Overview

Dataset statistics

Number of variables6
Number of observations306
Missing cells177
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory48.4 B

Variable types

Categorical2
Text4

Dataset

Description경상남도 거제시 체육시설업현황(상호명, 주소, 위도, 경도, 전화번호, 기준일자) 등에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079326

Alerts

기준일자 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 기준일자High correlation
기준일자 is highly imbalanced (96.8%)Imbalance
시설주소(지번) has 26 (8.5%) missing valuesMissing
전화번호 has 149 (48.7%) missing valuesMissing

Reproduction

Analysis started2024-04-16 22:51:57.391809
Analysis finished2024-04-16 22:51:57.971350
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
당구장업
101 
체육도장업
80 
체력단련장업
51 
골프연습장업
31 
<NA>
16 
Other values (6)
27 

Length

Max length10
Median length7
Mean length4.996732
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 101
33.0%
체육도장업 80
26.1%
체력단련장업 51
16.7%
골프연습장업 31
 
10.1%
<NA> 16
 
5.2%
수영장업 9
 
2.9%
가상체험 체육시설업 8
 
2.6%
체육교습업 4
 
1.3%
무도학원업 3
 
1.0%
종합체육시설업 2
 
0.7%

Length

2024-04-17T07:51:58.026703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당구장업 101
32.2%
체육도장업 80
25.5%
체력단련장업 51
16.2%
골프연습장업 31
 
9.9%
na 16
 
5.1%
수영장업 9
 
2.9%
가상체험 8
 
2.5%
체육시설업 8
 
2.5%
체육교습업 4
 
1.3%
무도학원업 3
 
1.0%
Other values (2) 3
 
1.0%

상호명
Text

Distinct300
Distinct (%)98.4%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-04-17T07:51:58.262243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.5377049
Min length2

Characters and Unicode

Total characters2299
Distinct characters325
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

Unique295 ?
Unique (%)96.7%

Sample

1st row삼성문화관수영장
2nd row오션사이드수영장
3rd row삼성중공업 거제호텔 수영장
4th row이야짐
5th row신원아침도시 수영장
ValueCountFrequency (%)
당구클럽 9
 
2.0%
당구장 8
 
1.8%
태권도장 8
 
1.8%
클럽 5
 
1.1%
아일랜드 4
 
0.9%
수영장 4
 
0.9%
한화리조트거제벨버디어 3
 
0.7%
용인대 3
 
0.7%
나라찬태권도장 3
 
0.7%
당구 3
 
0.7%
Other values (360) 390
88.6%
2024-04-17T07:51:58.620683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
5.9%
장 118
 
5.1%
구 99
 
4.3%
당 92
 
4.0%
스 86
 
3.7%
도 72
 
3.1%
태 56
 
2.4%
권 56
 
2.4%
럽 49
 
2.1%
클 49
 
2.1%
Other values (315) 1487
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2014
87.6%
Space Separator 135
 
5.9%
Uppercase Letter 68
 
3.0%
Lowercase Letter 32
 
1.4%
Decimal Number 18
 
0.8%
Close Punctuation 12
 
0.5%
Open Punctuation 12
 
0.5%
Other Punctuation 7
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 118
 
5.9%
구 99
 
4.9%
당 92
 
4.6%
스 86
 
4.3%
도 72
 
3.6%
태 56
 
2.8%
권 56
 
2.8%
럽 49
 
2.4%
클 49
 
2.4%
프 34
 
1.7%
Other values (267) 1303
64.7%
Uppercase Letter
ValueCountFrequency (%)
M 12
17.6%
J 8
11.8%
S 6
8.8%
B 6
8.8%
G 6
8.8%
C 5
 
7.4%
Y 4
 
5.9%
P 3
 
4.4%
T 3
 
4.4%
N 2
 
2.9%
Other values (9) 13
19.1%
Lowercase Letter
ValueCountFrequency (%)
o 5
15.6%
i 4
12.5%
d 4
12.5%
y 4
12.5%
b 2
 
6.2%
t 2
 
6.2%
m 2
 
6.2%
l 1
 
3.1%
a 1
 
3.1%
r 1
 
3.1%
Other values (6) 6
18.8%
Decimal Number
ValueCountFrequency (%)
0 6
33.3%
7 3
16.7%
2 2
 
