Overview

Dataset statistics

Number of variables7
Number of observations7280
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory426.7 KiB
Average record size in memory60.0 B

Variable types

Numeric4
Categorical2
Text1

Dataset

Description친환경인증 농산물에 대한 2016년 이후 시도별 인증 통계 정보(연도별, 시도별, 시군구별, 구분(건수, 농가수, 면적, 출하량), 계, 유기농산물, 무농약농산물)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20230808000000002385

Alerts

계 is highly overall correlated with 유기농산물 and 1 other fieldsHigh correlation
유기농산물 is highly overall correlated with 계 and 1 other fieldsHigh correlation
무농약농산물 is highly overall correlated with 계 and 1 other fieldsHigh correlation
계 has 1108 (15.2%) zerosZeros
유기농산물 has 2318 (31.8%) zerosZeros
무농약농산물 has 1165 (16.0%) zerosZeros

Reproduction

Analysis started2023-12-11 03:06:18.738869
Analysis finished2023-12-11 03:06:21.939229
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.9665
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.1 KiB
2023-12-11T12:06:21.989395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2019
Q32021
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.011774
Coefficient of variation (CV)0.00099643756
Kurtosis-1.2641355
Mean2018.9665
Median Absolute Deviation (MAD)2
Skewness0.033728869
Sum14698076
Variance4.0472348
MonotonicityDecreasing
2023-12-11T12:06:22.118222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2018 1068
14.7%
2017 1068
14.7%
2016 1068
14.7%
2022 1044
14.3%
2021 1044
14.3%
2019 1044
14.3%
2020 944
13.0%
ValueCountFrequency (%)
2016 1068
14.7%
2017 1068
14.7%
2018 1068
14.7%
2019 1044
14.3%
2020 944
13.0%
2021 1044
14.3%
2022 1044
14.3%
ValueCountFrequency (%)
2022 1044
14.3%
2021 1044
14.3%
2020 944
13.0%
2019 1044
14.3%
2018 1068
14.7%
2017 1068
14.7%
2016 1068
14.7%

시도별
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.0 KiB
경기
1320 
경북
696 
서울
684 
경남
648 
전남
616 
Other values (12)
3316 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 1320
18.1%
경북 696
9.6%
서울 684
9.4%
경남 648
8.9%
전남 616
8.5%
강원 504
 
6.9%
충남 472
 
6.5%
전북 468
 
6.4%
부산 428
 
5.9%
충북 416
 
5.7%
Other values (7) 1028
14.1%

Length

2023-12-11T12:06:22.256430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 1320
18.1%
경북 696
9.6%
서울 684
9.4%
경남 648
8.9%
전남 616
8.5%
강원 504
 
6.9%
충남 472
 
6.5%
전북 468
 
6.4%
부산 428
 
5.9%
충북 416
 
5.7%
Other values (7) 1028
14.1%

시군구별
Text

Distinct246
Distinct (%)3.4%
Missing4
Missing (%)0.1%
Memory size57.0 KiB
2023-12-11T12:06:22.682412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4881803
Min length2

Characters and Unicode

Total characters25380
Distinct characters156
Distinct categories4 ?
Distinct scripts3 ?
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 row횡성군
2nd row횡성군
3rd row횡성군
4th row횡성군
5th row양양군
ValueCountFrequency (%)
중구 160
 
2.0%
창원시 160
 
2.0%
동구 156
 
1.9%
남구 144
 
1.8%
북구 140
 
1.7%
서구 136
 
1.7%
수원시 136
 
1.7%
청주시 136
 
1.7%
성남시 108
 
1.3%
고양시 108
 
1.3%
Other values (234) 6784
83.1%
2023-12-11T12:06:23.404288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 3072
 
12.1%
구 2952
 
11.6%
군 2380
 
9.4%
892
 
3.5%
주 732
 
2.9%
천 680
 
2.7%
양 676
 
2.7%
산 676
 
2.7%
성 608
 
2.4%
동 552
 
2.2%
Other values (146) 12160
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24468
96.4%
Space Separator 892
 
3.5%
Uppercase Letter 12
 
< 0.1%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3072
 
12.6%
구 2952
 
12.1%
군 2380
 
9.7%
주 732
 
3.0%
천 680
 
2.8%
양 676
 
2.8%
산 676
 
2.8%
성 608
 
2.5%
동 552
 
2.3%
원 548
 
2.2%
Other values (140) 11592
47.4%
Uppercase Letter
ValueCountFrequency (%)
R 4
33.3%
E 4
33.3%
F 4
33.3%
Other Punctuation
ValueCountFrequency (%)
# 4
50.0%
! 4
50.0%
Space Separator
ValueCountFrequency (%)
892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24468
96.4%
Common 900
 
