Overview

Dataset statistics

Number of variables12
Number of observations127
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory101.0 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 35 (27.6%) zerosZeros
재배면적 has 35 (27.6%) zerosZeros

Reproduction

Analysis started2024-03-23 07:45:27.946966
Analysis finished2024-03-23 07:45:34.249272
Duration6.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9315.8583
Minimum14
Maximum11990
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-23T07:45:34.447860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile2184.9
Q16578.5
median11771
Q311955
95-th percentile11983.7
Maximum11990
Range11976
Interquartile range (IQR)5376.5

Descriptive statistics

Standard deviation3812.1214
Coefficient of variation (CV)0.40920776
Kurtosis-0.3938561
Mean9315.8583
Median Absolute Deviation (MAD)207
Skewness-1.103594
Sum1183114
Variance14532270
MonotonicityStrictly increasing
2024-03-23T07:45:34.889364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 1
 
0.8%
304 1
 
0.8%
11954 1
 
0.8%
11953 1
 
0.8%
11947 1
 
0.8%
11945 1
 
0.8%
11944 1
 
0.8%
11942 1
 
0.8%
11941 1
 
0.8%
11940 1
 
0.8%
Other values (117) 117
92.1%
ValueCountFrequency (%)
14 1
0.8%
304 1
0.8%
878 1
0.8%
879 1
0.8%
1136 1
0.8%
1885 1
0.8%
2163 1
0.8%
2236 1
0.8%
2240 1
0.8%
2241 1
0.8%
ValueCountFrequency (%)
11990 1
0.8%
11989 1
0.8%
11988 1
0.8%
11987 1
0.8%
11986 1
0.8%
11985 1
0.8%
11984 1
0.8%
11983 1
0.8%
11982 1
0.8%
11981 1
0.8%

등록기관
Text

Distinct51
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T07:45:35.347393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length10.480315
Min length10

Characters and Unicode

Total characters1331
Distinct characters69
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

Unique25 ?
Unique (%)19.7%

Sample

1st row경북지원 문경사무소
2nd row경기지원 화성ㆍ오산사무소
3rd row경기지원 남양주ㆍ구리사무소
4th row경기지원 남양주ㆍ구리사무소
5th row전남지원 품질관리과
ValueCountFrequency (%)
경남지원 37
14.6%
강원지원 29
 
11.4%
철원사무소 21
 
8.3%
품질관리과 18
 
7.1%
충남지원 16
 
6.3%
밀양사무소 12
 
4.7%
경북지원 12
 
4.7%
경기지원 11
 
4.3%
전남지원 10
 
3.9%
전북지원 5
 
2.0%
Other values (45) 83
32.7%
2024-03-23T07:45:36.532116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 180
13.5%
지 127
 
9.5%
127
 
9.5%
무 111
 
8.3%
사 109
 
8.2%
소 109
 
8.2%
남 70
 
5.3%
경 62
 
4.7%
강 31
 
2.3%
양 25
 
1.9%
Other values (59) 380
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1204
90.5%
Space Separator 127
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 180
15.0%
지 127
 
10.5%
무 111
 
9.2%
사 109
 
9.1%
소 109
 
9.1%
남 70
 
5.8%
경 62
 
5.1%
강 31
 
2.6%
양 25
 
2.1%
주 24
 
2.0%
Other values (58) 356
29.6%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1204
90.5%
Common 127
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 180
15.0%
지 127
 
10.5%
무 111
 
9.2%
사 109
 
9.1%
소 109
 
9.1%
남 70
 
5.8%
경 62
 
5.1%
강 31
 
2.6%
양 25
 
2.1%
주 24
 
2.0%
Other values (58) 356
29.6%
Common
ValueCountFrequency (%)
127
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1185
89.0%
ASCII 127
 
9.5%
Compat Jamo 19
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 180
15.2%
지 127
 
10.7%
무 111
 
9.4%
사 109
 
9.2%
소 109
 
9.2%
남 70
 
5.9%
경 62
 
5.2%
강 31
 
2.6%
양 25
 
2.1%
주 24
 
2.0%
Other values (57) 337
28.4%
ASCII
ValueCountFrequency (%)
127
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 19
100.0%

