Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells4762
Missing cells (%)3.4%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.2 MiB
Average record size in memory126.0 B

Variable types

Categorical6
Text3
Numeric3
DateTime2

Dataset

Description국립종자원 정부보급종 공급 계통출고 내역에 대한 데이터로 년산,작물명,품종명,지원명,출고번호,출고차수,시도,시군구,읍면동,단위,출고전체량,미소독물량,출고일자,확인일자 등의 항목을 제공합니다.
Author농림축산식품부 국립종자원
URLhttps://www.data.go.kr/data/15066228/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
단위 is highly overall correlated with 작물명High correlation
작물명 is highly overall correlated with 단위High correlation
출고전체량 is highly overall correlated with 미소독물량High correlation
미소독물량 is highly overall correlated with 출고전체량High correlation
지원명 is highly overall correlated with 시도High correlation
시도 is highly overall correlated with 지원명High correlation
읍면동 has 331 (3.3%) missing valuesMissing
확인일자 has 4431 (44.3%) missing valuesMissing
미소독물량 has 1476 (14.8%) zerosZeros

Reproduction

Analysis started2023-12-12 09:53:11.844266
Analysis finished2023-12-12 09:53:15.174436
Duration3.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
3425 
2020
3419 
2022
3156 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 3425
34.2%
2020 3419
34.2%
2022 3156
31.6%

Length

2023-12-12T18:53:15.253016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:53:15.368765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 3425
34.2%
2020 3419
34.2%
2022 3156
31.6%

작물명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
벼
4611 
봄감자
2243 
콩
1448 
보리
736 
팥
 
366
Other values (7)
596 

Length

Max length6
Median length1
Mean length1.6238
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row봄감자
2nd row벼
3rd row벼
4th row콩
5th row호밀

Common Values

ValueCountFrequency (%)
벼 4611
46.1%
봄감자 2243
22.4%
콩 1448
 
14.5%
보리 736
 
7.4%
팥 366
 
3.7%
호밀 306
 
3.1%
밀 144
 
1.4%
호밀(춘파) 58
 
0.6%
보리(춘파) 53
 
0.5%
벼(비축) 19
 
0.2%
Other values (2) 16
 
0.2%

Length

2023-12-12T18:53:15.477580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벼 4611
46.1%
봄감자 2243
22.4%
콩 1448
 
14.5%
보리 736
 
7.4%
팥 366
 
3.7%
호밀 306
 
3.1%
밀 144
 
1.4%
호밀(춘파 58
 
0.6%
보리(춘파 53
 
0.5%
벼(비축 19
 
0.2%
Other values (2) 16
 
0.2%

품종명
Text

Distinct69
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:53:15.719898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.1692
Min length2

Characters and Unicode

Total characters31692
Distinct characters83
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row수미
2nd row영호진미
3rd row일품벼
4th row대원콩
5th row곡우
ValueCountFrequency (%)
수미 1545
 
15.4%
대원콩 706
 
7.1%
동진찰벼 493
 
4.9%
삼광벼 460
 
4.6%
백옥찰벼 416
 
4.2%
두백 370
 
3.7%
아라리팥 366
 
3.7%
곡우 364
 
3.6%
선풍콩 315
 
3.1%
신동진벼 291
 
2.9%
Other values (59) 4674
46.7%
2023-12-12T18:53:16.097795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 3446
 
10.9%
미 2254
 
7.1%
수 1594
 
5.0%
콩 1448
 
4.6%
리 1408
 
4.4%
찰 1390
 
4.4%
진 1098
 
3.5%
대 1078
 
3.4%
보 847
 
2.7%
백 802
 
2.5%
Other values (73) 16327
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31369
99.0%
Decimal Number 217
 
0.7%
Open Punctuation 53
 
0.2%
Close Punctuation 53
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 3446
 
