Overview

Dataset statistics

Number of variables9
Number of observations5318
Missing cells5621
Missing cells (%)11.7%
Duplicate rows103
Duplicate rows (%)1.9%
Total size in memory384.4 KiB
Average record size in memory74.0 B

Variable types

Text3
Categorical3
Numeric2
DateTime1

Dataset

Description국립농산물품질관리원에서 관리하는 생산, 유통 단계에서의 농산물 독소류 분석결과(품목, 수거단계, 재배양식, 생산 지역, 재배면적, 조사물량, 등록일자, 분석결과)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20170912000000000793

Alerts

Dataset has 103 (1.9%) duplicate rowsDuplicates
재배양식 is highly imbalanced (91.3%)Imbalance
분석결과 is highly imbalanced (96.3%)Imbalance
재배면적 has 3875 (72.9%) missing valuesMissing
조사물량 has 1744 (32.8%) missing valuesMissing
재배면적 is highly skewed (γ1 = 22.33281417)Skewed
조사물량 is highly skewed (γ1 = 48.33554364)Skewed
조사물량 has 80 (1.5%) zerosZeros

Reproduction

Analysis started2024-03-23 07:38:20.348369
Analysis finished2024-03-23 07:38:24.871683
Duration4.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목명
Text

Distinct61
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
2024-03-23T07:38:25.096759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length13
Mean length4.2124859
Min length1

Characters and Unicode

Total characters22402
Distinct characters87
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.2%

Sample

1st row콩(대두)
2nd row콩(대두)
3rd row서리태
4th row서리태
5th row쌀보리쌀
ValueCountFrequency (%)
멥쌀(일반 1194
22.4%
옥수수 945
17.7%
콩(대두 448
 
8.4%
쌀 350
 
6.6%
쌀보리쌀 301
 
5.6%
찹쌀(일반 241
 
4.5%
기타(콩 230
 
4.3%
기타(보리쌀 187
 
3.5%
기타(쌀 135
 
2.5%
메현미 126
 
2.4%
Other values (56) 1172
22.0%
2024-03-23T07:38:25.906586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
쌀 3055
13.6%
( 2605
11.6%
) 2605
11.6%
수 2038
 
9.1%
일 1435
 
6.4%
반 1435
 
6.4%
멥 1194
 
5.3%
옥 945
 
4.2%
기 790
 
3.5%
콩 782
 
3.5%
Other values (77) 5518
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17180
76.7%
Open Punctuation 2605
 
11.6%
Close Punctuation 2605
 
11.6%
Space Separator 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 3055
17.8%
수 2038
11.9%
일 1435
 
8.4%
반 1435
 
8.4%
멥 1194
 
6.9%
옥 945
 
5.5%
기 790
 
4.6%
콩 782
 
4.6%
리 716
 
4.2%
타 685
 
4.0%
Other values (74) 4105
23.9%
Open Punctuation
ValueCountFrequency (%)
( 2605
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2605
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17180
76.7%
Common 5222
 
23.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 3055
17.8%
수 2038
11.9%
일 1435
 
8.4%
반 1435
 
8.4%
멥 1194
 
6.9%
옥 945
 
5.5%
기 790
 
4.6%
콩 782
 
4.6%
리 716
 
4.2%
타 685
 
4.0%
Other values (74) 4105
23.9%
Common
ValueCountFrequency (%)
( 2605
49.9%
) 2605
49.9%
12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17180
76.7%
ASCII 5222
 
23.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
쌀 3055
17.8%
수 2038
11.9%
일 1435
 
8.4%
반 1435
 
8.4%
멥 1194
 
6.9%
옥 945
 
5.5%
기 790
 
4.6%
콩 782
 
4.6%
리 716
 
4.2%
타 685
 
4.0%
Other values (74) 4105
23.9%
ASCII
ValueCountFrequency (%)
( 2605
49.9%
) 2605
49.9%
12
 
