Overview

Dataset statistics

Number of variables18
Number of observations48
Missing cells229
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory150.8 B

Variable types

Text8
Categorical6
Numeric2
Unsupported1
DateTime1

Dataset

Description제주 마을관광 정보 데이터로 공공데이터 뉴딜 사업으로 구축된 데이터입니다. 제주도 마을별 낚시터 및 갯바위낚시에 대한 데이터로 낚시터 유형과 주소, 위치 등의 항목을 제공합니다.
Author제주관광공사
URLhttps://www.data.go.kr/data/15109362/fileData.do

Alerts

낚시터유형 has constant value ""Constant
안전시설현황 has constant value ""Constant
편익시설현황 has constant value ""Constant
데이터기준일자 has constant value ""Constant
주요어종 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
주변환경유형 is highly overall correlated with 주요어종High correlation
위도 is highly overall correlated with 시군구명 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 읍면동명 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
주변환경유형 is highly imbalanced (85.4%)Imbalance
주차가능수 is highly imbalanced (85.4%)Imbalance
낚시터전화번호 has 46 (95.8%) missing valuesMissing
소재지도로명주소 has 41 (85.4%) missing valuesMissing
주요포인트 has 48 (100.0%) missing valuesMissing
안전시설현황 has 47 (97.9%) missing valuesMissing
편익시설현황 has 47 (97.9%) missing valuesMissing
낚시터명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
주요포인트 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 17:53:35.639965
Analysis finished2023-12-12 17:53:37.052325
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

마을명
Text

Distinct24
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T02:53:37.172082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.375
Min length4

Characters and Unicode

Total characters258
Distinct characters50
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

Unique12 ?
Unique (%)25.0%

Sample

1st row태흥1리마을
2nd row가파리마을
3rd row가파리마을
4th row가파리마을
5th row가파리마을
ValueCountFrequency (%)
신양리마을 5
 
10.4%
가파리마을 5
 
10.4%
대서리마을 4
 
8.3%
고산1리마을 3
 
6.2%
신양2리마을 3
 
6.2%
묵리마을 3
 
6.2%
오봉리마을 3
 
6.2%
상모1리마을 2
 
4.2%
조일리마을 2
 
4.2%
천진리마을 2
 
4.2%
Other values (14) 16
33.3%
2023-12-13T02:53:37.478053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 50
19.4%
을 48
18.6%
리 47
18.2%
신 9
 
3.5%
양 9
 
3.5%
1 7
 
2.7%
가 5
 
1.9%
파 5
 
1.9%
5
 
1.9%
대 5
 
1.9%
Other values (40) 68
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
93.8%
Decimal Number 11
 
4.3%
Space Separator 5
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 50
20.7%
을 48
19.8%
리 47
19.4%
신 9
 
3.7%
양 9
 
3.7%
가 5
 
2.1%
파 5
 
2.1%
대 5
 
2.1%
서 4
 
1.7%
묵 3
 
1.2%
Other values (36) 57
23.6%
Decimal Number
ValueCountFrequency (%)
1 7
63.6%
2 3
27.3%
3 1
 
9.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
93.8%
Common 16
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 50
20.7%
을 48
19.8%
리 47
19.4%
신 9
 
3.7%
양 9
 
3.7%
가 5
 
2.1%
파 5
 
2.1%
대 5
 
2.1%
서 4
 
1.7%
묵 3
 
1.2%
Other values (36) 57
23.6%
Common
ValueCountFrequency (%)
1 7
43.8%
5
31.2%
2 3
18.8%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
93.8%
ASCII 16
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 50
20.7%
을 48
19.8%
리 47
19.4%
신 9
 
3.7%
양 9
 
3.7%
가 5
 
2.1%
파 5
 
2.1%
대 5
 
2.1%
서 4
 
1.7%
묵 3
 
1.2%
Other values (36) 57
23.6%
ASCII
ValueCountFrequency (%)
1 7
43.8%
5
31.2%
2 3
18.8%
3 1
 
6.2%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
제주시
25 
서귀포시
23 

Length

Max length4
Median length3
Mean length3.4791667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 25
52.1%
서귀포시 23
47.9%

Length

2023-12-13T02:53:37.626693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:37.730902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 25
52.1%
서귀포시 23
47.9%

읍면동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
대정읍
13 
추자면
12 
우도면
7 
성산읍
5 
한경면
4 
Other values (6)
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique5 ?
Unique (%)10.4%

