Overview

Dataset statistics

Number of variables14
Number of observations2491
Missing cells3894
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory279.9 KiB
Average record size in memory115.1 B

Variable types

Categorical3
Text6
Numeric3
DateTime2

Dataset

Description품종보호권 국유 품종 도유 품종 실시권 처분현황에 대한 데이터로 품종보호권자,품종명,주소,출원번호,작물명,처분권리,처분연도,육성기관,실시만료일,실시계약일,계약기간,실시권자,실시수량,등록번호 등의 항목을 제공합니다.
Author농림축산식품부 국립종자원
URLhttps://www.data.go.kr/data/15065697/fileData.do

Alerts

육성기관 is highly overall correlated with 품종보호권자High correlation
품종보호권자 is highly overall correlated with 육성기관High correlation
처분연도 is highly overall correlated with 등록번호High correlation
등록번호 is highly overall correlated with 처분연도High correlation
품종보호권자 is highly imbalanced (87.2%)Imbalance
처분권리 is highly imbalanced (82.2%)Imbalance
육성기관 is highly imbalanced (70.9%)Imbalance
주소 has 1054 (42.3%) missing valuesMissing
출원번호 has 1944 (78.0%) missing valuesMissing
처분연도 has 29 (1.2%) missing valuesMissing
실시만료일 has 100 (4.0%) missing valuesMissing
실시계약일 has 93 (3.7%) missing valuesMissing
계약기간 has 31 (1.2%) missing valuesMissing
실시수량 has 73 (2.9%) missing valuesMissing
등록번호 has 547 (22.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:25:53.598232
Analysis finished2023-12-12 18:25:56.348451
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품종보호권자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
대한민국
2404 
충청북도
 
48
경상남도
 
38
경상북도
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
대한민국 2404
96.5%
충청북도 48
 
1.9%
경상남도 38
 
1.5%
경상북도 1
 
< 0.1%

Length

2023-12-13T03:25:56.433509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:25:56.542834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대한민국 2404
96.5%
충청북도 48
 
1.9%
경상남도 38
 
1.5%
경상북도 1
 
< 0.1%

품종명
Text

Distinct821
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
2023-12-13T03:25:56.897682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.4022481
Min length2

Characters and Unicode

Total characters8475
Distinct characters369
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)16.0%

Sample

1st row새나라
2nd row만풍
3rd row조생황금
4th row진미
5th row화산101호
ValueCountFrequency (%)
아리수 96
 
3.9%
루비에스 69
 
2.8%
썸머프린스 46
 
1.8%
선홍 36
 
1.4%
하모니 34
 
1.4%
샤이니 30
 
1.2%
원미 25
 
1.0%
옐로드림 24
 
1.0%
감풍 24
 
1.0%
조완 22
 
0.9%
Other values (811) 2085
83.7%
2023-12-13T03:25:57.445985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 410
 
4.8%
이 229
 
2.7%
리 218
 
2.6%
드 196
 
2.3%
홍 188
 
2.2%
니 182
 
2.1%
아 170
 
2.0%
린 162
 
1.9%
미 157
 
1.9%
원 156
 
1.8%
Other values (359) 6407
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7983
94.2%
Decimal Number 454
 
5.4%
Uppercase Letter 20
 
0.2%
Dash Punctuation 16
 
0.2%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 410
 
5.1%
이 229
 
2.9%
리 218
 
2.7%
드 196
 
2.5%
홍 188
 
2.4%
니 182
 
2.3%
아 170
 
2.1%
린 162
 
2.0%
미 157
 
2.0%
원 156
 
2.0%
Other values (344) 5915
74.1%
Decimal Number
ValueCountFrequency (%)
0 156
34.4%
1 101
22.2%
3 73
16.1%
2 50
 
11.0%
4 30
 
6.6%
7 15
 
3.3%
6 9
 
2.0%
9 8
 
1.8%
5 8
 
1.8%
8 4
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
R 10
50.0%
P 8
40.0%
A 2
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7983
94.2%
Common 472
 