11.0%
미 2254
 
7.2%
수 1594
 
5.1%
콩 1448
 
4.6%
리 1408
 
4.5%
찰 1390
 
4.4%
진 1098
 
3.5%
대 1078
 
3.4%
보 847
 
2.7%
백 802
 
2.6%
Other values (70) 16004
51.0%
Decimal Number
ValueCountFrequency (%)
1 217
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31369
99.0%
Common 323
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 3446
 
11.0%
미 2254
 
7.2%
수 1594
 
5.1%
콩 1448
 
4.6%
리 1408
 
4.5%
찰 1390
 
4.4%
진 1098
 
3.5%
대 1078
 
3.4%
보 847
 
2.7%
백 802
 
2.6%
Other values (70) 16004
51.0%
Common
ValueCountFrequency (%)
1 217
67.2%
( 53
 
16.4%
) 53
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31369
99.0%
ASCII 323
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 3446
 
11.0%
미 2254
 
7.2%
수 1594
 
5.1%
콩 1448
 
4.6%
리 1408
 
4.5%
찰 1390
 
4.4%
진 1098
 
3.5%
대 1078
 
3.4%
보 847
 
2.7%
백 802
 
2.6%
Other values (70) 16004
51.0%
ASCII
ValueCountFrequency (%)
1 217
67.2%
( 53
 
16.4%
) 53
 
16.4%

지원명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강원진흥원
2243 
전북지원
1998 
충남지원
1123 
전남지원
990 
경북지원
970 
Other values (4)
2676 

Length

Max length7
Median length4
Mean length4.4055
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원진흥원
2nd row경남지원
3rd row경북지원
4th row경북지원
5th row전북지원

Common Values

ValueCountFrequency (%)
강원진흥원 2243
22.4%
전북지원 1998
20.0%
충남지원 1123
11.2%
전남지원 990
9.9%
경북지원 970
9.7%
경남지원 933
9.3%
강원지원 766
 
7.7%
경기종자관리소 604
 
6.0%
충북지원 373
 
3.7%

Length

2023-12-12T18:53:16.232619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:53:16.349693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원진흥원 2243
22.4%
전북지원 1998
20.0%
충남지원 1123
11.2%
전남지원 990
9.9%
경북지원 970
9.7%
경남지원 933
9.3%
강원지원 766
 
7.7%
경기종자관리소 604
 
6.0%
충북지원 373
 
3.7%

출고번호
Real number (ℝ)

Distinct486
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.7458
Minimum1
Maximum761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:53:16.499411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q117
median57.5
Q3132
95-th percentile265
Maximum761
Range760
Interquartile range (IQR)115

Descriptive statistics

Standard deviation104.39128
Coefficient of variation (CV)1.1503704
Kurtosis11.054964
Mean90.7458
Median Absolute Deviation (MAD)46.5
Skewness2.7097703
Sum907458
Variance10897.54
MonotonicityNot monotonic
2023-12-12T18:53:16.641004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 383
 
3.8%
2 268
 
2.7%
11 250
 
2.5%
13 217
 
2.2%
6 155
 
1.6%
12 138
 
1.4%
10 137
 
1.4%
3 133
 
1.3%
5 132
 
1.3%
7 119
 
1.2%
Other values (476) 8068
80.7%
ValueCountFrequency (%)
1 383
3.8%
2 268
2.7%
3 133
 
1.3%
4 93
 
0.9%
5 132
 
1.3%
6 155
1.6%
7 119
 
1.2%
8 85
 
0.9%
9 86
 
0.9%
10 137
 
1.4%
ValueCountFrequency (%)
761 3
< 0.1%
759 1
 
< 0.1%
758 1
 
< 0.1%
756 1
 
< 0.1%
754 1
 
< 0.1%
753 1
 
< 0.1%
752 2
< 0.1%
751 1
 
< 0.1%
749 3
< 0.1%
748 2
< 0.1%

출고차수
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
6127 
2
1797 
3
937 
4
924 
5
 
215

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row4
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 6127
61.3%
2 1797
 
