Overview

Dataset statistics

Number of variables7
Number of observations310
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 KiB
Average record size in memory60.4 B

Variable types

Categorical3
Text1
Numeric3

Dataset

Description정보보급종 수매가격 내역으로 년산,작물명,품종명,구분,종자대금,생산보상금,포장합계 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15066262/fileData.do

Alerts

종자대금 is highly overall correlated with 생산보상금 and 2 other fieldsHigh correlation
생산보상금 is highly overall correlated with 종자대금 and 2 other fieldsHigh correlation
포장합계 is highly overall correlated with 종자대금 and 2 other fieldsHigh correlation
구분 is highly overall correlated with 종자대금 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 06:34:40.271794
Analysis finished2023-12-12 06:34:41.716136
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2020
106 
2021
106 
2022
98 

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 106
34.2%
2021 106
34.2%
2022 98
31.6%

Length

2023-12-12T15:34:41.798183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:34:41.932392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 106
34.2%
2021 106
34.2%
2022 98
31.6%

작물명
Categorical

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
벼
162 
콩
58 
보리
54 
밀
24 
팥
 
6

Length

Max length2
Median length1
Mean length1.1935484
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
벼 162
52.3%
콩 58
 
18.7%
보리 54
 
17.4%
밀 24
 
7.7%
팥 6
 
1.9%
호밀 6
 
1.9%

Length

2023-12-12T15:34:42.071268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:34:42.196161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
벼 162
52.3%
콩 58
 
18.7%
보리 54
 
17.4%
밀 24
 
7.7%
팥 6
 
1.9%
호밀 6
 
1.9%

품종명
Text

Distinct59
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T15:34:42.469325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.5612903
Min length2

Characters and Unicode

Total characters1104
Distinct characters75
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

Unique0 ?
Unique (%)0.0%

Sample

1st row금강밀
2nd row금강밀
3rd row백강밀
4th row백강밀
5th row새금강밀
ValueCountFrequency (%)
금강밀 6
 
1.9%
추청벼 6
 
1.9%
참드림 6
 
1.9%
진풍콩 6
 
1.9%
친들벼 6
 
1.9%
백강밀 6
 
1.9%
해담쌀 6
 
1.9%
일품벼 6
 
1.9%
청아콩 6
 
1.9%
누리찰쌀보리 6
 
1.9%
Other values (49) 250
80.6%
2023-12-12T15:34:43.012169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 106
 
9.6%
리 78
 
7.1%
콩 58
 
5.3%
보 58
 
5.3%
찰 40
 
3.6%
쌀 36
 
3.3%
새 36
 
3.3%
미 30
 
2.7%
풍 30
 
2.7%
진 30
 
2.7%
Other values (65) 602
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1092
98.9%
Decimal Number 12
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 106
 
9.7%
리 78
 
7.1%
콩 58
 
5.3%
보 58
 
5.3%
찰 40
 
3.7%
쌀 36
 
3.3%
새 36
 
3.3%
미 30
 
2.7%
풍 30
 
2.7%
진 30
 
2.7%
Other values (64) 590
54.0%
Decimal Number
ValueCountFrequency (%)
1 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1092
98.9%
Common 12
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 106
 
9.7%
리 78
 
7.1%
콩 58
 
5.3%
보 58
 
5.3%
찰 40
 
3.7%
쌀 36
 
3.3%
새 36
 
3.3%
미 30
 
2.7%
풍 30
 
2.7%
진 30
 
2.7%
Other values (64) 590
54.0%
Common
ValueCountFrequency (%)
1 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1092
98.9%
ASCII 12
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 106
 
9.7%
리 78
 
7.1%
콩 58
 
5.3%
보 58
 
5.3%
찰 40
 
3.7%
쌀 36
 
3.3%
새 36
 
3.3%
미 30
 
2.7%
풍 30
 
2.7%
진 30
 
2.7%
Other values (64) 590
54.0%
ASCII
ValueCountFrequency (%)
1 12
100.0%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
산물
155 
포장
155 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산물
2nd row포장
3rd row산물
4th row포장
5th row산물

Common Values

ValueCountFrequency (%)
산물 155
50.0%
포장 155
50.0%

Length

2023-12-12T15:34:43.189440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:34:43.603151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산물 155
50.0%
포장 155
50.0%

종자대금
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48082.419
Minimum696
Maximum460000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:34:43.707700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum696
5-th percentile840
Q11400
median19670
Q356000
95-th percentile248000
Maximum460000
Range459304
Interquartile range (IQR)54600

Descriptive statistics

Standard deviation77851.6
Coefficient of variation (CV)1.6191282
Kurtosis6.0378889
Mean48082.419
Median Absolute Deviation (MAD)18747
Skewness2.4704264
Sum14905550
Variance6.0608716 × 109
MonotonicityNot monotonic
2023-12-12T15:34:43.836919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1400 29
 
9.4%
56000 29
 
9.4%
1600 27
 
8.7%
64000 27
 
8.7%
52000 25
 
8.1%
1300 25
 
8.1%
975 12
 
3.9%
39000 12
 
3.9%
256400 9
 
2.9%
6410 9
 
2.9%
Other values (34) 106
34.2%
ValueCountFrequency (%)
696 4
 
1.3%
732 4
 
1.3%
785 5
 
1.6%
840 5
 
1.6%
884 4
 
1.3%
962 5
 
1.6%
975 12
3.9%
1300 25
8.1%
1400 29
9.4%
1552 1
 
0.3%
ValueCountFrequency (%)
460000 1
 
0.3%
405200 1
 
0.3%
364000 1
 
0.3%
283200 1
 
0.3%
265600 2
 
0.6%
256400 9
2.9%
248000 2
 
0.6%
235600 8
2.6%
230000 7
2.3%
65600 1
 
0.3%

생산보상금
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15355.955
Minimum174
Maximum92000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:34:43.986916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174
5-th percentile210
Q1700
median4630
Q328000
95-th percentile49600
Maximum92000
Range91826
Interquartile range (IQR)27300