5.6%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 410
 
5.1%
이 229
 
2.9%
리 218
 
2.7%
드 196
 
2.5%
홍 188
 
2.4%
니 182
 
2.3%
아 170
 
2.1%
린 162
 
2.0%
미 157
 
2.0%
원 156
 
2.0%
Other values (344) 5915
74.1%
Common
ValueCountFrequency (%)
0 156
33.1%
1 101
21.4%
3 73
15.5%
2 50
 
10.6%
4 30
 
6.4%
- 16
 
3.4%
7 15
 
3.2%
6 9
 
1.9%
9 8
 
1.7%
5 8
 
1.7%
Other values (2) 6
 
1.3%
Latin
ValueCountFrequency (%)
R 10
50.0%
P 8
40.0%
A 2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7983
94.2%
ASCII 492
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 410
 
5.1%
이 229
 
2.9%
리 218
 
2.7%
드 196
 
2.5%
홍 188
 
2.4%
니 182
 
2.3%
아 170
 
2.1%
린 162
 
2.0%
미 157
 
2.0%
원 156
 
2.0%
Other values (344) 5915
74.1%
ASCII
ValueCountFrequency (%)
0 156
31.7%
1 101
20.5%
3 73
14.8%
2 50
 
10.2%
4 30
 
6.1%
- 16
 
3.3%
7 15
 
3.0%
R 10
 
2.0%
6 9
 
1.8%
9 8
 
1.6%
Other values (5) 24
 
4.9%

주소
Text

MISSING 

Distinct267
Distinct (%)18.6%
Missing1054
Missing (%)42.3%
Memory size19.6 KiB
2023-12-13T03:25:57.780950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length10.686152
Min length5

Characters and Unicode

Total characters15356
Distinct characters191
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

Unique87 ?
Unique (%)6.1%

Sample

1st row충청북도 음성군 삼성면
2nd row충청북도 음성군 삼성면
3rd row충청북도 음성군 삼성면
4th row충청북도 음성군 삼성면
5th row충청북도 음성군 삼성면
ValueCountFrequency (%)
경북 372
 
8.5%
충북 235
 
5.4%
경기도 191
 
4.4%
전남 187
 
4.3%
옥천군 173
 
4.0%
경산시 162
 
3.7%
이원면 142
 
3.2%
하양읍 111
 
2.5%
수원시 87
 
2.0%
권선구 87
 
2.0%
Other values (336) 2629
60.1%
2023-12-13T03:25:58.237346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2941
19.2%
경 911
 
5.9%
시 904
 
5.9%
북 785
 
5.1%
면 747
 
4.9%
군 545
 
3.5%
천 430
 
2.8%
산 408
 
2.7%
남 400
 
2.6%
충 372
 
2.4%
Other values (181) 6913
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12408
80.8%
Space Separator 2941
 
19.2%
Decimal Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 911
 
7.3%
시 904
 
7.3%
북 785
 
6.3%
면 747
 
6.0%
군 545
 
4.4%
천 430
 
3.5%
산 408
 
3.3%
남 400
 
3.2%
충 372
 
3.0%
도 371
 
3.0%
Other values (178) 6535
52.7%
Decimal Number
ValueCountFrequency (%)
2 6
85.7%
1 1
 
14.3%
Space Separator
ValueCountFrequency (%)
2941
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12408
80.8%
Common 2948
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 911
 
7.3%
시 904
 
7.3%
북 785
 
6.3%
면 747
 
6.0%
군 545
 
4.4%
천 430
 
3.5%
산 408
 
3.3%
남 400
 
3.2%
충 372
 
3.0%
도 371
 
3.0%
Other values (178) 6535
52.7%
Common
ValueCountFrequency (%)
2941
99.8%
2 6
 
0.2%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12408
80.8%
ASCII 2948
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2941
99.8%
2 6
 
0.2%
1 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
경 911
 
7.3%
시 904
 
7.3%
북 785
 
6.3%
면 747
 
6.0%
군 545
 
4.4%
천 430
 
3.5%
산 408
 
3.3%
남 400
 
3.2%
충 372
 
3.0%
도 371
 
3.0%
Other values (178) 6535
52.7%

출원번호
Text

MISSING 

Distinct122
Distinct (%)22.3%
Missing1944
Missing (%)78.0%
Memory size19.6 KiB
2023-12-13T03:25:58.562276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9195612
Min length6

