Overview

Dataset statistics

Number of variables11
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory91.2 B

Variable types

Text3
Categorical6
Numeric1
DateTime1

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 면동High correlation
지목 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
소유자 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
지목 is highly imbalanced (69.6%)Imbalance
관리번호 has unique valuesUnique
도서명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:12:29.661503
Analysis finished2023-12-10 23:12:30.789490
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T08:12:30.986729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters671
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

Unique61 ?
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-12-33 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%
경남-거제-12-41 1
 
1.6%
경남-거제-12-42 1
 
1.6%
Other values (51) 51
83.6%
2023-12-11T08:12:31.433007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 183
27.3%
2 78
11.6%
1 77
11.5%
경 61
 
9.1%
남 61
 
9.1%
거 61
 
9.1%
제 61
 
9.1%
3 16
 
2.4%
4 16
 
2.4%
5 16
 
2.4%
Other values (5) 41
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 244
36.4%
Other Letter 244
36.4%
Dash Punctuation 183
27.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 78
32.0%
1 77
31.6%
3 16
 
6.6%
4 16
 
6.6%
5 16
 
6.6%
0 15
 
6.1%
6 8
 
3.3%
7 6
 
2.5%
8 6
 
2.5%
9 6
 
2.5%
Other Letter
ValueCountFrequency (%)
경 61
25.0%
남 61
25.0%
거 61
25.0%
제 61
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 427
63.6%
Hangul 244
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 183
42.9%
2 78
18.3%
1 77
18.0%
3 16
 
3.7%
4 16
 
3.7%
5 16
 
3.7%
0 15
 
3.5%
6 8
 
1.9%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 61
25.0%
남 61
25.0%
거 61
25.0%
제 61
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 427
63.6%
Hangul 244
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 183
42.9%
2 78
18.3%
1 77
18.0%
3 16
 
3.7%
4 16
 
3.7%
5 16
 
3.7%
0 15
 
3.5%
6 8
 
1.9%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 61
25.0%
남 61
25.0%
거 61
25.0%
제 61
25.0%

도서명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T08:12:31.707427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.7377049
Min length2

Characters and Unicode

Total characters350
Distinct characters86
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

Unique61 ?
Unique (%)100.0%

Sample

1st row북여도(1)
2nd row북여도(2)
3rd row남여도(1)
4th row남여도(2)
5th row소다포도
ValueCountFrequency (%)
북여도(1 1
 
1.6%
소송도(작은솔섬 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%
소고개도(동섬 1
 
1.6%
고개등대도(등대섬 1
 
1.6%
Other values (51) 51
83.6%
2023-12-11T08:12:32.098708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 60
17.1%
( 44
 
12.6%
) 44
 
12.6%
대 20
 
5.7%
섬 16
 
4.6%
소 9
 
2.6%
손 8
 
2.3%
병 8
 
2.3%
1 7
 
2.0%
2 7
 
2.0%
Other values (76) 127
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
69.1%
Open Punctuation 44
 
12.6%
Close Punctuation 44
 
12.6%
Decimal Number 19
 
5.4%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 60
24.8%
대 20
 
8.3%
섬 16
 
6.6%
소 9
 
3.7%
손 8
 
3.3%
병 8
 
3.3%
여 7
 
2.9%
동 5
 
2.1%
고 5
 
2.1%
사 4
 
1.7%
Other values (68) 100
41.3%
Decimal Number
ValueCountFrequency (%)
1 7
36.8%
2 7
36.8%
3 3
15.8%
5 1
 
5.3%
4 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
69.1%
Common 108
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 60
24.8%
대 20
 
8.3%
섬 16
 
6.6%
소 9
 
3.7%
손 8
 
3.3%
병 8
 
3.3%
여 7
 
2.9%
동 5
 
2.1%
고 5
 
2.1%
사 4
 
1.7%
Other values (68) 100
41.3%
Common
ValueCountFrequency (%)
( 44
40.7%
) 44
40.7%
1 7
 
6.5%
2 7
 
6.5%
3 3
 
2.8%
5 1
 
0.9%
4 1
 
0.9%
, 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
69.1%
ASCII 108
30.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 60
24.8%
대 20
 