Sample

1st row남원읍
2nd row대정읍
3rd row대정읍
4th row대정읍
5th row대정읍

Common Values

ValueCountFrequency (%)
대정읍 13
27.1%
추자면 12
25.0%
우도면 7
14.6%
성산읍 5
 
10.4%
한경면 4
 
8.3%
안덕면 2
 
4.2%
남원읍 1
 
2.1%
표선면 1
 
2.1%
하효동 1
 
2.1%
구좌읍 1
 
2.1%

Length

2023-12-13T02:53:37.862193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대정읍 13
27.1%
추자면 12
25.0%
우도면 7
14.6%
성산읍 5
 
10.4%
한경면 4
 
8.3%
안덕면 2
 
4.2%
남원읍 1
 
2.1%
표선면 1
 
2.1%
하효동 1
 
2.1%
구좌읍 1
 
2.1%

행정리명
Text

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T02:53:38.090997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1666667
Min length2

Characters and Unicode

Total characters152
Distinct characters43
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)27.1%

Sample

1st row태흥1리
2nd row가파리
3rd row가파리
4th row가파리
5th row가파리
ValueCountFrequency (%)
가파리 5
 
10.4%
신양리 4
 
8.3%
대서리 4
 
8.3%
고산1리 3
 
6.2%
신양2리 3
 
6.2%
묵리 3
 
6.2%
오봉리 3
 
6.2%
마라리 2
 
4.2%
천진리 2
 
4.2%
상모1리 2
 
4.2%
Other values (15) 17
35.4%
2023-12-13T02:53:38.395966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 47
30.9%
신 9
 
5.9%
양 8
 
5.3%
1 8
 
5.3%
가 5
 
3.3%
대 5
 
3.3%
파 5
 
3.3%
서 4
 
2.6%
오 3
 
2.0%
상 3
 
2.0%
Other values (33) 55
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140
92.1%
Decimal Number 12
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 47
33.6%
신 9
 
6.4%
양 8
 
5.7%
가 5
 
3.6%
대 5
 
3.6%
파 5
 
3.6%
서 4
 
2.9%
오 3
 
2.1%
상 3
 
2.1%
봉 3
 
2.1%
Other values (30) 48
34.3%
Decimal Number
ValueCountFrequency (%)
1 8
66.7%
2 3
 
25.0%
3 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
92.1%
Common 12
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 47
33.6%
신 9
 
6.4%
양 8
 
5.7%
가 5
 
3.6%
대 5
 
3.6%
파 5
 
3.6%
서 4
 
2.9%
오 3
 
2.1%
상 3
 
2.1%
봉 3
 
2.1%
Other values (30) 48
34.3%
Common
ValueCountFrequency (%)
1 8
66.7%
2 3
 
25.0%
3 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
92.1%
ASCII 12
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 47
33.6%
신 9
 
6.4%
양 8
 
5.7%
가 5
 
3.6%
대 5
 
3.6%
파 5
 
3.6%
서 4
 
2.9%
오 3
 
2.1%
상 3
 
2.1%
봉 3
 
2.1%
Other values (30) 48
34.3%
ASCII
ValueCountFrequency (%)
1 8
66.7%
2 3
 
25.0%
3 1
 
8.3%

낚시터명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T02:53:38.712582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13.5
Mean length9.875
Min length3

Characters and Unicode

Total characters474
Distinct characters124
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row태흥리 갯바위
2nd row큰아끈여 갯바위
3rd row냇골챙이 정자 아래 갯바위
4th row가파도 남측 갯바위
5th row가파도 제단 밑 갯바위
ValueCountFrequency (%)
갯바위 32
25.2%
앞 7
 
5.5%
아래 4
 
3.1%
상추자도 3
 
2.4%
해안 3
 
2.4%
우측 3
 
2.4%
하추자도 3
 
2.4%
낚시터 3
 
2.4%
해안도로 2
 
1.6%
우두곶 2
 
1.6%
Other values (59) 65
51.2%
2023-12-13T02:53:39.150056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
16.7%
바 36
 
7.6%
위 35
 
7.4%
갯 34
 
7.2%
도 13
 
2.7%
해 10
 
2.1%
측 9
 
1.9%
자 9
 
1.9%
앞 8
 
1.7%
리 8
 
1.7%
Other values (114) 233
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 395
83.3%
Space Separator 79
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
바 36
 