Characters and Unicode

Total characters4332
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)10.6%

Sample

1st row2012-352
2nd row2012-352
3rd row2012-352
4th row2013-203
5th row2013-203
ValueCountFrequency (%)
2015-294 61
 
11.2%
2015-293 45
 
8.2%
2015-225 30
 
5.5%
2015-406 25
 
4.6%
2017-226 24
 
4.4%
2013-291 22
 
4.0%
2014-188 20
 
3.7%
2014-327 20
 
3.7%
2016-310 17
 
3.1%
2012-276 16
 
2.9%
Other values (112) 267
48.8%
2023-12-13T03:25:59.074990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1003
23.2%
1 715
16.5%
0 652
15.1%
- 547
12.6%
5 312
 
7.2%
4 265
 
6.1%
3 229
 
5.3%
6 191
 
4.4%
9 162
 
3.7%
7 148
 
3.4%
Other values (7) 108
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3773
87.1%
Dash Punctuation 547
 
12.6%
Lowercase Letter 8
 
0.2%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1003
26.6%
1 715
19.0%
0 652
17.3%
5 312
 
8.3%
4 265
 
7.0%
3 229
 
6.1%
6 191
 
5.1%
9 162
 
4.3%
7 148
 
3.9%
8 96
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
o 3
37.5%
v 3
37.5%
e 1
 
12.5%
c 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
N 3
75.0%
D 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 547
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4320
99.7%
Latin 12
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1003
23.2%
1 715
16.6%
0 652
15.1%
- 547
12.7%
5 312
 
7.2%
4 265
 
6.1%
3 229
 
5.3%
6 191
 
4.4%
9 162
 
3.8%
7 148
 
3.4%
Latin
ValueCountFrequency (%)
N 3
25.0%
o 3
25.0%
v 3
25.0%
D 1
 
8.3%
e 1
 
8.3%
c 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1003
23.2%
1 715
16.5%
0 652
15.1%
- 547
12.6%
5 312
 
7.2%
4 265
 
6.1%
3 229
 
5.3%
6 191
 
4.4%
9 162
 
3.7%
7 148
 
3.4%
Other values (7) 108
 
2.5%

작물명
Text

Distinct82
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
2023-12-13T03:25:59.355552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.8382176
Min length1

Characters and Unicode

Total characters7070
Distinct characters132
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.3%

Sample

1st row사과
2nd row배
3rd row배
4th row복숭아
5th row이탈리안라이그라스
ValueCountFrequency (%)
사과 356
 
14.3%
국화 177
 
7.1%
장미 162
 
6.5%
복숭아 131
 
5.3%
배 130
 
5.2%
단감 109
 
4.4%
비모란선인장 101
 
4.1%
플럼코트 90
 
3.6%
프리지아 89
 
3.6%
포인세티아 83
 
3.3%
Other values (71) 1063
42.7%
2023-12-13T03:25:59.847064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 356
 
5.0%
과 356
 
5.0%
아 316
 
4.5%
장 270
 
3.8%
리 248
 
3.5%
라 220
 
3.1%
인 188
 
2.7%
화 187
 
2.6%
국 184
 
2.6%
감 171
 
2.4%
Other values (122) 4574
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7068
> 99.9%
Space Separator 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 356
 
5.0%
과 356
 
5.0%
아 316
 
4.5%
장 270
 
3.8%
리 248
 
3.5%
라 220
 
3.1%
인 188
 
2.7%
화 187
 
2.6%
국 184
 
2.6%
감 171
 
2.4%
Other values (120) 4572
64.7%
Space Separator
ValueCountFrequency (%)
1
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7068
> 99.9%
Common 1
 
< 0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 356
 
5.0%
과 356
 
5.0%
아 316
 
4.5%
장 270
 
3.8%
리 248
 
3.5%
라 220
 
3.1%
인 188
 
2.7%
화 187
 
2.6%
국 184
 
2.6%
감 171
 
2.4%
Other values (120) 4572
64.7%
Common
ValueCountFrequency (%)
1
100.0%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7068
> 99.9%
ASCII 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 356
 
