Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells34498
Missing cells (%)19.2%
Duplicate rows401
Duplicate rows (%)4.0%
Total size in memory1.5 MiB
Average record size in memory154.0 B

Variable types

Text7
Categorical8
Unsupported3

Dataset

Description생산 또는 유통 중인 농산물에 대해 시군, 생산자(판매자), 작물별로 중금속 여부를 분석한 결과
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001677

Alerts

Dataset has 401 (4.0%) duplicate rowsDuplicates
재배양식 is highly overall correlated with 수거단계 and 5 other fieldsHigh correlation
수거단계 is highly overall correlated with 재배양식 and 5 other fieldsHigh correlation
Unnamed: 15 is highly overall correlated with 수거단계 and 6 other fieldsHigh correlation
Unnamed: 11 is highly overall correlated with 수거단계 and 6 other fieldsHigh correlation
Unnamed: 16 is highly overall correlated with 수거단계 and 6 other fieldsHigh correlation
Unnamed: 17 is highly overall correlated with 수거단계 and 6 other fieldsHigh correlation
Unnamed: 10 is highly overall correlated with Unnamed: 11 and 3 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with 수거단계 and 5 other fieldsHigh correlation
수거단계 is highly imbalanced (77.1%)Imbalance
재배양식 is highly imbalanced (86.1%)Imbalance
Unnamed: 9 is highly imbalanced (94.9%)Imbalance
Unnamed: 10 is highly imbalanced (98.7%)Imbalance
Unnamed: 11 is highly imbalanced (99.1%)Imbalance
Unnamed: 15 is highly imbalanced (99.8%)Imbalance
Unnamed: 16 is highly imbalanced (99.8%)Imbalance
Unnamed: 17 is highly imbalanced (99.6%)Imbalance
재배면적 has 2640 (26.4%) missing valuesMissing
조사물량 has 1791 (17.9%) missing valuesMissing
Unnamed: 12 has 9992 (99.9%) missing valuesMissing
Unnamed: 13 has 9995 (> 99.9%) missing valuesMissing
Unnamed: 14 has 9997 (> 99.9%) missing valuesMissing
조사물량 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등록일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-22 22:20:52.459509
Analysis finished2023-12-22 22:21:04.781574
Duration12.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목명
Text

Distinct343
Distinct (%)3.4%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-22T22:21:05.309186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length4.4628389
Min length1

Characters and Unicode

Total characters44615
Distinct characters299
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

Unique98 ?
Unique (%)1.0%

Sample

1st row무
2nd row수미(슈페리어)
3rd row현미
4th row멥쌀(일반)
5th row기타(쌀)
ValueCountFrequency (%)
멥쌀(일반 2499
24.9%
현미 1661
 
16.6%
홍고추(붉은고추 287
 
2.9%
풋고추 214
 
2.1%
수미(슈페리어 194
 
1.9%
밤고구마 168
 
1.7%
일반부추(조선부추 165
 
1.6%
대파 161
 
1.6%
시금치 153
 
1.5%
백태 149
 
1.5%
Other values (336) 4374
43.6%
2023-12-22T22:21:07.000031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4414
 
9.9%
) 4060
 
9.1%
반 2978
 
6.7%
일 2976
 
6.7%
쌀 2669
 
6.0%
멥 2499
 
5.6%
미 1972
 
4.4%
현 1693
 
3.8%
추 1688
 
3.8%
고 1254
 
2.8%
Other values (289) 18412
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36029
80.8%
Open Punctuation 4414
 
9.9%
Close Punctuation 4060
 
9.1%
Decimal Number 72
 
0.2%
Space Separator 28
 
0.1%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
반 2978
 
8.3%
일 2976
 
8.3%
쌀 2669
 
7.4%
멥 2499
 
6.9%
미 1972
 
5.5%
현 1693
 
4.7%
추 1688
 
4.7%
고 1254
 
3.5%
수 1002
 
2.8%
마 608
 
1.7%
Other values (275) 16690
46.3%
Decimal Number
ValueCountFrequency (%)
1 26
36.1%
5 14
19.4%
4 11
15.3%
0 9
 
12.5%
6 7
 
9.7%
7 3
 
4.2%
3 1
 
1.4%
2 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
A 4
33.3%
M 4
33.3%
Open Punctuation
ValueCountFrequency (%)
( 4414
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4060
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36029
80.8%
Common 8574
 
