Overview

Dataset statistics

Number of variables12
Number of observations145
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory100.9 B

Variable types

Numeric4
Text3
Categorical3
DateTime2

Dataset

Description국립농산물품질관리원에서 관리하는 농산물이력추적등록단체 정보서비스(등록번호, 등록기관, 단계구분, 생산자단체, 대표자명, 유효기간, 대표품목, 주소, 등록농가수, 등록필지, 재배면적 등)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001681

Alerts

등록번호 is highly overall correlated with 등록농가수High correlation
등록농가수 is highly overall correlated with 등록번호High correlation
등록필지 is highly overall correlated with 재배면적High correlation
재배면적 is highly overall correlated with 등록필지High correlation
등록번호 has unique valuesUnique
등록필지 has 39 (26.9%) zerosZeros
재배면적 has 39 (26.9%) zerosZeros

Reproduction

Analysis started2024-03-23 07:44:47.970591
Analysis finished2024-03-23 07:44:54.159542
Duration6.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9180.8276
Minimum14
Maximum11986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-23T07:44:54.450999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile2177.6
Q16561
median11745
Q311947
95-th percentile11977.8
Maximum11986
Range11972
Interquartile range (IQR)5386

Descriptive statistics

Standard deviation3835.8121
Coefficient of variation (CV)0.41780679
Kurtosis-0.56363253
Mean9180.8276
Median Absolute Deviation (MAD)233
Skewness-1.0279432
Sum1331220
Variance14713454
MonotonicityStrictly increasing
2024-03-23T07:44:54.914179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 1
 
0.7%
11948 1
 
0.7%
11896 1
 
0.7%
11898 1
 
0.7%
11902 1
 
0.7%
11904 1
 
0.7%
11910 1
 
0.7%
11911 1
 
0.7%
11915 1
 
0.7%
11923 1
 
0.7%
Other values (135) 135
93.1%
ValueCountFrequency (%)
14 1
0.7%
304 1
0.7%
878 1
0.7%
879 1
0.7%
1029 1
0.7%
1136 1
0.7%
1885 1
0.7%
2163 1
0.7%
2236 1
0.7%
2240 1
0.7%
ValueCountFrequency (%)
11986 1
0.7%
11985 1
0.7%
11984 1
0.7%
11983 1
0.7%
11982 1
0.7%
11981 1
0.7%
11980 1
0.7%
11978 1
0.7%
11977 1
0.7%
11976 1
0.7%

등록기관
Text

Distinct55
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-23T07:44:55.334476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length10.4
Min length10

Characters and Unicode

Total characters1508
Distinct characters73
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)16.6%

Sample

1st row경북지원 문경사무소
2nd row경기지원 화성ㆍ오산사무소
3rd row경기지원 남양주ㆍ구리사무소
4th row경기지원 남양주ㆍ구리사무소
5th row경기지원 김포사무소
ValueCountFrequency (%)
경남지원 40
 
13.8%
강원지원 30
 
10.3%
충남지원 22
 
7.6%
품질관리과 21
 
7.2%
철원사무소 21
 
7.2%
경북지원 13
 
4.5%
경기지원 12
 
4.1%
밀양사무소 11
 
3.8%
전남지원 11
 
3.8%
천안사무소 8
 
2.8%
Other values (49) 101
34.8%
2024-03-23T07:44:56.117820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 199
13.2%
지 145
 
9.6%
145
 
9.6%
무 126
 
8.4%
사 124
 
8.2%
소 124
 
8.2%
남 79
 
5.2%
경 67
 
4.4%
강 33
 
2.2%
주 29
 
1.9%
Other values (63) 437
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1363
90.4%
Space Separator 145
 
9.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 199
14.6%
지 145
 
10.6%
무 126
 
9.2%
사 124
 
9.1%
소 124
 
9.1%
남 79
 
5.8%
경 67
 
4.9%
강 33
 
2.4%
주 29
 
2.1%
충 26
 
1.9%
Other values (62) 411
30.2%
Space Separator
ValueCountFrequency (%)
145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1363
90.4%
Common 145
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 199
14.6%
지 145
 
10.6%
무 126
 
9.2%
사 124
 
9.1%
소 124
 
9.1%
남 79
 
5.8%
경 67
 
4.9%
강 33
 
2.4%
주 29
 
2.1%
충 26
 
1.9%
Other values (62) 411
30.2%
Common
ValueCountFrequency (%)
145
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1345
89.2%
ASCII 145
 
9.6%
Compat Jamo 18
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 199
14.8%
지 145
 