5.0%
과 356
 
5.0%
아 316
 
4.5%
장 270
 
3.8%
리 248
 
3.5%
라 220
 
3.1%
인 188
 
2.7%
화 187
 
2.6%
국 184
 
2.6%
감 171
 
2.4%
Other values (120) 4572
64.7%
ASCII
ValueCountFrequency (%)
1
50.0%
X 1
50.0%

처분권리
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
통상실시
2391 
전용실시
 
61
<NA>
 
39

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전용실시
2nd row전용실시
3rd row전용실시
4th row전용실시
5th row통상실시

Common Values

ValueCountFrequency (%)
통상실시 2391
96.0%
전용실시 61
 
2.4%
<NA> 39
 
1.6%

Length

2023-12-13T03:26:00.031557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:26:00.150447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통상실시 2391
96.0%
전용실시 61
 
2.4%
na 39
 
1.6%

처분연도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)0.7%
Missing29
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean2013.1401
Minimum2001
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.0 KiB
2023-12-13T03:26:00.263596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2005
Q12011
median2014
Q32016
95-th percentile2017
Maximum2018
Range17
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.8324655
Coefficient of variation (CV)0.0019037251
Kurtosis-0.20332961
Mean2013.1401
Median Absolute Deviation (MAD)2
Skewness-0.91775068
Sum4956351
Variance14.687792
MonotonicityNot monotonic
2023-12-13T03:26:00.405818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2016 500
20.1%
2017 371
14.9%
2015 264
10.6%
2013 235
9.4%
2014 192
 
7.7%
2011 150
 
6.0%
2006 119
 
4.8%
2012 116
 
4.7%
2010 106
 
4.3%
2007 94
 
3.8%
Other values (7) 315
12.6%
ValueCountFrequency (%)
2001 3
 
0.1%
2002 2
 
0.1%
2004 75
3.0%
2005 46
 
1.8%
2006 119
4.8%
2007 94
3.8%
2008 28
 
1.1%
2009 88
3.5%
2010 106
4.3%
2011 150
6.0%
ValueCountFrequency (%)
2018 73
 
2.9%
2017 371
14.9%
2016 500
20.1%
2015 264
10.6%
2014 192
 
7.7%
2013 235
9.4%
2012 116
 
4.7%
2011 150
 
6.0%
2010 106
 
4.3%
2009 88
 
3.5%

육성기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
원예특작과학원
2033 
식량과학원
272 
축산과학원
 
67
충북농업기술원
 
48
경남농업기술원
 
38
Other values (7)
 
33

Length

Max length15
Median length7
Mean length6.7535126
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row원예특작과학원
2nd row원예특작과학원
3rd row원예특작과학원
4th row원예특작과학원
5th row축산과학원

Common Values

ValueCountFrequency (%)
원예특작과학원 2033
81.6%
식량과학원 272
 
10.9%
축산과학원 67
 
2.7%
충북농업기술원 48
 
1.9%
경남농업기술원 38
 
1.5%
농업과학원 10
 
0.4%
원예특작과학원 난지농업연구소 9
 
0.4%
작물과학원 7
 
0.3%
작물과학원 영남농업연구소 2
 
0.1%
고령지농업연구소 2
 
0.1%
Other values (2) 3
 
0.1%

Length

2023-12-13T03:26:00.570544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원예특작과학원 2042
81.5%
식량과학원 272
 
10.9%
축산과학원 67
 
2.7%
충북농업기술원 48
 
1.9%
경남농업기술원 38
 
1.5%
작물과학원 11
 
0.4%
농업과학원 10
 
0.4%
난지농업연구소 9
 
0.4%
영남농업연구소 2
 
0.1%
고령지농업연구소 2
 
0.1%
Other values (2) 3
 
0.1%

실시만료일
Date

MISSING 

Distinct515
Distinct (%)21.5%
Missing100
Missing (%)4.0%
Memory size19.6 KiB
Minimum2006-07-18 00:00:00
Maximum2027-01-26 00:00:00
2023-12-13T03:26:01.170602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:01.375092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실시계약일
Date

