Overview

Dataset statistics

Number of variables7
Number of observations154
Missing cells7
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory56.9 B

Variable types

Text5
DateTime2

Dataset

Description식품위생법 제47조(위생등급), 식품위생법 시행규칙 제61조(우수업소·모범업소 지정 등)에 따른 전주시 내 모범음식점 현황을 제공합니다
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=3079790

Alerts

데이터기준일자 has constant value ""Constant
소재지전화번호 has 7 (4.5%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 23:49:01.521401
Analysis finished2024-03-13 23:49:02.046043
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct154
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T08:49:02.176367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.987013
Min length2

Characters and Unicode

Total characters922
Distinct characters262
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

Unique154 ?
Unique (%)100.0%

Sample

1st row수라간
2nd row천하장사
3rd row만석군
4th row풀꽃세상채식뷔페
5th row모악칡냉면
ValueCountFrequency (%)
수라간 1
 
0.6%
정가네양평해장국아중점 1
 
0.6%
팔미가 1
 
0.6%
참예우한우명품관 1
 
0.6%
정가네양평해장국아중2호점 1
 
0.6%
돔베초밥 1
 
0.6%
라라코스트(삼천점 1
 
0.6%
착한밥상 1
 
0.6%
십장생오리아중점 1
 
0.6%
한가정 1
 
0.6%
Other values (147) 147
93.6%
2024-03-14T08:49:02.463207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
5.0%
22
 
2.4%
18
 
2.0%
17
 
1.8%
16
 
1.7%
15
 
1.6%
14
 
1.5%
14
 
1.5%
13
 
1.4%
12
 
1.3%
Other values (252) 735
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
96.3%
Open Punctuation 11
 
1.2%
Close Punctuation 11
 
1.2%
Decimal Number 8
 
0.9%
Space Separator 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
46
 
5.2%
22
 
2.5%
18
 
2.0%
17
 
1.9%
16
 
1.8%
15
 
1.7%
14
 
1.6%
14
 
1.6%
13
 
1.5%
12
 
1.4%
Other values (244) 701
78.9%
Decimal Number
ValueCountFrequency (%)
0 3
37.5%
9 2
25.0%
2 2
25.0%
6 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
96.3%
Common 34
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
46
 
5.2%
22
 
2.5%
18
 
2.0%
17
 
1.9%
16
 
1.8%
15
 
1.7%
14
 
1.6%
14
 
1.6%
13
 
1.5%
12
 
1.4%
Other values (244) 701
78.9%
Common
ValueCountFrequency (%)
( 11
32.4%
) 11
32.4%
0 3
 
8.8%
3
 
8.8%
9 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
? 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
96.3%
ASCII 34
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
46
 
5.2%
22
 
2.5%
18
 
2.0%
17
 
1.9%
16
 
1.8%
15
 
1.7%
14
 
1.6%
14
 
1.6%
13
 
1.5%
12
 
1.4%
Other values (244) 701
78.9%
ASCII
ValueCountFrequency (%)
( 11
32.4%
) 11
32.4%
0 3
 
8.8%
3
 
8.8%
9 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
? 1
 
2.9%
Distinct151
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T08:49:02.754484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.2662338
Min length2

Characters and Unicode

Total characters503
Distinct characters124
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

Unique148 ?
Unique (%)96.1%

Sample

1st row조석창
2nd row백은영
3rd row이준행
4th row허인교
5th row권옥자
ValueCountFrequency (%)
대표이사 4
 
2.5%
이사 2
 
1.2%
류신철 2
 
1.2%
최정희 2
 
1.2%
김영희 2
 
1.2%
손춘식 1
 
0.6%
정슬의 1
 
0.6%
박은아 1
 
0.6%
전대군 1
 
0.6%
김혁정 1
 
0.6%
Other values (145) 145
89.5%
2024-03-14T08:49:03.176008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
5.6%
27
 
5.4%
27
 
5.4%
16
 
3.2%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
9
 
1.8%
Other values (114) 339
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
98.4%
Space Separator 8
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
5.7%
27
 
5.5%
27
 
5.5%
16
 
3.2%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
9
 
1.8%
Other values (113) 331
66.9%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 495
98.4%
Common 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
5.7%
27
 
5.5%
27
 
5.5%
16
 
3.2%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
9
 
1.8%
Other values (113) 331
66.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
98.4%
ASCII 8
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
28
 
5.7%
27
 
5.5%
27
 
5.5%
16
 
3.2%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
9
 
1.8%
Other values (113) 331
66.9%
ASCII
ValueCountFrequency (%)
8
100.0%
Distinct153
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T08:49:03.540995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length47
Mean length30.24026
Min length20

Characters and Unicode

Total characters4657
Distinct characters154
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)98.7%

Sample

1st row전라북도 전주시 완산구 세내로 505 (효자동3가)
2nd row전라북도 전주시 덕진구 온고을로 546-1 (여의동)
3rd row전라북도 전주시 덕진구 기린대로 718-3 (팔복동1가)
4th row전라북도 전주시 완산구 우림로 1036-13 (중인동)
5th row전라북도 전주시 완산구 삼천동1가 625-2
ValueCountFrequency (%)
전라북도 154
 
15.8%
전주시 154
 
15.8%
덕진구 78
 
8.0%
완산구 76
 
7.8%
1층 14
 
1.4%
인후동1가 13
 
1.3%
송천동2가 12
 
1.2%
중화산동2가 12
 
1.2%
효자동3가 12
 
1.2%
백제대로 9
 
0.9%
Other values (281) 440
45.2%
2024-03-14T08:49:04.018413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/