18.0%
3 937
 
9.4%
4 924
 
9.2%
5 215
 
2.1%

Length

2023-12-12T18:53:16.767841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:53:16.862301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6127
61.3%
2 1797
 
18.0%
3 937
 
9.4%
4 924
 
9.2%
5 215
 
2.1%

시도
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전라남도
1569 
경상북도
1488 
경상남도
1376 
충청남도
1282 
전라북도
1136 
Other values (12)
3149 

Length

Max length7
Median length4
Mean length4.2084
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원특별자치도
2nd row경상남도
3rd row경상북도
4th row경상북도
5th row전라북도

Common Values

ValueCountFrequency (%)
전라남도 1569
15.7%
경상북도 1488
14.9%
경상남도 1376
13.8%
충청남도 1282
12.8%
전라북도 1136
11.4%
경기도 1038
10.4%
강원특별자치도 743
7.4%
충청북도 631
6.3%
인천광역시 169
 
1.7%
울산광역시 158
 
1.6%
Other values (7) 410
 
4.1%

Length

2023-12-12T18:53:16.985673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 1569
15.7%
경상북도 1488
14.9%
경상남도 1376
13.8%
충청남도 1282
12.8%
전라북도 1136
11.4%
경기도 1038
10.4%
강원특별자치도 743
7.4%
충청북도 631
6.3%
인천광역시 169
 
1.7%
울산광역시 158
 
1.6%
Other values (7) 410
 
4.1%

시군구
Text

Distinct179
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:53:17.357998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0312
Min length2

Characters and Unicode

Total characters30312
Distinct characters130
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

Unique5 ?
Unique (%)< 0.1%

Sample

1st row양양군
2nd row함안군
3rd row경산시
4th row봉화군
5th row정읍시
ValueCountFrequency (%)
해남군 162
 
1.6%
김제시 160
 
1.6%
정읍시 131
 
1.3%
강릉시 130
 
1.3%
합천군 130
 
1.3%
서산시 123
 
1.2%
부여군 116
 
1.2%
당진시 113
 
1.1%
경주시 113
 
1.1%
고성군 109
 
1.1%
Other values (169) 8738
87.2%
2023-12-12T18:53:17.920067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 5200
 
17.2%
시 4614
 
15.2%
주 1385
 
4.6%
천 1205
 
4.0%
산 999
 
3.3%
성 918
 
3.0%
안 792
 
2.6%
양 764
 
2.5%
영 539
 
1.8%
진 533
 
1.8%
Other values (120) 13363
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30287
99.9%
Space Separator 25
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 5200
 
17.2%
시 4614
 
15.2%
주 1385
 
4.6%
천 1205
 
4.0%
산 999
 
3.3%
성 918
 
3.0%
안 792
 
2.6%
양 764
 
2.5%
영 539
 
1.8%
진 533
 
1.8%
Other values (119) 13338
44.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30287
99.9%
Common 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 5200
 
17.2%
시 4614
 
15.2%
주 1385
 
4.6%
천 1205
 
4.0%
산 999
 
3.3%
성 918
 
3.0%
안 792
 
2.6%
양 764
 
2.5%
영 539
 
1.8%
진 533
 
1.8%
Other values (119) 13338
44.0%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30287
99.9%
ASCII 25
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 5200
 
17.2%
시 4614
 
15.2%
주 1385
 
4.6%
천 1205
 
4.0%
산 999
 
3.3%
성 918
 
3.0%
안 792
 
2.6%
양 764
 
2.5%
영 539
 
1.8%
진 533
 
1.8%
Other values (119) 13338
44.0%
ASCII
ValueCountFrequency (%)
25
100.0%

읍면동
Text

MISSING 

Distinct1669
Distinct (%)17.3%
Missing331
Missing (%)3.3%
Memory size156.2 KiB
2023-12-12T18:53:18.379429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.0826352
Min length2

Characters and Unicode

Total characters29806
Distinct characters306
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