MISSING 

Distinct410
Distinct (%)17.1%
Missing93
Missing (%)3.7%
Memory size19.6 KiB
Minimum2001-10-29 00:00:00
Maximum2018-02-10 00:00:00
2023-12-13T03:26:01.597620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:01.784425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약기간
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)0.3%
Missing31
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean5.0666667
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.0 KiB
2023-12-13T03:26:01.936481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.8371109
Coefficient of variation (CV)0.36258767
Kurtosis-1.4894198
Mean5.0666667
Median Absolute Deviation (MAD)2
Skewness-0.19709597
Sum12464
Variance3.3749763
MonotonicityNot monotonic
2023-12-13T03:26:02.065113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
7 1042
41.8%
3 663
26.6%
5 390
 
15.7%
4 232
 
9.3%
2 90
 
3.6%
1 27
 
1.1%
6 16
 
0.6%
(Missing) 31
 
1.2%
ValueCountFrequency (%)
1 27
 
1.1%
2 90
 
3.6%
3 663
26.6%
4 232
 
9.3%
5 390
 
15.7%
6 16
 
0.6%
7 1042
41.8%
ValueCountFrequency (%)
7 1042
41.8%
6 16
 
0.6%
5 390
 
15.7%
4 232
 
9.3%
3 663
26.6%
2 90
 
3.6%
1 27
 
1.1%

실시권자
Text

Distinct440
Distinct (%)17.8%
Missing23
Missing (%)0.9%
Memory size19.6 KiB
2023-12-13T03:26:02.378578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.0012156
Min length2

Characters and Unicode

Total characters17279
Distinct characters299
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)5.3%

Sample

1st row삼협농원
2nd row삼협농원
3rd row삼협농원
4th row삼협농원
5th rowABS코리아
ValueCountFrequency (%)
농업기술실용화재단 111
 
4.0%
농업회사법인 109
 
3.9%
영농조합법인 93
 
3.4%
주식회사 58
 
2.1%
카이노스 49
 
1.8%
삼성농원 45
 
1.6%
하늘화훼종묘 40
 
1.4%
한국과수농업협동조합연합회 39
 
1.4%
베스트멈 37
 
1.3%
진흥종묘 37
 
1.3%
Other values (438) 2150
77.7%
2023-12-13T03:26:02.957325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 1869
 
10.8%
원 1090
 
6.3%
인 571
 
3.3%
법 549
 
3.2%
합 534
 
3.1%
업 510
 
3.0%
묘 501
 
2.9%
조 484
 
2.8%
영 456
 
2.6%
종 355
 
2.1%
Other values (289) 10360
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16521
95.6%
Space Separator 302
 
1.7%
Other Symbol 194
 
1.1%
Uppercase Letter 163
 
0.9%
Open Punctuation 44
 
0.3%
Close Punctuation 44
 
0.3%
Lowercase Letter 8
 
< 0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 1869
 
11.3%
원 1090
 
6.6%
인 571
 
3.5%
법 549
 
3.3%
합 534
 
3.2%
업 510
 
3.1%
묘 501
 
3.0%
조 484
 
2.9%
영 456
 
2.8%
종 355
 
2.1%
Other values (275) 9602
58.1%
Uppercase Letter
ValueCountFrequency (%)
S 50
30.7%
M 35
21.5%
F 26
16.0%
C 18
 
11.0%
A 15
 
9.2%
B 15
 
9.2%
H 2
 
1.2%
N 2
 
1.2%
Space Separator
ValueCountFrequency (%)
302
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 8
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16715
96.7%
Common 393
 
2.3%
Latin 171
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 1869
 
11.2%
원 1090
 
6.5%
인 571
 
3.4%
법 549
 
3.3%
합 534
 
3.2%
업 510
 
3.1%
묘 501
 
3.0%
조 484
 
2.9%
영 456
 
2.7%
종 355
 
2.1%
Other values (276) 9796
58.6%
Latin
ValueCountFrequency (%)
S 50
29.2%
M 35
20.5%
F 26
15.2%
C 18
 