11.1%
3 2
 
11.1%
6 2
 
11.1%
5 1
 
5.6%
1 1
 
5.6%
4 1
 
5.6%
Space Separator
ValueCountFrequency (%)
135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2014
87.6%
Common 185
 
8.0%
Latin 100
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 118
 
5.9%
구 99
 
4.9%
당 92
 
4.6%
스 86
 
4.3%
도 72
 
3.6%
태 56
 
2.8%
권 56
 
2.8%
럽 49
 
2.4%
클 49
 
2.4%
프 34
 
1.7%
Other values (267) 1303
64.7%
Latin
ValueCountFrequency (%)
M 12
 
12.0%
J 8
 
8.0%
S 6
 
6.0%
B 6
 
6.0%
G 6
 
6.0%
o 5
 
5.0%
C 5
 
5.0%
i 4
 
4.0%
Y 4
 
4.0%
d 4
 
4.0%
Other values (25) 40
40.0%
Common
ValueCountFrequency (%)
135
73.0%
) 12
 
6.5%
( 12
 
6.5%
. 7
 
3.8%
0 6
 
3.2%
7 3
 
1.6%
2 2
 
1.1%
3 2
 
1.1%
6 2
 
1.1%
- 1
 
0.5%
Other values (3) 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2014
87.6%
ASCII 285
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
47.4%
M 12
 
4.2%
) 12
 
4.2%
( 12
 
4.2%
J 8
 
2.8%
. 7
 
2.5%
S 6
 
2.1%
B 6
 
2.1%
G 6
 
2.1%
0 6
 
2.1%
Other values (38) 75
26.3%
Hangul
ValueCountFrequency (%)
장 118
 
5.9%
구 99
 
4.9%
당 92
 
4.6%
스 86
 
4.3%
도 72
 
3.6%
태 56
 
2.8%
권 56
 
2.8%
럽 49
 
2.4%
클 49
 
2.4%
프 34
 
1.7%
Other values (267) 1303
64.7%

시설주소(지번)
Text

MISSING 

Distinct262
Distinct (%)93.6%
Missing26
Missing (%)8.5%
Memory size2.5 KiB
2024-04-17T07:51:58.859113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length21.957143
Min length12

Characters and Unicode

Total characters6148
Distinct characters174
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)87.9%

Sample

1st row경상남도 거제시 장평동 530
2nd row경상남도 거제시 장승포동 426-33
3rd row경상남도 거제시 장평동 444-1
4th row경상남도 거제시 장목면 농소리 25
5th row경상남도 거제시 장목면 농소리 25
ValueCountFrequency (%)
거제시 281
21.0%
경상남도 280
21.0%
고현동 62
 
4.6%
장평동 44
 
3.3%
옥포동 43
 
3.2%
아주동 29
 
2.2%
2층 23
 
1.7%
상동동 22
 
1.6%
수월동 15
 
1.1%
3층 14
 
1.0%
Other values (392) 522
39.1%
2024-04-17T07:51:59.231586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1055
17.2%
상 329
 
5.4%
1 315
 
5.1%
동 303
 
4.9%
제 299
 
4.9%
거 298
 
4.8%
도 284
 
4.6%
시 282
 
4.6%
경 281
 
4.6%
남 280
 
4.6%
Other values (164) 2422
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3424
55.7%
Decimal Number 1427
23.2%
Space Separator 1055
 
17.2%
Dash Punctuation 214
 
3.5%
Other Punctuation 12
 
0.2%
Math Symbol 5
 
0.1%
Uppercase Letter 5
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 329
 
9.6%
동 303
 
8.8%
제 299
 
8.7%
거 298
 
8.7%
도 284
 
8.3%
시 282
 
8.2%
경 281
 
8.2%
남 280
 
8.2%
포 71
 
2.1%
현 69
 
2.0%
Other values (141) 928
27.1%
Decimal Number
ValueCountFrequency (%)
1 315
22.1%
2 194
13.6%
3 153
10.7%
0 151
10.6%
5 130
9.1%
4 125
 
