Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory57.3 B

Variable types

Categorical2
DateTime1
Text4

Dataset

Description울산광역시 중구 관할 구역 내 소재한 이용원에 대한 데이터 입니다. 해당 데이터는 명칭, 소재지(도로명),소재지(지번), 연락처 등의 정보를 포함하고 있습니다.
Author울산광역시 중구
URLhttps://www.data.go.kr/data/15055273/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 2 (2.0%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique
영업소 주소(지번) has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:16:27.939935
Analysis finished2024-03-14 10:16:30.043928
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
이용업
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 100
100.0%

Length

2024-03-14T19:16:30.246526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:16:30.533965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 100
100.0%

신고일자
Date

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
Minimum1966-10-21 00:00:00
Maximum2023-12-01 00:00:00
2024-03-14T19:16:30.846492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:16:31.299837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-03-14T19:16:32.438244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length5
Mean length5.8
Min length2

Characters and Unicode

Total characters580
Distinct characters159
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

Unique96 ?
Unique (%)96.0%

Sample

1st row월성이용원
2nd row반도이용원
3rd row세기이용원
4th row칠성이용원
5th row태화이용원
ValueCountFrequency (%)
선경이용원 2
 
1.9%
퀸즈헤나 2
 
1.9%
구내이용원 1
 
1.0%
신세계사우나 1
 
1.0%
월성이용원 1
 
1.0%
이영숙이용원 1
 
1.0%
남경남성컷트전문점 1
 
1.0%
원더풀 1
 
1.0%
남자의향기 1
 
1.0%
길헤어 1
 
1.0%
Other values (92) 92
88.5%
2024-03-14T19:16:33.974514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 69
 
11.9%
용 63
 
10.9%
원 63
 
10.9%
성 20
 
3.4%
남 15
 
2.6%
나 12
 
2.1%
헤 11
 
1.9%
트 9
 
1.6%
컷 9
 
1.6%
점 8
 
1.4%
Other values (149) 301
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 528
91.0%
Uppercase Letter 18
 
3.1%
Lowercase Letter 10
 
1.7%
Open Punctuation 7
 
1.2%
Close Punctuation 7
 
1.2%
Space Separator 4
 
0.7%
Other Punctuation 4
 
0.7%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 69
 
13.1%
용 63
 
11.9%
원 63
 
11.9%
성 20
 
3.8%
남 15
 
2.8%
나 12
 
2.3%
헤 11
 
2.1%
트 9
 
1.7%
컷 9
 
1.7%
점 8
 
1.5%
Other values (126) 249
47.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
16.7%
S 3
16.7%
E 2
11.1%
H 2
11.1%
R 2
11.1%
W 1
 
5.6%
P 1
 
5.6%
O 1
 
5.6%
A 1
 
5.6%
U 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
i 2
20.0%
h 2
20.0%
g 2
20.0%
e 2
20.0%
t 2
20.0%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 1
25.0%
# 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
8 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 528
91.0%
Latin 28
 
4.8%
Common 24
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 69
 
13.1%
용 63
 
11.9%
원 63
 
11.9%
성 20
 
3.8%
남 15
 
2.8%
나 12
 
2.3%
헤 11
 
2.1%
트 9
 
1.7%
컷 9
 
1.7%
점 8
 
1.5%
Other values (126) 249
47.2%
Latin
ValueCountFrequency (%)
B 3
10.7%
S 3
10.7%
E 2
 
7.1%
i 2
 
7.1%
h 2
 
7.1%
g 2
 
7.1%
e 2
 
7.1%
H 2
 
7.1%
R 2
 
7.1%
t 2
 
7.1%
Other values (6) 6
21.4%
Common
ValueCountFrequency (%)
( 7
29.2%
) 7
29.2%
4
16.7%
, 2
 
8.3%
8 2
 
8.3%
. 1
 
4.2%
# 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 528
91.0%
ASCII 52
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 69
 
13.1%
용 63
 
11.9%
원 63
 
11.9%
성 20
 
3.8%
남 15
 
2.8%
나 12
 
2.3%
헤 11
 
2.1%
트 9
 
1.7%
컷 9
 
1.7%
점 8
 
1.5%
Other values (126) 249
47.2%
ASCII
ValueCountFrequency (%)
( 7
 
13.5%
) 7
 
13.5%
4
 
7.7%
B 3
 
5.8%
S 3
 
5.8%
E 2
 
3.8%
i 2
 
3.8%
h 2
 
3.8%
g 2
 
3.8%
e 2
 
3.8%
Other values (13) 18
34.6%

영업소 주소(도로명)
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-03-14T19:16:35.118038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length25.91
Min length20

