Overview

Dataset statistics

Number of variables5
Number of observations73
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)1.4%
Total size in memory3.0 KiB
Average record size in memory41.8 B

Variable types

Categorical1
DateTime1
Text3

Dataset

Description부산광역시 부산진구 내 등록된 목욕장업 현황을 제공하고 있습니다업종명, 신고일자, 업소명,주소 등의 정보를 제공합니다.
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15025545/fileData.do

Alerts

업종명 has constant value ""Constant
Dataset has 1 (1.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 23:56:32.643948
Analysis finished2023-12-11 23:56:33.291583
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
목욕장업
73 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목욕장업
2nd row목욕장업
3rd row목욕장업
4th row목욕장업
5th row목욕장업

Common Values

ValueCountFrequency (%)
목욕장업 73
100.0%

Length

2023-12-12T08:56:33.383990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:56:33.530668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 73
100.0%
Distinct70
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
Minimum1963-01-10 00:00:00
Maximum2023-02-20 00:00:00
2023-12-12T08:56:33.656399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:56:33.825117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct71
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T08:56:34.107140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length4.5068493
Min length2

Characters and Unicode

Total characters329
Distinct characters124
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)94.5%

Sample

1st row은하탕
2nd row한일탕
3rd row백수
4th row대성
5th row경마탕
ValueCountFrequency (%)
수정 2
 
2.4%
주식회사 2
 
2.4%
옥수탕 2
 
2.4%
주)국제식품 1
 
1.2%
목화사우나 1
 
1.2%
가야대중사우나24시 1
 
1.2%
대현탕 1
 
1.2%
은하탕 1
 
1.2%
lg탕 1
 
1.2%
금강헬씨랜드 1
 
1.2%
Other values (69) 69
84.1%
2023-12-12T08:56:34.850002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
9.4%
14
 
4.3%
13
 
4.0%
13
 
4.0%
11
 
3.3%
11
 
3.3%
11
 
3.3%
9
 
2.7%
7
 
2.1%
6
 
1.8%
Other values (114) 203
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 310
94.2%
Space Separator 9
 
2.7%
Decimal Number 6
 
1.8%
Uppercase Letter 2
 
0.6%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
31
 
10.0%
14
 
4.5%
13
 
4.2%
13
 
4.2%
11
 
3.5%
11
 
3.5%
11
 
3.5%
7
 
2.3%
6
 
1.9%
5
 
1.6%
Other values (107) 188
60.6%
Decimal Number
ValueCountFrequency (%)
4 3
50.0%
2 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 310
94.2%
Common 17
 
5.2%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
31
 
10.0%
14
 
4.5%
13
 
4.2%
13
 
4.2%
11
 
3.5%
11
 
3.5%
11
 
3.5%
7
 
2.3%
6
 
1.9%
5
 
1.6%
Other values (107) 188
60.6%
Common
ValueCountFrequency (%)
9
52.9%
4 3
 
17.6%
2 3
 
17.6%
) 1
 
5.9%
( 1
 
5.9%
Latin
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 310
94.2%
ASCII 19
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
31
 
10.0%
14
 
4.5%
13
 
4.2%
13
 
4.2%
11
 
3.5%
11
 
3.5%
11
 
3.5%
7
 
2.3%
6
 
1.9%
5
 
1.6%
Other values (107) 188
60.6%
ASCII
ValueCountFrequency (%)
9
47.4%
4 3
 
15.8%
2 3
 
15.8%
G 1
 
5.3%
) 1
 
5.3%
( 1
 
5.3%
L 1
 
5.3%
Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T08:56:35.092910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length28.273973
Min length23

Characters and Unicode

Total characters2064
Distinct characters97
Distinct categories7 ?
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 (%)97.3%

Sample

1st row부산광역시 부산진구 가야대로703번가길 16 (당감동)
2nd row부산광역시 부산진구 범양로 124 (양정동)
3rd row부산광역시 부산진구 황령대로74번길 26 (전포동)
4th row부산광역시 부산진구 당감로16번길 48 (당감동)
5th row부산광역시 부산진구 경마장로 3 (범전동)
ValueCountFrequency (%)
부산광역시 73
19.1%
부산진구 73
19.1%
당감동 11
 
2.9%
개금동 9
 
2.3%
부전동 8
 
2.1%
초읍동 8
 
2.1%
전포동 6
 
1.6%
양정동 6
 
1.6%
가야동 6
 
1.6%
부암동 5
 
1.3%
Other values (142) 178
46.5%
2023-12-12T08:56:35.444901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
15.0%
163
 
7.9%
147
 
7.1%
82
 
4.0%
76
 
3.7%
75
 
3.6%
75
 
3.6%
( 73
 
3.5%
73
 
3.5%
73
 
3.5%
Other values (87) 917
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1288
62.4%
Space Separator 310
 