단계구분
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
생산
92 
유통
25 
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 92
72.4%
유통 25
 
19.7%
판매 10
 
7.9%

Length

2024-03-23T07:45:37.065159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:45:37.524564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생산 92
72.4%
유통 25
 
19.7%
판매 10
 
7.9%

생산자단체명
Text

Distinct116
Distinct (%)92.1%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-03-23T07:45:38.196396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.3333333
Min length3

Characters and Unicode

Total characters924
Distinct characters201
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

Unique106 ?
Unique (%)84.1%

Sample

1st row문경농협경제사업본부
2nd row수원지구원예농협산지유통센터
3rd row진접농업협동조합
4th row미금농업협동조합
5th row동곡농협
ValueCountFrequency (%)
농업회사법인 6
 
4.4%
죽장사과영농조합법인 2
 
1.5%
동철원농업협동조합 2
 
1.5%
주)청솔 2
 
1.5%
주식회사 2
 
1.5%
성남배작목반 2
 
1.5%
금산농협농산물산지유통센터 2
 
1.5%
남천안버섯영농조합법인 2
 
1.5%
철원농업협동조합 2
 
1.5%
김화농업협동조합 2
 
1.5%
Other values (111) 113
82.5%
2024-03-23T07:45:39.152887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 66
 
7.1%
조 35
 
3.8%
합 34
 
3.7%
협 29
 
3.1%
인 27
 
2.9%
법 26
 
2.8%
산 25
 
2.7%
동 25
 
2.7%
영 22
 
2.4%
목 21
 
2.3%
Other values (191) 614
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 885
95.8%
Space Separator 12
 
1.3%
Close Punctuation 7
 
0.8%
Open Punctuation 7
 
0.8%
Uppercase Letter 7
 
0.8%
Lowercase Letter 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 66
 
7.5%
조 35
 
4.0%
합 34
 
3.8%
협 29
 
3.3%
인 27
 
3.1%
법 26
 
2.9%
산 25
 
2.8%
동 25
 
2.8%
영 22
 
2.5%
목 21
 
2.4%
Other values (179) 575
65.0%
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 (%)
p 2
40.0%
e 2
40.0%
r 1
20.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 885
95.8%
Common 27
 
2.9%
Latin 12
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 66
 
7.5%
조 35
 
4.0%
합 34
 
3.8%
협 29
 
3.3%
인 27
 
3.1%
법 26
 
2.9%
산 25
 
2.8%
동 25
 
2.8%
영 22
 
2.5%
목 21
 
2.4%
Other values (179) 575
65.0%
Latin
ValueCountFrequency (%)
p 2
16.7%
G 2
16.7%
P 2
16.7%
e 2
16.7%
A 1
8.3%
r 1
8.3%
T 1
8.3%
K 1
8.3%
Common
ValueCountFrequency (%)
12
44.4%
) 7
25.9%
( 7
25.9%
& 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 885
95.8%
ASCII 39
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 66
 
7.5%
조 35
 
4.0%
합 34
 
3.8%
협 29
 
3.3%
인 27
 
3.1%
법 26
 
2.9%
산 25
 
2.8%
동 25
 
2.8%
영 22
 
2.5%
목 21
 
2.4%
Other values (179) 575
65.0%
ASCII
ValueCountFrequency (%)
12
30.8%
) 7
17.9%
( 7
17.9%
p 2
 
5.1%
G 2
 
5.1%
P 2
 
5.1%
e 2
 
5.1%
A 1
 
2.6%
r 1
 
2.6%
& 1
 
2.6%
Other values (2) 2
 
5.1%

대표자명
Categorical

Distinct38
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
이**
23 
김**
22 
정**
8 
박**
8 
조**
7 
Other values (33)
59 

Length

Max length6
Median length3
Mean length3.023622
Min length3

Unique

Unique17 ?
Unique (%)13.4%

Sample

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

Common Values

ValueCountFrequency (%)
이** 23
18.1%
김** 22
17.3%
정** 8
 
6.3%
박** 8
 
6.3%
조** 7
 
5.5%
최** 5
 
3.9%
황** 5
 
3.9%
고** 3
 
2.4%
유** 3
 
2.4%
구** 3
 
2.4%
Other values (28) 40
31.5%

Length

2024-03-23T07:45:39.594983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이 23
18.1%
김 22
17.3%
정 8
 
