Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells3
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory79.7 B

Variable types

Categorical3
Text3
Numeric2
DateTime1

Dataset

Description경상남도 거제시 유원시설업현황(영업종류, 상호명, 소재지, 위도, 경도, 전화번호, 영업상태, 신고일자, 기준일자)등에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079557

Alerts

영업상태 has constant value ""Constant
기준일자 has constant value ""Constant
위도 is highly overall correlated with 영업종류High correlation
영업종류 is highly overall correlated with 위도High correlation
영업종류 is highly imbalanced (67.6%)Imbalance
전화번호 has 3 (13.0%) missing valuesMissing
상호명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:19:46.471703
Analysis finished2023-12-10 23:19:47.515432
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

영업종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
기타유원시설업
21 
종합유원시설업
 
1
일반유원시설업
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique2 ?
Unique (%)8.7%

Sample

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

Common Values

ValueCountFrequency (%)
기타유원시설업 21
91.3%
종합유원시설업 1
 
4.3%
일반유원시설업 1
 
4.3%

Length

2023-12-11T08:19:47.593458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:19:47.704749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타유원시설업 21
91.3%
종합유원시설업 1
 
4.3%
일반유원시설업 1
 
4.3%

상호명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T08:19:47.921370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length7.5217391
Min length3

Characters and Unicode

Total characters173
Distinct characters84
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row노리파크 거제상동점
2nd row롤리폴리(옥포점)
3rd row차타타 거제장평점
4th row아지트
5th row야사노(거제옥포점)
ValueCountFrequency (%)
상동점 2
 
5.9%
점핑스타 2
 
5.9%
라크씨엘 2
 
5.9%
노리파크 1
 
2.9%
블루매직랜드 1
 
2.9%
거제랜드 1
 
2.9%
오션어드벤처 1
 
2.9%
벨르앙쥬 1
 
2.9%
주)잼놀 1
 
2.9%
벽산점 1
 
2.9%
Other values (21) 21
61.8%
2023-12-11T08:19:48.308242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
6.4%
점 11
 
6.4%
거 7
 
4.0%
제 7
 
4.0%
스 6
 
3.5%
타 5
 
2.9%
상 5
 
2.9%
동 5
 
2.9%
크 4
 
2.3%
드 4
 
2.3%
Other values (74) 108
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
90.2%
Space Separator 11
 
6.4%
Close Punctuation 3
 
1.7%
Open Punctuation 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 11
 
7.1%
거 7
 
4.5%
제 7
 
4.5%
스 6
 
3.8%
타 5
 
3.2%
상 5
 
3.2%
동 5
 
3.2%
크 4
 
2.6%
드 4
 
2.6%
랜 3
 
1.9%
Other values (71) 99
63.5%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
90.2%
Common 17
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 11
 
7.1%
거 7
 
4.5%
제 7
 
4.5%
스 6
 
3.8%
타 5
 
3.2%
상 5
 
3.2%
동 5
 
3.2%
크 4
 
2.6%
드 4
 
2.6%
랜 3
 
1.9%
Other values (71) 99
63.5%
Common
ValueCountFrequency (%)
11
64.7%
) 3
 
17.6%
( 3
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
90.2%
ASCII 17
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
64.7%
) 3
 
17.6%
( 3
 
17.6%
Hangul
ValueCountFrequency (%)
점 11
 
7.1%
거 7
 
4.5%
제 7
 
4.5%
스 6
 
3.8%
타 5
 
3.2%
상 5
 
3.2%
동 5
 
3.2%
크 4
 
2.6%
드 4
 
2.6%
랜 3
 
1.9%
Other values (71) 99
63.5%

소재지(도로명)
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T08:19:48.548786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length30.347826
Min length22

Characters and Unicode

Total characters698
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 상동7길 30-1 상가동 지하1층 101호 (상동동)
2nd row경상남도 거제시 옥포로 250 (옥포동)
3rd row경상남도 거제시 장평4로 63 (장평동)
4th row경상남도 거제시 덕포5길 26 (덕포동)
5th row경상남도 거제시 옥포로10길 24-1 2층 (옥포동)
ValueCountFrequency (%)
경상남도 23
 
16.0%
거제시 23
 
16.0%
상동동 7
 
4.9%
2층 5
 
3.5%
고현동 4
 
2.8%
일운면 3
 
2.1%
거제중앙로 3
 
2.1%
상동5길 3
 
2.1%
지하1층 2
 
1.4%
거제대로 2
 
1.4%
Other values (65) 69
47.9%
2023-12-11T08:19:48.966842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
17.3%
상 35
 