19.2%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
반 2978
 
8.3%
일 2976
 
8.3%
쌀 2669
 
7.4%
멥 2499
 
6.9%
미 1972
 
5.5%
현 1693
 
4.7%
추 1688
 
4.7%
고 1254
 
3.5%
수 1002
 
2.8%
마 608
 
1.7%
Other values (275) 16690
46.3%
Common
ValueCountFrequency (%)
( 4414
51.5%
) 4060
47.4%
28
 
0.3%
1 26
 
0.3%
5 14
 
0.2%
4 11
 
0.1%
0 9
 
0.1%
6 7
 
0.1%
7 3
 
< 0.1%
3 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 4
33.3%
A 4
33.3%
M 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36029
80.8%
ASCII 8586
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4414
51.4%
) 4060
47.3%
28
 
0.3%
1 26
 
0.3%
5 14
 
0.2%
4 11
 
0.1%
0 9
 
0.1%
6 7
 
0.1%
B 4
 
< 0.1%
A 4
 
< 0.1%
Other values (4) 9
 
0.1%
Hangul
ValueCountFrequency (%)
반 2978
 
8.3%
일 2976
 
8.3%
쌀 2669
 
7.4%
멥 2499
 
6.9%
미 1972
 
5.5%
현 1693
 
4.7%
추 1688
 
4.7%
고 1254
 
3.5%
수 1002
 
2.8%
마 608
 
1.7%
Other values (275) 16690
46.3%

수거단계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
생산
7006 
유통/판매
2615 
먹찰)
 
132
고을)
 
45
진주애호박)
 
28
Other values (31)
 
174

Length

Max length11
Median length2
Mean length2.8493
Min length2

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
생산 7006
70.1%
유통/판매 2615
 
26.2%
먹찰) 132
 
1.3%
고을) 45
 
0.4%
진주애호박) 28
 
0.3%
뫼옥수수) 27
 
0.3%
적엽상추) 22
 
0.2%
잎양파) 19
 
0.2%
출하 15
 
0.1%
원형수박 10
 
0.1%
Other values (26) 81
 
0.8%

Length

2023-12-22T22:21:07.822606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
생산 7006
70.0%
유통/판매 2615
 
26.1%
먹찰 132
 
1.3%
고을 45
 
0.4%
진주애호박 28
 
0.3%
뫼옥수수 27
 
0.3%
적엽상추 22
 
0.2%
잎양파 19
 
0.2%
출하 15
 
0.1%
서광 10
 
0.1%
Other values (27) 84
 
0.8%

재배양식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9171 
친환경(인증) 무농약
 
242
생산
 
218
GAP(인증)
 
103
유통/판매
 
91
Other values (20)
 
175

Length

Max length11
Median length3
Mean length3.3265
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반 9171
91.7%
친환경(인증) 무농약 242
 
2.4%
생산 218
 
2.2%
GAP(인증) 103
 
1.0%
유통/판매 91
 
0.9%
직불제(쌀소득) 71
 
0.7%
친환경(인증) 유기 44
 
0.4%
친환경(인증) 저농약 12
 
0.1%
단비 10
 
0.1%
봉옥) 8
 
0.1%
Other values (15) 30
 
0.3%

Length

2023-12-22T22:21:08.396485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반 9171
89.1%
친환경(인증 298
 
2.9%
무농약 242
 
2.3%
생산 218
 
2.1%
gap(인증 103
 
1.0%
유통/판매 91
 
0.9%
직불제(쌀소득 71
 
0.7%
유기 44
 
0.4%
저농약 12
 
0.1%
단비 10
 
0.1%
Other values (16) 38
 
0.4%

생산자
Text

Distinct741
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-22T22:21:09.118309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.3573
Min length2

Characters and Unicode

Total characters33573
Distinct characters329
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique490 ?
Unique (%)4.9%

Sample

1st row손**
2nd row손**
3rd row유**
4th row이**
5th row백**
ValueCountFrequency (%)
김 1745
17.4%
이 1241
 
12.4%
박 723
 
7.2%
정 435
 
4.3%
최 399
 
4.0%
일반 299
 
3.0%
조 248
 
2.5%
강 225
 
2.2%
장 172
 
1.7%
미 171
 
1.7%
Other values (725) 4352
43.5%
2023-12-22T22:21:10.741229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 19328
57.6%
김 1755
 
5.2%
이 1270
 
3.8%
박 734
 
2.2%
정 456
 
1.4%
조 418
 
1.2%
최 400
 
1.2%
협 379
 
1.1%
반 345
 
1.0%
일 323
 
1.0%
Other values (319) 8165
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 19334
57.6%
Other Letter 13741
40.9%
Space Separator 309
 
