Overview

Dataset statistics

Number of variables6
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory51.7 B

Variable types

Numeric1
Categorical3
Text2

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
지정일자 is highly imbalanced (52.0%)Imbalance
업무범위 is highly imbalanced (52.5%)Imbalance
지정번호 has unique valuesUnique
기관명 has unique valuesUnique
검사기관 소재지 has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:24:11.517304
Analysis finished2024-03-23 07:24:13.118606
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.469388
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-03-23T07:24:13.368838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median38
Q355
95-th percentile64.6
Maximum67
Range66
Interquartile range (IQR)35

Descriptive statistics

Standard deviation20.088452
Coefficient of variation (CV)0.55083053
Kurtosis-1.2173931
Mean36.469388
Median Absolute Deviation (MAD)18
Skewness-0.15387749
Sum1787
Variance403.54592
MonotonicityStrictly increasing
2024-03-23T07:24:14.650077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
56 1
 
2.0%
41 1
 
2.0%
43 1
 
2.0%
44 1
 
2.0%
46 1
 
2.0%
47 1
 
2.0%
49 1
 
2.0%
50 1
 
2.0%
51 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
4 1
2.0%
6 1
2.0%
7 1
2.0%
9 1
2.0%
10 1
2.0%
11 1
2.0%
14 1
2.0%
16 1
2.0%
ValueCountFrequency (%)
67 1
2.0%
66 1
2.0%
65 1
2.0%
64 1
2.0%
63 1
2.0%
62 1
2.0%
61 1
2.0%
60 1
2.0%
59 1
2.0%
58 1
2.0%

지정일자
Categorical

IMBALANCE 

Distinct13
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size524.0 B
2021-12-07
36 
2021-05-25
 
2
2022-09-20
 
1
2022-12-16
 
1
2023-02-06
 
1
Other values (8)

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique11 ?
Unique (%)22.4%

Sample

1st row2021-12-07
2nd row2021-12-07
3rd row2021-12-07
4th row2021-12-07
5th row2021-12-07

Common Values

ValueCountFrequency (%)
2021-12-07 36
73.5%
2021-05-25 2
 
4.1%
2022-09-20 1
 
2.0%
2022-12-16 1
 
2.0%
2023-02-06 1
 
2.0%
2020-12-03 1
 
2.0%
2020-12-24 1
 
2.0%
2021-03-08 1
 
2.0%
2021-04-12 1
 
2.0%
2021-07-09 1
 
2.0%
Other values (3) 3
 
6.1%

Length

2024-03-23T07:24:15.202691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-12-07 36
73.5%
2021-05-25 2
 
4.1%
2022-09-20 1
 
2.0%
2022-12-16 1
 
2.0%
2023-02-06 1
 
2.0%
2020-12-03 1
 
2.0%
2020-12-24 1
 
2.0%
2021-03-08 1
 
2.0%
2021-04-12 1
 
2.0%
2021-07-09 1
 
2.0%
Other values (3) 3
 
6.1%

기관명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-23T07:24:15.655905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length11.387755
Min length5

Characters and Unicode

Total characters558
Distinct characters135
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

Unique49 ?
Unique (%)100.0%

Sample

1st row한국에스지에스(주)
2nd row(재)환동해산업연구원
3rd row농협경제지주(주)식품알앤디연구소
4th row전북대학교 산학협력단
5th row전주대학교
ValueCountFrequency (%)
산학협력단 7
 
10.4%
주식회사 4
 
6.0%
재)전남바이오산업진흥원 2
 
3.0%
한국에스지에스(주 1
 
1.5%
한국농수산식품유통공사본사 1
 
1.5%
주)현농 1
 
1.5%
재)환경기술정책연구원 1
 
1.5%
사단법인 1
 
1.5%
kotiti시험연구원 1
 
1.5%
국제분석연구원(주 1
 
1.5%
Other values (47) 47
70.1%
2024-03-23T07:24:16.668602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
5.4%
( 29
 
5.2%
) 29
 
5.2%
19
 
3.4%
19
 
3.4%
19
 
3.4%
18
 
3.2%
16
 
2.9%
15
 
2.7%
12
 
2.2%
Other values (125) 352
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
85.1%
Open Punctuation 29
 