9.1%
위 35
 
8.9%
갯 34
 
8.6%
도 13
 
3.3%
해 10
 
2.5%
측 9
 
2.3%
자 9
 
2.3%
앞 8
 
2.0%
리 8
 
2.0%
장 7
 
1.8%
Other values (113) 226
57.2%
Space Separator
ValueCountFrequency (%)
79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 395
83.3%
Common 79
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
바 36
 
9.1%
위 35
 
8.9%
갯 34
 
8.6%
도 13
 
3.3%
해 10
 
2.5%
측 9
 
2.3%
자 9
 
2.3%
앞 8
 
2.0%
리 8
 
2.0%
장 7
 
1.8%
Other values (113) 226
57.2%
Common
ValueCountFrequency (%)
79
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 395
83.3%
ASCII 79
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
100.0%
Hangul
ValueCountFrequency (%)
바 36
 
9.1%
위 35
 
8.9%
갯 34
 
8.6%
도 13
 
3.3%
해 10
 
2.5%
측 9
 
2.3%
자 9
 
2.3%
앞 8
 
2.0%
리 8
 
2.0%
장 7
 
1.8%
Other values (113) 226
57.2%

낚시터유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
바다
48 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
바다 48
100.0%

Length

2023-12-13T02:53:39.318363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:39.469519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
바다 48
100.0%

낚시터전화번호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing46
Missing (%)95.8%
Memory size516.0 B
2023-12-13T02:53:39.597248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters9
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

Unique2 ?
Unique (%)100.0%

Sample

1st row064-760-2772
2nd row064-783-8855
ValueCountFrequency (%)
064-760-2772 1
50.0%
064-783-8855 1
50.0%
2023-12-13T02:53:39.920689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4
16.7%
7 4
16.7%
0 3
12.5%
6 3
12.5%
8 3
12.5%
4 2
8.3%
2 2
8.3%
5 2
8.3%
3 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
83.3%
Dash Punctuation 4
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 4
20.0%
0 3
15.0%
6 3
15.0%
8 3
15.0%
4 2
10.0%
2 2
10.0%
5 2
10.0%
3 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4
16.7%
7 4
16.7%
0 3
12.5%
6 3
12.5%
8 3
12.5%
4 2
8.3%
2 2
8.3%
5 2
8.3%
3 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4
16.7%
7 4
16.7%
0 3
12.5%
6 3
12.5%
8 3
12.5%
4 2
8.3%
2 2
8.3%
5 2
8.3%
3 1
 
4.2%

소재지도로명주소
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing41
Missing (%)85.4%
Memory size516.0 B
2023-12-13T02:53:40.120889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length25.142857
Min length23

Characters and Unicode

Total characters176
Distinct characters41
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

Unique7 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 성산읍 섭지코지로 261
2nd row제주특별자치도 서귀포시 성산읍 섭지코지로 95
3rd row제주특별자치도 서귀포시 성산읍 섭지코지로 107
4th row제주특별자치도 서귀포시 성산읍 환해장성로 416
5th row제주특별자치도 제주시 우도면 안비양길 51
ValueCountFrequency (%)
제주특별자치도 7
20.0%
서귀포시 4
11.4%
성산읍 4
11.4%
제주시 3
 
8.6%
섭지코지로 3
 
8.6%
261 1
 
2.9%
95 1
 
2.9%
107 1
 
2.9%
환해장성로 1
 
2.9%
416 1
 
2.9%
Other values (9) 9
25.7%
2023-12-13T02:53:40.488760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
15.9%
제 10
 
5.7%
주 10
 
5.7%
자 9
 
5.1%
도 8
 
4.5%
특 7
 
4.0%
별 7
 
4.0%
치 7
 
4.0%
시 7
 
4.0%
지 6
 
3.4%
Other values (31) 77
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127
72.2%
Space Separator 28
 
15.9%
Decimal Number 20
 
11.4%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 10
 
7.9%
주 10
 
7.9%
자 9
 
7.1%
도 8
 
6.3%
특 7
 
5.5%
별 7
 
5.5%
치 7
 
5.5%
시 7
 
5.5%
지 6
 
4.7%
로 6
 
4.7%
Other values (21) 50
39.4%
Decimal Number
ValueCountFrequency (%)
1 4
20.0%
2 4
20.0%
6 4
20.0%
4 2
10.0%
7 2
10.0%
5 2
10.0%
0 1
 
