Overview

Dataset statistics

Number of variables11
Number of observations62
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory91.1 B

Variable types

Text3
Categorical7
Numeric1

Dataset

Description경상남도 거제시 무인도서현황 관리번호, 도서명, 소재지, 지목, 면적, 관리유형, 소유자 등의 항목을 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079270

Alerts

소재지 has constant value ""Constant
기준일 has constant value ""Constant
면적(㎡) is highly overall correlated with 지목 and 1 other fieldsHigh correlation
면동 is highly overall correlated with 리High correlation
리 is highly overall correlated with 면동 and 1 other fieldsHigh correlation
지목 is highly overall correlated with 면적(㎡) High correlation
관리유형 is highly overall correlated with 리High correlation
소유자 is highly overall correlated with 면적(㎡) High correlation
지목 is highly imbalanced (54.1%)Imbalance
관리번호 has unique valuesUnique
도서명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:12:16.818947
Analysis finished2023-12-10 23:12:17.465461
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-11T08:12:17.619480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters682
Distinct characters15
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

Unique62 ?
Unique (%)100.0%

Sample

1st row경남-거제-12-01
2nd row경남-거제-12-02
3rd row경남-거제-12-03
4th row경남-거제-12-04
5th row경남-거제-12-05
ValueCountFrequency (%)
경남-거제-12-01 1
 
1.6%
경남-거제-12-46 1
 
1.6%
경남-거제-12-61 1
 
1.6%
경남-거제-12-34 1
 
1.6%
경남-거제-12-35 1
 
1.6%
경남-거제-12-36 1
 
1.6%
경남-거제-12-37 1
 
1.6%
경남-거제-12-38 1
 
1.6%
경남-거제-12-39 1
 
1.6%
경남-거제-12-40 1
 
1.6%
Other values (52) 52
83.9%
2023-12-11T08:12:17.909271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 186
27.3%
1 79
11.6%
2 79
11.6%
경 62
 
9.1%
남 62
 
9.1%
거 62
 
9.1%
제 62
 
9.1%
5 16
 
2.3%
3 16
 
2.3%
4 16
 
2.3%
Other values (5) 42
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 248
36.4%
Other Letter 248
36.4%
Dash Punctuation 186
27.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 79
31.9%
2 79
31.9%
5 16
 
6.5%
3 16
 
6.5%
4 16
 
6.5%
0 15
 
6.0%
6 9
 
3.6%
7 6
 
2.4%
8 6
 
2.4%
9 6
 
2.4%
Other Letter
ValueCountFrequency (%)
경 62
25.0%
남 62
25.0%
거 62
25.0%
제 62
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 434
63.6%
Hangul 248
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 186
42.9%
1 79
18.2%
2 79
18.2%
5 16
 
3.7%
3 16
 
3.7%
4 16
 
3.7%
0 15
 
3.5%
6 9
 
2.1%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 62
25.0%
남 62
25.0%
거 62
25.0%
제 62
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434
63.6%
Hangul 248
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 186
42.9%
1 79
18.2%
2 79
18.2%
5 16
 
3.7%
3 16
 
3.7%
4 16
 
3.7%
0 15
 
3.5%
6 9
 
2.1%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 62
25.0%
남 62
25.0%
거 62
25.0%
제 62
25.0%

도서명
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-11T08:12:18.109055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.7580645
Min length2

Characters and Unicode

Total characters357
Distinct characters85
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

Unique62 ?
Unique (%)100.0%

Sample

1st row북여도(1)
2nd row북여도(2)
3rd row남여도(1)
4th row남여도(2)
5th row소다포도
ValueCountFrequency (%)
북여도(1 1
 
1.6%
계도 1
 
1.6%
갈도 1
 
1.6%
소록도 1
 
1.6%
항도 1
 
1.6%
방화도 1
 
1.6%
유대도(1)(고래섬 1
 
1.6%
유대도(2 1
 
1.6%
유대도(3 1
 
1.6%
사두도 1
 
1.6%
Other values (52) 52
83.9%
2023-12-11T08:12:18.415627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 61
17.1%
) 45
 
12.6%
( 45
 
12.6%
대 20
 
5.6%
섬 17
 
4.8%
소 10
 
2.8%
병 8
 
2.2%
손 8
 
2.2%
1 7
 
2.0%
동 7
 
2.0%
Other values (75) 129
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 247
69.2%
Close Punctuation 45
 
