Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells6
Missing cells (%)< 0.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory810.5 KiB
Average record size in memory83.0 B

Variable types

Numeric3
Categorical2
Text2
DateTime2

Dataset

Description인증번호에 대해 품목별 인증 현황(인증번호, 인증종류명, 인증농가, 인증품목명, 재배(작업장)면적(사육두수), 생산(수입)계획량, 인증기간(시작일), 인증기간(종료일), 원재료인증구분)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001679

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
인증종류명 is highly overall correlated with 원재료인증구분High correlation
원재료인증구분 is highly overall correlated with 재배(작업장)면적(사육두수) and 2 other fieldsHigh correlation
재배(작업장)면적(사육두수) is highly overall correlated with 생산(수입)계획량 and 1 other fieldsHigh correlation
생산(수입)계획량 is highly overall correlated with 재배(작업장)면적(사육두수) and 1 other fieldsHigh correlation
원재료인증구분 is highly imbalanced (79.8%)Imbalance
재배(작업장)면적(사육두수) is highly skewed (γ1 = 70.60950595)Skewed
생산(수입)계획량 is highly skewed (γ1 = 58.68134645)Skewed

Reproduction

Analysis started2024-01-05 22:18:01.168353
Analysis finished2024-01-05 22:18:07.334845
Duration6.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인증번호
Real number (ℝ)

Distinct5818
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14040343
Minimum1300013
Maximum99900026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T22:18:07.661145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1300013
5-th percentile10100792
Q111304049
median14600025
Q315307828
95-th percentile17303235
Maximum99900026
Range98600013
Interquartile range (IQR)4003779.2

Descriptive statistics

Standard deviation6940447.3
Coefficient of variation (CV)0.49432179
Kurtosis119.99817
Mean14040343
Median Absolute Deviation (MAD)1500691.5
Skewness9.8604545
Sum1.4040343 × 1011
Variance4.8169809 × 1013
MonotonicityNot monotonic
2024-01-05T22:18:08.395259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4100031 22
 
0.2%
13100641 22
 
0.2%
12303591 19
 
0.2%
13100609 19
 
0.2%
13100449 17
 
0.2%
17100822 15
 
0.1%
15100578 14
 
0.1%
15310600 14
 
0.1%
13100002 13
 
0.1%
10303737 12
 
0.1%
Other values (5808) 9833
98.3%
ValueCountFrequency (%)
1300013 1
 
< 0.1%
1300014 2
 
< 0.1%
1300018 3
< 0.1%
1300020 2
 
< 0.1%
1300021 2
 
< 0.1%
1300022 2
 
< 0.1%
1300024 3
< 0.1%
1301135 3
< 0.1%
1301136 5
0.1%
1301138 5
0.1%
ValueCountFrequency (%)
99900026 1
< 0.1%
99900022 1
< 0.1%
99800600 1
< 0.1%
99800582 1
< 0.1%
99800575 1
< 0.1%
99800529 1
< 0.1%
99800127 1
< 0.1%
99800119 1
< 0.1%
99800083 1
< 0.1%
99800042 1
< 0.1%

인증종류명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
무농약농산물
4851 
유기농산물
4162 
취급자
854 
유기가공식품
 
90
유기축산물
 
23
Other values (2)
 
20

Length

Max length9
Median length8
Mean length5.331
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유기농산물
2nd row유기농산물
3rd row유기농산물
4th row유기농산물
5th row무농약농산물

Common Values

ValueCountFrequency (%)
무농약농산물 4851
48.5%
유기농산물 4162
41.6%
취급자 854
 
8.5%
유기가공식품 90
 
0.9%
유기축산물 23
 
0.2%
무농약원료가공식품 17
 
0.2%
비식용유기가공품 3
 
< 0.1%

Length

2024-01-05T22:18:09.039079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-05T22:18:09.419106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무농약농산물 4851
48.5%
유기농산물 4162
41.6%
취급자 854
 
8.5%
유기가공식품 90
 
0.9%
유기축산물 23
 
0.2%
무농약원료가공식품 17
 
0.2%
비식용유기가공품 3
 
< 0.1%

인증농가
Text

Distinct6561
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-05T22:18:10.302758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length3
Mean length3.2873
Min length2