5.0%
1 33
 
4.7%
거 33
 
4.7%
제 33
 
4.7%
동 33
 
4.7%
경 23
 
3.3%
남 23
 
3.3%
도 23
 
3.3%
시 23
 
3.3%
Other values (90) 318
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
57.4%
Decimal Number 122
 
17.5%
Space Separator 121
 
17.3%
Open Punctuation 19
 
2.7%
Close Punctuation 19
 
2.7%
Dash Punctuation 6
 
0.9%
Uppercase Letter 6
 
0.9%
Math Symbol 2
 
0.3%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 35
 
8.7%
거 33
 
8.2%
제 33
 
8.2%
동 33
 
8.2%
경 23
 
5.7%
남 23
 
5.7%
도 23
 
5.7%
시 23
 
5.7%
로 18
 
4.5%
층 10
 
2.5%
Other values (67) 147
36.7%
Decimal Number
ValueCountFrequency (%)
1 33
27.0%
2 22
18.0%
0 17
13.9%
4 13
 
10.7%
5 11
 
9.0%
6 9
 
7.4%
3 7
 
5.7%
8 5
 
4.1%
7 4
 
3.3%
9 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
16.7%
R 1
16.7%
A 1
16.7%
I 1
16.7%
P 1
16.7%
B 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
， 1
50.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 401
57.4%
Common 291
41.7%
Latin 6
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 35
 
8.7%
거 33
 
8.2%
제 33
 
8.2%
동 33
 
8.2%
경 23
 
5.7%
남 23
 
5.7%
도 23
 
5.7%
시 23
 
5.7%
로 18
 
4.5%
층 10
 
2.5%
Other values (67) 147
36.7%
Common
ValueCountFrequency (%)
121
41.6%
1 33
 
11.3%
2 22
 
7.6%
( 19
 
6.5%
) 19
 
6.5%
0 17
 
5.8%
4 13
 
4.5%
5 11
 
3.8%
6 9
 
3.1%
3 7
 
2.4%
Other values (7) 20
 
6.9%
Latin
ValueCountFrequency (%)
K 1
16.7%
R 1
16.7%
A 1
16.7%
I 1
16.7%
P 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 401
57.4%
ASCII 296
42.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
40.9%
1 33
 
11.1%
2 22
 
7.4%
( 19
 
6.4%
) 19
 
6.4%
0 17
 
5.7%
4 13
 
4.4%
5 11
 
3.7%
6 9
 
3.0%
3 7
 
2.4%
Other values (12) 25
 
8.4%
Hangul
ValueCountFrequency (%)
상 35
 
8.7%
거 33
 
8.2%
제 33
 
8.2%
동 33
 
8.2%
경 23
 
5.7%
남 23
 
5.7%
도 23
 
5.7%
시 23
 
5.7%
로 18
 
4.5%
층 10
 
2.5%
Other values (67) 147
36.7%
None
ValueCountFrequency (%)
， 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.878613
Minimum34.795334
Maximum35.007888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T08:19:49.112247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.795334
5-th percentile34.83579
Q134.865299
median34.876107
Q334.891126
95-th percentile34.910546
Maximum35.007888
Range0.212554
Interquartile range (IQR)0.025828

Descriptive statistics

Standard deviation0.037237368
Coefficient of variation (CV)0.0010676275
Kurtosis6.932173
Mean34.878613
Median Absolute Deviation (MAD)0.014902
Skewness1.4430774
Sum802.20811
Variance0.0013866216
MonotonicityNot monotonic
2023-12-11T08:19:49.224823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
34.869281 1
 
4.3%
34.896917 1
 
4.3%
34.889276 1
 
4.3%
34.834901 1
 
4.3%
34.87638 1
 
4.3%
34.843791 1
 
4.3%
34.87348 1
 
4.3%
34.874262 1
 
4.3%
34.861205 1
 
4.3%
34.87889 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
34.795334 1
4.3%
34.834901 1
4.3%
34.843791 1
4.3%
34.86044 1
4.3%
34.861205 1
4.3%
34.863695 1
4.3%
34.866902 1
4.3%
34.868057 1
4.3%
34.869281 1
4.3%
34.87348 1
4.3%
ValueCountFrequency (%)
35.007888 1
4.3%
34.91206 1
4.3%
34.896917 1
4.3%
34.895834 1
4.3%
34.893997 1
4.3%
34.891197 1
4.3%
34.891056 1
4.3%
34.889276 1
4.3%
34.887155 1
4.3%
34.87889 1
4.3%