Characters and Unicode

Total characters2591
Distinct characters121
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

Unique100 ?
Unique (%)100.0%

Sample

1st row울산광역시 중구 한결길 35 (교동)
2nd row울산광역시 중구 옥골샘4길 9 (옥교동,(1층))
3rd row울산광역시 중구 병영로 3 (남외동)
4th row울산광역시 중구 당산5길 6, 1층 (우정동)
5th row울산광역시 중구 난곡16길 1, 1층 (태화동)
ValueCountFrequency (%)
울산광역시 100
 
17.5%
중구 100
 
17.5%
1층 36
 
6.3%
반구동 21
 
3.7%
남외동 11
 
1.9%
우정동 11
 
1.9%
태화동 10
 
1.7%
다운동 9
 
1.6%
19 5
 
0.9%
3층 5
 
0.9%
Other values (195) 265
46.2%
2024-03-14T19:16:36.703724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
18.3%
구 138
 
5.3%
1 133
 
5.1%
동 113
 
4.4%
산 113
 
4.4%
( 107
 
4.1%
) 106
 
4.1%
중 102
 
3.9%
울 100
 
3.9%
역 100
 
3.9%
Other values (111) 1106
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1457
56.2%
Space Separator 473
 
18.3%
Decimal Number 375
 
14.5%
Open Punctuation 107
 
4.1%
Close Punctuation 107
 
4.1%
Other Punctuation 64
 
2.5%
Dash Punctuation 7
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 138
 
9.5%
동 113
 
7.8%
산 113
 
7.8%
중 102
 
7.0%
울 100
 
6.9%
역 100
 
6.9%
시 100
 
6.9%
광 100
 
6.9%
길 72
 
4.9%
층 52
 
3.6%
Other values (94) 467
32.1%
Decimal Number
ValueCountFrequency (%)
1 133
35.5%
3 53
 
14.1%
2 39
 
10.4%
4 32
 
8.5%
0 27
 
7.2%
6 22
 
5.9%
5 21
 
5.6%
9 19
 
5.1%
7 16
 
4.3%
8 13
 
3.5%
Close Punctuation
ValueCountFrequency (%)
) 106
99.1%
} 1
 
0.9%
Space Separator
ValueCountFrequency (%)
473
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1457
56.2%
Common 1133
43.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 138
 
9.5%
동 113
 
7.8%
산 113
 
7.8%
중 102
 
7.0%
울 100
 
6.9%
역 100
 
6.9%
시 100
 
6.9%
광 100
 
6.9%
길 72
 
4.9%
층 52
 
3.6%
Other values (94) 467
32.1%
Common
ValueCountFrequency (%)
473
41.7%
1 133
 
11.7%
( 107
 
9.4%
) 106
 
9.4%
, 64
 
5.6%
3 53
 
4.7%
2 39
 
3.4%
4 32
 
2.8%
0 27
 
2.4%
6 22
 
1.9%
Other values (6) 77
 
6.8%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1457
56.2%
ASCII 1134
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
41.7%
1 133
 
11.7%
( 107
 
9.4%
) 106
 
9.3%
, 64
 
5.6%
3 53
 
4.7%
2 39
 
3.4%
4 32
 
2.8%
0 27
 
2.4%
6 22
 
1.9%
Other values (7) 78
 
6.9%
Hangul
ValueCountFrequency (%)
구 138
 
9.5%
동 113
 
7.8%
산 113
 
7.8%
중 102
 
7.0%
울 100
 
6.9%
역 100
 
6.9%
시 100
 
6.9%
광 100
 
6.9%
길 72
 
4.9%
층 52
 
3.6%
Other values (94) 467
32.1%

영업소 주소(지번)
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-03-14T19:16:37.917734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length20.8
Min length17

Characters and Unicode

Total characters2080
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

Unique100 ?
Unique (%)100.0%

Sample

1st row울산광역시 중구 교동 399-1
2nd row울산광역시 중구 옥교동 132-6 (1층)
3rd row울산광역시 중구 남외동 210-2
4th row울산광역시 중구 우정동 285-24 1층
5th row울산광역시 중구 태화동 893-7 (1층)
ValueCountFrequency (%)
울산광역시 100
22.8%
중구 100
22.8%
반구동 22
 
