Overview

Dataset statistics

Number of variables10
Number of observations104
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory84.3 B

Variable types

Text3
Categorical5
Numeric1
DateTime1

Dataset

Description경상남도 거제시 현수막 게시대(공공용, 상업용) 현황 자료입니다. 현수막 게시대의 고유번호, 설치장소, 규격 등의 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079327

Alerts

규격(가로x세로) has constant value ""Constant
기준일 has constant value ""Constant
면 is highly overall correlated with 열High correlation
열 is highly overall correlated with 면High correlation
열 is highly imbalanced (52.4%)Imbalance

Reproduction

Analysis started2023-12-10 23:27:21.631968
Analysis finished2023-12-10 23:27:22.944988
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Text

Distinct83
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-11T08:27:23.164318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5576923
Min length4

Characters and Unicode

Total characters474
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)61.5%

Sample

1st row행1-1
2nd row행1-2
3rd row행1-3
4th row행1-4
5th row행1-5
ValueCountFrequency (%)
행1-1 4
 
3.8%
행3-1 2
 
1.9%
행7-2 2
 
1.9%
행4-17 2
 
1.9%
행9-2 2
 
1.9%
행12-1 2
 
1.9%
행11-2 2
 
1.9%
행11-1 2
 
1.9%
행9-3 2
 
1.9%
행8-1 2
 
1.9%
Other values (73) 82
78.8%
2023-12-11T08:27:23.604918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 114
24.1%
행 104
21.9%
- 104
21.9%
2 29
 
6.1%
3 24
 
5.1%
4 21
 
4.4%
7 20
 
4.2%
6 18
 
3.8%
5 17
 
3.6%
9 13
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 266
56.1%
Other Letter 104
 
21.9%
Dash Punctuation 104
 
21.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 114
42.9%
2 29
 
10.9%
3 24
 
9.0%
4 21
 
7.9%
7 20
 
7.5%
6 18
 
6.8%
5 17
 
6.4%
9 13
 
4.9%
8 10
 
3.8%
Other Letter
ValueCountFrequency (%)
행 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 370
78.1%
Hangul 104
 
21.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 114
30.8%
- 104
28.1%
2 29
 
7.8%
3 24
 
6.5%
4 21
 
5.7%
7 20
 
5.4%
6 18
 
4.9%
5 17
 
4.6%
9 13
 
3.5%
8 10
 
2.7%
Hangul
ValueCountFrequency (%)
행 104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 370
78.1%
Hangul 104
 
21.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 114
30.8%
- 104
28.1%
2 29
 
7.8%
3 24
 
6.5%
4 21
 
5.7%
7 20
 
5.4%
6 18
 
4.9%
5 17
 
4.6%
9 13
 
3.5%
8 10
 
2.7%
Hangul
ValueCountFrequency (%)
행 104
100.0%

읍면동
Categorical

Distinct18
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size964.0 B
고현동
13 
장승포동
11 
사등면
9 
옥포2동
8 
아주동
8 
Other values (13)
55 

Length

Max length4
Median length3
Mean length3.2211538
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고현동 13
12.5%
장승포동 11
10.6%
사등면 9
 
8.7%
옥포2동 8
 
7.7%
아주동 8
 
7.7%
장목면 7
 
6.7%
일운면 7
 
6.7%
상문동 6
 
5.8%
수양동 6
 
5.8%
거제면 6
 
5.8%
Other values (8) 23
22.1%

Length

2023-12-11T08:27:23.770855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고현동 13
12.5%
장승포동 11
10.6%
사등면 9
 
8.7%
옥포2동 8
 
7.7%
아주동 8
 
7.7%
장목면 7
 
6.7%
일운면 7
 
6.7%
수양동 6
 
5.8%
거제면 6
 
5.8%
상문동 6
 
5.8%
Other values (8) 23
22.1%

설치장소
Text

Distinct80
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-11T08:27:24.033257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.8942308
Min length3

Characters and Unicode

Total characters925
Distinct characters161
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

Unique69 ?
Unique (%)66.3%

Sample

1st row거원아파트 앞 국도변
2nd row일운주유소 앞 국도변
3rd row구조라 입구 국도변
4th row소동리 동성(아) 입구
5th row구조라 수정마을
ValueCountFrequency (%)
앞 22
 