경도
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65266
Minimum128.60862
Maximum128.71212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T08:19:49.390476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.60862
5-th percentile128.61723
Q1128.62715
median128.63327
Q3128.68992
95-th percentile128.70953
Maximum128.71212
Range0.1035
Interquartile range (IQR)0.062768

Descriptive statistics

Standard deviation0.034218827
Coefficient of variation (CV)0.00026597838
Kurtosis-1.2123397
Mean128.65266
Median Absolute Deviation (MAD)0.008793
Skewness0.67718278
Sum2959.0113
Variance0.0011709282
MonotonicityNot monotonic
2023-12-11T08:19:49.532455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
128.631956 1
 
4.3%
128.689927 1
 
4.3%
128.624681 1
 
4.3%
128.701622 1
 
4.3%
128.625371 1
 
4.3%
128.702943 1
 
4.3%
128.689907 1
 
4.3%
128.632964 1
 
4.3%
128.629615 1
 
4.3%
128.627763 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
128.608619 1
4.3%
128.616402 1
4.3%
128.624681 1
4.3%
128.625371 1
4.3%
128.626088 1
4.3%
128.626535 1
4.3%
128.627763 1
4.3%
128.629615 1
4.3%
128.631244 1
4.3%
128.631956 1
4.3%
ValueCountFrequency (%)
128.712119 1
4.3%
128.710263 1
4.3%
128.702943 1
4.3%
128.701622 1
4.3%
128.694136 1
4.3%
128.689927 1
4.3%
128.689907 1
4.3%
128.665854 1
4.3%
128.650058 1
4.3%
128.642063 1
4.3%

전화번호
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing3
Missing (%)13.0%
Memory size316.0 B
2023-12-11T08:19:49.733515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.1
Min length12

Characters and Unicode

Total characters242
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

Unique20 ?
Unique (%)100.0%

Sample

1st row055-632-7959
2nd row055-688-0234
3rd row055-636-1734
4th row055-687-1030
5th row055-641-9900
ValueCountFrequency (%)
055-634-0060 1
 
5.0%
055-636-1734 1
 
5.0%
055-632-5486 1
 
5.0%
055-733-7201 1
 
5.0%
0507-1471-1204 1
 
5.0%
055-645-3412 1
 
5.0%
055-634-0860 1
 
5.0%
055-634-2773 1
 
5.0%
055-637-5553 1
 
5.0%
055-638-0226 1
 
5.0%
Other values (10) 10
50.0%
2023-12-11T08:19:50.207656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 52
21.5%
0 41
16.9%
- 40
16.5%
6 24
9.9%
3 22
9.1%
7 13
 
5.4%
4 12
 
5.0%
1 11
 
4.5%
8 11
 
4.5%
2 9
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
83.5%
Dash Punctuation 40
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 52
25.7%
0 41
20.3%
6 24
11.9%
3 22
10.9%
7 13
 
6.4%
4 12
 
5.9%
1 11
 
5.4%
8 11
 
5.4%
2 9
 
4.5%
9 7
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 52
21.5%
0 41
16.9%
- 40
16.5%
6 24
9.9%
3 22
9.1%
7 13
 
5.4%
4 12
 
5.0%
1 11
 
4.5%
8 11
 
4.5%
2 9
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 52
21.5%
0 41
16.9%
- 40
16.5%
6 24
9.9%
3 22
9.1%
7 13
 
5.4%
4 12
 
5.0%
1 11
 
4.5%
8 11
 
4.5%
2 9
 
3.7%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
영업중
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 23
100.0%

Length

2023-12-11T08:19:50.375274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:19:50.482796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 23
100.0%

허가(신고)일자
Date

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2013-06-12 00:00:00
Maximum2021-06-07 00:00:00
2023-12-11T08:19:50.626402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:50.770478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2021-09-06
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-06
2nd row2021-09-06
3rd row2021-09-06
4th row2021-09-06
5th row2021-09-06

Common Values

ValueCountFrequency (%)
2021-09-06 23
100.0%

Length

2023-12-11T08:19:50.994224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:19:51.098736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-06 23
100.0%

