Overview

Dataset statistics

Number of variables19
Number of observations1234
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory199.0 KiB
Average record size in memory165.1 B

Variable types

Categorical9
Text2
Numeric8

Dataset

Description국립종자원 정부보급종 우선공급 내역에 대한 데이터로 년산,지원명,사업체명,사업체종류,시도,시군구,품종명,소계_신청량,사전_신청량,우선_신청량,소계_배정량,사전_배정량,우선_배정량,소계_농가량,사전_농가량,우선_농가량,소계_농가잔량,사전_농가잔량,우선_농가잔량 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15066259/fileData.do

Alerts

사전_신청량 has constant value ""Constant
사전_배정량 has constant value ""Constant
사전_농가량 has constant value ""Constant
사전_농가잔량 has constant value ""Constant
지원명 is highly overall correlated with 시도 and 1 other fieldsHigh correlation
시도 is highly overall correlated with 지원명 and 1 other fieldsHigh correlation
소계_신청량 is highly overall correlated with 우선_신청량 and 4 other fieldsHigh correlation
우선_신청량 is highly overall correlated with 소계_신청량 and 4 other fieldsHigh correlation
소계_배정량 is highly overall correlated with 소계_신청량 and 4 other fieldsHigh correlation
우선_배정량 is highly overall correlated with 소계_신청량 and 4 other fieldsHigh correlation
소계_농가량 is highly overall correlated with 소계_신청량 and 4 other fieldsHigh correlation
우선_농가량 is highly overall correlated with 소계_신청량 and 4 other fieldsHigh correlation
소계_농가잔량 is highly overall correlated with 우선_농가잔량High correlation
우선_농가잔량 is highly overall correlated with 소계_농가잔량High correlation
품종명 is highly overall correlated with 지원명 and 1 other fieldsHigh correlation
소계_배정량 has 30 (2.4%) zerosZeros
우선_배정량 has 30 (2.4%) zerosZeros
소계_농가량 has 47 (3.8%) zerosZeros
우선_농가량 has 47 (3.8%) zerosZeros
소계_농가잔량 has 1133 (91.8%) zerosZeros
우선_농가잔량 has 1133 (91.8%) zerosZeros

Reproduction

Analysis started2023-12-12 04:37:26.972456
Analysis finished2023-12-12 04:37:36.891566
Duration9.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2021
437 
2022
431 
2020
366 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2021
5th row2022

Common Values

ValueCountFrequency (%)
2021 437
35.4%
2022 431
34.9%
2020 366
29.7%

Length

2023-12-12T13:37:36.981895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:37.112828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 437
35.4%
2022 431
34.9%
2020 366
29.7%

지원명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
전남지원
458 
전북지원
274 
경기종자관리소
147 
충남지원
131 
경북지원
103 
Other values (4)
121 

Length

Max length8
Median length4
Mean length4.3735818
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남지원
2nd row경남지원
3rd row강원지원
4th row강원지원
5th row강원지원

Common Values

ValueCountFrequency (%)
전남지원 458
37.1%
전북지원 274
22.2%
경기종자관리소 147
 
11.9%
충남지원 131
 
10.6%
경북지원 103
 
8.3%
경남지원 63
 
5.1%
강원지원 30
 
2.4%
충북지원 23
 
1.9%
제주도농업기술원 5
 
0.4%

Length

2023-12-12T13:37:37.261617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:37.435856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전남지원 458
37.1%
전북지원 274
22.2%
경기종자관리소 147
 
11.9%
충남지원 131
 
10.6%
경북지원 103
 
8.3%
경남지원 63
 
5.1%
강원지원 30
 
2.4%
충북지원 23
 
1.9%
제주도농업기술원 5
 
0.4%
Distinct356
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T13:37:37.784062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length9.4570502
Min length4

Characters and Unicode

Total characters11670
Distinct characters262
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)5.3%

Sample

1st row고성거제통영농협쌀조합공동사업법인
2nd row고성거제통영농협쌀조합공동사업법인
3rd row동송농협RPC
4th row동송농협RPC
5th row동송농협RPC
ValueCountFrequency (%)
영농조합법인 26
 