10.0%
입구 15
 
6.8%
주변 13
 
5.9%
내 12
 
5.4%
면사무소 11
 
5.0%
동사무소 8
 
3.6%
국도변 6
 
2.7%
옆 4
 
1.8%
삼거리 4
 
1.8%
사곡삼거리 3
 
1.4%
Other values (106) 123
55.7%
2023-12-11T08:27:24.497185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
13.1%
소 28
 
3.0%
사 26
 
2.8%
주 26
 
2.8%
구 26
 
2.8%
입 24
 
2.6%
변 23
 
2.5%
앞 23
 
2.5%
아 20
 
2.2%
) 20
 
2.2%
Other values (151) 588
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 748
80.9%
Space Separator 121
 
13.1%
Close Punctuation 20
 
2.2%
Open Punctuation 20
 
2.2%
Decimal Number 8
 
0.9%
Uppercase Letter 6
 
0.6%
Other Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 28
 
3.7%
사 26
 
3.5%
주 26
 
3.5%
구 26
 
3.5%
입 24
 
3.2%
변 23
 
3.1%
앞 23
 
3.1%
아 20
 
2.7%
리 20
 
2.7%
무 19
 
2.5%
Other values (139) 513
68.6%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
2 3
37.5%
7 1
 
12.5%
4 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
C 2
33.3%
T 2
33.3%
Space Separator
ValueCountFrequency (%)
121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 748
80.9%
Common 170
 
18.4%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 28
 
3.7%
사 26
 
3.5%
주 26
 
3.5%
구 26
 
3.5%
입 24
 
3.2%
변 23
 
3.1%
앞 23
 
3.1%
아 20
 
2.7%
리 20
 
2.7%
무 19
 
2.5%
Other values (139) 513
68.6%
Common
ValueCountFrequency (%)
121
71.2%
) 20
 
11.8%
( 20
 
11.8%
1 3
 
1.8%
2 3
 
1.8%
7 1
 
0.6%
4 1
 
0.6%
. 1
 
0.6%
Latin
ValueCountFrequency (%)
K 2
28.6%
C 2
28.6%
T 2
28.6%
e 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 748
80.9%
ASCII 177
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
68.4%
) 20
 
11.3%
( 20
 
11.3%
1 3
 
1.7%
2 3
 
1.7%
K 2
 
1.1%
C 2
 
1.1%
T 2
 
1.1%
7 1
 
0.6%
4 1
 
0.6%
Other values (2) 2
 
1.1%
Hangul
ValueCountFrequency (%)
소 28
 
3.7%
사 26
 
3.5%
주 26
 
3.5%
구 26
 
3.5%
입 24
 
3.2%
변 23
 
3.1%
앞 23
 
3.1%
아 20
 
2.7%
리 20
 
2.7%
무 19
 
2.5%
Other values (139) 513
68.6%

열
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size964.0 B
1
83 
2
14 
3
 
6
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 83
79.8%
2 14
 
13.5%
3 6
 
5.8%
6 1
 
1.0%

Length

2023-12-11T08:27:24.652275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:27:24.750123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 83
79.8%
2 14
 
13.5%
3 6
 
5.8%
6 1
 
1.0%

단
Categorical

Distinct5
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size964.0 B
5
57 
4
22 
2
10 
3
10 
6
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row5
4th row5
5th row2

Common Values

ValueCountFrequency (%)
5 57
54.8%
4 22
 
21.2%
2 10
 
9.6%
3 10
 
9.6%
6 5
 
4.8%

Length

2023-12-11T08:27:24.839844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:27:24.967319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 57
54.8%
4 22
 
21.2%
2 10
 
9.6%
3 10
 
9.6%
6 5
 
4.8%

면
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8269231
Minimum2
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T08:27:25.107536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median5
Q36
95-th percentile11.7
Maximum24
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.3105958
Coefficient of variation (CV)0.56815506
Kurtosis8.4066523
Mean5.8269231
Median Absolute Deviation (MAD)1
Skewness2.2831528
Sum606
Variance10.960045
MonotonicityNot monotonic
2023-12-11T08:27:25.221775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5 42
40.4%
4 14
 