0.2%

수거단계
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
유통/판매
3877 
생산
1441 

Length

Max length5
Median length5
Mean length4.1871004
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생산
2nd row생산
3rd row생산
4th row생산
5th row유통/판매

Common Values

ValueCountFrequency (%)
유통/판매 3877
72.9%
생산 1441
 
27.1%

Length

2024-03-23T07:38:26.316061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:26.623380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통/판매 3877
72.9%
생산 1441
 
27.1%

재배양식
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
일반
5190 
친환경(인증) 무농약
 
63
GAP(인증)
 
35
친환경(인증) 유기
 
29
지리적표시
 
1

Length

Max length11
Median length3
Mean length3.1664159
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반 5190
97.6%
친환경(인증) 무농약 63
 
1.2%
GAP(인증) 35
 
0.7%
친환경(인증) 유기 29
 
0.5%
지리적표시 1
 
< 0.1%

Length

2024-03-23T07:38:27.004843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:27.431869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 5190
95.9%
친환경(인증 92
 
1.7%
무농약 63
 
1.2%
gap(인증 35
 
0.6%
유기 29
 
0.5%
지리적표시 1
 
< 0.1%

생산자
Text

Distinct1088
Distinct (%)20.5%
Missing2
Missing (%)< 0.1%
Memory size41.7 KiB
2024-03-23T07:38:27.925438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length4.5521068
Min length3

Characters and Unicode

Total characters24199
Distinct characters346
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique624 ?
Unique (%)11.7%

Sample

1st row김**
2nd row장**
3rd row채**
4th row김**
5th row김**
ValueCountFrequency (%)
김 518
 
9.7%
이 376
 
7.1%
박 182
 
3.4%
정 135
 
2.5%
미 132
 
2.5%
최 125
 
2.4%
강 82
 
1.5%
조 71
 
1.3%
유 64
 
1.2%
56
 
1.1%
Other values (1077) 3575
67.2%
2024-03-23T07:38:28.846021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 10789
44.6%
농 657
 
2.7%
협 590
 
2.4%
미 590
 
2.4%
김 526
 
2.2%
합 524
 
2.2%
이 498
 
2.1%
조 451
 
1.9%
산 439
 
1.8%
인 367
 
1.5%
Other values (336) 8768
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12966
53.6%
Other Punctuation 10790
44.6%
Uppercase Letter 264
 
1.1%
Open Punctuation 95
 
0.4%
Dash Punctuation 56
 
0.2%
Close Punctuation 11
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Decimal Number 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 657
 
5.1%
협 590
 
4.6%
미 590
 
4.6%
김 526
 
4.1%
합 524
 
4.0%
이 498
 
3.8%
조 451
 
3.5%
산 439
 
3.4%
인 367
 
2.8%
장 348
 
2.7%
Other values (316) 7976
61.5%
Uppercase Letter
ValueCountFrequency (%)
C 94
35.6%
P 90
34.1%
R 69
26.1%
S 5
 
1.9%
N 3
 
1.1%
F 1
 
0.4%
O 1
 
0.4%
D 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
r 3
33.3%
c 2
22.2%
p 2
22.2%
o 1
 
11.1%
g 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 10789
> 99.9%
. 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 7
87.5%
1 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12966
53.6%
Common 10960
45.3%
Latin 273
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 657
 
5.1%
협 590
 
4.6%
미 590
 
4.6%
김 526
 
4.1%
합 524
 
4.0%
이 498
 
3.8%
조 451
 
3.5%
산 439
 
3.4%
인 367
 
2.8%
장 348
 
2.7%
Other values (316) 7976
61.5%
Latin
ValueCountFrequency (%)
C 94
34.4%
P 90
33.0%
R 69
25.3%
S 5
 
1.8%
N 3
 
1.1%
r 3
 
1.1%
c 2
 
0.7%
p 2
 
0.7%
o 1
 
0.4%
F 1
 
0.4%
Other values (3) 3
 
1.1%
Common
ValueCountFrequency (%)
* 10789
98.4%
( 95
 
0.9%
- 56
 
0.5%
) 11
 
0.1%
0 7
 
0.1%
1 1
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12966
53.6%
ASCII 11233
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 10789
96.0%
( 95
 
