Overview

Dataset statistics

Number of variables9
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory77.7 B

Variable types

Numeric2
Categorical4
Text3

Dataset

Description전라남도 신안군 마을하수처리시설현황으로 읍면명, 소재지주소, 시설년도, 처리방식, 데이터기준일자를 포함하고 있습니다.
Author전라남도 신안군
URLhttps://www.data.go.kr/data/15113630/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 읍면명High correlation
읍면명 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-05-11 10:28:27.374207
Analysis finished2024-05-11 10:28:30.812364
Duration3.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T10:28:31.101880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2024-05-11T10:28:31.714177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
전라남도
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 36
100.0%

Length

2024-05-11T10:28:32.340756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:28:32.704404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 36
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
신안군
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신안군 36
100.0%

Length

2024-05-11T10:28:33.015954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:28:33.365200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신안군 36
100.0%

읍면명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
흑산면
11 
도초면
5 
하의면
5 
비금면
4 
증도면
2 
Other values (8)
9 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique7 ?
Unique (%)19.4%

Sample

1st row압해읍
2nd row증도면
3rd row증도면
4th row임자면
5th row자은면

Common Values

ValueCountFrequency (%)
흑산면 11
30.6%
도초면 5
13.9%
하의면 5
13.9%
비금면 4
 
11.1%
증도면 2
 
5.6%
자은면 2
 
5.6%
압해읍 1
 
2.8%
임자면 1
 
2.8%
신의면 1
 
2.8%
장산면 1
 
2.8%
Other values (3) 3
 
8.3%

Length

2024-05-11T10:28:33.745076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
흑산면 11
30.6%
도초면 5
13.9%
하의면 5
13.9%
비금면 4
 
11.1%
증도면 2
 
5.6%
자은면 2
 
5.6%
압해읍 1
 
2.8%
임자면 1
 
2.8%
신의면 1
 
2.8%
장산면 1
 
2.8%
Other values (3) 3
 
8.3%

시설명
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-11T10:28:34.412781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2222222
Min length6

Characters and Unicode

Total characters224
Distinct characters53
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

Unique34 ?
Unique (%)94.4%

Sample

1st row중촌마을하수
2nd row증동마을하수
3rd row우전마을하수
4th row전장마을하수
5th row백길마을하수
ValueCountFrequency (%)
대리마을하수 2
 
5.6%
종남마을하수 1
 
2.8%
곰실마을하수 1
 
2.8%
오리마을하수 1
 
2.8%
도목마을하수 1
 
2.8%
홍도1마을하수 1
 
2.8%
홍도2마을하수 1
 
2.8%
가거도마을하수 1
 
2.8%
수리마을하수 1
 
2.8%
중촌마을하수 1
 
2.8%
Other values (25) 25
69.4%
2024-05-11T10:28:35.721410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 38
17.0%
마 36
16.1%
을 36
16.1%
하 36
16.1%
도 9
 
4.0%
리 8
 
3.6%
목 3
 
1.3%
장 3
 
1.3%
대 2
 
0.9%
2 2
 
0.9%
Other values (43) 51
22.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 220
98.2%
Decimal Number 4
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 38
17.3%
마 36
16.4%
을 36
16.4%
하 36
16.4%
도 9
 
4.1%
리 8
 
3.6%
목 3
 
1.4%
장 3
 
1.4%
대 2
 
0.9%
사 2
 
0.9%
Other values (41) 47
21.4%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 220
98.2%
Common 4
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 38
17.3%
마 36
16.4%
을 36
16.4%
하 36
16.4%
도 9
 
4.1%
리 8
 
3.6%
목 3
 
1.4%
장 3
 
1.4%
대 2
 
0.9%
사 2
 
0.9%
Other values (41) 47
21.4%
Common
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 220
98.2%
ASCII 4
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 38
17.3%
마 36
16.4%
을 36
16.4%
하 36
16.4%
도 9
 
4.1%
리 8
 
3.6%
목 3
 
1.4%
장 3
 
1.4%
대 2
 
0.9%
사 2
 
0.9%
Other values (41) 47
21.4%
ASCII
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%