0.9%
Uppercase Letter 49
 
0.1%
Open Punctuation 45
 
0.1%
Decimal Number 40
 
0.1%
Close Punctuation 39
 
0.1%
Lowercase Letter 8
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 1755
 
12.8%
이 1270
 
9.2%
박 734
 
5.3%
정 456
 
3.3%
조 418
 
3.0%
최 400
 
2.9%
협 379
 
2.8%
반 345
 
2.5%
일 323
 
2.4%
농 319
 
2.3%
Other values (290) 7342
53.4%
Decimal Number
ValueCountFrequency (%)
2 8
20.0%
0 8
20.0%
1 5
12.5%
5 5
12.5%
4 4
10.0%
3 3
 
7.5%
6 3
 
7.5%
9 2
 
5.0%
7 1
 
2.5%
8 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
C 16
32.7%
P 14
28.6%
R 12
24.5%
A 5
 
10.2%
D 1
 
2.0%
O 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
p 2
25.0%
r 2
25.0%
c 2
25.0%
g 1
12.5%
o 1
12.5%
Other Punctuation
ValueCountFrequency (%)
* 19328
> 99.9%
/ 5
 
< 0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
309
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19774
58.9%
Hangul 13742
40.9%
Latin 57
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 1755
 
12.8%
이 1270
 
9.2%
박 734
 
5.3%
정 456
 
3.3%
조 418
 
3.0%
최 400
 
2.9%
협 379
 
2.8%
반 345
 
2.5%
일 323
 
2.4%
농 319
 
2.3%
Other values (291) 7343
53.4%
Common
ValueCountFrequency (%)
* 19328
97.7%
309
 
1.6%
( 45
 
0.2%
) 39
 
0.2%
2 8
 
< 0.1%
0 8
 
< 0.1%
- 7
 
< 0.1%
1 5
 
< 0.1%
5 5
 
< 0.1%
/ 5
 
< 0.1%
Other values (7) 15
 
0.1%
Latin
ValueCountFrequency (%)
C 16
28.1%
P 14
24.6%
R 12
21.1%
A 5
 
8.8%
p 2
 
3.5%
r 2
 
3.5%
c 2
 
3.5%
D 1
 
1.8%
g 1
 
1.8%
O 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19831
59.1%
Hangul 13741
40.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 19328
97.5%
309
 
1.6%
( 45
 
0.2%
) 39
 
0.2%
C 16
 
0.1%
P 14
 
0.1%
R 12
 
0.1%
2 8
 
< 0.1%
0 8
 
< 0.1%
- 7
 
< 0.1%
Other values (18) 45
 
0.2%
Hangul
ValueCountFrequency (%)
김 1755
 
12.8%
이 1270
 
9.2%
박 734
 
5.3%
정 456
 
3.3%
조 418
 
3.0%
최 400
 
2.9%
협 379
 
2.8%
반 345
 
2.5%
일 323
 
2.4%
농 319
 
2.3%
Other values (290) 7342
53.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주소
Text

Distinct470
Distinct (%)4.7%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-22T22:21:12.237172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.7539508
Min length1

Characters and Unicode

Total characters97520
Distinct characters191
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)0.7%

Sample

1st row전라남도 무안군
2nd row충청남도 당진시
3rd row충청남도 서천군
4th row충남 서산시
5th row경기도 파주시
ValueCountFrequency (%)
경상북도 889
 
4.5%
충청남도 862
 
4.4%
충남 804
 
4.1%
경북 756
 
3.8%
경상남도 613
 
3.1%
경남 590
 
3.0%
전남 578
 
2.9%
강원도 542
 
2.8%
경기도 538
 
2.7%
전라남도 516
 
2.6%
Other values (298) 12949
65.9%
2023-12-22T22:21:14.298487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38580
39.6%
군 5389
 
5.5%
도 5004
 
5.1%
시 4299
 
4.4%
남 4278
 
4.4%
경 4062
 
4.2%
북 3094
 
3.2%
충 2553
 
2.6%
청 1877
 
1.9%
전 1705
 
1.7%
Other values (181) 26679
27.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58289
59.8%
Space Separator 38580
39.6%
Other Punctuation 619
 
0.6%
Decimal Number 24
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 5389
 
