Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory898.4 KiB
Average record size in memory92.0 B

Variable types

Numeric3
Text1
Categorical6

Dataset

Description우리나라 연안의 마을어업, 정치망어업에 대한 정보로 양식대상 종명,어업방법명,어업유형명, 어업종류코드 등의 데이터를 제공한다.
Author해양수산부
URLhttps://www.data.go.kr/data/15114195/fileData.do

Alerts

어업유형명(fs_ty_nm) is highly overall correlated with 어업종류코드(fs_knd_cd) and 1 other fieldsHigh correlation
어업종류코드(fs_knd_cd) is highly overall correlated with 어업면허명(fs_lcns_nm) and 1 other fieldsHigh correlation
어업면허명(fs_lcns_nm) is highly overall correlated with 어업종류코드(fs_knd_cd) and 1 other fieldsHigh correlation
공간정보일련번호(gid) is highly overall correlated with 시도명(sido_nm) and 1 other fieldsHigh correlation
시군구코드(sgg_cd) is highly overall correlated with 시도명(sido_nm) and 1 other fieldsHigh correlation
시도명(sido_nm) is highly overall correlated with 공간정보일련번호(gid) and 2 other fieldsHigh correlation
관련부서명(rel_dept_nm) is highly overall correlated with 공간정보일련번호(gid) and 2 other fieldsHigh correlation
공간정보일련번호(gid) has unique valuesUnique

Reproduction

Analysis started2024-05-18 09:21:53.240848
Analysis finished2024-05-18 09:21:58.238554
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일련번호(gid)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7411.92
Minimum1
Maximum14760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T18:21:58.551823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile751.95
Q13741.75
median7453
Q311096.25
95-th percentile14028.1
Maximum14760
Range14759
Interquartile range (IQR)7354.5

Descriptive statistics

Standard deviation4254.0823
Coefficient of variation (CV)0.57395146
Kurtosis-1.1957257
Mean7411.92
Median Absolute Deviation (MAD)3677.5
Skewness-0.01052922
Sum74119200
Variance18097217
MonotonicityNot monotonic
2024-05-18T18:21:58.894351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11060 1
 
< 0.1%
7124 1
 
< 0.1%
6662 1
 
< 0.1%
14547 1
 
< 0.1%
10607 1
 
< 0.1%
3356 1
 
< 0.1%
7141 1
 
< 0.1%
7112 1
 
< 0.1%
4816 1
 
< 0.1%
10807 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
14760 1
< 0.1%
14757 1
< 0.1%
14756 1
< 0.1%
14755 1
< 0.1%
14754 1
< 0.1%
14752 1
< 0.1%
14751 1
< 0.1%
14750 1
< 0.1%
14747 1
< 0.1%
14746 1
< 0.1%

시군구코드(sgg_cd)
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45755.643
Minimum26140
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T18:21:59.294072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26140
5-th percentile31170
Q146130
median46890
Q347770
95-th percentile48840
Maximum50130
Range23990
Interquartile range (IQR)1640

Descriptive statistics

Standard deviation4447.8313
Coefficient of variation (CV)0.097208365
Kurtosis10.072832
Mean45755.643
Median Absolute Deviation (MAD)760
Skewness-3.2471002
Sum4.5755644 × 108
Variance19783203
MonotonicityNot monotonic
2024-05-18T18:21:59.751772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46890 1072
 
10.7%
46910 843
 
8.4%
48220 785
 
7.8%
46130 754
 
7.5%
46770 671
 
6.7%
46900 569
 
5.7%
44825 496
 
5.0%
48310 462
 
4.6%
48840 374
 
3.7%
28720 271
 
2.7%
Other values (53) 3703
37.0%
ValueCountFrequency (%)
26140 1
 
< 0.1%
26200 1
 
< 0.1%
26290 1
 
< 0.1%
26350 10
 
0.1%
26380 6
 
0.1%
26440 21
 
0.2%
26500 3
 
< 0.1%
26710 72
0.7%
28110 61
0.6%
28185 1
 
< 0.1%
ValueCountFrequency (%)
50130 45
 
0.4%
50110 122
 
1.2%
48850 31
 
0.3%
48840 374
3.7%
48820 224
 
2.2%
48310 462
4.6%
48240 76
 
0.8%
48220 785
7.8%
48120 192
 
1.9%
47940 14
 
0.1%

시군군명(sgg_nm)
Text

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T18:22:00.297014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.0634
Min length7