13.5%
10 12
 
11.5%
2 10
 
9.6%
6 8
 
7.7%
3 7
 
6.7%
8 4
 
3.8%
12 3
 
2.9%
15 2
 
1.9%
9 1
 
1.0%
ValueCountFrequency (%)
2 10
 
9.6%
3 7
 
6.7%
4 14
 
13.5%
5 42
40.4%
6 8
 
7.7%
8 4
 
3.8%
9 1
 
1.0%
10 12
 
11.5%
12 3
 
2.9%
15 2
 
1.9%
ValueCountFrequency (%)
24 1
 
1.0%
15 2
 
1.9%
12 3
 
2.9%
10 12
 
11.5%
9 1
 
1.0%
8 4
 
3.8%
6 8
 
7.7%
5 42
40.4%
4 14
 
13.5%
3 7
 
6.7%

규격(가로x세로)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
5.2x0.7m
104 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.2x0.7m
2nd row5.2x0.7m
3rd row5.2x0.7m
4th row5.2x0.7m
5th row5.2x0.7m

Common Values

ValueCountFrequency (%)
5.2x0.7m 104
100.0%

Length

2023-12-11T08:27:25.347084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:27:25.432250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.2x0.7m 104
100.0%

주소
Text

Distinct93
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-11T08:27:25.722568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length19.884615
Min length15

Characters and Unicode

Total characters2068
Distinct characters77
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)78.8%

Sample

1st row경상남도 거제시 일운면 지세포리 758
2nd row경상남도 거제시 일운면 지세포리 808-4
3rd row경상남도 거제시 일운면 구조라리 28-1
4th row경상남도 거제시 일운면 소동리 산66-2
5th row경상남도 거제시 일운면 구조라리 97-11
ValueCountFrequency (%)
경상남도 104
22.7%
거제시 104
22.7%
고현동 13
 
2.8%
장승포동 11
 
2.4%
옥포동 10
 
2.2%
사등면 9
 
2.0%
일운면 7
 
1.5%
아주동 7
 
1.5%
장목면 7
 
1.5%
거제면 6
 
1.3%
Other values (129) 181
39.4%
2023-12-11T08:27:26.218113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
356
17.2%
도 116
 
5.6%
상 111
 
5.4%
거 110
 
5.3%
제 110
 
5.3%
남 107
 
5.2%
시 104
 
5.0%
경 104
 
5.0%
- 77
 
3.7%
1 72
 
3.5%
Other values (67) 801
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1216
58.8%
Decimal Number 395
 
19.1%
Space Separator 356
 
17.2%
Dash Punctuation 77
 
3.7%
Open Punctuation 12
 
0.6%
Close Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 116
 
9.5%
상 111
 
9.1%
거 110
 
9.0%
제 110
 
9.0%
남 107
 
8.8%
시 104
 
8.6%
경 104
 
8.6%
동 72
 
5.9%
면 44
 
3.6%
리 43
 
3.5%
Other values (53) 295
24.3%
Decimal Number
ValueCountFrequency (%)
1 72
18.2%
4 50
12.7%
2 48
12.2%
3 45
11.4%
8 41
10.4%
9 32
8.1%
0 28
 
7.1%
7 27
 
6.8%
5 27
 
6.8%
6 25
 
6.3%
Space Separator
ValueCountFrequency (%)
356
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1216
58.8%
Common 852
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 116
 
9.5%
상 111
 
9.1%
거 110
 
9.0%
제 110
 
9.0%
남 107
 
8.8%
시 104
 
8.6%
경 104
 
8.6%
동 72
 
5.9%
면 44
 
3.6%
리 43
 
3.5%
Other values (53) 295
24.3%
Common
ValueCountFrequency (%)
356
41.8%
- 77
 
9.0%
1 72
 
8.5%
4 50
 
5.9%
2 48
 
5.6%
3 45
 
5.3%
8 41
 
4.8%
9 32
 
3.8%
0 28
 
3.3%
7 27
 
3.2%
Other values (4) 76
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1216
58.8%
ASCII 852
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
356
41.8%
- 77
 
9.0%
1 72
 
8.5%
4 50
 
5.9%
2 48
 
5.6%
3 45
 
5.3%
8 41
 
4.8%
9 32
 
3.8%
0 28
 
3.3%
7 27
 
3.2%
Other values (4) 76
 
8.9%
Hangul
ValueCountFrequency (%)
도 116
 
9.5%
상 111
 
9.1%
거 110
 
9.0%
제 110
 
9.0%
남 107
 
8.8%
시 104
 
8.6%
경 104
 
8.6%
동 72
 
5.9%
면 44
 
3.6%
리 43
 
3.5%
Other values (53) 295
24.3%

비고
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
상업용
69 
행정용
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상업용 69
66.3%
행정용 35
33.7%