Unique189 ?
Unique (%)2.0%

Sample

1st row손양면
2nd row법수면
3rd row와촌면
4th row명호면
5th row소성면
ValueCountFrequency (%)
남면 69
 
0.7%
서면 37
 
0.4%
북면 36
 
0.4%
군북면 32
 
0.3%
대산면 32
 
0.3%
마산합포구 30
 
0.3%
금성면 30
 
0.3%
동면 28
 
0.3%
산내면 26
 
0.3%
송정동 25
 
0.3%
Other values (1662) 9389
96.5%
2023-12-12T18:53:18.976390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 6780
22.7%
동 1984
 
6.7%
읍 1462
 
4.9%
산 1044
 
3.5%
성 528
 
1.8%
천 516
 
1.7%
남 509
 
1.7%
양 393
 
1.3%
서 374
 
1.3%
북 373
 
1.3%
Other values (296) 15843
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29384
98.6%
Decimal Number 324
 
1.1%
Space Separator 75
 
0.3%
Other Punctuation 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 6780
23.1%
동 1984
 
6.8%
읍 1462
 
5.0%
산 1044
 
3.6%
성 528
 
1.8%
천 516
 
1.8%
남 509
 
1.7%
양 393
 
1.3%
서 374
 
1.3%
북 373
 
1.3%
Other values (288) 15421
52.5%
Decimal Number
ValueCountFrequency (%)
1 131
40.4%
2 112
34.6%
3 52
 
16.0%
4 17
 
5.2%
5 8
 
2.5%
6 4
 
1.2%
Space Separator
ValueCountFrequency (%)
75
100.0%
Other Punctuation
ValueCountFrequency (%)
. 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29384
98.6%
Common 422
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 6780
23.1%
동 1984
 
6.8%
읍 1462
 
5.0%
산 1044
 
3.6%
성 528
 
1.8%
천 516
 
1.8%
남 509
 
1.7%
양 393
 
1.3%
서 374
 
1.3%
북 373
 
1.3%
Other values (288) 15421
52.5%
Common
ValueCountFrequency (%)
1 131
31.0%
2 112
26.5%
75
17.8%
3 52
 
12.3%
. 23
 
5.5%
4 17
 
4.0%
5 8
 
1.9%
6 4
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29384
98.6%
ASCII 422
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 6780
23.1%
동 1984
 
6.8%
읍 1462
 
5.0%
산 1044
 
3.6%
성 528
 
1.8%
천 516
 
1.8%
남 509
 
1.7%
양 393
 
1.3%
서 374
 
1.3%
북 373
 
1.3%
Other values (288) 15421
52.5%
ASCII
ValueCountFrequency (%)
1 131
31.0%
2 112
26.5%
75
17.8%
3 52
 
12.3%
. 23
 
5.5%
4 17
 
4.0%
5 8
 
1.9%
6 4
 
0.9%

단위
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20
8186 
5
1814 

Length

Max length2
Median length2
Mean length1.8186
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row20
4th row5
5th row20

Common Values

ValueCountFrequency (%)
20 8186
81.9%
5 1814
 
18.1%

Length

2023-12-12T18:53:19.162992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:53:19.279327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 8186
81.9%
5 1814
 
18.1%

출고전체량
Real number (ℝ)

HIGH CORRELATION 

Distinct823
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1389.671
Minimum0
Maximum28000
Zeros57
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:53:19.411326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q140
median180
Q3960
95-th percentile7140
Maximum28000
Range28000
Interquartile range (IQR)920

Descriptive statistics

Standard deviation3416.1477
Coefficient of variation (CV)2.4582421
Kurtosis21.341358
Mean1389.671
Median Absolute Deviation (MAD)160
Skewness4.3275531
Sum13896710
Variance11670065
MonotonicityNot monotonic
2023-12-12T18:53:19.591614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 1018
 