12.6%
Open Punctuation 45
 
12.6%
Decimal Number 19
 
5.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 61
24.7%
대 20
 
8.1%
섬 17
 
6.9%
소 10
 
4.0%
병 8
 
3.2%
손 8
 
3.2%
동 7
 
2.8%
여 7
 
2.8%
사 4
 
1.6%
고 4
 
1.6%
Other values (67) 101
40.9%
Decimal Number
ValueCountFrequency (%)
1 7
36.8%
2 7
36.8%
3 3
15.8%
4 1
 
5.3%
5 1
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
69.2%
Common 110
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 61
24.7%
대 20
 
8.1%
섬 17
 
6.9%
소 10
 
4.0%
병 8
 
3.2%
손 8
 
3.2%
동 7
 
2.8%
여 7
 
2.8%
사 4
 
1.6%
고 4
 
1.6%
Other values (67) 101
40.9%
Common
ValueCountFrequency (%)
) 45
40.9%
( 45
40.9%
1 7
 
6.4%
2 7
 
6.4%
3 3
 
2.7%
4 1
 
0.9%
5 1
 
0.9%
, 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 247
69.2%
ASCII 110
30.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 61
24.7%
대 20
 
8.1%
섬 17
 
6.9%
소 10
 
4.0%
병 8
 
3.2%
손 8
 
3.2%
동 7
 
2.8%
여 7
 
2.8%
사 4
 
1.6%
고 4
 
1.6%
Other values (67) 101
40.9%
ASCII
ValueCountFrequency (%)
) 45
40.9%
( 45
40.9%
1 7
 
6.4%
2 7
 
6.4%
3 3
 
2.7%
4 1
 
0.9%
5 1
 
0.9%
, 1
 
0.9%

소재지
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
거제시
62 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
거제시 62
100.0%

Length

2023-12-11T08:12:18.521562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:18.604114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거제시 62
100.0%

면동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
남부면
18 
장목면
14 
사등면
9 
둔덕면
6 
하청면
6 
Other values (5)
9 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
남부면 18
29.0%
장목면 14
22.6%
사등면 9
14.5%
둔덕면 6
 
9.7%
하청면 6
 
9.7%
거제면 3
 
4.8%
일운면 2
 
3.2%
동부면 2
 
3.2%
옥포동 1
 
1.6%
장평동 1
 
1.6%

Length

2023-12-11T08:12:18.681601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:18.776256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부면 18
29.0%
장목면 14
22.6%
사등면 9
14.5%
둔덕면 6
 
9.7%
하청면 6
 
9.7%
거제면 3
 
4.8%
일운면 2
 
3.2%
동부면 2
 
3.2%
옥포동 1
 
1.6%
장평동 1
 
1.6%

리
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Memory size628.0 B
다포리
10 
창호리
6 
갈곶리
6 
연구리
4 
시방리
4 
Other values (20)
32 

Length

Max length4
Median length3
Mean length3.0483871
Min length3

Unique

Unique11 ?
Unique (%)17.7%

Sample

1st row갈곶리
2nd row갈곶리
3rd row갈곶리
4th row갈곶리
5th row다포리

Common Values

ValueCountFrequency (%)
다포리 10
16.1%
창호리 6
 
9.7%
갈곶리 6
 
9.7%
연구리 4
 
6.5%
시방리 4
 
6.5%
유호리 4
 
6.5%
학산리 3
 
4.8%
장목리 2
 
3.2%
탑포리 2
 
3.2%
<NA> 2
 
3.2%
Other values (15) 19
30.6%

Length

2023-12-11T08:12:18.883861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다포리 10
16.1%
갈곶리 6
 
9.7%
창호리 6
 
9.7%
연구리 4
 
6.5%
시방리 4
 
6.5%
유호리 4
 
6.5%
학산리 3
 
4.8%
외포리 2
 
3.2%
오량리 2
 
3.2%
법동리 2
 
3.2%
Other values (15) 19
30.6%

지번
Text

Distinct59
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-11T08:12:19.070227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.1935484
Min length2

Characters and Unicode

Total characters260
Distinct characters15
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

Unique56 ?
Unique (%)90.3%

Sample

1st row431
2nd row432
3rd row433
4th row434
5th row산23
ValueCountFrequency (%)
산23 2
 
3.2%
산91 2
 
3.2%
산97 2
 
3.2%
산46 1
 
1.6%
산22 1
 
1.6%
산167-1외1 1
 
1.6%
산49 1
 
1.6%
431 1
 
1.6%
산68외1 1
 
1.6%
산124-1외19 1
 
1.6%
Other values (50) 50
79.4%
2023-12-11T08:12:19.384271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 58
22.3%
1 49
18.8%
4 23
 