5.0%
9 1
 
5.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127
72.2%
Common 49
 
27.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 10
 
7.9%
주 10
 
7.9%
자 9
 
7.1%
도 8
 
6.3%
특 7
 
5.5%
별 7
 
5.5%
치 7
 
5.5%
시 7
 
5.5%
지 6
 
4.7%
로 6
 
4.7%
Other values (21) 50
39.4%
Common
ValueCountFrequency (%)
28
57.1%
1 4
 
8.2%
2 4
 
8.2%
6 4
 
8.2%
4 2
 
4.1%
7 2
 
4.1%
5 2
 
4.1%
0 1
 
2.0%
9 1
 
2.0%
- 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127
72.2%
ASCII 49
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
57.1%
1 4
 
8.2%
2 4
 
8.2%
6 4
 
8.2%
4 2
 
4.1%
7 2
 
4.1%
5 2
 
4.1%
0 1
 
2.0%
9 1
 
2.0%
- 1
 
2.0%
Hangul
ValueCountFrequency (%)
제 10
 
7.9%
주 10
 
7.9%
자 9
 
7.1%
도 8
 
6.3%
특 7
 
5.5%
별 7
 
5.5%
치 7
 
5.5%
시 7
 
5.5%
지 6
 
4.7%
로 6
 
4.7%
Other values (21) 50
39.4%

소재지지번주소
Text

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T02:53:40.773217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length24.854167
Min length22

Characters and Unicode

Total characters1193
Distinct characters71
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

Unique44 ?
Unique (%)91.7%

Sample

1st row제주특별자치도 서귀포시 남원읍 태흥리 1831-3
2nd row제주특별자치도 서귀포시 대정읍 가파리 428
3rd row제주특별자치도 서귀포시 대정읍 가파리 525-3
4th row제주특별자치도 서귀포시 대정읍 가파리 533-1
5th row제주특별자치도 서귀포시 대정읍 가파리 18-1
ValueCountFrequency (%)
제주특별자치도 48
19.2%
제주시 25
 
10.0%
서귀포시 23
 
9.2%
대정읍 13
 
5.2%
추자면 12
 
4.8%
산 10
 
4.0%
가파리 7
 
2.8%
우도면 7
 
2.8%
연평리 7
 
2.8%
성산읍 5
 
2.0%
Other values (70) 93
37.2%
2023-12-13T02:53:41.216440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
16.9%
제 73
 
6.1%
주 73
 
6.1%
자 60
 
5.0%
도 55
 
4.6%
시 48
 
4.0%
리 48
 
4.0%
치 48
 
4.0%
특 48
 
4.0%
별 48
 
4.0%
Other values (61) 490
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 800
67.1%
Space Separator 202
 
16.9%
Decimal Number 164
 
13.7%
Dash Punctuation 27
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 73
 
9.1%
주 73
 
9.1%
자 60
 
7.5%
도 55
 
6.9%
시 48
 
6.0%
리 48
 
6.0%
치 48
 
6.0%
특 48
 
6.0%
별 48
 
6.0%
서 27
 
3.4%
Other values (49) 272
34.0%
Decimal Number
ValueCountFrequency (%)
1 38
23.2%
3 28
17.1%
5 20
12.2%
2 19
11.6%
7 15
 
9.1%
6 11
 
6.7%
4 11
 
6.7%
8 10
 
6.1%
0 6
 
3.7%
9 6
 
3.7%
Space Separator
ValueCountFrequency (%)
202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 800
67.1%
Common 393
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 73
 
9.1%
주 73
 
9.1%
자 60
 
7.5%
도 55
 
6.9%
시 48
 
6.0%
리 48
 
6.0%
치 48
 
6.0%
특 48
 
6.0%
별 48
 
6.0%
서 27
 
3.4%
Other values (49) 272
34.0%
Common
ValueCountFrequency (%)
202
51.4%
1 38
 
9.7%
3 28
 
7.1%
- 27
 
6.9%
5 20
 
5.1%
2 19
 
4.8%
7 15
 
3.8%
6 11
 
2.8%
4 11
 
2.8%
8 10
 
2.5%
Other values (2) 12
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 800
67.1%
ASCII 393
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
51.4%
1 38
 