1.9%
나비골월송친환경영농조합법인 12
 
0.9%
농업회사법인 12
 
0.9%
법인 10
 
0.7%
우리밀 10
 
0.7%
세지농업협동조합 8
 
0.6%
신김포농협rpc 8
 
0.6%
천지농협협동조합 7
 
0.5%
팽성농협rpc 7
 
0.5%
울산연합rpc 7
 
0.5%
Other values (372) 1265
92.2%
2023-12-12T13:37:38.272591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1166
 
10.0%
715
 
6.1%
703
 
6.0%
590
 
5.1%
503
 
4.3%
485
 
4.2%
393
 
3.4%
376
 
3.2%
351
 
3.0%
C 295
 
2.5%
Other values (252) 6093
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10317
88.4%
Uppercase Letter 885
 
7.6%
Close Punctuation 155
 
1.3%
Open Punctuation 155
 
1.3%
Space Separator 143
 
1.2%
Decimal Number 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1166
 
11.3%
715
 
6.9%
703
 
6.8%
590
 
5.7%
503
 
4.9%
485
 
4.7%
393
 
3.8%
376
 
3.6%
351
 
3.4%
246
 
2.4%
Other values (241) 4789
46.4%
Uppercase Letter
ValueCountFrequency (%)
C 295
33.3%
P 286
32.3%
R 286
32.3%
S 9
 
1.0%
D 9
 
1.0%
Decimal Number
ValueCountFrequency (%)
3 5
33.3%
5 5
33.3%
1 5
33.3%
Close Punctuation
ValueCountFrequency (%)
) 155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 155
100.0%
Space Separator
ValueCountFrequency (%)
143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10317
88.4%
Latin 885
 
7.6%
Common 468
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1166
 
11.3%
715
 
6.9%
703
 
6.8%
590
 
5.7%
503
 
4.9%
485
 
4.7%
393
 
3.8%
376
 
3.6%
351
 
3.4%
246
 
2.4%
Other values (241) 4789
46.4%
Common
ValueCountFrequency (%)
) 155
33.1%
( 155
33.1%
143
30.6%
3 5
 
1.1%
5 5
 
1.1%
1 5
 
1.1%
Latin
ValueCountFrequency (%)
C 295
33.3%
P 286
32.3%
R 286
32.3%
S 9
 
1.0%
D 9
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10317
88.4%
ASCII 1353
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1166
 
11.3%
715
 
6.9%
703
 
6.8%
590
 
5.7%
503
 
4.9%
485
 
4.7%
393
 
3.8%
376
 
3.6%
351
 
3.4%
246
 
2.4%
Other values (241) 4789
46.4%
ASCII
ValueCountFrequency (%)
C 295
21.8%
P 286
21.1%
R 286
21.1%
) 155
11.5%
( 155
11.5%
143
10.6%
S 9
 
0.7%
D 9
 
0.7%
3 5
 
0.4%
5 5
 
0.4%

사업체종류
Categorical

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
정부지원RPC
352 
맥류우선공급업체
255 
들녘경영체
223 
시군 추천업체
124 
품종명칭 경영체
121 
Other values (3)
159 

Length

Max length11
Median length9
Mean length7.3095624
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정부지원RPC 352
28.5%
맥류우선공급업체 255
20.7%
들녘경영체 223
18.1%
시군 추천업체 124
 
10.0%
품종명칭 경영체 121
 
9.8%
기존 우선공급업체 92
 
7.5%
당해연도 후보 경영체 55
 
4.5%
고품질쌀 최적 경영체 12
 
1.0%

Length

2023-12-12T13:37:38.808729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:38.982755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정부지원rpc 352
20.6%
맥류우선공급업체 255
15.0%
들녘경영체 223
13.1%
경영체 188
11.0%
시군 124
 
7.3%
추천업체 124
 
7.3%
품종명칭 121
 
7.1%
기존 92
 
5.4%
우선공급업체 92
 
5.4%
당해연도 55
 
3.2%
Other values (3) 79
 
4.6%

시도
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
전남
442 
전북
274 
경기
147 
충남
125 
경북
103 
Other values (7)
143 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남
2nd row경남
3rd row강원
4th row강원
5th row강원

