Overview

Dataset statistics

Number of variables6
Number of observations32
Missing cells3
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory53.1 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description남양주시 목욕장업소에 대한 데이터로 업소명, 업소소재지(도로명), 업소소재지(지번), 소재지 전화번호 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/3033728/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업소소재지(도로명) has 2 (6.2%) missing valuesMissing
전화번호 has 1 (3.1%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
업소소재지(지번) has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:21:00.788977
Analysis finished2024-04-06 08:21:02.465423
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-06T17:21:03.074975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-04-06T17:21:03.498172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

업소명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-06T17:21:04.079314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.1875
Min length3

Characters and Unicode

Total characters230
Distinct characters95
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

Unique32 ?
Unique (%)100.0%

Sample

1st row대일목욕탕
2nd row천우탕
3rd row삼신목욕탕
4th row목화대중목욕탕
5th row마석사우나
ValueCountFrequency (%)
대일목욕탕 1
 
2.8%
천우탕 1
 
2.8%
주)새앰 1
 
2.8%
샘사우나 1
 
2.8%
수동사우나 1
 
2.8%
노블레스 1
 
2.8%
스파24시 1
 
2.8%
미소황토불가마 1
 
2.8%
펜션 1
 
2.8%
로데오유황24시사우나 1
 
2.8%
Other values (26) 26
72.2%
2024-04-06T17:21:04.815322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
우 17
 
7.4%
나 16
 
7.0%
사 16
 
7.0%
스 13
 
5.7%
파 8
 
3.5%
4 5
 
2.2%
목 5
 
2.2%
시 5
 
2.2%
탕 5
 
2.2%
2 5
 
2.2%
Other values (85) 135
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
92.2%
Decimal Number 10
 
4.3%
Space Separator 4
 
1.7%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 17
 
8.0%
나 16
 
7.5%
사 16
 
7.5%
스 13
 
6.1%
파 8
 
3.8%
목 5
 
2.4%
시 5
 
2.4%
탕 5
 
2.4%
마 5
 
2.4%
황 4
 
1.9%
Other values (80) 118
55.7%
Decimal Number
ValueCountFrequency (%)
4 5
50.0%
2 5
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
92.2%
Common 18
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 17
 
8.0%
나 16
 
7.5%
사 16
 
7.5%
스 13
 
6.1%
파 8
 
3.8%
목 5
 
2.4%
시 5
 
2.4%
탕 5
 
2.4%
마 5
 
2.4%
황 4
 
1.9%
Other values (80) 118
55.7%
Common
ValueCountFrequency (%)
4 5
27.8%
2 5
27.8%
4
22.2%
( 2
 
11.1%
) 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
92.2%
ASCII 18
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
우 17
 
8.0%
나 16
 
7.5%
사 16
 
7.5%
스 13
 
6.1%
파 8
 
3.8%
목 5
 
2.4%
시 5
 
2.4%
탕 5
 
2.4%
마 5
 
2.4%
황 4
 
1.9%
Other values (80) 118
55.7%
ASCII
ValueCountFrequency (%)
4 5
27.8%
2 5
27.8%
4
22.2%
( 2
 
11.1%
) 2
 
11.1%

업소소재지(도로명)
Text

MISSING 

Distinct30
Distinct (%)100.0%
Missing2
Missing (%)6.2%
Memory size388.0 B
2024-04-06T17:21:05.315704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length42
Mean length35.233333
Min length21

Characters and Unicode

Total characters1057
Distinct characters121
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row경기도 남양주시 퇴계원읍 퇴계원로 21
2nd row경기도 남양주시 홍유릉로 345 (금곡동)
3rd row경기도 남양주시 퇴계원읍 퇴계원로46번길 11
4th row경기도 남양주시 화도읍 마석중앙로28번길 19
5th row경기도 남양주시 진건읍 진건오남로 71 (지2층)
ValueCountFrequency (%)
경기도 30
 
15.4%
남양주시 30
 
15.4%
다산동 5
 
2.6%
일부 4
 
2.1%
화도읍 4
 
2.1%
지층 4
 
2.1%
퇴계원읍 3
 
1.5%
진접읍 3
 
1.5%
오남읍 3
 
1.5%
진건오남로 3
 
1.5%
Other values (95) 106
54.4%
2024-04-06T17:21:06.147791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
 