8.8%
2 22
 
8.5%
3 22
 
8.5%
외 14
 
5.4%
9 13
 
5.0%
5 12
 
4.6%
8 11
 
4.2%
- 11
 
4.2%
Other values (5) 25
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 175
67.3%
Other Letter 72
27.7%
Dash Punctuation 11
 
4.2%
Space Separator 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
28.0%
4 23
13.1%
2 22
12.6%
3 22
12.6%
9 13
 
7.4%
5 12
 
6.9%
8 11
 
6.3%
7 10
 
5.7%
6 9
 
5.1%
0 4
 
2.3%
Other Letter
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 188
72.3%
Hangul 72
 
27.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
26.1%
4 23
12.2%
2 22
11.7%
3 22
11.7%
9 13
 
6.9%
5 12
 
6.4%
8 11
 
5.9%
- 11
 
5.9%
7 10
 
5.3%
6 9
 
4.8%
Other values (3) 6
 
3.2%
Hangul
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 188
72.3%
Hangul 72
 
27.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%
ASCII
ValueCountFrequency (%)
1 49
26.1%
4 23
12.2%
2 22
11.7%
3 22
11.7%
9 13
 
6.9%
5 12
 
6.4%
8 11
 
5.9%
- 11
 
5.9%
7 10
 
5.3%
6 9
 
4.8%
Other values (3) 6
 
3.2%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
임야
56 
전/임야
6 

Length

Max length4
Median length2
Mean length2.1935484
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임야 56
90.3%
전/임야 6
 
9.7%

Length

2023-12-11T08:12:19.508367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:19.601045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임야 56
90.3%
전/임야 6
 
9.7%

면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21390.677
Minimum79
Maximum434181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-11T08:12:19.707116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79
5-th percentile392.5
Q12132.5
median6831.5
Q313988
95-th percentile80984.75
Maximum434181
Range434102
Interquartile range (IQR)11855.5

Descriptive statistics

Standard deviation58469.588
Coefficient of variation (CV)2.7334145
Kurtosis42.046585
Mean21390.677
Median Absolute Deviation (MAD)5737.5
Skewness6.1054993
Sum1326222
Variance3.4186928 × 109
MonotonicityNot monotonic
2023-12-11T08:12:20.150441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2579 2
 
3.2%
8331 2
 
3.2%
723 1
 
1.6%
101449 1
 
1.6%
81090 1
 
1.6%
8232 1
 
1.6%
38416 1
 
1.6%
6149 1
 
1.6%
595 1
 
1.6%
20939 1
 
1.6%
Other values (50) 50
80.6%
ValueCountFrequency (%)
79 1
1.6%
205 1
1.6%
326 1
1.6%
392 1
1.6%
402 1
1.6%
437 1
1.6%
447 1
1.6%
457 1
1.6%
595 1
1.6%
627 1
1.6%
ValueCountFrequency (%)
434181 1
1.6%
121488 1
1.6%
101449 1
1.6%
81090 1
1.6%
78985 1
1.6%
47363 1
1.6%
38416 1
1.6%
37587 1
1.6%
35802 1
1.6%
22017 1
1.6%

관리유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
이용가능
29 
준보전
15 
개발가능
8 
절대보전
5 
<NA>
5 

Length

Max length4
Median length4
Mean length3.7580645
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이용가능
2nd row이용가능
3rd row이용가능
4th row이용가능
5th row준보전

Common Values

ValueCountFrequency (%)
이용가능 29
46.8%
준보전 15
24.2%
개발가능 8
 
12.9%
절대보전 5
 
8.1%
<NA> 5
 
8.1%

Length

2023-12-11T08:12:20.297142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:20.392578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용가능 29
46.8%
준보전 15
24.2%
개발가능 8
 
12.9%
절대보전 5
 
8.1%
na 5
 
8.1%

소유자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size628.0 B
사유지
32 
국(재정경제부)
13 
국(산림청)
10 
국(재무부)
4 
국(국방부)
 
1
Other values (2)
 
2

Length

Max length11
Median length3
Mean length4.983871
Min length3

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row국(재정경제부)
2nd row국(재정경제부)
3rd row국(재정경제부)
4th row국(재정경제부)
5th row국(산림청)

Common Values

ValueCountFrequency (%)
사유지 32
51.6%
국(재정경제부) 13
21.0%
국(산림청) 10
 
16.1%
국(재무부) 4
 
6.5%
국(국방부) 1
 
1.6%
국(국방부)/경상남도 1
 
1.6%
국(국토해양부) 1
 
1.6%

Length

2023-12-11T08:12:20.514500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:20.620178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유지 32
51.6%
국(재정경제부 13
21.0%
국(산림청 10
 
