Overview

Dataset statistics

Number of variables7
Number of observations1685
Missing cells0
Missing cells (%)0.0%
Duplicate rows35
Duplicate rows (%)2.1%
Total size in memory93.9 KiB
Average record size in memory57.1 B

Variable types

Text1
Categorical3
Numeric1
DateTime1
Boolean1

Dataset

Description농업통계를 생산하는 농산물소득조사분석 시스템에서 작목별 통계입력 데이터를 마감 관리하는 정보로 작목별 입력 마감, 관리자 검토 , 마감 정보를 제공합니다.
Author농촌진흥청
URLhttps://www.data.go.kr/data/15072470/fileData.do

Alerts

Dataset has 35 (2.1%) duplicate rowsDuplicates
해당년도 is highly overall correlated with 관리자마감여부High correlation
작목통계유형코드 is highly overall correlated with 작목입력유형코드High correlation
작목입력유형코드 is highly overall correlated with 작목통계유형코드High correlation
관리자마감여부 is highly overall correlated with 해당년도High correlation

Reproduction

Analysis started2023-12-12 10:40:51.829667
Analysis finished2023-12-12 10:40:52.636955
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

작목코드
Text

Distinct222
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2023-12-12T19:40:52.867003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.3839763
Min length1

Characters and Unicode

Total characters7387
Distinct characters227
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 row시설양상추
2nd row시설청경채
3rd row시설취나물
4th row시설호박(반촉성)
5th row시설호박(억제)
ValueCountFrequency (%)
녹차(사용안함 15
 
0.9%
한라봉(사용안함 15
 
0.9%
망고(사용안함 14
 
0.8%
청견 14
 
0.8%
금감(사용안함 14
 
0.8%
머루(사용안함 14
 
0.8%
구마늘 8
 
0.5%
풋마늘 8
 
0.5%
월동배추 8
 
0.5%
노지오이 8
 
0.5%
Other values (212) 1567
93.0%
2023-12-12T19:40:53.310001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 418
 
5.7%
설 395
 
5.3%
( 361
 
4.9%
) 361
 
4.9%
지 201
 
2.7%
리 159
 
2.2%
추 155
 
2.1%
감 128
 
1.7%
노 118
 
1.6%
용 116
 
1.6%
Other values (217) 4975
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6649
90.0%
Open Punctuation 361
 
4.9%
Close Punctuation 361
 
4.9%
Decimal Number 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 418
 
6.3%
설 395
 
5.9%
지 201
 
3.0%
리 159
 
2.4%
추 155
 
2.3%
감 128
 
1.9%
노 118
 
1.8%
용 116
 
1.7%
자 115
 
1.7%
마 114
 
1.7%
Other values (213) 4730
71.1%
Decimal Number
ValueCountFrequency (%)
4 8
50.0%
6 8
50.0%
Open Punctuation
ValueCountFrequency (%)
( 361
100.0%
Close Punctuation
ValueCountFrequency (%)
) 361
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6649
90.0%
Common 738
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 418
 
6.3%
설 395
 
5.9%
지 201
 
3.0%
리 159
 
2.4%
추 155
 
2.3%
감 128
 
1.9%
노 118
 
1.8%
용 116
 
1.7%
자 115
 
1.7%
마 114
 
1.7%
Other values (213) 4730
71.1%
Common
ValueCountFrequency (%)
( 361
48.9%
) 361
48.9%
4 8
 
1.1%
6 8
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6649
90.0%
ASCII 738
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 418
 
6.3%
설 395
 
5.9%
지 201
 
3.0%
리 159
 
2.4%
추 155
 
2.3%
감 128
 
1.9%
노 118
 
1.8%
용 116
 
1.7%
자 115
 
1.7%
마 114
 
1.7%
Other values (213) 4730
71.1%
ASCII
ValueCountFrequency (%)
( 361
48.9%
) 361
48.9%
4 8
 
