Overview

Dataset statistics

Number of variables9
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory76.9 B

Variable types

Numeric1
Categorical3
Text5

Dataset

Description다중이용업소의 안전관리에 관한 특별법 제 21조에 의거 경상남도 소재 다중이용업소 중 안전관리 우수업소 목록 데이터
Author경상남도
URLhttps://www.data.go.kr/data/15108144/fileData.do

Alerts

공표일자 is highly overall correlated with 비고_신규 또는 갱신High correlation
비고_신규 또는 갱신 is highly overall correlated with 공표일자High correlation
연번 has unique valuesUnique
업소명 has unique valuesUnique
화재배상책임보험 일련번호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:14:54.302088
Analysis finished2024-03-14 20:14:56.391265
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size425.0 B
2024-03-15T05:14:56.606002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2024-03-15T05:14:57.008249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

업종
Categorical

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size392.0 B
휴게음식점
13 
일반음식점
10 
영화상영관
5 
가상체험체육시설
2 
유흥주점
2 

Length

Max length8
Median length5
Mean length5.0909091
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row영화상영관
2nd row영화상영관
3rd row휴게음식점
4th row일반음식점
5th row휴게음식점

Common Values

ValueCountFrequency (%)
휴게음식점 13
39.4%
일반음식점 10
30.3%
영화상영관 5
 
15.2%
가상체험체육시설 2
 
6.1%
유흥주점 2
 
6.1%
목욕장업 1
 
3.0%

Length

2024-03-15T05:14:57.342118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:14:57.727019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 13
39.4%
일반음식점 10
30.3%
영화상영관 5
 
15.2%
가상체험체육시설 2
 
6.1%
유흥주점 2
 
6.1%
목욕장업 1
 
3.0%

업소명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-15T05:14:58.497051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length8.5757576
Min length2

Characters and Unicode

Total characters283
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row롯데시네마 진주혁신점
2nd rowCGV진주혁신
3rd row스타벅스 진주신안점
4th row루나피에나
5th row카페 드 몰른
ValueCountFrequency (%)
롯데시네마 3
 
5.8%
카페 3
 
5.8%
스타벅스 2
 
3.8%
파스쿠찌 2
 
3.8%
고성축산농협 1
 
1.9%
양산가촌점 1
 
1.9%
브라더골프 1
 
1.9%
힐링카페 1
 
1.9%
멋쟁이 1
 
1.9%
라이브 1
 
1.9%
Other values (36) 36
69.2%
2024-03-15T05:14:59.651872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
6.7%
점 13
 
4.6%
스 11
 
3.9%
마 7
 
2.5%
라 6
 
2.1%
페 5
 
1.8%
프 5
 
1.8%
C 5
 
1.8%
카 5
 
1.8%
데 4
 
1.4%
Other values (126) 203
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
86.2%
Space Separator 19
 
6.7%
Uppercase Letter 9
 
3.2%
Close Punctuation 4
 
1.4%
Open Punctuation 4
 
1.4%
Decimal Number 1
 
0.4%
Other Symbol 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 13
 
5.3%
스 11
 
4.5%
마 7
 
2.9%
라 6
 
2.5%
페 5
 
2.0%
프 5
 
2.0%
카 5
 
2.0%
데 4
 
1.6%
양 4
 
1.6%
한 4
 
1.6%
Other values (115) 180
73.8%
Uppercase Letter
ValueCountFrequency (%)
C 5
55.6%
G 1
 