10.8%
무 126
 
9.4%
사 124
 
9.2%
소 124
 
9.2%
남 79
 
5.9%
경 67
 
5.0%
강 33
 
2.5%
주 29
 
2.2%
충 26
 
1.9%
Other values (61) 393
29.2%
ASCII
ValueCountFrequency (%)
145
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 18
100.0%

단계구분
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
생산
106 
유통
29 
판매
 
10

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유통
2nd row유통
3rd row판매
4th row판매
5th row유통

Common Values

ValueCountFrequency (%)
생산 106
73.1%
유통 29
 
20.0%
판매 10
 
6.9%

Length

2024-03-23T07:44:56.384106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:44:56.670089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생산 106
73.1%
유통 29
 
20.0%
판매 10
 
6.9%

생산자단체명
Text

Distinct133
Distinct (%)92.4%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2024-03-23T07:44:57.054280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.2708333
Min length2

Characters and Unicode

Total characters1047
Distinct characters226
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)84.7%

Sample

1st row문경농협경제사업본부
2nd row수원지구원예농협산지유통센터
3rd row진접농업협동조합
4th row미금농업협동조합
5th row신김포농협미곡종합처리장양촌사업소
ValueCountFrequency (%)
농업회사법인 6
 
3.9%
주식회사 3
 
1.9%
동송농업협동조합 2
 
1.3%
철원농업협동조합 2
 
1.3%
금산농협농산물산지유통센터 2
 
1.3%
남천안버섯영농조합법인 2
 
1.3%
동철원농업협동조합 2
 
1.3%
그린농산 2
 
1.3%
죽장사과영농조합법인 2
 
1.3%
주)청솔 2
 
1.3%
Other values (127) 130
83.9%
2024-03-23T07:44:57.672153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 76
 
7.3%
조 42
 
4.0%
합 41
 
3.9%
인 34
 
3.2%
법 32
 
3.1%
협 31
 
3.0%
영 30
 
2.9%
산 27
 
2.6%
동 25
 
2.4%
목 22
 
2.1%
Other values (216) 687
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1010
96.5%
Space Separator 12
 
1.1%
Uppercase Letter 7
 
0.7%
Open Punctuation 6
 
0.6%
Close Punctuation 6
 
0.6%
Lowercase Letter 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 76
 
7.5%
조 42
 
4.2%
합 41
 
4.1%
인 34
 
3.4%
법 32
 
3.2%
협 31
 
3.1%
영 30
 
3.0%
산 27
 
2.7%
동 25
 
2.5%
목 22
 
2.2%
Other values (204) 650
64.4%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
P 2
28.6%
A 1
14.3%
T 1
14.3%
K 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
p 2
40.0%
r 1
20.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1010
96.5%
Common 25
 
2.4%
Latin 12
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 76
 
7.5%
조 42
 
4.2%
합 41
 
4.1%
인 34
 
3.4%
법 32
 
3.2%
협 31
 
3.1%
영 30
 
3.0%
산 27
 
2.7%
동 25
 
2.5%
목 22
 
2.2%
Other values (204) 650
64.4%
Latin
ValueCountFrequency (%)
e 2
16.7%
G 2
16.7%
P 2
16.7%
p 2
16.7%
A 1
8.3%
r 1
8.3%
T 1
8.3%
K 1
8.3%
Common
ValueCountFrequency (%)
12
48.0%
( 6
24.0%
) 6
24.0%
& 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1010
96.5%
ASCII 37
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 76
 
7.5%
조 42
 
4.2%
합 41
 
4.1%
인 34
 
3.4%
법 32
 
3.2%
협 31
 
3.1%
영 30
 
3.0%
산 27
 
2.7%
동 25
 
2.5%
목 22
 
2.2%
Other values (204) 650
64.4%
ASCII
ValueCountFrequency (%)
12
32.4%
( 6
16.2%
) 6
16.2%
e 2
 
5.4%
G 2
 
5.4%
P 2
 
5.4%
p 2
 
5.4%
A 1
 
2.7%
r 1
 
2.7%
& 1
 
2.7%
Other values (2) 2
 
5.4%

대표자명
Categorical

Distinct39
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
김**
29 
이**
26 
박**
10 
정**
9 
조**
8 
Other values (34)
63 

Length

Max length6
Median length3
Mean length3.0206897
Min length3

Unique

Unique16 ?
Unique (%)11.0%

Sample

1st row김**
2nd row이**
3rd row최**
4th row김**
5th row신**

Common Values

ValueCountFrequency (%)
김** 29
20.0%
이** 26
17.9%
박** 10
 
6.9%
정** 9
 
6.2%
조** 8
 
5.5%
황** 5
 
3.4%
최** 5
 
3.4%
윤** 3
 
2.1%
유** 3
 
2.1%
구** 3
 
2.1%
Other values (29) 44
30.3%

Length

2024-03-23T07:44:58.078219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김 29
20.0%
이 26
17.9%
박 10
 
