Overview

Dataset statistics

Number of variables9
Number of observations4570
Missing cells4947
Missing cells (%)12.0%
Duplicate rows80
Duplicate rows (%)1.8%
Total size in memory330.4 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 80 (1.8%) duplicate rowsDuplicates
재배양식 is highly imbalanced (89.7%)Imbalance
분석결과 is highly imbalanced (98.6%)Imbalance
재배면적 has 3395 (74.3%) missing valuesMissing
조사물량 has 1550 (33.9%) missing valuesMissing
재배면적 is highly skewed (γ1 = 22.65550635)Skewed
조사물량 is highly skewed (γ1 = 45.20079582)Skewed
조사물량 has 76 (1.7%) zerosZeros

Reproduction

Analysis started2024-03-23 07:38:05.330848
Analysis finished2024-03-23 07:38:08.749085
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목명
Text

Distinct54
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size35.8 KiB
2024-03-23T07:38:08.968779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length4.4002188
Min length1

Characters and Unicode

Total characters20109
Distinct characters78
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.2%

Sample

1st row기타(보리쌀)
2nd row기타(보리쌀)
3rd row기타(보리쌀)
4th row옥수수
5th row기장쌀
ValueCountFrequency (%)
멥쌀(일반 1128
24.7%
옥수수 864
18.9%
콩(대두 397
 
8.7%
쌀보리쌀 265
 
5.8%
기타(콩 229
 
5.0%
찹쌀(일반 191
 
4.2%
기타(보리쌀 170
 
3.7%
쌀 158
 
3.5%
기타(쌀 132
 
2.9%
건고추 117
 
2.6%
Other values (48) 923
20.2%
2024-03-23T07:38:09.782659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
쌀 2626
13.1%
( 2388
11.9%
) 2388
11.9%
수 1864
 
9.3%
일 1319
 
6.6%
반 1319
 
6.6%
멥 1128
 
5.6%
옥 864
 
4.3%
기 727
 
3.6%
콩 717
 
3.6%
Other values (68) 4769
23.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15320
76.2%
Open Punctuation 2388
 
11.9%
Close Punctuation 2388
 
11.9%
Other Punctuation 9
 
< 0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 2626
17.1%
수 1864
12.2%
일 1319
 
8.6%
반 1319
 
8.6%
멥 1128
 
7.4%
옥 864
 
5.6%
기 727
 
4.7%
콩 717
 
4.7%
타 641
 
4.2%
리 622
 
4.1%
Other values (64) 3493
22.8%
Open Punctuation
ValueCountFrequency (%)
( 2388
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2388
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15320
76.2%
Common 4789
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 2626
17.1%
수 1864
12.2%
일 1319
 
8.6%
반 1319
 
8.6%
멥 1128
 
7.4%
옥 864
 
5.6%
기 727
 
4.7%
콩 717
 
4.7%
타 641
 
4.2%
리 622
 
4.1%
Other values (64) 3493
22.8%
Common
ValueCountFrequency (%)
( 2388
49.9%
) 2388
49.9%
, 9
 
0.2%
4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15320
76.2%
ASCII 4789
 
23.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
쌀 2626
17.1%
수 1864
12.2%
일 1319
 
8.6%
반 1319
 
8.6%
멥 1128
 
7.4%
옥 864
 
5.6%
기 727
 
4.7%
콩 717
 
4.7%
타 641
 
4.2%
리 622
 
4.1%
Other values (64) 3493
22.8%
ASCII
ValueCountFrequency (%)
( 2388
49.9%
) 2388
49.9%
, 9
 
0.2%
4
 
0.1%

수거단계
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.8 KiB
유통/판매
3396 
생산
1174 

Length

Max length5
Median length5
Mean length4.2293217
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통/판매 3396
74.3%
생산 1174
 
25.7%

Length

2024-03-23T07:38:10.049389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:10.333731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통/판매 3396
74.3%
생산 1174
 
25.7%

재배양식
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.8 KiB
일반
4456 
친환경(인증) 무농약
 
59
친환경(인증) 유기
 
28
GAP(인증)
 
27

Length

Max length11
Median length3
Mean length3.1757112
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 4456
97.5%
친환경(인증) 무농약 59
 
1.3%
친환경(인증) 유기 28
 
0.6%
GAP(인증) 27
 
0.6%

Length

2024-03-23T07:38:10.634190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:10.958964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 4456
95.7%
친환경(인증 87
 
1.9%
무농약 59
 
1.3%
유기 28
 
0.6%
gap(인증 27
 
0.6%

생산자
Text

Distinct983
Distinct (%)21.5%
Missing2
Missing (%)< 0.1%
Memory size35.8 KiB
2024-03-23T07:38:11.401138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length4.5426883
Min length3

