Overview

Dataset statistics

Number of variables5
Number of observations83
Missing cells6
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory41.5 B

Variable types

Text4
DateTime1

Dataset

Description전북특별자치도 전통식품 명인 현황 데이터입니다. 지정번호, 성명, 보유기능, 지정일, 소재지 등의 정보를 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081477/fileData.do

Alerts

지정일 has 6 (7.2%) missing valuesMissing
지정번호 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:55:30.272292
Analysis finished2024-03-15 01:55:31.738656
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-03-15T10:55:32.483464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0963855
Min length3

Characters and Unicode

Total characters340
Distinct characters17
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

Unique83 ?
Unique (%)100.0%

Sample

1st row제1호
2nd row제2호
3rd row제6호
4th row제7호
5th row제9호
ValueCountFrequency (%)
수산 6
 
6.7%
제1호 2
 
2.2%
제2호 2
 
2.2%
제6호 2
 
2.2%
제52호 1
 
1.1%
제61호 1
 
1.1%
제68호 1
 
1.1%
제67호 1
 
1.1%
제66호 1
 
1.1%
제65호 1
 
1.1%
Other values (71) 71
79.8%
2024-03-15T10:55:33.795116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 83
24.4%
호 83
24.4%
2 20
 
5.9%
4 19
 
5.6%
1 18
 
5.3%
7 18
 
5.3%
6 18
 
5.3%
5 17
 
5.0%
3 16
 
4.7%
8 12
 
3.5%
Other values (7) 36
10.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
52.6%
Decimal Number 154
45.3%
Space Separator 6
 
1.8%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 20
13.0%
4 19
12.3%
1 18
11.7%
7 18
11.7%
6 18
11.7%
5 17
11.0%
3 16
10.4%
8 12
7.8%
0 8
 
5.2%
9 8
 
5.2%
Other Letter
ValueCountFrequency (%)
제 83
46.4%
호 83
46.4%
수 6
 
3.4%
산 6
 
3.4%
가 1
 
0.6%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
52.6%
Common 161
47.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 20
12.4%
4 19
11.8%
1 18
11.2%
7 18
11.2%
6 18
11.2%
5 17
10.6%
3 16
9.9%
8 12
7.5%
0 8
 
5.0%
9 8
 
5.0%
Other values (2) 7
 
4.3%
Hangul
ValueCountFrequency (%)
제 83
46.4%
호 83
46.4%
수 6
 
3.4%
산 6
 
3.4%
가 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
52.6%
ASCII 161
47.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 83
46.4%
호 83
46.4%
수 6
 
3.4%
산 6
 
3.4%
가 1
 
0.6%
ASCII
ValueCountFrequency (%)
2 20
12.4%
4 19
11.8%
1 18
11.2%
7 18
11.2%
6 18
11.2%
5 17
10.6%
3 16
9.9%
8 12
7.5%
0 8
 
5.0%
9 8
 
5.0%
Other values (2) 7
 
4.3%

성 명
Text

Distinct76
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-03-15T10:55:34.673826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters249
Distinct characters67
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

Unique71 ?
Unique (%)85.5%

Sample

1st row조*귀
2nd row김*수
3rd row박*서
4th row이*춘
5th row조*형
ValueCountFrequency (%)
김*자 4
 
4.8%
김*세 2
 
2.4%
이*자 2
 
2.4%
김*숙 2
 
2.4%
임*순 2
 
2.4%
안*자 1
 
1.2%
백*자 1
 
1.2%
강*옥 1
 
1.2%
김*근 1
 
1.2%
서*례 1
 
1.2%
Other values (66) 66
79.5%
2024-03-15T10:55:36.163177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 83
33.3%
김 18
 
7.2%
자 13
 
5.2%
숙 8
 
3.2%
임 7
 
2.8%
이 6
 
2.4%
박 5
 
2.0%
유 5
 
2.0%
수 5
 
2.0%
순 5
 
2.0%
Other values (57) 94
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
66.7%
Other Punctuation 83
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 18
 
