Overview

Dataset statistics

Number of variables6
Number of observations103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory49.3 B

Variable types

Text5
DateTime1

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 07:28:09.255570
Analysis finished2024-03-23 07:28:12.793443
Duration3.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:13.345088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0582524
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

Unique103 ?
Unique (%)100.0%

Sample

1st row제1호
2nd row제2호
3rd row제3호
4th row제5호
5th row제6호
ValueCountFrequency (%)
제1호 1
 
1.0%
제89호 1
 
1.0%
제86호 1
 
1.0%
제85호 1
 
1.0%
제84호 1
 
1.0%
제83호 1
 
1.0%
제82호 1
 
1.0%
제81호 1
 
1.0%
제80호 1
 
1.0%
제79호 1
 
1.0%
Other values (93) 93
90.3%
2024-03-23T07:28:14.404239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 103
24.6%
호 103
24.6%
1 39
 
9.3%
8 21
 
5.0%
6 21
 
5.0%
9 21
 
5.0%
0 21
 
5.0%
2 20
 
4.8%
7 20
 
4.8%
3 19
 
4.5%
Other values (2) 30
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
50.7%
Other Letter 206
49.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39
18.4%
8 21
9.9%
6 21
9.9%
9 21
9.9%
0 21
9.9%
2 20
9.4%
7 20
9.4%
3 19
9.0%
5 16
7.5%
4 14
 
6.6%
Other Letter
ValueCountFrequency (%)
제 103
50.0%
호 103
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 212
50.7%
Hangul 206
49.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 39
18.4%
8 21
9.9%
6 21
9.9%
9 21
9.9%
0 21
9.9%
2 20
9.4%
7 20
9.4%
3 19
9.0%
5 16
7.5%
4 14
 
6.6%
Hangul
ValueCountFrequency (%)
제 103
50.0%
호 103
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212
50.7%
Hangul 206
49.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 103
50.0%
호 103
50.0%
ASCII
ValueCountFrequency (%)
1 39
18.4%
8 21
9.9%
6 21
9.9%
9 21
9.9%
0 21
9.9%
2 20
9.4%
7 20
9.4%
3 19
9.0%
5 16
7.5%
4 14
 
6.6%

등록명칭
Text

UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:14.947211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.815534
Min length3

Characters and Unicode

Total characters496
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

Unique103 ?
Unique (%)100.0%

Sample

1st row보성녹차
2nd row하동녹차
3rd row고창복분자주
4th row영양고춧가루
5th row의성마늘
ValueCountFrequency (%)
보성녹차 1
 
0.9%
김천포도 1
 
0.9%
부산대저토마토 1
 
0.9%
거문도쑥 1
 
0.9%
진도검정쌀 1
 
0.9%
한우 1
 
0.9%
고흥 1
 
0.9%
창녕마늘 1
 
0.9%
나주배 1
 
0.9%
영광한우 1
 
0.9%
Other values (97) 97
90.7%
2024-03-23T07:28:15.928331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 30
 
6.0%
산 15
 
3.0%
영 12
 
2.4%
주 12
 
2.4%
쌀 12
 
2.4%
성 11
 
2.2%
수 11
 
2.2%
삼 11
 
2.2%
한 10
 
2.0%
려 10
 
2.0%
Other values (151) 362
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 488
98.4%
Space Separator 4
 
0.8%
Other Punctuation 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 30
 
6.1%
산 15
 
3.1%
영 12
 
2.5%
주 12
 
2.5%
쌀 12
 
2.5%
성 11
 
2.3%
수 11
 
2.3%
삼 11
 
2.3%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 354
72.5%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 488
98.4%
Common 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 30
 
6.1%
산 15
 
3.1%
영 12
 
2.5%
주 12
 
2.5%
쌀 12
 
2.5%
성 11
 
2.3%
수 11
 
2.3%
삼 11
 
2.3%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 354
72.5%
Common
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
( 1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 488
98.4%
ASCII 8
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 30
 
6.1%
산 15
 
3.1%
영 12
 
2.5%
주 12
 
2.5%
쌀 12
 
2.5%
성 11
 
2.3%
수 11
 
2.3%
삼 11
 
2.3%
한 10
 
2.0%
려 10
 
2.0%
Other values (147) 354
72.5%
ASCII
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
( 1
 
12.5%
) 1
 
12.5%

등록일자
Date

Distinct73
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
Minimum2002-01-25 00:00:00
Maximum2024-01-23 00:00:00
2024-03-23T07:28:16.326031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:28:16.656978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대상지역
Text