15.0%
Decimal Number 295
 
14.3%
Open Punctuation 73
 
3.5%
Close Punctuation 73
 
3.5%
Dash Punctuation 15
 
0.7%
Other Punctuation 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
12.7%
147
 
11.4%
82
 
6.4%
76
 
5.9%
75
 
5.8%
75
 
5.8%
73
 
5.7%
73
 
5.7%
73
 
5.7%
46
 
3.6%
Other values (72) 405
31.4%
Decimal Number
ValueCountFrequency (%)
1 58
19.7%
3 36
12.2%
2 32
10.8%
6 32
10.8%
7 30
10.2%
5 26
8.8%
0 22
 
7.5%
9 20
 
6.8%
8 20
 
6.8%
4 19
 
6.4%
Space Separator
ValueCountFrequency (%)
310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1288
62.4%
Common 776
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
12.7%
147
 
11.4%
82
 
6.4%
76
 
5.9%
75
 
5.8%
75
 
5.8%
73
 
5.7%
73
 
5.7%
73
 
5.7%
46
 
3.6%
Other values (72) 405
31.4%
Common
ValueCountFrequency (%)
310
39.9%
( 73
 
9.4%
) 73
 
9.4%
1 58
 
7.5%
3 36
 
4.6%
2 32
 
4.1%
6 32
 
4.1%
7 30
 
3.9%
5 26
 
3.4%
0 22
 
2.8%
Other values (5) 84
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1288
62.4%
ASCII 776
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
39.9%
( 73
 
9.4%
) 73
 
9.4%
1 58
 
7.5%
3 36
 
4.6%
2 32
 
4.1%
6 32
 
4.1%
7 30
 
3.9%
5 26
 
3.4%
0 22
 
2.8%
Other values (5) 84
 
10.8%
Hangul
ValueCountFrequency (%)
163
12.7%
147
 
11.4%
82
 
6.4%
76
 
5.9%
75
 
5.8%
75
 
5.8%
73
 
5.7%
73
 
5.7%
73
 
5.7%
46
 
3.6%
Other values (72) 405
31.4%
Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T08:56:35.713187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length22.068493
Min length18

Characters and Unicode

Total characters1611
Distinct characters70
Distinct categories5 ?
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 (%)97.3%

Sample

1st row부산광역시 부산진구 당감동 978
2nd row부산광역시 부산진구 양정동 503-42
3rd row부산광역시 부산진구 전포동 378-24
4th row부산광역시 부산진구 당감동 241-48
5th row부산광역시 부산진구 범전동 63-32
ValueCountFrequency (%)
부산광역시 73
23.9%
부산진구 73
23.9%
당감동 11
 
3.6%
개금동 9
 
3.0%
부전동 8
 
2.6%
초읍동 8
 
2.6%
양정동 6
 
2.0%
전포동 6
 
2.0%
가야동 6
 
2.0%
연지동 5
 
1.6%
Other values (87) 100
32.8%
2023-12-12T08:56:36.117749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
18.9%
160
 
9.9%
146
 
9.1%
75
 
4.7%
74
 
4.6%
73
 
4.5%
73
 
4.5%
73
 
4.5%
73
 
4.5%
- 63
 
3.9%
Other values (60) 497
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 928
57.6%
Decimal Number 315
 
19.6%
Space Separator 304
 
18.9%
Dash Punctuation 63
 
3.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
160
17.2%
146
15.7%
75
8.1%
74
8.0%
73
7.9%
73
7.9%
73
7.9%
73
7.9%
18
 
1.9%
11
 
1.2%
Other values (47) 152
16.4%
Decimal Number
ValueCountFrequency (%)
1 61
19.4%
3 47
14.9%
2 44
14.0%
4 37
11.7%
7 24
 
7.6%
5 24
 
7.6%
8 21
 
6.7%
9 21
 
6.7%
6 19
 
6.0%
0 17
 
5.4%
Space Separator
ValueCountFrequency (%)
304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 928
57.6%
Common 683
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
160
17.2%
146
15.7%
75
8.1%
74
8.0%
73
7.9%
73
7.9%
73
7.9%
73
7.9%
18
 
1.9%
11
 
1.2%
Other values (47) 152
16.4%
Common
ValueCountFrequency (%)
304
44.5%
- 63
 
9.2%
1 61
 
8.9%
3 47
 
6.9%
2 44
 
6.4%
4 37
 
5.4%
7 24
 
3.5%
5 24
 
3.5%
8 21
 
3.1%
9 21
 
3.1%
Other values (3) 37
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 928
57.6%
ASCII 683
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304
44.5%
- 63
 