11.1%
V 1
 
11.1%
T 1
 
11.1%
D 1
 
11.1%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 245
86.6%
Common 29
 
10.2%
Latin 9
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 13
 
5.3%
스 11
 
4.5%
마 7
 
2.9%
라 6
 
2.4%
페 5
 
2.0%
프 5
 
2.0%
카 5
 
2.0%
데 4
 
1.6%
양 4
 
1.6%
한 4
 
1.6%
Other values (116) 181
73.9%
Common
ValueCountFrequency (%)
19
65.5%
) 4
 
13.8%
( 4
 
13.8%
2 1
 
3.4%
. 1
 
3.4%
Latin
ValueCountFrequency (%)
C 5
55.6%
G 1
 
11.1%
V 1
 
11.1%
T 1
 
11.1%
D 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
86.2%
ASCII 38
 
13.4%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
50.0%
C 5
 
13.2%
) 4
 
10.5%
( 4
 
10.5%
G 1
 
2.6%
V 1
 
2.6%
2 1
 
2.6%
T 1
 
2.6%
. 1
 
2.6%
D 1
 
2.6%
Hangul
ValueCountFrequency (%)
점 13
 
5.3%
스 11
 
4.5%
마 7
 
2.9%
라 6
 
2.5%
페 5
 
2.0%
프 5
 
2.0%
카 5
 
2.0%
데 4
 
1.6%
양 4
 
1.6%
한 4
 
1.6%
Other values (115) 180
73.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

화재배상책임보험 일련번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-15T05:15:00.415502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.636364
Min length14

Characters and Unicode

Total characters549
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st rowMU-48-2016-268889
2nd rowMU-48-2020-377289
3rd rowMU-48-2022-384251
4th rowMU-48-2009-107683
5th rowMU-48-2016-284889
ValueCountFrequency (%)
mu-48-2016-268889 1
 
3.0%
mu-48-2010-118207 1
 
3.0%
mu-48-2019-368950 1
 
3.0%
mu-48-2018-353649 1
 
3.0%
mu-48-2017-311969 1
 
3.0%
mu-48-2012-175062 1
 
3.0%
mu-48-2011-154918 1
 
3.0%
mu-48-2015-239010 1
 
3.0%
mu-48-2016-256409 1
 
3.0%
mu-48-2013-194145 1
 
3.0%
Other values (23) 23
69.7%
2024-03-15T05:15:01.589807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 87
15.8%
2 66
12.0%
8 64
11.7%
0 59
10.7%
4 50
9.1%
1 48
8.7%
M 33
 
6.0%
U 33
 
6.0%
9 31
 
5.6%
3 30
 
5.5%
Other values (3) 48
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 396
72.1%
Dash Punctuation 87
 
15.8%
Uppercase Letter 66
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 66
16.7%
8 64
16.2%
0 59
14.9%
4 50
12.6%
1 48
12.1%
9 31
7.8%
3 30
7.6%
6 18
 
4.5%
5 17
 
4.3%
7 13
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
M 33
50.0%
U 33
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 483
88.0%
Latin 66
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 87
18.0%
2 66
13.7%
8 64
13.3%
0 59
12.2%
4 50
10.4%
1 48
9.9%
9 31
 
6.4%
3 30
 
6.2%
6 18
 
3.7%
5 17
 
3.5%
Latin
ValueCountFrequency (%)
M 33
50.0%
U 33
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 87
15.8%
2 66
12.0%
8 64
11.7%
0 59
10.7%
4 50
9.1%
1 48
8.7%
M 33
 
6.0%
U 33
 
6.0%
9 31
 
5.6%
3 30
 
5.5%
Other values (3) 48
8.7%

관할
Text

Distinct18
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-15T05:15:02.386569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3030303
Min length2

Characters and Unicode

Total characters76
Distinct characters28
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

Unique8 ?
Unique (%)24.2%

Sample

1st row진주
2nd row진주
3rd row진주
4th row통영
5th row통영
ValueCountFrequency (%)
밀양 4
12.1%
김해서부 3
 
9.1%
진주 3
 
9.1%
양산 3
 
9.1%
통영 2
 
6.1%
하동 2
 
6.1%
산청 2
 
6.1%
김해동부 2
 
6.1%
거제 2
 
6.1%
함안 2
 
6.1%
Other values (8) 8
24.2%
2024-03-15T05:15:03.568935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 8
 
10.5%
해 6
 
7.9%
산 5
 
6.6%
김 5
 
6.6%
부 5
 
6.6%
밀 4
 
5.3%
동 4
 
5.3%
서 3
 
3.9%
진 3
 
3.9%
주 3
 
3.9%
Other values (18) 30
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 8
 
