Overview

Dataset statistics

Number of variables6
Number of observations104
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory50.3 B

Variable types

Text5
Numeric1

Dataset

Description지리적표시관리 인증, 심사 등의 업무 관리(등록번호, 등록명칭, 등록일자, 대상지역, 생산계획량, 구성현황 등)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001691

Alerts

등록번호 has unique valuesUnique
등록명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:27:16.706295
Analysis finished2024-03-23 07:27:18.788721
Duration2.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-03-23T07:27:19.200761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0192308
Min length3

Characters and Unicode

Total characters418
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)100.0%

Sample

1st row제109호
2nd row제107호
3rd row제108호
4th row제106호
5th row제105호
ValueCountFrequency (%)
제109호 1
 
1.0%
제107호 1
 
1.0%
제32호 1
 
1.0%
제37호 1
 
1.0%
제36호 1
 
1.0%
제35호 1
 
1.0%
제34호 1
 
1.0%
제38호 1
 
1.0%
제41호 1
 
1.0%
제40호 1
 
1.0%
Other values (94) 94
90.4%
2024-03-23T07:27:20.270672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 104
24.9%
호 104
24.9%
1 31
 
7.4%
9 21
 
5.0%
7 21
 
5.0%
8 21
 
5.0%
6 21
 
5.0%
0 20
 
4.8%
5 20
 
4.8%
2 19
 
4.5%
Other values (2) 36
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
50.2%
Other Letter 208
49.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31
14.8%
9 21
10.0%
7 21
10.0%
8 21
10.0%
6 21
10.0%
0 20
9.5%
5 20
9.5%
2 19
9.0%
3 19
9.0%
4 17
8.1%
Other Letter
ValueCountFrequency (%)
제 104
50.0%
호 104
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 210
50.2%
Hangul 208
49.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 31
14.8%
9 21
10.0%
7 21
10.0%
8 21
10.0%
6 21
10.0%
0 20
9.5%
5 20
9.5%
2 19
9.0%
3 19
9.0%
4 17
8.1%
Hangul
ValueCountFrequency (%)
제 104
50.0%
호 104
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 210
50.2%
Hangul 208
49.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 104
50.0%
호 104
50.0%
ASCII
ValueCountFrequency (%)
1 31
14.8%
9 21
10.0%
7 21
10.0%
8 21
10.0%
6 21
10.0%
0 20
9.5%
5 20
9.5%
2 19
9.0%
3 19
9.0%
4 17
8.1%

등록명칭
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-03-23T07:27:20.842696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.8173077
Min length3

Characters and Unicode

Total characters501
Distinct characters161
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)100.0%

Sample

1st row양구시래기
2nd row부안오디
3rd row곡성토란
4th row태안달래
5th row기장쪽파
ValueCountFrequency (%)
양구시래기 1
 
0.9%
무안양파 1
 
0.9%
삼척마늘 1
 
0.9%
여주쌀 1
 
0.9%
정선찰옥수수 1
 
0.9%
광양매실 1
 
0.9%
고창복분자 1
 
0.9%
청송사과 1
 
0.9%
진부당귀 1
 
0.9%
청양고춧가루 1
 
0.9%
Other values (98) 98
90.7%
2024-03-23T07:27:21.852811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 31
 
6.2%
산 14
 
2.8%
영 13
 
2.6%
주 12
 
2.4%
쌀 12
 
2.4%
삼 11
 
2.2%
수 11
 
2.2%
양 10
 
2.0%
한 10
 
2.0%
려 10
 
2.0%
Other values (151) 367
73.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
98.4%
Space Separator 4
 
0.8%
Other Punctuation 2
 
0.4%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 31
 
6.3%
산 14
 
2.8%
영 13
 
2.6%
주 12
 
2.4%
쌀 12
 
2.4%
삼 11
 
2.2%
수 11
 
2.2%
양 10
 
2.0%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 359
72.8%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
98.4%
Common 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 31
 