Characters and Unicode

Total characters80634
Distinct characters75
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

Unique6 ?
Unique (%)0.1%

Sample

1st row전라남도 진도군
2nd row전라남도 장흥군
3rd row경상남도 통영시
4th row경상북도 경주시
5th row강원도 삼척시
ValueCountFrequency (%)
전라남도 4911
24.6%
경상남도 2171
 
10.9%
완도군 1072
 
5.4%
충청남도 888
 
4.4%
신안군 843
 
4.2%
통영시 785
 
3.9%
여수시 754
 
3.8%
고흥군 671
 
3.4%
진도군 569
 
2.8%
태안군 496
 
2.5%
Other values (62) 6840
34.2%
2024-05-18T18:22:01.198201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 11089
13.8%
10000
12.4%
남 8555
 
10.6%
군 6596
 
8.2%
전 5355
 
6.6%
라 5355
 
6.6%
시 3962
 
4.9%
경 2829
 
3.5%
상 2658
 
3.3%
안 1679
 
2.1%
Other values (65) 22556
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70634
87.6%
Space Separator 10000
 
12.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 11089
15.7%
남 8555
 
12.1%
군 6596
 
9.3%
전 5355
 
7.6%
라 5355
 
7.6%
시 3962
 
5.6%
경 2829
 
4.0%
상 2658
 
3.8%
안 1679
 
2.4%
고 1129
 
1.6%
Other values (64) 21427
30.3%
Space Separator
ValueCountFrequency (%)
10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70634
87.6%
Common 10000
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 11089
15.7%
남 8555
 
12.1%
군 6596
 
9.3%
전 5355
 
7.6%
라 5355
 
7.6%
시 3962
 
5.6%
경 2829
 
4.0%
상 2658
 
3.8%
안 1679
 
2.4%
고 1129
 
1.6%
Other values (64) 21427
30.3%
Common
ValueCountFrequency (%)
10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70634
87.6%
ASCII 10000
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 11089
15.7%
남 8555
 
12.1%
군 6596
 
9.3%
전 5355
 
7.6%
라 5355
 
7.6%
시 3962
 
5.6%
경 2829
 
4.0%
상 2658
 
3.8%
안 1679
 
2.4%
고 1129
 
1.6%
Other values (64) 21427
30.3%
ASCII
ValueCountFrequency (%)
10000
100.0%

어업종류코드(fs_knd_cd)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양식어업
7257 
마을어업
2454 
정치망어업
 
289

Length

Max length5
Median length4
Mean length4.0289
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마을어업
2nd row양식어업
3rd row양식어업
4th row양식어업
5th row양식어업

Common Values

ValueCountFrequency (%)
양식어업 7257
72.6%
마을어업 2454
 
24.5%
정치망어업 289
 
2.9%

Length

2024-05-18T18:22:01.490493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T18:22:01.698231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양식어업 7257
72.6%
마을어업 2454
 
24.5%
정치망어업 289
 
2.9%

시도명(sido_nm)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전라남도
4911 
경상남도
2171 
충청남도
888 
경상북도
 
487
전라북도
 
444
Other values (6)
1099 

Length

Max length7
Median length4
Mean length4.0675
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라남도
2nd row전라남도
3rd row경상남도
4th row경상북도
5th row강원도

Common Values

ValueCountFrequency (%)
전라남도 4911
49.1%
경상남도 2171
21.7%
충청남도 888
 
8.9%
경상북도 487
 
4.9%
전라북도 444
 
4.4%
인천광역시 382
 
3.8%
강원도 245
 
2.5%
제주특별자치도 167
 
1.7%
경기도 134
 
1.3%
부산광역시 115
 
1.1%

Length

2024-05-18T18:22:01.913816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 4911
49.1%
경상남도 2171
21.7%
충청남도 888
 