8.3%
섬 16
 
6.6%
소 9
 
3.7%
손 8
 
3.3%
병 8
 
3.3%
여 7
 
2.9%
동 5
 
2.1%
고 5
 
2.1%
사 4
 
1.7%
Other values (68) 100
41.3%
ASCII
ValueCountFrequency (%)
( 44
40.7%
) 44
40.7%
1 7
 
6.5%
2 7
 
6.5%
3 3
 
2.8%
5 1
 
0.9%
4 1
 
0.9%
, 1
 
0.9%

소재지
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
거제시
61 

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 61
100.0%

Length

2023-12-11T08:12:32.230211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:32.316146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거제시 61
100.0%

면동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
남부면
18 
장목면
13 
사등면
9 
둔덕면
6 
하청면
6 
Other values (5)
9 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
남부면 18
29.5%
장목면 13
21.3%
사등면 9
14.8%
둔덕면 6
 
9.8%
하청면 6
 
9.8%
거제면 3
 
4.9%
일운면 2
 
3.3%
동부면 2
 
3.3%
옥포동 1
 
1.6%
장평동 1
 
1.6%

Length

2023-12-11T08:12:32.411994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:32.554715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부면 18
29.5%
장목면 13
21.3%
사등면 9
14.8%
둔덕면 6
 
9.8%
하청면 6
 
9.8%
거제면 3
 
4.9%
일운면 2
 
3.3%
동부면 2
 
3.3%
옥포동 1
 
1.6%
장평동 1
 
1.6%

리
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
다포리
10 
창호리
6 
갈곶리
6 
연구리
4 
시방리
4 
Other values (20)
31 

Length

Max length4
Median length3
Mean length2.9508197
Min length1

Unique

Unique12 ?
Unique (%)19.7%

Sample

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

Common Values

ValueCountFrequency (%)
다포리 10
16.4%
창호리 6
 
9.8%
갈곶리 6
 
9.8%
연구리 4
 
6.6%
시방리 4
 
6.6%
유호리 4
 
6.6%
학산리 3
 
4.9%
장목리 2
 
3.3%
- 2
 
3.3%
탑포리 2
 
3.3%
Other values (15) 18
29.5%

Length

2023-12-11T08:12:32.695947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다포리 10
16.4%
갈곶리 6
 
9.8%
창호리 6
 
9.8%
연구리 4
 
6.6%
시방리 4
 
6.6%
유호리 4
 
6.6%
학산리 3
 
4.9%
법동리 2
 
3.3%
술역리 2
 
3.3%
오량리 2
 
3.3%
Other values (15) 18
29.5%

지번
Text

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T08:12:32.905525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.6065574
Min length2

Characters and Unicode

Total characters281
Distinct characters17
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

Unique55 ?
Unique (%)90.2%

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%
산3-1외6 1
 
1.6%
산1 1
 
1.6%
산285외1 1
 
1.6%
431 1
 
1.6%
산33-1외16 1
 
1.6%
산111-1 1
 
1.6%
Other values (49) 49
79.0%
2023-12-11T08:12:33.325187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 62
22.1%
1 49
17.4%
4 24
 
8.5%
3 23
 
8.2%
2 21
 
7.5%
외 14
 
5.0%
9 13
 
4.6%
6 13
 
4.6%
5 12
 
4.3%
7 12
 
4.3%
Other values (7) 38
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 183
65.1%
Other Letter 80
28.5%
Dash Punctuation 11
 
3.9%
Other Punctuation 6
 
2.1%
Space Separator 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
26.8%
4 24
13.1%
3 23
12.6%
2 21
11.5%
9 13
 
7.1%
6 13
 
7.1%
5 12
 
6.6%
7 12
 
6.6%
8 12
 
6.6%
0 4
 
2.2%
Other Letter
ValueCountFrequency (%)
산 62
77.5%
외 14
 
17.5%
필 2
 
2.5%
지 2
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201
71.5%
Hangul 80
 
28.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
24.4%
4 24
11.9%
3 23
11.4%
2 21
10.4%
9 13
 