5.2%
Close Punctuation 29
 
5.2%
Space Separator 18
 
3.2%
Uppercase Letter 6
 
1.1%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
 
6.3%
19
 
4.0%
19
 
4.0%
19
 
4.0%
16
 
3.4%
15
 
3.2%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
Other values (117) 310
65.3%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
I 2
33.3%
O 1
16.7%
K 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 476
85.3%
Common 76
 
13.6%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
 
6.3%
19
 
4.0%
19
 
4.0%
19
 
4.0%
16
 
3.4%
15
 
3.2%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
Other values (118) 311
65.3%
Latin
ValueCountFrequency (%)
T 2
33.3%
I 2
33.3%
O 1
16.7%
K 1
16.7%
Common
ValueCountFrequency (%)
( 29
38.2%
) 29
38.2%
18
23.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
85.1%
ASCII 82
 
14.7%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
30
 
6.3%
19
 
4.0%
19
 
4.0%
19
 
4.0%
16
 
3.4%
15
 
3.2%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
Other values (117) 310
65.3%
ASCII
ValueCountFrequency (%)
( 29
35.4%
) 29
35.4%
18
22.0%
T 2
 
2.4%
I 2
 
2.4%
O 1
 
1.2%
K 1
 
1.2%
None
ValueCountFrequency (%)
1
100.0%
Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-23T07:24:17.086619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length45
Mean length37
Min length20

Characters and Unicode

Total characters1813
Distinct characters221
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row경기도 의왕시 맑은내길 67 (오전동) 301호~304호
2nd row경상북도 울진군 죽변면 해양과학길 22 환동해산업연구원
3rd row경기도 수원시 영통구 센트럴타운로 114-8 (이의동) 8∼9층, 경기도 안성시 미양면 강덕1길 161 1
4th row전라북도 정읍시 첨단과학로 241 (신정동) 401호
5th row전라북도 전주시 완산구 천잠로 303 (효자동2가) (전주대학교 농생명EM환경연구센터)
ValueCountFrequency (%)
경기도 13
 
3.8%
서울특별시 7
 
2.0%
전라남도 6
 
1.7%
경상남도 4
 
1.2%
유성구 4
 
1.2%
대전광역시 4
 
1.2%
성남시 3
 
0.9%
전라북도 3
 
0.9%
1 3
 
0.9%
충청남도 3
 
0.9%
Other values (265) 295
85.5%
2024-03-23T07:24:18.093598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
311
 
17.2%
1 66
 
3.6%
( 52
 
2.9%
) 52
 
2.9%
50
 
2.8%
47
 
2.6%
46
 
2.5%
2 44
 
2.4%
41
 
2.3%
37
 
2.0%
Other values (211) 1067
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1076
59.3%
Space Separator 311
 
17.2%
Decimal Number 283
 
15.6%
Open Punctuation 52
 
2.9%
Close Punctuation 52
 
2.9%
Other Punctuation 14
 
0.8%
Dash Punctuation 12
 
0.7%
Math Symbol 6
 
0.3%
Uppercase Letter 6
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
4.6%
47
 
4.4%
46
 
4.3%
41
 
3.8%
37
 
3.4%
31
 
2.9%
22
 
2.0%
21
 
2.0%
21
 
2.0%
21
 
2.0%
Other values (187) 739
68.7%
Decimal Number
ValueCountFrequency (%)
1 66
23.3%
2 44
15.5%
0 34
12.0%
3 28
9.9%
5 23
 
8.1%
4 22
 
7.8%
7 18
 
6.4%
9 17
 
6.0%
8 16
 
5.7%
6 15
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
F 1
16.7%
C 1
16.7%
T 1
16.7%
M 1
16.7%
I 1
16.7%
E 1
16.7%
Math Symbol
ValueCountFrequency (%)
4
66.7%
~ 2
33.3%
Space Separator
ValueCountFrequency (%)
311
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1076
59.3%
Common 730
40.3%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
4.6%
47
 
4.4%
46
 
4.3%
41
 
3.8%
37
 
3.4%
31
 
2.9%
22
 
2.0%
21
 
2.0%
21
 
2.0%
21
 
2.0%
Other values (187) 739
68.7%
Common
ValueCountFrequency (%)
311
42.6%
1 66
 
9.0%
( 52
 
7.1%
) 52
 
7.1%
2 44
 
6.0%
0 34
 
4.7%
3 28
 
3.8%
5 23
 
3.2%
4 22
 
3.0%
7 18
 
2.5%
Other values (7) 80
 
11.0%
Latin
ValueCountFrequency (%)
F 1
14.3%
C 1
14.3%
T 1
14.3%
M 1
14.3%
I 1
14.3%
E 1
14.3%
s 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1076
59.3%
ASCII 733
40.4%
Math Operators 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
311
42.4%
1 66
 