9.7%
3 28
 
7.1%
- 27
 
6.9%
5 20
 
5.1%
2 19
 
4.8%
7 15
 
3.8%
6 11
 
2.8%
4 11
 
2.8%
8 10
 
2.5%
Other values (2) 12
 
3.1%
Hangul
ValueCountFrequency (%)
제 73
 
9.1%
주 73
 
9.1%
자 60
 
7.5%
도 55
 
6.9%
시 48
 
6.0%
리 48
 
6.0%
치 48
 
6.0%
특 48
 
6.0%
별 48
 
6.0%
서 27
 
3.4%
Other values (49) 272
34.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.483405
Minimum33.113933
Maximum33.96759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:53:41.388379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.113933
5-th percentile33.165121
Q133.241372
median33.42518
Q333.64637
95-th percentile33.963185
Maximum33.96759
Range0.85365615
Interquartile range (IQR)0.40499717

Descriptive statistics

Standard deviation0.29871247
Coefficient of variation (CV)0.0089212094
Kurtosis-1.0430228
Mean33.483405
Median Absolute Deviation (MAD)0.18551911
Skewness0.67074788
Sum1607.2035
Variance0.089229141
MonotonicityNot monotonic
2023-12-13T02:53:41.629545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
33.2790840139 1
 
2.1%
33.5233998792 1
 
2.1%
33.4973231431 1
 
2.1%
33.5155991891 1
 
2.1%
33.4892117605 1
 
2.1%
33.4906671003 1
 
2.1%
33.5512464095 1
 
2.1%
33.9661197083 1
 
2.1%
33.9675895854 1
 
2.1%
33.9616949114 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
33.1139334356 1
2.1%
33.1221093158 1
2.1%
33.1640651788 1
2.1%
33.1670831174 1
2.1%
33.1681219753 1
2.1%
33.1697166024 1
2.1%
33.1706264132 1
2.1%
33.2032502367 1
2.1%
33.2061098283 1
2.1%
33.2143146312 1
2.1%
ValueCountFrequency (%)
33.9675895854 1
2.1%
33.9661197083 1
2.1%
33.9639868041 1
2.1%
33.9616949114 1
2.1%
33.9569026254 1
2.1%
33.9529242891 1
2.1%
33.9527856134 1
2.1%
33.9501360495 1
2.1%
33.9457207409 1
2.1%
33.943033253 1
2.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.48814
Minimum126.15353
Maximum126.97178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:53:41.831221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.15353
5-th percentile126.16452
Q1126.27586
median126.30761
Q3126.86493
95-th percentile126.96332
Maximum126.97178
Range0.81824961
Interquartile range (IQR)0.58906745

Descriptive statistics

Standard deviation0.3079788
Coefficient of variation (CV)0.0024348433
Kurtosis-1.3853049
Mean126.48814
Median Absolute Deviation (MAD)0.069177613
Skewness0.67509196
Sum6071.4306
Variance0.09485094
MonotonicityNot monotonic
2023-12-13T02:53:42.011012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
126.731138298 1
 
2.1%
126.9492559218 1
 
2.1%
126.9694808972 1
 
2.1%
126.9717778881 1
 
2.1%
126.9640982047 1
 
2.1%
126.9615850284 1
 
2.1%
126.6469450628 1
 
2.1%
126.2915836156 1
 
2.1%
126.284254492 1
 
2.1%
126.2860132876 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
126.1535282749 1
2.1%
126.1626323653 1
2.1%
126.163091361 1
2.1%
126.1671611027 1
2.1%
126.183580597 1
2.1%
126.1961274094 1
2.1%
126.2123188198 1
2.1%
126.2645450726 1
2.1%
126.2677441396 1
2.1%
126.2682441739 1
2.1%
ValueCountFrequency (%)
126.9717778881 1
2.1%
126.9694808972 1
2.1%
126.9640982047 1
2.1%
126.9618745559 1
2.1%
126.9615850284 1
2.1%
126.9585725775 1
2.1%
126.9492559218 1
2.1%
126.9350003485 1
2.1%
126.931465555 1
2.1%
126.9290909704 1
2.1%

주요어종
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
벵에돔+농어+자리돔+볼락+한치+참돔+부시리
11 
감성돔+돌돔+자리돔+농어+볼락+참돔
11 
감성돔+벤자리+삼치+방어+벵에돔+한치
8 
참돔+벵에돔+무늬오징어+볼락
7 
참돔+벵에돔+무늬오징어+돌돔+볼락
5 
Other values (5)
6 