소재지주소
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-11T10:28:36.469587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.583333
Min length18

Characters and Unicode

Total characters777
Distinct characters81
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

Unique34 ?
Unique (%)94.4%

Sample

1st row전라남도 신안군 압해읍 복룡리 121-9
2nd row전라남도 신안군 증도면 증동리 1966-3
3rd row전라남도 신안군 증도면 우전리 77
4th row전라남도 신안군 임자면 도찬리 213-4
5th row전라남도 신안군 자은면 유각리 847-1
ValueCountFrequency (%)
전라남도 36
20.0%
신안군 36
20.0%
흑산면 11
 
6.1%
도초면 5
 
2.8%
하의면 5
 
2.8%
비금면 4
 
2.2%
89 2
 
1.1%
자은면 2
 
1.1%
홍도리 2
 
1.1%
증도면 2
 
1.1%
Other values (72) 75
41.7%
2024-05-11T10:28:37.748223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
18.5%
도 51
 
6.6%
전 37
 
4.8%
안 37
 
4.8%
신 37
 
4.8%
군 36
 
4.6%
라 36
 
4.6%
남 36
 
4.6%
면 35
 
4.5%
리 33
 
4.2%
Other values (71) 295
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
60.1%
Space Separator 144
 
18.5%
Decimal Number 139
 
17.9%
Dash Punctuation 27
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 51
10.9%
전 37
 
7.9%
안 37
 
7.9%
신 37
 
7.9%
군 36
 
7.7%
라 36
 
7.7%
남 36
 
7.7%
면 35
 
7.5%
리 33
 
7.1%
산 15
 
3.2%
Other values (59) 114
24.4%
Decimal Number
ValueCountFrequency (%)
1 31
22.3%
2 16
11.5%
4 14
10.1%
7 13
9.4%
5 13
9.4%
3 13
9.4%
0 11
 
7.9%
8 11
 
7.9%
9 10
 
7.2%
6 7
 
5.0%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 467
60.1%
Common 310
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 51
10.9%
전 37
 
7.9%
안 37
 
7.9%
신 37
 
7.9%
군 36
 
7.7%
라 36
 
7.7%
남 36
 
7.7%
면 35
 
7.5%
리 33
 
7.1%
산 15
 
3.2%
Other values (59) 114
24.4%
Common
ValueCountFrequency (%)
144
46.5%
1 31
 
10.0%
- 27
 
8.7%
2 16
 
5.2%
4 14
 
4.5%
7 13
 
4.2%
5 13
 
4.2%
3 13
 
4.2%
0 11
 
3.5%
8 11
 
3.5%
Other values (2) 17
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 467
60.1%
ASCII 310
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
46.5%
1 31
 
10.0%
- 27
 
8.7%
2 16
 
5.2%
4 14
 
4.5%
7 13
 
4.2%
5 13
 
4.2%
3 13
 
4.2%
0 11
 
3.5%
8 11
 
3.5%
Other values (2) 17
 
5.5%
Hangul
ValueCountFrequency (%)
도 51
10.9%
전 37
 
7.9%
안 37
 
7.9%
신 37
 
7.9%
군 36
 
7.7%
라 36
 
7.7%
남 36
 
7.7%
면 35
 
7.5%
리 33
 
7.1%
산 15
 
3.2%
Other values (59) 114
24.4%

시설년도
Real number (ℝ)

Distinct16
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.8333
Minimum1999
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T10:28:38.195245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2000.75
Q12004.75
median2009
Q32012
95-th percentile2018.25
Maximum2019
Range20
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation5.7246335
Coefficient of variation (CV)0.0028497304
Kurtosis-0.7192278
Mean2008.8333
Median Absolute Deviation (MAD)3.5
Skewness0.29859002
Sum72318
Variance32.771429
MonotonicityNot monotonic
2024-05-11T10:28:38.630984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2010 5
13.9%
2009 5
13.9%
2012 3
8.3%
2018 3
8.3%
2002 3
8.3%
2019 2
 