10.5%
A 15
 
8.8%
B 15
 
8.8%
c 8
 
4.7%
H 2
 
1.2%
N 2
 
1.2%
Common
ValueCountFrequency (%)
302
76.8%
( 44
 
11.2%
) 44
 
11.2%
1 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16521
95.6%
ASCII 564
 
3.3%
None 194
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 1869
 
11.3%
원 1090
 
6.6%
인 571
 
3.5%
법 549
 
3.3%
합 534
 
3.2%
업 510
 
3.1%
묘 501
 
3.0%
조 484
 
2.9%
영 456
 
2.8%
종 355
 
2.1%
Other values (275) 9602
58.1%
ASCII
ValueCountFrequency (%)
302
53.5%
S 50
 
8.9%
( 44
 
7.8%
) 44
 
7.8%
M 35
 
6.2%
F 26
 
4.6%
C 18
 
3.2%
A 15
 
2.7%
B 15
 
2.7%
c 8
 
1.4%
Other values (3) 7
 
1.2%
None
ValueCountFrequency (%)
㈜ 194
100.0%

실시수량
Text

MISSING 

Distinct460
Distinct (%)19.0%
Missing73
Missing (%)2.9%
Memory size19.6 KiB
2023-12-13T03:26:03.339031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.7282878
Min length3

Characters and Unicode

Total characters13851
Distinct characters22
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

Unique237 ?
Unique (%)9.8%

Sample

1st row70000주
2nd row70000주
3rd row70000주
4th row70000주
5th row45000kg
ValueCountFrequency (%)
2000주 209
 
8.6%
1000주 196
 
8.1%
3000주 148
 
6.1%
5000주 105
 
4.3%
10000주 73
 
3.0%
30000주 66
 
2.7%
20000주 65
 
2.7%
500주 63
 
2.6%
50000주 47
 
1.9%
100000주 32
 
1.3%
Other values (423) 1414
58.5%
2023-12-13T03:26:03.885834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7192
51.9%
주 1727
 
12.5%
1 794
 
5.7%
5 661
 
4.8%
2 657
 
4.7%
3 500
 
3.6%
g 431
 
3.1%
k 415
 
3.0%
272
 
2.0%
4 271
 
2.0%
Other values (12) 931
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10735
77.5%
Other Letter 1855
 
13.4%
Lowercase Letter 846
 
6.1%
Space Separator 272
 
2.0%
Other Punctuation 131
 
0.9%
Uppercase Letter 12
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7192
67.0%
1 794
 
7.4%
5 661
 
6.2%
2 657
 
6.1%
3 500
 
4.7%
4 271
 
2.5%
6 243
 
2.3%
7 194
 
1.8%
8 146
 
1.4%
9 77
 
0.7%
Other Letter
ValueCountFrequency (%)
주 1727
93.1%
립 80
 
4.3%
구 33
 
1.8%
병 12
 
0.6%
본 3
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
g 431
50.9%
k 415
49.1%
Other Punctuation
ValueCountFrequency (%)
, 119
90.8%
. 12
 
9.2%
Uppercase Letter
ValueCountFrequency (%)
L 8
66.7%
G 4
33.3%
Space Separator
ValueCountFrequency (%)
272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11138
80.4%
Hangul 1855
 
13.4%
Latin 858
 
6.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7192
64.6%
1 794
 
7.1%
5 661
 
5.9%
2 657
 
5.9%
3 500
 
4.5%
272
 
2.4%
4 271
 
2.4%
6 243
 
2.2%
7 194
 
1.7%
8 146
 
1.3%
Other values (3) 208
 
1.9%
Hangul
ValueCountFrequency (%)
주 1727
93.1%
립 80
 
4.3%
구 33
 
1.8%
병 12
 
0.6%
본 3
 
0.2%
Latin
ValueCountFrequency (%)
g 431
50.2%
k 415
48.4%
L 8
 
0.9%
G 4
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11996
86.6%
Hangul 1855
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7192
60.0%
1 794
 
