Overview

Dataset statistics

Number of variables8
Number of observations152
Missing cells309
Missing cells (%)25.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory67.9 B

Variable types

Numeric1
Text4
Categorical1
Unsupported2

Dataset

Description우수품종상 수상업체 정보(년도, 작물, 품종, 출품기관, 육종가(부분공개), 수상명), 작물별 우수품종의 정보를 볼수 있고 활용을 통해 개인육종가의 수상률 또는 기관별(업체) 수상률을 알아볼수 있다.
URLhttps://www.data.go.kr/data/15055087/fileData.do

Alerts

Unnamed: 6 has 152 (100.0%) missing valuesMissing
Unnamed: 7 has 152 (100.0%) missing valuesMissing
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 22:31:51.341326
Analysis finished2023-12-12 22:31:52.521339
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct18
Distinct (%)11.9%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean2013.1788
Minimum2005
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T07:31:52.567358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2006
Q12008
median2013
Q32018
95-th percentile2021.5
Maximum2022
Range17
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.2890908
Coefficient of variation (CV)0.0026272335
Kurtosis-1.2646168
Mean2013.1788
Median Absolute Deviation (MAD)5
Skewness0.078959444
Sum303990
Variance27.974481
MonotonicityIncreasing
2023-12-13T07:31:52.664264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2006 13
 
8.6%
2007 11
 
7.2%
2014 8
 
5.3%
2020 8
 
5.3%
2019 8
 
5.3%
2018 8
 
5.3%
2017 8
 
5.3%
2016 8
 
5.3%
2015 8
 
5.3%
2013 8
 
5.3%
Other values (8) 63
41.4%
ValueCountFrequency (%)
2005 7
4.6%
2006 13
8.6%
2007 11
7.2%
2008 8
5.3%
2009 8
5.3%
2010 8
5.3%
2011 8
5.3%
2012 8
5.3%
2013 8
5.3%
2014 8
5.3%
ValueCountFrequency (%)
2022 8
5.3%
2021 8
5.3%
2020 8
5.3%
2019 8
5.3%
2018 8
5.3%
2017 8
5.3%
2016 8
5.3%
2015 8
5.3%
2014 8
5.3%
2013 8
5.3%

작물
Text

Distinct66
Distinct (%)43.7%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T07:31:52.873376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length2.3907285
Min length1

Characters and Unicode

Total characters361
Distinct characters107
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

Unique43 ?
Unique (%)28.5%

Sample

1st row사과
2nd row수박
3rd row벼
4th row벼
5th row무
ValueCountFrequency (%)
벼 14
 
9.3%
복숭아 13
 
8.6%
고추 10
 
6.6%
장미 7
 
4.6%
사과 6
 
4.0%
무 5
 
3.3%
국화 5
 
3.3%
배 4
 
2.6%
수박 4
 
2.6%
상추 4
 
2.6%
Other values (56) 79
52.3%
2023-12-13T07:31:53.197063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 19
 
5.3%
벼 14
 
3.9%
아 14
 
3.9%
복 14
 
3.9%
숭 13
 
3.6%
고 13
 
3.6%
리 11
 
3.0%
수 10
 
2.8%
배 9
 
2.5%
마 7
 
1.9%
Other values (97) 237
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 359
99.4%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 19
 
5.3%
벼 14
 
3.9%
아 14
 
3.9%
복 14
 
3.9%
숭 13
 
3.6%
고 13
 
3.6%
리 11
 
3.1%
수 10
 
2.8%
배 9
 
2.5%
마 7
 
1.9%
Other values (95) 235
65.5%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 359
99.4%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 19
 
5.3%
벼 14
 
3.9%
아 14
 
3.9%
복 14
 
3.9%
숭 13
 
3.6%
고 13
 
3.6%
리 11
 
3.1%
수 10
 
2.8%
배 9
 
2.5%
마 7
 
1.9%
Other values (95) 235
65.5%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 359
99.4%
ASCII 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 19
 
5.3%
벼 14
 
3.9%
아 14
 
3.9%
복 14
 
3.9%
숭 13
 
3.6%
고 13
 
3.6%
리 11
 
3.1%
수 10
 
2.8%
배 9
 
2.5%
마 7
 
1.9%
Other values (95) 235
65.5%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