0.8%
C 94
 
0.8%
P 90
 
0.8%
R 69
 
0.6%
- 56
 
0.5%
) 11
 
0.1%
0 7
 
0.1%
S 5
 
< 0.1%
N 3
 
< 0.1%
Other values (10) 14
 
0.1%
Hangul
ValueCountFrequency (%)
농 657
 
5.1%
협 590
 
4.6%
미 590
 
4.6%
김 526
 
4.1%
합 524
 
4.0%
이 498
 
3.8%
조 451
 
3.5%
산 439
 
3.4%
인 367
 
2.8%
장 348
 
2.7%
Other values (316) 7976
61.5%

주소
Text

Distinct205
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
2024-03-23T07:38:29.403306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length11.008838
Min length10

Characters and Unicode

Total characters58545
Distinct characters127
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

Unique17 ?
Unique (%)0.3%

Sample

1st row제주특별자치도 서귀포시
2nd row제주특별자치도 서귀포시
3rd row제주특별자치도 서귀포시
4th row제주특별자치도 서귀포시
5th row제주특별자치도 서귀포시
ValueCountFrequency (%)
전라남도 840
 
7.9%
경상북도 804
 
7.6%
경상남도 645
 
6.1%
경기도 626
 
5.9%
충청북도 600
 
5.6%
전라북도 447
 
4.2%
강원도 437
 
4.1%
충청남도 374
 
3.5%
제주특별자치도 195
 
1.8%
괴산군 154
 
1.4%
Other values (184) 5514
51.8%
2024-03-23T07:38:30.364081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21272
36.3%
도 5169
 
8.8%
군 2818
 
4.8%
시 2727
 
4.7%
경 2157
 
3.7%
남 2118
 
3.6%
북 1865
 
3.2%
상 1504
 
2.6%
전 1332
 
2.3%
라 1287
 
2.2%
Other values (117) 16296
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37273
63.7%
Space Separator 21272
36.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 5169
 
13.9%
군 2818
 
7.6%
시 2727
 
7.3%
경 2157
 
5.8%
남 2118
 
5.7%
북 1865
 
5.0%
상 1504
 
4.0%
전 1332
 
3.6%
라 1287
 
3.5%
청 1210
 
3.2%
Other values (116) 15086
40.5%
Space Separator
ValueCountFrequency (%)
21272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37273
63.7%
Common 21272
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 5169
 
13.9%
군 2818
 
7.6%
시 2727
 
7.3%
경 2157
 
5.8%
남 2118
 
5.7%
북 1865
 
5.0%
상 1504
 
4.0%
전 1332
 
3.6%
라 1287
 
3.5%
청 1210
 
3.2%
Other values (116) 15086
40.5%
Common
ValueCountFrequency (%)
21272
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37273
63.7%
ASCII 21272
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21272
100.0%
Hangul
ValueCountFrequency (%)
도 5169
 
13.9%
군 2818
 
7.6%
시 2727
 
7.3%
경 2157
 
5.8%
남 2118
 
5.7%
북 1865
 
5.0%
상 1504
 
4.0%
전 1332
 
3.6%
라 1287
 
3.5%
청 1210
 
3.2%
Other values (116) 15086
40.5%

재배면적
Real number (ℝ)

MISSING  SKEWED 

Distinct462
Distinct (%)32.0%
Missing3875
Missing (%)72.9%
Infinite0
Infinite (%)0.0%
Mean1576.0873
Minimum17
Maximum180000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.9 KiB
2024-03-23T07:38:30.714249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile150
Q1330
median700
Q31600
95-th percentile4000
Maximum180000
Range179983
Interquartile range (IQR)1270

