Overview

Dataset statistics

Number of variables6
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory49.6 B

Variable types

Text5
Categorical1

Dataset

Description(2022년6월기준) 우수한 우리 식품의 계승발전을 위해 지정한 식품제조, 가공, 조리 등의 분야의 식품명인 현황
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220216000000002028

Alerts

대한민국식품명인 현황('22년 6월 기준, 79명) has unique valuesUnique
Unnamed: 1 has unique valuesUnique
Unnamed: 2 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:12:26.036991
Analysis finished2023-12-11 03:12:26.756523
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대한민국식품명인 현황('22년 6월 기준, 79명)
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-11T12:12:26.953519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8941176
Min length1

Characters and Unicode

Total characters161
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

Unique85 ?
Unique (%)100.0%

Sample

1st row연번
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
연번 1
 
1.2%
44 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T12:12:27.411085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 19
11.8%
1 19
11.8%
2 19
11.8%
3 19
11.8%
5 18
11.2%
6 18
11.2%
7 18
11.2%
8 13
8.1%
9 8
5.0%
0 8
5.0%
Other values (2) 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 159
98.8%
Other Letter 2
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 19
11.9%
1 19
11.9%
2 19
11.9%
3 19
11.9%
5 18
11.3%
6 18
11.3%
7 18
11.3%
8 13
8.2%
9 8
5.0%
0 8
5.0%
Other Letter
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159
98.8%
Hangul 2
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
4 19
11.9%
1 19
11.9%
2 19
11.9%
3 19
11.9%
5 18
11.3%
6 18
11.3%
7 18
11.3%
8 13
8.2%
9 8
5.0%
0 8
5.0%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 159
98.8%
Hangul 2
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 19
11.9%
1 19
11.9%
2 19
11.9%
3 19
11.9%
5 18
11.3%
6 18
11.3%
7 18
11.3%
8 13
8.2%
9 8
5.0%
0 8
5.0%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Unnamed: 1
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-11T12:12:27.727544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4
Min length3

Characters and Unicode

Total characters340
Distinct characters17
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

Unique85 ?
Unique (%)100.0%

Sample

1st row지정번호
2nd row제1호
3rd row제2호
4th row제6호
5th row제7호
ValueCountFrequency (%)
지정번호 1
 
1.2%
제52호 1
 
1.2%
제71호 1
 
1.2%
제70호 1
 
1.2%
제69호 1
 
1.2%
제68호 1
 
1.2%
제67호 1
 
1.2%
제66호 1
 
1.2%
제65호 1
 
1.2%
제64호 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T12:12:28.248814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 85
25.0%
제 84
24.7%
6 19
 
5.6%
2 19
 
5.6%
7 19
 
5.6%
8 18
 
5.3%
4 18
 
5.3%
1 18
 
5.3%
3 16
 
4.7%
5 15
 
4.4%
Other values (7) 29
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
51.5%
Decimal Number 162
47.6%
Dash Punctuation 3
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 19
11.7%
2 19
11.7%
7 19
11.7%
8 18
11.1%
4 18
11.1%
1 18
11.1%
3 16
9.9%
5 15
9.3%
9 11
6.8%
0 9
5.6%
Other Letter
ValueCountFrequency (%)
호 85
48.6%
제 84
48.0%
가 3
 
1.7%
정 1
 
0.6%
번 1
 
0.6%
지 1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
51.5%
Common 165
48.5%

Most frequent character per script

Common
ValueCountFrequency (%)
6 19
11.5%
2 19
11.5%
7 19
11.5%
8 18
10.9%
4 18
10.9%
1 18
10.9%
3 16
9.7%
5 15
9.1%
9 11
6.7%
0 9
5.5%
Hangul
ValueCountFrequency (%)
호 85
48.6%
제 84
48.0%
가 3
 
1.7%
정 1
 
0.6%
번 1
 
0.6%
지 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
51.5%
ASCII 165
48.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 85
48.6%
제 84
48.0%
가 3
 
1.7%
정 1
 
0.6%
번 1
 
0.6%
지 1
 
0.6%
ASCII
ValueCountFrequency (%)
6 19
11.5%
2 19
11.5%
7 19
11.5%
8 18
10.9%
4 18
10.9%
1 18
10.9%
3 16
9.7%
5 15
9.1%
9 11
6.7%
0 9
5.5%

Unnamed: 2
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-11T12:12:28.589908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9882353
Min length2

Characters and Unicode

Total characters254
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st row성명
2nd row조영귀
3rd row김창수
4th row박재서
5th row이기춘
ValueCountFrequency (%)
성명 1
 
1.2%
이연순 1
 
1.2%
정영석 1
 
1.2%
김명자 1
 
1.2%
김택상 1
 
1.2%
강경순 1
 
1.2%
정승환 1
 
1.2%
윤미월 1
 
1.2%
백정자 1
 
1.2%
강순옥 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T12:12:29.023032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 17
 
