Overview

Dataset statistics

Number of variables7
Number of observations1568
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory90.5 KiB
Average record size in memory59.1 B

Variable types

Categorical4
Text1
Numeric2

Dataset

Description국립종자원 정부보급종 시도별 품종별 출고 내역에 대한 데이터로 년산,지원명,시도명,작물명,품종명,수송차수,신청량 등의 항목을 제공합니다.
Author농림축산식품부 국립종자원
URLhttps://www.data.go.kr/data/15066260/fileData.do

Alerts

지원명 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 지원명High correlation

Reproduction

Analysis started2023-12-12 09:49:13.688574
Analysis finished2023-12-12 09:49:15.208637
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
2020
548 
2021
532 
2022
488 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2020 548
34.9%
2021 532
33.9%
2022 488
31.1%

Length

2023-12-12T18:49:15.301933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:49:15.422121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 548
34.9%
2021 532
33.9%
2022 488
31.1%

지원명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
충남지원
312 
경남지원
255 
강원진흥원
212 
전남지원
185 
경북지원
175 
Other values (5)
429 

Length

Max length8
Median length4
Mean length4.3533163
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충남지원 312
19.9%
경남지원 255
16.3%
강원진흥원 212
13.5%
전남지원 185
11.8%
경북지원 175
11.2%
전북지원 128
8.2%
경기종자관리소 106
 
6.8%
충북지원 99
 
6.3%
강원지원 90
 
5.7%
제주도농업기술원 6
 
0.4%

Length

2023-12-12T18:49:15.555303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:49:15.690395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충남지원 312
19.9%
경남지원 255
16.3%
강원진흥원 212
13.5%
전남지원 185
11.8%
경북지원 175
11.2%
전북지원 128
8.2%
경기종자관리소 106
 
6.8%
충북지원 99
 
6.3%
강원지원 90
 
5.7%
제주도농업기술원 6
 
0.4%

시도명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
전라남도
145 
전라북도
142 
경상남도
137 
경상북도
132 
충청남도
126 
Other values (12)
886 

Length

Max length7
Median length4
Mean length4.567602
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 145
9.2%
전라북도 142
9.1%
경상남도 137
 
8.7%
경상북도 132
 
8.4%
충청남도 126
 
8.0%
경기도 121
 
7.7%
충청북도 116
 
7.4%
강원특별자치도 110
 
7.0%
울산광역시 97
 
6.2%
인천광역시 89
 
5.7%
Other values (7) 353
22.5%

Length

2023-12-12T18:49:15.851008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 145
9.2%
전라북도 142
9.1%
경상남도 137
 
8.7%
경상북도 132
 
8.4%
충청남도 126
 
8.0%
경기도 121
 
7.7%
충청북도 116
 
7.4%
강원특별자치도 110
 
7.0%
울산광역시 97
 
6.2%
인천광역시 89
 
5.7%
Other values (7) 353
22.5%

작물명
Categorical

Distinct12
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
벼
691 
봄감자
212 
콩
208 
보리
203 
밀
 
69
Other values (7)
185 

Length

Max length6
Median length1
Mean length1.7193878
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
벼 691
44.1%
봄감자 212
 
13.5%
콩 208
 
13.3%
보리 203
 
12.9%
밀 69
 
4.4%
팥 47
 
3.0%
호밀 42
 
2.7%
보리(춘파) 37
 
2.4%
호밀(춘파) 26
 
1.7%
벼(비축) 20
 
1.3%
Other values (2) 13
 
0.8%

Length

2023-12-12T18:49:15.974790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벼 691
44.1%
봄감자 212
 
13.5%
콩 208
 
13.3%
보리 203
 
12.9%
밀 69
 
4.4%
팥 47
 
3.0%
호밀 42
 
2.7%
보리(춘파 37
 
2.4%
호밀(춘파 26
 
1.7%
벼(비축 20
 
1.3%
Other values (2) 13
 
0.8%

품종명
Text

Distinct70
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
2023-12-12T18:49:16.207144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.440051
Min length2

