무범위 is highly imbalanced (71.9%)Imbalance
소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:15:25.886338
Analysis finished2023-12-11 03:15:26.858909
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Real number (ℝ)

Distinct38
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.04878
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T12:15:26.938846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q19
median19
Q331
95-th percentile40
Maximum42
Range41
Interquartile range (IQR)22

Descriptive statistics

Standard deviation12.751375
Coefficient of variation (CV)0.63601748
Kurtosis-1.2775652
Mean20.04878
Median Absolute Deviation (MAD)12
Skewness0.14821243
Sum822
Variance162.59756
MonotonicityIncreasing
2023-12-11T12:15:27.094682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
4 3
 
7.3%
5 2
 
4.9%
1 1
 
2.4%
34 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
32 1
 
2.4%
Other values (28) 28
68.3%
ValueCountFrequency (%)
1 1
 
2.4%
2 1
 
2.4%
3 1
 
2.4%
4 3
7.3%
5 2
4.9%
6 1
 
2.4%
7 1
 
2.4%
9 1
 
2.4%
10 1
 
2.4%
11 1
 
2.4%
ValueCountFrequency (%)
42 1
2.4%
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%

지정일자
Date

Distinct29
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum2010-04-23 00:00:00
Maximum2015-12-15 00:00:00
2023-12-11T12:15:27.272611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:15:27.482504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

안전성검사기관명
Text

Distinct38
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T12:15:27.799299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length10.829268
Min length5

Characters and Unicode

Total characters444
Distinct characters116
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

Unique36 ?
Unique (%)87.8%

Sample

1st row한국에스지에스㈜
2nd row(재)경북해양바이오산업연구원
3rd row동의과학대학교산학협력단(동의분석센터)
4th row농협중앙회식품연구원
5th row농협중앙회식품연구원
ValueCountFrequency (%)
농협중앙회식품연구원 3
 
6.7%
다산생명과학원(주 2
 
4.4%
농협중앙회인삼검사소 1
 
2.2%
순천향대학교산학협력단 1
 
2.2%
㈜산업공해연구소 1
 
2.2%
㈜씨티케이 1
 
2.2%
한국에스지에스㈜ 1
 
2.2%
충북대학교산학협력단 1
 
2.2%
한국농어촌공사 1
 
2.2%
서울시농수산식품공사 1
 
2.2%
Other values (32) 32
71.1%
2023-12-11T12:15:28.374858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 25
 
5.6%
연 17
 
3.8%
구 17
 
3.8%
산 16
 
3.6%
원 15
 
3.4%
( 13
 
2.9%
대 13
 
2.9%
) 13
 
2.9%
협 12
 
2.7%
교 11
 
2.5%
Other values (106) 292
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
91.2%
Open Punctuation 13
 
2.9%
Close Punctuation 13
 
2.9%
Other Symbol 9
 
2.0%
Space Separator 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 25
 
6.2%
연 17
 
4.2%
구 17
 
4.2%
산 16
 
4.0%
원 15
 
3.7%
대 13
 
3.2%
협 12
 
3.0%
교 11
 
2.7%
농 10
 
2.5%
주 9
 
2.2%
Other values (102) 260
64.2%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 414
93.2%
Common 30
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 25
 
6.0%
연 17
 
4.1%
구 17
 
4.1%
산 16
 
3.9%
원 15
 
3.6%
대 13
 
3.1%
협 12
 
2.9%
교 11
 
2.7%
농 10
 
2.4%
주 9
 
2.2%
Other values (103) 269
65.0%
Common
ValueCountFrequency (%)
( 13
43.3%
) 13
43.3%
4
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
91.2%
ASCII 30
 
6.8%
None 9
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 25
 
6.2%
연 17
 
4.2%
구 17
 
4.2%
산 16
 
4.0%
원 15
 
3.7%
대 13
 
3.2%
협 12
 
3.0%
교 11
 
2.7%
농 10
 
2.5%
주 9
 
2.2%
Other values (102) 260
64.2%
ASCII
ValueCountFrequency (%)
( 13
43.3%
) 13
43.3%
4
 
13.3%
None
ValueCountFrequency (%)
㈜ 9
100.0%

소재지
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T12:15:28.795220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length28
Mean length24.926829
Min length16

Characters and Unicode

Total characters1022
Distinct characters155
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