10.8%
자 13
 
7.8%
숙 8
 
4.8%
임 7
 
4.2%
이 6
 
3.6%
박 5
 
3.0%
유 5
 
3.0%
수 5
 
3.0%
순 5
 
3.0%
근 4
 
2.4%
Other values (56) 90
54.2%
Other Punctuation
ValueCountFrequency (%)
* 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
66.7%
Common 83
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 18
 
10.8%
자 13
 
7.8%
숙 8
 
4.8%
임 7
 
4.2%
이 6
 
3.6%
박 5
 
3.0%
유 5
 
3.0%
수 5
 
3.0%
순 5
 
3.0%
근 4
 
2.4%
Other values (56) 90
54.2%
Common
ValueCountFrequency (%)
* 83
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
66.7%
ASCII 83
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 83
100.0%
Hangul
ValueCountFrequency (%)
김 18
 
10.8%
자 13
 
7.8%
숙 8
 
4.8%
임 7
 
4.2%
이 6
 
3.6%
박 5
 
3.0%
유 5
 
3.0%
수 5
 
3.0%
순 5
 
3.0%
근 4
 
2.4%
Other values (56) 90
54.2%

보유기능
Text

Distinct78
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-03-15T10:55:37.423855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.9277108
Min length6

Characters and Unicode

Total characters658
Distinct characters140
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)88.0%

Sample

1st row주류(송화백일주)
2nd row주류(금산인삼주)
3rd row주류(안동소주)
4th row주류(문배주)
5th row주류(전주이강주)
ValueCountFrequency (%)
엿류(쌀엿 2
 
2.2%
식품(죽염 2
 
2.2%
식품(포기김치 2
 
2.2%
식품(유과 2
 
2.2%
주류(안동소주 2
 
2.2%
식품(진주비빔밥 1
 
1.1%
장류(순창고추장 1
 
1.1%
식품류(도토리묵 1
 
1.1%
장류(청국장 1
 
1.1%
주류(병영소주 1
 
1.1%
Other values (74) 74
83.1%
2024-03-15T10:55:39.052092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 83
 
12.6%
) 83
 
12.6%
주 50
 
7.6%
식 45
 
6.8%
품 42
 
6.4%
류 41
 
6.2%
장 19
 
2.9%
엿 9
 
1.4%
과 9
 
1.4%
차 8
 
1.2%
Other values (130) 269
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
72.8%
Open Punctuation 83
 
12.6%
Close Punctuation 83
 
12.6%
Space Separator 7
 
1.1%
Other Punctuation 5
 
0.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 50
 
10.4%
식 45
 
9.4%
품 42
 
8.8%
류 41
 
8.6%
장 19
 
4.0%
엿 9
 
1.9%
과 9
 
1.9%
차 8
 
1.7%
김 7
 
1.5%
초 7
 
1.5%
Other values (125) 242
50.5%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
72.8%
Common 179
 
27.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 50
 
10.4%
식 45
 
9.4%
품 42
 
8.8%
류 41
 
8.6%
장 19
 
4.0%
엿 9
 
1.9%
과 9
 
1.9%
차 8
 
1.7%
김 7
 
1.5%
초 7
 
1.5%
Other values (125) 242
50.5%
Common
ValueCountFrequency (%)
( 83
46.4%
) 83
46.4%
7
 
3.9%
, 5
 
2.8%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
72.8%
ASCII 179
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 83
46.4%
) 83
46.4%
7
 
3.9%
, 5
 
2.8%
- 1
 
0.6%
Hangul
ValueCountFrequency (%)
주 50
 
10.4%
식 45
 
9.4%
품 42
 
8.8%
류 41
 
8.6%
장 19
 
4.0%
엿 9
 
1.9%
과 9
 
1.9%
차 8
 
1.7%
김 7
 
1.5%
초 7
 
1.5%
Other values (125) 242
50.5%

지정일
Date

MISSING 

Distinct29
Distinct (%)37.7%
Missing6
Missing (%)7.2%
Memory size792.0 B
Minimum1994-08-06 00:00:00
Maximum2018-11-30 00:00:00
2024-03-15T10:55:39.430248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:55:39.827506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