16.1%
국(재무부 4
 
6.5%
국(국방부 1
 
1.6%
국(국방부)/경상남도 1
 
1.6%
국(국토해양부 1
 
1.6%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
2018-07-31
62 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-07-31
2nd row2018-07-31
3rd row2018-07-31
4th row2018-07-31
5th row2018-07-31

Common Values

ValueCountFrequency (%)
2018-07-31 62
100.0%

Length

2023-12-11T08:12:20.726527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:20.807179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-07-31 62
100.0%

Interactions

2023-12-11T08:12:17.214940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:12:20.864814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도서명면동리지번지목면적(㎡)관리유형소유자
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
도서명1.0001.0001.0001.0001.0001.0001.0001.0001.000
면동1.0001.0001.0001.0000.9280.4590.0000.6200.719
리1.0001.0001.0001.0000.0000.7500.7560.9290.519
지번1.0001.0000.9280.0001.0001.0001.0000.4720.835
지목1.0001.0000.4590.7501.0001.0000.9090.0000.060
면적(㎡)1.0001.0000.0000.7561.0000.9091.0000.4630.677
관리유형1.0001.0000.6200.9290.4720.0000.4631.0000.508
소유자1.0001.0000.7190.5190.8350.0600.6770.5081.000
2023-12-11T08:12:20.969764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유자지목리면동관리유형
소유자1.0000.0460.1740.4570.361
지목0.0461.0000.4780.3250.000
리0.1740.4781.0000.8320.544
면동0.4570.3250.8321.0000.395
관리유형0.3610.0000.5440.3951.000
2023-12-11T08:12:21.065893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(㎡)면동리지목관리유형소유자
면적(㎡)1.0000.0000.3610.7150.1920.525
면동0.0001.0000.8320.3250.3950.457
리0.3610.8321.0000.4780.5440.174
지목0.7150.3250.4781.0000.0000.046
관리유형0.1920.3950.5440.0001.0000.361
소유자0.5250.4570.1740.0460.3611.000

Missing values

2023-12-11T08:12:17.298393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:12:17.420093image/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

관리번호도서명소재지면동리지번지목면적(㎡)관리유형소유자기준일
0경남-거제-12-01북여도(1)거제시남부면갈곶리431임야723이용가능국(재정경제부)2018-07-31
1경남-거제-12-02북여도(2)거제시남부면갈곶리432임야437이용가능국(재정경제부)2018-07-31
2경남-거제-12-03남여도(1)거제시남부면갈곶리433임야392이용가능국(재정경제부)2018-07-31
3경남-거제-12-04남여도(2)거제시남부면갈곶리434임야326이용가능국(재정경제부)2018-07-31
4경남-거제-12-05소다포도거제시남부면다포리산23임야1587준보전국(산림청)2018-07-31
5경남-거제-12-06대손(병)대도(1)거제시남부면다포리산42임야37587절대보전국(산림청)2018-07-31
6경남-거제-12-07대손(병)대도(2)거제시남부면다포리산43임야18843절대보전국(산림청)2018-07-31
7경남-거제-12-08소손(병)대도(1)거제시남부면다포리산44임야2579준보전국(산림청)2018-07-31
8경남-거제-12-09소손(병)대도(2)거제시남부면다포리산45임야11504절대보전국(산림청)2018-07-31
9경남-거제-12-10대손(병)대도(4)거제시남부면다포리산50임야14039절대보전국(재정경제부)2018-07-31
관리번호도서명소재지면동리지번지목면적(㎡)관리유형소유자기준일
52경남-거제-12-53광지말도(딴섬)거제시장목면구영리산91임야35802이용가능사유지2018-07-31
53경남-거제-12-54망와도거제시장목면유호리산4임야15074준보전사유지2018-07-31
54경남-거제-12-55대범벅도거제시장목면장목리산131임야9521이용가능사유지2018-07-31
55경남-거제-12-56소범벅도거제시장목면장목리산132임야3868이용가능사유지2018-07-31
56경남-거제-12-57귤도거제시장평동<NA>산130임야2975이용가능사유지2018-07-31
57경남-거제-12-58다포도거제시남부면다포리산22임야8430<NA>국(산림청)2018-07-31
58경남-거제-12-59소손(병)대도(3)거제시남부면다포리산46임야12397<NA>국(산림청)2018-07-31
59경남-거제-12-60대손(병)대도(3)거제시남부면다포리산49임야6331<NA>국(재정경제부)2018-07-31
60경남-거제-12-61갈도거제시남부면갈곶리산1임야121488<NA>사유지2018-07-31
61경남-거제-12-62송도거제시남부면갈곶리산41임야8331<NA>사유지2018-07-31