9.0%
( 52
 
7.1%
) 52
 
7.1%
2 44
 
6.0%
0 34
 
4.6%
3 28
 
3.8%
5 23
 
3.1%
4 22
 
3.0%
7 18
 
2.5%
Other values (13) 83
 
11.3%
Hangul
ValueCountFrequency (%)
50
 
4.6%
47
 
4.4%
46
 
4.3%
41
 
3.8%
37
 
3.4%
31
 
2.9%
22
 
2.0%
21
 
2.0%
21
 
2.0%
21
 
2.0%
Other values (187) 739
68.7%
Math Operators
ValueCountFrequency (%)
4
100.0%

업무범위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
유해물질 분석
44 
검사(안전성조사),유해물질 분석

Length

Max length17
Median length7
Mean length8.0204082
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유해물질 분석
2nd row유해물질 분석
3rd row유해물질 분석
4th row검사(안전성조사),유해물질 분석
5th row유해물질 분석

Common Values

ValueCountFrequency (%)
유해물질 분석 44
89.8%
검사(안전성조사),유해물질 분석 5
 
10.2%

Length

2024-03-23T07:24:18.500768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:24:18.900483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분석 49
50.0%
유해물질 44
44.9%
검사(안전성조사),유해물질 5
 
5.1%

유해물질항목
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
농산물(잔류농약)
14 
농산물(잔류농약.중금속),농지(중금속)
농산물(잔류농약.중금속)
농산물(병원성미생물.잔류농약.중금속)
농산물(중금속)
Other values (16)
18 

Length

Max length44
Median length34
Mean length17.265306
Min length7

Unique

Unique14 ?
Unique (%)28.6%

Sample

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

Common Values

ValueCountFrequency (%)
농산물(잔류농약) 14
28.6%
농산물(잔류농약.중금속),농지(중금속) 7
14.3%
농산물(잔류농약.중금속) 5
 
10.2%
농산물(병원성미생물.잔류농약.중금속) 3
 
6.1%
농산물(중금속) 2
 
4.1%
농산물(잔류농약.중금속),농지(중금속),용수(중금속) 2
 
4.1%
농산물(잔류농약.중금속),농지(기타.중금속) 2
 
4.1%
농지(중금속),용수(중금속) 1
 
2.0%
농산물(잔류농약.중금속),농지(중금속),자재(중금속) 1
 
2.0%
농산물(병원성미생물.잔류농약.중금속),농지(중금속),용수(중금속) 1
 
2.0%
Other values (11) 11
22.4%

Length

2024-03-23T07:24:19.292585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농산물(잔류농약 16
30.8%
농산물(잔류농약.중금속),농지(중금속 7
13.5%
농산물(잔류농약.중금속 5
 
9.6%
농산물(병원성미생물.잔류농약.중금속 3
 
5.8%
농산물(중금속 2
 
3.8%
농산물(잔류농약.중금속),농지(중금속),용수(중금속 2
 
3.8%
농산물(잔류농약.중금속),농지(기타.중금속 2
 
3.8%
농산물(병원성미생물.잔류농약 1
 
1.9%
농산물(병원성미생물.잔류농약.중금속),농지(중금속),용수(중금속),자재(중금속 1
 
1.9%
농산물(방사능.잔류농약.중금속 1
 
1.9%
Other values (12) 12
23.1%

Interactions

2024-03-23T07:24:12.223433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:24:19.566228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자기관명검사기관 소재지업무범위유해물질항목
지정번호1.0000.0001.0001.0000.1950.697
지정일자0.0001.0001.0001.0000.0000.000
기관명1.0001.0001.0001.0001.0001.000
검사기관 소재지1.0001.0001.0001.0001.0001.000
업무범위0.1950.0001.0001.0001.0000.753
유해물질항목0.6970.0001.0001.0000.7531.000
2024-03-23T07:24:19.808258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무범위지정일자유해물질항목
업무범위1.0000.0000.520
지정일자0.0001.0000.000
유해물질항목0.5200.0001.000
2024-03-23T07:24:19.998499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자업무범위유해물질항목
지정번호1.0000.0000.1210.273
지정일자0.0001.0000.0000.000
업무범위0.1210.0001.0000.520
유해물질항목0.2730.0000.5201.000