Length

2023-12-11T08:27:26.347008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:27:26.445444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 69
66.3%
행정용 35
33.7%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum2020-07-31 00:00:00
Maximum2020-07-31 00:00:00
2023-12-11T08:27:26.528963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:27:26.616071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T08:27:22.581462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:27:26.685146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호읍면동설치장소열단면주소비고
고유번호1.0000.9970.9870.9240.3260.7350.9840.000
읍면동0.9971.0000.7360.0000.0400.0001.0000.000
설치장소0.9870.7361.0000.9290.1940.8510.9980.945
열0.9240.0000.9291.0000.0270.9200.0000.309
단0.3260.0400.1940.0271.0000.6450.0000.278
면0.7350.0000.8510.9200.6451.0000.0000.361
주소0.9841.0000.9980.0000.0000.0001.0000.784
비고0.0000.0000.9450.3090.2780.3610.7841.000
2023-12-11T08:27:26.812634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단열비고읍면동
단1.0000.0090.3340.000
열0.0091.0000.2030.000
비고0.3340.2031.0000.000
읍면동0.0000.0000.0001.000
2023-12-11T08:27:26.931145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면읍면동열단비고
면1.0000.0000.8800.4820.377
읍면동0.0001.0000.0000.0000.000
열0.8800.0001.0000.0090.203
단0.4820.0000.0091.0000.334
비고0.3770.0000.2030.3341.000

Missing values

2023-12-11T08:27:22.707644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:27:22.877457image/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

고유번호읍면동설치장소열단면규격(가로x세로)주소비고기준일
0행1-1일운면거원아파트 앞 국도변1445.2x0.7m경상남도 거제시 일운면 지세포리 758상업용2020-07-31
1행1-2일운면일운주유소 앞 국도변1445.2x0.7m경상남도 거제시 일운면 지세포리 808-4상업용2020-07-31
2행1-3일운면구조라 입구 국도변1555.2x0.7m경상남도 거제시 일운면 구조라리 28-1상업용2020-07-31
3행1-4일운면소동리 동성(아) 입구1555.2x0.7m경상남도 거제시 일운면 소동리 산66-2상업용2020-07-31
4행1-5일운면구조라 수정마을1225.2x0.7m경상남도 거제시 일운면 구조라리 97-11상업용2020-07-31
5행1-6일운면대명리조트 뒷편1665.2x0.7m경상남도 거제시 일운면 소동리 산14-14상업용2020-07-31
6행2-1동부면오망천 주변1565.2x0.7m경상남도 거제시 동부면 산양리 945-8상업용2020-07-31
7행3-1남부면저구 주유소 주변1555.2x0.7m경상남도 거제시 남부면 저구리 2-5상업용2020-07-31
8행4-1거제면서정마을(제일고옆)입구2485.2x0.7m경상남도 거제시 거제면 서정리 545-3상업용2020-07-31
9행4-2거제면죽림마을 삼거리1445.2x0.7m경상남도 거제시 거제면 동상리 107(구)상업용2020-07-31
고유번호읍면동설치장소열단면규격(가로x세로)주소비고기준일
94행17-2고현동신현 2교(국도14호선)1225.2x0.7m경상남도 거제시 고현동 1024-1(도)행정용2020-07-31
95행17-3고현동중곡초교 교차로(덕산1차상가)1225.2x0.7m경상남도 거제시 고현동 1047행정용2020-07-31
96행17-4고현동금곡교 입구1225.2x0.7m경상남도 거제시 고현동 71-3행정용2020-07-31
97행17-5고현동중곡육교 주변(7열)1445.2x0.7m경상남도 거제시 고현동 2-2행정용2020-07-31
98행17-6고현동보조운동장앞1225.2x0.7m경상남도 거제시 고현동 906행정용2020-07-31
99행17-7고현동고현시외버스터미널 앞1555.2x0.7m경상남도 거제시 고현동 983(도)행정용2020-07-31
100행18-1상문동동사무소 앞1555.2x0.7m경상남도 거제시 상동동 167-2(도)행정용2020-07-31
101행18-2상문동독봉산웰빙공원 입구1555.2x0.7m경상남도 거제시 상동동 385-5(도)행정용2020-07-31
102행18-3상문동포스코아파트 앞1555.2x0.7m경상남도 거제시 상동동 912-5(도)행정용2020-07-31
103행19-1수양동동사무소 앞1445.2x0.7m경상남도 거제시 양정동 859-1행정용2020-07-31