Overview

Dataset statistics

Number of variables5
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory44.2 B

Variable types

Numeric2
Categorical1
Text2

Dataset

Description전북특별자치도 다중이용업 안전관리 우수업소(업종, 시설명, 위치 등)전북특별자치도 다중이용시설 안전관리 우수업소로 선정된 가게의 한국표준산업분류에 따른 영업의 종류
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081305/fileData.do

Alerts

순번 is highly overall correlated with 최초등록High correlation
최초등록 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:02:23.477797
Analysis finished2024-03-14 15:02:25.050848
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T00:02:25.187410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-03-15T00:02:25.499007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

최초등록
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5263
Minimum2013
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T00:02:25.846505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013.8
Q12016
median2018
Q32019
95-th percentile2020
Maximum2020
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1053101
Coefficient of variation (CV)0.0010435106
Kurtosis-0.59752032
Mean2017.5263
Median Absolute Deviation (MAD)2
Skewness-0.61524477
Sum114999
Variance4.4323308
MonotonicityIncreasing
2024-03-15T00:02:26.065512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020 12
21.1%
2019 11
19.3%
2018 9
15.8%
2017 8
14.0%
2016 7
12.3%
2014 4
 
7.0%
2013 3
 
5.3%
2015 3
 
5.3%
ValueCountFrequency (%)
2013 3
 
5.3%
2014 4
 
7.0%
2015 3
 
5.3%
2016 7
12.3%
2017 8
14.0%
2018 9
15.8%
2019 11
19.3%
2020 12
21.1%
ValueCountFrequency (%)
2020 12
21.1%
2019 11
19.3%
2018 9
15.8%
2017 8
14.0%
2016 7
12.3%
2015 3
 
5.3%
2014 4
 
7.0%
2013 3
 
5.3%

업종
Categorical

Distinct13
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
일반음식점
24 
휴게음식점
14 
영화상영관
4 
고시원
3 
유흥주점
 
2
Other values (8)
10 

Length

Max length13
Median length5
Mean length5.0175439
Min length2

Unique

Unique6 ?
Unique (%)10.5%

Sample

1st row유흥주점
2nd row학원
3rd row노래엽습장
4th row휴게음식점
5th row일반음식점

Common Values

ValueCountFrequency (%)
일반음식점 24
42.1%
휴게음식점 14
24.6%
영화상영관 4
 
7.0%
고시원 3
 
5.3%
유흥주점 2
 
3.5%
목욕장업 2
 
3.5%
스크린골프연습장 2
 
3.5%
학원 1
 
1.8%
노래엽습장 1
 
1.8%
산후조리원 1
 
1.8%
Other values (3) 3
 
5.3%

Length

2024-03-15T00:02:26.446635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 24
42.1%
휴게음식점 14
24.6%
영화상영관 4
 
7.0%
고시원 3
 
5.3%
유흥주점 2
 
3.5%
목욕장업 2
 
3.5%
스크린골프연습장 2
 
3.5%
학원 1
 
1.8%
노래엽습장 1
 
1.8%
산후조리원 1
 
1.8%
Other values (3) 3
 
5.3%

업소명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-03-15T00:02:27.334641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length7.7894737
Min length3

Characters and Unicode

Total characters444
Distinct characters195
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row부영음악광장
2nd row지평선학당
3rd row뮤직시티 노래연습장
4th row탐앤탐스 전주신시가지
5th row한스델리 김제점
ValueCountFrequency (%)
투썸플레이스 2
 
2.5%
김제점 2
 
2.5%
애슐리w 1
 
1.2%
공음청정한우 1
 
1.2%
로뎀나무고시원 1
 
1.2%
삼선가커피숍 1
 
1.2%
남원고시원 1
 
1.2%
칠보산오리 1
 
1.2%
익산점 1
 
1.2%
홈플러스 1
 
1.2%
Other values (69) 69
85.2%
2024-03-15T00:02:28.685495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
5.4%
스 22
 