Characters and Unicode

Total characters20751
Distinct characters337
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

Unique561 ?
Unique (%)12.3%

Sample

1st row부**
2nd row윤**
3rd row김**
4th row강**
5th row문**
ValueCountFrequency (%)
김 435
 
9.5%
이 312
 
6.8%
박 144
 
3.2%
정 120
 
2.6%
미 109
 
2.4%
최 105
 
2.3%
강 74
 
1.6%
조 62
 
1.4%
유 54
 
1.2%
52
 
1.1%
Other values (972) 3101
67.9%
2024-03-23T07:38:12.395873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9277
44.7%
농 549
 
2.6%
협 519
 
2.5%
미 491
 
2.4%
김 439
 
2.1%
합 433
 
2.1%
이 418
 
2.0%
산 395
 
1.9%
조 375
 
1.8%
인 305
 
1.5%
Other values (327) 7550
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11084
53.4%
Other Punctuation 9280
44.7%
Uppercase Letter 224
 
1.1%
Open Punctuation 86
 
0.4%
Dash Punctuation 52
 
0.3%
Close Punctuation 11
 
0.1%
Decimal Number 8
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 549
 
5.0%
협 519
 
4.7%
미 491
 
4.4%
김 439
 
4.0%
합 433
 
3.9%
이 418
 
3.8%
산 395
 
3.6%
조 375
 
3.4%
인 305
 
2.8%
장 294
 
2.7%
Other values (307) 6866
61.9%
Uppercase Letter
ValueCountFrequency (%)
C 80
35.7%
P 77
34.4%
R 60
26.8%
S 4
 
1.8%
D 1
 
0.4%
F 1
 
0.4%
O 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
r 2
33.3%
g 1
16.7%
c 1
16.7%
p 1
16.7%
o 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 9277
> 99.9%
, 2
 
< 0.1%
. 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 7
87.5%
1 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11084
53.4%
Common 9437
45.5%
Latin 230
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 549
 
5.0%
협 519
 
4.7%
미 491
 
4.4%
김 439
 
4.0%
합 433
 
3.9%
이 418
 
3.8%
산 395
 
3.6%
조 375
 
3.4%
인 305
 
2.8%
장 294
 
2.7%
Other values (307) 6866
61.9%
Latin
ValueCountFrequency (%)
C 80
34.8%
P 77
33.5%
R 60
26.1%
S 4
 
1.7%
r 2
 
0.9%
D 1
 
0.4%
F 1
 
0.4%
g 1
 
0.4%
c 1
 
0.4%
p 1
 
0.4%
Other values (2) 2
 
0.9%
Common
ValueCountFrequency (%)
* 9277
98.3%
( 86
 
0.9%
- 52
 
0.6%
) 11
 
0.1%
0 7
 
0.1%
, 2
 
< 0.1%
. 1
 
< 0.1%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11084
53.4%
ASCII 9667
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9277
96.0%
( 86
 
0.9%
C 80
 
0.8%
P 77
 
0.8%
R 60
 
0.6%
- 52
 
0.5%
) 11
 
0.1%
0 7
 
0.1%
S 4
 
< 0.1%
r 2
 
< 0.1%
Other values (10) 11
 
0.1%
Hangul
ValueCountFrequency (%)
농 549
 
5.0%
협 519
 
4.7%
미 491
 
4.4%
김 439
 
4.0%
합 433
 
3.9%
이 418
 
3.8%
산 395
 
3.6%
조 375
 
3.4%
인 305
 
2.8%
장 294
 
2.7%
Other values (307) 6866
61.9%

주소
Text

Distinct187
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size35.8 KiB
2024-03-23T07:38:13.009609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length10.961488
Min length10

Characters and Unicode

Total characters50094
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

Unique13 ?
Unique (%)0.3%

Sample

1st row제주특별자치도 제주시
2nd row제주특별자치도 서귀포시
3rd row제주특별자치도 서귀포시
4th row제주특별자치도 서귀포시
5th row제주특별자치도 서귀포시
ValueCountFrequency (%)
전라남도 693
 
7.6%
경상북도 683
 
7.5%
경상남도 578
 
6.3%
경기도 548
 
6.0%
충청북도 512
 
5.6%
강원도 437
 
4.8%
전라북도 379
 
4.1%
충청남도 320
 
3.5%
제주특별자치도 164
 
1.8%
괴산군 129
 
1.4%
Other values (183) 4697
51.4%
2024-03-23T07:38:14.277540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18280
36.5%
도 4432
 
8.8%
군 2414
 
4.8%
시 2341
 
4.7%
경 1881
 
3.8%
남 1823
 
3.6%
북 1588
 
3.2%
상 1307
 
2.6%
전 1111
 
2.2%
라 1072
 
2.1%
Other values (117) 13845
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31814
63.5%
Space Separator 18280
36.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4432
 