5.0%
우정동 13
 
3.0%
남외동 12
 
2.7%
태화동 12
 
2.7%
1층 10
 
2.3%
다운동 9
 
2.1%
복산동 5
 
1.1%
학성동 5
 
1.1%
Other values (135) 151
34.4%
2024-03-14T19:16:39.241589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
436
21.0%
구 123
 
5.9%
산 108
 
5.2%
동 106
 
5.1%
울 100
 
4.8%
광 100
 
4.8%
역 100
 
4.8%
시 100
 
4.8%
중 100
 
4.8%
- 94
 
4.5%
Other values (69) 713
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1083
52.1%
Decimal Number 447
21.5%
Space Separator 436
21.0%
Dash Punctuation 94
 
4.5%
Open Punctuation 9
 
0.4%
Close Punctuation 9
 
0.4%
Other Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 123
11.4%
산 108
10.0%
동 106
9.8%
울 100
9.2%
광 100
9.2%
역 100
9.2%
시 100
9.2%
중 100
9.2%
반 23
 
2.1%
정 16
 
1.5%
Other values (52) 207
19.1%
Decimal Number
ValueCountFrequency (%)
1 91
20.4%
4 58
13.0%
3 58
13.0%
2 49
11.0%
5 44
9.8%
7 35
 
7.8%
0 32
 
7.2%
6 30
 
6.7%
9 26
 
5.8%
8 24
 
5.4%
Close Punctuation
ValueCountFrequency (%)
) 8
88.9%
} 1
 
11.1%
Space Separator
ValueCountFrequency (%)
436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1083
52.1%
Common 996
47.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 123
11.4%
산 108
10.0%
동 106
9.8%
울 100
9.2%
광 100
9.2%
역 100
9.2%
시 100
9.2%
중 100
9.2%
반 23
 
2.1%
정 16
 
1.5%
Other values (52) 207
19.1%
Common
ValueCountFrequency (%)
436
43.8%
- 94
 
9.4%
1 91
 
9.1%
4 58
 
5.8%
3 58
 
5.8%
2 49
 
4.9%
5 44
 
4.4%
7 35
 
3.5%
0 32
 
3.2%
6 30
 
3.0%
Other values (6) 69
 
6.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1083
52.1%
ASCII 997
47.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
436
43.7%
- 94
 
9.4%
1 91
 
9.1%
4 58
 
5.8%
3 58
 
5.8%
2 49
 
4.9%
5 44
 
4.4%
7 35
 
3.5%
0 32
 
3.2%
6 30
 
3.0%
Other values (7) 70
 
7.0%
Hangul
ValueCountFrequency (%)
구 123
11.4%
산 108
10.0%
동 106
9.8%
울 100
9.2%
광 100
9.2%
역 100
9.2%
시 100
9.2%
중 100
9.2%
반 23
 
2.1%
정 16
 
1.5%
Other values (52) 207
19.1%

소재지전화
Text

MISSING 

Distinct69
Distinct (%)70.4%
Missing2
Missing (%)2.0%
Memory size928.0 B
2024-03-14T19:16:39.984520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length9.9489796
Min length1

Characters and Unicode

Total characters975
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)68.4%

Sample

1st row 052- 243-5269
2nd row052 -246 -2263
3rd row 052- 292-6094
4th row 052- 243-2095
5th row052 -249 -1169
ValueCountFrequency (%)
052 45
32.8%
249 5
 
3.6%
245 3
 
2.2%
246 2
 
1.5%
292 2
 
1.5%
286 2
 
1.5%
298 2
 
1.5%
296 2
 
1.5%
211-0333 1
 
0.7%
293-7600 1
 
0.7%
Other values (72) 72
52.6%
2024-03-14T19:16:41.465067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 166
17.0%
151
15.5%
- 134
13.7%
0 115
11.8%
5 96
9.8%
4 66
 
6.8%
9 59
 
6.1%
1 47
 
4.8%
8 38
 
3.9%
6 36
 
3.7%
Other values (2) 67
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 690
70.8%
Space Separator 151
 
15.5%
Dash Punctuation 134
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 166
24.1%
0 115
16.7%
5 96
13.9%
4 66
 
9.6%
9 59
 
8.6%
1 47
 
6.8%
8 38
 
5.5%
6 36
 
5.2%
3 35
 
5.1%
7 32
 
4.6%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 975
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 166
17.0%
151
15.5%
- 134
13.7%
0 115
11.8%
5 96
9.8%
4 66
 
6.8%
9 59
 
6.1%
1 47
 
4.8%
8 38
 
3.9%
6 36
 
3.7%
Other values (2) 67
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 975
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 166
17.0%
151
15.5%
- 134
13.7%
0 115
11.8%
5 96
9.8%
4 66
 
