Overview

Dataset statistics

Number of variables6
Number of observations364
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.5 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description10년간 채소종자의 국내, 해외 채종 비율을 제공하여1,300여개의 종자업 등록업체 및 유관기관(농업기술센터, 도 기술원 등)에게 종자산업 육성을 위한 기본 데이터 베이스로 활용
URLhttps://www.data.go.kr/data/15019338/fileData.do

Reproduction

Analysis started2023-12-13 00:09:31.283024
Analysis finished2023-12-13 00:09:31.668018
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct18
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.489
Minimum2005
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T09:09:31.708714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005
Q12009
median2013
Q32018
95-th percentile2022
Maximum2022
Range17
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.1690316
Coefficient of variation (CV)0.0025672013
Kurtosis-1.1905156
Mean2013.489
Median Absolute Deviation (MAD)4
Skewness0.0060319664
Sum732910
Variance26.718887
MonotonicityDecreasing
2023-12-13T09:09:31.790214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2013 21
 
5.8%
2012 21
 
5.8%
2014 21
 
5.8%
2011 21
 
5.8%
2005 20
 
5.5%
2006 20
 
5.5%
2007 20
 
5.5%
2008 20
 
5.5%
2009 20
 
5.5%
2010 20
 
5.5%
Other values (8) 160
44.0%
ValueCountFrequency (%)
2005 20
5.5%
2006 20
5.5%
2007 20
5.5%
2008 20
5.5%
2009 20
5.5%
2010 20
5.5%
2011 21
5.8%
2012 21
5.8%
2013 21
5.8%
2014 21
5.8%
ValueCountFrequency (%)
2022 20
5.5%
2021 20
5.5%
2020 20
5.5%
2019 20
5.5%
2018 20
5.5%
2017 20
5.5%
2016 20
5.5%
2015 20
5.5%
2014 21
5.8%
2013 21
5.8%

작물
Categorical

Distinct25
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
고추
 
18
대목용 오이
 
18
호박
 
18
대목용 수박
 
18
대목용 고추
 
18
Other values (20)
274 

Length

Max length7
Median length6
Mean length3.3626374
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고추
2nd row당근
3rd row무
4th row배추
5th row브로콜리

Common Values

ValueCountFrequency (%)
고추 18
 
4.9%
대목용 오이 18
 
4.9%
호박 18
 
4.9%
대목용 수박 18
 
4.9%
대목용 고추 18
 
4.9%
참외 18
 
4.9%
오이 18
 
4.9%
양파 18
 
4.9%
당근 18
 
4.9%
대목용 토마토 18
 
4.9%
Other values (15) 184
50.5%

Length

2023-12-13T09:09:31.914390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대목용 100
20.5%
고추 36
 
7.4%
오이 36
 
7.4%
호박 36
 
7.4%
수박 36
 
7.4%
토마토 32
 
6.6%
참외 28
 
5.7%
파 18
 
3.7%
양파 18
 
3.7%
당근 18
 
3.7%
Other values (14) 130
26.6%

총생산량
Text

Distinct337
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T09:09:32.125101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.3489011
Min length2

Characters and Unicode

Total characters2675
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)90.1%

Sample

1st row41619.00
2nd row29523.00
3rd row734665.00
4th row100611.00
5th row2017.00
ValueCountFrequency (%)
0.00 18
 
5.0%
40.00 4
 
1.1%
82.00 2
 
0.6%
664.00 2
 
0.6%
116.00 2
 
0.6%
53.00 2
 
0.6%
27.00 2
 
0.6%
58.00 2
 
0.6%
36501.00 1
 
0.3%
39672.00 1
 
0.3%
Other values (326) 326
90.1%
2023-12-13T09:09:32.453990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 877
32.8%
. 362
13.5%
1 216
 
8.1%
4 184
 
6.9%
2 174
 
6.5%
3 164
 
6.1%
5 156
 
5.8%
8 145
 
5.4%
6 139
 
5.2%
7 127
 
4.7%
Other values (2) 131
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2309
86.3%
Other Punctuation 362
 