13.9%
군 2414
 
7.6%
시 2341
 
7.4%
경 1881
 
5.9%
남 1823
 
5.7%
북 1588
 
5.0%
상 1307
 
4.1%
전 1111
 
3.5%
라 1072
 
3.4%
청 1015
 
3.2%
Other values (116) 12830
40.3%
Space Separator
ValueCountFrequency (%)
18280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31814
63.5%
Common 18280
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4432
 
13.9%
군 2414
 
7.6%
시 2341
 
7.4%
경 1881
 
5.9%
남 1823
 
5.7%
북 1588
 
5.0%
상 1307
 
4.1%
전 1111
 
3.5%
라 1072
 
3.4%
청 1015
 
3.2%
Other values (116) 12830
40.3%
Common
ValueCountFrequency (%)
18280
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31814
63.5%
ASCII 18280
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18280
100.0%
Hangul
ValueCountFrequency (%)
도 4432
 
13.9%
군 2414
 
7.6%
시 2341
 
7.4%
경 1881
 
5.9%
남 1823
 
5.7%
북 1588
 
5.0%
상 1307
 
4.1%
전 1111
 
3.5%
라 1072
 
3.4%
청 1015
 
3.2%
Other values (116) 12830
40.3%

재배면적
Real number (ℝ)

MISSING  SKEWED 

Distinct398
Distinct (%)33.9%
Missing3395
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean1589.24
Minimum17
Maximum180000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.3 KiB
2024-03-23T07:38:14.687775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile163.5
Q1330
median700
Q31565
95-th percentile4000
Maximum180000
Range179983
Interquartile range (IQR)1235

Descriptive statistics

Standard deviation6136.4239
Coefficient of variation (CV)3.8612317
Kurtosis623.00508
Mean1589.24
Median Absolute Deviation (MAD)370
Skewness22.655506
Sum1867357
Variance37655698
MonotonicityNot monotonic
2024-03-23T07:38:15.077965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330 246
 
5.4%
1000 88
 
1.9%
500 45
 
1.0%
660 34
 
0.7%
400 29
 
0.6%
600 29
 
0.6%
100 24
 
0.5%
300 22
 
0.5%
1200 16
 
0.4%
3000 15
 
0.3%
Other values (388) 627
 
13.7%
(Missing) 3395
74.3%
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 3
 
0.1%
60 1
 
< 0.1%
66 1
 
< 0.1%
100 24
0.5%
ValueCountFrequency (%)
180000 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%
16528 1
< 0.1%

조사물량
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct172
Distinct (%)5.7%
Missing1550
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean1023.9431
Minimum0
Maximum1000000
Zeros76
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size40.3 KiB
2024-03-23T07:38:15.433635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14.95
median30
Q3200
95-th percentile2000
Maximum1000000
Range1000000
Interquartile range (IQR)195.05

Descriptive statistics

Standard deviation19819.81
Coefficient of variation (CV)19.356359
Kurtosis2193.679
Mean1023.9431
Median Absolute Deviation (MAD)28
Skewness45.200796
Sum3092308.1
Variance3.9282486 × 108
MonotonicityNot monotonic
2024-03-23T07:38:15.913005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 340
 
7.4%
10.0 261
 
5.7%
100.0 224
 
4.9%
20.0 218
 
4.8%
1.0 123
 
2.7%
50.0 119
 
2.6%
3.0 118
 
2.6%
1000.0 118
 
2.6%
40.0 110
 
2.4%
30.0 94
 
2.1%
Other values (162) 1295
28.3%
(Missing) 1550
33.9%
ValueCountFrequency (%)
0.0 76
 
1.7%
0.45 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 123
 
2.7%
1.2 2
 
< 0.1%
1.4 2
 
< 0.1%
1.5 9
 
0.2%
1.6 6
 
0.1%
2.0 340
7.4%
2.5 1
 
< 0.1%
ValueCountFrequency (%)
1000000.0 1
 
< 0.1%
400000.0 1
 
< 0.1%
75000.0 1
 
< 0.1%
72000.0 1
 
< 0.1%
50000.0 3
0.1%
40000.0 2
 
< 0.1%
22000.0 1
 
< 0.1%
20000.0 5
0.1%
18000.0 1
 
< 0.1%
15000.0 1
 
< 0.1%

등록일자
Date

Distinct404
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size35.8 KiB
Minimum2017-05-08 00:00:00
Maximum2022-08-19 00:00:00
2024-03-23T07:38:16.320915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:16.684736image/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 size35.8 KiB
적합
4561 
부적합(회수폐기 및 생산 단계 재조사)
 
5
부적합 (폐기)
 