3.5%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3072
 
12.6%
구 2952
 
12.1%
군 2380
 
9.7%
주 732
 
3.0%
천 680
 
2.8%
양 676
 
2.8%
산 676
 
2.8%
성 608
 
2.5%
동 552
 
2.3%
원 548
 
2.2%
Other values (140) 11592
47.4%
Common
ValueCountFrequency (%)
892
99.1%
# 4
 
0.4%
! 4
 
0.4%
Latin
ValueCountFrequency (%)
R 4
33.3%
E 4
33.3%
F 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24468
96.4%
ASCII 912
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 3072
 
12.6%
구 2952
 
12.1%
군 2380
 
9.7%
주 732
 
3.0%
천 680
 
2.8%
양 676
 
2.8%
산 676
 
2.8%
성 608
 
2.5%
동 552
 
2.3%
원 548
 
2.2%
Other values (140) 11592
47.4%
ASCII
ValueCountFrequency (%)
892
97.8%
# 4
 
0.4%
R 4
 
0.4%
E 4
 
0.4%
F 4
 
0.4%
! 4
 
0.4%

구분(건수, 농가수, 면적, 출하량)
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.0 KiB
건수(건)
1820 
농가수(호)
1820 
면적(ha)
1820 
출하량(톤)
1820 

Length

Max length6
Median length6
Mean length5.75
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건수(건)
2nd row농가수(호)
3rd row면적(ha)
4th row출하량(톤)
5th row건수(건)

Common Values

ValueCountFrequency (%)
건수(건) 1820
25.0%
농가수(호) 1820
25.0%
면적(ha) 1820
25.0%
출하량(톤) 1820
25.0%

Length

2023-12-11T12:06:23.558326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:06:23.660980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건수(건 1820
25.0%
농가수(호 1820
25.0%
면적(ha 1820
25.0%
출하량(톤 1820
25.0%

계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3105
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean632.43776
Minimum0
Maximum63823
Zeros1108
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size64.1 KiB
2023-12-11T12:06:23.775754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median83
Q3366
95-th percentile3347.25
Maximum63823
Range63823
Interquartile range (IQR)363.5

Descriptive statistics

Standard deviation1968.3908
Coefficient of variation (CV)3.1123866
Kurtosis206.696
Mean632.43776
Median Absolute Deviation (MAD)83
Skewness10.25167
Sum4604146.9
Variance3874562.4
MonotonicityNot monotonic
2023-12-11T12:06:23.904474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1108
 
15.2%
1.0 283
 
3.9%
2.0 180
 
2.5%
3.0 103
 
1.4%
4.0 91
 
1.2%
5.0 65
 
0.9%
8.0 41
 
0.6%
6.0 40
 
0.5%
7.0 37
 
0.5%
15.0 35
 
0.5%
Other values (3095) 5297
72.8%
ValueCountFrequency (%)
0.0 1108
15.2%
0.01 20
 
0.3%
0.02 8
 
0.1%
0.03 3
 
< 0.1%
0.04 5
 
0.1%
0.05 2
 
< 0.1%
0.06 1
 
< 0.1%
0.09 1
 
< 0.1%
0.1 4
 
0.1%
0.12 1
 
< 0.1%
ValueCountFrequency (%)
63823.0 1
< 0.1%
43637.6 1
< 0.1%
24682.0 1
< 0.1%
23376.36 1
< 0.1%
20775.08 1
< 0.1%
20489.0 1
< 0.1%
20146.0 1
< 0.1%
19371.55 1
< 0.1%
18868.07 1
< 0.1%
18808.99 1
< 0.1%

유기농산물
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2257
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.69644
Minimum0
Maximum19195.03
Zeros2318
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size64.1 KiB
2023-12-11T12:06:24.032581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10.835
Q384
95-th percentile893.3425
Maximum19195.03
Range19195.03
Interquartile range (IQR)84

Descriptive statistics

Standard deviation619.67944
Coefficient of variation (CV)3.5070284
Kurtosis179.71645
Mean176.69644
Median Absolute Deviation (MAD)10.835
Skewness10.105977
Sum1286350.1
Variance384002.61
MonotonicityNot monotonic
2023-12-11T12:06:24.171941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2318
31.8%
1.0 327
 
4.5%
2.0 190
 
2.6%
3.0 114
 
1.6%
5.0 77
 
1.1%
4.0 68
 
0.9%
12.0 59
 
0.8%
15.0 57
 
0.8%
11.0 54
 
0.7%
13.0 47
 
0.6%
Other values (2247) 3969
54.5%
ValueCountFrequency (%)
0.0 2318
31.8%
0.02 1
 
< 0.1%
0.03 1
 
< 0.1%
0.05 2
 
< 0.1%
0.08 1
 
< 0.1%
0.1 5
 
0.1%
0.11 1
 
< 0.1%
0.12 2
 
< 0.1%
0.13 2
 
< 0.1%
0.15 4
 
0.1%
ValueCountFrequency (%)
19195.03 1
< 0.1%
9704.73 1
< 0.1%
9043.89 1
< 0.1%
8159.15 1
< 0.1%
7968.0 1
< 0.1%
7911.42 1
< 0.1%
7892.75 1
< 0.1%
7793.18 1
< 0.1%
7779.16 1
< 0.1%
7179.13 1
< 0.1%