15.6%
1 53
 
5.0%
남 37
 
3.5%
경 35
 
3.3%
도 35
 
3.3%
주 33
 
3.1%
0 33
 
3.1%
시 32
 
3.0%
, 32
 
3.0%
로 31
 
2.9%
Other values (111) 571
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 595
56.3%
Decimal Number 205
 
19.4%
Space Separator 165
 
15.6%
Other Punctuation 32
 
3.0%
Open Punctuation 24
 
2.3%
Close Punctuation 24
 
2.3%
Math Symbol 5
 
0.5%
Dash Punctuation 4
 
0.4%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 37
 
6.2%
경 35
 
5.9%
도 35
 
5.9%
주 33
 
5.5%
시 32
 
5.4%
로 31
 
5.2%
양 30
 
5.0%
기 30
 
5.0%
층 20
 
3.4%
동 19
 
3.2%
Other values (94) 293
49.2%
Decimal Number
ValueCountFrequency (%)
1 53
25.9%
0 33
16.1%
2 26
12.7%
3 20
 
9.8%
7 18
 
8.8%
8 15
 
7.3%
5 11
 
5.4%
6 11
 
5.4%
9 9
 
4.4%
4 9
 
4.4%
Space Separator
ValueCountFrequency (%)
165
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 595
56.3%
Common 459
43.4%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 37
 
6.2%
경 35
 
5.9%
도 35
 
5.9%
주 33
 
5.5%
시 32
 
5.4%
로 31
 
5.2%
양 30
 
5.0%
기 30
 
5.0%
층 20
 
3.4%
동 19
 
3.2%
Other values (94) 293
49.2%
Common
ValueCountFrequency (%)
165
35.9%
1 53
 
11.5%
0 33
 
7.2%
, 32
 
7.0%
2 26
 
5.7%
( 24
 
5.2%
) 24
 
5.2%
3 20
 
4.4%
7 18
 
3.9%
8 15
 
3.3%
Other values (6) 49
 
10.7%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 595
56.3%
ASCII 462
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
35.7%
1 53
 
11.5%
0 33
 
7.1%
, 32
 
6.9%
2 26
 
5.6%
( 24
 
5.2%
) 24
 
5.2%
3 20
 
4.3%
7 18
 
3.9%
8 15
 
3.2%
Other values (7) 52
 
11.3%
Hangul
ValueCountFrequency (%)
남 37
 
6.2%
경 35
 
5.9%
도 35
 
5.9%
주 33
 
5.5%
시 32
 
5.4%
로 31
 
5.2%
양 30
 
5.0%
기 30
 
5.0%
층 20
 
3.4%
동 19
 
3.2%
Other values (94) 293
49.2%

업소소재지(지번)
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-06T17:21:06.535690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length36
Mean length31.375
Min length17

Characters and Unicode

Total characters1004
Distinct characters107
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 남양주시 퇴계원읍 퇴계원리 299-11
2nd row경기도 남양주시 금곡동 680-1
3rd row경기도 남양주시 진접읍 장현리 633-1
4th row경기도 남양주시 퇴계원읍 퇴계원리 255-17
5th row경기도 남양주시 화도읍 창현리 495-10
ValueCountFrequency (%)
경기도 32
 
16.9%
남양주시 32
 
16.9%
다산동 5
 
2.6%
진접읍 4
 
2.1%
화도읍 4
 
2.1%
와부읍 3
 
1.6%
퇴계원읍 3
 
1.6%
퇴계원리 3
 
1.6%
오남리 3
 
1.6%
금곡동 3
 
1.6%
Other values (84) 97
51.3%
2024-04-06T17:21:07.264446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
18.7%
1 52
 
5.2%
0 41
 
4.1%
남 39
 
3.9%
도 36
 
3.6%
주 35
 
3.5%
시 33
 
3.3%
기 32
 
3.2%
경 32
 
3.2%
양 32
 
3.2%
Other values (97) 484
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
53.5%
Decimal Number 222
22.1%
Space Separator 188
 