Missing values

2024-03-23T07:24:12.592627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:24:12.984771image/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 소재지업무범위유해물질항목
012021-12-07한국에스지에스(주)경기도 의왕시 맑은내길 67 (오전동) 301호~304호유해물질 분석농산물(병원성미생물.잔류농약.중금속),농지(중금속),용수(중금속),자재(중금속)
122021-12-07(재)환동해산업연구원경상북도 울진군 죽변면 해양과학길 22 환동해산업연구원유해물질 분석농산물(잔류농약)
242021-12-07농협경제지주(주)식품알앤디연구소경기도 수원시 영통구 센트럴타운로 114-8 (이의동) 8∼9층, 경기도 안성시 미양면 강덕1길 161 1유해물질 분석농산물(잔류농약.중금속),농지(중금속)
362021-12-07전북대학교 산학협력단전라북도 정읍시 첨단과학로 241 (신정동) 401호검사(안전성조사),유해물질 분석농산물(잔류농약.중금속),농지(중금속),자재(중금속)
472021-12-07전주대학교전라북도 전주시 완산구 천잠로 303 (효자동2가) (전주대학교 농생명EM환경연구센터)유해물질 분석농산물(잔류농약.중금속),농지(중금속),용수(중금속)
592021-12-07(주)한국분석기술연구원부산광역시 동구 대영로 267 (초량동) 해광빌딩 301호유해물질 분석농산물(병원성미생물.잔류농약.중금속)
6102021-12-07(주)한국유로핀즈 분석서비스경기도 군포시 산본로101번길 13 (당정동)유해물질 분석농산물(잔류농약.중금속),농지(중금속),용수(중금속)
7112021-12-07수원여자대학교 식품분석연구센터경기도 화성시 봉담읍 주석로 1098유해물질 분석농산물(병원성미생물.잔류농약.중금속),농지(중금속),용수(중금속)
8142021-12-07(주)오에이티씨서울특별시 금천구 범안로 1130 (가산동) 디지털엠파이어빌딩(803∼806호, 907∼912호)검사(안전성조사),유해물질 분석농산물(병원성미생물.잔류농약.중금속),농지(중금속)
9162021-12-07(재)창녕양파장류연구소경상남도 창녕군 대지면 우포2로 1085 (재)창녕양파장류연구소유해물질 분석농산물(잔류농약.중금속),농지(중금속)
지정번호지정일자기관명검사기관 소재지업무범위유해물질항목
39582020-12-03안동대학교 산학협력단경상북도 안동시 경동로 1375 공동실험실습관 4층 416호 (송천동)유해물질 분석농산물(잔류농약)
40592020-12-24한울생명과학(주)대전광역시 유성구 가정북로 26-18 (장동)유해물질 분석농산물(잔류농약)
41602021-03-08한라분석연구원(주)제주특별자치도 제주시 첨단로 213-3 124호, 125호 (영평동)유해물질 분석농산물(잔류농약.중금속)
42612021-04-12주식회사 휴먼바이오충청남도 공주시 한적2길 52-103 (금흥동)유해물질 분석농산물(잔류농약)
43622021-05-25주식회사 바이오푸드랩경기도 성남시 중원구 둔촌대로 388 701,720호 (상대원동)유해물질 분석농산물(잔류농약)
44632021-05-25제주대학교 산학협력단제주특별자치도 제주시 제주대학로 102 감귤화훼과학기술센터 208호 (아라일동)유해물질 분석농산물(잔류농약)
45642021-07-09(주)아워홈 식품연구원서울특별시 강서구 마곡중앙10로 91 (주)아워홈 식품연구원, 7층 분석연구팀 (마곡동)유해물질 분석농산물(방사능.잔류농약.중금속)
46652021-07-23부설기관 동강생물사업단강원도 영월군 영월읍 동강로 716 동강생태공원 내 영월바이오산업센터유해물질 분석농산물(잔류농약, 중금속)
47662022-05-18주식회사 에스에이피분석평가연구소대전광역시 유성구 테크노3로 65, 6층유해물질 분석농산물(잔류농약.중금속),농지(중금속)
48672023-01-16㈜분석기술과미래대구광역시 달서구 성서로 329, 동원비즈플랫폼 802호유해물질 분석농산물(잔류농약)