Distinct74
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:17.202282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length39
Mean length15.68932
Min length2

Characters and Unicode

Total characters1616
Distinct characters105
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)56.3%

Sample

1st row행정구역상 전라남도 보성군 일원
2nd row행정구역상 경상남도 하동군 일원
3rd row행정구역상 전라북도 고창군 일원
4th row행정구역상 경상북도 영양군 일원
5th row행정구역상 경상북도 의성군 일원
ValueCountFrequency (%)
일원 85
21.9%
행정구역상 76
19.5%
전라남도 29
 
7.5%
강원도 12
 
3.1%
경상북도 10
 
2.6%
경상남도 8
 
2.1%
국내 8
 
2.1%
충청남도 7
 
1.8%
전라북도 7
 
1.8%
충청북도 6
 
1.5%
Other values (103) 141
36.2%
2024-03-23T07:28:18.072879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
286
17.7%
원 99
 
6.1%
상 96
 
5.9%
도 94
 
5.8%
역 86
 
5.3%
일 86
 
5.3%
정 79
 
4.9%
구 78
 
4.8%
행 76
 
4.7%
군 68
 
4.2%
Other values (95) 568
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1308
80.9%
Space Separator 286
 
17.7%
Other Punctuation 16
 
1.0%
Decimal Number 3
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 99
 
7.6%
상 96
 
7.3%
도 94
 
7.2%
역 86
 
6.6%
일 86
 
6.6%
정 79
 
6.0%
구 78
 
6.0%
행 76
 
5.8%
군 68
 
5.2%
남 50
 
3.8%
Other values (88) 496
37.9%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
286
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1308
80.9%
Common 307
 
19.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 99
 
7.6%
상 96
 
7.3%
도 94
 
7.2%
역 86
 
6.6%
일 86
 
6.6%
정 79
 
6.0%
구 78
 
6.0%
행 76
 
5.8%
군 68
 
5.2%
남 50
 
3.8%
Other values (88) 496
37.9%
Common
ValueCountFrequency (%)
286
93.2%
, 16
 
5.2%
0 2
 
0.7%
) 1
 
0.3%
( 1
 
0.3%
4 1
 
0.3%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1308
80.9%
ASCII 308
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
286
92.9%
, 16
 
5.2%
0 2
 
0.6%
) 1
 
0.3%
( 1
 
0.3%
4 1
 
0.3%
m 1
 
0.3%
Hangul
ValueCountFrequency (%)
원 99
 
7.6%
상 96
 
7.3%
도 94
 
7.2%
역 86
 
6.6%
일 86
 
6.6%
정 79
 
6.0%
구 78
 
6.0%
행 76
 
5.8%
군 68
 
5.2%
남 50
 
3.8%
Other values (88) 496
37.9%

생산계획량
Text

Distinct102
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:18.732674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.7864078
Min length1

Characters and Unicode

Total characters493
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

Unique101 ?
Unique (%)98.1%

Sample

1st row10톤
2nd row6톤
3rd row2톤
4th row395톤
5th row10340톤
ValueCountFrequency (%)
2378톤 2
 
1.9%
6780.5톤 1
 
1.0%
9195톤 1
 
1.0%
387톤 1
 
1.0%
7081톤 1
 
1.0%
1240톤 1
 
1.0%
31524톤 1
 
1.0%
7070톤 1
 
1.0%
503톤 1
 
1.0%
21370톤 1
 
1.0%
Other values (92) 92
89.3%
2024-03-23T07:28:19.816983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
톤 103
20.9%
1 56
11.4%
0 55
11.2%
2 47
9.5%
3 44
8.9%
6 34
 
6.9%
5 32
 
6.5%
4 32
 
6.5%
8 30
 
6.1%
9 29
 
5.9%
Other values (2) 31
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 387
78.5%
Other Letter 103
 
20.9%
Other Punctuation 3
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 56
14.5%
0 55
14.2%
2 47
12.1%
3 44
11.4%
6 34
8.8%
5 32
8.3%
4 32
8.3%
8 30
7.8%
9 29
7.5%
7 28
7.2%
Other Letter
ValueCountFrequency (%)
톤 103
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 390
79.1%
Hangul 103
 
20.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 56
14.4%
0 55
14.1%
2 47
12.1%
3 44
11.3%
6 34
8.7%
5 32
8.2%
4 32
8.2%
8 30
7.7%
9 29
7.4%
7 28
7.2%
Hangul
ValueCountFrequency (%)
톤 103
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 390
79.1%
Hangul 103
 