8.8%
6 112
 
7.8%
9 97
 
6.8%
8 76
 
5.3%
7 74
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
20.0%
A 1
20.0%
P 1
20.0%
I 1
20.0%
R 1
20.0%
Other Punctuation
ValueCountFrequency (%)
， 11
91.7%
. 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3424
55.7%
Common 2717
44.2%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 329
 
9.6%
동 303
 
8.8%
제 299
 
8.7%
거 298
 
8.7%
도 284
 
8.3%
시 282
 
8.2%
경 281
 
8.2%
남 280
 
8.2%
포 71
 
2.1%
현 69
 
2.0%
Other values (141) 928
27.1%
Common
ValueCountFrequency (%)
1055
38.8%
1 315
 
11.6%
- 214
 
7.9%
2 194
 
7.1%
3 153
 
5.6%
0 151
 
5.6%
5 130
 
4.8%
4 125
 
4.6%
6 112
 
4.1%
9 97
 
3.6%
Other values (7) 171
 
6.3%
Latin
ValueCountFrequency (%)
e 2
28.6%
K 1
14.3%
A 1
14.3%
P 1
14.3%
I 1
14.3%
R 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3424
55.7%
ASCII 2713
44.1%
None 11
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1055
38.9%
1 315
 
11.6%
- 214
 
7.9%
2 194
 
7.2%
3 153
 
5.6%
0 151
 
5.6%
5 130
 
4.8%
4 125
 
4.6%
6 112
 
4.1%
9 97
 
3.6%
Other values (12) 167
 
6.2%
Hangul
ValueCountFrequency (%)
상 329
 
9.6%
동 303
 
8.8%
제 299
 
8.7%
거 298
 
8.7%
도 284
 
8.3%
시 282
 
8.2%
경 281
 
8.2%
남 280
 
8.2%
포 71
 
2.1%
현 69
 
2.0%
Other values (141) 928
27.1%
None
ValueCountFrequency (%)
， 11
100.0%

시설주소(도로명)
Text

Distinct299
Distinct (%)98.0%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-04-17T07:51:59.483277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length29.245902
Min length19

Characters and Unicode

Total characters8920
Distinct characters202
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique294 ?
Unique (%)96.4%

Sample

1st row경상남도 거제시 장평3로 80-45，1층 (장평동)
2nd row경상남도 거제시 장승로 145 (장승포동)
3rd row경상남도 거제시 장평3로 80-37 (장평동)
4th row경상남도 거제시 일운면 지세포3길 99
5th row경상남도 거제시 계룡로9길 21-2 (고현동，신원 아침의도시)
ValueCountFrequency (%)
경상남도 305
 
18.5%
거제시 305
 
18.5%
고현동 56
 
3.4%
장평동 40
 
2.4%
옥포동 33
 
2.0%
아주동 24
 
1.5%
수양로 21
 
1.3%
상동동 18
 
1.1%
2층 15
 
0.9%
수월동 15
 
0.9%
Other values (512) 814
49.5%
2024-04-17T07:51:59.878214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1341
 
15.0%
제 384
 
4.3%
거 378
 
4.2%
상 376
 
4.2%
동 367
 
4.1%
1 354
 
4.0%
남 313
 
3.5%
도 311
 
3.5%
경 309
 
3.5%
시 308
 
3.5%
Other values (192) 4479
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5070
56.8%
Decimal Number 1578
 
17.7%
Space Separator 1341
 
15.0%
Other Punctuation 305
 
3.4%
Open Punctuation 271
 
3.0%
Close Punctuation 271
 
3.0%
Dash Punctuation 60
 
0.7%
Math Symbol 16
 
0.2%
Uppercase Letter 6
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 384
 
7.6%
거 378
 
7.5%
상 376
 
7.4%
동 367
 
7.2%
남 313
 
6.2%
도 311
 
6.1%
경 309
 
6.1%
시 308
 
6.1%
로 272
 
5.4%
층 176
 
3.5%
Other values (168) 1876
37.0%
Decimal Number
ValueCountFrequency (%)
1 354
22.4%
2 290
18.4%
3 220
13.9%
0 167
10.6%
4 156
9.9%
5 127
 