Common Values

ValueCountFrequency (%)
전남 442
35.8%
전북 274
22.2%
경기 147
 
11.9%
충남 125
 
10.1%
경북 103
 
8.3%
경남 56
 
4.5%
강원 30
 
2.4%
충북 23
 
1.9%
광주 16
 
1.3%
울산 7
 
0.6%
Other values (2) 11
 
0.9%

Length

2023-12-12T13:37:39.155477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전남 442
35.8%
전북 274
22.2%
경기 147
 
11.9%
충남 125
 
10.1%
경북 103
 
8.3%
경남 56
 
4.5%
강원 30
 
2.4%
충북 23
 
1.9%
광주 16
 
1.3%
울산 7
 
0.6%
Other values (2) 11
 
0.9%
Distinct98
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T13:37:39.512128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0097245
Min length2

Characters and Unicode

Total characters3714
Distinct characters89
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.5%

Sample

1st row고성군
2nd row고성군
3rd row철원군
4th row철원군
5th row철원군
ValueCountFrequency (%)
익산시 67
 
5.4%
해남군 64
 
5.2%
김제시 58
 
4.7%
나주시 47
 
3.8%
영광군 46
 
3.7%
함평군 44
 
3.6%
장흥군 43
 
3.5%
군산시 38
 
3.1%
화순군 35
 
2.8%
평택시 34
 
2.8%
Other values (88) 758
61.4%
2023-12-12T13:37:40.047215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
639
 
17.2%
610
 
16.4%
181
 
4.9%
133
 
3.6%
107
 
2.9%
91
 
2.5%
86
 
2.3%
82
 
2.2%
78
 
2.1%
76
 
2.0%
Other values (79) 1631
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3714
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
639
 
17.2%
610
 
16.4%
181
 
4.9%
133
 
3.6%
107
 
2.9%
91
 
2.5%
86
 
2.3%
82
 
2.2%
78
 
2.1%
76
 
2.0%
Other values (79) 1631
43.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3714
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
639
 
17.2%
610
 
16.4%
181
 
4.9%
133
 
3.6%
107
 
2.9%
91
 
2.5%
86
 
2.3%
82
 
2.2%
78
 
2.1%
76
 
2.0%
Other values (79) 1631
43.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3714
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
639
 
17.2%
610
 
16.4%
181
 
4.9%
133
 
3.6%
107
 
2.9%
91
 
2.5%
86
 
2.3%
82
 
2.2%
78
 
2.1%
76
 
2.0%
Other values (79) 1631
43.9%

품종명
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
신동진벼(일반)
227 
새청무(일반)
159 
삼광벼(일반)
113 
새금강밀(일반)
87 
금강밀(일반)
71 
Other values (31)
577 

Length

Max length10
Median length7
Mean length7.5494327
Min length6

Unique

Unique6 ?
Unique (%)0.5%

Sample

1st row영호진미(일반)
2nd row해담쌀(일반)
3rd row오대벼(일반)
4th row오대벼(일반)
5th row오대벼(일반)

Common Values

ValueCountFrequency (%)
신동진벼(일반) 227
18.4%
새청무(일반) 159
12.9%
삼광벼(일반) 113
 
9.2%
새금강밀(일반) 87
 
7.1%
금강밀(일반) 71
 
5.8%
추청벼(일반) 65
 
5.3%
일품벼(일반) 60
 
4.9%
동진찰벼(일반) 51
 
4.1%
백옥찰벼(일반) 50
 
4.1%
고시히카리(일반) 44
 
3.6%
Other values (26) 307
24.9%

Length

2023-12-12T13:37:40.218910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신동진벼(일반 227
18.4%
새청무(일반 159
12.9%
삼광벼(일반 113
 
9.2%
새금강밀(일반 87
 
7.1%
금강밀(일반 71
 
5.8%
추청벼(일반 65
 
5.3%
일품벼(일반 60
 
4.9%
동진찰벼(일반 51
 
4.1%
백옥찰벼(일반 50
 
4.1%
고시히카리(일반 44
 
3.6%
Other values (26) 307
24.9%

소계_신청량
Real number (ℝ)