1.1%
6 8
 
1.1%

작목통계유형코드
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
노지채소
279 
식량작물
235 
시설과채류
231 
과수
222 
시설엽근채류
147 
Other values (7)
571 

Length

Max length6
Median length5
Mean length3.7537092
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시설엽근채류
2nd row시설엽근채류
3rd row시설엽근채류
4th row시설과채류
5th row시설과채류

Common Values

ValueCountFrequency (%)
노지채소 279
16.6%
식량작물 235
13.9%
시설과채류 231
13.7%
과수 222
13.2%
시설엽근채류 147
8.7%
약용작물 140
8.3%
화훼 124
7.4%
축산 91
 
5.4%
특용작물 80
 
4.7%
시설과수 78
 
4.6%
Other values (2) 58
 
3.4%

Length

2023-12-12T19:40:53.499696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노지채소 279
16.6%
식량작물 235
13.9%
시설과채류 231
13.7%
과수 222
13.2%
시설엽근채류 147
8.7%
약용작물 140
8.3%
화훼 124
7.4%
축산 91
 
5.4%
특용작물 80
 
4.7%
시설과수 78
 
4.6%
Other values (2) 58
 
3.4%

작목입력유형코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
일반작물
459 
시설채소
378 
노지채소
279 
과수
226 
화훼
124 
Other values (6)
219 

Length

Max length7
Median length4
Mean length3.5560831
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반작물 459
27.2%
시설채소 378
22.4%
노지채소 279
16.6%
과수 226
13.4%
화훼 124
 
7.4%
축산 91
 
5.4%
시설과수 70
 
4.2%
새송이팽이버섯 22
 
1.3%
느타리(균상) 16
 
0.9%
표고,영지버섯 12
 
0.7%

Length

2023-12-12T19:40:53.646420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반작물 459
27.2%
시설채소 378
22.4%
노지채소 279
16.6%
과수 226
13.4%
화훼 124
 
7.4%
축산 91
 
5.4%
시설과수 70
 
4.2%
새송이팽이버섯 22
 
1.3%
느타리(균상 16
 
0.9%
표고,영지버섯 12
 
0.7%

입력절기구분코드
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
하절기
828 
동.하절기
613 
동절기
244 

Length

Max length5
Median length3
Mean length3.7275964
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동.하절기
2nd row동.하절기
3rd row동.하절기
4th row동.하절기
5th row동.하절기

Common Values

ValueCountFrequency (%)
하절기 828
49.1%
동.하절기 613
36.4%
동절기 244
 
14.5%

Length

2023-12-12T19:40:54.120914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:54.252691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하절기 828
49.1%
동.하절기 613
36.4%
동절기 244
 
14.5%

해당년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.6955
Minimum2012
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-12T19:40:54.365597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014
median2016
Q32018
95-th percentile2019
Maximum2019
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.2735723
Coefficient of variation (CV)0.0011279344
Kurtosis-1.1445191
Mean2015.6955
Median Absolute Deviation (MAD)2
Skewness-0.14857077
Sum3396447
Variance5.169131
MonotonicityNot monotonic
2023-12-12T19:40:54.477618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2018 229
13.6%
2019 229
13.6%
2017 227
13.5%
2016 225
13.4%
2015 221
13.1%
2012 220
13.1%
2014 218
12.9%
2013 116
6.9%
ValueCountFrequency (%)
2012 220
13.1%
2013 116
6.9%
2014 218
12.9%
2015 221
13.1%
2016 225
13.4%
2017 227
13.5%
2018 229
13.6%
2019 229
13.6%
ValueCountFrequency (%)
2019 229
13.6%
2018 229
13.6%
2017 227
13.5%
2016 225
13.4%
2015 221
13.1%
2014 218
12.9%
2013 116
6.9%
2012 220
13.1%

입력마감일
Date

Distinct34
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
Minimum2014-06-15 00:00:00
Maximum2020-02-10 00:00:00
2023-12-12T19:40:54.600152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:40:54.754791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