Characters and Unicode

Total characters5394
Distinct characters84
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

Unique0 ?
Unique (%)0.0%

Sample

1st row오대벼
2nd row고시히카리
3rd row해담쌀
4th row조명1호
5th row대안벼
ValueCountFrequency (%)
곡우 68
 
4.3%
대원콩 48
 
3.1%
동진찰벼 48
 
3.1%
수미 48
 
3.1%
아라리팥 47
 
3.0%
삼광벼 42
 
2.7%
두백 42
 
2.7%
백옥찰벼 41
 
2.6%
운광벼 40
 
2.6%
선풍콩 40
 
2.6%
Other values (60) 1104
70.4%
2023-12-12T18:49:16.641263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 510
 
9.5%
리 360
 
6.7%
보 264
 
4.9%
찰 214
 
4.0%
콩 208
 
3.9%
미 193
 
3.6%
쌀 178
 
3.3%
진 144
 
2.7%
대 129
 
2.4%
광 119
 
2.2%
Other values (74) 3075
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5264
97.6%
Decimal Number 56
 
1.0%
Close Punctuation 37
 
0.7%
Open Punctuation 37
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 510
 
9.7%
리 360
 
6.8%
보 264
 
5.0%
찰 214
 
4.1%
콩 208
 
4.0%
미 193
 
3.7%
쌀 178
 
3.4%
진 144
 
2.7%
대 129
 
2.5%
광 119
 
2.3%
Other values (71) 2945
55.9%
Decimal Number
ValueCountFrequency (%)
1 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5264
97.6%
Common 130
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 510
 
9.7%
리 360
 
6.8%
보 264
 
5.0%
찰 214
 
4.1%
콩 208
 
4.0%
미 193
 
3.7%
쌀 178
 
3.4%
진 144
 
2.7%
대 129
 
2.5%
광 119
 
2.3%
Other values (71) 2945
55.9%
Common
ValueCountFrequency (%)
1 56
43.1%
) 37
28.5%
( 37
28.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5264
97.6%
ASCII 130
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 510
 
9.7%
리 360
 
6.8%
보 264
 
5.0%
찰 214
 
4.1%
콩 208
 
4.0%
미 193
 
3.7%
쌀 178
 
3.4%
진 144
 
2.7%
대 129
 
2.5%
광 119
 
2.3%
Other values (71) 2945
55.9%
ASCII
ValueCountFrequency (%)
1 56
43.1%
) 37
28.5%
( 37
28.5%

수송차수
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7589286
Minimum0
Maximum5
Zeros6
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size13.9 KiB
2023-12-12T18:49:16.764132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1088997
Coefficient of variation (CV)0.63044045
Kurtosis0.4398375
Mean1.7589286
Median Absolute Deviation (MAD)0
Skewness1.2537624
Sum2758
Variance1.2296586
MonotonicityNot monotonic
2023-12-12T18:49:16.867190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 934
59.6%
2 273
 
17.4%
3 175
 
11.2%
4 147
 
9.4%
5 33
 
2.1%
0 6
 
0.4%
ValueCountFrequency (%)
0 6
 
0.4%
1 934
59.6%
2 273
 
17.4%
3 175
 
11.2%
4 147
 
9.4%
5 33
 
2.1%
ValueCountFrequency (%)
5 33
 
2.1%
4 147
 
9.4%
3 175
 
11.2%
2 273
 
17.4%
1 934
59.6%
0 6
 
0.4%

신청량
Real number (ℝ)

Distinct785
Distinct (%)50.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47610.07
Minimum0
Maximum1916800
Zeros5
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size13.9 KiB
2023-12-12T18:49:16.997630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q1180
median1500
Q313075
95-th percentile217056
Maximum1916800
Range1916800
Interquartile range (IQR)12895