5.0%
점 11
 
2.5%
산 10
 
2.3%
이 9
 
2.0%
고 8
 
1.8%
리 8
 
1.8%
원 8
 
1.8%
레 7
 
1.6%
제 7
 
1.6%
Other values (185) 330
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
90.3%
Space Separator 24
 
5.4%
Uppercase Letter 10
 
2.3%
Lowercase Letter 4
 
0.9%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 22
 
5.5%
점 11
 
2.7%
산 10
 
2.5%
이 9
 
2.2%
고 8
 
2.0%
리 8
 
2.0%
원 8
 
2.0%
레 7
 
1.7%
제 7
 
1.7%
가 7
 
1.7%
Other values (171) 304
75.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
V 1
10.0%
G 1
10.0%
D 1
10.0%
W 1
10.0%
T 1
10.0%
R 1
10.0%
H 1
10.0%
P 1
10.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 402
90.5%
Common 28
 
6.3%
Latin 14
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 22
 
5.5%
점 11
 
2.7%
산 10
 
2.5%
이 9
 
2.2%
고 8
 
2.0%
리 8
 
2.0%
원 8
 
2.0%
레 7
 
1.7%
제 7
 
1.7%
가 7
 
1.7%
Other values (172) 305
75.9%
Latin
ValueCountFrequency (%)
c 4
28.6%
C 2
14.3%
V 1
 
7.1%
G 1
 
7.1%
D 1
 
7.1%
W 1
 
7.1%
T 1
 
7.1%
R 1
 
7.1%
H 1
 
7.1%
P 1
 
7.1%
Common
ValueCountFrequency (%)
24
85.7%
( 2
 
7.1%
) 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 401
90.3%
ASCII 42
 
9.5%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
57.1%
c 4
 
9.5%
C 2
 
4.8%
( 2
 
4.8%
) 2
 
4.8%
V 1
 
2.4%
G 1
 
2.4%
D 1
 
2.4%
W 1
 
2.4%
T 1
 
2.4%
Other values (3) 3
 
7.1%
Hangul
ValueCountFrequency (%)
스 22
 
5.5%
점 11
 
2.7%
산 10
 
2.5%
이 9
 
2.2%
고 8
 
2.0%
리 8
 
2.0%
원 8
 
2.0%
레 7
 
1.7%
제 7
 
1.7%
가 7
 
1.7%
Other values (171) 304
75.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-03-15T00:02:30.056520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length14.245614
Min length10

Characters and Unicode

Total characters812
Distinct characters111
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

Unique55 ?
Unique (%)96.5%

Sample

1st row남원시 큰들길 23-9
2nd row김제시 도장로 74
3rd row부안군 변산면 변산해변로 51
4th row전주시 완산구 우전로 208
5th row김제시 동서로 183
ValueCountFrequency (%)
김제시 8
 
3.9%
전주시 8
 
3.9%
부안군 7
 
3.4%
고창군 7
 
3.4%
완산구 5
 
2.4%
남원시 5
 
2.4%
군산시 5
 
2.4%
고창읍 5
 
2.4%
익산시 5
 
2.4%
변산면 5
 
2.4%
Other values (126) 147
71.0%
2024-03-15T00:02:31.848855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
 
18.5%
1 43
 
5.3%
로 40
 
4.9%
시 33
 
4.1%
군 29
 
3.6%
산 26
 
3.2%
2 23
 
2.8%
3 20
 
2.5%
7 18
 
2.2%
5 17
 
2.1%
Other values (101) 413
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
59.0%
Decimal Number 174
 
21.4%
Space Separator 150
 
18.5%
Dash Punctuation 9
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 40
 
8.4%
시 33
 
6.9%
군 29
 
6.1%
산 26
 
5.4%
주 17
 
3.5%
면 16
 
3.3%
길 16
 
3.3%
읍 15
 
3.1%
고 14
 
2.9%
안 14
 
2.9%
Other values (89) 259
54.1%
Decimal Number
ValueCountFrequency (%)
1 43
24.7%
2 23
13.2%
3 20
11.5%
7 18
10.3%
5 17
 