10.5%
해 6
 
7.9%
산 5
 
6.6%
김 5
 
6.6%
부 5
 
6.6%
밀 4
 
5.3%
동 4
 
5.3%
서 3
 
3.9%
진 3
 
3.9%
주 3
 
3.9%
Other values (18) 30
39.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 8
 
10.5%
해 6
 
7.9%
산 5
 
6.6%
김 5
 
6.6%
부 5
 
6.6%
밀 4
 
5.3%
동 4
 
5.3%
서 3
 
3.9%
진 3
 
3.9%
주 3
 
3.9%
Other values (18) 30
39.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 8
 
10.5%
해 6
 
7.9%
산 5
 
6.6%
김 5
 
6.6%
부 5
 
6.6%
밀 4
 
5.3%
동 4
 
5.3%
서 3
 
3.9%
진 3
 
3.9%
주 3
 
3.9%
Other values (18) 30
39.5%

주소
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-15T05:15:04.626784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length21.090909
Min length16

Characters and Unicode

Total characters696
Distinct characters100
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

Unique33 ?
Unique (%)100.0%

Sample

1st row경상남도 진주시 동진로 440
2nd row경상남도 진주시 에나로 127번길 30
3rd row경상남도 진주시 진양호로 355
4th row경상남도 통영시 산양읍 척포길 628-113
5th row경상남도 통영시 광도면 남해안대로 1160-95
ValueCountFrequency (%)
경상남도 33
 
20.9%
김해시 5
 
3.2%
밀양시 4
 
2.5%
양산시 3
 
1.9%
진주시 3
 
1.9%
거제시 2
 
1.3%
함안군 2
 
1.3%
남해안대로 2
 
1.3%
8 2
 
1.3%
산청군 2
 
1.3%
Other values (97) 100
63.3%
2024-03-15T05:15:05.918056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
18.2%
남 39
 
5.6%
경 34
 
4.9%
도 34
 
4.9%
상 33
 
4.7%
로 28
 
4.0%
2 21
 
3.0%
시 20
 
2.9%
5 19
 
2.7%
1 16
 
2.3%
Other values (90) 325
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
60.5%
Space Separator 127
 
18.2%
Decimal Number 126
 
18.1%
Dash Punctuation 11
 
1.6%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Other Punctuation 3
 
0.4%
Math Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 39
 
9.3%
경 34
 
8.1%
도 34
 
8.1%
상 33
 
7.8%
로 28
 
6.7%
시 20
 
4.8%
군 14
 
3.3%
양 12
 
2.9%
면 11
 
2.6%
해 11
 
2.6%
Other values (74) 185
43.9%
Decimal Number
ValueCountFrequency (%)
2 21
16.7%
5 19
15.1%
1 16
12.7%
3 15
11.9%
6 14
11.1%
8 11
8.7%
4 10
7.9%
0 8
 
6.3%
9 7
 
5.6%
7 5
 
4.0%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
60.5%
Common 275
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 39
 
9.3%
경 34
 
8.1%
도 34
 
8.1%
상 33
 
7.8%
로 28
 
6.7%
시 20
 
4.8%
군 14
 
3.3%
양 12
 
2.9%
면 11
 
2.6%
해 11
 
2.6%
Other values (74) 185
43.9%
Common
ValueCountFrequency (%)
127
46.2%
2 21
 
7.6%
5 19
 
6.9%
1 16
 
5.8%
3 15
 
5.5%
6 14
 
5.1%
- 11
 
4.0%
8 11
 
4.0%
4 10
 
3.6%
0 8
 
2.9%
Other values (6) 23
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
60.5%
ASCII 275
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
46.2%
2 21
 