18.7%
Dash Punctuation 23
 
2.3%
Other Punctuation 15
 
1.5%
Close Punctuation 7
 
0.7%
Open Punctuation 7
 
0.7%
Math Symbol 4
 
0.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 39
 
7.3%
도 36
 
6.7%
주 35
 
6.5%
시 33
 
6.1%
기 32
 
6.0%
경 32
 
6.0%
양 32
 
6.0%
리 24
 
4.5%
동 19
 
3.5%
읍 18
 
3.4%
Other values (80) 237
44.1%
Decimal Number
ValueCountFrequency (%)
1 52
23.4%
0 41
18.5%
3 18
 
8.1%
2 18
 
8.1%
6 17
 
7.7%
8 17
 
7.7%
5 17
 
7.7%
7 16
 
7.2%
4 14
 
6.3%
9 12
 
5.4%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
53.5%
Common 466
46.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 39
 
7.3%
도 36
 
6.7%
주 35
 
6.5%
시 33
 
6.1%
기 32
 
6.0%
경 32
 
6.0%
양 32
 
6.0%
리 24
 
4.5%
동 19
 
3.5%
읍 18
 
3.4%
Other values (80) 237
44.1%
Common
ValueCountFrequency (%)
188
40.3%
1 52
 
11.2%
0 41
 
8.8%
- 23
 
4.9%
3 18
 
3.9%
2 18
 
3.9%
6 17
 
3.6%
8 17
 
3.6%
5 17
 
3.6%
7 16
 
3.4%
Other values (6) 59
 
12.7%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
53.5%
ASCII 467
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
40.3%
1 52
 
11.1%
0 41
 
8.8%
- 23
 
4.9%
3 18
 
3.9%
2 18
 
3.9%
6 17
 
3.6%
8 17
 
3.6%
5 17
 
3.6%
7 16
 
3.4%
Other values (7) 60
 
12.8%
Hangul
ValueCountFrequency (%)
남 39
 
7.3%
도 36
 
6.7%
주 35
 
6.5%
시 33
 
6.1%
기 32
 
6.0%
경 32
 
6.0%
양 32
 
6.0%
리 24
 
4.5%
동 19
 
3.5%
읍 18
 
3.4%
Other values (80) 237
44.1%

전화번호
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing1
Missing (%)3.1%
Memory size388.0 B
2024-04-06T17:21:07.670545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.129032
Min length12

Characters and Unicode

Total characters376
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row031-571-6528
2nd row031-591-0411
3rd row031-574-6722
4th row031-528-1717
5th row031-594-6504
ValueCountFrequency (%)
031-571-6528 1
 
3.2%
031-593-8388 1
 
3.2%
0507-1338-1911 1
 
3.2%
031-556-5000 1
 
3.2%
031-592-3530 1
 
3.2%
0507-1468-0386 1
 
3.2%
031-521-3333 1
 
3.2%
031-575-9834 1
 
3.2%
031-574-8887 1
 
3.2%
031-528-4310 1
 
3.2%
Other values (21) 21
67.7%
2024-04-06T17:21:08.780514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
16.5%
0 55
14.6%
3 54
14.4%
1 50
13.3%
5 50
13.3%
7 23
 
6.1%
8 23
 
6.1%
9 17
 
4.5%
2 16
 
4.3%
6 14
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 314
83.5%
Dash Punctuation 62
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
17.5%
3 54
17.2%
1 50
15.9%
5 50
15.9%
7 23
7.3%
8 23
7.3%
9 17
 
5.4%
2 16
 
5.1%
6 14
 
4.5%
4 12
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
16.5%
0 55
14.6%
3 54
14.4%
1 50
13.3%
5 50
13.3%
7 23
 
6.1%
8 23
 
6.1%
9 17
 
4.5%
2 16
 
4.3%
6 14
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
16.5%
0 55
14.6%
3 54
14.4%
1 50
13.3%
5 50
13.3%
7 23
 