6.6%
5 661
 
5.5%
2 657
 
5.5%
3 500
 
4.2%
g 431
 
3.6%
k 415
 
3.5%
272
 
2.3%
4 271
 
2.3%
6 243
 
2.0%
Other values (7) 560
 
4.7%
Hangul
ValueCountFrequency (%)
주 1727
93.1%
립 80
 
4.3%
구 33
 
1.8%
병 12
 
0.6%
본 3
 
0.2%

등록번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct750
Distinct (%)38.6%
Missing547
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean3188.302
Minimum10
Maximum8723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.0 KiB
2023-12-13T03:26:04.044465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile489
Q11663
median3306
Q34561.25
95-th percentile5895
Maximum8723
Range8713
Interquartile range (IQR)2898.25

Descriptive statistics

Standard deviation1743.5228
Coefficient of variation (CV)0.54684996
Kurtosis-1.086509
Mean3188.302
Median Absolute Deviation (MAD)1501
Skewness0.020587868
Sum6198059
Variance3039871.7
MonotonicityNot monotonic
2023-12-13T03:26:04.243303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1152 54
 
2.2%
4386 42
 
1.7%
643 36
 
1.4%
4209 32
 
1.3%
4326 22
 
0.9%
2513 19
 
0.8%
3576 17
 
0.7%
5520 17
 
0.7%
5517 17
 
0.7%
1808 16
 
0.6%
Other values (740) 1672
67.1%
(Missing) 547
 
22.0%
ValueCountFrequency (%)
10 2
 
0.1%
24 3
 
0.1%
25 2
 
0.1%
26 10
0.4%
47 1
 
< 0.1%
49 2
 
0.1%
171 1
 
< 0.1%
211 2
 
0.1%
233 6
0.2%
256 1
 
< 0.1%
ValueCountFrequency (%)
8723 1
 
< 0.1%
6835 3
0.1%
6745 2
0.1%
6719 1
 
< 0.1%
6681 2
0.1%
6680 2
0.1%
6623 2
0.1%
6621 1
 
< 0.1%
6620 1
 
< 0.1%
6604 2
0.1%

Interactions

2023-12-13T03:25:55.404984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:54.730579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:55.073041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:55.528430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:54.853594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:55.186541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:55.655576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:54.971965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:25:55.292424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:26:04.358167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품종보호권자작물명처분권리처분연도육성기관계약기간등록번호
품종보호권자1.0000.8180.0000.2531.0000.2550.366
작물명0.8181.0000.4260.7480.9330.7920.847
처분권리0.0000.4261.0000.2150.1640.1470.129
처분연도0.2530.7480.2151.0000.3780.3410.707
육성기관1.0000.9330.1640.3781.0000.3380.414
계약기간0.2550.7920.1470.3410.3381.0000.295
등록번호0.3660.8470.1290.7070.4140.2951.000
2023-12-13T03:26:04.485773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
육성기관처분권리품종보호권자
육성기관1.0000.1250.998
처분권리0.1251.0000.000
품종보호권자0.9980.0001.000
2023-12-13T03:26:04.605680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분연도계약기간등록번호품종보호권자처분권리육성기관
처분연도1.0000.1630.7280.1540.2620.167
계약기간0.1631.0000.1100.1770.1570.172
등록번호0.7280.1101.0000.2420.0960.201
품종보호권자0.1540.1770.2421.0000.0000.998
처분권리0.2620.1570.0960.0001.0000.125
육성기관0.1670.1720.2010.9980.1251.000

Missing values

2023-12-13T03:25:55.796178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:25:55.988719image/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.
2023-12-13T03:25:56.213366image/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

품종보호권자품종명주소출원번호작물명처분권리처분연도육성기관실시만료일실시계약일계약기간실시권자실시수량등록번호
0대한민국새나라<NA><NA>사과전용실시2002원예특작과학원2008-10-262001-10-297삼협농원70000주10
1대한민국만풍<NA><NA>배전용실시2001원예특작과학원2008-10-262001-10-297삼협농원70000주24
2대한민국조생황금<NA><NA>배전용실시2001원예특작과학원2008-10-262001-10-297삼협농원70000주25
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