6.3%
산 14
 
2.8%
영 13
 
2.6%
주 12
 
2.4%
쌀 12
 
2.4%
삼 11
 
2.2%
수 11
 
2.2%
양 10
 
2.0%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 359
72.8%
Common
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
) 1
 
12.5%
( 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
98.4%
ASCII 8
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 31
 
6.3%
산 14
 
2.8%
영 13
 
2.6%
주 12
 
2.4%
쌀 12
 
2.4%
삼 11
 
2.2%
수 11
 
2.2%
양 10
 
2.0%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 359
72.8%
ASCII
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
) 1
 
12.5%
( 1
 
12.5%

등록일자
Real number (ℝ)

Distinct71
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20099162
Minimum20020125
Maximum20200226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:27:22.288029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020125
5-th percentile20050853
Q120070678
median20091217
Q320123245
95-th percentile20169028
Maximum20200226
Range180101
Interquartile range (IQR)52567

Descriptive statistics

Standard deviation38593.905
Coefficient of variation (CV)0.0019201748
Kurtosis-0.23171584
Mean20099162
Median Absolute Deviation (MAD)25091
Skewness0.57809309
Sum2.0903128 × 109
Variance1.4894895 × 109
MonotonicityDecreasing
2024-03-23T07:27:22.907472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131210 4
 
3.8%
20070827 4
 
3.8%
20100325 4
 
3.8%
20150330 3
 
2.9%
20061207 3
 
2.9%
20101108 3
 
2.9%
20071220 3
 
2.9%
20081016 2
 
1.9%
20150708 2
 
1.9%
20100712 2
 
1.9%
Other values (61) 74
71.2%
ValueCountFrequency (%)
20020125 1
1.0%
20030502 1
1.0%
20040115 1
1.0%
20050305 1
1.0%
20050718 1
1.0%
20050825 1
1.0%
20051014 1
1.0%
20051201 1
1.0%
20051226 2
1.9%
20060508 1
1.0%
ValueCountFrequency (%)
20200226 1
 
1.0%
20190917 2
1.9%
20180528 1
 
1.0%
20180319 1
 
1.0%
20170511 1
 
1.0%
20160622 2
1.9%
20160218 1
 
1.0%
20160212 1
 
1.0%
20150708 2
1.9%
20150330 3
2.9%

대상지역
Text

Distinct73
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-03-23T07:27:23.425237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length17
Mean length16.201923
Min length2

Characters and Unicode

Total characters1685
Distinct characters104
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)53.8%

Sample

1st row강원도 양구군 일원
2nd row전라북도 부안군 일원
3rd row전라남도 곡성군 일원
4th row충청남도 태안군
5th row부산광역시 기장군
ValueCountFrequency (%)
일원 94
23.3%
행정구역상 85
21.0%
전라남도 27
 
6.7%
강원도 14
 
3.5%
경상북도 11
 
2.7%
경상남도 9
 
2.2%
충청남도 8
 
2.0%
국내 8
 
2.0%
전라북도 7
 
1.7%
충청북도 6
 
1.5%
Other values (100) 135
33.4%
2024-03-23T07:27:24.554578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300
17.8%
원 110
 
6.5%
상 107
 
6.4%
도 97
 
5.8%
일 94
 
5.6%
역 93
 
5.5%
정 88
 
5.2%
구 87
 
5.2%
행 85
 
5.0%
군 67
 
4.0%
Other values (94) 557
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1368
81.2%
Space Separator 300
 
17.8%
Other Punctuation 13
 
0.8%
Decimal Number 3
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 110
 
8.0%
상 107
 
7.8%
도 97
 
7.1%
일 94
 
6.9%
역 93
 
6.8%
정 88
 
6.4%
구 87
 
6.4%
행 85
 
6.2%
군 67
 
4.9%
남 48
 
3.5%
Other values (89) 492
36.0%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
300
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1368
81.2%
Common 316
 
18.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 110
 
8.0%
상 107
 
7.8%
도 97
 
7.1%
일 94
 
6.9%
역 93
 
6.8%
정 88
 
6.4%
구 87
 
6.4%
행 85
 
6.2%
군 67
 
4.9%
남 48
 
3.5%
Other values (89) 492
36.0%
Common
ValueCountFrequency (%)
300
94.9%
, 13
 
4.1%
0 2
 
0.6%
4 1
 
0.3%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1368
81.2%
ASCII 317
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
94.6%
, 13
 