8.9%
경상북도 487
 
4.9%
전라북도 444
 
4.4%
인천광역시 382
 
3.8%
강원도 245
 
2.5%
제주특별자치도 167
 
1.7%
경기도 134
 
1.3%
부산광역시 115
 
1.1%

관련부서명(rel_dept_nm)
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
해양수산과
3231 
수산경영과
1072 
신안군 해양수산과
843 
통영시 어업진흥과
785 
어업생산과
754 
Other values (27)
3315 

Length

Max length10
Median length5
Mean length5.9247
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row수산지원과
2nd row해양수산과
3rd row통영시 어업진흥과
4th row해양수산과
5th row해양수산과

Common Values

ValueCountFrequency (%)
해양수산과 3231
32.3%
수산경영과 1072
 
10.7%
신안군 해양수산과 843
 
8.4%
통영시 어업진흥과 785
 
7.8%
어업생산과 754
 
7.5%
수산과 632
 
6.3%
수산지원과 569
 
5.7%
바다자원과 462
 
4.6%
옹진군 해양수산과 271
 
2.7%
수산진흥과 190
 
1.9%
Other values (22) 1191
 
11.9%

Length

2024-05-18T18:22:02.291329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해양수산과 4982
39.3%
수산경영과 1072
 
8.4%
신안군 843
 
6.6%
통영시 785
 
6.2%
어업진흥과 785
 
6.2%
어업생산과 754
 
5.9%
수산과 632
 
5.0%
수산지원과 569
 
4.5%
바다자원과 462
 
3.6%
옹진군 271
 
2.1%
Other values (27) 1536
 
12.1%

개정년도(refm_yr)
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020
7616 
2022
1641 
2021
 
743

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2022
5th row2020

Common Values

ValueCountFrequency (%)
2020 7616
76.2%
2022 1641
 
16.4%
2021 743
 
7.4%

Length

2024-05-18T18:22:02.701009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T18:22:03.006701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 7616
76.2%
2022 1641
 
16.4%
2021 743
 
7.4%

어업면허명(fs_lcns_nm)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양식어업
6999 
마을어업
2359 
정치망어업
 
316
양식어업(한정)
 
222
마을어업(한정)
 
104

Length

Max length8
Median length4
Mean length4.162
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마을어업
2nd row양식어업
3rd row양식어업
4th row양식어업
5th row양식어업

Common Values

ValueCountFrequency (%)
양식어업 6999
70.0%
마을어업 2359
 
23.6%
정치망어업 316
 
3.2%
양식어업(한정) 222
 
2.2%
마을어업(한정) 104
 
1.0%

Length

2024-05-18T18:22:03.391349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T18:22:03.743426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양식어업 6999
70.0%
마을어업 2359
 
23.6%
정치망어업 316
 
3.2%
양식어업(한정 222
 
2.2%
마을어업(한정 104
 
1.0%

어업유형명(fs_ty_nm)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
패류양식업
3722 
마을어업
2452 
해조류양식
1618 
복합양식업
879 
어류등양식업
768 
Other values (3)
561 

Length

Max length6
Median length5
Mean length4.8316
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마을어업
2nd row패류양식업
3rd row어류등양식업
4th row협동양식업
5th row복합양식업

Common Values

ValueCountFrequency (%)
패류양식업 3722
37.2%
마을어업 2452
24.5%
해조류양식 1618
16.2%
복합양식업 879
 
8.8%
어류등양식업 768
 
7.7%
정치망어업 317
 
3.2%
협동양식업 240
 
2.4%
외해양식업 4
 
< 0.1%

Length

2024-05-18T18:22:04.143727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T18:22:04.516418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
패류양식업 3722
37.2%
마을어업 2452
24.5%
해조류양식 1618
16.2%
복합양식업 879
 
8.8%
어류등양식업 768
 
7.7%
정치망어업 317
 
3.2%
협동양식업 240
 
2.4%
외해양식업 4
 
< 0.1%

어장면적(fsgr_xtn)
Real number (ℝ)