Descriptive statistics

Standard deviation5856.1895
Coefficient of variation (CV)3.7156504
Kurtosis624.03573
Mean1576.0873
Median Absolute Deviation (MAD)370
Skewness22.332814
Sum2274294
Variance34294955
MonotonicityNot monotonic
2024-03-23T07:38:31.051384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330 298
 
5.6%
1000 112
 
2.1%
500 54
 
1.0%
300 42
 
0.8%
100 35
 
0.7%
660 35
 
0.7%
400 34
 
0.6%
600 33
 
0.6%
2000 22
 
0.4%
3000 21
 
0.4%
Other values (452) 757
 
14.2%
(Missing) 3875
72.9%
ValueCountFrequency (%)
17 1
 
< 0.1%
20 5
0.1%
26 1
 
< 0.1%
30 5
0.1%
33 6
0.1%
35 1
 
< 0.1%
50 6
0.1%
60 5
0.1%
66 1
 
< 0.1%
90 1
 
< 0.1%
ValueCountFrequency (%)
180000 1
< 0.1%
70000 1
< 0.1%
66000 1
< 0.1%
46157 1
< 0.1%
33000 1
< 0.1%
30000 1
< 0.1%
24000 1
< 0.1%
23256 1
< 0.1%
18195 1
< 0.1%
18000 1
< 0.1%

조사물량
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct193
Distinct (%)5.4%
Missing1744
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean1057.7195
Minimum0
Maximum1000000
Zeros80
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size46.9 KiB
2024-03-23T07:38:31.375286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median35
Q3280
95-th percentile2200
Maximum1000000
Range1000000
Interquartile range (IQR)275

Descriptive statistics

Standard deviation18325.547
Coefficient of variation (CV)17.325525
Kurtosis2535.5598
Mean1057.7195
Median Absolute Deviation (MAD)33
Skewness48.335544
Sum3780289.6
Variance3.3582566 × 108
MonotonicityNot monotonic
2024-03-23T07:38:31.921446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 387
 
7.3%
10.0 294
 
5.5%
100.0 271
 
5.1%
20.0 262
 
4.9%
1000.0 154
 
2.9%
1.0 151
 
2.8%
40.0 138
 
2.6%
50.0 138
 
2.6%
3.0 130
 
2.4%
500.0 103
 
1.9%
Other values (183) 1546
29.1%
(Missing) 1744
32.8%
ValueCountFrequency (%)
0.0 80
1.5%
0.45 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 151
2.8%
1.2 4
 
0.1%
1.4 3
 
0.1%
1.5 10
 
0.2%
1.58 1
 
< 0.1%
1.6 10
 
0.2%
1.8 1
 
< 0.1%
ValueCountFrequency (%)
1000000.0 1
 
< 0.1%
400000.0 1
 
< 0.1%
75000.0 1
 
< 0.1%
72000.0 1
 
< 0.1%
70000.0 1
 
< 0.1%
57000.0 1
 
< 0.1%
50000.0 3
0.1%
40000.0 2
< 0.1%
35000.0 1
 
< 0.1%
30000.0 2
< 0.1%

등록일자
Date

Distinct472
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
Minimum2017-05-08 00:00:00
Maximum2023-10-31 00:00:00
2024-03-23T07:38:32.333658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:32.801428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

분석결과
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.7 KiB
적합
5285 
부적합 (폐기)
 
27
부적합(회수폐기 및 생산 단계 재조사)
 
6

Length

Max length21
Median length2
Mean length2.0518992
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 5285
99.4%
부적합 (폐기) 27
 
0.5%
부적합(회수폐기 및 생산 단계 재조사) 6
 
0.1%

Length

2024-03-23T07:38:33.245380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:33.572666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 5285
98.4%
부적합 27
 