4.1%
0 2
 
0.6%
m 1
 
0.3%
4 1
 
0.3%
Hangul
ValueCountFrequency (%)
원 110
 
8.0%
상 107
 
7.8%
도 97
 
7.1%
일 94
 
6.9%
역 93
 
6.8%
정 88
 
6.4%
구 87
 
6.4%
행 85
 
6.2%
군 67
 
4.9%
남 48
 
3.5%
Other values (89) 492
36.0%

생산계획량
Text

Distinct103
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-03-23T07:27:25.157666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.7692308
Min length1

Characters and Unicode

Total characters496
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)98.1%

Sample

1st row518톤
2nd row1030톤
3rd row1700톤
4th row264.76톤
5th row2800톤
ValueCountFrequency (%)
2378톤 2
 
1.9%
821톤 1
 
1.0%
28792톤 1
 
1.0%
18619톤 1
 
1.0%
4482톤 1
 
1.0%
2655톤 1
 
1.0%
15228톤 1
 
1.0%
373톤 1
 
1.0%
1242톤 1
 
1.0%
1151톤 1
 
1.0%
Other values (93) 93
89.4%
2024-03-23T07:27:25.882046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
톤 104
21.0%
1 57
11.5%
0 56
11.3%
2 45
9.1%
3 43
8.7%
5 34
 
6.9%
6 33
 
6.7%
4 31
 
6.2%
7 30
 
6.0%
9 30
 
6.0%
Other values (2) 33
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 388
78.2%
Other Letter 104
 
21.0%
Other Punctuation 4
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 57
14.7%
0 56
14.4%
2 45
11.6%
3 43
11.1%
5 34
8.8%
6 33
8.5%
4 31
8.0%
7 30
7.7%
9 30
7.7%
8 29
7.5%
Other Letter
ValueCountFrequency (%)
톤 104
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 392
79.0%
Hangul 104
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 57
14.5%
0 56
14.3%
2 45
11.5%
3 43
11.0%
5 34
8.7%
6 33
8.4%
4 31
7.9%
7 30
7.7%
9 30
7.7%
8 29
7.4%
Hangul
ValueCountFrequency (%)
톤 104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
79.0%
Hangul 104
 
21.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
톤 104
100.0%
ASCII
ValueCountFrequency (%)
1 57
14.5%
0 56
14.3%
2 45
11.5%
3 43
11.0%
5 34
8.7%
6 33
8.4%
4 31
7.9%
7 30
7.7%
9 30
7.7%
8 29
7.4%

구성현황
Text

Distinct95
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-03-23T07:27:26.307943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.480769
Min length7

Characters and Unicode

Total characters1298
Distinct characters191
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

Unique91 ?
Unique (%)87.5%

Sample

1st row양구시래기생산자연합회영농조합법인
2nd row부안뽕 영농조합법인
3rd row사단법인 곡성군토란생산자협의회
4th row태안달래영농조합법인
5th row기장쪽파영농조합법인
ValueCountFrequency (%)
사단법인 13
 
9.9%
영농조합법인 11
 
8.4%
사)고려인삼연합회 7
 
5.3%
영광고추산업연합회 2
 
1.5%
영월고추영농조합법인 2
 
1.5%
동고령농업협동조합 2
 
1.5%
영암무화과생산자단체영농조합법인 1
 
0.8%
한국인삼생산자협의회 1
 
0.8%
여주쌀생산자협의회 1
 
0.8%
정선찰옥수수영농조합법인 1
 
0.8%
Other values (90) 90
68.7%
2024-03-23T07:27:27.081693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
합 92
 
7.1%
인 82
 
6.3%
법 72
 
5.5%
영 69
 
5.3%
조 68
 
5.2%
농 64
 
4.9%
산 49
 
3.8%
회 48
 
3.7%
사 47
 
3.6%
자 31
 
2.4%
Other values (181) 676
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1229
94.7%
Space Separator 27
 