9.2%
도 5004
 
8.6%
시 4299
 
7.4%
남 4278
 
7.3%
경 4062
 
7.0%
북 3094
 
5.3%
충 2553
 
4.4%
청 1877
 
3.2%
전 1705
 
2.9%
상 1614
 
2.8%
Other values (170) 24414
41.9%
Decimal Number
ValueCountFrequency (%)
0 9
37.5%
9 5
20.8%
1 5
20.8%
2 3
 
12.5%
3 2
 
8.3%
Other Punctuation
ValueCountFrequency (%)
* 618
99.8%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
38580
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
| 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58289
59.8%
Common 39231
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 5389
 
9.2%
도 5004
 
8.6%
시 4299
 
7.4%
남 4278
 
7.3%
경 4062
 
7.0%
북 3094
 
5.3%
충 2553
 
4.4%
청 1877
 
3.2%
전 1705
 
2.9%
상 1614
 
2.8%
Other values (170) 24414
41.9%
Common
ValueCountFrequency (%)
38580
98.3%
* 618
 
1.6%
0 9
 
< 0.1%
9 5
 
< 0.1%
1 5
 
< 0.1%
) 4
 
< 0.1%
2 3
 
< 0.1%
( 2
 
< 0.1%
| 2
 
< 0.1%
3 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58289
59.8%
ASCII 39231
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38580
98.3%
* 618
 
1.6%
0 9
 
< 0.1%
9 5
 
< 0.1%
1 5
 
< 0.1%
) 4
 
< 0.1%
2 3
 
< 0.1%
( 2
 
< 0.1%
| 2
 
< 0.1%
3 2
 
< 0.1%
Hangul
ValueCountFrequency (%)
군 5389
 
9.2%
도 5004
 
8.6%
시 4299
 
7.4%
남 4278
 
7.3%
경 4062
 
7.0%
북 3094
 
5.3%
충 2553
 
4.4%
청 1877
 
3.2%
전 1705
 
2.9%
상 1614
 
2.8%
Other values (170) 24414
41.9%

재배면적
Text

MISSING 

Distinct2980
Distinct (%)40.5%
Missing2640
Missing (%)26.4%
Memory size156.2 KiB
2023-12-22T22:21:15.904607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length4
Mean length3.9194293
Min length1

Characters and Unicode

Total characters28847
Distinct characters120
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

Unique1592 ?
Unique (%)21.6%

Sample

1st row1030
2nd row3749
3rd row5054
4th row1854
5th row1531
ValueCountFrequency (%)
330 273
 
3.6%
1000 131
 
1.7%
660 120
 
1.6%
500 89
 
1.2%
200 86
 
1.1%
100 80
 
1.0%
300 75
 
1.0%
600 71
 
0.9%
3000 62
 
0.8%
2000 57
 
0.7%
Other values (2963) 6626
86.4%
2023-12-22T22:21:18.269019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5146
17.8%
1 3771
13.1%
2 2951
10.2%
3 2891
10.0%
6 2027
 
7.0%
5 1970
 
6.8%
4 1896
 
6.6%
8 1716
 
5.9%
9 1688
 
5.9%
7 1637
 
5.7%
Other values (110) 3154
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25693
89.1%
Other Letter 1831
 
6.3%
Space Separator 1253
 
4.3%
Other Punctuation 68
 
0.2%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 198
 
10.8%
북 120
 
6.6%
시 116
 
6.3%
경 116
 
6.3%
도 97
 
5.3%
원 78
 
4.3%
남 75
 
4.1%
강 75
 
4.1%
천 61
 
3.3%
충 57
 
3.1%
Other values (96) 838
45.8%
Decimal Number
ValueCountFrequency (%)
0 5146
20.0%
1 3771
14.7%
2 2951
11.5%
3 2891
11.3%
6 2027
 
7.9%
5 1970
 
7.7%
4 1896
 
7.4%
8 1716
 
6.7%
9 1688
 
6.6%
7 1637
 
6.4%
Other Punctuation
ValueCountFrequency (%)
* 48
70.6%
. 20
29.4%
Space Separator
ValueCountFrequency (%)
1253
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27016
93.7%
Hangul 1831
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 198
 
10.8%
북 120
 
6.6%
시 116
 
6.3%
경 116
 
6.3%
도 97
 
5.3%
원 78
 
4.3%
남 75
 
4.1%
강 75
 
4.1%
천 61
 
3.3%
충 57
 
3.1%
Other values (96) 838
45.8%
Common
ValueCountFrequency (%)
0 5146
19.0%
1 3771
14.0%
2 2951
10.9%
3 2891
10.7%
6 2027
 