9.8%
0 16
 
9.2%
4 15
 
8.6%
8 10
 
5.7%
6 8
 
4.6%
9 4
 
2.3%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
59.0%
Common 333
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 40
 
8.4%
시 33
 
6.9%
군 29
 
6.1%
산 26
 
5.4%
주 17
 
3.5%
면 16
 
3.3%
길 16
 
3.3%
읍 15
 
3.1%
고 14
 
2.9%
안 14
 
2.9%
Other values (89) 259
54.1%
Common
ValueCountFrequency (%)
150
45.0%
1 43
 
12.9%
2 23
 
6.9%
3 20
 
6.0%
7 18
 
5.4%
5 17
 
5.1%
0 16
 
4.8%
4 15
 
4.5%
8 10
 
3.0%
- 9
 
2.7%
Other values (2) 12
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
59.0%
ASCII 333
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
45.0%
1 43
 
12.9%
2 23
 
6.9%
3 20
 
6.0%
7 18
 
5.4%
5 17
 
5.1%
0 16
 
4.8%
4 15
 
4.5%
8 10
 
3.0%
- 9
 
2.7%
Other values (2) 12
 
3.6%
Hangul
ValueCountFrequency (%)
로 40
 
8.4%
시 33
 
6.9%
군 29
 
6.1%
산 26
 
5.4%
주 17
 
3.5%
면 16
 
3.3%
길 16
 
3.3%
읍 15
 
3.1%
고 14
 
2.9%
안 14
 
2.9%
Other values (89) 259
54.1%

Interactions

2024-03-15T00:02:24.384657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:23.874050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:24.557351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:24.113656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:02:32.115762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번최초등록업종업소명소재지
순번1.0000.9510.1331.0000.928
최초등록0.9511.0000.1281.0001.000
업종0.1330.1281.0001.0000.000
업소명1.0001.0001.0001.0001.000
소재지0.9281.0000.0001.0001.000
2024-03-15T00:02:32.377893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번최초등록업종
순번1.0000.9870.000
최초등록0.9871.0000.256
업종0.0000.2561.000

Missing values

2024-03-15T00:02:24.764894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:02:24.984299image/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

순번최초등록업종업소명소재지
012013유흥주점부영음악광장남원시 큰들길 23-9
122013학원지평선학당김제시 도장로 74
232013노래엽습장뮤직시티 노래연습장부안군 변산면 변산해변로 51
342014휴게음식점탐앤탐스 전주신시가지전주시 완산구 우전로 208
452014일반음식점한스델리 김제점김제시 동서로 183
562014일반음식점석정힐cc클럽하우스고창군 고창읍 석정1로 105
672014목욕장업무주덕유산리조트찜질방무주군 설천면 만선로 185
782015휴게음식점엔제리너스김제중앙김제시 동서로 170
892015일반음식점HR하누리고창cc레스토랑고창군 심원면 애향갯벌로 70
9102015일반음식점모항해나루가족호텔레스토랑부안군 변산면 모항해변길 73
순번최초등록업종업소명소재지
47482020휴게음식점투썸플레이스 군산수송점군산시 남수송3길 43
48492020휴게음식점한국맥도날드 익산영등DT점익산시 무왕로 1046
49502020휴게음식점맥도날드 정읍정읍시 남북로 51
50512020스크린골프연습장메이저 스크린골프남원시 원천로 103-2
51522020영화상영관지평선시네마김제시 도작로 224-32
52532020일반음식점까미나레완주군 소양면 모래재로 75-5
53542020일반음식점순창맛집순창군 순창읍 민속마을길 6-3
54552020스크린골프연습장힐링스크린고창군 고창읍 교촌2길 25
55562020휴게음식점이레커피 꽃을피우다부안군 부안읍 수정길 9
56572020일반음식점수라원무주군 설천면 무설로 1482