HIGH CORRELATION 

Distinct390
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20746.904
Minimum0
Maximum300000
Zeros8
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:40.382422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile566
Q13000
median9000
Q325000
95-th percentile77346
Maximum300000
Range300000
Interquartile range (IQR)22000

Descriptive statistics

Standard deviation32111.473
Coefficient of variation (CV)1.5477718
Kurtosis19.186036
Mean20746.904
Median Absolute Deviation (MAD)7000
Skewness3.7030107
Sum25601680
Variance1.0311467 × 109
MonotonicityNot monotonic
2023-12-12T13:37:40.546626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 57
 
4.6%
10000 55
 
4.5%
20000 41
 
3.3%
4000 40
 
3.2%
3000 38
 
3.1%
5000 37
 
3.0%
6000 33
 
2.7%
1000 29
 
2.4%
30000 24
 
1.9%
40000 24
 
1.9%
Other values (380) 856
69.4%
ValueCountFrequency (%)
0 8
0.6%
40 1
 
0.1%
60 2
 
0.2%
80 2
 
0.2%
100 4
 
0.3%
140 1
 
0.1%
160 2
 
0.2%
200 15
1.2%
260 1
 
0.1%
300 2
 
0.2%
ValueCountFrequency (%)
300000 2
0.2%
225180 1
 
0.1%
222140 1
 
0.1%
220000 1
 
0.1%
219440 1
 
0.1%
210000 1
 
0.1%
200000 3
0.2%
180180 1
 
0.1%
175000 1
 
0.1%
173380 1
 
0.1%

사전_신청량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
0
1234 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1234
100.0%

Length

2023-12-12T13:37:40.675901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:40.759283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1234
100.0%

우선_신청량
Real number (ℝ)

HIGH CORRELATION 

Distinct390
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20746.904
Minimum0
Maximum300000
Zeros8
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:40.848412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile566
Q13000
median9000
Q325000
95-th percentile77346
Maximum300000
Range300000
Interquartile range (IQR)22000

Descriptive statistics

Standard deviation32111.473
Coefficient of variation (CV)1.5477718
Kurtosis19.186036
Mean20746.904
Median Absolute Deviation (MAD)7000
Skewness3.7030107
Sum25601680
Variance1.0311467 × 109
MonotonicityNot monotonic
2023-12-12T13:37:40.967028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 57
 
4.6%
10000 55
 
4.5%
20000 41
 
3.3%
4000 40
 
3.2%
3000 38
 
3.1%
5000 37
 
3.0%
6000 33
 
2.7%
1000 29
 
2.4%
30000 24
 
1.9%
40000 24
 
1.9%
Other values (380) 856
69.4%
ValueCountFrequency (%)
0 8
0.6%
40 1
 
0.1%
60 2
 
0.2%
80 2
 
0.2%
100 4
 
0.3%
140 1
 
0.1%
160 2
 
0.2%
200 15
1.2%
260 1
 
0.1%
300 2
 
0.2%
ValueCountFrequency (%)
300000 2
0.2%
225180 1
 
0.1%
222140 1
 
0.1%
220000 1
 
0.1%
219440 1
 
0.1%
210000 1
 
0.1%
200000 3
0.2%
180180 1
 
0.1%
175000 1
 
0.1%
173380 1
 
0.1%

소계_배정량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct515
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14475.972
Minimum0
Maximum256060
Zeros30
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:41.155598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile246
Q12000
median6000
Q316485
95-th percentile56077
Maximum256060
Range256060
Interquartile range (IQR)14485

Descriptive statistics

Standard deviation23329.459
Coefficient of variation (CV)1.6115987
Kurtosis23.810076
Mean14475.972
Median Absolute Deviation (MAD)4830
Skewness4.0280797
Sum17863350
Variance5.4426364 × 108
MonotonicityNot monotonic
2023-12-12T13:37:41.286190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 37
 