7.6%
5 19
 
6.9%
1 16
 
5.8%
3 15
 
5.5%
6 14
 
5.1%
- 11
 
4.0%
8 11
 
4.0%
4 10
 
3.6%
0 8
 
2.9%
Other values (6) 23
 
8.4%
Hangul
ValueCountFrequency (%)
남 39
 
9.3%
경 34
 
8.1%
도 34
 
8.1%
상 33
 
7.8%
로 28
 
6.7%
시 20
 
4.8%
군 14
 
3.3%
양 12
 
2.9%
면 11
 
2.6%
해 11
 
2.6%
Other values (74) 185
43.9%

안전시설 등 설치내역
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-15T05:15:06.770621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length175
Median length87
Mean length82
Min length19

Characters and Unicode

Total characters2706
Distinct characters99
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

Unique31 ?
Unique (%)93.9%

Sample

1st row소화기구, sp, 자탐, 시경, 유도등, 비상조명, 휴비, 비방, 시경, 누경
2nd row소화기구, 옥소, sp, 자탐, 시경, 누차, 비방, 유도등, 완강기, 비상조명, 휴비,
3rd row소화기, 자탐,유도등, 휴비, 완강기, 시경
4th row수동식소화기, 자동확산소화용구, 비상조명등, 휴대용비상조명등, 피난구유도등, 완강기, 비상경보설비, 비상방송설비, 가스누설경보기, 자동화재탐지기(감), 비상구, 누전차단기
5th row수동식소화기, 자동확산소화용구, 휴대용비상조명등, 피난구유도등, 완강기, 비상경보설비, 가스누설경보기, 비상구, 누전차단기, 피난안내도
ValueCountFrequency (%)
누전차단기 24
 
6.9%
휴대용비상조명등 23
 
6.6%
수동식소화기 23
 
6.6%
피난안내도 22
 
6.3%
비상구 22
 
6.3%
피난구유도등 14
 
4.0%
방화문 14
 
4.0%
자동화재탐지설비 11
 
3.2%
완강기 10
 
2.9%
가스누설경보기 10
 
2.9%
Other values (60) 174
50.1%
2024-03-15T05:15:08.102758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 327
 
12.1%
315
 
11.6%
비 162
 
6.0%
기 120
 
4.4%
상 103
 
3.8%
화 90
 
3.3%
등 74
 
2.7%
도 70
 
2.6%
설 69
 
2.5%
동 63
 
2.3%
Other values (89) 1313
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2017
74.5%
Other Punctuation 328
 
12.1%
Space Separator 315
 
11.6%
Open Punctuation 17
 
0.6%
Close Punctuation 17
 
0.6%
Lowercase Letter 6
 
0.2%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 162
 
8.0%
기 120
 
5.9%
상 103
 
5.1%
화 90
 
4.5%
등 74
 
3.7%
도 70
 
3.5%
설 69
 
3.4%
동 63
 
3.1%
소 50
 
2.5%
구 50
 
2.5%
Other values (77) 1166
57.8%
Uppercase Letter
ValueCountFrequency (%)
H 2
33.3%
S 1
16.7%
V 1
16.7%
A 1
16.7%
P 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 327
99.7%
/ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
s 3
50.0%
p 3
50.0%
Space Separator
ValueCountFrequency (%)
315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2017
74.5%
Common 677
 
25.0%
Latin 12
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 162
 
8.0%
기 120
 
5.9%
상 103
 
5.1%
화 90
 
4.5%
등 74
 
3.7%
도 70
 
3.5%
설 69
 
3.4%
동 63
 
3.1%
소 50
 
2.5%
구 50
 
2.5%
Other values (77) 1166
57.8%
Latin
ValueCountFrequency (%)
s 3
25.0%
p 3
25.0%
H 2
16.7%
S 1
 
8.3%
V 1
 
8.3%
A 1
 
8.3%
P 1
 
8.3%
Common
ValueCountFrequency (%)
, 327
48.3%
315
46.5%
( 17
 
2.5%
) 17
 
2.5%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2017
74.5%
ASCII 689
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 327
47.5%
315
45.7%
( 17
 