7.5%
5 1970
 
7.3%
4 1896
 
7.0%
8 1716
 
6.4%
9 1688
 
6.2%
7 1637
 
6.1%
Other values (4) 1323
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27016
93.7%
Hangul 1831
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5146
19.0%
1 3771
14.0%
2 2951
10.9%
3 2891
10.7%
6 2027
 
7.5%
5 1970
 
7.3%
4 1896
 
7.0%
8 1716
 
6.4%
9 1688
 
6.2%
7 1637
 
6.1%
Other values (4) 1323
 
4.9%
Hangul
ValueCountFrequency (%)
군 198
 
10.8%
북 120
 
6.6%
시 116
 
6.3%
경 116
 
6.3%
도 97
 
5.3%
원 78
 
4.3%
남 75
 
4.1%
강 75
 
4.1%
천 61
 
3.3%
충 57
 
3.1%
Other values (96) 838
45.8%

조사물량
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1791
Missing (%)17.9%
Memory size156.2 KiB

등록일자
Unsupported

REJECTED  UNSUPPORTED 

Missing72
Missing (%)0.7%
Memory size156.2 KiB

분석결과
Text

Distinct264
Distinct (%)2.6%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2023-12-22T22:21:19.380560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length2
Mean length2.265059
Min length1

Characters and Unicode

Total characters22637
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)2.0%

Sample

1st row적합
2nd row적합
3rd row적합
4th row적합
5th row적합
ValueCountFrequency (%)
적합 9528
94.2%
폐기 108
 
1.1%
부적합 108
 
1.1%
1000 8
 
0.1%
2000 7
 
0.1%
20150730 6
 
0.1%
20110728 4
 
< 0.1%
20130701 4
 
< 0.1%
20120726 4
 
< 0.1%
20161027 4
 
< 0.1%
Other values (261) 336
 
3.3%
2023-12-22T22:21:21.491751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
적 9639
42.6%
합 9639
42.6%
0 898
 
4.0%
1 508
 
2.2%
2 506
 
2.2%
7 155
 
0.7%
132
 
0.6%
8 122
 
0.5%
6 115
 
0.5%
부 111
 
0.5%
Other values (33) 812
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19665
86.9%
Decimal Number 2614
 
11.5%
Space Separator 132
 
0.6%
Close Punctuation 111
 
0.5%
Open Punctuation 111
 
0.5%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
적 9639
49.0%
합 9639
49.0%
부 111
 
0.6%
기 111
 
0.6%
폐 111
 
0.6%
조 3
 
< 0.1%
군 3
 
< 0.1%
북 3
 
< 0.1%
경 3
 
< 0.1%
진 3
 
< 0.1%
Other values (19) 39
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 898
34.4%
1 508
19.4%
2 506
19.4%
7 155
 
5.9%
8 122
 
4.7%
6 115
 
4.4%
3 104
 
4.0%
4 73
 
2.8%
5 68
 
2.6%
9 65
 
2.5%
Space Separator
ValueCountFrequency (%)
132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Other Punctuation
ValueCountFrequency (%)
* 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19665
86.9%
Common 2972
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
적 9639
49.0%
합 9639
49.0%
부 111
 
0.6%
기 111
 
0.6%
폐 111
 
0.6%
조 3
 
< 0.1%
군 3
 
< 0.1%
북 3
 
< 0.1%
경 3
 
< 0.1%
진 3
 
< 0.1%
Other values (19) 39
 
0.2%
Common
ValueCountFrequency (%)
0 898
30.2%
1 508
17.1%
2 506
17.0%
7 155
 
5.2%
132
 
4.4%
8 122
 
4.1%
6 115
 
3.9%
) 111
 
3.7%
( 111
 
3.7%
3 104
 
3.5%
Other values (4) 210
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19665
86.9%
ASCII 2972
 
13.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
적 9639
49.0%
합 9639
49.0%
부 111
 
0.6%
기 111
 
0.6%
폐 111
 
0.6%
조 3
 
< 0.1%
군 3
 
< 0.1%
북 3
 
< 0.1%
경 3
 
< 0.1%
진 3
 
< 0.1%
Other values (19) 39
 
0.2%
ASCII
ValueCountFrequency (%)
0 898
30.2%
1 508
17.1%
2 506
17.0%
7 155
 
5.2%
132
 
4.4%
8 122
 
4.1%
6 115
 
3.9%
) 111
 
3.7%
( 111
 
3.7%
3 104
 
3.5%
Other values (4) 210
 
7.1%

Unnamed: 9
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9644 
적합
 
310
40
 
5
구월)
 