3.0%
5000 33
 
2.7%
10000 33
 
2.7%
6000 30
 
2.4%
0 30
 
2.4%
1000 25
 
2.0%
3000 23
 
1.9%
4000 23
 
1.9%
20000 21
 
1.7%
8000 19
 
1.5%
Other values (505) 960
77.8%
ValueCountFrequency (%)
0 30
2.4%
20 1
 
0.1%
40 2
 
0.2%
60 4
 
0.3%
80 2
 
0.2%
100 4
 
0.3%
120 5
 
0.4%
180 1
 
0.1%
200 9
 
0.7%
220 4
 
0.3%
ValueCountFrequency (%)
256060 1
0.1%
219440 1
0.1%
174000 1
0.1%
173380 1
0.1%
160000 1
0.1%
150000 1
0.1%
146800 1
0.1%
138000 1
0.1%
136820 1
0.1%
130000 1
0.1%

사전_배정량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
0
1234 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1234
100.0%

Length

2023-12-12T13:37:41.397280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:41.496754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1234
100.0%

우선_배정량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct515
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14475.972
Minimum0
Maximum256060
Zeros30
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:41.607874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile246
Q12000
median6000
Q316485
95-th percentile56077
Maximum256060
Range256060
Interquartile range (IQR)14485

Descriptive statistics

Standard deviation23329.459
Coefficient of variation (CV)1.6115987
Kurtosis23.810076
Mean14475.972
Median Absolute Deviation (MAD)4830
Skewness4.0280797
Sum17863350
Variance5.4426364 × 108
MonotonicityNot monotonic
2023-12-12T13:37:41.730700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 37
 
3.0%
5000 33
 
2.7%
10000 33
 
2.7%
6000 30
 
2.4%
0 30
 
2.4%
1000 25
 
2.0%
3000 23
 
1.9%
4000 23
 
1.9%
20000 21
 
1.7%
8000 19
 
1.5%
Other values (505) 960
77.8%
ValueCountFrequency (%)
0 30
2.4%
20 1
 
0.1%
40 2
 
0.2%
60 4
 
0.3%
80 2
 
0.2%
100 4
 
0.3%
120 5
 
0.4%
180 1
 
0.1%
200 9
 
0.7%
220 4
 
0.3%
ValueCountFrequency (%)
256060 1
0.1%
219440 1
0.1%
174000 1
0.1%
173380 1
0.1%
160000 1
0.1%
150000 1
0.1%
146800 1
0.1%
138000 1
0.1%
136820 1
0.1%
130000 1
0.1%

소계_농가량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct524
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14064.408
Minimum0
Maximum256060
Zeros47
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:41.836357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile120
Q12000
median6000
Q316000
95-th percentile55223
Maximum256060
Range256060
Interquartile range (IQR)14000

Descriptive statistics

Standard deviation22714.331
Coefficient of variation (CV)1.6150221
Kurtosis25.028577
Mean14064.408
Median Absolute Deviation (MAD)4900
Skewness4.0882851
Sum17355480
Variance5.1594082 × 108
MonotonicityNot monotonic
2023-12-12T13:37:41.949066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47
 
3.8%
2000 37
 
3.0%
10000 34
 
2.8%
5000 33
 
2.7%
1000 27
 
2.2%
6000 27
 
2.2%
4000 22
 
1.8%
3000 20
 
1.6%
20000 18
 
1.5%
8000 18
 
1.5%
Other values (514) 951
77.1%
ValueCountFrequency (%)
0 47
3.8%
20 1
 
0.1%
40 2
 
0.2%
60 4
 
0.3%
80 2
 
0.2%
100 4
 
0.3%
120 5
 
0.4%
180 1
 
0.1%
200 8
 
0.6%
220 4
 
0.3%
ValueCountFrequency (%)
256060 1
0.1%
219440 1
0.1%
164000 1
0.1%
160000 1
0.1%
155140 1
0.1%
150000 1
0.1%
146800 1
0.1%
138000 1
0.1%
136820 1
0.1%
121900 1
0.1%

사전_농가량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
0
1234 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1234
100.0%

Length

2023-12-12T13:37:42.074093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:42.148958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1234
100.0%