13.5%
Space Separator 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 877
38.0%
1 216
 
9.4%
4 184
 
8.0%
2 174
 
7.5%
3 164
 
7.1%
5 156
 
6.8%
8 145
 
6.3%
6 139
 
6.0%
7 127
 
5.5%
9 127
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 362
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2675
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 877
32.8%
. 362
13.5%
1 216
 
8.1%
4 184
 
6.9%
2 174
 
6.5%
3 164
 
6.1%
5 156
 
5.8%
8 145
 
5.4%
6 139
 
5.2%
7 127
 
4.7%
Other values (2) 131
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 877
32.8%
. 362
13.5%
1 216
 
8.1%
4 184
 
6.9%
2 174
 
6.5%
3 164
 
6.1%
5 156
 
5.8%
8 145
 
5.4%
6 139
 
5.2%
7 127
 
4.7%
Other values (2) 131
 
4.9%

국내생산
Text

Distinct278
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T09:09:32.701930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.0302198
Min length2

Characters and Unicode

Total characters2195
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)68.4%

Sample

1st row642.00
2nd row1350.00
3rd row66926.00
4th row58737.00
5th row
ValueCountFrequency (%)
0.00 41
 
11.4%
30.00 7
 
1.9%
10.00 7
 
1.9%
40.00 6
 
1.7%
7.00 3
 
0.8%
23.00 3
 
0.8%
68.00 2
 
0.6%
116.00 2
 
0.6%
92.00 2
 
0.6%
100.00 2
 
0.6%
Other values (267) 285
79.2%
2023-12-13T09:09:33.279505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 885
40.3%
. 360
16.4%
1 157
 
7.2%
4 122
 
5.6%
2 108
 
4.9%
6 108
 
4.9%
3 101
 
4.6%
5 100
 
4.6%
8 87
 
4.0%
9 87
 
4.0%
Other values (2) 80
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1827
83.2%
Other Punctuation 360
 
16.4%
Space Separator 8
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 885
48.4%
1 157
 
8.6%
4 122
 
6.7%
2 108
 
5.9%
6 108
 
5.9%
3 101
 
5.5%
5 100
 
5.5%
8 87
 
4.8%
9 87
 
4.8%
7 72
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 360
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 885
40.3%
. 360
16.4%
1 157
 
7.2%
4 122
 
5.6%
2 108
 
4.9%
6 108
 
4.9%
3 101
 
4.6%
5 100
 
4.6%
8 87
 
4.0%
9 87
 
4.0%
Other values (2) 80
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 885
40.3%
. 360
16.4%
1 157
 
7.2%
4 122
 
5.6%
2 108
 
4.9%
6 108
 
4.9%
3 101
 
4.6%
5 100
 
4.6%
8 87
 
4.0%
9 87
 
4.0%
Other values (2) 80
 
3.6%

해외생산
Text

Distinct311
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T09:09:33.512864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.1593407
Min length2

Characters and Unicode

Total characters2606
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)84.6%

Sample

1st row40977.00
2nd row28173.00
3rd row667739.00
4th row41874.00
5th row2017.00
ValueCountFrequency (%)
0.00 52
 
14.4%
7224.00 2
 
0.6%
276631.00 1
 
0.3%
76783.00 1
 
0.3%
40977.00 1
 
0.3%
34405.00 1
 
0.3%
166525.00 1
 
0.3%
12698.00 1
 
0.3%
31853.00 1
 
0.3%
30268.00 1
 
0.3%
Other values (300) 300
82.9%
2023-12-13T09:09:33.852496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 894
34.3%
. 362
13.9%
4 190
 
7.3%
2 180
 
6.9%
1 169
 
6.5%
3 153
 
5.9%
7 151
 
5.8%
5 130
 
5.0%
6 127
 
4.9%
8 124
 
4.8%
Other values (2) 126
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2240
86.0%
Other Punctuation 362
 
13.9%
Space Separator 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 894
39.9%
4 190
 