3
100
 
3
Other values (31)
 
35

Length

Max length9
Median length4
Mean length3.9468
Min length2

Unique

Unique27 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9644
96.4%
적합 310
 
3.1%
40 5
 
0.1%
구월) 3
 
< 0.1%
100 3
 
< 0.1%
200 2
 
< 0.1%
20140923 2
 
< 0.1%
1000 2
 
< 0.1%
20141001 2
 
< 0.1%
20130823 1
 
< 0.1%
Other values (26) 26
 
0.3%

Length

2023-12-22T22:21:22.576715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9644
96.4%
적합 310
 
3.1%
40 5
 
< 0.1%
구월 3
 
< 0.1%
100 3
 
< 0.1%
200 2
 
< 0.1%
20140923 2
 
< 0.1%
1000 2
 
< 0.1%
20141001 2
 
< 0.1%
1640 1
 
< 0.1%
Other values (28) 28
 
0.3%

Unnamed: 10
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9954 
적합
 
25
생산
 
3
20120619
 
3
20130620
 
2
Other values (12)
 
13

Length

Max length8
Median length4
Mean length3.9995
Min length2

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9954
99.5%
적합 25
 
0.2%
생산 3
 
< 0.1%
20120619 3
 
< 0.1%
20130620 2
 
< 0.1%
20140529 2
 
< 0.1%
998 1
 
< 0.1%
1000 1
 
< 0.1%
1500 1
 
< 0.1%
20130801 1
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2023-12-22T22:21:23.343509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9954
99.5%
적합 25
 
0.2%
생산 3
 
< 0.1%
20120619 3
 
< 0.1%
20130620 2
 
< 0.1%
20140529 2
 
< 0.1%
7000 1
 
< 0.1%
20120329 1
 
< 0.1%
20130823 1
 
< 0.1%
1200 1
 
< 0.1%
Other values (7) 7
 
0.1%

Unnamed: 11
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9979 
적합
 
13
일반
 
3
20160802
 
1
20120817
 
1
Other values (3)
 
3

Length

Max length8
Median length4
Mean length3.9983
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9979
99.8%
적합 13
 
0.1%
일반 3
 
< 0.1%
20160802 1
 
< 0.1%
20120817 1
 
< 0.1%
1800 1
 
< 0.1%
1500 1
 
< 0.1%
20150803 1
 
< 0.1%

Length

2023-12-22T22:21:23.998841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T22:21:24.722718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9979
99.8%
적합 13
 
0.1%
일반 3
 
< 0.1%
20160802 1
 
< 0.1%
20120817 1
 
< 0.1%
1800 1
 
< 0.1%
1500 1
 
< 0.1%
20150803 1
 
< 0.1%

Unnamed: 12
Text

MISSING 

Distinct6
Distinct (%)75.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2023-12-22T22:21:25.158873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.875
Min length2

Characters and Unicode

Total characters31
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)62.5%

Sample

1st row적합
2nd row김**
3rd row적합
4th row이**
5th row20120724
ValueCountFrequency (%)
적합 3
37.5%
김 1
 
12.5%
이 1
 
12.5%
20120724 1
 
12.5%
20120731 1
 
12.5%
남 1
 
12.5%
2023-12-22T22:21:26.748803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 6
19.4%
2 5
16.1%
0 4
12.9%
적 3
9.7%
합 3
9.7%
1 3
9.7%
7 2
 
6.5%
김 1
 
3.2%
이 1
 
3.2%
4 1
 
3.2%
Other values (2) 2
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
51.6%
Other Letter 9
29.0%
Other Punctuation 6
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5
31.2%
0 4
25.0%
1 3
18.8%
7 2
 
12.5%
4 1
 
6.2%
3 1
 
6.2%
Other Letter
ValueCountFrequency (%)
적 3
33.3%
합 3
33.3%
김 1
 
11.1%
이 1
 
11.1%
남 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
71.0%
Hangul 9
29.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 6
27.3%
2 5
22.7%
0 4
18.2%
1 3
13.6%
7 2
 
9.1%
4 1
 
4.5%
3 1
 
4.5%
Hangul
ValueCountFrequency (%)
적 3
33.3%
합 3
33.3%
김 1
 
11.1%
이 1
 
11.1%
남 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
71.0%
Hangul 9
29.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 6
27.3%
2 5
22.7%
0 4
18.2%
1 3
13.6%
7 2
 