Unique41 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 주촌면 농소리 155-1 김해의생명센터204호(김해분석실)
2nd row경상북도 울진군 죽변면 후정리 688-3
3rd row부산광역시 부산진구 양지로 54 동의과학대학교 산학관 5층 동의분석센터
4th row경기도 광주시 곤지암읍 경충대로 731
5th row경기도 안성시 미양면 강덕1길 161
ValueCountFrequency (%)
전라남도 7
 
3.3%
경기도 6
 
2.8%
경상남도 4
 
1.9%
서울특별시 4
 
1.9%
충청남도 3
 
1.4%
충청북도 3
 
1.4%
청주시 3
 
1.4%
전라북도 3
 
1.4%
서울시 3
 
1.4%
금천구 2
 
0.9%
Other values (168) 177
82.3%
2023-12-11T12:15:29.475268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
17.0%
1 36
 
3.5%
시 33
 
3.2%
도 29
 
2.8%
구 23
 
2.3%
로 23
 
2.3%
0 22
 
2.2%
산 21
 
2.1%
6 21
 
2.1%
5 20
 
2.0%
Other values (145) 620
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
61.5%
Decimal Number 185
 
18.1%
Space Separator 174
 
17.0%
Dash Punctuation 13
 
1.3%
Open Punctuation 5
 
0.5%
Close Punctuation 5
 
0.5%
Other Punctuation 5
 
0.5%
Uppercase Letter 4
 
0.4%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 33
 
5.2%
도 29
 
4.6%
구 23
 
3.7%
로 23
 
3.7%
산 21
 
3.3%
동 20
 
3.2%
남 18
 
2.9%
전 15
 
2.4%
경 13
 
2.1%
주 13
 
2.1%
Other values (124) 421
66.9%
Decimal Number
ValueCountFrequency (%)
1 36
19.5%
0 22
11.9%
6 21
11.4%
5 20
10.8%
4 18
9.7%
2 17
9.2%
3 16
8.6%
8 14
 
7.6%
9 11
 
5.9%
7 10
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
T 1
25.0%
S 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 629
61.5%
Common 389
38.1%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 33
 
5.2%
도 29
 
4.6%
구 23
 
3.7%
로 23
 
3.7%
산 21
 
3.3%
동 20
 
3.2%
남 18
 
2.9%
전 15
 
2.4%
경 13
 
2.1%
주 13
 
2.1%
Other values (124) 421
66.9%
Common
ValueCountFrequency (%)
174
44.7%
1 36
 
9.3%
0 22
 
5.7%
6 21
 
5.4%
5 20
 
5.1%
4 18
 
4.6%
2 17
 
4.4%
3 16
 
4.1%
8 14
 
3.6%
- 13
 
3.3%
Other values (7) 38
 
9.8%
Latin
ValueCountFrequency (%)
I 1
25.0%
T 1
25.0%
S 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 629
61.5%
ASCII 393
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
44.3%
1 36
 
9.2%
0 22
 
5.6%
6 21
 
5.3%
5 20
 
5.1%
4 18
 
4.6%
2 17
 
4.3%
3 16
 
4.1%
8 14
 
3.6%
- 13
 
3.3%
Other values (11) 42
 
10.7%
Hangul
ValueCountFrequency (%)
시 33
 
5.2%
도 29
 
4.6%
구 23
 
3.7%
로 23
 
3.7%
산 21
 
3.3%
동 20
 
3.2%
남 18
 
2.9%
전 15
 
2.4%
경 13
 
2.1%
주 13
 
2.1%
Other values (124) 421
66.9%

업무범위
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
유해물질분석
39 
검사, 유해물질분석
 
2

Length

Max length10
Median length6
Mean length6.195122
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유해물질분석 39
95.1%
검사, 유해물질분석 2
 
4.9%

Length

2023-12-11T12:15:29.639201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:15:29.763221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유해물질분석 41
95.3%
검사 2
 
4.7%

유해물질 항목
Text

Distinct21
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T12:15:29.942631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length19.487805
Min length7

Characters and Unicode

Total characters799
Distinct characters40
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

Unique16 ?
Unique (%)39.0%

Sample

1st row농산물(잔류농약),농지(기타성분, 중금속),자재(중금속)
2nd row농산물(잔류농약)
3rd row농산물(잔류농약, 중금속, 병원성미생물),농지(중금속),용수(기타성분, 중금속)
4th row농산물(잔류농약, 중금속) 농지(중금속), 용수(중금속, 기타성분)
5th row농산물(잔류농약)
ValueCountFrequency (%)
농산물(잔류농약 35
35.7%
중금속 21
21.4%
농지(중금속 17
17.3%
병원성미생물 5
 