우선_농가량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct524
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14064.408
Minimum0
Maximum256060
Zeros47
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T13:37:42.238344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile120
Q12000
median6000
Q316000
95-th percentile55223
Maximum256060
Range256060
Interquartile range (IQR)14000

Descriptive statistics

Standard deviation22714.331
Coefficient of variation (CV)1.6150221
Kurtosis25.028577
Mean14064.408
Median Absolute Deviation (MAD)4900
Skewness4.0882851
Sum17355480
Variance5.1594082 × 108
MonotonicityNot monotonic
2023-12-12T13:37:42.355798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47
 
3.8%
2000 37
 
3.0%
10000 34
 
2.8%
5000 33
 
2.7%
1000 27
 
2.2%
6000 27
 
2.2%
4000 22
 
1.8%
3000 20
 
1.6%
20000 18
 
1.5%
8000 18
 
1.5%
Other values (514) 951
77.1%
ValueCountFrequency (%)
0 47
3.8%
20 1
 
0.1%
40 2
 
0.2%
60 4
 
0.3%
80 2
 
0.2%
100 4
 
0.3%
120 5
 
0.4%
180 1
 
0.1%
200 8
 
0.6%
220 4
 
0.3%
ValueCountFrequency (%)
256060 1
0.1%
219440 1
0.1%
164000 1
0.1%
160000 1
0.1%
155140 1
0.1%
150000 1
0.1%
146800 1
0.1%
138000 1
0.1%
136820 1
0.1%
121900 1
0.1%

소계_농가잔량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411.56402
Minimum-1000
Maximum26600
Zeros1133
Zeros (%)91.8%
Negative1
Negative (%)0.1%
Memory size11.0 KiB
2023-12-12T13:37:42.472389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1000
5-th percentile0
Q10
median0
Q30
95-th percentile1856
Maximum26600
Range27600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2217.489
Coefficient of variation (CV)5.3879565
Kurtosis61.689762
Mean411.56402
Median Absolute Deviation (MAD)0
Skewness7.3863774
Sum507870
Variance4917257.6
MonotonicityNot monotonic
2023-12-12T13:37:42.596133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1133
91.8%
3000 8
 
0.6%
2000 5
 
0.4%
200 4
 
0.3%
20 3
 
0.2%
120 3
 
0.2%
4000 3
 
0.2%
800 3
 
0.2%
1400 3
 
0.2%
6000 2
 
0.2%
Other values (63) 67
 
5.4%
ValueCountFrequency (%)
-1000 1
 
0.1%
0 1133
91.8%
10 1
 
0.1%
20 3
 
0.2%
40 1
 
0.1%
80 1
 
0.1%
100 1
 
0.1%
120 3
 
0.2%
200 4
 
0.3%
280 1
 
0.1%
ValueCountFrequency (%)
26600 1
0.1%
23860 1
0.1%
21920 1
0.1%
20880 1
0.1%
19800 1
0.1%
18760 1
0.1%
18240 1
0.1%
17600 1
0.1%
16580 1
0.1%
16000 1
0.1%

사전_농가잔량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
0
1234 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1234
100.0%

Length

2023-12-12T13:37:42.714069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:42.819144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1234
100.0%

우선_농가잔량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411.56402
Minimum-1000
Maximum26600
Zeros1133
Zeros (%)91.8%
Negative1
Negative (%)0.1%
Memory size11.0 KiB
2023-12-12T13:37:42.952892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1000
5-th percentile0
Q10
median0
Q30
95-th percentile1856
Maximum26600
Range27600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2217.489
Coefficient of variation (CV)5.3879565
Kurtosis61.689762
Mean411.56402
Median Absolute Deviation (MAD)0
Skewness7.3863774
Sum507870
Variance4917257.6
MonotonicityNot monotonic
2023-12-12T13:37:43.082453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1133
91.8%
3000 8
 