9.1%
4 1
 
4.5%
3 1
 
4.5%
Hangul
ValueCountFrequency (%)
적 3
33.3%
합 3
33.3%
김 1
 
11.1%
이 1
 
11.1%
남 1
 
11.1%

Unnamed: 13
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-22T22:21:27.408309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.8
Min length2

Characters and Unicode

Total characters34
Distinct characters17
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

Unique3 ?
Unique (%)60.0%

Sample

1st row경기도 용인시
2nd row충북 영동군
3rd row적합
4th row적합
5th row충청북도 음성군
ValueCountFrequency (%)
적합 2
25.0%
경기도 1
12.5%
용인시 1
12.5%
충북 1
12.5%
영동군 1
12.5%
충청북도 1
12.5%
음성군 1
12.5%
2023-12-22T22:21:28.849561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
35.3%
적 2
 
5.9%
도 2
 
5.9%
군 2
 
5.9%
합 2
 
5.9%
충 2
 
5.9%
북 2
 
5.9%
영 1
 
2.9%
음 1
 
2.9%
청 1
 
2.9%
Other values (7) 7
20.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
64.7%
Space Separator 12
35.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
적 2
 
9.1%
도 2
 
9.1%
군 2
 
9.1%
합 2
 
9.1%
충 2
 
9.1%
북 2
 
9.1%
영 1
 
4.5%
음 1
 
4.5%
청 1
 
4.5%
동 1
 
4.5%
Other values (6) 6
27.3%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
64.7%
Common 12
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
적 2
 
9.1%
도 2
 
9.1%
군 2
 
9.1%
합 2
 
9.1%
충 2
 
9.1%
북 2
 
9.1%
영 1
 
4.5%
음 1
 
4.5%
청 1
 
4.5%
동 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
64.7%
ASCII 12
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
100.0%
Hangul
ValueCountFrequency (%)
적 2
 
9.1%
도 2
 
9.1%
군 2
 
9.1%
합 2
 
9.1%
충 2
 
9.1%
북 2
 
9.1%
영 1
 
4.5%
음 1
 
4.5%
청 1
 
4.5%
동 1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB

Unnamed: 15
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
2000
 
1
2070
 
1
12000
 
1

Length

Max length5
Median length4
Mean length4.0001
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
2000 1
 
< 0.1%
2070 1
 
< 0.1%
12000 1
 
< 0.1%

Length

2023-12-22T22:21:29.673082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T22:21:30.543038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
2000 1
 
< 0.1%
2070 1
 
< 0.1%
12000 1
 
< 0.1%

Unnamed: 16
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
20140811
 
1
20110714
 
1
20160713
 
1

Length

Max length8
Median length4
Mean length4.0012
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
20140811 1
 
< 0.1%
20110714 1
 
< 0.1%
20160713 1
 
< 0.1%

Length

2023-12-22T22:21:31.522798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T22:21:32.867446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
20140811 1
 
< 0.1%
20110714 1
 
< 0.1%
20160713 1
 
< 0.1%

Unnamed: 17
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
적합
 
3

Length

Max length4
Median length4
Mean length3.9994
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
적합 3
 
< 0.1%

Length

2023-12-22T22:21:33.680411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T22:21:34.290501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
적합 3
 