8.0%
7 83
 
5.3%
6 67
 
4.2%
8 66
 
4.2%
9 48
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
16.7%
K 1
16.7%
A 1
16.7%
P 1
16.7%
I 1
16.7%
R 1
16.7%
Other Punctuation
ValueCountFrequency (%)
， 304
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1341
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Close Punctuation
ValueCountFrequency (%)
) 271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5070
56.8%
Common 3842
43.1%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 384
 
7.6%
거 378
 
7.5%
상 376
 
7.4%
동 367
 
7.2%
남 313
 
6.2%
도 311
 
6.1%
경 309
 
6.1%
시 308
 
6.1%
로 272
 
5.4%
층 176
 
3.5%
Other values (168) 1876
37.0%
Common
ValueCountFrequency (%)
1341
34.9%
1 354
 
9.2%
， 304
 
7.9%
2 290
 
7.5%
( 271
 
7.1%
) 271
 
7.1%
3 220
 
5.7%
0 167
 
4.3%
4 156
 
4.1%
5 127
 
3.3%
Other values (7) 341
 
8.9%
Latin
ValueCountFrequency (%)
e 2
25.0%
B 1
12.5%
K 1
12.5%
A 1
12.5%
P 1
12.5%
I 1
12.5%
R 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5070
56.8%
ASCII 3546
39.8%
None 304
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1341
37.8%
1 354
 
10.0%
2 290
 
8.2%
( 271
 
7.6%
) 271
 
7.6%
3 220
 
6.2%
0 167
 
4.7%
4 156
 
4.4%
5 127
 
3.6%
7 83
 
2.3%
Other values (13) 266
 
7.5%
Hangul
ValueCountFrequency (%)
제 384
 
7.6%
거 378
 
7.5%
상 376
 
7.4%
동 367
 
7.2%
남 313
 
6.2%
도 311
 
6.1%
경 309
 
6.1%
시 308
 
6.1%
로 272
 
5.4%
층 176
 
3.5%
Other values (168) 1876
37.0%
None
ValueCountFrequency (%)
， 304
100.0%

전화번호
Text

MISSING 

Distinct154
Distinct (%)98.1%
Missing149
Missing (%)48.7%
Memory size2.5 KiB
2024-04-17T07:52:00.099139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.968153
Min length9

Characters and Unicode

Total characters1879
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

Unique151 ?
Unique (%)96.2%

Sample

1st row055-630-5230
2nd row055-680-1000
3rd row055-631-2114
4th row1670-9977
5th row055-633-1989
ValueCountFrequency (%)
055-632-7004 2
 
1.3%
1670-9977 2
 
1.3%
055-681-7787 2
 
1.3%
055-636-6607 1
 
0.6%
055-630-1430 1
 
0.6%
055-687-4672 1
 
0.6%
055-687-4168 1
 
0.6%
055-630-5230 1
 
0.6%
055-688-2303 1
 
0.6%
055-635-7001 1
 
0.6%
Other values (144) 144
91.7%
2024-04-17T07:52:00.424871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 390
20.8%
- 312
16.6%
0 259
13.8%
6 229
12.2%
3 162
8.6%
8 142
 
7.6%
7 110
 
5.9%
1 86
 
4.6%
2 79
 
4.2%
4 60
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1567
83.4%
Dash Punctuation 312
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 390
24.9%
0 259
16.5%
6 229
14.6%
3 162
10.3%
8 142
 
9.1%
7 110
 
7.0%
1 86
 
5.5%
2 79
 
5.0%
4 60
 
3.8%
9 50
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1879
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 390
20.8%
- 312
16.6%
0 259
13.8%
6 229
12.2%
3 162
8.6%
8 142
 
7.6%
7 110
 
5.9%
1 86
 
4.6%
2 79
 
4.2%
4 60
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1879
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 390
20.8%
- 312
16.6%
0 259
13.8%
6 229
12.2%
3 162
8.6%
8 142
 
7.6%
7 110
 
5.9%
1 86
 
4.6%
2 79
 
4.2%
4 60
 
3.2%

기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2022-09-26
305 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9803922
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2022-09-26
2nd row2022-09-26
3rd row2022-09-26
4th row2022-09-26
5th row2022-09-26