Distinct1324
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.884747
Minimum0.08
Maximum2522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T18:22:04.910643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.08
5-th percentile1.9
Q15
median10
Q320
95-th percentile82
Maximum2522
Range2521.92
Interquartile range (IQR)15

Descriptive statistics

Standard deviation53.470184
Coefficient of variation (CV)2.4432627
Kurtosis553.78524
Mean21.884747
Median Absolute Deviation (MAD)6
Skewness15.968069
Sum218847.47
Variance2859.0606
MonotonicityNot monotonic
2024-05-18T18:22:05.289321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 1201
 
12.0%
5.0 1047
 
10.5%
20.0 742
 
7.4%
3.0 437
 
4.4%
2.0 429
 
4.3%
4.0 335
 
3.4%
15.0 287
 
2.9%
6.0 253
 
2.5%
8.0 221
 
2.2%
30.0 197
 
2.0%
Other values (1314) 4851
48.5%
ValueCountFrequency (%)
0.08 1
 
< 0.1%
0.1 1
 
< 0.1%
0.11 2
< 0.1%
0.12 2
< 0.1%
0.13 4
< 0.1%
0.14 2
< 0.1%
0.15 1
 
< 0.1%
0.16 1
 
< 0.1%
0.17 1
 
< 0.1%
0.18 2
< 0.1%
ValueCountFrequency (%)
2522.0 1
< 0.1%
1389.3 1
< 0.1%
882.0 1
< 0.1%
766.2 1
< 0.1%
703.0 1
< 0.1%
658.0 1
< 0.1%
649.0 1
< 0.1%
591.0 1
< 0.1%
579.2 1
< 0.1%
552.0 1
< 0.1%

Interactions

2024-05-18T18:21:56.703644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:55.088950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:55.913992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:56.887772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:55.369579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:56.198731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:57.117495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:55.642001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T18:21:56.524844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T18:22:05.465190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)시군구코드(sgg_cd)시군군명(sgg_nm)어업종류코드(fs_knd_cd)시도명(sido_nm)관련부서명(rel_dept_nm)개정년도(refm_yr)어업면허명(fs_lcns_nm)어업유형명(fs_ty_nm)어장면적(fsgr_xtn)
공간정보일련번호(gid)1.0000.8020.9830.3100.8540.9320.3800.3870.4010.049
시군구코드(sgg_cd)0.8021.0001.0000.2430.9760.9500.2190.2490.3580.019
시군군명(sgg_nm)0.9831.0001.0000.5271.0001.0000.6470.6440.6940.000
어업종류코드(fs_knd_cd)0.3100.2430.5271.0000.3460.3460.2660.9250.9570.057
시도명(sido_nm)0.8540.9761.0000.3461.0000.9640.4490.3480.5050.060
관련부서명(rel_dept_nm)0.9320.9501.0000.3460.9641.0000.5680.5260.5490.032
개정년도(refm_yr)0.3800.2190.6470.2660.4490.5681.0000.4100.1610.034
어업면허명(fs_lcns_nm)0.3870.2490.6440.9250.3480.5260.4101.0000.8310.019
어업유형명(fs_ty_nm)0.4010.3580.6940.9570.5050.5490.1610.8311.0000.086
어장면적(fsgr_xtn)0.0490.0190.0000.0570.0600.0320.0340.0190.0861.000
2024-05-18T18:22:05.715938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명(sido_nm)개정년도(refm_yr)관련부서명(rel_dept_nm)어업유형명(fs_ty_nm)어업종류코드(fs_knd_cd)어업면허명(fs_lcns_nm)
시도명(sido_nm)1.0000.2950.7820.2670.2160.200
개정년도(refm_yr)0.2951.0000.3480.1030.0870.341
관련부서명(rel_dept_nm)0.7820.3481.0000.2480.1860.279
어업유형명(fs_ty_nm)0.2670.1030.2481.0000.9720.706
어업종류코드(fs_knd_cd)0.2160.0870.1860.9721.0000.974
어업면허명(fs_lcns_nm)0.2000.3410.2790.7060.9741.000
2024-05-18T18:22:05.928160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)시군구코드(sgg_cd)어장면적(fsgr_xtn)어업종류코드(fs_knd_cd)시도명(sido_nm)관련부서명(rel_dept_nm)개정년도(refm_yr)어업면허명(fs_lcns_nm)어업유형명(fs_ty_nm)
공간정보일련번호(gid)1.000-0.3770.1180.1950.5870.6760.2470.1710.204
시군구코드(sgg_cd)-0.3771.000-0.1850.1680.9380.7860.1500.1620.201
어장면적(fsgr_xtn)0.118-0.1851.0000.0230.0310.0140.0140.0130.048
어업종류코드(fs_knd_cd)0.1950.1680.0231.0000.2160.1860.0870.9740.972
시도명(sido_nm)0.5870.9380.0310.2161.0000.7820.2950.2000.267
관련부서명(rel_dept_nm)0.6760.7860.0140.1860.7821.0000.3480.2790.248
개정년도(refm_yr)0.2470.1500.0140.0870.2950.3481.0000.3410.103
어업면허명(fs_lcns_nm)0.1710.1620.0130.9740.2000.2790.3411.0000.706
어업유형명(fs_ty_nm)0.2040.2010.0480.9720.2670.2480.1030.7061.000