6.3%
박 8
 
6.3%
조 7
 
5.5%
최 5
 
3.9%
황 5
 
3.9%
고 3
 
2.4%
유 3
 
2.4%
구 3
 
2.4%
Other values (28) 40
31.5%

유효기간 시작일
Date

Distinct103
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2020-04-22 00:00:00
Maximum2023-03-16 00:00:00
2024-03-23T07:45:40.044989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:40.455106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

유효기간 종료일
Date

Distinct104
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-04-21 00:00:00
Maximum2026-09-27 00:00:00
2024-03-23T07:45:40.866802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:41.377130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대표품목
Categorical

Distinct31
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
쌀
24 
파프리카
17 
사과
12 
토마토
8 
단감
7 
Other values (26)
59 

Length

Max length7
Median length5
Mean length2.519685
Min length1

Unique

Unique15 ?
Unique (%)11.8%

Sample

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

Common Values

ValueCountFrequency (%)
쌀 24
18.9%
파프리카 17
13.4%
사과 12
 
9.4%
토마토 8
 
6.3%
단감 7
 
5.5%
배 7
 
5.5%
더덕 6
 
4.7%
딸기 6
 
4.7%
표고버섯 5
 
3.9%
포도 5
 
3.9%
Other values (21) 30
23.6%

Length

2024-03-23T07:45:41.759902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
쌀 24
18.9%
파프리카 17
13.4%
사과 12
 
9.4%
토마토 8
 
6.3%
단감 7
 
5.5%
배 7
 
5.5%
더덕 6
 
4.7%
딸기 6
 
4.7%
표고버섯 5
 
3.9%
포도 5
 
3.9%
Other values (21) 30
23.6%

도로명주소
Text

Distinct55
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T07:45:42.295669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.8267717
Min length7

Characters and Unicode

Total characters994
Distinct characters69
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

Unique31 ?
Unique (%)24.4%

Sample

1st row경상북도 문경시
2nd row경기도 화성시
3rd row경기도 남양주시
4th row경기도 남양주시
5th row광주광역시 광산구
ValueCountFrequency (%)
경상남도 37
 
14.6%
강원도 29
 
11.4%
철원군 21
 
8.3%
충청남도 14
 
5.5%
경상북도 12
 
4.7%
밀양시 12
 
4.7%
경기도 11
 
4.3%
전라남도 8
 
3.1%
창원시 7
 
2.8%
전라북도 5
 
2.0%
Other values (56) 98
38.6%
2024-03-23T07:45:43.340060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
12.8%
도 123
 
12.4%
시 66
 
6.6%
남 64
 
6.4%
경 62
 
6.2%
군 61
 
6.1%
원 59
 
5.9%
상 53
 
5.3%
강 31
 
3.1%
주 28
 
2.8%
Other values (59) 320
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 867
87.2%
Space Separator 127
 
12.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 123
14.2%
시 66
 
7.6%
남 64
 
7.4%
경 62
 
7.2%
군 61
 
7.0%
원 59
 
6.8%
상 53
 
6.1%
강 31
 
3.6%
주 28
 
3.2%
양 21
 
2.4%
Other values (58) 299
34.5%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 867
87.2%
Common 127
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 123
14.2%
시 66
 
7.6%
남 64
 
7.4%
경 62
 
7.2%
군 61
 
7.0%
원 59
 
6.8%
상 53
 
6.1%
강 31
 
3.6%
주 28
 
3.2%
양 21
 
2.4%
Other values (58) 299
34.5%
Common
ValueCountFrequency (%)
127
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 867
87.2%
ASCII 127
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
100.0%
Hangul
ValueCountFrequency (%)
도 123
14.2%
시 66
 
7.6%
남 64
 
7.4%
경 62
 
7.2%
군 61
 
7.0%
원 59
 
6.8%
상 53
 
6.1%
강 31
 
3.6%
주 28
 
3.2%
양 21
 
2.4%
Other values (58) 299
34.5%

등록농가수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8503937
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-23T07:45:43.798101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q38.5
95-th percentile19.8
Maximum97
Range96
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation9.6765784
Coefficient of variation (CV)1.412558
Kurtosis59.963132
Mean6.8503937
Median Absolute Deviation (MAD)3
Skewness6.6674254
Sum870
Variance93.63617
MonotonicityNot monotonic
2024-03-23T07:45:44.215988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 25
19.7%
3 18
14.2%
2 13
10.2%
5 12
9.4%
8 10
 