5.1%
용수(중금속 4
 
4.1%
기타성분 3
 
3.1%
자재(중금속 3
 
3.1%
농산물(중금속 2
 
2.0%
용수(일반오염물질 1
 
1.0%
특정유해물질 1
 
1.0%
Other values (6) 6
 
6.1%
2023-12-11T12:15:30.427477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 93
11.6%
( 68
 
8.5%
) 67
 
8.4%
57
 
7.1%
, 56
 
7.0%
중 50
 
6.3%
금 50
 
6.3%
속 50
 
6.3%
물 47
 
5.9%
산 38
 
4.8%
Other values (30) 223
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 551
69.0%
Open Punctuation 68
 
8.5%
Close Punctuation 67
 
8.4%
Space Separator 57
 
7.1%
Other Punctuation 56
 
7.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 93
16.9%
중 50
9.1%
금 50
9.1%
속 50
9.1%
물 47
8.5%
산 38
 
6.9%
잔 36
 
6.5%
류 36
 
6.5%
약 36
 
6.5%
지 19
 
3.4%
Other values (26) 96
17.4%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 551
69.0%
Common 248
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 93
16.9%
중 50
9.1%
금 50
9.1%
속 50
9.1%
물 47
8.5%
산 38
 
6.9%
잔 36
 
6.5%
류 36
 
6.5%
약 36
 
6.5%
지 19
 
3.4%
Other values (26) 96
17.4%
Common
ValueCountFrequency (%)
( 68
27.4%
) 67
27.0%
57
23.0%
, 56
22.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 551
69.0%
ASCII 248
31.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 93
16.9%
중 50
9.1%
금 50
9.1%
속 50
9.1%
물 47
8.5%
산 38
 
6.9%
잔 36
 
6.5%
류 36
 
6.5%
약 36
 
6.5%
지 19
 
3.4%
Other values (26) 96
17.4%
ASCII
ValueCountFrequency (%)
( 68
27.4%
) 67
27.0%
57
23.0%
, 56
22.6%

전화번호
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T12:15:30.734119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters492
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

Unique41 ?
Unique (%)100.0%

Sample

1st row031-460-8031
2nd row054-780-3401
3rd row051-860-3259
4th row031-760-9852
5th row031-8046-8780
ValueCountFrequency (%)
031-460-8031 1
 
2.4%
061-750-5345 1
 
2.4%
033-250-7268 1
 
2.4%
041-530-3027 1
 
2.4%
031-400-1846 1
 
2.4%
02-3435-0390 1
 
2.4%
043-212-3322 1
 
2.4%
041-751-3010 1
 
2.4%
043-292-8179 1
 
2.4%
061-336-3104 1
 
2.4%
Other values (31) 31
75.6%
2023-12-11T12:15:31.244463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
18.1%
- 82
16.7%
2 54
11.0%
3 50
10.2%
1 44
8.9%
6 42
8.5%
4 36
7.3%
5 34
 
6.9%
8 24
 
4.9%
7 20
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 410
83.3%
Dash Punctuation 82
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
21.7%
2 54
13.2%
3 50
12.2%
1 44
10.7%
6 42
10.2%
4 36
8.8%
5 34
 
8.3%
8 24
 
5.9%
7 20
 
4.9%
9 17
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 492
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
18.1%
- 82
16.7%
2 54
11.0%
3 50
10.2%
1 44
8.9%
6 42
8.5%
4 36
7.3%
5 34
 
6.9%
8 24
 
4.9%
7 20
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
18.1%
- 82
16.7%
2 54
11.0%
3 50
10.2%
1 44
8.9%
6 42
8.5%
4 36
7.3%
5 34
 
6.9%
8 24
 
4.9%
7 20
 
4.1%

Interactions

2023-12-11T12:15:26.394354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:15:31.367018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자안전성검사기관명소재지업무범위유해물질 항목전화번호
지정번호1.0000.9731.0001.0000.2790.3691.000
지정일자0.9731.0001.0001.0000.0000.0001.000
안전성검사기관명1.0001.0001.0001.0001.0000.8271.000
소재지1.0001.0001.0001.0001.0001.0001.000
업무범위0.2790.0001.0001.0001.0000.7701.000
유해물질 항목0.3690.0000.8271.0000.7701.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
2023-12-11T12:15:31.515761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호업무범위
지정번호1.0000.176
업무범위0.1761.000