9.2%
1 61
 
8.9%
3 47
 
6.9%
2 44
 
6.4%
4 37
 
5.4%
7 24
 
3.5%
5 24
 
3.5%
8 21
 
3.1%
9 21
 
3.1%
Other values (3) 37
 
5.4%
Hangul
ValueCountFrequency (%)
160
17.2%
146
15.7%
75
8.1%
74
8.0%
73
7.9%
73
7.9%
73
7.9%
73
7.9%
18
 
1.9%
11
 
1.2%
Other values (47) 152
16.4%

Correlations

2023-12-12T08:56:36.205458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고일자업소명영업소 주소(도로명)영업소 주소(지번)
신고일자1.0000.9981.0001.000
업소명0.9981.0001.0001.000
영업소 주소(도로명)1.0001.0001.0001.000
영업소 주소(지번)1.0001.0001.0001.000

Missing values

2023-12-12T08:56:33.130677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:56:33.233360image/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

업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)
0목욕장업1963-01-10은하탕부산광역시 부산진구 가야대로703번가길 16 (당감동)부산광역시 부산진구 당감동 978
1목욕장업1968-09-27한일탕부산광역시 부산진구 범양로 124 (양정동)부산광역시 부산진구 양정동 503-42
2목욕장업1968-11-26백수부산광역시 부산진구 황령대로74번길 26 (전포동)부산광역시 부산진구 전포동 378-24
3목욕장업1969-02-08대성부산광역시 부산진구 당감로16번길 48 (당감동)부산광역시 부산진구 당감동 241-48
4목욕장업1970-05-09경마탕부산광역시 부산진구 경마장로 3 (범전동)부산광역시 부산진구 범전동 63-32
5목욕장업1973-10-12수복부산광역시 부산진구 가야대로572번길 83 (가야동)부산광역시 부산진구 가야동 440-1
6목욕장업1973-12-13중앙부산광역시 부산진구 가야대로 653-1 (가야동)부산광역시 부산진구 가야동 22-1
7목욕장업1983-12-30문화부산광역시 부산진구 성지로61번길 17 (연지동)부산광역시 부산진구 연지동 10-5
8목욕장업1984-01-28성지곡부산광역시 부산진구 초읍천로108번길 74 (초읍동)부산광역시 부산진구 초읍동 272-1
9목욕장업1984-01-30성수부산광역시 부산진구 백양순환로 12 (당감동)부산광역시 부산진구 당감동 348-35
업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)
63목욕장업2009-01-02롯데휘트니스목욕장부산광역시 부산진구 중앙대로969번길 11 (양정동)부산광역시 부산진구 양정동 273-1
64목욕장업2011-12-19현대사우나헬스부산광역시 부산진구 동평로 350, 양정현대프라자 지하2층 201호 (양정동)부산광역시 부산진구 양정동 511-3 양정현대프라자
65목욕장업2012-07-03신선 사우나 휘트니스부산광역시 부산진구 개금온정로 5 (개금동)부산광역시 부산진구 개금동 197-5 성원상떼뷰 상가1층,지하1층일부
66목욕장업2012-11-01한웅레포츠서면점부산광역시 부산진구 전포대로 162 (전포동)부산광역시 부산진구 전포동 362-62 3층 301호
67목욕장업2014-08-22양정사우나부산광역시 부산진구 중앙대로909번길 25 (양정동)부산광역시 부산진구 양정동 389-7 중앙대로 909동 25호
68목욕장업2017-01-02백양산한가족사우나부산광역시 부산진구 백양산로53번길 24 (부암동)부산광역시 부산진구 부암동 729
69목욕장업2018-06-21주식회사 윈즈휘트니스부산광역시 부산진구 중앙대로 777, 서면호텔 복합시설 3층 (부전동)부산광역시 부산진구 부전동 573-7 서면호텔 복합시설 3층
70목욕장업2020-07-08우성스마트사우나부산광역시 부산진구 동평로 269, 2층 201호 (연지동, 연지우성스마트시티뷰)부산광역시 부산진구 연지동 42-4 연지우성스마트시티뷰
71목욕장업2021-03-16약수탕부산광역시 부산진구 새싹로 50-1, 지하1층 (부전동)부산광역시 부산진구 부전동 393-27
72목욕장업2023-02-20(주)국제식품 양정점 국제온천부산광역시 부산진구 거제대로 70, 6층 일부, 7층, 9층 (양정동)부산광역시 부산진구 양정동 321-2

Duplicate rows

Most frequently occurring

업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)# duplicates
0목욕장업1986-11-05수정부산광역시 부산진구 부전로 193-1 (부전동)부산광역시 부산진구 부전동 39-12