Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells2267
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Numeric1
Categorical3
Text1

Dataset

Description- 연도·시도·재배지 구분·채소별 재매 면적 정보를 제공합니다. - 단위: 헥타르 - 데이터 제공처: KOSIS 국가통계포털
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/854

Alerts

재배면적 has 2267 (22.7%) missing valuesMissing

Reproduction

Analysis started2023-12-11 20:17:07.904607
Analysis finished2023-12-11 20:17:08.357133
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.0477
Minimum2000
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:17:08.402174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001
Q12005
median2011
Q32017
95-th percentile2021
Maximum2022
Range22
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.6222511
Coefficient of variation (CV)0.0032929359
Kurtosis-1.1981521
Mean2011.0477
Median Absolute Deviation (MAD)6
Skewness0.001957388
Sum20110477
Variance43.85421
MonotonicityNot monotonic
2023-12-12T05:17:08.487203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2010 467
 
4.7%
2016 465
 
4.7%
2022 460
 
4.6%
2020 453
 
4.5%
2005 448
 
4.5%
2004 447
 
4.5%
2013 445
 
4.5%
2007 444
 
4.4%
2003 443
 
4.4%
2017 443
 
4.4%
Other values (13) 5485
54.9%
ValueCountFrequency (%)
2000 422
4.2%
2001 422
4.2%
2002 405
4.0%
2003 443
4.4%
2004 447
4.5%
2005 448
4.5%
2006 429
4.3%
2007 444
4.4%
2008 420
4.2%
2009 434
4.3%
ValueCountFrequency (%)
2022 460
4.6%
2021 432
4.3%
2020 453
4.5%
2019 403
4.0%
2018 423
4.2%
2017 443
4.4%
2016 465
4.7%
2015 416
4.2%
2014 416
4.2%
2013 445
4.5%

시도
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
세종특별자치시
 
619
충청북도
 
617
광주광역시
 
611
전라남도
 
608
강원도
 
605
Other values (12)
6940 

Length

Max length7
Median length5
Mean length4.422
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전광역시
2nd row전라남도
3rd row서울특별시
4th row경상남도
5th row부산광역시

Common Values

ValueCountFrequency (%)
세종특별자치시 619
 
6.2%
충청북도 617
 
6.2%
광주광역시 611
 
6.1%
전라남도 608
 
6.1%
강원도 605
 
6.0%
대구광역시 600
 
6.0%
대전광역시 599
 
6.0%
전라북도 597
 
6.0%
서울특별시 576
 
5.8%
울산광역시 576
 
5.8%
Other values (7) 3992
39.9%

Length

2023-12-12T05:17:08.582573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
세종특별자치시 619
 
6.2%
충청북도 617
 
6.2%
광주광역시 611
 
6.1%
전라남도 608
 
6.1%
강원도 605
 
6.0%
대구광역시 600
 
6.0%
대전광역시 599
 
6.0%
전라북도 597
 
6.0%
울산광역시 576
 
5.8%
서울특별시 576
 
5.8%
Other values (7) 3992
39.9%

재배지구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
밭
5043 
논
4957 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row논
2nd row논
3rd row밭
4th row논
5th row밭

Common Values

ValueCountFrequency (%)
밭 5043
50.4%
논 4957
49.6%

Length

2023-12-12T05:17:08.678170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:17:08.748609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
밭 5043
50.4%
논 4957
49.6%

채소구분
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
겨울무
 
302
기타무
 
292
양파
 
289
과채류
 
287
쪽파
 
284
Other values (32)
8546 

Length

Max length5
Median length4
Mean length2.9155
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고추
2nd row기타배추
3rd row가을무
4th row일반총각무
5th row기타배추

Common Values

ValueCountFrequency (%)
겨울무 302
 
3.0%
기타무 292
 
2.9%
양파 289
 
2.9%
과채류 287
 
2.9%
쪽파 284
 
2.8%
생강 283
 
2.8%
기타배추 283
 
2.8%
무 계 282
 
2.8%
겨울배추 282
 
2.8%
조미채소 279
 
2.8%
Other values (27) 7137
71.4%

Length

2023-12-12T05:17:08.842344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
겨울무 302
 