4

Length

Max length21
Median length2
Mean length2.0260394
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 4561
99.8%
부적합(회수폐기 및 생산 단계 재조사) 5
 
0.1%
부적합 (폐기) 4
 
0.1%

Length

2024-03-23T07:38:16.956910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:38:17.323888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 4561
99.3%
부적합(회수폐기 5
 
0.1%
및 5
 
0.1%
생산 5
 
0.1%
단계 5
 
0.1%
재조사 5
 
0.1%
부적합 4
 
0.1%
폐기 4
 
0.1%

Interactions

2024-03-23T07:38:07.115938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:06.410671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:07.463902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:38:06.695740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:38:17.522928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목명수거단계재배양식재배면적조사물량분석결과
품목명1.0000.4990.3090.5590.0000.085
수거단계0.4991.0000.1410.0000.0000.030
재배양식0.3090.1411.0000.1660.1720.000
재배면적0.5590.0000.1661.000NaN0.000
조사물량0.0000.0000.172NaN1.0000.000
분석결과0.0850.0300.0000.0000.0001.000
2024-03-23T07:38:17.805212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석결과재배양식수거단계
분석결과1.0000.0000.050
재배양식0.0001.0000.093
수거단계0.0500.0931.000
2024-03-23T07:38:17.974366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배면적조사물량수거단계재배양식분석결과
재배면적1.0000.4600.0000.1360.000
조사물량0.4601.0000.0000.1630.000
수거단계0.0000.0001.0000.0930.050
재배양식0.1360.1630.0931.0000.000
분석결과0.0000.0000.0500.0001.000

Missing values

2024-03-23T07:38:07.846284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:38:08.338251image/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.
2024-03-23T07:38:08.595858image/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
0기타(보리쌀)유통/판매일반부**제주특별자치도 제주시<NA>3.02022-07-05적합
1기타(보리쌀)유통/판매일반윤**제주특별자치도 서귀포시<NA>5.02022-07-05적합
2기타(보리쌀)유통/판매일반김**제주특별자치도 서귀포시<NA>5.02022-07-05적합
3옥수수생산일반강**제주특별자치도 서귀포시17001000.02022-07-05적합
4기장쌀생산일반문**제주특별자치도 서귀포시1451800.02022-07-05적합
5옥수수생산일반한**제주특별자치도 서귀포시29863000.02022-06-20적합
6기타(보리)생산일반박**제주특별자치도 서귀포시38152000.02022-06-20적합
7옥수수생산일반김**제주특별자치도 서귀포시43734000.02022-06-20적합
8기타(기장)생산일반윤**제주특별자치도 제주시1000200.02022-08-19적합
9기타(기장)생산일반김**제주특별자치도 제주시2000200.02022-08-19적합
품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과
4560옥수수유통/판매일반괴**협충청북도 괴산군<NA><NA>2017-07-18적합
4561쌀보리쌀유통/판매일반정**충청북도 증평군<NA><NA>2017-07-13적합
4562콩(대두)유통/판매일반심**경기도 여주시<NA><NA>2017-07-13적합
4563수수쌀유통/판매일반권**충청북도 음성군<NA><NA>2017-07-13적합
4564쌀보리쌀유통/판매일반유**경기도 평택시<NA><NA>2017-07-13적합
4565쌀보리쌀유통/판매일반용**협전라남도 장흥군<NA><NA>2017-07-12적합
4566멥쌀(일반)유통/판매일반롯**사안성공장경기도 안성시<NA><NA>2017-07-12적합
4567쌀보리쌀유통/판매일반서**농협쌀조합공동사업법인전라북도 김제시<NA><NA>2017-07-10적합
4568옥수수유통/판매일반순**협전라남도 순천시<NA><NA>2017-07-10적합
4569옥수수유통/판매일반여**협돌산갓유통센터전라남도 여수시<NA><NA>2017-07-10적합

Duplicate rows

Most frequently occurring

품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과# duplicates
25멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-15적합25
26멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-21적합13
27멥쌀(일반)유통/판매일반-***강원도 철원군<NA><NA>2017-11-22적합12
0건고추유통/판매일반생**불명경상남도 진주시<NA><NA>2017-07-04적합3
4기타(기장)생산일반김**제주특별자치도 제주시10001000.02017-08-18적합3
20기타(콩)유통/판매일반일**이스경기도 남양주시<NA><NA>2017-07-13적합3
31멥쌀(일반)유통/판매일반미**전라북도 전주시<NA>2.02021-06-22적합3
61옥수수유통/판매일반차**경상남도 의령군<NA><NA>2017-07-25적합3
68콩(대두)유통/판매일반군**협충청북도 괴산군<NA><NA>2018-07-24적합3
71콩(대두)유통/판매일반금**협경기도 파주시<NA><NA>2018-07-11적합3