Missing values

2023-12-11T12:15:26.582787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:15:26.796871image/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

지정번호지정일자안전성검사기관명소재지업무범위유해물질 항목전화번호
012010-04-23한국에스지에스㈜경상남도 김해시 주촌면 농소리 155-1 김해의생명센터204호(김해분석실)유해물질분석농산물(잔류농약),농지(기타성분, 중금속),자재(중금속)031-460-8031
122010-04-23(재)경북해양바이오산업연구원경상북도 울진군 죽변면 후정리 688-3유해물질분석농산물(잔류농약)054-780-3401
232010-06-04동의과학대학교산학협력단(동의분석센터)부산광역시 부산진구 양지로 54 동의과학대학교 산학관 5층 동의분석센터유해물질분석농산물(잔류농약, 중금속, 병원성미생물),농지(중금속),용수(기타성분, 중금속)051-860-3259
342010-06-04농협중앙회식품연구원경기도 광주시 곤지암읍 경충대로 731유해물질분석농산물(잔류농약, 중금속) 농지(중금속), 용수(중금속, 기타성분)031-760-9852
442010-06-04농협중앙회식품연구원경기도 안성시 미양면 강덕1길 161유해물질분석농산물(잔류농약)031-8046-8780
542010-06-04농협중앙회식품연구원대전광역시 중구 대둔산로 199번길 43번지유해물질분석농산물(잔류농약)042-585-1147
652010-09-17다산생명과학원(주)광주광역시 광산구 우산동 1064-3(광주분석실)유해물질분석농산물(잔류농약, 중금속, 병원성미생물), 농지(중금속), 자재(중금속)062-942-6600
752010-09-17다산생명과학원(주)전라남도 화순군 화순읍 대리 5(화순분석실)유해물질분석용수(기타성분, 중금속)061-375-6235
862010-09-17전북대학교산학협력단전라북도 전주시 덕진구 덕진동 664-14유해물질분석농산물(잔류농약, 중금속) 농지(중금속), 자재(중금속)063-270-4828
972010-11-08전주대학교(농생명환경연구센터)전라북도 전주시 완산구 천참로 330번지검사, 유해물질분석농산물(잔류농약, 중금속)063-220-2950
지정번호지정일자안전성검사기관명소재지업무범위유해물질 항목전화번호
31322014-02-26제일분석센타(주)서울특별시 구로구 디지털로 272. 한신IT타워 912호유해물질분석농산물(잔류농약, 중금속), 농지(중금속)02-862-8666
32332014-03-07충북대학교산학협력단충청북도 청주시 서원구 충대로 1, 충북대 S21-3동 126호유해물질분석농산물(잔류농약, 중금속), 농지(중금속)043-261-3432
33342014-07-28한국농식품분석연구소(주)전라남도 순천시 중앙로 186유해물질분석농산물(잔류농약)061-811-3370
34352015-03-10(재)금산국제인삼약초연구소충청남도 금산군 금산읍 인삼광장로 25유해물질분석농산물(잔류농약, 중금속), 농지(중금속)041-750-1600
35362015-04-07아이센(주)울산광역시 울주군 삼남면 강당2길26유해물질분석농산물(잔류농약)052-264-2242
36382015-07-29㈜에코아임친환경기술연구원전라남도 강진군 성전면 송계로 650-94유해물질분석농산물(잔류농약)061-433-2675
37392015-08-19한국인터텍테스팅서비스(주)서울시 성동구 아차산로5길 7, 아주디지털타워 3층유해물질분석농산물(잔류농약)02-6090-9600
38402015-09-21㈜씨티케이경기도 성남시 분당구 판교로 744 분당테크노파크 C동 204호유해물질분석농산물(잔류농약)031-702-3155
39412015-12-01㈜산업공해연구소서울시 금천구 디지털로 130 남성프라자빌딩 10층 1008~1010호유해물질분석농산물(중금속, 병원성미생물)02-2026-1252
40422015-12-15한국임업진흥원서울시 강서구 공항대로 475유해물질분석농산물(잔류농약)02-6393-2725