품종
Text

Distinct150
Distinct (%)99.3%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T07:31:53.484364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.2384106
Min length2

Characters and Unicode

Total characters489
Distinct characters219
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

Unique149 ?
Unique (%)98.7%

Sample

1st row홍로
2nd row씨제로
3rd row일미
4th row남평
5th row태청
ValueCountFrequency (%)
자홍 2
 
1.3%
섬애 1
 
0.7%
스위트골드 1
 
0.7%
풍원미 1
 
0.7%
아라리 1
 
0.7%
핫립 1
 
0.7%
흑보석 1
 
0.7%
다유 1
 
0.7%
토스트 1
 
0.7%
청남 1
 
0.7%
Other values (141) 141
92.8%
2023-12-13T07:31:53.905543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 13
 
2.7%
이 10
 
2.0%
청 9
 
1.8%
호 9
 
1.8%
드 8
 
1.6%
리 8
 
1.6%
홍 7
 
1.4%
대 7
 
1.4%
백 7
 
1.4%
피 6
 
1.2%
Other values (209) 405
82.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
91.0%
Decimal Number 21
 
4.3%
Uppercase Letter 16
 
3.3%
Dash Punctuation 3
 
0.6%
Lowercase Letter 3
 
0.6%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 13
 
2.9%
이 10
 
2.2%
청 9
 
2.0%
호 9
 
2.0%
드 8
 
1.8%
리 8
 
1.8%
홍 7
 
1.6%
대 7
 
1.6%
백 7
 
1.6%
피 6
 
1.3%
Other values (186) 361
81.1%
Uppercase Letter
ValueCountFrequency (%)
R 4
25.0%
A 3
18.8%
B 2
12.5%
U 1
 
6.2%
T 1
 
6.2%
E 1
 
6.2%
H 1
 
6.2%
C 1
 
6.2%
L 1
 
6.2%
N 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 5
23.8%
2 4
19.0%
5 3
14.3%
8 2
 
9.5%
0 2
 
9.5%
4 2
 
9.5%
9 2
 
9.5%
3 1
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
n 1
33.3%
o 1
33.3%
a 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 445
91.0%
Common 25
 
5.1%
Latin 19
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 13
 
2.9%
이 10
 
2.2%
청 9
 
2.0%
호 9
 
2.0%
드 8
 
1.8%
리 8
 
1.8%
홍 7
 
1.6%
대 7
 
1.6%
백 7
 
1.6%
피 6
 
1.3%
Other values (186) 361
81.1%
Latin
ValueCountFrequency (%)
R 4
21.1%
A 3
15.8%
B 2
10.5%
U 1
 
5.3%
T 1
 
5.3%
E 1
 
5.3%
n 1
 
5.3%
o 1
 
5.3%
a 1
 
5.3%
H 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
1 5
20.0%
2 4
16.0%
5 3
12.0%
- 3
12.0%
8 2
 
8.0%
0 2
 
8.0%
4 2
 
8.0%
9 2
 
8.0%
1
 
4.0%
3 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
91.0%
ASCII 44
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 13
 
2.9%
이 10
 
2.2%
청 9
 
2.0%
호 9
 
2.0%
드 8
 
1.8%
리 8
 
1.8%
홍 7
 
1.6%
대 7
 
1.6%
백 7
 
1.6%
피 6
 
1.3%
Other values (186) 361
81.1%
ASCII
ValueCountFrequency (%)
1 5
 
11.4%
R 4
 
9.1%
2 4
 
9.1%
5 3
 
6.8%
- 3
 
6.8%
A 3
 
6.8%
8 2
 
4.5%
B 2
 
4.5%
0 2
 
4.5%
4 2
 
4.5%
Other values (13) 14
31.8%

출품기관
Text

Distinct76
Distinct (%)50.3%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T07:31:54.129427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.205298
Min length2

Characters and Unicode

Total characters1088
Distinct characters147
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)35.1%

Sample

1st row원예연구소
2nd row신젠타종묘(주)
3rd row영남농업연구소
4th row호남농업연구소
5th row신젠타종묘(주)
ValueCountFrequency (%)
국립식량과학원 20
 