2.9%
기타무 292
 
2.8%
양파 289
 
2.8%
과채류 287
 
2.8%
쪽파 284
 
2.8%
생강 283
 
2.8%
기타배추 283
 
2.8%
무 282
 
2.7%
계 282
 
2.7%
겨울배추 282
 
2.7%
Other values (28) 7416
72.1%

재배면적
Text

MISSING 

Distinct2585
Distinct (%)33.4%
Missing2267
Missing (%)22.7%
Memory size156.2 KiB
2023-12-12T05:17:09.095886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length2.8008535
Min length1

Characters and Unicode

Total characters21659
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

Unique2122 ?
Unique (%)27.4%

Sample

1st row14
2nd row5
3rd row740
4th row51
5th row0
ValueCountFrequency (%)
0 2124
27.5%
1 218
 
2.8%
2 126
 
1.6%
3 122
 
1.6%
4 79
 
1.0%
5 70
 
0.9%
7 57
 
0.7%
16 55
 
0.7%
9 55
 
0.7%
6 54
 
0.7%
Other values (2575) 4773
61.7%
2023-12-12T05:17:09.480814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3646
16.8%
1 3035
14.0%
2 2325
10.7%
3 2010
9.3%
4 1739
8.0%
5 1621
7.5%
6 1581
7.3%
7 1494
6.9%
9 1423
 
6.6%
8 1422
 
6.6%
Other values (2) 1363
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20296
93.7%
Other Punctuation 1314
 
6.1%
Dash Punctuation 49
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3646
18.0%
1 3035
15.0%
2 2325
11.5%
3 2010
9.9%
4 1739
8.6%
5 1621
8.0%
6 1581
7.8%
7 1494
7.4%
9 1423
 
7.0%
8 1422
 
7.0%
Other Punctuation
ValueCountFrequency (%)
. 1314
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21659
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3646
16.8%
1 3035
14.0%
2 2325
10.7%
3 2010
9.3%
4 1739
8.0%
5 1621
7.5%
6 1581
7.3%
7 1494
6.9%
9 1423
 
6.6%
8 1422
 
6.6%
Other values (2) 1363
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3646
16.8%
1 3035
14.0%
2 2325
10.7%
3 2010
9.3%
4 1739
8.0%
5 1621
7.5%
6 1581
7.3%
7 1494
6.9%
9 1423
 
6.6%
8 1422
 
6.6%
Other values (2) 1363
 
6.3%

Interactions

2023-12-12T05:17:08.173518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:17:09.561144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시도재배지구분채소구분
연도1.0000.0000.0000.000
시도0.0001.0000.0000.000
재배지구분0.0000.0001.0000.000
채소구분0.0000.0000.0001.000
2023-12-12T05:17:09.636304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배지구분시도채소구분
재배지구분1.0000.0000.000
시도0.0001.0000.000
채소구분0.0000.0001.000
2023-12-12T05:17:09.711232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시도재배지구분채소구분
연도1.0000.0000.0000.000
시도0.0001.0000.0000.000
재배지구분0.0000.0001.0000.000
채소구분0.0000.0000.0001.000

Missing values

2023-12-12T05:17:08.256223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:17:08.324898image/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

연도시도재배지구분채소구분재배면적
29152002대전광역시논고추14
47602003전라남도논기타배추<NA>
126282010서울특별시밭가을무5
48972003경상남도논일반총각무<NA>
265532021부산광역시밭기타배추<NA>
174092013경상북도논배추계740
196302015충청북도논봄배추51
279812022광주광역시논봄무0
168572013울산광역시밭가을배추144
8852000충청남도밭양파231
연도시도재배지구분채소구분재배면적
79202006대전광역시논참외0
231202018울산광역시논대파5.74
258452020강원도논배추계66.2917
249242019전라남도밭겨울배추3263.0797
282542022세종특별자치시밭겨울배추<NA>
256352020울산광역시논파5.704
244322019세종특별자치시논총각무0
70722005충청북도밭호박449
91692007광주광역시밭마늘30
39412003대구광역시논배추계54