Characters and Unicode

Total characters32873
Distinct characters447
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

Unique4761 ?
Unique (%)47.6%

Sample

1st row주유원
2nd row오범용
3rd row민필기
4th row이병주
5th row이금신
ValueCountFrequency (%)
박홍진 21
 
0.2%
임성실 20
 
0.2%
김정희 16
 
0.2%
김호양 14
 
0.1%
양승호 14
 
0.1%
농업회사법인 13
 
0.1%
김봉수 12
 
0.1%
유성진 12
 
0.1%
김영신 12
 
0.1%
김승옥 11
 
0.1%
Other values (6691) 10100
98.6%
2024-01-05T22:18:11.815043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2010
 
6.1%
이 1493
 
4.5%
박 961
 
2.9%
정 955
 
2.9%
영 883
 
2.7%
성 547
 
1.7%
수 544
 
1.7%
순 543
 
1.7%
진 444
 
1.4%
현 439
 
1.3%
Other values (437) 24054
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31231
95.0%
Lowercase Letter 633
 
1.9%
Uppercase Letter 410
 
1.2%
Space Separator 246
 
0.7%
Open Punctuation 140
 
0.4%
Close Punctuation 140
 
0.4%
Other Punctuation 66
 
0.2%
Decimal Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2010
 
6.4%
이 1493
 
4.8%
박 961
 
3.1%
정 955
 
3.1%
영 883
 
2.8%
성 547
 
1.8%
수 544
 
1.7%
순 543
 
1.7%
진 444
 
1.4%
현 439
 
1.4%
Other values (374) 22412
71.8%
Lowercase Letter
ValueCountFrequency (%)
a 95
15.0%
n 77
12.2%
e 56
 
8.8%
r 46
 
7.3%
i 46
 
7.3%
t 42
 
6.6%
o 37
 
5.8%
h 33
 
5.2%
l 30
 
4.7%
d 29
 
4.6%
Other values (16) 142
22.4%
Uppercase Letter
ValueCountFrequency (%)
A 47
 
11.5%
S 37
 
9.0%
C 33
 
8.0%
I 31
 
7.6%
L 27
 
6.6%
N 22
 
5.4%
T 21
 
5.1%
E 21
 
5.1%
O 20
 
4.9%
R 16
 
3.9%
Other values (15) 135
32.9%
Other Punctuation
ValueCountFrequency (%)
. 43
65.2%
, 18
27.3%
& 3
 
4.5%
: 1
 
1.5%
/ 1
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 138
98.6%
[ 2
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 138
98.6%
] 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 5
71.4%
1 2
 
28.6%
Space Separator
ValueCountFrequency (%)
246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31231
95.0%
Latin 1043
 
3.2%
Common 599
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2010
 
6.4%
이 1493
 
4.8%
박 961
 
3.1%
정 955
 
3.1%
영 883
 
2.8%
성 547
 
1.8%
수 544
 
1.7%
순 543
 
1.7%
진 444
 
1.4%
현 439
 
1.4%
Other values (374) 22412
71.8%
Latin
ValueCountFrequency (%)
a 95
 
9.1%
n 77
 
7.4%
e 56
 
5.4%
A 47
 
4.5%
r 46
 
4.4%
i 46
 
4.4%
t 42
 
4.0%
o 37
 
3.5%
S 37
 
3.5%
h 33
 
3.2%
Other values (41) 527
50.5%
Common
ValueCountFrequency (%)
246
41.1%
( 138
23.0%
) 138
23.0%
. 43
 
7.2%
, 18
 
3.0%
2 5
 
0.8%
& 3
 
0.5%
1 2
 
0.3%
[ 2
 
0.3%
] 2
 
0.3%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31231
95.0%
ASCII 1642
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2010
 