Descriptive statistics

Standard deviation180377.45
Coefficient of variation (CV)3.7886406
Kurtosis43.483315
Mean47610.07
Median Absolute Deviation (MAD)1460
Skewness6.1826424
Sum74652590
Variance3.2536023 × 1010
MonotonicityNot monotonic
2023-12-12T18:49:17.229259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 78
 
5.0%
40 57
 
3.6%
60 46
 
2.9%
100 31
 
2.0%
80 29
 
1.8%
160 21
 
1.3%
200 18
 
1.1%
120 18
 
1.1%
220 15
 
1.0%
140 14
 
0.9%
Other values (775) 1241
79.1%
ValueCountFrequency (%)
0 5
 
0.3%
5 13
 
0.8%
10 11
 
0.7%
15 2
 
0.1%
20 78
5.0%
25 3
 
0.2%
30 6
 
0.4%
35 8
 
0.5%
40 57
3.6%
45 5
 
0.3%
ValueCountFrequency (%)
1916800 1
0.1%
1803480 1
0.1%
1648980 1
0.1%
1635320 1
0.1%
1570320 1
0.1%
1474160 1
0.1%
1458540 1
0.1%
1394920 1
0.1%
1377480 1
0.1%
1252860 1
0.1%

Interactions

2023-12-12T18:49:14.711227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:49:14.165769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:49:14.837666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:49:14.603509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:49:17.325034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명시도명작물명품종명수송차수신청량
년산1.0000.0000.0000.3300.4840.4100.000
지원명0.0001.0000.9710.6430.7820.2820.181
시도명0.0000.9711.0000.0000.1810.0000.000
작물명0.3300.6430.0001.0000.9780.7290.000
품종명0.4840.7820.1810.9781.0000.8750.403
수송차수0.4100.2820.0000.7290.8751.0000.125
신청량0.0000.1810.0000.0000.4030.1251.000
2023-12-12T18:49:17.425099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명작물명시도명
년산1.0000.0000.1570.000
지원명0.0001.0000.3350.862
작물명0.1570.3351.0000.000
시도명0.0000.8620.0001.000
2023-12-12T18:49:17.512233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수송차수신청량년산지원명시도명작물명
수송차수1.0000.0920.1860.1520.0000.374
신청량0.0921.0000.0000.0560.0000.000
년산0.1860.0001.0000.0000.0000.157
지원명0.1520.0560.0001.0000.8620.335
시도명0.0000.0000.0000.8621.0000.000
작물명0.3740.0000.1570.3350.0001.000

Missing values

2023-12-12T18:49:15.007380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:49:15.150142image/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

년산지원명시도명작물명품종명수송차수신청량
02020경기종자관리소경기도벼오대벼213760
12020경기종자관리소경기도벼고시히카리2210200
22020경기종자관리소경기도벼해담쌀23080
32020경기종자관리소경기도벼조명1호2440
42020경기종자관리소경기도벼대안벼2205480
52020경기종자관리소경기도벼추청벼1761640
62020경기종자관리소경기도벼동진찰벼21320
72020경기종자관리소경기도벼삼광벼2291860
82020경기종자관리소경기도벼영호진미3153480
92020경기종자관리소경기도벼백옥찰벼4940
년산지원명시도명작물명품종명수송차수신청량
15582022강원지원강원특별자치도콩대원콩144315
15592022강원지원강원특별자치도콩청아콩111680
15602022강원지원강원특별자치도콩진풍콩110
15612022강원지원강원특별자치도밀금강밀1580
15622022강원지원강원특별자치도밀조경밀1660
15632022강원지원강원특별자치도팥아라리팥118355
15642022강원지원강원특별자치도호밀곡우119880
15652022제주도농업기술원제주특별자치도콩풍산나물콩146625
15662022제주도농업기술원제주특별자치도콩아람콩13000
15672022제주도농업기술원제주특별자치도호밀곡우1240