6.7%
순 13
 
5.1%
자 12
 
4.7%
정 9
 
3.5%
숙 9
 
3.5%
임 8
 
3.1%
박 7
 
2.8%
영 7
 
2.8%
수 7
 
2.8%
이 6
 
2.4%
Other values (89) 159
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 17
 
6.7%
순 13
 
5.1%
자 12
 
4.7%
정 9
 
3.5%
숙 9
 
3.5%
임 8
 
3.1%
박 7
 
2.8%
영 7
 
2.8%
수 7
 
2.8%
이 6
 
2.4%
Other values (89) 159
62.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 17
 
6.7%
순 13
 
5.1%
자 12
 
4.7%
정 9
 
3.5%
숙 9
 
3.5%
임 8
 
3.1%
박 7
 
2.8%
영 7
 
2.8%
수 7
 
2.8%
이 6
 
2.4%
Other values (89) 159
62.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 17
 
6.7%
순 13
 
5.1%
자 12
 
4.7%
정 9
 
3.5%
숙 9
 
3.5%
임 8
 
3.1%
박 7
 
2.8%
영 7
 
2.8%
수 7
 
2.8%
이 6
 
2.4%
Other values (89) 159
62.6%

Unnamed: 3
Text

Distinct81
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-11T12:12:29.293958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.8823529
Min length3

Characters and Unicode

Total characters670
Distinct characters141
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)90.6%

Sample

1st row지정품목
2nd row주류(송화백일주)
3rd row주류(금산인삼주)
4th row주류(안동소주)
5th row주류(문배주)
ValueCountFrequency (%)
식품(유과 3
 
3.5%
식품(쌀엿 2
 
2.3%
주류(안동소주 2
 
2.3%
장류(순창고추장 2
 
2.3%
지정품목 1
 
1.2%
주류(오메기술 1
 
1.2%
장류(죽염된장 1
 
1.2%
김치류(배추통김치 1
 
1.2%
장류(즙장 1
 
1.2%
식품류(도토리묵 1
 
1.2%
Other values (71) 71
82.6%
2023-12-11T12:12:30.083404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 81
 
12.1%
) 81
 
12.1%
주 53
 
7.9%
식 47
 
7.0%
품 43
 
6.4%
류 41
 
6.1%
장 19
 
2.8%
차 9
 
1.3%
과 9
 
1.3%
초 9
 
1.3%
Other values (131) 278
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 499
74.5%
Open Punctuation 81
 
12.1%
Close Punctuation 81
 
12.1%
Other Punctuation 7
 
1.0%
Dash Punctuation 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 53
 
10.6%
식 47
 
9.4%
품 43
 
8.6%
류 41
 
8.2%
장 19
 
3.8%
차 9
 
1.8%
과 9
 
1.8%
초 9
 
1.8%
리 9
 
1.8%
엿 8
 
1.6%
Other values (124) 252
50.5%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
/ 2
28.6%
․ 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 499
74.5%
Common 171
 
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 53
 
10.6%
식 47
 
9.4%
품 43
 
8.6%
류 41
 
8.2%
장 19
 
3.8%
차 9
 
1.8%
과 9
 
1.8%
초 9
 
1.8%
리 9
 
1.8%
엿 8
 
1.6%
Other values (124) 252
50.5%
Common
ValueCountFrequency (%)
( 81
47.4%
) 81
47.4%
, 4
 
2.3%
/ 2
 
1.2%
- 1
 
0.6%
1
 
0.6%
․ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 499
74.5%
ASCII 170
 
25.4%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 81
47.6%
) 81
47.6%
, 4
 
2.4%
/ 2
 
1.2%
- 1
 
0.6%
1
 
0.6%
Hangul
ValueCountFrequency (%)
주 53
 
10.6%
식 47
 
9.4%
품 43
 
8.6%
류 41
 
8.2%
장 19
 
3.8%
차 9
 
1.8%
과 9
 
1.8%
초 9
 
1.8%
리 9
 
1.8%
엿 8
 
1.6%
Other values (124) 252
50.5%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%

Unnamed: 4
Categorical

Distinct30
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size812.0 B
'18. 11. 30
9 
`16. 12. 8
7 
‘15. 09. 23
7 
‘13. 12. 03
7 
‘12. 10. 09
6 
Other values (25)
49 

Length

Max length11
Median length11
Mean length10.752941
Min length3

Unique

Unique10 ?
Unique (%)11.8%

Sample

1st row지정일
2nd row’94. 08. 06
3rd row’94. 08. 06
4th row’95. 07. 15
5th row’95. 07. 15

Common Values

ValueCountFrequency (%)
'18. 11. 30 9
 
10.6%
`16. 12. 8 7
 
8.2%
‘15. 09. 23 7
 
8.2%
‘13. 12. 03 7
 
8.2%
‘12. 10. 09 6
 
7.1%
‘14. 12. 23 5
 
5.9%
’96. 04. 04 4
 
4.7%
’21. 12. 7 3
 
3.5%
‘20. 12. 14 3
 
3.5%
'19. 12. 5 3
 
3.5%
Other values (20) 31
36.5%

Length

2023-12-11T12:12:30.258375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12 36
 