Length

Max length23
Median length19.5
Mean length19.104167
Min length5

Unique

Unique4 ?
Unique (%)8.3%

Sample

1st row참돔+돌돔+다금바리+벵어돔+부시리
2nd row벵에돔+농어+자리돔+볼락+한치+참돔+부시리
3rd row벵에돔+농어+자리돔+볼락+한치+참돔+부시리
4th row벵에돔+농어+자리돔+볼락+한치+참돔+부시리
5th row벵에돔+농어+자리돔+볼락+한치+참돔+부시리

Common Values

ValueCountFrequency (%)
벵에돔+농어+자리돔+볼락+한치+참돔+부시리 11
22.9%
감성돔+돌돔+자리돔+농어+볼락+참돔 11
22.9%
감성돔+벤자리+삼치+방어+벵에돔+한치 8
16.7%
참돔+벵에돔+무늬오징어+볼락 7
14.6%
참돔+벵에돔+무늬오징어+돌돔+볼락 5
10.4%
참돔+돌돔+볼락+벵에돔+무늬오징어+독가시치 2
 
4.2%
참돔+돌돔+다금바리+벵어돔+부시리 1
 
2.1%
참돔+돌돔+다금바리+벵에돔+부시리 1
 
2.1%
참돔+우럭 1
 
2.1%
감성돔+농어 1
 
2.1%

Length

2023-12-13T02:53:42.242098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:42.395908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
벵에돔+농어+자리돔+볼락+한치+참돔+부시리 11
22.9%
감성돔+돌돔+자리돔+농어+볼락+참돔 11
22.9%
감성돔+벤자리+삼치+방어+벵에돔+한치 8
16.7%
참돔+벵에돔+무늬오징어+볼락 7
14.6%
참돔+벵에돔+무늬오징어+돌돔+볼락 5
10.4%
참돔+돌돔+볼락+벵에돔+무늬오징어+독가시치 2
 
4.2%
참돔+돌돔+다금바리+벵어돔+부시리 1
 
2.1%
참돔+돌돔+다금바리+벵에돔+부시리 1
 
2.1%
참돔+우럭 1
 
2.1%
감성돔+농어 1
 
2.1%

주요포인트
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

주변환경유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
갯바위
47 
배낚시
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
갯바위 47
97.9%
배낚시 1
 
2.1%

Length

2023-12-13T02:53:42.533377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:42.615512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갯바위 47
97.9%
배낚시 1
 
2.1%

안전시설현황
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing47
Missing (%)97.9%
Memory size516.0 B
2023-12-13T02:53:42.747241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row구명조끼+구명부환+방파제
ValueCountFrequency (%)
구명조끼+구명부환+방파제 1
100.0%
2023-12-13T02:53:43.050133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 2
15.4%
명 2
15.4%
+ 2
15.4%
조 1
7.7%
끼 1
7.7%
부 1
7.7%
환 1
7.7%
방 1
7.7%
파 1
7.7%
제 1
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
84.6%
Math Symbol 2
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2
18.2%
명 2
18.2%
조 1
9.1%
끼 1
9.1%
부 1
9.1%
환 1
9.1%
방 1
9.1%
파 1
9.1%
제 1
9.1%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
84.6%
Common 2
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2
18.2%
명 2
18.2%
조 1
9.1%
끼 1
9.1%
부 1
9.1%
환 1
9.1%
방 1
9.1%
파 1
9.1%
제 1
9.1%
Common
ValueCountFrequency (%)
+ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
84.6%
ASCII 2
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 2
18.2%
명 2
18.2%
조 1
9.1%
끼 1
9.1%
부 1
9.1%
환 1
9.1%
방 1
9.1%
파 1
9.1%
제 1
9.1%
ASCII
ValueCountFrequency (%)
+ 2
100.0%

편익시설현황
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing47
Missing (%)97.9%
Memory size516.0 B
2023-12-13T02:53:43.221672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters16
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row매점+매표소+휴게실+야외테라스
ValueCountFrequency (%)
매점+매표소+휴게실+야외테라스 1
100.0%
2023-12-13T02:53:43.475723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 3
18.8%
매 2
12.5%
점 1
 
