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

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 07:24:30.088931
Analysis finished2024-03-23 07:24:31.356222
Duration1.27 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%
Mean37.081633
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-03-23T07:24:31.509247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median38
Q355
95-th percentile68.2
Maximum71
Range70
Interquartile range (IQR)35

Descriptive statistics

Standard deviation20.948187
Coefficient of variation (CV)0.56492083
Kurtosis-1.1691038
Mean37.081633
Median Absolute Deviation (MAD)18
Skewness-0.052128106
Sum1817
Variance438.82653
MonotonicityStrictly increasing
2024-03-23T07:24:31.905372image/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 (%)
71 1
2.0%
70 1
2.0%
69 1
2.0%
67 1
2.0%
66 1
2.0%
65 1
2.0%
64 1
2.0%
63 1
2.0%
62 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%
2023-11-16 1
 
2.0%
2021-07-09 1
 
2.0%
2021-07-23 1
 
2.0%
2022-05-18 1
 
2.0%
2023-01-16 1
 
2.0%
Other values (3) 3
 
6.1%

Length

2024-03-23T07:24:32.300043image/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%
2023-11-16 1
 
2.0%
2021-07-09 1
 
2.0%
2021-07-23 1
 
2.0%
2022-05-18 1
 
2.0%
2023-01-16 1
 
2.0%
Other values (3) 3
 
6.1%

기관명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-23T07:24:32.732027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length11.938776
Min length5

Characters and Unicode

Total characters585
Distinct characters136
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
 
10.0%
주식회사 3
 
4.3%
재)전남바이오산업진흥원 2
 
2.9%
한국에스지에스(주 1
 
1.4%
재)환경기술정책연구원 1
 
1.4%
사단법인 1
 
1.4%
kotiti시험연구원 1
 
1.4%
국제분석연구원(주 1
 
1.4%
한경국립대학교 1
 
1.4%
주)엔텍분석연구원 1
 
1.4%
Other values (51) 51
72.9%
2024-03-23T07:24:33.609320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 28
 
4.8%
28
 
4.8%
) 28
 
4.8%
22
 
3.8%
22
 
3.8%
21
 
3.6%
20
 
3.4%
16
 
2.7%
16
 
2.7%
13
 
2.2%
Other values (126) 371
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
85.6%
Open Punctuation 28
 
4.8%
Close Punctuation 28
 
4.8%
Space Separator 21
 
3.6%
Uppercase Letter 6
 
1.0%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
5.6%
22
 
4.4%
22
 
4.4%
20
 
4.0%
16
 
3.2%
16
 
3.2%
13
 
2.6%
13
 
2.6%
12
 
2.4%
12
 
2.4%
Other values (118) 327
65.3%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
I 2
33.3%
K 1
16.7%
O 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
85.8%
Common 77
 
13.2%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
5.6%
22
 
4.4%
22
 
4.4%
20
 
4.0%
16
 
3.2%
16
 
3.2%
13
 
2.6%
13
 
2.6%
12
 
2.4%
12
 
2.4%
Other values (119) 328
65.3%
Latin
ValueCountFrequency (%)
T 2
33.3%
I 2
33.3%
K 1
16.7%
O 1
16.7%
Common
ValueCountFrequency (%)
( 28
36.4%
) 28
36.4%
21
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
85.6%
ASCII 83
 
14.2%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 28
33.7%
) 28
33.7%
21
25.3%
T 2
 
2.4%
I 2
 
2.4%
K 1
 
1.2%
O 1
 
1.2%
Hangul
ValueCountFrequency (%)
28
 
5.6%
22
 
4.4%
22
 
4.4%
20
 
4.0%
16
 
3.2%
16
 
3.2%
13
 
2.6%
13
 
2.6%
12
 
2.4%
12
 
2.4%
Other values (118) 327
65.3%
None
ValueCountFrequency (%)
1
100.0%
Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-23T07:24:34.138748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length47
Mean length37.408163
Min length20

Characters and Unicode

Total characters1833
Distinct characters226
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 14
 
4.0%
서울특별시 7
 
2.0%
전라남도 6
 
1.7%
경상남도 4
 
1.1%
전라북도 3
 
0.9%
1 3
 
0.9%
유성구 3
 
0.9%
대전광역시 3
 
0.9%
충청남도 2
 
0.6%
청주시 2
 
0.6%
Other values (277) 302
86.5%
2024-03-23T07:24:34.970442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
 
17.1%
1 67
 
3.7%
52
 
2.8%
) 51
 
2.8%
( 51
 
2.8%
48
 
2.6%
45
 
2.5%
2 41
 
2.2%
39
 
2.1%
0 39
 
2.1%
Other values (216) 1087
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1083
59.1%
Space Separator 313
 
17.1%
Decimal Number 297
 
16.2%
Close Punctuation 51
 
2.8%
Open Punctuation 51
 
2.8%
Other Punctuation 14
 
0.8%
Dash Punctuation 9
 
0.5%
Math Symbol 8
 
0.4%
Uppercase Letter 6
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
4.8%
48
 
4.4%
45
 
4.2%
39
 
3.6%
38
 
3.5%
34
 
3.1%
23
 
2.1%
22
 
2.0%
20
 
1.8%
20
 
1.8%
Other values (192) 742
68.5%
Decimal Number
ValueCountFrequency (%)
1 67
22.6%
2 41
13.8%
0 39
13.1%
3 30
10.1%
7 24
 
8.1%
4 22
 
7.4%
8 21
 
7.1%
5 18
 
6.1%
6 18
 
6.1%
9 17
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
F 1
16.7%
C 1
16.7%
E 1
16.7%
T 1
16.7%
I 1
16.7%
M 1
16.7%
Math Symbol
ValueCountFrequency (%)
~ 4
50.0%
4
50.0%
Space Separator
ValueCountFrequency (%)
313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1083
59.1%
Common 743
40.5%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
4.8%
48
 