소재지
Text

Distinct61
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-03-15T10:55:40.700805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0361446
Min length3

Characters and Unicode

Total characters418
Distinct characters64
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

Unique47 ?
Unique (%)56.6%

Sample

1st row전북 완주
2nd row충남 금산
3rd row경북 안동
4th row경기 김포
5th row전북 전주
ValueCountFrequency (%)
전남 17
 
10.4%
경기 12
 
7.3%
충남 10
 
6.1%
전북 10
 
6.1%
경남 9
 
5.5%
경북 9
 
5.5%
담양 6
 
3.7%
하동 4
 
2.4%
강원 4
 
2.4%
광주 3
 
1.8%
Other values (62) 80
48.8%
2024-03-15T10:55:41.986726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
19.6%
남 40
 
9.6%
경 31
 
7.4%
전 29
 
6.9%
북 22
 
5.3%
주 20
 
4.8%
충 14
 
3.3%
양 13
 
3.1%
기 13
 
3.1%
천 10
 
2.4%
Other values (54) 144
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
80.4%
Space Separator 82
 
19.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 40
 
11.9%
경 31
 
9.2%
전 29
 
8.6%
북 22
 
6.5%
주 20
 
6.0%
충 14
 
4.2%
양 13
 
3.9%
기 13
 
3.9%
천 10
 
3.0%
동 9
 
2.7%
Other values (53) 135
40.2%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
80.4%
Common 82
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 40
 
11.9%
경 31
 
9.2%
전 29
 
8.6%
북 22
 
6.5%
주 20
 
6.0%
충 14
 
4.2%
양 13
 
3.9%
기 13
 
3.9%
천 10
 
3.0%
동 9
 
2.7%
Other values (53) 135
40.2%
Common
ValueCountFrequency (%)
82
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 336
80.4%
ASCII 82
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
100.0%
Hangul
ValueCountFrequency (%)
남 40
 
11.9%
경 31
 
9.2%
전 29
 
8.6%
북 22
 
6.5%
주 20
 
6.0%
충 14
 
4.2%
양 13
 
3.9%
기 13
 
3.9%
천 10
 
3.0%
동 9
 
2.7%
Other values (53) 135
40.2%

Correlations

2024-03-15T10:55:42.248073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호성 명보유기능지정일소재지
지정번호1.0001.0001.0001.0001.000
성 명1.0001.0000.9730.0000.000
보유기능1.0000.9731.0000.9710.983
지정일1.0000.0000.9711.0000.000
소재지1.0000.0000.9830.0001.000

Missing values

2024-03-15T10:55:31.278277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:55:31.619811image/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

지정번호성 명보유기능지정일소재지
0제1호조*귀주류(송화백일주)1994-08-06전북 완주
1제2호김*수주류(금산인삼주)<NA>충남 금산
2제6호박*서주류(안동소주)1995-07-15경북 안동
3제7호이*춘주류(문배주)<NA>경기 김포
4제9호조*형주류(전주이강주)1996-04-04전북 전주
5제10호유*자주류(옥로주)<NA>경기 용인
6제11호임*순주류(구기자주)<NA>충남 청양
7제12호최*근주류(계명주)<NA>경기남양주
8제13호남*란주류(가야곡왕주)1997-12-15충남 논산
9제14호홍*리식품(매실농축액)<NA>전남 광양
지정번호성 명보유기능지정일소재지
73제81호구*숙떡류(기정떡)2018-11-30전남 화순
74제82호박*완육류(가리구이)2018-11-30전남 담양
75제83호최*자엿류(쌀엿)2018-11-30경북 울진
76제84호김*숙주류(고소리술)2018-11-30제주 서귀포
77수산 제1호김*자식품(어란)1999-11-27제주도
78수산 제2호이*자식품(제주옥돔)2012-05-21전남 영암
79수산 제3호정*현식품(죽염)2015-09-23전북 부안
80수산 제4호김*세식품(죽염)2016-12-01경남 함양
81수산 제5호김*배식품(새우젓)2016-12-01충남 아산
82수산 제6호유*근식품(어리굴젓)2016-12-01충남 서산