Overview

Dataset statistics

Number of variables8
Number of observations275
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.4 KiB
Average record size in memory68.5 B

Variable types

Categorical4
Text1
Numeric3

Dataset

Description정부보급종 생산계획 현황으로 년산,지원명,시도,작물명,품종명,면적(ha),종자량(kg),생산목표(톤) 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15066261/fileData.do

Alerts

시도 is highly overall correlated with 지원명High correlation
지원명 is highly overall correlated with 시도High correlation
면적(ha) is highly overall correlated with 종자량(kg) and 1 other fieldsHigh correlation
종자량(kg) is highly overall correlated with 면적(ha) and 1 other fieldsHigh correlation
생산목표(톤) is highly overall correlated with 면적(ha) and 1 other fieldsHigh correlation
면적(ha) has 10 (3.6%) zerosZeros
종자량(kg) has 13 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-12 13:57:41.506778
Analysis finished2023-12-12 13:57:43.214266
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2020
100 
2021
88 
2022
87 

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 100
36.4%
2021 88
32.0%
2022 87
31.6%

Length

2023-12-12T22:57:43.275321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:57:43.383452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
36.4%
2021 88
32.0%
2022 87
31.6%

지원명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
전북지원
50 
경남지원
40 
전남지원
39 
충남지원
36 
경기종자관리소
33 
Other values (4)
77 

Length

Max length7
Median length4
Mean length4.3672727
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북지원 50
18.2%
경남지원 40
14.5%
전남지원 39
14.2%
충남지원 36
13.1%
경기종자관리소 33
12.0%
경북지원 27
9.8%
강원지원 25
9.1%
충북지원 23
8.4%
영암사무소 2
 
0.7%

Length

2023-12-12T22:57:43.510788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:57:43.660262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북지원 50
18.2%
경남지원 40
14.5%
전남지원 39
14.2%
충남지원 36
13.1%
경기종자관리소 33
12.0%
경북지원 27
9.8%
강원지원 25
9.1%
충북지원 23
8.4%
영암사무소 2
 
0.7%

시도
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
전라북도
50 
전라남도
41 
경상남도
40 
충청남도
36 
경기도
33 
Other values (3)
75 

Length

Max length7
Median length4
Mean length4.1527273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 50
18.2%
전라남도 41
14.9%
경상남도 40
14.5%
충청남도 36
13.1%
경기도 33
12.0%
경상북도 27
9.8%
강원특별자치도 25
9.1%
충청북도 23
8.4%

Length

2023-12-12T22:57:43.843517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:57:44.006729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 50
18.2%
전라남도 41
14.9%
경상남도 40
14.5%
충청남도 36
13.1%
경기도 33
12.0%
경상북도 27
9.8%
강원특별자치도 25
9.1%
충청북도 23
8.4%

작물명
Categorical

Distinct7
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
벼
139 
콩
66 
보리
39 
밀
19 
팥
 
6
Other values (2)
 
6

Length

Max length4
Median length1
Mean length1.1709091
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
벼 139
50.5%
콩 66
24.0%
보리 39
 
14.2%
밀 19
 
6.9%
팥 6
 
2.2%
호밀 5
 
1.8%
TEST 1
 
0.4%

Length

2023-12-12T22:57:44.144392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:57:44.299227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
벼 139
50.5%
콩 66
24.0%
보리 39
 
14.2%
밀 19
 
6.9%
팥 6
 
2.2%
호밀 5
 
1.8%
test 1
 
0.4%

품종명
Text

Distinct61
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T22:57:44.542192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.5854545
Min length2

Characters and Unicode

Total characters986
Distinct characters84
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

Unique5 ?
Unique (%)1.8%

Sample

1st row삼광벼
2nd row오대벼
3rd row오륜벼
4th row운광벼
5th row탄력공급분
ValueCountFrequency (%)
대원콩 18
 
6.5%
삼광벼 16
 
5.8%
대찬콩 12
 
4.4%
해담쌀 9
 
3.3%
추청벼 8
 
2.9%
탄력공급분 8
 
2.9%
선풍콩 8
 
2.9%
새일미벼 7
 
2.5%
풍산나물콩 7
 
2.5%
흰찰쌀보리 7
 
2.5%
Other values (51) 175
63.6%
2023-12-12T22:57:44.936616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 92
 
9.3%
콩 66
 
6.7%
리 57
 
5.8%
대 41
 
4.2%
보 41
 
4.2%
쌀 31
 
3.1%
찰 30
 
3.0%
새 28
 
2.8%
광 26
 
2.6%
풍 24
 
2.4%
Other values (74) 550
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 973
98.7%
Decimal Number 9
 