7.9%
13 8
 
6.3%
6 7
 
5.5%
4 7
 
5.5%
21 4
 
3.1%
12 4
 
3.1%
Other values (9) 19
15.0%
ValueCountFrequency (%)
1 25
19.7%
2 13
10.2%
3 18
14.2%
4 7
 
5.5%
5 12
9.4%
6 7
 
5.5%
7 3
 
2.4%
8 10
 
7.9%
9 3
 
2.4%
10 2
 
1.6%
ValueCountFrequency (%)
97 1
 
0.8%
22 2
 
1.6%
21 4
3.1%
17 1
 
0.8%
16 2
 
1.6%
14 2
 
1.6%
13 8
6.3%
12 4
3.1%
11 3
 
2.4%
10 2
 
1.6%

등록필지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.16535
Minimum0
Maximum8925
Zeros35
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-23T07:45:44.598227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q322.5
95-th percentile2053.8
Maximum8925
Range8925
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation1068.7506
Coefficient of variation (CV)3.5964846
Kurtosis36.418884
Mean297.16535
Median Absolute Deviation (MAD)3
Skewness5.4684383
Sum37740
Variance1142227.9
MonotonicityNot monotonic
2024-03-23T07:45:45.006477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
27.6%
4 11
 
8.7%
3 10
 
7.9%
1 10
 
7.9%
2 9
 
7.1%
5 4
 
3.1%
11 3
 
2.4%
10 2
 
1.6%
6 2
 
1.6%
53 1
 
0.8%
Other values (40) 40
31.5%
ValueCountFrequency (%)
0 35
27.6%
1 10
 
7.9%
2 9
 
7.1%
3 10
 
7.9%
4 11
 
8.7%
5 4
 
3.1%
6 2
 
1.6%
7 1
 
0.8%
9 1
 
0.8%
10 2
 
1.6%
ValueCountFrequency (%)
8925 1
0.8%
4376 1
0.8%
4190 1
0.8%
3026 1
0.8%
2817 1
0.8%
2488 1
0.8%
2175 1
0.8%
1771 1
0.8%
1726 1
0.8%
1218 1
0.8%

재배면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct92
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean793946.31
Minimum0
Maximum16690976
Zeros35
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-23T07:45:45.416188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8036
Q354717.5
95-th percentile6321214.9
Maximum16690976
Range16690976
Interquartile range (IQR)54717.5

Descriptive statistics

Standard deviation2639458.3
Coefficient of variation (CV)3.3244796
Kurtosis17.611781
Mean793946.31
Median Absolute Deviation (MAD)8036
Skewness4.0946673
Sum1.0083118 × 108
Variance6.9667403 × 1012
MonotonicityNot monotonic
2024-03-23T07:45:45.904911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 35
27.6%
7948.0 2
 
1.6%
12668.0 1
 
0.8%
9413.7 1
 
0.8%
14557.0 1
 
0.8%
65000.0 1
 
0.8%
29656.0 1
 
0.8%
9252.0 1
 
0.8%
3250.0 1
 
0.8%
2330.0 1
 
0.8%
Other values (82) 82
64.6%
ValueCountFrequency (%)
0.0 35
27.6%
1848.0 1
 
0.8%
1921.0 1
 
0.8%
2330.0 1
 
0.8%
2380.0 1
 
0.8%
2744.0 1
 
0.8%
2876.0 1
 
0.8%
3000.0 1
 
0.8%
3234.0 1
 
0.8%
3250.0 1
 
0.8%
ValueCountFrequency (%)
16690976.0 1
0.8%
13030084.0 1
0.8%
12964151.0 1
0.8%
8940652.0 1
0.8%
8688330.0 1
0.8%
7533517.0 1
0.8%
6958035.0 1
0.8%
4835301.31 1
0.8%
4221527.03 1
0.8%
3737970.0 1
0.8%