6.9%
정 9
 
6.2%
조 8
 
5.5%
황 5
 
3.4%
최 5
 
3.4%
고 3
 
2.1%
임 3
 
2.1%
유 3
 
2.1%
Other values (29) 44
30.3%

유효기간 시작일
Date

Distinct119
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2019-10-08 00:00:00
Maximum2022-09-23 00:00:00
2024-03-23T07:44:58.460590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:58.847510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

유효기간 종료일
Date

Distinct120
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-10-07 00:00:00
Maximum2026-09-27 00:00:00
2024-03-23T07:44:59.216579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:59.564497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대표품목
Categorical

Distinct36
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
쌀
27 
파프리카
19 
사과
12 
토마토
11 
단감
8 
Other values (31)
68 

Length

Max length7
Median length5
Mean length2.537931
Min length1

Unique

Unique17 ?
Unique (%)11.7%

Sample

1st row사과
2nd row배
3rd row사과
4th row사과
5th row쌀

Common Values

ValueCountFrequency (%)
쌀 27
18.6%
파프리카 19
13.1%
사과 12
 
8.3%
토마토 11
 
7.6%
단감 8
 
5.5%
배 7
 
4.8%
딸기 6
 
4.1%
표고버섯 6
 
4.1%
더덕 6
 
4.1%
포도 5
 
3.4%
Other values (26) 38
26.2%

Length

2024-03-23T07:44:59.823531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
쌀 27
18.6%
파프리카 19
13.1%
사과 12
 
8.3%
토마토 11
 
7.6%
단감 8
 
5.5%
배 7
 
4.8%
딸기 6
 
4.1%
표고버섯 6
 
4.1%
더덕 6
 
4.1%
포도 5
 
3.4%
Other values (26) 38
26.2%

도로명주소
Text

Distinct60
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-23T07:45:00.194932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.9172414
Min length7

Characters and Unicode

Total characters1148
Distinct characters72
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)22.1%

Sample

1st row경상북도 문경시
2nd row경기도 화성시
3rd row경기도 남양주시
4th row경기도 남양주시
5th row경기도 김포시
ValueCountFrequency (%)
경상남도 40
 
13.8%
강원도 30
 
10.3%
철원군 21
 
7.2%
충청남도 20
 
6.9%
경상북도 13
 
4.5%
경기도 12
 
4.1%
밀양시 11
 
3.8%
전라남도 9
 
3.1%
천안시 8
 
2.8%
제주특별자치도 8
 
2.8%
Other values (61) 118
40.7%
2024-03-23T07:45:01.252131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
12.6%
도 141
 
12.3%
시 79
 
6.9%
남 73
 
6.4%
경 67
 
5.8%
군 66
 
5.7%
원 60
 
5.2%
상 58
 
5.1%
주 37
 
3.2%
강 33
 
2.9%
Other values (62) 389
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1003
87.4%
Space Separator 145
 
12.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 141
 
14.1%
시 79
 
7.9%
남 73
 
7.3%
경 67
 
6.7%
군 66
 
6.6%
원 60
 
6.0%
상 58
 
5.8%
주 37
 
3.7%
강 33
 
3.3%
청 28
 
2.8%
Other values (61) 361
36.0%
Space Separator
ValueCountFrequency (%)
145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1003
87.4%
Common 145
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 141
 
14.1%
시 79
 
7.9%
남 73
 
7.3%
경 67
 
6.7%
군 66
 
6.6%
원 60
 
6.0%
상 58
 
5.8%
주 37
 
3.7%
강 33
 
3.3%
청 28
 
2.8%
Other values (61) 361
36.0%
Common
ValueCountFrequency (%)
145
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1003
87.4%
ASCII 145
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
100.0%
Hangul
ValueCountFrequency (%)
도 141
 
14.1%
시 79
 
7.9%
남 73
 
7.3%
경 67
 
6.7%
군 66
 
6.6%
원 60
 
6.0%
상 58
 
5.8%
주 37
 
3.7%
강 33
 
3.3%
청 28
 
2.8%
Other values (61) 361
36.0%

등록농가수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0413793
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-23T07:45:01.614392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q38
95-th percentile16
Maximum22
Range21
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.1785828
Coefficient of variation (CV)0.85718552
Kurtosis1.2224222
Mean6.0413793
Median Absolute Deviation (MAD)3
Skewness1.2762338
Sum876
Variance26.81772
MonotonicityNot monotonic
2024-03-23T07:45:02.047190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 29
20.0%
3 16
11.0%
2 16
11.0%
5 14
9.7%
8 12
8.3%
4 11
 