Missing values

2024-05-18T18:21:57.481034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T18:21:57.996368image/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

공간정보일련번호(gid)시군구코드(sgg_cd)시군군명(sgg_nm)어업종류코드(fs_knd_cd)시도명(sido_nm)관련부서명(rel_dept_nm)개정년도(refm_yr)어업면허명(fs_lcns_nm)어업유형명(fs_ty_nm)어장면적(fsgr_xtn)
110941106046900전라남도 진도군마을어업전라남도수산지원과2020마을어업마을어업56.0
108311080946800전라남도 장흥군양식어업전라남도해양수산과2020양식어업패류양식업20.0
3112308648220경상남도 통영시양식어업경상남도통영시 어업진흥과2020양식어업어류등양식업2.0
3757372347130경상북도 경주시양식어업경상북도해양수산과2022양식어업협동양식업5.3
24024142230강원도 삼척시양식어업강원도해양수산과2020양식어업복합양식업4.0
3155312948220경상남도 통영시양식어업경상남도통영시 어업진흥과2020양식어업패류양식업3.5
9883987946890전라남도 완도군양식어업전라남도수산경영과2020양식어업패류양식업1.5
132081320244180충청남도 보령시양식어업충청남도수산과2021양식어업패류양식업5.0
3176315048220경상남도 통영시양식어업경상남도통영시 어업진흥과2020양식어업패류양식업6.3
105171050246890전라남도 완도군양식어업전라남도수산경영과2020양식어업복합양식업15.0
공간정보일련번호(gid)시군구코드(sgg_cd)시군군명(sgg_nm)어업종류코드(fs_knd_cd)시도명(sido_nm)관련부서명(rel_dept_nm)개정년도(refm_yr)어업면허명(fs_lcns_nm)어업유형명(fs_ty_nm)어장면적(fsgr_xtn)
138401383944825충청남도 태안군양식어업충청남도수산과2020양식어업어류등양식업3.0
2237220648120경상남도 창원시마을어업경상남도수산산림과2020마을어업마을어업22.5
9036900746130전라남도 여수시양식어업전라남도어업생산과2020양식어업해조류양식5.0
137811378044825충청남도 태안군양식어업충청남도수산과2022양식어업패류양식업6.0
7099701646910전라남도 신안군마을어업전라남도신안군 해양수산과2020마을어업마을어업82.0
5868582046770전라남도 고흥군양식어업전라남도해양수산과2020양식어업패류양식업2.0
128161278550130제주특별자치도 서귀포시마을어업제주특별자치도서귀포시 해양수산과2021마을어업마을어업198.0
23222942230강원도 삼척시양식어업강원도해양수산과2020양식어업협동양식업24.4
75775748310경상남도 거제시양식어업경상남도바다자원과2022양식어업어류등양식업5.0
128721283950110제주특별자치도 제주시마을어업제주특별자치도제주시 해양수산과2021마을어업마을어업29.75