12.5%
개인육종가 18
 
11.2%
국립원예특작과학원 11
 
6.9%
주)농우바이오 6
 
3.8%
신젠타종묘(주 6
 
3.8%
농우바이오(주 4
 
2.5%
경남농업기술원 4
 
2.5%
국립산림과학원 3
 
1.9%
충남농업기술원 3
 
1.9%
우리종묘 2
 
1.2%
Other values (69) 83
51.9%
2023-12-13T07:31:54.480695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 87
 
8.0%
농 53
 
4.9%
종 44
 
4.0%
과 41
 
3.8%
국 40
 
3.7%
립 38
 
3.5%
학 37
 
3.4%
기 27
 
2.5%
업 26
 
2.4%
주 25
 
2.3%
Other values (137) 670
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1024
94.1%
Open Punctuation 23
 
2.1%
Close Punctuation 23
 
2.1%
Space Separator 9
 
0.8%
Uppercase Letter 6
 
0.6%
Other Symbol 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 87
 
8.5%
농 53
 
5.2%
종 44
 
4.3%
과 41
 
4.0%
국 40
 
3.9%
립 38
 
3.7%
학 37
 
3.6%
기 27
 
2.6%
업 26
 
2.5%
주 25
 
2.4%
Other values (128) 606
59.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
K 1
16.7%
J 1
16.7%
N 1
16.7%
H 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1027
94.4%
Common 55
 
5.1%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 87
 
8.5%
농 53
 
5.2%
종 44
 
4.3%
과 41
 
4.0%
국 40
 
3.9%
립 38
 
3.7%
학 37
 
3.6%
기 27
 
2.6%
업 26
 
2.5%
주 25
 
2.4%
Other values (129) 609
59.3%
Latin
ValueCountFrequency (%)
S 2
33.3%
K 1
16.7%
J 1
16.7%
N 1
16.7%
H 1
16.7%
Common
ValueCountFrequency (%)
( 23
41.8%
) 23
41.8%
9
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1024
94.1%
ASCII 61
 
5.6%
None 3
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 87
 
8.5%
농 53
 
5.2%
종 44
 
4.3%
과 41
 
4.0%
국 40
 
3.9%
립 38
 
3.7%
학 37
 
3.6%
기 27
 
2.6%
업 26
 
2.5%
주 25
 
2.4%
Other values (128) 606
59.2%
ASCII
ValueCountFrequency (%)
( 23
37.7%
) 23
37.7%
9
 
14.8%
S 2
 
3.3%
K 1
 
1.6%
J 1
 
1.6%
N 1
 
1.6%
H 1
 
1.6%
None
ValueCountFrequency (%)
㈜ 3
100.0%

육종가
Text

Distinct123
Distinct (%)81.5%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T07:31:54.773354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters453
Distinct characters95
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

Unique101 ?
Unique (%)66.9%

Sample

1st row신.억
2nd row김.재
3rd row황.구
4th row신.식
5th row강.수
ValueCountFrequency (%)
권.하 4
 
2.6%
이.희 4
 
2.6%
김.규 3
 
2.0%
이.우 3
 
2.0%
김.현 2
 
1.3%
권.일 2
 
1.3%
이.순 2
 
1.3%
김.권 2
 
1.3%
임.철 2
 
1.3%
조.현 2
 
1.3%
Other values (113) 125
82.8%
2023-12-13T07:31:55.189696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 151
33.3%
김 30
 
6.6%
이 22
 
4.9%
권 11
 
2.4%
박 10
 
2.2%
강 9
 
2.0%
최 9
 
2.0%
조 8
 
1.8%
정 8
 
1.8%
현 8
 
1.8%
Other values (85) 187
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
66.7%
Other Punctuation 151
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 30
 
9.9%
이 22
 
7.3%
권 11
 
3.6%
박 10
 
3.3%
강 9
 
3.0%
최 9
 
3.0%
조 8
 
2.6%
정 8
 
2.6%
현 8
 
2.6%
임 7
 
2.3%
Other values (84) 180
59.6%
Other Punctuation
ValueCountFrequency (%)
. 151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
66.7%
Common 151
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 30
 
9.9%
이 22
 
7.3%
권 11
 
3.6%
박 10
 
3.3%
강 9
 
3.0%
최 9
 
3.0%
조 8
 
2.6%
정 8
 
2.6%
현 8
 
2.6%
임 7
 
2.3%
Other values (84) 180
59.6%
Common
ValueCountFrequency (%)
. 151
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
66.7%
ASCII 151
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 151
100.0%
Hangul
ValueCountFrequency (%)
김 30
 