Interactions

2023-12-11T08:19:47.059922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:46.845621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:47.153575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:46.963308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:19:51.179299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업종류상호명소재지(도로명)위도경도전화번호허가(신고)일자
영업종류1.0001.0001.0000.6860.0001.0001.000
상호명1.0001.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.0001.0001.000
위도0.6861.0001.0001.0000.6901.0000.000
경도0.0001.0001.0000.6901.0001.0000.783
전화번호1.0001.0001.0001.0001.0001.0001.000
허가(신고)일자1.0001.0001.0000.0000.7831.0001.000
2023-12-11T08:19:51.317223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도영업종류
위도1.000-0.0420.526
경도-0.0421.0000.000
영업종류0.5260.0001.000

Missing values

2023-12-11T08:19:47.279436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:19:47.458584image/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

영업종류상호명소재지(도로명)위도경도전화번호영업상태허가(신고)일자기준일자
0기타유원시설업노리파크 거제상동점경상남도 거제시 상동7길 30-1 상가동 지하1층 101호 (상동동)34.869281128.631956055-632-7959영업중2014-08-072021-09-06
1기타유원시설업롤리폴리(옥포점)경상남도 거제시 옥포로 250 (옥포동)34.896917128.689927055-688-0234영업중2014-09-112021-09-06
2기타유원시설업차타타 거제장평점경상남도 거제시 장평4로 63 (장평동)34.887155128.608619055-636-1734영업중2017-01-192021-09-06
3기타유원시설업아지트경상남도 거제시 덕포5길 26 (덕포동)34.91206128.710263<NA>영업중2017-07-122021-09-06
4기타유원시설업야사노(거제옥포점)경상남도 거제시 옥포로10길 24-1 2층 (옥포동)34.891197128.694136055-687-1030영업중2017-08-252021-09-06
5기타유원시설업슈슈봉봉 거제점경상남도 거제시 중곡1로 48 해원빌딩 2층 (고현동)34.895834128.626088055-641-9900영업중2018-09-192021-09-06
6기타유원시설업바운스경상남도 거제시 장목면 거제북로 2501-40 한화리조트거제벨버디어35.007888128.712119055-635-0150영업중2018-09-212021-09-06
7기타유원시설업상동키즈랜드경상남도 거제시 상동5길 117-40 210호 (상동동)34.86044128.63327055-635-3995영업중2018-10-182021-09-06
8기타유원시설업라크씨엘경상남도 거제시 수양로 448-21 세정빌딩 201호 (수월동)34.893997128.642063055-637-5486영업중2018-11-212021-09-06
9기타유원시설업상문동 행복누림문화센터 놀이방경상남도 거제시 거제중앙로 1641 행복누림문화센터 2층 (상동동)34.868057128.637854055-636-7130영업중2019-03-272021-09-06
영업종류상호명소재지(도로명)위도경도전화번호영업상태허가(신고)일자기준일자
13기타유원시설업수영하는 아기경상남도 거제시 수양로 110 601동 B201~3호 (양정동 거제2차 IPARK)34.866902128.650058055-638-0226영업중2019-10-012021-09-06
14기타유원시설업점핑스타 상동점경상남도 거제시 계룡로 56 2층 (상동동)34.876107128.626535055-637-5553영업중2019-12-122021-09-06
15기타유원시설업트램폴린파크경상남도 거제시 거제중앙로 1793 하람빌딩 2층 (고현동)34.87889128.627763055-634-2773영업중2019-12-192021-09-06
16기타유원시설업점핑스타 벽산점경상남도 거제시 상동5길 115 2동 4층 402~403호 (상동동)34.861205128.629615055-634-0860영업중2019-12-262021-09-06
17기타유원시설업(주)잼놀경상남도 거제시 거제중앙로 1726 지하1층 (상동동)34.874262128.632964055-645-3412영업중2020-05-182021-09-06
18기타유원시설업벨르앙쥬경상남도 거제시 용소1길 15 302호 (아주동)34.87348128.6899070507-1471-1204영업중2020-11-022021-09-06
19종합유원시설업오션어드벤처경상남도 거제시 일운면 거제대로 266034.843791128.702943055-733-7201영업중2013-06-122021-09-06
20일반유원시설업거제랜드경상남도 거제시 계룡로 61 거제포로수용소유적공원 (고현동)34.87638128.625371055-950-7885영업중2019-05-032021-09-06
21기타유원시설업블루매직랜드경상남도 거제시 일운면 지세포해안로 25，거제조선해양문화관34.834901128.701622<NA>영업중2021-06-072021-09-06
22기타유원시설업스타스페이스경상남도 거제시 고현로11길 20 (고현동, 엠파크)34.889276128.624681<NA>영업중2016-12-162021-09-06