10.2%
40 738
 
7.4%
60 508
 
5.1%
5 391
 
3.9%
80 382
 
3.8%
100 372
 
3.7%
120 250
 
2.5%
200 231
 
2.3%
160 197
 
2.0%
140 190
 
1.9%
Other values (813) 5723
57.2%
ValueCountFrequency (%)
0 57
 
0.6%
5 391
 
3.9%
10 189
 
1.9%
15 120
 
1.2%
20 1018
10.2%
25 70
 
0.7%
30 75
 
0.8%
35 55
 
0.5%
40 738
7.4%
45 24
 
0.2%
ValueCountFrequency (%)
28000 1
 
< 0.1%
27020 1
 
< 0.1%
27000 4
 
< 0.1%
26500 2
 
< 0.1%
26120 1
 
< 0.1%
26100 1
 
< 0.1%
26000 8
0.1%
25600 2
 
< 0.1%
25480 1
 
< 0.1%
25000 10
0.1%

미소독물량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct686
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1229.6725
Minimum0
Maximum28000
Zeros1476
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:53:19.743941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median100
Q3720
95-th percentile6221
Maximum28000
Range28000
Interquartile range (IQR)700

Descriptive statistics

Standard deviation3285.184
Coefficient of variation (CV)2.6715926
Kurtosis24.225864
Mean1229.6725
Median Absolute Deviation (MAD)100
Skewness4.6127989
Sum12296725
Variance10792434
MonotonicityNot monotonic
2023-12-12T18:53:19.930149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1476
 
14.8%
20 929
 
9.3%
40 664
 
6.6%
60 464
 
4.6%
80 348
 
3.5%
100 326
 
3.3%
5 326
 
3.3%
120 220
 
2.2%
200 209
 
2.1%
160 172
 
1.7%
Other values (676) 4866
48.7%
ValueCountFrequency (%)
0 1476
14.8%
5 326
 
3.3%
10 149
 
1.5%
15 98
 
1.0%
20 929
9.3%
25 50
 
0.5%
30 43
 
0.4%
35 36
 
0.4%
40 664
6.6%
45 13
 
0.1%
ValueCountFrequency (%)
28000 1
 
< 0.1%
27000 4
 
< 0.1%
26500 2
 
< 0.1%
26120 1
 
< 0.1%
26100 1
 
< 0.1%
26000 7
0.1%
25600 2
 
< 0.1%
25480 1
 
< 0.1%
25000 10
0.1%
24580 1
 
< 0.1%

출고일자
Date

Distinct309
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-09-17 00:00:00
Maximum2023-05-10 00:00:00
2023-12-12T18:53:20.101796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:20.288397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

확인일자
Date

MISSING 

Distinct206
Distinct (%)3.7%
Missing4431
Missing (%)44.3%
Memory size156.2 KiB
Minimum2020-09-21 00:00:00
Maximum2023-05-10 00:00:00
2023-12-12T18:53:20.441226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:20.579475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T18:53:14.291081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:13.502877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:13.902376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:14.415466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:13.638986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:14.047318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:14.538534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:13.769593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:53:14.173490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:53:20.688544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산작물명품종명지원명출고번호출고차수시도단위출고전체량미소독물량
년산1.0000.1990.4360.1760.3070.1760.0680.0120.0060.038
작물명0.1991.0000.9780.7150.4650.6260.2041.0000.1900.195
품종명0.4360.9781.0000.9630.6970.8630.7941.0000.3940.395
지원명0.1760.7150.9631.0000.3860.5820.8180.3270.1160.117
출고번호0.3070.4650.6970.3861.0000.5720.2930.5370.1540.175
출고차수0.1760.6260.8630.5820.5721.0000.3670.2640.1160.114
시도0.0680.2040.7940.8180.2930.3671.0000.1010.1190.101
단위0.0121.0001.0000.3270.5370.2640.1011.0000.1950.207
출고전체량0.0060.1900.3940.1160.1540.1160.1190.1951.0000.999
미소독물량0.0380.1950.3950.1170.1750.1140.1010.2070.9991.000
2023-12-12T18:53:21.179781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원명년산시도단위출고차수작물명
지원명1.0000.0780.5030.3270.3850.403
년산0.0781.0000.0360.0210.1340.090
시도0.5030.0361.0000.0900.1980.075
단위0.3270.0210.0901.0000.3230.999
출고차수0.3850.1340.1980.3231.0000.409
작물명0.4030.0900.0750.9990.4091.000
2023-12-12T18:53:21.331010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출고번호출고전체량미소독물량년산작물명지원명출고차수시도단위
출고번호1.0000.2810.3930.1930.2140.1860.2720.1180.412
출고전체량0.2811.0000.8170.0040.0810.0520.0480.0460.149
미소독물량0.3930.8171.0000.0230.0830.0530.0470.0390.159
년산0.1930.0040.0231.0000.0900.0780.1340.0360.021
작물명0.2140.0810.0830.0901.0000.4030.4090.0750.999
지원명0.1860.0520.0530.0780.4031.0000.3850.5030.327
출고차수0.2720.0480.0470.1340.4090.3851.0000.1980.323
시도0.1180.0460.0390.0360.0750.5030.1981.0000.090
단위0.4120.1490.1590.0210.9990.3270.3230.0901.000