0.5%
폐기 27
 
0.5%
부적합(회수폐기 6
 
0.1%
및 6
 
0.1%
생산 6
 
0.1%
단계 6
 
0.1%
재조사 6
 
0.1%

Interactions

2024-03-23T07:38:22.837958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:22.011032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:23.134739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:22.528162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:38:33.791071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목명수거단계재배양식재배면적조사물량분석결과
품목명1.0000.5380.2460.5010.0000.532
수거단계0.5381.0000.0690.0000.0000.071
재배양식0.2460.0691.0000.1610.1520.000
재배면적0.5010.0000.1611.000NaN0.000
조사물량0.0000.0000.152NaN1.0000.000
분석결과0.5320.0710.0000.0000.0001.000
2024-03-23T07:38:34.075815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석결과재배양식수거단계
분석결과1.0000.0000.117
재배양식0.0001.0000.084
수거단계0.1170.0841.000
2024-03-23T07:38:34.320959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배면적조사물량수거단계재배양식분석결과
재배면적1.0000.4070.0000.1320.000
조사물량0.4071.0000.0000.1440.000
수거단계0.0000.0001.0000.0840.117
재배양식0.1320.1440.0841.0000.000
분석결과0.0000.0000.1170.0001.000

Missing values

2024-03-23T07:38:23.566330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:38:24.231213image/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.
2024-03-23T07:38:24.720849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과
0콩(대두)생산일반김**제주특별자치도 서귀포시1000100.02023-07-25적합
1콩(대두)생산일반장**제주특별자치도 서귀포시100060.02023-07-20적합
2서리태생산일반채**제주특별자치도 서귀포시10004.02023-07-17적합
3서리태생산일반김**제주특별자치도 서귀포시100080.02023-07-17적합
4쌀보리쌀유통/판매일반김**제주특별자치도 서귀포시<NA><NA>2023-06-21적합
5쌀보리쌀유통/판매일반구**제주특별자치도 제주시<NA><NA>2023-06-21적합
6맥주보리쌀유통/판매일반김**제주특별자치도 서귀포시<NA><NA>2023-06-21적합
7옥수수생산일반유**제주특별자치도 서귀포시31643000.02023-06-16적합
8옥수수생산일반김**제주특별자치도 서귀포시22384000.02023-06-16적합
9옥수수생산일반고**제주특별자치도 서귀포시25913000.02023-06-16적합
품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과
5308옥수수유통/판매일반괴**협충청북도 괴산군<NA><NA>2017-07-18적합
5309쌀보리쌀유통/판매일반정**충청북도 증평군<NA><NA>2017-07-13적합
5310콩(대두)유통/판매일반심**경기도 여주시<NA><NA>2017-07-13적합
5311수수쌀유통/판매일반권**충청북도 음성군<NA><NA>2017-07-13적합
5312쌀보리쌀유통/판매일반유**경기도 평택시<NA><NA>2017-07-13적합
5313쌀보리쌀유통/판매일반용**협전라남도 장흥군<NA><NA>2017-07-12적합
5314멥쌀(일반)유통/판매일반롯**사안성공장경기도 안성시<NA><NA>2017-07-12적합
5315쌀보리쌀유통/판매일반서**농협쌀조합공동사업법인전라북도 김제시<NA><NA>2017-07-10적합
5316옥수수유통/판매일반순**협전라남도 순천시<NA><NA>2017-07-10적합
5317옥수수유통/판매일반여**협돌산갓유통센터전라남도 여수시<NA><NA>2017-07-10적합

Duplicate rows

Most frequently occurring

품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과# duplicates
27멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-15적합25
28멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-21적합13
29멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-22적합12
53밀생산일반이**충청북도 청주시3001000.02023-07-31부적합 (폐기)4
63쌀유통/판매일반생**미상충청북도 청주시<NA><NA>2023-07-10적합4
0건고추유통/판매일반생**불명경상남도 진주시<NA><NA>2017-07-04적합3
4기타(기장)생산일반김**제주특별자치도 제주시10001000.02017-08-18적합3
22기타(콩)유통/판매일반일**이스경기도 남양주시<NA><NA>2017-07-13적합3
35멥쌀(일반)유통/판매일반미**전라북도 전주시<NA>2.02021-06-22적합3
51밀생산일반생**혼합충청북도 청주시3001000.02023-07-31부적합 (폐기)3