20.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
톤 103
100.0%
ASCII
ValueCountFrequency (%)
1 56
14.4%
0 55
14.1%
2 47
12.1%
3 44
11.3%
6 34
8.7%
5 32
8.2%
4 32
8.2%
8 30
7.7%
9 29
7.4%
7 28
7.2%

구성현황
Text

Distinct93
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:20.247840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length12.68932
Min length7

Characters and Unicode

Total characters1307
Distinct characters193
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

Unique88 ?
Unique (%)85.4%

Sample

1st row영농조합법인 보성녹차연합회
2nd row하동차영농조합법인
3rd row고창으뜸복분자주 영농조합법인
4th row영양고추영농조합법인
5th row의성마늘생산자단체협의회영농조합법인
ValueCountFrequency (%)
사단법인 15
 
11.2%
영농조합법인 11
 
8.2%
사)고려인삼연합회 7
 
5.2%
영월고추영농조합법인 2
 
1.5%
동고령농업협동조합 2
 
1.5%
안성시농특산물생산자연합회 2
 
1.5%
영광고추산업연합회 2
 
1.5%
금산깻잎영농조합법인 1
 
0.7%
괴산대학찰옥수수영농조합법인 1
 
0.7%
고흥한우명품화사업단 1
 
0.7%
Other values (90) 90
67.2%
2024-03-23T07:28:20.901573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
합 89
 
6.8%
인 82
 
6.3%
법 72
 
5.5%
영 65
 
5.0%
조 64
 
4.9%
농 62
 
4.7%
회 53
 
4.1%
사 51
 
3.9%
산 50
 
3.8%
31
 
2.4%
Other values (183) 688
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1234
94.4%
Space Separator 31
 
2.4%
Close Punctuation 21
 
1.6%
Open Punctuation 21
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
합 89
 
7.2%
인 82
 
6.6%
법 72
 
5.8%
영 65
 
5.3%
조 64
 
5.2%
농 62
 
5.0%
회 53
 
4.3%
사 51
 
4.1%
산 50
 
4.1%
자 31
 
2.5%
Other values (180) 615
49.8%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1234
94.4%
Common 73
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
합 89
 
7.2%
인 82
 
6.6%
법 72
 
5.8%
영 65
 
5.3%
조 64
 
5.2%
농 62
 
5.0%
회 53
 
4.3%
사 51
 
4.1%
산 50
 
4.1%
자 31
 
2.5%
Other values (180) 615
49.8%
Common
ValueCountFrequency (%)
31
42.5%
) 21
28.8%
( 21
28.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1234
94.4%
ASCII 73
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
합 89
 
7.2%
인 82
 
6.6%
법 72
 
5.8%
영 65
 
5.3%
조 64
 
5.2%
농 62
 
5.0%
회 53
 
4.3%
사 51
 
4.1%
산 50
 
4.1%
자 31
 
2.5%
Other values (180) 615
49.8%
ASCII
ValueCountFrequency (%)
31
42.5%
) 21
28.8%
( 21
28.8%

Correlations

2024-03-23T07:28:21.148300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일자대상지역구성현황
등록일자1.0000.9740.996
대상지역0.9741.0001.000
구성현황0.9961.0001.000

Missing values

2024-03-23T07:28:12.253077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:28:12.684313image/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
0제1호보성녹차2002-01-25행정구역상 전라남도 보성군 일원10톤영농조합법인 보성녹차연합회
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2제3호고창복분자주2004-01-15행정구역상 전라북도 고창군 일원2톤고창으뜸복분자주 영농조합법인
3제5호영양고춧가루2005-03-05행정구역상 경상북도 영양군 일원395톤영양고추영농조합법인
4제6호의성마늘2005-07-18행정구역상 경상북도 의성군 일원10340톤의성마늘생산자단체협의회영농조합법인
5제7호괴산고추2005-08-25행정구역상 충청북도 괴산군 일원1482톤괴산고추영농조합법인
6제8호순창전통고추장2005-10-14행정구역상 전라북도 순창군 일원60톤영농조합법인순창전통고추장연합회
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8제10호성주참외2005-12-01행정구역상 경상북도 성주군 일원65969톤성주참외생산자단체협의회영농조합법인
9제11호해남겨울배추2005-12-26행정구역상 전라남도 해남군 일원68393톤해남겨울배추협의회영농조합법인
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98제109호양구시래기2024-01-23양구군 일대518톤양구시래기생산자연합회영농조합법인
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101제112호곡성멜론2022-11-07전라남도 곡성군 전역3024톤농업회사법인 곡성멜론주식회사
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