6.2%
표 1
 
6.2%
소 1
 
6.2%
휴 1
 
6.2%
게 1
 
6.2%
실 1
 
6.2%
야 1
 
6.2%
외 1
 
6.2%
Other values (3) 3
18.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
81.2%
Math Symbol 3
 
18.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
매 2
15.4%
점 1
7.7%
표 1
7.7%
소 1
7.7%
휴 1
7.7%
게 1
7.7%
실 1
7.7%
야 1
7.7%
외 1
7.7%
테 1
7.7%
Other values (2) 2
15.4%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
81.2%
Common 3
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
매 2
15.4%
점 1
7.7%
표 1
7.7%
소 1
7.7%
휴 1
7.7%
게 1
7.7%
실 1
7.7%
야 1
7.7%
외 1
7.7%
테 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
+ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
81.2%
ASCII 3
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 3
100.0%
Hangul
ValueCountFrequency (%)
매 2
15.4%
점 1
7.7%
표 1
7.7%
소 1
7.7%
휴 1
7.7%
게 1
7.7%
실 1
7.7%
야 1
7.7%
외 1
7.7%
테 1
7.7%
Other values (2) 2
15.4%

주차가능수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
47 
50
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 47
97.9%
50 1
 
2.1%

Length

2023-12-13T02:53:43.591902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:43.701724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
97.9%
50 1
 
2.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2022-09-30 00:00:00
Maximum2022-09-30 00:00:00
2023-12-13T02:53:43.776357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:53:43.864699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:53:36.369261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:53:36.200659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:53:36.441468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:53:36.306919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:53:43.941481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
마을명시군구명읍면동명행정리명낚시터명낚시터전화번호소재지도로명주소소재지지번주소위도경도주요어종주변환경유형
마을명1.0000.9940.9961.0001.0000.0001.0001.0000.9921.0000.9820.000
시군구명0.9941.0001.0001.0001.0000.0001.0001.0000.8930.0000.9750.000
읍면동명0.9961.0001.0001.0001.0000.0001.0001.0000.9680.9600.9710.000
행정리명1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0000.9920.000
낚시터명1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
낚시터전화번호0.0000.0000.0000.0000.0001.000NaN0.0000.0000.0000.000NaN
소재지도로명주소1.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000NaN
소재지지번주소1.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
위도0.9920.8930.9681.0001.0000.0001.0001.0001.0000.8290.9410.000
경도1.0000.0000.9601.0001.0000.0001.0001.0000.8291.0000.9760.080
주요어종0.9820.9750.9710.9921.0000.0001.0001.0000.9410.9761.0001.000
주변환경유형0.0000.0000.0000.0001.000NaNNaN1.0000.0000.0801.0001.000
2023-12-13T02:53:44.066905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차가능수시군구명읍면동명주요어종주변환경유형
주차가능수1.000NaNNaNNaNNaN
시군구명NaN1.0000.8970.7830.000
읍면동명NaN0.8971.0000.8680.000
주요어종NaN0.7830.8681.0000.909
주변환경유형NaN0.0000.0000.9091.000
2023-12-13T02:53:44.163511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시군구명읍면동명주요어종주변환경유형주차가능수
위도1.0000.3990.9070.8670.8140.000NaN
경도0.3991.0000.0000.8490.9000.000NaN
시군구명0.9070.0001.0000.8970.7830.000NaN
읍면동명0.8670.8490.8971.0000.8680.000NaN
주요어종0.8140.9000.7830.8681.0000.909NaN
주변환경유형0.0000.0000.0000.0000.9091.000NaN
주차가능수NaNNaNNaNNaNNaNNaN1.000

Missing values

2023-12-13T02:53:36.572392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:53:36.804002image/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.
2023-12-13T02:53:36.978745image/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