2.5%
) 17
 
2.5%
s 3
 
0.4%
p 3
 
0.4%
H 2
 
0.3%
S 1
 
0.1%
V 1
 
0.1%
A 1
 
0.1%
Other values (2) 2
 
0.3%
Hangul
ValueCountFrequency (%)
비 162
 
8.0%
기 120
 
5.9%
상 103
 
5.1%
화 90
 
4.5%
등 74
 
3.7%
도 70
 
3.5%
설 69
 
3.4%
동 63
 
3.1%
소 50
 
2.5%
구 50
 
2.5%
Other values (77) 1166
57.8%

공표일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size392.0 B
2022-11-09
27 
2023-11-09
6 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-11-09
2nd row2023-11-09
3rd row2023-11-09
4th row2022-11-09
5th row2022-11-09

Common Values

ValueCountFrequency (%)
2022-11-09 27
81.8%
2023-11-09 6
 
18.2%

Length

2024-03-15T05:15:08.513441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:15:08.780858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11-09 27
81.8%
2023-11-09 6
 
18.2%

비고_신규 또는 갱신
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size392.0 B
갱신
21 
신규
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row갱신
2nd row신규
3rd row신규
4th row갱신
5th row갱신

Common Values

ValueCountFrequency (%)
갱신 21
63.6%
신규 12
36.4%

Length

2024-03-15T05:15:08.961664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:15:09.137033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갱신 21
63.6%
신규 12
36.4%

Interactions

2024-03-15T05:14:55.145011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:15:09.262653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업소명화재배상책임보험 일련번호관할주소안전시설 등 설치내역공표일자비고_신규 또는 갱신
연번1.0000.6041.0001.0000.9201.0000.9100.6480.344
업종0.6041.0001.0001.0000.6431.0000.9180.0000.120
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
화재배상책임보험 일련번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
관할0.9200.6431.0001.0001.0001.0001.0000.4470.516
주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
안전시설 등 설치내역0.9100.9181.0001.0001.0001.0001.0001.0001.000
공표일자0.6480.0001.0001.0000.4471.0001.0001.0000.730
비고_신규 또는 갱신0.3440.1201.0001.0000.5161.0001.0000.7301.000
2024-03-15T05:15:09.570511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고_신규 또는 갱신공표일자업종
비고_신규 또는 갱신1.0000.5210.041
공표일자0.5211.0000.000
업종0.0410.0001.000
2024-03-15T05:15:10.065715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종공표일자비고_신규 또는 갱신
연번1.0000.3260.4260.209
업종0.3261.0000.0000.041
공표일자0.4260.0001.0000.521
비고_신규 또는 갱신0.2090.0410.5211.000

Missing values

2024-03-15T05:14:55.586221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:14:56.212999image/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

