Overview

Dataset statistics

Number of variables4
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory996.0 B
Average record size in memory36.9 B

Variable types

Text2
DateTime1
Categorical1

Dataset

Description부산광역시 서구에 위치하고있는 체력단련장업소에 대한 데이터로 업체명, 도로명 주소, 인허가일자, 업종 정보를 제공하고있습니다.
URLhttps://www.data.go.kr/data/15045169/fileData.do

Alerts

업종 has constant value ""Constant
업체명 has unique valuesUnique
소재지주소 has unique valuesUnique
인허가일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:48:49.658567
Analysis finished2023-12-12 03:48:50.049278
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:48:50.231788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.1111111
Min length2

Characters and Unicode

Total characters165
Distinct characters86
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

Unique27 ?
Unique (%)100.0%

Sample

1st row피플헬스
2nd row부산스포츠클럽
3rd row808피트니스
4th row한웅레포츠
5th row금천 헬스장
ValueCountFrequency (%)
오성피트니스 2
 
5.7%
피플헬스 1
 
2.9%
이젠피티앤필라테스 1
 
2.9%
제이윤 1
 
2.9%
멀티짐 1
 
2.9%
럭키네 1
 
2.9%
pt 1
 
2.9%
301피트니스 1
 
2.9%
지니 1
 
2.9%
킨더짐 1
 
2.9%
Other values (24) 24
68.6%
2023-12-12T12:48:50.729339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 13
 
7.9%
피 10
 
6.1%
트 9
 
5.5%
8
 
4.8%
이 7
 
4.2%
니 7
 
4.2%
짐 6
 
3.6%
포 4
 
2.4%
0 3
 
1.8%
티 3
 
1.8%
Other values (76) 95
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
78.8%
Uppercase Letter 14
 
8.5%
Decimal Number 9
 
5.5%
Space Separator 8
 
4.8%
Lowercase Letter 2
 
1.2%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 13
 
10.0%
피 10
 
7.7%
트 9
 
6.9%
이 7
 
5.4%
니 7
 
5.4%
짐 6
 
4.6%
포 4
 
3.1%
티 3
 
2.3%
오 3
 
2.3%
헬 3
 
2.3%
Other values (56) 65
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 2
14.3%
A 2
14.3%
G 2
14.3%
P 1
7.1%
S 1
7.1%
N 1
7.1%
E 1
7.1%
Y 1
7.1%
M 1
7.1%
F 1
7.1%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
8 2
22.2%
1 2
22.2%
3 2
22.2%
Lowercase Letter
ValueCountFrequency (%)
p 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
78.8%
Common 19
 
11.5%
Latin 16
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 13
 
10.0%
피 10
 
7.7%
트 9
 
6.9%
이 7
 
5.4%
니 7
 
5.4%
짐 6
 
4.6%
포 4
 
3.1%
티 3
 
2.3%
오 3
 
2.3%
헬 3
 
2.3%
Other values (56) 65
50.0%
Latin
ValueCountFrequency (%)
T 2
12.5%
A 2
12.5%
G 2
12.5%
P 1
 
6.2%
p 1
 
6.2%
t 1
 
6.2%
S 1
 
6.2%
N 1
 
6.2%
E 1
 
6.2%
Y 1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
8
42.1%
0 3
 
15.8%
8 2
 
10.5%
1 2
 
10.5%
3 2
 
10.5%
( 1
 
5.3%
) 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
78.8%
ASCII 35
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 13
 
10.0%
피 10
 
7.7%
트 9
 
6.9%
이 7
 
5.4%
니 7
 
5.4%
짐 6
 
4.6%
포 4
 
3.1%
티 3
 
2.3%
오 3
 
2.3%
헬 3
 
2.3%
Other values (56) 65
50.0%
ASCII
ValueCountFrequency (%)
8
22.9%
0 3
 
8.6%
8 2
 
5.7%
T 2
 
5.7%
1 2
 
5.7%
3 2
 
5.7%
A 2
 
5.7%
G 2
 
5.7%
P 1
 
2.9%
p 1
 
2.9%
Other values (10) 10
28.6%

소재지주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:48:51.129982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length31.259259
Min length21

Characters and Unicode

Total characters844
Distinct characters79
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row부산광역시 서구 충무대로256번길 7 (충무동1가)
2nd row부산광역시 서구 성산길 45 (암남동)
3rd row부산광역시 서구 충무대로 24 (암남동)
4th row부산광역시 서구 보수대로 105-1 (부용동1가)
5th row부산광역시 서구 해돋이로 279 (아미동2가)
ValueCountFrequency (%)
부산광역시 27
 
16.3%
서구 27
 
16.3%
구덕로 6
 
3.6%
2층 5
 
3.0%
보수대로 5
 
3.0%
충무대로 4
 
2.4%
서대신동2가 4
 
2.4%
암남동 3
 
1.8%
3층 3
 
1.8%
동대신동3가 3
 
1.8%
Other values (70) 79
47.6%
2023-12-12T12:48:51.669174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
 
16.5%
구 39
 
4.6%
1 39
 
4.6%
동 34
 
4.0%
서 32
 
3.8%
부 31
 
3.7%
산 29
 
3.4%
2 29
 
3.4%
( 27
 
3.2%
광 27
 
3.2%
Other values (69) 418
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
56.3%
Decimal Number 144
 