마을명시군구명읍면동명행정리명낚시터명낚시터유형낚시터전화번호소재지도로명주소소재지지번주소위도경도주요어종주요포인트주변환경유형안전시설현황편익시설현황주차가능수데이터기준일자
0태흥1리마을서귀포시남원읍태흥1리태흥리 갯바위바다<NA><NA>제주특별자치도 서귀포시 남원읍 태흥리 1831-333.279084126.731138참돔+돌돔+다금바리+벵어돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
1가파리마을서귀포시대정읍가파리큰아끈여 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 42833.169717126.264545벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
2가파리마을서귀포시대정읍가파리냇골챙이 정자 아래 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 525-333.167083126.268244벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
3가파리마을서귀포시대정읍가파리가파도 남측 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 533-133.164065126.270976벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
4가파리마을서귀포시대정읍가파리가파도 제단 밑 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 18-133.168122126.278629벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
5가파리마을서귀포시대정읍가파리옹짓물 정자 아래 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 333.170626126.277494벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
6마라리마을서귀포시대정읍마라리할망당 아래 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 58433.122109126.267744벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
7마라리마을서귀포시대정읍마라리장군바위 부근 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 가파리 583-133.113933126.268452벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
8무릉1리마을서귀포시대정읍무릉1리무릉리 해안도로 갯바위바다<NA><NA>제주특별자치도 서귀포시 대정읍 무릉리 4093-333.259695126.183581감성돔+벤자리+삼치+방어+벵에돔+한치<NA>갯바위<NA><NA><NA>2022-09-30
9상모1리마을서귀포시대정읍상모1리산이물바다<NA><NA>제주특별자치도 서귀포시 대정읍 상모리 130-1033.20611126.290839벵에돔+농어+자리돔+볼락+한치+참돔+부시리<NA>갯바위<NA><NA><NA>2022-09-30
마을명시군구명읍면동명행정리명낚시터명낚시터유형낚시터전화번호소재지도로명주소소재지지번주소위도경도주요어종주요포인트주변환경유형안전시설현황편익시설현황주차가능수데이터기준일자
38묵리마을제주시추자면묵리하추자도 오지박 입구바다<NA><NA>제주특별자치도 제주시 추자면 묵리 산 5133.952786126.31131감성돔+돌돔+자리돔+농어+볼락+참돔<NA>갯바위<NA><NA><NA>2022-09-30
39신양리마을제주시추자면신양1리모진이몽돌해변바다<NA><NA>제주특별자치도 제주시 추자면 신양리 5633.945721126.334391감성돔+돌돔+자리돔+농어+볼락+참돔<NA>갯바위<NA><NA><NA>2022-09-30
40신양2리마을제주시추자면신양2리장작평사바다<NA><NA>제주특별자치도 제주시 추자면 신양리 434-2733.943033126.32634감성돔+농어<NA>배낚시<NA><NA><NA>2022-09-30
41신양2리마을제주시추자면신양2리하추자도 남동측 끝단바다<NA><NA>제주특별자치도 제주시 추자면 신양리 산 14733.931739126.329952감성돔+돌돔+자리돔+농어+볼락+참돔<NA>갯바위<NA><NA><NA>2022-09-30
42신양2리마을제주시추자면신양2리신양리 해안 갯바위바다<NA><NA>제주특별자치도 제주시 추자면 신양리 산 14333.93518126.3274감성돔+돌돔+자리돔+농어+볼락+참돔<NA>갯바위<NA><NA><NA>2022-09-30
43예초리마을제주시추자면예초리예초리 해안도로 갯바위바다<NA><NA>제주특별자치도 제주시 추자면 예초리 산 133.956903126.337471감성돔+돌돔+자리돔+농어+볼락+참돔<NA>갯바위<NA><NA><NA>2022-09-30
44고산1리마을제주시한경면고산1리차귀도 등측 갯바위바다<NA><NA>제주특별자치도 제주시 한경면 고산리 산 3733.311369126.153528감성돔+벤자리+삼치+방어+벵에돔+한치<NA>갯바위<NA><NA><NA>2022-09-30
45고산1리마을제주시한경면고산1리수월약수터 앞 갯바위바다<NA><NA>제주특별자치도 제주시 한경면 고산리 3653-333.300676126.167161감성돔+벤자리+삼치+방어+벵에돔+한치<NA>갯바위<NA><NA><NA>2022-09-30
46고산1리마을제주시한경면고산1리수월봉 갯바위바다<NA><NA>제주특별자치도 제주시 한경면 고산리 3696-233.295677126.162632감성돔+벤자리+삼치+방어+벵에돔+한치<NA>갯바위<NA><NA><NA>2022-09-30
47용당리마을제주시한경면용당리풍력발전소 앞 갯바위바다<NA><NA>제주특별자치도 제주시 한경면 용수리 3895-133.336549126.163091감성돔+벤자리+삼치+방어+벵에돔+한치<NA>갯바위<NA><NA><NA>2022-09-30