6.5%
6 13
 
6.5%
5 12
 
6.0%
7 12
 
6.0%
8 12
 
6.0%
- 11
 
5.5%
Other values (3) 11
 
5.5%
Hangul
ValueCountFrequency (%)
산 62
77.5%
외 14
 
17.5%
필 2
 
2.5%
지 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201
71.5%
Hangul 80
 
28.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 62
77.5%
외 14
 
17.5%
필 2
 
2.5%
지 2
 
2.5%
ASCII
ValueCountFrequency (%)
1 49
24.4%
4 24
11.9%
3 23
11.4%
2 21
10.4%
9 13
 
6.5%
6 13
 
6.5%
5 12
 
6.0%
7 12
 
6.0%
8 12
 
6.0%
- 11
 
5.5%
Other values (3) 11
 
5.5%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size620.0 B
임야
54 
전/임야
 
4
임야/대
 
1
전/임야/도로
 
1
전/임야/대/잡
 
1

Length

Max length8
Median length2
Mean length2.3442623
Min length2

Unique

Unique3 ?
Unique (%)4.9%

Sample

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

Common Values

ValueCountFrequency (%)
임야 54
88.5%
전/임야 4
 
6.6%
임야/대 1
 
1.6%
전/임야/도로 1
 
1.6%
전/임야/대/잡 1
 
1.6%

Length

2023-12-11T08:12:33.461255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:33.569102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임야 54
88.5%
전/임야 4
 
6.6%
임야/대 1
 
1.6%
전/임야/도로 1
 
1.6%
전/임야/대/잡 1
 
1.6%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22982.918
Minimum79
Maximum434181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-11T08:12:33.684428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79
5-th percentile392
Q12217
median6149
Q317058
95-th percentile81090
Maximum434181
Range434102
Interquartile range (IQR)14841

Descriptive statistics

Standard deviation59145.543
Coefficient of variation (CV)2.5734566
Kurtosis40.120954
Mean22982.918
Median Absolute Deviation (MAD)5426
Skewness5.9228396
Sum1401958
Variance3.4981952 × 109
MonotonicityNot monotonic
2023-12-11T08:12:33.846810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8331 2
 
3.3%
723 1
 
1.6%
9818 1
 
1.6%
8232 1
 
1.6%
43105 1
 
1.6%
6149 1
 
1.6%
595 1
 
1.6%
2579 1
 
1.6%
20939 1
 
1.6%
4364 1
 
1.6%
Other values (50) 50
82.0%
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%
55348 1
1.6%
51625 1
1.6%
47363 1
1.6%
43105 1
1.6%
35802 1
1.6%

관리유형
Categorical

Distinct4
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
이용가능
29 
준보전
18 
개발가능
9 
절대보전
5 

Length

Max length4
Median length4
Mean length3.704918
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용가능 29
47.5%
준보전 18
29.5%
개발가능 9
 
14.8%
절대보전 5
 
8.2%

Length

2023-12-11T08:12:34.001481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:34.098571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용가능 29
47.5%
준보전 18
29.5%
개발가능 9
 
14.8%
절대보전 5
 
8.2%

소유자
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size620.0 B
사유지
27 
국(기획재정부)
16 
국(산림청)
6 
사유지/국(산림청)
3 
국(산림청,환경부)
 
2
Other values (7)
7 

Length

Max length18
Median length17
Mean length6.1803279
Min length3

Unique

Unique7 ?
Unique (%)11.5%

Sample

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

Common Values

ValueCountFrequency (%)
사유지 27
44.3%
국(기획재정부) 16
26.2%
국(산림청) 6
 
9.8%
사유지/국(산림청) 3
 
4.9%
국(산림청,환경부) 2
 
3.3%
국(국방부) 1
 
1.6%
국(국방부)/경상남도 1
 
1.6%
국(국토해양부) 1
 
1.6%
사유지/국(건설부) 1
 
1.6%
사유지/국(기획재정부,해양수산부) 1
 
1.6%
Other values (2) 2
 
3.3%

Length

2023-12-11T08:12:34.214747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사유지 27
44.3%
국(기획재정부 16
26.2%
국(산림청 6
 