4.4%
45
 
4.2%
39
 
3.6%
38
 
3.5%
34
 
3.1%
23
 
2.1%
22
 
2.0%
20
 
1.8%
20
 
1.8%
Other values (192) 742
68.5%
Common
ValueCountFrequency (%)
313
42.1%
1 67
 
9.0%
) 51
 
6.9%
( 51
 
6.9%
2 41
 
5.5%
0 39
 
5.2%
3 30
 
4.0%
7 24
 
3.2%
4 22
 
3.0%
8 21
 
2.8%
Other values (7) 84
 
11.3%
Latin
ValueCountFrequency (%)
F 1
14.3%
C 1
14.3%
E 1
14.3%
T 1
14.3%
I 1
14.3%
M 1
14.3%
s 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1083
59.1%
ASCII 746
40.7%
Math Operators 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
42.0%
1 67
 
9.0%
) 51
 
6.8%
( 51
 
6.8%
2 41
 
5.5%
0 39
 
5.2%
3 30
 
4.0%
7 24
 
3.2%
4 22
 
2.9%
8 21
 
2.8%
Other values (13) 87
 
11.7%
Hangul
ValueCountFrequency (%)
52
 
4.8%
48
 
4.4%
45
 
4.2%
39
 
3.6%
38
 
3.5%
34
 
3.1%
23
 
2.1%
22
 
2.0%
20
 
1.8%
20
 
1.8%
Other values (192) 742
68.5%
Math Operators
ValueCountFrequency (%)
4
100.0%

업무범위
Categorical

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

2024-03-23T07:24:35.359592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:24:35.584585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분석 49
50.0%
유해물질 44
44.9%
검사(안전성조사),유해물질 5
 
5.1%
Distinct19
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
농산물(잔류농약)
16 
농산물(잔류농약.중금속),농지(중금속)
농산물(잔류농약.중금속)
농산물(병원성미생물.잔류농약.중금속)
농산물(중금속)
Other values (14)
16 

Length

Max length44
Median length34
Mean length16.714286
Min length7

Unique

Unique12 ?
Unique (%)24.5%

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)
5th row농산물(잔류농약.중금속),농지(중금속),용수(중금속)

Common Values

ValueCountFrequency (%)
농산물(잔류농약) 16
32.7%
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(병원성미생물.잔류농약.중금속),농지(중금속),용수(중금속) 1
 
2.0%
농산물(병원성미생물.잔류농약.중금속),농지(중금속) 1
 
2.0%
Other values (9) 9
18.4%

Length

2024-03-23T07:24:36.150491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농산물(잔류농약 18
34.6%
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 (10) 10
19.2%

Interactions

2024-03-23T07:24:30.818148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:24:36.525680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자기관명검사기관 소재지업무범위유해물질항목
지정번호1.0000.4971.0001.0000.0000.638
지정일자0.4971.0001.0001.0000.0000.000
기관명1.0001.0001.0001.0001.0001.000
검사기관 소재지1.0001.0001.0001.0001.0001.000
업무범위0.0000.0001.0001.0001.0000.696
유해물질항목0.6380.0001.0001.0000.6961.000
2024-03-23T07:24:36.810723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무범위지정일자유해물질항목
업무범위1.0000.0000.498
지정일자0.0001.0000.000
유해물질항목0.4980.0001.000
2024-03-23T07:24:36.972539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자업무범위유해물질항목
지정번호1.0000.2080.0000.244
지정일자0.2081.0000.0000.000
업무범위0.0000.0001.0000.498
유해물질항목0.2440.0000.4981.000

Missing values

2024-03-23T07:24:31.034320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:24:31.276817image/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)
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
39582023-11-16국립안동대학교 산학협력단경상북도 안동시 경동로 1375 공동실험실습관 4층 416호 (송천동)유해물질 분석농산물(잔류농약)
40622021-05-25주식회사 바이오푸드랩경기도 성남시 중원구 둔촌대로 388 701,720호 (상대원동)유해물질 분석농산물(잔류농약)
41632021-05-25제주대학교 산학협력단제주특별자치도 제주시 제주대학로 102 감귤화훼과학기술센터 208호 (아라일동)유해물질 분석농산물(잔류농약)
42642021-07-09(주)아워홈 식품연구원서울특별시 강서구 마곡중앙10로 91 (주)아워홈 식품연구원, 7층 분석연구팀 (마곡동)유해물질 분석농산물(방사능.잔류농약.중금속)
43652021-07-23부설기관 동강생물사업단강원도 영월군 영월읍 동강로 716 동강생태공원 내 영월바이오산업센터유해물질 분석농산물(잔류농약, 중금속)
44662022-05-18주식회사 에스에이피분석평가연구소대전광역시 유성구 테크노3로 65, 6층 620,621,622호 (관평동)유해물질 분석농산물(잔류농약.중금속),농지(중금속)
45672023-01-16㈜분석기술과미래대구광역시 달서구 성서로 329, 동원비즈플랫폼 802호, 807호~810호 (갈산동)유해물질 분석농산물(잔류농약)
46692023-08-16서울대학교 그린바이오과학기술연구원강원특별자치도 평창군 대화면 평창대로 1447 103동 317호유해물질 분석농산물(잔류농약)
47702023-12-20(주) 세스코 시험분석연구원서울특별시 강동구 상일로10길 36 (상일동) 8~9층유해물질 분석농산물(잔류농약)
48712024-02-15(주)티에스피분석연구소경기도 평택시 만세로 1738-17 (죽백동) 1층유해물질 분석농산물(잔류농약.중금속)