6.4%
이 1493
 
4.8%
박 961
 
3.1%
정 955
 
3.1%
영 883
 
2.8%
성 547
 
1.8%
수 544
 
1.7%
순 543
 
1.7%
진 444
 
1.4%
현 439
 
1.4%
Other values (374) 22412
71.8%
ASCII
ValueCountFrequency (%)
246
 
15.0%
( 138
 
8.4%
) 138
 
8.4%
a 95
 
5.8%
n 77
 
4.7%
e 56
 
3.4%
A 47
 
2.9%
r 46
 
2.8%
i 46
 
2.8%
. 43
 
2.6%
Other values (53) 710
43.2%

인증품목명
Text

Distinct631
Distinct (%)6.3%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2024-01-05T22:18:12.434194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length2.4986992
Min length1

Characters and Unicode

Total characters24972
Distinct characters394
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

Unique198 ?
Unique (%)2.0%

Sample

1st row벼
2nd row홍고추
3rd row벼
4th row녹차잎
5th row밤
ValueCountFrequency (%)
벼 2165
 
21.6%
찰벼 304
 
3.0%
밤 259
 
2.6%
감자 163
 
1.6%
블루베리 158
 
1.6%
양파 147
 
1.5%
고사리 127
 
1.3%
무 117
 
1.2%
이탈리안라이그라스 107
 
1.1%
마늘 105
 
1.0%
Other values (633) 6369
63.6%
2024-01-05T22:18:13.679154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 2511
 
10.1%
류 926
 
3.7%
리 918
 
3.7%
추 818
 
3.3%
고 705
 
2.8%
채 531
 
2.1%
양 435
 
1.7%
이 425
 
1.7%
마 422
 
1.7%
찰 390
 
1.6%
Other values (384) 16891
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24477
98.0%
Close Punctuation 190
 
0.8%
Open Punctuation 190
 
0.8%
Lowercase Letter 78
 
0.3%
Space Separator 27
 
0.1%
Uppercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 2511
 
10.3%
류 926
 
3.8%
리 918
 
3.8%
추 818
 
3.3%
고 705
 
2.9%
채 531
 
2.2%
양 435
 
1.8%
이 425
 
1.7%
마 422
 
1.7%
찰 390
 
1.6%
Other values (361) 16396
67.0%
Lowercase Letter
ValueCountFrequency (%)
a 14
17.9%
e 14
17.9%
n 8
10.3%
o 6
7.7%
s 6
7.7%
h 6
7.7%
t 5
 
6.4%
r 4
 
5.1%
b 3
 
3.8%
y 3
 
3.8%
Other values (6) 9
11.5%
Uppercase Letter
ValueCountFrequency (%)
K 4
40.0%
S 3
30.0%
C 2
20.0%
B 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 190
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24477
98.0%
Common 407
 
1.6%
Latin 88
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 2511
 
10.3%
류 926
 
3.8%
리 918
 
3.8%
추 818
 
3.3%
고 705
 
2.9%
채 531
 
2.2%
양 435
 
1.8%
이 425
 
1.7%
마 422
 
1.7%
찰 390
 
1.6%
Other values (361) 16396
67.0%
Latin
ValueCountFrequency (%)
a 14
15.9%
e 14
15.9%
n 8
9.1%
o 6
 
6.8%
s 6
 
6.8%
h 6
 
6.8%
t 5
 
5.7%
r 4
 
4.5%
K 4
 
4.5%
S 3
 
3.4%
Other values (10) 18
20.5%
Common
ValueCountFrequency (%)
) 190
46.7%
( 190
46.7%
27
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24477
98.0%
ASCII 495
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 2511
 
10.3%
류 926
 
3.8%
리 918
 
3.8%
추 818
 
3.3%
고 705
 
2.9%
채 531
 
2.2%
양 435
 
1.8%
이 425
 
1.7%
마 422
 
1.7%
찰 390
 
1.6%
Other values (361) 16396
67.0%
ASCII
ValueCountFrequency (%)
) 190
38.4%
( 190
38.4%
27
 
5.5%
a 14
 
2.8%
e 14
 
2.8%
n 8
 
1.6%
o 6
 
1.2%
s 6
 
1.2%
h 6
 
1.2%
t 5
 
1.0%
Other values (13) 29
 
5.9%

재배(작업장)면적(사육두수)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5146
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17856.814
Minimum0.1
Maximum36582630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T22:18:14.067082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile50
Q1412.75
median1921
Q35913
95-th percentile25200.1
Maximum36582630
Range36582629
Interquartile range (IQR)5500.25