< 0.1%

Correlations

2023-12-22T22:21:34.706827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수거단계재배양식Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 15Unnamed: 16
수거단계1.0000.9910.9670.7780.8201.0001.000NaNNaN
재배양식0.9911.0000.9920.7780.8201.0001.000NaNNaN
Unnamed: 90.9670.9921.0000.6470.9670.0000.000NaNNaN
Unnamed: 100.7780.7780.6471.0001.0000.0000.000NaNNaN
Unnamed: 110.8200.8200.9671.0001.0000.0000.000NaNNaN
Unnamed: 121.0001.0000.0000.0000.0001.0001.0001.0001.000
Unnamed: 131.0001.0000.0000.0000.0001.0001.0001.0001.000
Unnamed: 15NaNNaNNaNNaNNaN1.0001.0001.0001.000
Unnamed: 16NaNNaNNaNNaNNaN1.0001.0001.0001.000
2023-12-22T22:21:35.332215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배양식수거단계Unnamed: 15Unnamed: 11Unnamed: 16Unnamed: 17Unnamed: 10Unnamed: 9
재배양식1.0000.8451.0000.6321.0001.0000.3720.868
수거단계0.8451.0001.0000.6321.0001.0000.3720.609
Unnamed: 151.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 110.6320.6321.0001.0001.0001.0000.6550.766
Unnamed: 161.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 171.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 100.3720.3721.0000.6551.0001.0001.0000.000
Unnamed: 90.8680.6091.0000.7661.0001.0000.0001.000
2023-12-22T22:21:36.072358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수거단계재배양식Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 15Unnamed: 16Unnamed: 17
수거단계1.0000.8450.6090.3720.6321.0001.0001.000
재배양식0.8451.0000.8680.3720.6321.0001.0001.000
Unnamed: 90.6090.8681.0000.0000.7661.0001.0001.000
Unnamed: 100.3720.3720.0001.0000.6551.0001.0001.000
Unnamed: 110.6320.6320.7660.6551.0001.0001.0001.000
Unnamed: 151.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 161.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 171.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-22T22:21:00.852942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T22:21:02.449828image/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.
2023-12-22T22:21:03.896046image/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

품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
8032무유통/판매일반손**전라남도 무안군<NA>120190704적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
30169수미(슈페리어)생산일반손**충청남도 당진시1030110020150702적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
29345현미생산일반유**충청남도 서천군3749225020150930적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
71677멥쌀(일반)생산일반이**충남 서산시5054275620070928적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
9909기타(쌀)생산일반백**경기도 파주시185490020190924적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
32985멥쌀(일반)생산일반권**경상남도 산청군153130020141020적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
70577현미생산일반김**전남 광양시45222020070926적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
28277현미생산일반신**전라북도 익산시5393358020151013적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
33481녹광생산일반김**경상남도 창녕군75710020140917적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
45380밤고구마유통/판매일반여**산영농조합법인경기 여주군<NA>NaN20131118적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
품목명수거단계재배양식생산자주소재배면적조사물량등록일자분석결과Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
58983붉은팥(적두)유통/판매일반대**산대구 남구<NA>520100610적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
44533멥쌀(일반)유통/판매일반이**강원 홍천군<NA>NaN20130108적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
15032옥수수유통/판매일반강**경상북도 의성군<NA>2020180731적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
19674멥쌀(일반)유통/판매일반서**협강원도 횡성군<NA>NaN20170814적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
43138현미생산일반정**충남 서산시4984250020131007적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
59376현미생산일반송**전남 보성군2999130020101006적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
28487여름무유통/판매일반오**전라북도 고창군<NA>220150714적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
70118현미생산일반양**전남 보성군309493520071001적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
31167멥쌀(일반)생산일반이**강원도 정선군236790020151008적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>
50956멥쌀(일반)유통/판매일반진**래대전 대덕구<NA>NaN20120524적합<NA><NA><NA><NA><NA>NaN<NA><NA><NA>

Duplicate rows

Most frequently occurring

품목명수거단계재배양식생산자주소재배면적분석결과Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 15Unnamed: 16Unnamed: 17# duplicates
307팽이버섯생산친환경(인증) 무농약그**스경상북도 청도군10000적합<NA><NA><NA><NA><NA><NA><NA><NA>33
211새송이생산친환경(인증) 무농약황**경상북도 청도군890적합<NA><NA><NA><NA><NA><NA><NA><NA>19
207새송이생산친환경(인증) 무농약양**경상북도 청도군6454적합<NA><NA><NA><NA><NA><NA><NA><NA>8
52딸기생산GAP(인증)김**경상남도 진주시660적합<NA><NA><NA><NA><NA><NA><NA><NA>7
147멥쌀(일반)유통/판매일반-***강원도 철원군<NA>적합<NA><NA><NA><NA><NA><NA><NA><NA>7
225시금치유통/판매일반가**협경기 포천시<NA>적합<NA><NA><NA><NA><NA><NA><NA><NA>7
297침출차유통/판매일반소**원서울 강남구<NA>적합<NA><NA><NA><NA><NA><NA><NA><NA>7
313팽이버섯생산친환경(인증) 무농약성**경상북도 청도군10000적합<NA><NA><NA><NA><NA><NA><NA><NA>7
273일반부추(조선부추)유통/판매일반구**협경기 구리시<NA>적합<NA><NA><NA><NA><NA><NA><NA><NA>6
142멥쌀(일반)생산일반최**강원도 정선군300적합<NA><NA><NA><NA><NA><NA><NA><NA>5