7.6%
13 8
 
5.5%
6 7
 
4.8%
7 5
 
3.4%
11 5
 
3.4%
Other values (8) 22
15.2%
ValueCountFrequency (%)
1 29
20.0%
2 16
11.0%
3 16
11.0%
4 11
 
7.6%
5 14
9.7%
6 7
 
4.8%
7 5
 
3.4%
8 12
8.3%
9 4
 
2.8%
10 2
 
1.4%
ValueCountFrequency (%)
22 2
 
1.4%
21 4
2.8%
17 1
 
0.7%
16 2
 
1.4%
14 2
 
1.4%
13 8
5.5%
12 5
3.4%
11 5
3.4%
10 2
 
1.4%
9 4
2.8%

등록필지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262.35172
Minimum0
Maximum8925
Zeros39
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-23T07:45:02.496160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319
95-th percentile1762
Maximum8925
Range8925
Interquartile range (IQR)19

Descriptive statistics

Standard deviation1004.1277
Coefficient of variation (CV)3.8274105
Kurtosis41.849129
Mean262.35172
Median Absolute Deviation (MAD)3
Skewness5.8605966
Sum38041
Variance1008272.5
MonotonicityNot monotonic
2024-03-23T07:45:03.227869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39
26.9%
2 12
 
8.3%
3 12
 
8.3%
1 12
 
8.3%
4 12
 
8.3%
11 3
 
2.1%
6 3
 
2.1%
5 3
 
2.1%
7 3
 
2.1%
10 2
 
1.4%
Other values (41) 44
30.3%
ValueCountFrequency (%)
0 39
26.9%
1 12
 
8.3%
2 12
 
8.3%
3 12
 
8.3%
4 12
 
8.3%
5 3
 
2.1%
6 3
 
2.1%
7 3
 
2.1%
9 2
 
1.4%
10 2
 
1.4%
ValueCountFrequency (%)
8925 1
0.7%
4376 1
0.7%
4190 1
0.7%
3026 1
0.7%
2817 1
0.7%
2488 1
0.7%
2175 1
0.7%
1771 1
0.7%
1726 1
0.7%
1218 1
0.7%

재배면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean700635.9
Minimum0
Maximum16690976
Zeros39
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-23T07:45:03.718737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7948
Q346464
95-th percentile4712546.5
Maximum16690976
Range16690976
Interquartile range (IQR)46464

Descriptive statistics

Standard deviation2481723.6
Coefficient of variation (CV)3.5421017
Kurtosis20.631611
Mean700635.9
Median Absolute Deviation (MAD)7948
Skewness4.4125368
Sum1.0159221 × 108
Variance6.1589523 × 1012
MonotonicityNot monotonic
2024-03-23T07:45:04.240767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 39
26.9%
7948.0 2
 
1.4%
12668.0 1
 
0.7%
162.0 1
 
0.7%
11396.0 1
 
0.7%
39194.0 1
 
0.7%
12908.0 1
 
0.7%
30640.0 1
 
0.7%
4110.0 1
 
0.7%
9252.0 1
 
0.7%
Other values (96) 96
66.2%
ValueCountFrequency (%)
0.0 39
26.9%
162.0 1
 
0.7%
1848.0 1
 
0.7%
1921.0 1
 
0.7%
2330.0 1
 
0.7%
2380.0 1
 
0.7%
2744.0 1
 
0.7%
2749.82 1
 
0.7%
2876.0 1
 
0.7%
3000.0 1
 
0.7%
ValueCountFrequency (%)
16690976.0 1
0.7%
13030084.0 1
0.7%
12964151.0 1
0.7%
8940652.0 1
0.7%
8688330.0 1
0.7%
7533517.0 1
0.7%
6958035.0 1
0.7%
4835301.31 1
0.7%
4221527.03 1
0.7%
3737970.0 1
0.7%