0.9%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 92
 
9.5%
콩 66
 
6.8%
리 57
 
5.9%
대 41
 
4.2%
보 41
 
4.2%
쌀 31
 
3.2%
찰 30
 
3.1%
새 28
 
2.9%
광 26
 
2.7%
풍 24
 
2.5%
Other values (70) 537
55.2%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
E 1
25.0%
S 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 973
98.7%
Common 9
 
0.9%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 92
 
9.5%
콩 66
 
6.8%
리 57
 
5.9%
대 41
 
4.2%
보 41
 
4.2%
쌀 31
 
3.2%
찰 30
 
3.1%
새 28
 
2.9%
광 26
 
2.7%
풍 24
 
2.5%
Other values (70) 537
55.2%
Latin
ValueCountFrequency (%)
T 2
50.0%
E 1
25.0%
S 1
25.0%
Common
ValueCountFrequency (%)
1 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 973
98.7%
ASCII 13
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 92
 
9.5%
콩 66
 
6.8%
리 57
 
5.9%
대 41
 
4.2%
보 41
 
4.2%
쌀 31
 
3.2%
찰 30
 
3.1%
새 28
 
2.9%
광 26
 
2.7%
풍 24
 
2.5%
Other values (70) 537
55.2%
ASCII
ValueCountFrequency (%)
1 9
69.2%
T 2
 
15.4%
E 1
 
7.7%
S 1
 
7.7%

면적(ha)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct179
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.969927
Minimum0
Maximum610
Zeros10
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T22:57:45.077852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.26
Q116.05
median30
Q376.55
95-th percentile242.4
Maximum610
Range610
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation92.587645
Coefficient of variation (CV)1.4034826
Kurtosis9.8445845
Mean65.969927
Median Absolute Deviation (MAD)19
Skewness2.9308658
Sum18141.73
Variance8572.472
MonotonicityNot monotonic
2023-12-12T22:57:45.232320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 11
 
4.0%
0.0 10
 
3.6%
22.0 9
 
3.3%
15.0 8
 
2.9%
10.0 7
 
2.5%
30.0 7
 
2.5%
16.0 7
 
2.5%
18.0 4
 
1.5%
12.0 4
 
1.5%
26.0 4
 
1.5%
Other values (169) 204
74.2%
ValueCountFrequency (%)
0.0 10
3.6%
0.6 1
 
0.4%
1.8 1
 
0.4%
2.0 1
 
0.4%
3.7 1
 
0.4%
4.5 1
 
0.4%
5.0 1
 
0.4%
5.8 1
 
0.4%
6.0 1
 
0.4%
6.2 1
 
0.4%
ValueCountFrequency (%)
610.0 1
0.4%
469.2 1
0.4%
460.0 1
0.4%
454.5 1
0.4%
429.0 1
0.4%
425.3 1
0.4%
400.0 2
0.7%
389.0 1
0.4%
383.0 1
0.4%
285.6 1
0.4%

종자량(kg)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct193
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4556.6655
Minimum0
Maximum30550
Zeros13
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T22:57:45.381883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile82.1
Q11030
median2000
Q35532
95-th percentile18597
Maximum30550
Range30550
Interquartile range (IQR)4502

Descriptive statistics

Standard deviation5855.8336
Coefficient of variation (CV)1.2851138
Kurtosis5.1467451
Mean4556.6655
Median Absolute Deviation (MAD)1389
Skewness2.2498451
Sum1253083
Variance34290788
MonotonicityNot monotonic
2023-12-12T22:57:45.536057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 13
 
4.7%
1800 8
 
2.9%
600 8
 
2.9%
900 7
 
2.5%
960 5
 
1.8%
1000 5
 
1.8%
1100 5
 
1.8%
1200 4
 
1.5%
1750 3
 
1.1%
2700 3
 
1.1%
Other values (183) 214
77.8%
ValueCountFrequency (%)
0 13
4.7%
17 1
 
0.4%
110 1
 
0.4%
120 1
 
0.4%
222 1
 
0.4%
300 1
 
0.4%
330 2
 
0.7%
400 3
 
1.1%
444 1
 
0.4%
550 1
 
0.4%
ValueCountFrequency (%)
30550 1
0.4%
30500 1
0.4%
27600 1
0.4%
25960 1
0.4%
25520 1
0.4%
24000 1
0.4%
23460 1
0.4%
22730 1
0.4%
21450 1
0.4%
20800 1
0.4%

생산목표(톤)
Real number (ℝ)

HIGH CORRELATION 

Distinct173
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean306.31818
Minimum0
Maximum3355
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T22:57:45.703841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.63
Q148
median118
Q3310
95-th percentile1291.6
Maximum3355
Range3355
Interquartile range (IQR)262