Common Values

ValueCountFrequency (%)
2022-09-26 305
99.7%
<NA> 1
 
0.3%

Length

2024-04-17T07:52:00.538129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:52:00.618537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-26 305
99.7%
na 1
 
0.3%

Correlations

2024-04-17T07:52:00.666282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종
업종1.000
2024-04-17T07:52:00.727417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자업종
기준일자1.0001.000
업종1.0001.000
2024-04-17T07:52:00.795171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종기준일자
업종1.0001.000
기준일자1.0001.000

Missing values

2024-04-17T07:51:57.741649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T07:51:57.824617image/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.
2024-04-17T07:51:57.913116image/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

업종상호명시설주소(지번)시설주소(도로명)전화번호기준일자
0수영장업삼성문화관수영장경상남도 거제시 장평동 530경상남도 거제시 장평3로 80-45，1층 (장평동)055-630-52302022-09-26
1수영장업오션사이드수영장경상남도 거제시 장승포동 426-33경상남도 거제시 장승로 145 (장승포동)055-680-10002022-09-26
2수영장업삼성중공업 거제호텔 수영장경상남도 거제시 장평동 444-1경상남도 거제시 장평3로 80-37 (장평동)055-631-21142022-09-26
3수영장업이야짐<NA>경상남도 거제시 일운면 지세포3길 99<NA>2022-09-26
4수영장업신원아침도시 수영장<NA>경상남도 거제시 계룡로9길 21-2 (고현동，신원 아침의도시)<NA>2022-09-26
5수영장업한화리조트거제벨버디어 수영장경상남도 거제시 장목면 농소리 25경상남도 거제시 장목면 거제북로 2501-40，지하3층<NA>2022-09-26
6수영장업한화리조트거제벨버디어 인피니티풀경상남도 거제시 장목면 농소리 25경상남도 거제시 장목면 거제북로 2501-40，17층1670-99772022-09-26
7수영장업찬스아이수영장 상동분원경상남도 거제시 상동동 483-7경상남도 거제시 거제중앙로 1739，찬스아이수영장 (상동동)055-633-19892022-09-26
8수영장업프리라움 수영장경상남도 거제시 수월동 1043-110경상남도 거제시 수양로 456-7，지하1층 (수월동)<NA>2022-09-26
9체육도장업거제소나무향기 태권도장경상남도 거제시 거제면 동상리 488-3경상남도 거제시 거제면 읍내로 25<NA>2022-09-26
업종상호명시설주소(지번)시설주소(도로명)전화번호기준일자
296가상체험 체육시설업상문 스크린골프경상남도 거제시 문동동 326-1경상남도 거제시 수양로 52 (문동동)<NA>2022-09-26
297가상체험 체육시설업홀인원스크린골프경상남도 거제시 장평동 1212-3경상남도 거제시 장평로 16-12，501，502호 (장평동)055-635-22112022-09-26
298가상체험 체육시설업스마트골프 아카데미경상남도 거제시 장평동 56-1 장평종합상가경상남도 거제시 장평로 37，장평종합상가 278호 (장평동)055-633-19802022-09-26
299가상체험 체육시설업대보 스크린경상남도 거제시 수월동 675-3경상남도 거제시 수월2길 13-24，2，3층 (수월동)<NA>2022-09-26
300가상체험 체육시설업이상수 골프아카데미경상남도 거제시 연초면 연사리 1369-1경상남도 거제시 연초면 거제대로 4447，2층<NA>2022-09-26
301체육교습업킹콩플러스 축구교실경상남도 거제시 상동동 224경상남도 거제시 상동5길 7，2층 (상동동)<NA>2022-09-26
302체육교습업케넥스 축구교실경상남도 거제시 수월동 1043-110경상남도 거제시 수양로 456-7，2층 (수월동)<NA>2022-09-26
303체육교습업경남FC 유소년 축구교실경상남도 거제시 고현동 1084-8경상남도 거제시 거제대로 4500-55，3층 (고현동)<NA>2022-09-26
304체육교습업에이원 축구클럽경상남도 거제시 상동동 925-3경상남도 거제시 상동5길 115，1동 지하1층 (상동동)<NA>2022-09-26
305<NA><NA><NA><NA><NA><NA>