관리자마감여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
False
1067 
True
618 
ValueCountFrequency (%)
False 1067
63.3%
True 618
36.7%
2023-12-12T19:40:54.898049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T19:40:52.256538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:40:54.973197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작목통계유형코드작목입력유형코드입력절기구분코드해당년도입력마감일관리자마감여부
작목통계유형코드1.0000.9760.7080.0000.6680.167
작목입력유형코드0.9761.0000.5740.0000.7270.133
입력절기구분코드0.7080.5741.0000.0610.3900.049
해당년도0.0000.0000.0611.0001.0000.698
입력마감일0.6680.7270.3901.0001.0000.854
관리자마감여부0.1670.1330.0490.6980.8541.000
2023-12-12T19:40:55.088458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작목입력유형코드작목통계유형코드관리자마감여부입력절기구분코드
작목입력유형코드1.0000.8850.1270.407
작목통계유형코드0.8851.0000.1290.427
관리자마감여부0.1270.1291.0000.081
입력절기구분코드0.4070.4270.0811.000
2023-12-12T19:40:55.196297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당년도작목통계유형코드작목입력유형코드입력절기구분코드관리자마감여부
해당년도1.0000.0000.0000.0290.700
작목통계유형코드0.0001.0000.8850.4270.129
작목입력유형코드0.0000.8851.0000.4070.127
입력절기구분코드0.0290.4270.4071.0000.081
관리자마감여부0.7000.1290.1270.0811.000

Missing values

2023-12-12T19:40:52.417176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:40:52.565533image/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

작목코드작목통계유형코드작목입력유형코드입력절기구분코드해당년도입력마감일관리자마감여부
0시설양상추시설엽근채류시설채소동.하절기20142015-06-30Y
1시설청경채시설엽근채류시설채소동.하절기20142015-06-30Y
2시설취나물시설엽근채류시설채소동.하절기20142015-06-30Y
3시설호박(반촉성)시설과채류시설채소동.하절기20142015-06-30Y
4시설호박(억제)시설과채류시설채소동.하절기20142015-06-30Y
5알로애시설엽근채류시설채소동.하절기20142015-06-30Y
6치커리시설엽근채류시설채소동.하절기20142015-06-30Y
7시설토마토(억제)시설과채류시설채소동.하절기20142015-06-30Y
8떫은감과수과수동.하절기20142015-06-30Y
9매실과수과수동.하절기20142015-06-30Y
작목코드작목통계유형코드작목입력유형코드입력절기구분코드해당년도입력마감일관리자마감여부
1675시설장미화훼화훼하절기20192019-12-31N
1676심비디움화훼화훼동.하절기20192019-12-31N
1677아이리스화훼화훼하절기20192019-12-31N
1678안개꽃화훼화훼하절기20192019-12-31N
1679알스트로메리아화훼화훼하절기20192019-12-31N
1680양란화훼화훼하절기20192019-12-31N
1681접목선인장화훼화훼동.하절기20192019-12-31N
1682카네이션화훼화훼하절기20192019-12-31N
1683칼라화훼화훼하절기20192019-12-31N
1684팔레높시스(호접란)화훼화훼동.하절기20192019-12-31N

Duplicate rows

Most frequently occurring

작목코드작목통계유형코드작목입력유형코드입력절기구분코드해당년도입력마감일관리자마감여부# duplicates
0금감(사용안함)과수과수하절기20122014-06-15Y2
1금감(사용안함)과수과수하절기20142015-06-30Y2
2금감(사용안함)과수과수하절기20152016-08-01N2
3금감(사용안함)과수과수하절기20162017-07-06N2
4금감(사용안함)과수과수하절기20182019-08-22N2
5금감(사용안함)과수과수하절기20192019-12-31N2
6녹차(사용안함)특용작물일반작물동절기20142015-06-30Y2
7녹차(사용안함)특용작물일반작물동절기20172018-07-22N2
8녹차(사용안함)특용작물일반작물동절기20192019-12-31N2
9망고(사용안함)과수과수하절기20122014-06-15Y2