14.2%
04 16
 
6.3%
09 16
 
6.3%
23 12
 
4.7%
18 10
 
4.0%
03 10
 
4.0%
30 9
 
3.6%
11 9
 
3.6%
‘12 8
 
3.2%
05 7
 
2.8%
Other values (35) 120
47.4%

Unnamed: 5
Text

Distinct56
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-11T12:12:30.537892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0588235
Min length3

Characters and Unicode

Total characters430
Distinct characters66
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

Unique38 ?
Unique (%)44.7%

Sample

1st row소재지
2nd row전북 전주
3rd row충남 금산
4th row경북 안동
5th row경기 김포
ValueCountFrequency (%)
전남 17
 
10.1%
경기 16
 
9.5%
전북 10
 
5.9%
경남 9
 
5.3%
경북 9
 
5.3%
충남 8
 
4.7%
담양 6
 
3.6%
하동 5
 
3.0%
충북 4
 
2.4%
강원 4
 
2.4%
Other values (57) 81
47.9%
2023-12-11T12:12:30.936879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
19.5%
남 39
 
9.1%
경 34
 
7.9%
전 30
 
7.0%
북 23
 
5.3%
주 20
 
4.7%
기 16
 
3.7%
천 13
 
3.0%
양 13
 
3.0%
충 13
 
3.0%
Other values (56) 145
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 346
80.5%
Space Separator 84
 
19.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 39
 
11.3%
경 34
 
9.8%
전 30
 
8.7%
북 23
 
6.6%
주 20
 
5.8%
기 16
 
4.6%
천 13
 
3.8%
양 13
 
3.8%
충 13
 
3.8%
동 11
 
3.2%
Other values (55) 134
38.7%
Space Separator
ValueCountFrequency (%)
84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
80.5%
Common 84
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 39
 
11.3%
경 34
 
9.8%
전 30
 
8.7%
북 23
 
6.6%
주 20
 
5.8%
기 16
 
4.6%
천 13
 
3.8%
양 13
 
3.8%
충 13
 
3.8%
동 11
 
3.2%
Other values (55) 134
38.7%
Common
ValueCountFrequency (%)
84
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 346
80.5%
ASCII 84
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
100.0%
Hangul
ValueCountFrequency (%)
남 39
 
11.3%
경 34
 
9.8%
전 30
 
8.7%
북 23
 
6.6%
주 20
 
5.8%
기 16
 
4.6%
천 13
 
3.8%
양 13
 
3.8%
충 13
 
3.8%
동 11
 
3.2%
Other values (55) 134
38.7%

Correlations

2023-12-11T12:12:31.103134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대한민국식품명인 현황('22년 6월 기준, 79명)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
대한민국식품명인 현황('22년 6월 기준, 79명)1.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0000.9920.996
Unnamed: 41.0001.0001.0000.9921.0000.000
Unnamed: 51.0001.0001.0000.9960.0001.000

Missing values

2023-12-11T12:12:26.607062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:12:26.713650image/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

대한민국식품명인 현황('22년 6월 기준, 79명)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0연번지정번호성명지정품목지정일소재지
11제1호조영귀주류(송화백일주)’94. 08. 06전북 전주
22제2호김창수주류(금산인삼주)’94. 08. 06충남 금산
33제6호박재서주류(안동소주)’95. 07. 15경북 안동
44제7호이기춘주류(문배주)’95. 07. 15경기 김포
55제9호조정형주류(전주이강주)’96. 04. 04전북 전주
66제10호유민자주류(옥로주)’96. 04. 04경기 용인
77제11호임영순주류(구기자주)’96. 04. 04충남 청양
88제12호최옥근주류(계명주)’96. 04. 04경기 남양주
99제13호남상란주류(가야곡왕주)’97. 12. 15충남 논산
대한민국식품명인 현황('22년 6월 기준, 79명)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
7575제84호김희숙주류(고소리술)'18. 11. 30제주 서귀포
7676제85호김순옥엿류(찹쌀조이당조청)'19. 12. 5전남 순천
7777제86호임경만식초류(보리식초)'19. 12. 5경북 영천
7878제36-가호조정현장류(순창고추장)'19. 12. 5전북 순창
7979제87호송성자식품(가리적)‘20. 12. 14경기 동두천
8080제88호박준미주류(청주신선주)‘20. 12. 14충북 청주
8181제20-가호김연박주류(안동소주)‘20. 12. 14경북 안동
8282제89호김외순가리구이’21. 12. 7경기 수원
8383제90호고화순고사리나물’21. 12. 7경기 남양주
8484제91호황인수작설차’21. 12. 7경남 하동