Descriptive statistics

Standard deviation514.6759
Coefficient of variation (CV)1.6802003
Kurtosis11.708558
Mean306.31818
Median Absolute Deviation (MAD)86.5
Skewness3.2523666
Sum84237.5
Variance264891.28
MonotonicityNot monotonic
2023-12-12T22:57:45.862014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110.0 8
 
2.9%
66.0 8
 
2.9%
21.0 7
 
2.5%
31.0 6
 
2.2%
32.0 6
 
2.2%
42.0 6
 
2.2%
26.0 5
 
1.8%
22.0 4
 
1.5%
310.0 4
 
1.5%
65.0 4
 
1.5%
Other values (163) 217
78.9%
ValueCountFrequency (%)
0.0 2
0.7%
2.5 1
 
0.4%
2.8 1
 
0.4%
3.0 1
 
0.4%
5.2 1
 
0.4%
7.0 1
 
0.4%
10.4 1
 
0.4%
11.0 3
1.1%
14.0 3
1.1%
14.9 1
 
0.4%
ValueCountFrequency (%)
3355.0 1
0.4%
2909.0 1
0.4%
2530.0 2
0.7%
2500.0 1
0.4%
2339.0 1
0.4%
2200.0 1
0.4%
2160.0 1
0.4%
2140.0 1
0.4%
2002.0 1
0.4%
1540.0 1
0.4%

Interactions

2023-12-12T22:57:42.631191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:41.940645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.290040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.766745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.074502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.394564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.882142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.191319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:57:42.497844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:57:45.997859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명시도작물명품종명면적(ha)종자량(kg)생산목표(톤)
년산1.0000.0000.0000.0000.0000.0000.0000.000
지원명0.0001.0001.0000.2390.8650.1030.1600.000
시도0.0001.0001.0000.2350.8820.2170.2010.068
작물명0.0000.2390.2351.0001.0000.0000.1980.060
품종명0.0000.8650.8821.0001.0000.7290.6790.674
면적(ha)0.0000.1030.2170.0000.7291.0000.9010.957
종자량(kg)0.0000.1600.2010.1980.6790.9011.0000.929
생산목표(톤)0.0000.0000.0680.0600.6740.9570.9291.000
2023-12-12T22:57:46.140068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산작물명시도지원명
년산1.0000.0000.0000.000
작물명0.0001.0000.1270.127
시도0.0000.1271.0000.998
지원명0.0000.1270.9981.000
2023-12-12T22:57:46.645545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(ha)종자량(kg)생산목표(톤)년산지원명시도작물명
면적(ha)1.0000.8580.8440.0000.0490.0730.000
종자량(kg)0.8581.0000.7090.0000.0720.0960.100
생산목표(톤)0.8440.7091.0000.0000.0000.0300.028
년산0.0000.0000.0001.0000.0000.0000.000
지원명0.0490.0720.0000.0001.0000.9980.127
시도0.0730.0960.0300.0000.9981.0000.127
작물명0.0000.1000.0280.0000.1270.1271.000

Missing values

2023-12-12T22:57:43.027825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:57:43.167358image/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

년산지원명시도작물명품종명면적(ha)종자량(kg)생산목표(톤)
02020강원지원강원특별자치도벼삼광벼52.02860286.0
12020강원지원강원특별자치도벼오대벼189.610428891.0
22020강원지원강원특별자치도벼오륜벼11.060561.0
32020강원지원강원특별자치도벼운광벼20.01100110.0
42020강원지원강원특별자치도벼탄력공급분0.0011.0
52020강원지원강원특별자치도콩대원콩84.05040134.0
62020강원지원강원특별자치도콩대풍콩16.0112026.0
72020강원지원강원특별자치도콩청아콩16.096026.0
82020강원지원강원특별자치도팥아라리팥12.261011.0
92020경기종자관리소경기도벼고시히카리86.34315435.0
년산지원명시도작물명품종명면적(ha)종자량(kg)생산목표(톤)
2652022충남지원충청남도콩대찬콩30.0180042.0
2662022충남지원충청남도콩선풍콩15.090021.0
2672022충북지원충청북도벼삼광벼64.03200352.0
2682022충북지원충청북도벼알찬미18.090099.0
2692022충북지원충청북도벼오대벼12.060066.0
2702022충북지원충청북도벼참드림26.01300143.0
2712022충북지원충청북도벼추청벼66.03300363.0
2722022충북지원충청북도보리올보리10.0180032.0
2732022충북지원충청북도콩대원콩116.06960163.0
2742022충북지원충청북도콩대찬콩16.096023.0