9.8%
사유지/국(산림청 3
 
4.9%
국(산림청,환경부 2
 
3.3%
국(국방부 1
 
1.6%
국(국방부)/경상남도 1
 
1.6%
국(국토해양부 1
 
1.6%
사유지/국(건설부 1
 
1.6%
사유지/국(기획재정부,해양수산부 1
 
1.6%
Other values (2) 2
 
3.3%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
Minimum2023-07-17 00:00:00
Maximum2023-07-17 00:00:00
2023-12-11T08:12:34.315633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:12:34.403462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T08:12:30.162427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:12:34.479922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도서명면동리지번지목면적관리유형소유자
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
도서명1.0001.0001.0001.0001.0001.0001.0001.0001.000
면동1.0001.0001.0000.9900.9280.2750.0000.5380.691
리1.0001.0000.9901.0000.4850.8490.4360.8280.744
지번1.0001.0000.9280.4851.0001.0001.0000.6040.990
지목1.0001.0000.2750.8491.0001.0000.7350.2080.950
면적1.0001.0000.0000.4361.0000.7351.0000.5310.952
관리유형1.0001.0000.5380.8280.6040.2080.5311.0000.803
소유자1.0001.0000.6910.7440.9900.9500.9520.8031.000
2023-12-11T08:12:34.601834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유자지목리면동관리유형
소유자1.0000.8330.2910.3660.455
지목0.8331.0000.4340.1000.166
리0.2910.4341.0000.7580.476
면동0.3660.1000.7581.0000.330
관리유형0.4550.1660.4760.3301.000
2023-12-11T08:12:34.728189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적면동리지목관리유형소유자
면적1.0000.0000.1770.6710.2280.670
면동0.0001.0000.7580.1000.3300.366
리0.1770.7581.0000.4340.4760.291
지목0.6710.1000.4341.0000.1660.833
관리유형0.2280.3300.4760.1661.0000.455
소유자0.6700.3660.2910.8330.4551.000

Missing values

2023-12-11T08:12:30.274160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:12:30.731704image/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

관리번호도서명소재지면동리지번지목면적관리유형소유자기준일
0경남-거제-12-01북여도(1)거제시남부면갈곶리431임야723이용가능국(기획재정부)2023-07-17
1경남-거제-12-02북여도(2)거제시남부면갈곶리432임야437이용가능국(기획재정부)2023-07-17
2경남-거제-12-03남여도(1)거제시남부면갈곶리433임야392이용가능국(기획재정부)2023-07-17
3경남-거제-12-04남여도(2)거제시남부면갈곶리434임야326이용가능국(기획재정부)2023-07-17
4경남-거제-12-05소다포도거제시남부면다포리산23임야10334준보전국(산림청)2023-07-17
5경남-거제-12-06대손(병)대도(1)거제시남부면다포리산42,산73임야55348절대보전국(산림청,환경부)2023-07-17
6경남-거제-12-07대손(병)대도(2)거제시남부면다포리산43,산66,산71임야51625절대보전국(산림청,환경부)2023-07-17
7경남-거제-12-08소손(병)대도(1)거제시남부면다포리산44임야2217준보전국(산림청)2023-07-17
8경남-거제-12-09소손(병)대도(2)거제시남부면다포리산45임야18985절대보전국(산림청)2023-07-17
9경남-거제-12-10대손(병)대도(4)거제시남부면다포리산50임야5475절대보전국(기획재정부)2023-07-17
관리번호도서명소재지면동리지번지목면적관리유형소유자기준일
51경남-거제-12-53광지말도(딴섬)거제시장목면구영리산91임야35802이용가능사유지2023-07-17
52경남-거제-12-54망와도거제시장목면유호리산4임야15074개발가능사유지2023-07-17
53경남-거제-12-55대범벅도거제시장목면장목리산131임야9521이용가능사유지2023-07-17
54경남-거제-12-56소범벅도거제시장목면장목리산132임야3868이용가능사유지2023-07-17
55경남-거제-12-57귤도거제시장평동-산130임야2975이용가능사유지2023-07-17
56경남-거제-12-58다포도거제시남부면다포리산22임야18413준보전국(산림청)2023-07-17
57경남-거제-12-59소손(병)대도(3)거제시남부면다포리산46임야25826준보전국(산림청)2023-07-17
58경남-거제-12-60대손(병)대도(3)거제시남부면다포리산49임야1432준보전국(기획재정부)2023-07-17
59경남-거제-12-61갈곶도거제시남부면갈곶리산1임야121488준보전사유지2023-07-17
60경남-거제-12-62송도거제시남부면갈곶리산41임야8331준보전사유지2023-07-17