Interactions

2024-03-23T07:44:52.230046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:49.415049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:50.329101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:51.132941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:52.487918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:49.685079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:50.479626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:51.370965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:52.727983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:49.914955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:50.634031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:51.598899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:52.971643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:50.156363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:50.876857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:44:51.968005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:45:04.543408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호등록기관단계구분대표자명대표품목도로명주소등록농가수등록필지재배면적
등록번호1.0000.4460.4260.6450.0000.6850.5990.5400.526
등록기관0.4461.0000.4620.6890.9651.0000.1750.0000.000
단계구분0.4260.4621.0000.0000.2600.5730.5890.0000.000
대표자명0.6450.6890.0001.0000.7190.7640.7010.4310.504
대표품목0.0000.9650.2600.7191.0000.9750.5250.0000.000
도로명주소0.6851.0000.5730.7640.9751.0000.0000.0000.000
등록농가수0.5990.1750.5890.7010.5250.0001.0000.5640.488
등록필지0.5400.0000.0000.4310.0000.0000.5641.0001.000
재배면적0.5260.0000.0000.5040.0000.0000.4881.0001.000
2024-03-23T07:45:04.872835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단계구분대표품목대표자명
단계구분1.0000.1100.000
대표품목0.1101.0000.205
대표자명0.0000.2051.000
2024-03-23T07:45:05.183598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호등록농가수등록필지재배면적단계구분대표자명대표품목
등록번호1.000-0.726-0.106-0.0630.2750.2470.000
등록농가수-0.7261.0000.0820.0500.3100.2960.194
등록필지-0.1060.0821.0000.9430.0000.1690.000
재배면적-0.0630.0500.9431.0000.0000.1980.000
단계구분0.2750.3100.0000.0001.0000.0000.110
대표자명0.2470.2960.1690.1980.0001.0000.205
대표품목0.0000.1940.0000.0000.1100.2051.000

Missing values

2024-03-23T07:44:53.372114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:44:53.857553image/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

등록번호등록기관단계구분생산자단체명대표자명유효기간 시작일유효기간 종료일대표품목도로명주소등록농가수등록필지재배면적
014경북지원 문경사무소유통문경농협경제사업본부김**2021-06-122024-06-11사과경상북도 문경시600.0
1304경기지원 화성ㆍ오산사무소유통수원지구원예농협산지유통센터이**2021-04-252024-04-24배경기도 화성시700.0
2878경기지원 남양주ㆍ구리사무소판매진접농업협동조합최**2021-06-092024-06-08사과경기도 남양주시900.0
3879경기지원 남양주ㆍ구리사무소판매미금농업협동조합김**2021-06-092024-06-08사과경기도 남양주시800.0
41029경기지원 김포사무소유통신김포농협미곡종합처리장양촌사업소신**2021-07-052024-07-04쌀경기도 김포시700.0
51136전남지원 품질관리과유통동곡농협이**2021-07-272024-07-26호박광주광역시 광산구800.0
61885전북지원 무주사무소생산양한오양**2022-03-122025-03-11사과전라북도 무주군72033569.0
72163강원지원 철원사무소유통동송농업협동조합진**2022-05-112025-05-10쌀강원도 철원군1600.0
82236강원지원 철원사무소유통김화농업협동조합엄**2022-06-052025-06-04쌀강원도 철원군2100.0
92240강원지원 철원사무소유통철원농업협동조합최**2022-06-052025-06-04쌀강원도 철원군1300.0
등록번호등록기관단계구분생산자단체명대표자명유효기간 시작일유효기간 종료일대표품목도로명주소등록농가수등록필지재배면적
13511976강원지원 홍천사무소생산서석농협토마토공선출하회정**2021-07-222024-07-21토마토강원도 홍천군31121350.6
13611977전북지원 남원사무소생산춘향골바래봉파프리카작목반이**2021-08-242024-08-23파프리카전라북도 남원시1796213202.9
13711978전북지원 남원사무소유통운봉농협농산물산지유통센터서**2021-08-242024-08-23파프리카전라북도 남원시100.0
13811980경남지원 품질관리과생산이호륜이**2021-09-062024-09-05파프리카경상남도 창원시149735.1
13911981충남지원 품질관리과생산배광호배**2021-11-012024-10-31표고버섯대전광역시 유성구171921.0
14011982경남지원 함안사무소유통가야원예영농조합법인박**2021-12-082024-12-07<NA>경상남도 함안군1100.0
14111983경남지원 밀양사무소생산안경자안**2021-01-212024-01-20파프리카경상남도 밀양시148036.0
14211984경남지원 밀양사무소생산이용재이**2022-02-072025-02-06단감경상남도 밀양시4344600.0
14311985충남지원 서산ㆍ태안사무소생산원북면영농조합법인김**2022-03-312025-03-30토마토충청남도 태안군1224270.0
14411986경남지원 품질관리과생산변재복변**2022-07-292025-07-28참다래(키위)경상남도 창원시1422145.0