Descriptive statistics

Standard deviation418256.75
Coefficient of variation (CV)23.42281
Kurtosis5911.4227
Mean17856.814
Median Absolute Deviation (MAD)1730.45
Skewness70.609506
Sum1.7856814 × 108
Variance1.7493871 × 1011
MonotonicityNot monotonic
2024-01-05T22:18:14.609216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 248
 
2.5%
1000.0 154
 
1.5%
200.0 152
 
1.5%
300.0 144
 
1.4%
50.0 116
 
1.2%
330.0 104
 
1.0%
500.0 103
 
1.0%
150.0 93
 
0.9%
30.0 78
 
0.8%
400.0 76
 
0.8%
Other values (5136) 8732
87.3%
ValueCountFrequency (%)
0.1 1
 
< 0.1%
1.0 14
0.1%
2.0 6
 
0.1%
3.0 8
0.1%
4.0 4
 
< 0.1%
5.0 15
0.1%
5.4 3
 
< 0.1%
6.0 1
 
< 0.1%
7.0 4
 
< 0.1%
7.5 1
 
< 0.1%
ValueCountFrequency (%)
36582629.5 1
< 0.1%
9505000.0 1
< 0.1%
8999800.0 1
< 0.1%
7144905.0 1
< 0.1%
5694100.0 1
< 0.1%
5666600.0 1
< 0.1%
5357300.0 1
< 0.1%
5044700.0 1
< 0.1%
4061900.0 1
< 0.1%
2992000.0 1
< 0.1%

생산(수입)계획량
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2551
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46870.197
Minimum0
Maximum70000000
Zeros96
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T22:18:15.116300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.95
Q1451
median2000
Q36752.5
95-th percentile51000
Maximum70000000
Range70000000
Interquartile range (IQR)6301.5

Descriptive statistics

Standard deviation909997.65
Coefficient of variation (CV)19.415272
Kurtosis4052.5559
Mean46870.197
Median Absolute Deviation (MAD)1890
Skewness58.681346
Sum4.6870197 × 108
Variance8.2809572 × 1011
MonotonicityNot monotonic
2024-01-05T22:18:15.564810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000.0 380
 
3.8%
100.0 305
 
3.0%
500.0 272
 
2.7%
2000.0 258
 
2.6%
200.0 236
 
2.4%
50.0 217
 
2.2%
300.0 195
 
1.9%
3000.0 188
 
1.9%
5000.0 154
 
1.5%
1500.0 153
 
1.5%
Other values (2541) 7642
76.4%
ValueCountFrequency (%)
0.0 96
1.0%
0.1 1
 
< 0.1%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
1.0 41
0.4%
1.4 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 20
 
0.2%
3.0 11
 
0.1%
4.0 4
 
< 0.1%
ValueCountFrequency (%)
70000000.0 1
< 0.1%
43506620.0 1
< 0.1%
19459930.0 1
< 0.1%
17861617.0 1
< 0.1%
10000000.0 1
< 0.1%
9915000.0 1
< 0.1%
8000000.0 1
< 0.1%
7560960.0 1
< 0.1%
6850000.0 1
< 0.1%
6336000.0 1
< 0.1%

인증기간(시작일)
Date

Distinct363
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-22 00:00:00
Maximum2023-12-21 00:00:00
2024-01-05T22:18:16.013875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:16.329414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인증기간(종료일)
Date

Distinct363
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-21 00:00:00
Maximum2024-12-20 00:00:00
2024-01-05T22:18:16.627607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:17.085429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

원재료인증구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9146 
무농약농산물
 
460
유기농산물
 
370
유기가공식품
 
12
유기축산물
 
11

Length

Max length9
Median length4
Mean length4.133
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9146
91.5%
무농약농산물 460
 
4.6%
유기농산물 370
 
3.7%
유기가공식품 12
 
0.1%
유기축산물 11
 
0.1%
무농약원료가공식품 1
 
< 0.1%

Length

2024-01-05T22:18:17.488266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-05T22:18:17.781309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9146
91.5%
무농약농산물 460
 