6.1%
8 23
 
6.1%
9 17
 
4.5%
2 16
 
4.3%
6 14
 
3.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2024-03-28 00:00:00
Maximum2024-03-28 00:00:00
2024-04-06T17:21:09.025580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:09.205743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:21:01.397152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:21:09.377634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명업소소재지(도로명)업소소재지(지번)전화번호
연번1.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
업소소재지(도로명)1.0001.0001.0001.0001.000
업소소재지(지번)1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-04-06T17:21:01.774711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:21:02.112125image/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.
2024-04-06T17:21:02.365020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업소명업소소재지(도로명)업소소재지(지번)전화번호데이터기준일자
01대일목욕탕경기도 남양주시 퇴계원읍 퇴계원로 21경기도 남양주시 퇴계원읍 퇴계원리 299-11031-571-65282024-03-28
12천우탕경기도 남양주시 홍유릉로 345 (금곡동)경기도 남양주시 금곡동 680-1031-591-04112024-03-28
23삼신목욕탕<NA>경기도 남양주시 진접읍 장현리 633-1031-574-67222024-03-28
34목화대중목욕탕경기도 남양주시 퇴계원읍 퇴계원로46번길 11경기도 남양주시 퇴계원읍 퇴계원리 255-17031-528-17172024-03-28
45마석사우나경기도 남양주시 화도읍 마석중앙로28번길 19경기도 남양주시 화도읍 창현리 495-10031-594-65042024-03-28
56수정사우나경기도 남양주시 진건읍 진건오남로 71 (지2층)경기도 남양주시 진건읍 용정리 778-9 지2층031-573-73112024-03-28
67하와이사우나(덕소)경기도 남양주시 와부읍 덕소로 118-4경기도 남양주시 와부읍 덕소리 537-3031-577-38002024-03-28
78광릉사우나경기도 남양주시 진접읍 금강로 1549경기도 남양주시 진접읍 장현리 64031-572-36852024-03-28
89광천대중목욕탕경기도 남양주시 경춘로 1003 (금곡동)경기도 남양주시 금곡동 158-10031-511-68192024-03-28
910선플렉스사우나<NA>경기도 남양주시 와부읍 덕소리 485-1 외 2필지031-576-45822024-03-28
연번업소명업소소재지(도로명)업소소재지(지번)전화번호데이터기준일자
2223미소황토불가마 펜션경기도 남양주시 수동면 축령산로 179-23 (1동,2동)경기도 남양주시 수동면 외방리 370 1동,2동<NA>2024-03-28
2324로데오유황24시사우나경기도 남양주시 별내중앙로 30 (별내동, 별내로데오몰801호,901호)경기도 남양주시 별내동 1006-1 별내로데오몰801호,901호031-528-43102024-03-28
2425해밀24시불가마사우나경기도 남양주시 진접읍 경복대로 239 (단우타워6층7층8층)경기도 남양주시 진접읍 금곡리 1042-2 단우타워6층,7층,8층031-574-88872024-03-28
2526대성사우나경기도 남양주시 퇴계원읍 퇴계원로 29, 지층 B101호, B102호경기도 남양주시 퇴계원읍 퇴계원리 290-9031-575-98342024-03-28
2627덕소사우나경기도 남양주시 와부읍 수레로116번길 16, 301호 일부, 601호 일부경기도 남양주시 와부읍 덕소리 50 301호 일부, 601호 일부031-521-33332024-03-28
2728다산스파경기도 남양주시 다산중앙로123번길 22-8, 리더스퀘어 803~805호 (다산동)경기도 남양주시 다산동 6060 리더스퀘어 803,804,805호0507-1468-03862024-03-28
2829웰스포사우나경기도 남양주시 화도읍 창현로 33, 웰스포빌딩 주1동(지1층,1층),주2동(1층),주3동(1층)경기도 남양주시 화도읍 창현리 551-1 웰스포빌딩 주1동(지1층,1층),주2동(1층),주3동(1층)031-592-35302024-03-28
2930다산킹찜질방경기도 남양주시 다산중앙로123번길 22-80, 신해메디컬타워 7층(701~703호,704~706호일부,707~710호)8층(801~811호) (다산동)경기도 남양주시 다산동 6062 신해메디컬타워 7층(701~703호,704~706호일부,707~710호)8층(801~811호)031-556-50002024-03-28
3031스파디움24경기도 남양주시 다산순환로 20, 다산현대프리미어캠퍼스 지하1층 일부 (다산동)경기도 남양주시 다산동 6143 다산현대프리미어캠퍼스 지1층 일부(씨씨비1-011호)0507-1338-19112024-03-28
3132도농애시앙스포츠센터경기도 남양주시 도농로 24, 부영애시앙 901동 (다산동, 부영애시앙)경기도 남양주시 다산동 4001-29 부영애시앙 901동031-569-53802024-03-28