5.6%
2005 2
 
5.6%
2017 2
 
5.6%
2006 2
 
5.6%
2008 2
 
5.6%
Other values (6) 7
19.4%
ValueCountFrequency (%)
1999 1
 
2.8%
2000 1
 
2.8%
2001 1
 
2.8%
2002 3
8.3%
2003 2
5.6%
2004 1
 
2.8%
2005 2
5.6%
2006 2
5.6%
2007 1
 
2.8%
2008 2
5.6%
ValueCountFrequency (%)
2019 2
 
5.6%
2018 3
8.3%
2017 2
 
5.6%
2012 3
8.3%
2010 5
13.9%
2009 5
13.9%
2008 2
 
5.6%
2007 1
 
2.8%
2006 2
 
5.6%
2005 2
 
5.6%

처리방식
Text

Distinct18
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-11T10:28:39.132967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.5555556
Min length3

Characters and Unicode

Total characters236
Distinct characters64
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)27.8%

Sample

1st row토양피복 접촉산화
2nd rowOAM
3rd rowOAM
4th rowFNR
5th row유동상담체
ValueCountFrequency (%)
fnr 8
15.7%
oam 6
 
11.8%
process 6
 
11.8%
유동상담체 4
 
7.8%
apb-sbr 2
 
3.9%
접촉포기 2
 
3.9%
다단계 2
 
3.9%
현수오수 2
 
3.9%
khbnr 2
 
3.9%
오수정화 2
 
3.9%
Other values (14) 15
29.4%
2024-05-11T10:28:40.085038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
6.4%
R 13
 
5.5%
s 12
 
5.1%
N 10
 
4.2%
A 10
 
4.2%
B 9
 
3.8%
M 8
 
3.4%
F 8
 
3.4%
P 8
 
3.4%
수 7
 
3.0%
Other values (54) 136
57.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 89
37.7%
Other Letter 89
37.7%
Lowercase Letter 36
15.3%
Space Separator 15
 
6.4%
Dash Punctuation 3
 
1.3%
Decimal Number 2
 
0.8%
Letter Number 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 7
 
7.9%
촉 4
 
4.5%
화 4
 
4.5%
접 4
 
4.5%
오 4
 
4.5%
기 4
 
4.5%
체 4
 
4.5%
담 4
 
4.5%
상 4
 
4.5%
유 4
 
4.5%
Other values (26) 46
51.7%
Uppercase Letter
ValueCountFrequency (%)
R 13
14.6%
N 10
11.2%
A 10
11.2%
B 9
10.1%
M 8
9.0%
F 8
9.0%
P 8
9.0%
O 6
6.7%
S 6
6.7%
K 2
 
2.2%
Other values (7) 9
10.1%
Lowercase Letter
ValueCountFrequency (%)
s 12
33.3%
e 6
16.7%
o 6
16.7%
r 6
16.7%
c 6
16.7%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 126
53.4%
Hangul 89
37.7%
Common 21
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 7
 
7.9%
촉 4
 
4.5%
화 4
 
4.5%
접 4
 
4.5%
오 4
 
4.5%
기 4
 
4.5%
체 4
 
4.5%
담 4
 
4.5%
상 4
 
4.5%
유 4
 
4.5%
Other values (26) 46
51.7%
Latin
ValueCountFrequency (%)
R 13
 
10.3%
s 12
 
9.5%
N 10
 
7.9%
A 10
 
7.9%
B 9
 
7.1%
M 8
 
6.3%
F 8
 
6.3%
P 8
 
6.3%
e 6
 
4.8%
O 6
 
4.8%
Other values (13) 36
28.6%
Common
ValueCountFrequency (%)
15
71.4%
- 3
 
14.3%
3 1
 
4.8%
. 1
 
4.8%
2 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146
61.9%
Hangul 89
37.7%
Number Forms 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
 