9.9%
이 22
 
7.3%
권 11
 
3.6%
박 10
 
3.3%
강 9
 
3.0%
최 9
 
3.0%
조 8
 
2.6%
정 8
 
2.6%
현 8
 
2.6%
임 7
 
2.3%
Other values (84) 180
59.6%

수상명
Categorical

Distinct11
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
농림축산식품부 장관상
44 
국무총리상
32 
농림수산식품부 장관상
25 
대통령상
18 
농림부장관상
15 
Other values (6)
18 

Length

Max length18
Median length16
Mean length8.4144737
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row대통령상
2nd row국무총리상
3rd row농림부장관상
4th row농림부장관상
5th row농림부장관상

Common Values

ValueCountFrequency (%)
농림축산식품부 장관상 44
28.9%
국무총리상 32
21.1%
농림수산식품부 장관상 25
16.4%
대통령상 18
11.8%
농림부장관상 15
 
9.9%
종자관리소장상 5
 
3.3%
국립종자원장상 3
 
2.0%
농림축산식품부 장관상(수출품종상) 3
 
2.0%
국무총리상(수출품종상) 3
 
2.0%
농림축산식품부 장관상(혁신상) 3
 
2.0%

Length

2023-12-13T07:31:55.345129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장관상 69
30.4%
농림축산식품부 50
22.0%
국무총리상 32
14.1%
농림수산식품부 25
 
11.0%
대통령상 18
 
7.9%
농림부장관상 15
 
6.6%
종자관리소장상 5
 
2.2%
국립종자원장상 3
 
1.3%
장관상(수출품종상 3
 
1.3%
국무총리상(수출품종상 3
 
1.3%
Other values (2) 4
 
1.8%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

Interactions

2023-12-13T07:31:51.872380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:31:55.441297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도작물출품기관수상명
년도1.0000.0000.7250.773
작물0.0001.0000.8800.000
출품기관0.7250.8801.0000.000
수상명0.7730.0000.0001.000
2023-12-13T07:31:55.530011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도수상명
년도1.0000.336
수상명0.3361.000

Missing values

2023-12-13T07:31:51.978915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:31:52.077805image/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.
2023-12-13T07:31:52.459774image/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

년도작물품종출품기관육종가수상명Unnamed: 6Unnamed: 7
02005사과홍로원예연구소신.억대통령상<NA><NA>
12005수박씨제로신젠타종묘(주)김.재국무총리상<NA><NA>
22005벼일미영남농업연구소황.구농림부장관상<NA><NA>
32005벼남평호남농업연구소신.식농림부장관상<NA><NA>
42005무태청신젠타종묘(주)강.수농림부장관상<NA><NA>
52005고추독야청청신젠타종묘(주)이.직농림부장관상<NA><NA>
62005참외오복꿀(주)농우바이오이.익농림부장관상<NA><NA>
72006딸기매향논산딸기시험장김.일대통령상<NA><NA>
82006벼동진1호호남농업연구소김.경국무총리상<NA><NA>
92006복숭아정만조생개인육종가이.만국무총리상<NA><NA>
년도작물품종출품기관육종가수상명Unnamed: 6Unnamed: 7
1422021벼해들국립식량과학원현.조농림축산식품부 장관상(혁신상)<NA><NA>
1432022수박피엠알아이조은파트너종묘김.재대통령상<NA><NA>
1442022청경채알피-1아시아종묘류.오국무총리상<NA><NA>
1452022양파킹콩제농조.연국무총리상(수출품종상)<NA><NA>
1462022사과루비에스국립원예특작과학원권.순농림축산식품부 장관상<NA><NA>
1472022복숭아사비나요엘수목원김.종농림축산식품부 장관상<NA><NA>
1482022밀새금강국립식량과학원강.식농림축산식품부 장관상<NA><NA>
1492022팽이버섯여름향1호충청북도농업기술원이.우농림축산식품부 장관상<NA><NA>
1502022멜론제이씨씨엠-02장춘종묘(주)최.규농림축산식품부 장관상(혁신상)<NA><NA>
151<NA><NA><NA><NA><NA><NA><NA><NA>