2.1%
Open Punctuation 21
 
1.6%
Close Punctuation 21
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
합 92
 
7.5%
인 82
 
6.7%
법 72
 
5.9%
영 69
 
5.6%
조 68
 
5.5%
농 64
 
5.2%
산 49
 
4.0%
회 48
 
3.9%
사 47
 
3.8%
자 31
 
2.5%
Other values (178) 607
49.4%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1229
94.7%
Common 69
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
합 92
 
7.5%
인 82
 
6.7%
법 72
 
5.9%
영 69
 
5.6%
조 68
 
5.5%
농 64
 
5.2%
산 49
 
4.0%
회 48
 
3.9%
사 47
 
3.8%
자 31
 
2.5%
Other values (178) 607
49.4%
Common
ValueCountFrequency (%)
27
39.1%
( 21
30.4%
) 21
30.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1229
94.7%
ASCII 69
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
합 92
 
7.5%
인 82
 
6.7%
법 72
 
5.9%
영 69
 
5.6%
조 68
 
5.5%
농 64
 
5.2%
산 49
 
4.0%
회 48
 
3.9%
사 47
 
3.8%
자 31
 
2.5%
Other values (178) 607
49.4%
ASCII
ValueCountFrequency (%)
27
39.1%
( 21
30.4%
) 21
30.4%

Interactions

2024-03-23T07:27:17.969484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:27:27.340678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일자대상지역구성현황
등록일자1.0000.8940.945
대상지역0.8941.0000.999
구성현황0.9450.9991.000

Missing values

2024-03-23T07:27:18.298789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:27:18.619461image/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

등록번호등록명칭등록일자대상지역생산계획량구성현황
0제109호양구시래기20200226강원도 양구군 일원518톤양구시래기생산자연합회영농조합법인
1제107호부안오디20190917전라북도 부안군 일원1030톤부안뽕 영농조합법인
2제108호곡성토란20190917전라남도 곡성군 일원1700톤사단법인 곡성군토란생산자협의회
3제106호태안달래20180528충청남도 태안군264.76톤태안달래영농조합법인
4제105호기장쪽파20180319부산광역시 기장군2800톤기장쪽파영농조합법인
5제104호영광모싯잎송편20170511전라남도 영광군 일원1566톤(사)영광에서모싯잎떡을만드는사람들
6제102호고려흑삼20160622국내19톤(사)고려인삼연합회
7제103호고려흑삼제품20160622국내13톤(사)고려인삼연합회
8제12호이천쌀20160218이천시 일원9톤이천쌀사랑영농조합법인
9제101호안성한우20160212안성시 일원1069톤안성축산업협동조합
등록번호등록명칭등록일자대상지역생산계획량구성현황
94제11호해남겨울배추20051226행정구역상 전라남도 해남군 일원68393톤해남겨울배추협의회영농조합법인
95제13호철원쌀20051226행정구역상 강원도 철원군 일원40620톤철원오대쌀생산자영농조합법인
96제10호성주참외20051201행정구역상 경상북도 성주군 일원65969톤성주참외생산자단체협의회영농조합법인
97제8호순창전통고추장20051014행정구역상 전라북도 순창군 일원60톤영농조합법인순창전통고추장연합회
98제7호괴산고추20050825행정구역상 충청북도 괴산군 일원1482톤괴산고추영농조합법인
99제6호의성마늘20050718행정구역상 경상북도 의성군 일원10340톤의성마늘생산자단체협의회영농조합법인
100제5호영양고춧가루20050305행정구역상 경상북도 영양군 일원395톤영양고추영농조합법인
101제3호고창복분자주20040115행정구역상 전라북도 고창군 일원2톤고창으뜸복분자주 영농조합법인
102제2호하동녹차20030502행정구역상 경상남도 하동군 일원6톤하동차영농조합법인
103제1호보성녹차20020125행정구역상 전라남도 보성군 일원10톤영농조합법인 보성녹차연합회