연번업종업소명화재배상책임보험 일련번호관할주소안전시설 등 설치내역공표일자비고_신규 또는 갱신
01영화상영관롯데시네마 진주혁신점MU-48-2016-268889진주경상남도 진주시 동진로 440소화기구, sp, 자탐, 시경, 유도등, 비상조명, 휴비, 비방, 시경, 누경2022-11-09갱신
12영화상영관CGV진주혁신MU-48-2020-377289진주경상남도 진주시 에나로 127번길 30소화기구, 옥소, sp, 자탐, 시경, 누차, 비방, 유도등, 완강기, 비상조명, 휴비,2023-11-09신규
23휴게음식점스타벅스 진주신안점MU-48-2022-384251진주경상남도 진주시 진양호로 355소화기, 자탐,유도등, 휴비, 완강기, 시경2023-11-09신규
34일반음식점루나피에나MU-48-2009-107683통영경상남도 통영시 산양읍 척포길 628-113수동식소화기, 자동확산소화용구, 비상조명등, 휴대용비상조명등, 피난구유도등, 완강기, 비상경보설비, 비상방송설비, 가스누설경보기, 자동화재탐지기(감), 비상구, 누전차단기2022-11-09갱신
45휴게음식점카페 드 몰른MU-48-2016-284889통영경상남도 통영시 광도면 남해안대로 1160-95수동식소화기, 자동확산소화용구, 휴대용비상조명등, 피난구유도등, 완강기, 비상경보설비, 가스누설경보기, 비상구, 누전차단기, 피난안내도2022-11-09갱신
56휴게음식점한국맥도날드(유) 사천DT점MU-48-2013-185805사천경상남도 사천시 사천읍 사천대로 1838소화기, 자동확산소화기, 비상벨설비, 유도등, 피난사다리, 휴대용비상조명등, 가스누설경보기, 비상구, 누전차단기, 피난안내도2022-11-09갱신
67영화상영관롯데시네마 김해부원관MU-48-2014-205349김해동부경상남도 김해시 김해대로 2352, 3~5층스프링클러설비, 자동화재탐지설비 등2022-11-09갱신
78일반음식점㈜외식명가오립스MU-48-2012-180720김해동부경상남도 김해시 김해대로 1765번길 8스프링클러설비, 자동화재탐지설비 등2022-11-09갱신
89일반음식점포웰CC점 대식당(구.김해CC레스토랑)MU-48-2009-110261김해서부경상남도 김해시 진례면 고모로134번길 54-49수동식소화기, 자동식소화기, 스프링클러, 유도등및유도표지, 비상조명등, 휴대용비상조명등, 비상벨설비, 비상방송설비, 가스누설경보기, 자동화재탐지기(감), 방화문, 비상구, 누전차단기, 피난안내도2022-11-09갱신
910영화상영관롯데시네마MU-48-2013-189829김해서부경상남도 김해시 장유로 469수동식소화기, 옥내소화전설비, 스프링클러, 비상조명등, 휴대용비상조명등, 피난구유도등, 비상구, 영상음향차단장치, 누전차단기, 피난안내도2022-11-09갱신
연번업종업소명화재배상책임보험 일련번호관할주소안전시설 등 설치내역공표일자비고_신규 또는 갱신
2324휴게음식점롯데리아 경남남지점MU-48-2014-202429창녕경상남도 창녕군 남지읍 문화길 35-4수동식소화기, 자동확산소화용구, 유도등, 비상경보설비, 비상구, 누전차단기, 피난안내도,휴대용비상조명등2022-11-09신규
2425일반음식점고성축산농협 한우프라자 2호점MU-48-2013-194145고성경상남도 고성군 회화면 남해안대로 3762소화기구,자탐,비방,유도등,휴비,완강기2022-11-09갱신
2526영화상영관보물섬시네마(남해작은영화관)MU-48-2016-256409남해경상남도 남해군 남해읍 선소로 12수동식소화기, 옥내소화전설비, 스프링쿨러H, 휴대용비상조명등, 피난구유도등, 통로유도등, 객석유도등, 공기호흡기, 비상벨설비,비상방송설비또는 단독경보형감지기, 비상방송설비, 시각경보기, 자동화재탐지기(감), 자동화재탐지기(회), 방화문, 비상구, 영상음향차단장치, 누전차단기, 피난안내도, 피난안내영상물, 제연설비2022-11-09갱신
2627일반음식점누마루MU-48-2015-239010하동경상남도 하동군 화개면 쌍계로 523-6수동식소화기, 스프링쿨러H, 스프링쿨러AV, 비상조명등, 휴대용비상조명등, 피난구유도등, 비상방송설비, 가스누설경보기, 자동화재탐지기(감), 비상구, 피난안내도, 누전차단기, 자동화재탐지기(회), 자동화재탐지설비2022-11-09신규
2728일반음식점하동솔잎한우프라자MU-48-2011-154918하동경상남도 하동군 고전면 하동읍성로 9수동식소화기, 간이스프링클러설비, 유도등및유도표지, 휴대용비상조명등, 자동화재탐지설비, 가스누설경보기, 방화문, 비상구, 누전차단기, 피난안내도2022-11-09신규
2829일반음식점영실한우프라자MU-48-2012-175062산청경상남도 산청군 단성면 목화로 912수동식소화기, 자동확산소화용구, 유도등및유도표지, 휴대용비상조명등, 비상벨설비,비상방송설비또는 단독경보형감지기, 시각경보기, 가스누설경보기, 자동화재탐지기(감), 방화문, 비상구, 누전차단기, 피난안내도2022-11-09갱신
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