17.1%
Space Separator 139
 
16.5%
Open Punctuation 27
 
3.2%
Close Punctuation 27
 
3.2%
Other Punctuation 25
 
3.0%
Dash Punctuation 5
 
0.6%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 39
 
8.2%
동 34
 
7.2%
서 32
 
6.7%
부 31
 
6.5%
산 29
 
6.1%
광 27
 
5.7%
역 27
 
5.7%
시 27
 
5.7%
로 26
 
5.5%
가 24
 
5.1%
Other values (52) 179
37.7%
Decimal Number
ValueCountFrequency (%)
1 39
27.1%
2 29
20.1%
3 19
13.2%
4 13
 
9.0%
0 12
 
8.3%
5 10
 
6.9%
7 9
 
6.2%
9 5
 
3.5%
6 5
 
3.5%
8 3
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
56.3%
Common 367
43.5%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 39
 
8.2%
동 34
 
7.2%
서 32
 
6.7%
부 31
 
6.5%
산 29
 
6.1%
광 27
 
5.7%
역 27
 
5.7%
시 27
 
5.7%
로 26
 
5.5%
가 24
 
5.1%
Other values (52) 179
37.7%
Common
ValueCountFrequency (%)
139
37.9%
1 39
 
10.6%
2 29
 
7.9%
( 27
 
7.4%
) 27
 
7.4%
, 25
 
6.8%
3 19
 
5.2%
4 13
 
3.5%
0 12
 
3.3%
5 10
 
2.7%
Other values (5) 27
 
7.4%
Latin
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
56.3%
ASCII 369
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
37.7%
1 39
 
10.6%
2 29
 
7.9%
( 27
 
7.3%
) 27
 
7.3%
, 25
 
6.8%
3 19
 
5.1%
4 13
 
3.5%
0 12
 
3.3%
5 10
 
2.7%
Other values (7) 29
 
7.9%
Hangul
ValueCountFrequency (%)
구 39
 
8.2%
동 34
 
7.2%
서 32
 
6.7%
부 31
 
6.5%
산 29
 
6.1%
광 27
 
5.7%
역 27
 
5.7%
시 27
 
5.7%
로 26
 
5.5%
가 24
 
5.1%
Other values (52) 179
37.7%

인허가일자
Date

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2000-08-29 00:00:00
Maximum2023-03-29 00:00:00
2023-12-12T12:48:51.850990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:52.049955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
체력단련장업
27 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 27
100.0%

Length

2023-12-12T12:48:52.213632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:52.340422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 27
100.0%

Correlations

2023-12-12T12:48:52.435592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명소재지주소인허가일자
업체명1.0001.0001.000
소재지주소1.0001.0001.000
인허가일자1.0001.0001.000

Missing values

2023-12-12T12:48:49.898210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:48:50.006283image/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

업체명소재지주소인허가일자업종
0피플헬스부산광역시 서구 충무대로256번길 7 (충무동1가)2000-08-29체력단련장업
1부산스포츠클럽부산광역시 서구 성산길 45 (암남동)2000-10-02체력단련장업
2808피트니스부산광역시 서구 충무대로 24 (암남동)2002-03-08체력단련장업
3한웅레포츠부산광역시 서구 보수대로 105-1 (부용동1가)2004-10-05체력단련장업
4금천 헬스장부산광역시 서구 해돋이로 279 (아미동2가)2005-05-10체력단련장업
5해수피아부산광역시 서구 충무대로 134 (남부민동)2008-02-14체력단련장업
6킹콩짐부산광역시 서구 보수대로 15, 상가-202호 (토성동1가, 봄여름가을겨울)2014-05-27체력단련장업
7뉴욕짐부산광역시 서구 구덕로321번길 13 (서대신동2가)2014-09-15체력단련장업
8이젠퍼스널트레이닝부산광역시 서구 구덕로322번길 7, 6층 (동대신동3가)2015-02-12체력단련장업
9세찬부산광역시 서구 대영로 44 (서대신동1가)2015-06-10체력단련장업
업체명소재지주소인허가일자업종
17오성피트니스 남포점부산광역시 서구 보수대로 27, 101동 2층 (토성동1가, 경동 리인)2019-07-17체력단련장업
18제이윤 멀티짐부산광역시 서구 구덕로 101, 4층 (충무동1가)2019-09-20체력단련장업
19럭키네 PT부산광역시 서구 구덕로 150, 3층 (토성동3가)2020-01-08체력단련장업
20301피트니스부산광역시 서구 구덕로321번길 21, 남영빌딩 401호 (서대신동2가)2020-03-18체력단련장업
21이젠피티앤필라테스부산광역시 서구 구덕로334번길 6, 2층 (동대신동3가)2020-08-10체력단련장업
22지니 pt샵부산광역시 서구 구덕로148번길 30, 1층 (토성동5가)2021-11-29체력단련장업
23뉴욕피티부산광역시 서구 망양로 99, 1, 2층 (동대신동3가)2021-12-13체력단련장업
24오케이피트니스 대신점부산광역시 서구 구덕로 317-1, 4층 (서대신동2가)2022-01-03체력단련장업
25피트니스 코리아부산광역시 서구 충무대로275번길 20, 지하1층 (충무동2가, 에코팰리스)2022-10-20체력단련장업
26투와이핏부산광역시 서구 충무대로 8, 5층 504호(암남동, 기산비치타운)2023-03-29체력단련장업