무농약농산물
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2903
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455.74128
Minimum0
Maximum63806
Zeros1165
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size64.1 KiB
2023-12-11T12:06:24.294023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median63.265
Q3241.0525
95-th percentile2306.34
Maximum63806
Range63806
Interquartile range (IQR)239.0525

Descriptive statistics

Standard deviation1631.392
Coefficient of variation (CV)3.5796451
Kurtosis412.01055
Mean455.74128
Median Absolute Deviation (MAD)63.265
Skewness14.747629
Sum3317796.5
Variance2661440
MonotonicityNot monotonic
2023-12-11T12:06:24.401406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1165
 
16.0%
1.0 308
 
4.2%
2.0 201
 
2.8%
3.0 91
 
1.2%
5.0 69
 
0.9%
4.0 68
 
0.9%
6.0 42
 
0.6%
8.0 38
 
0.5%
13.0 36
 
0.5%
15.0 36
 
0.5%
Other values (2893) 5226
71.8%
ValueCountFrequency (%)
0.0 1165
16.0%
0.01 20
 
0.3%
0.02 7
 
0.1%
0.03 2
 
< 0.1%
0.04 5
 
0.1%
0.05 2
 
< 0.1%
0.06 1
 
< 0.1%
0.09 1
 
< 0.1%
0.1 5
 
0.1%
0.12 4
 
0.1%
ValueCountFrequency (%)
63806.0 1
< 0.1%
43331.21 1
< 0.1%
24363.0 1
< 0.1%
20722.21 1
< 0.1%
20215.1 1
< 0.1%
20111.0 1
< 0.1%
18666.77 1
< 0.1%
17014.4 1
< 0.1%
16952.51 1
< 0.1%
15745.42 1
< 0.1%

Interactions

2023-12-11T12:06:21.151924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:19.489279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.053369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.614765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:21.276159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:19.647622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.194098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.721330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:21.421352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:19.767812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.336344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.862334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:21.544728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:19.903095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:20.476011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:06:21.018983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:06:24.482058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별시도별구분(건수, 농가수, 면적, 출하량)계유기농산물무농약농산물
연도별1.0000.0000.0000.0000.0050.000
시도별0.0001.0000.0000.1980.2890.135
구분(건수, 농가수, 면적, 출하량)0.0000.0001.0000.1900.1630.152
계0.0000.1980.1901.0000.5270.991
유기농산물0.0050.2890.1630.5271.0000.263
무농약농산물0.0000.1350.1520.9910.2631.000
2023-12-11T12:06:24.864874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(건수, 농가수, 면적, 출하량)시도별
구분(건수, 농가수, 면적, 출하량)1.0000.000
시도별0.0001.000
2023-12-11T12:06:24.944932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별계유기농산물무농약농산물시도별구분(건수, 농가수, 면적, 출하량)
연도별1.0000.0220.0560.0020.0000.000
계0.0221.0000.9170.9890.0940.123
유기농산물0.0560.9171.0000.8740.1340.112
무농약농산물0.0020.9890.8741.0000.0640.099
시도별0.0000.0940.1340.0641.0000.000
구분(건수, 농가수, 면적, 출하량)0.0000.1230.1120.0990.0001.000

Missing values

2023-12-11T12:06:21.744917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:06:21.886776image/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

연도별시도별시군구별구분(건수, 농가수, 면적, 출하량)계유기농산물무농약농산물
02022강원횡성군건수(건)131.071.060.0
12022강원횡성군농가수(호)131.071.060.0
22022강원횡성군면적(ha)201.96121.9680.0
32022강원횡성군출하량(톤)1752.71366.49386.21
42022강원양양군건수(건)71.015.056.0
52022강원양양군농가수(호)71.015.056.0
62022강원양양군면적(ha)52.7310.8741.86
72022강원양양군출하량(톤)240.825.74215.06
82022강원동해시건수(건)28.04.024.0
92022강원동해시농가수(호)56.04.052.0
연도별시도별시군구별구분(건수, 농가수, 면적, 출하량)계유기농산물무농약농산물
72702016충북충주시면적(ha)439.0158.0281.0
72712016충북충주시출하량(톤)3987.01208.02779.0
72722016충북청주시 상당구건수(건)82.019.063.0
72732016충북청주시 상당구농가수(호)204.047.0157.0
72742016충북청주시 상당구면적(ha)180.032.0148.0
72752016충북청주시 상당구출하량(톤)1486.0292.01194.0
72762016충북괴산군건수(건)171.044.0127.0
72772016충북괴산군농가수(호)457.0193.0264.0
72782016충북괴산군면적(ha)419.0176.0243.0
72792016충북괴산군출하량(톤)8808.01525.07283.0