8.5%
2 180
 
8.0%
1 169
 
7.5%
3 153
 
6.8%
7 151
 
6.7%
5 130
 
5.8%
6 127
 
5.7%
8 124
 
5.5%
9 122
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 362
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2606
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 894
34.3%
. 362
13.9%
4 190
 
7.3%
2 180
 
6.9%
1 169
 
6.5%
3 153
 
5.9%
7 151
 
5.8%
5 130
 
5.0%
6 127
 
4.9%
8 124
 
4.8%
Other values (2) 126
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 894
34.3%
. 362
13.9%
4 190
 
7.3%
2 180
 
6.9%
1 169
 
6.5%
3 153
 
5.9%
7 151
 
5.8%
5 130
 
5.0%
6 127
 
4.9%
8 124
 
4.8%
Other values (2) 126
 
4.8%

해외채종율
Text

Distinct228
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T09:09:34.173491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.9175824
Min length2

Characters and Unicode

Total characters1790
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)52.5%

Sample

1st row98.00
2nd row95.00
3rd row91.00
4th row42.00
5th row100.00
ValueCountFrequency (%)
0.00 52
 
14.4%
100.00 28
 
7.7%
99.90 11
 
3.0%
99.00 5
 
1.4%
98.80 4
 
1.1%
99.10 4
 
1.1%
97.00 4
 
1.1%
99.70 3
 
0.8%
95.00 3
 
0.8%
94.00 3
 
0.8%
Other values (217) 245
67.7%
2023-12-13T09:09:34.586124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 459
25.6%
. 362
20.2%
9 319
17.8%
8 112
 
6.3%
7 97
 
5.4%
1 95
 
5.3%
4 79
 
4.4%
6 72
 
4.0%
5 70
 
3.9%
3 64
 
3.6%
Other values (2) 61
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1424
79.6%
Other Punctuation 362
 
20.2%
Space Separator 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 459
32.2%
9 319
22.4%
8 112
 
7.9%
7 97
 
6.8%
1 95
 
6.7%
4 79
 
5.5%
6 72
 
5.1%
5 70
 
4.9%
3 64
 
4.5%
2 57
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 362
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 459
25.6%
. 362
20.2%
9 319
17.8%
8 112
 
6.3%
7 97
 
5.4%
1 95
 
5.3%
4 79
 
4.4%
6 72
 
4.0%
5 70
 
3.9%
3 64
 
3.6%
Other values (2) 61
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 459
25.6%
. 362
20.2%
9 319
17.8%
8 112
 
6.3%
7 97
 
5.4%
1 95
 
5.3%
4 79
 
4.4%
6 72
 
4.0%
5 70
 
3.9%
3 64
 
3.6%
Other values (2) 61
 
3.4%

Interactions

2023-12-13T09:09:31.439966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:09:34.663837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도작물
연도1.0000.000
작물0.0001.000
2023-12-13T09:09:34.725672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도작물
연도1.0000.000
작물0.0001.000

Missing values

2023-12-13T09:09:31.561567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:09:31.637975image/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

연도작물총생산량국내생산해외생산해외채종율
02022고추41619.00642.0040977.0098.00
12022당근29523.001350.0028173.0095.00
22022무734665.0066926.00667739.0091.00
32022배추100611.0058737.0041874.0042.00
42022브로콜리2017.002017.00100.00
52022상추23749.00300.0023449.0099.00
62022수박8249.00535.007715.0094.00
72022시금치104974.00104974.00100.00
82022양배추72724.001827.0070898.0097.00
92022양파49348.009856.0039492.0080.00
연도작물총생산량국내생산해외생산해외채종율
3542005참외2085.00317.001768.0084.80
3552005토마토1594.0034.001560.0097.87
3562005파44079.003632.0040447.0091.76
3572005호박23248.002067.0021181.0091.11
3582005대목용 고추132.0010.00122.0092.42
3592005대목용 수박10.0010.000.000.00
3602005대목용 오이5.005.000.000.00
3612005대목용 참외80.0080.000.000.00
3622005대목용 토마토69.000.0069.00100.00
3632005대목용 호박74820.00590.0074230.0099.21