0.6%
2000 5
 
0.4%
200 4
 
0.3%
20 3
 
0.2%
120 3
 
0.2%
4000 3
 
0.2%
800 3
 
0.2%
1400 3
 
0.2%
6000 2
 
0.2%
Other values (63) 67
 
5.4%
ValueCountFrequency (%)
-1000 1
 
0.1%
0 1133
91.8%
10 1
 
0.1%
20 3
 
0.2%
40 1
 
0.1%
80 1
 
0.1%
100 1
 
0.1%
120 3
 
0.2%
200 4
 
0.3%
280 1
 
0.1%
ValueCountFrequency (%)
26600 1
0.1%
23860 1
0.1%
21920 1
0.1%
20880 1
0.1%
19800 1
0.1%
18760 1
0.1%
18240 1
0.1%
17600 1
0.1%
16580 1
0.1%
16000 1
0.1%

Interactions

2023-12-12T13:37:35.305053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:28.397217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.736210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.683225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.489989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.444494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.348593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.336618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.409041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:28.553398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.870600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.777880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.625056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.546279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.450127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.449016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.554584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:28.662821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.992843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.877946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.727438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.667469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.567414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.556750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.697584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:28.793348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.118525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.977420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.823810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.774321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.671353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.692120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.819515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:28.912071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.243184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.069086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.933083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.919882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.766739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.826841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.961211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.023247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.348457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.164616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.075698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.020513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.918036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.956507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:36.096039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.176704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.447607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.288166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.180197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.150409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.032260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.085390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:36.227299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:29.326858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:30.574617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:31.381155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:32.314812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:33.254719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:34.167819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:35.205206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:37:43.182222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명사업체종류시도시군구품종명소계_신청량우선_신청량소계_배정량우선_배정량소계_농가량우선_농가량소계_농가잔량우선_농가잔량
년산1.0000.0000.2300.0000.0000.3630.0000.0000.0000.0000.0000.0000.0160.016
지원명0.0001.0000.5921.0001.0000.9250.2720.2720.3150.3150.3290.3290.1970.197
사업체종류0.2300.5921.0000.6570.8620.8110.2060.2060.1980.1980.1920.1920.0000.000
시도0.0001.0000.6571.0001.0000.9070.2750.2750.3200.3200.3290.3290.1670.167
시군구0.0001.0000.8621.0001.0000.9320.7170.7170.7160.7160.6980.6980.6170.617
품종명0.3630.9250.8110.9070.9321.0000.2400.2400.2600.2600.2840.2840.0000.000
소계_신청량0.0000.2720.2060.2750.7170.2401.0001.0000.9450.9450.9460.9460.3540.354
우선_신청량0.0000.2720.2060.2750.7170.2401.0001.0000.9450.9450.9460.9460.3540.354
소계_배정량0.0000.3150.1980.3200.7160.2600.9450.9451.0001.0000.9990.9990.4570.457
우선_배정량0.0000.3150.1980.3200.7160.2600.9450.9451.0001.0000.9990.9990.4570.457
소계_농가량0.0000.3290.1920.3290.6980.2840.9460.9460.9990.9991.0001.0000.3740.374
우선_농가량0.0000.3290.1920.3290.6980.2840.9460.9460.9990.9991.0001.0000.3740.374
소계_농가잔량0.0160.1970.0000.1670.6170.0000.3540.3540.4570.4570.3740.3741.0001.000
우선_농가잔량0.0160.1970.0000.1670.6170.0000.3540.3540.4570.4570.3740.3741.0001.000
2023-12-12T13:37:43.354611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명시도사업체종류품종명
년산1.0000.0000.0000.1490.178
지원명0.0001.0000.9990.3410.611
시도0.0000.9991.0000.3470.521
사업체종류0.1490.3410.3471.0000.465
품종명0.1780.6110.5210.4651.000
2023-12-12T13:37:43.492728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소계_신청량우선_신청량소계_배정량우선_배정량소계_농가량우선_농가량소계_농가잔량우선_농가잔량년산지원명사업체종류시도품종명
소계_신청량1.0001.0000.9160.9160.9060.9060.1340.1340.0000.0900.1020.1200.082
우선_신청량1.0001.0000.9160.9160.9060.9060.1340.1340.0000.0900.1020.1200.082
소계_배정량0.9160.9161.0001.0000.9850.9850.1860.1860.0000.1050.0980.1410.089
우선_배정량0.9160.9161.0001.0000.9850.9850.1860.1860.0000.1050.0980.1410.089
소계_농가량0.9060.9060.9850.9851.0001.0000.0910.0910.0000.1110.0950.1460.098
우선_농가량0.9060.9060.9850.9851.0001.0000.0910.0910.0000.1110.0950.1460.098
소계_농가잔량0.1340.1340.1860.1860.0910.0911.0001.0000.0100.0900.0000.0710.000
우선_농가잔량0.1340.1340.1860.1860.0910.0911.0001.0000.0100.0900.0000.0710.000
년산0.0000.0000.0000.0000.0000.0000.0100.0101.0000.0000.1490.0000.178
지원명0.0900.0900.1050.1050.1110.1110.0900.0900.0001.0000.3410.9990.611
사업체종류0.1020.1020.0980.0980.0950.0950.0000.0000.1490.3411.0000.3470.465
시도0.1200.1200.1410.1410.1460.1460.0710.0710.0000.9990.3471.0000.521
품종명0.0820.0820.0890.0890.0980.0980.0000.0000.1780.6110.4650.5211.000