4.6%
유기농산물 370
 
3.7%
유기가공식품 12
 
0.1%
유기축산물 11
 
0.1%
무농약원료가공식품 1
 
< 0.1%

Interactions

2024-01-05T22:18:05.153219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:03.405461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:04.262664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:05.604179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:03.620934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:04.535114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:06.022740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:03.895219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:18:04.824948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-05T22:18:18.233311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증번호인증종류명재배(작업장)면적(사육두수)생산(수입)계획량원재료인증구분
인증번호1.0000.3530.2990.2310.105
인증종류명0.3531.0000.0000.220NaN
재배(작업장)면적(사육두수)0.2990.0001.0000.735NaN
생산(수입)계획량0.2310.2200.7351.000NaN
원재료인증구분0.105NaNNaNNaN1.000
2024-01-05T22:18:18.519802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증종류명원재료인증구분
인증종류명1.0001.000
원재료인증구분1.0001.000
2024-01-05T22:18:18.763274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증번호재배(작업장)면적(사육두수)생산(수입)계획량인증종류명원재료인증구분
인증번호1.0000.2120.0640.2540.128
재배(작업장)면적(사육두수)0.2121.0000.5220.0001.000
생산(수입)계획량0.0640.5221.0000.1421.000
인증종류명0.2540.0000.1421.0001.000
원재료인증구분0.1281.0001.0001.0001.000

Missing values

2024-01-05T22:18:06.451581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-05T22:18:07.035013image/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

인증번호인증종류명인증농가인증품목명재배(작업장)면적(사육두수)생산(수입)계획량인증기간(시작일)인증기간(종료일)원재료인증구분
1152616100240유기농산물주유원벼2538.01760.02023-10-082024-10-07<NA>
1551311100101유기농산물오범용홍고추497.01200.02023-06-102024-06-09<NA>
4198015101493유기농산물민필기벼3028.02100.02023-10-262024-10-25<NA>
526615101345유기농산물이병주녹차잎1099.080.02023-09-182024-09-17<NA>
9913717303862무농약농산물이금신밤3300.02000.02023-04-212024-04-20<NA>
5592813100828유기농산물정상진호밀700.01000.02023-04-252024-04-24<NA>
4424410100839유기농산물유용상청상추1112.04000.02023-04-062024-04-05<NA>
1458410304617무농약농산물백성현양파762.02000.02023-02-262024-02-25<NA>
3353818100184유기농산물강영식기장11279.01650.02023-11-232024-11-22<NA>
4368213100740유기농산물정태희가지100.0300.02023-04-012024-03-31<NA>
인증번호인증종류명인증농가인증품목명재배(작업장)면적(사육두수)생산(수입)계획량인증기간(시작일)인증기간(종료일)원재료인증구분
2257417100150유기농산물곽미자벼2207.01540.02023-10-172024-10-16<NA>
6732517302703무농약농산물오낙근블루베리9493.04700.02023-03-062024-03-05<NA>
3394613303001무농약농산물이해동건표고버섯5020.01000.02023-01-062024-01-05<NA>
9335415104373유기농산물김효철벼1830.51300.02023-10-182024-10-17<NA>
7125116303306무농약농산물이술범땅콩2000.02000.02023-06-172024-06-16<NA>
7234910305652무농약농산물이두순마늘1800.02500.02023-06-182024-06-17<NA>
5325410304149무농약농산물김영섭로메인1200.05000.02023-10-252024-10-24<NA>
5564812100677유기농산물최달현표고버섯1320.06000.02023-03-262024-03-25<NA>
2868915308259무농약농산물전복수밤12095.02900.02023-07-222024-07-21<NA>
6679499200042유기축산물JW & HS Robinson젖소(시유)414.01148680.02023-04-042024-04-03<NA>

Duplicate rows

Most frequently occurring

인증번호인증종류명인증농가인증품목명재배(작업장)면적(사육두수)생산(수입)계획량인증기간(시작일)인증기간(종료일)원재료인증구분# duplicates
014302401무농약농산물박상준두릅200.0100.02023-11-212024-11-20<NA>2