6.8%
9 59
 
6.1%
1 47
 
4.8%
8 38
 
3.9%
6 36
 
3.7%
Other values (2) 67
6.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-01-31
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-31
2nd row2024-01-31
3rd row2024-01-31
4th row2024-01-31
5th row2024-01-31

Common Values

ValueCountFrequency (%)
2024-01-31 100
100.0%

Length

2024-03-14T19:16:41.956384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:16:42.284537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-31 100
100.0%

Correlations

2024-03-14T19:16:42.526931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고일자업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
신고일자1.0000.9971.0001.0000.825
업소명0.9971.0001.0001.0000.996
영업소 주소(도로명)1.0001.0001.0001.0001.000
영업소 주소(지번)1.0001.0001.0001.0001.000
소재지전화0.8250.9961.0001.0001.000

Missing values

2024-03-14T19:16:29.265527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:16:29.658328image/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)소재지전화데이터기준일
0이용업1966-10-21월성이용원울산광역시 중구 한결길 35 (교동)울산광역시 중구 교동 399-1052- 243-52692024-01-31
1이용업1973-04-23반도이용원울산광역시 중구 옥골샘4길 9 (옥교동,(1층))울산광역시 중구 옥교동 132-6 (1층)052 -246 -22632024-01-31
2이용업1974-05-13세기이용원울산광역시 중구 병영로 3 (남외동)울산광역시 중구 남외동 210-2052- 292-60942024-01-31
3이용업1975-08-11칠성이용원울산광역시 중구 당산5길 6, 1층 (우정동)울산광역시 중구 우정동 285-24 1층052- 243-20952024-01-31
4이용업1977-03-14태화이용원울산광역시 중구 난곡16길 1, 1층 (태화동)울산광역시 중구 태화동 893-7 (1층)052 -249 -11692024-01-31
5이용업1979-06-15복산이용원울산광역시 중구 새즈믄해거리 50, 1층 (성남동)울산광역시 중구 성남동 68-9052 -245 -52112024-01-31
6이용업1980-04-02삼흥이용원울산광역시 중구 구교로 182, 1층 (반구동)울산광역시 중구 반구동 246-8052-0292-64422024-01-31
7이용업1983-08-26경성이용원울산광역시 중구 옥교3길 7 (옥교동)울산광역시 중구 옥교동 309-6052-0243-20772024-01-31
8이용업1983-06-02당신이발소울산광역시 중구 화진4길 31, 1층 (태화동)울산광역시 중구 태화동 30-1052 -245 -67052024-01-31
9이용업1983-09-10학성이용원울산광역시 중구 학산로 17 (학성동)울산광역시 중구 학성동 432-373052- 297-25522024-01-31
업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)소재지전화데이터기준일
90이용업2021-09-27엘샤론코리아울산광역시 중구 화진4길 27 (태화동)울산광역시 중구 태화동 30-22024-01-31
91이용업2021-11-29아담남성컷트울산광역시 중구 구교12길 15, 1층 (반구동)울산광역시 중구 반구동 45-222024-01-31
92이용업2022-02-16대송이용원울산광역시 중구 다운6길 47, 1층 (다운동)울산광역시 중구 다운동 756-72024-01-31
93이용업2022-03-08남성컷트클럽울산광역시 중구 서원2길 51, 1층 (반구동)울산광역시 중구 반구동 101-202024-01-31
94이용업2022-05-06블루스바버샵(BLUES BARBERSHOP)울산광역시 중구 중앙길 79, 1층 (성남동)울산광역시 중구 성남동 182-32024-01-31
95이용업2023-02-03샵(#)헤어울산광역시 중구 남외1길 23, 102호 (남외동)울산광역시 중구 남외동 506-82024-01-31
96이용업2023-04-248,8(eight,eight)울산광역시 중구 내황13길 33-1, 1층 (반구동)울산광역시 중구 반구동 354-32024-01-31
97이용업2023-05-31남성컷맨즈헤어울산광역시 중구 반구정6길 30-16, 1층 103호 (반구동)울산광역시 중구 반구동 644-42024-01-31
98이용업2023-08-29학성사우나이용원울산광역시 중구 내황3길 19, 3층 (반구동)울산광역시 중구 반구동 775-52024-01-31
99이용업2023-12-01송이발소울산광역시 중구 반구정9길 23, 103호 (반구동)울산광역시 중구 반구동 290-132024-01-31