10.3%
R 13
 
8.9%
s 12
 
8.2%
N 10
 
6.8%
A 10
 
6.8%
B 9
 
6.2%
M 8
 
5.5%
F 8
 
5.5%
P 8
 
5.5%
e 6
 
4.1%
Other values (17) 47
32.2%
Hangul
ValueCountFrequency (%)
수 7
 
7.9%
촉 4
 
4.5%
화 4
 
4.5%
접 4
 
4.5%
오 4
 
4.5%
기 4
 
4.5%
체 4
 
4.5%
담 4
 
4.5%
상 4
 
4.5%
유 4
 
4.5%
Other values (26) 46
51.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-08
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-08
2nd row2024-05-08
3rd row2024-05-08
4th row2024-05-08
5th row2024-05-08

Common Values

ValueCountFrequency (%)
2024-05-08 36
100.0%

Length

2024-05-11T10:28:40.686850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:28:41.015013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-05-08 36
100.0%

Interactions

2024-05-11T10:28:28.867775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:28:28.252134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:28:29.183637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:28:28.568590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:28:41.207673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번읍면명시설명소재지주소시설년도처리방식
순번1.0000.8400.9461.0000.4900.642
읍면명0.8401.0000.7241.0000.0000.000
시설명0.9460.7241.0000.9930.9501.000
소재지주소1.0001.0000.9931.0001.0001.000
시설년도0.4900.0000.9501.0001.0000.918
처리방식0.6420.0001.0001.0000.9181.000
2024-05-11T10:28:41.474972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설년도읍면명
순번1.000-0.3120.525
시설년도-0.3121.0000.000
읍면명0.5250.0001.000

Missing values

2024-05-11T10:28:29.746117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:28:30.526490image/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

순번시도시군구읍면명시설명소재지주소시설년도처리방식데이터기준일자
01전라남도신안군압해읍중촌마을하수전라남도 신안군 압해읍 복룡리 121-92019토양피복 접촉산화2024-05-08
12전라남도신안군증도면증동마을하수전라남도 신안군 증도면 증동리 1966-32008OAM2024-05-08
23전라남도신안군증도면우전마을하수전라남도 신안군 증도면 우전리 772012OAM2024-05-08
34전라남도신안군임자면전장마을하수전라남도 신안군 임자면 도찬리 213-42017FNR2024-05-08
45전라남도신안군자은면백길마을하수전라남도 신안군 자은면 유각리 847-12019유동상담체2024-05-08
56전라남도신안군자은면구영마을하수전라남도 신안군 자은면 구영리 1209-12010FNR Process2024-05-08
67전라남도신안군비금면덕산마을하수전라남도 신안군 비금면 덕산리 137-402012SMMIAR2024-05-08
78전라남도신안군비금면내월마을하수전라남도 신안군 비금면 내월리 1073-32006유동상담체2024-05-08
89전라남도신안군비금면용소마을하수전라남도 신안군 비금면 용소리 4892009FNR Process2024-05-08
910전라남도신안군비금면도고마을하수전라남도 신안군 비금면 비금북부길 11252018FNR Process2024-05-08
순번시도시군구읍면명시설명소재지주소시설년도처리방식데이터기준일자
2627전라남도신안군하의면곰실마을하수전라남도 신안군 하의면 곰실길 11-512017FNR2024-05-08
2728전라남도신안군하의면종남마을하수전라남도 신안군 하의면 후광리 63-22002유동상담체2024-05-08
2829전라남도신안군하의면대리마을하수전라남도 신안군 하의면 대리 570-102003KHBNR2024-05-08
2930전라남도신안군하의면신도마을하수전라남도 신안군 하의면 능산리 1035-22000L.C정화 공법2024-05-08
3031전라남도신안군하의면후광마을하수전라남도 신안군 하의면 후광리 645-102009APB-SBR2024-05-08
3132전라남도신안군신의면모농마을하수전라남도 신안군 신의면 상태동리 614-22009DBS2024-05-08
3233전라남도신안군장산면대리마을하수전라남도 신안군 장산면 도창리 945-42010KHBNR2024-05-08
3334전라남도신안군안좌면읍동마을하수전라남도 신안군 안좌면 읍동리 373-22009OAM2024-05-08
3435전라남도신안군팔금면읍리마을하수전라남도 신안군 팔금면 읍리 504-12010FNR Process2024-05-08
3536전라남도신안군암태면장단고마을하수전라남도 신안군 암태면 단고리 5172010FNR Process2024-05-08