Missing values

2023-12-12T18:53:14.715248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:53:14.972732image/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.
2023-12-12T18:53:15.114578image/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

년산작물명품종명지원명출고번호출고차수시도시군구읍면동단위출고전체량미소독물량출고일자확인일자
169312020봄감자수미강원진흥원2101강원특별자치도양양군손양면20436043602021-02-08<NA>
407882022벼영호진미경남지원561경상남도함안군법수면20422042202023-02-032023-02-03
446282022벼일품벼경북지원1334경상북도경산시와촌면20158015802023-03-132023-03-15
316102021콩대원콩경북지원311경상북도봉화군명호면51535452022-05-022022-05-04
200322020호밀곡우전북지원211전라북도정읍시소성면201801802020-10-072020-10-07
153512020봄감자수미강원진흥원871대구광역시달성군가창면2040402020-11-21<NA>
412402022벼영호진미경남지원761경상북도구미시송정동20300030002023-02-082023-02-10
563442022봄감자수미강원진흥원1071인천광역시옹진군북도면20166016602023-02-20<NA>
573432022봄감자두백강원진흥원1801강원특별자치도춘천시강남동201801802023-03-09<NA>
245882021벼조명1호전남지원343전라남도해남군마산면208608602022-03-102022-03-14
년산작물명품종명지원명출고번호출고차수시도시군구읍면동단위출고전체량미소독물량출고일자확인일자
567702022봄감자두백강원진흥원1291경기도고양시화정1동2040402023-03-07<NA>
115412020콩대원콩강원지원91강원특별자치도홍천군남면540502021-04-232021-04-28
130082020콩선풍콩전북지원51전라남도무안군운남면54351802021-05-032021-05-03
280902021벼삼광벼충남지원1902경상북도영덕군강구면20344034402022-03-28<NA>
520722022콩대원콩강원지원41강원특별자치도삼척시남양동56002023-05-042023-05-10
530422022콩선풍콩전북지원301전라북도김제시공덕면531002023-05-10<NA>
521522022콩대원콩강원지원61강원특별자치도동해시북삼동53002023-05-042023-05-04
227372021벼추청벼경기종자관리소481경기도양평군옥천면204004002022-02-24<NA>
487082022벼안평충남지원2211전라북도김제시진봉면2080802023-03-30<NA>
255292021벼신동진벼전남지원494전라남도구례군구례읍207207202022-03-162022-03-17

Duplicate rows

Most frequently occurring

년산작물명품종명지원명출고번호출고차수시도시군구읍면동단위출고전체량미소독물량출고일자확인일자# duplicates
02020봄감자수미강원진흥원511경상남도사천시곤명면20002020-11-13<NA>2