Descriptive statistics

Standard deviation18356.982
Coefficient of variation (CV)1.1954308
Kurtosis0.42287237
Mean15355.955
Median Absolute Deviation (MAD)4403
Skewness1.0496005
Sum4760346
Variance3.3697878 × 108
MonotonicityNot monotonic
2023-12-12T15:34:44.130893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
928 26
 
8.4%
37120 26
 
8.4%
27680 24
 
7.7%
692 24
 
7.7%
700 23
 
7.4%
28000 23
 
7.4%
1282 9
 
2.9%
51280 9
 
2.9%
11680 8
 
2.6%
292 8
 
2.6%
Other values (42) 130
41.9%
ValueCountFrequency (%)
174 4
1.3%
183 4
1.3%
196 5
1.6%
210 5
1.6%
244 4
1.3%
265 4
1.3%
288 5
1.6%
292 8
2.6%
388 1
 
0.3%
410 1
 
0.3%
ValueCountFrequency (%)
92000 1
 
0.3%
81040 1
 
0.3%
72800 1
 
0.3%
56640 1
 
0.3%
53120 2
 
0.6%
51280 9
2.9%
49600 2
 
0.6%
47120 8
2.6%
46000 7
2.3%
41000 3
 
1.0%

포장합계
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63438.374
Minimum870
Maximum552000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:34:44.304288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum870
5-th percentile1050
Q12292
median24300
Q391680
95-th percentile297600
Maximum552000
Range551130
Interquartile range (IQR)89388

Descriptive statistics

Standard deviation94317.35
Coefficient of variation (CV)1.4867555
Kurtosis5.1287058
Mean63438.374
Median Absolute Deviation (MAD)23116
Skewness2.2283861
Sum19665896
Variance8.8957626 × 109
MonotonicityNot monotonic
2023-12-12T15:34:44.523793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2328 26
 
8.4%
93120 26
 
8.4%
91680 24
 
7.7%
2292 24
 
7.7%
2000 23
 
7.4%
80000 23
 
7.4%
7692 9
 
2.9%
307680 9
 
2.9%
50680 8
 
2.6%
1267 8
 
2.6%
Other values (42) 130
41.9%
ValueCountFrequency (%)
870 4
 
1.3%
915 4
 
1.3%
981 5
 
1.6%
1050 5
 
1.6%
1149 4
 
1.3%
1219 4
 
1.3%
1250 5
 
1.6%
1267 8
 
2.6%
1940 1
 
0.3%
2000 23
7.4%
ValueCountFrequency (%)
552000 1
 
0.3%
486240 1
 
0.3%
436800 1
 
0.3%
339840 1
 
0.3%
318720 2
 
0.6%
307680 9
2.9%
297600 2
 
0.6%
282720 8
2.6%
276000 7
2.3%
97000 3
 
1.0%

Interactions

2023-12-12T15:34:41.181365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:40.619474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:40.898800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:41.276343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:40.704652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:41.005467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:41.378177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:40.785357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:34:41.093013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:34:44.636074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산작물명품종명구분종자대금생산보상금포장합계
년산1.0000.0000.0000.0000.2400.6140.240
작물명0.0001.0001.0000.0000.6860.7220.686
품종명0.0001.0001.0000.0000.3210.0000.321
구분0.0000.0000.0001.0000.9270.9830.927
종자대금0.2400.6860.3210.9271.0000.9791.000
생산보상금0.6140.7220.0000.9830.9791.0000.979
포장합계0.2400.6860.3210.9271.0000.9791.000
2023-12-12T15:34:44.764912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작물명년산구분
작물명1.0000.0000.000
년산0.0001.0000.000
구분0.0000.0001.000
2023-12-12T15:34:44.872841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종자대금생산보상금포장합계년산작물명구분
종자대금1.0000.9470.9790.1530.4700.760
생산보상금0.9471.0000.9860.4510.4870.875
포장합계0.9790.9861.0000.1530.4700.760
년산0.1530.4510.1531.0000.0000.000
작물명0.4700.4870.4700.0001.0000.000
구분0.7600.8750.7600.0000.0001.000

Missing values

2023-12-12T15:34:41.511241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:34:41.660103image/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

년산작물명품종명구분종자대금생산보상금포장합계
02020밀금강밀산물9752441219
12020밀금강밀포장39000976048760
22020밀백강밀산물9752441219
32020밀백강밀포장39000976048760
42020밀새금강밀산물9752441219
52020밀새금강밀포장39000976048760
62020밀조경밀산물9752441219
72020밀조경밀포장39000976048760
82020벼고시히카리산물14009282328
92020벼고시히카리포장560003712093120
년산작물명품종명구분종자대금생산보상금포장합계
3002022콩청아콩산물575011506900
3012022콩청아콩포장23000046000276000
3022022콩태광콩산물575011506900
3032022콩태광콩포장23000046000276000
3042022콩풍산나물콩산물620012407440
3052022콩풍산나물콩포장24800049600297600
3062022팥아라리팥산물9100182010920
3072022팥아라리팥포장36400072800436800
3082022호밀곡우산물16254902115
3092022호밀곡우포장650001960084600