Interactions

2024-03-23T07:45:32.115038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:29.390453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:30.186129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:31.152020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:32.350928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:29.551771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:30.436726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:31.392843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:32.838485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:29.699307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:30.669351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:31.637376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:33.084453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:29.918288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:30.899357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:45:31.861564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:45:46.281764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호등록기관단계구분대표자명대표품목도로명주소등록농가수등록필지재배면적
등록번호1.0000.3260.4390.0000.0000.6090.5470.5940.582
등록기관0.3261.0000.0000.7990.9801.0000.8640.0000.000
단계구분0.4390.0001.0000.0000.0000.3450.1590.0000.000
대표자명0.0000.7990.0001.0000.8190.8030.5620.2750.389
대표품목0.0000.9800.0000.8191.0000.9830.2380.0000.000
도로명주소0.6091.0000.3450.8030.9831.0000.8600.0000.000
등록농가수0.5470.8640.1590.5620.2380.8601.0000.4460.408
등록필지0.5940.0000.0000.2750.0000.0000.4461.0001.000
재배면적0.5820.0000.0000.3890.0000.0000.4081.0001.000
2024-03-23T07:45:46.535677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단계구분대표품목대표자명
단계구분1.0000.0000.000
대표품목0.0001.0000.287
대표자명0.0000.2871.000
2024-03-23T07:45:46.699389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호등록농가수등록필지재배면적단계구분대표자명대표품목
등록번호1.000-0.693-0.152-0.1110.2850.0000.000
등록농가수-0.6931.0000.0810.0590.1490.2680.102
등록필지-0.1520.0811.0000.9520.0000.0930.000
재배면적-0.1110.0590.9521.0000.0000.1380.000
단계구분0.2850.1490.0000.0001.0000.0000.000
대표자명0.0000.2680.0930.1380.0001.0000.287
대표품목0.0000.1020.0000.0000.0000.2871.000

Missing values

2024-03-23T07:45:33.482085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:45:34.037401image/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
41136전남지원 품질관리과유통동곡농협이**2021-07-272024-07-26호박광주광역시 광산구800.0
51885전북지원 무주사무소생산양한오양**2022-03-122025-03-11사과전라북도 무주군72033569.0
62163강원지원 철원사무소유통동송농업협동조합진**2022-05-112025-05-10쌀강원도 철원군1600.0
72236강원지원 철원사무소유통김화농업협동조합엄**2022-06-052025-06-04쌀강원도 철원군2100.0
82240강원지원 철원사무소유통철원농업협동조합최**2022-06-052025-06-04쌀강원도 철원군1300.0
92241강원지원 철원사무소판매철원농업협동조합최**2022-06-052025-06-04쌀강원도 철원군1300.0
등록번호등록기관단계구분생산자단체명대표자명유효기간 시작일유효기간 종료일대표품목도로명주소등록농가수등록필지재배면적
11711981충남지원 품질관리과생산배광호배**2021-11-012024-10-31표고버섯대전광역시 유성구171921.0
11811982경남지원 함안사무소유통가야원예영농조합법인공**2021-12-082024-12-07<NA>경상남도 함안군1200.0
11911983경남지원 밀양사무소생산안경자안**2021-01-212024-01-20파프리카경상남도 밀양시148036.0
12011984경남지원 밀양사무소생산이용재이**2022-02-072025-02-06단감경상남도 밀양시4344600.0
12111985충남지원 서산ㆍ태안사무소생산원북면영농조합법인김**2022-03-312025-03-30토마토충청남도 태안군1224270.0
12211986경남지원 품질관리과생산변재복변**2022-07-292025-07-28참다래(키위)경상남도 창원시1422145.0
12311987경기지원 남양주ㆍ구리사무소유통농업회사법인 신선미세상(주)손**2022-10-192025-10-18상추경기도 남양주시500.0
12411988경북지원 청송ㆍ영양사무소유통농업회사법인주식회사솔스윗지**2022-12-202025-12-19사과경상북도 청송군100.0
12511989경남지원 산청사무소생산조형섭조**2023-01-112026-01-10곶감경상남도 산청군11025552.0
12611990경남지원 밀양사무소생산이병태(하늘농원)이**2023-01-132026-01-12사과경상남도 밀양시12324220.5