Missing values

2023-12-12T13:37:36.433728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:37:36.733227image/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

년산지원명사업체명사업체종류시도시군구품종명소계_신청량사전_신청량우선_신청량소계_배정량사전_배정량우선_배정량소계_농가량사전_농가량우선_농가량소계_농가잔량사전_농가잔량우선_농가잔량
02020경남지원고성거제통영농협쌀조합공동사업법인정부지원RPC경남고성군영호진미(일반)600006000600006000600006000000
12020경남지원고성거제통영농협쌀조합공동사업법인정부지원RPC경남고성군해담쌀(일반)200002000200002000200002000000
22020강원지원동송농협RPC정부지원RPC강원철원군오대벼(일반)200000020000011600001160001160000116000000
32021강원지원동송농협RPC정부지원RPC강원철원군오대벼(일반)200000020000014680001468001468000146800000
42022강원지원동송농협RPC정부지원RPC강원철원군오대벼(일반)220000022000013800001380001380000138000000
52021강원지원동철원농협기존 우선공급업체강원철원군오대벼(일반)710000710005210005210052100052100000
62022강원지원동철원농협기존 우선공급업체강원철원군오대벼(일반)650000650004100004100041000041000000
72020강원지원철원농협RPC정부지원RPC강원철원군오대벼(일반)10000001000005800005800058000058000000
82020강원지원동철원농협기존 우선공급업체강원철원군오대벼(일반)710000710004100004100041000041000000
92021강원지원철원농협RPC정부지원RPC강원철원군오대벼(일반)900000900006610006610066100066100000
년산지원명사업체명사업체종류시도시군구품종명소계_신청량사전_신청량우선_신청량소계_배정량사전_배정량우선_배정량소계_농가량사전_농가량우선_농가량소계_농가잔량사전_농가잔량우선_농가잔량
12242021경남지원합천우리밀영농조합법인맥류우선공급업체경남합천군백강밀(일반)400000400002000002000020000020000000
12252022경남지원합천우리밀영농조합법인맥류우선공급업체경남합천군백강밀(일반)300000300003000003000030000030000000
12262021충남지원칠산원예영농조합들녘경영체충남부여군친들벼(일반)800080080008000008000800
12272021충남지원여울영농조합법인맥류우선공급업체충남부여군금강밀(일반)760007600760007600760007600000
12282022충남지원여울영농조합법인맥류우선공급업체충남부여군금강밀(일반)500005000500005000500005000000
12292020충남지원꿈에영농조합법인맥류우선공급업체충남부여군금강밀(일반)600006000600006000600006000000
12302021충남지원꿈에영농조합법인맥류우선공급업체충남부여군금강밀(일반)500005000500005000500005000000
12312022전남지원봉황농업협동조합들녘경영체전남나주시백옥찰벼(일반)224002240000000000
12322022충남지원세도청송영농조합법인들녘경영체충남부여군친들벼(일반)400004000400004000400004000000
12332020충남지원세도청송영농조합법인들녘경영체충남부여군친들벼(일반)100001000100001000100001000000