Overview

Dataset statistics

Number of variables9
Number of observations763
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.5 KiB
Average record size in memory77.2 B

Variable types

Categorical3
Text1
Numeric5

Dataset

Description전북특별자치도 도시군계획시설 현황(시군구, 시설종류, 시설의세분, 결정시설수 등)행정 구역으로 나눈 시와 도의 이름
Author전북특별자치도
URLhttps://www.data.go.kr/data/15048071/fileData.do

Alerts

시도 has constant value ""Constant
결정 시설수 is highly overall correlated with 결정 면적 and 1 other fieldsHigh correlation
결정 면적 is highly overall correlated with 결정 시설수High correlation
결정 연장 is highly overall correlated with 결정 시설수High correlation
미집행 시설수 is highly overall correlated with 미집행 면적High correlation
미집행 면적 is highly overall correlated with 미집행 시설수High correlation
결정 연장 has 513 (67.2%) zerosZeros
미집행 시설수 has 571 (74.8%) zerosZeros
미집행 면적 has 570 (74.7%) zerosZeros

Reproduction

Analysis started2024-03-14 13:38:18.834119
Analysis finished2024-03-14 13:38:26.434671
Duration7.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
전라북도
763 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 763
100.0%

Length

2024-03-14T22:38:26.845107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:38:27.145489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 763
100.0%

시군구
Categorical

Distinct14
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
전주시
76 
군산시
74 
익산시
72 
정읍시
62 
완주군
62 
Other values (9)
417 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 76
10.0%
군산시 74
9.7%
익산시 72
9.4%
정읍시 62
 
8.1%
완주군 62
 
8.1%
남원시 60
 
7.9%
김제시 55
 
7.2%
고창군 53
 
6.9%
부안군 49
 
6.4%
무주군 43
 
5.6%
Other values (4) 157
20.6%

Length

2024-03-14T22:38:27.465576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 76
10.0%
군산시 74
9.7%
익산시 72
9.4%
정읍시 62
 
8.1%
완주군 62
 
8.1%
남원시 60
 
7.9%
김제시 55
 
7.2%
고창군 53
 
6.9%
부안군 49
 
6.4%
무주군 43
 
5.6%
Other values (4) 157
20.6%

시설 종류
Categorical

Distinct39
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
도로(기능별)
68 
공원
66 
학교
62 
도로
48 
수도공급설비
 
40
Other values (34)
479 

Length

Max length14
Median length13
Mean length4.4023591
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row도로
2nd row도로
3rd row도로
4th row도로
5th row도로(사용형태별)

Common Values

ValueCountFrequency (%)
도로(기능별) 68
 
8.9%
공원 66
 
8.7%
학교 62
 
8.1%
도로 48
 
6.3%
수도공급설비 40
 
5.2%
도로(사용형태별) 37
 
4.8%
광장 35
 
4.6%
체육시설 31
 
4.1%
녹지 29
 
3.8%
하천 28
 
3.7%
Other values (29) 319
41.8%

Length

2024-03-14T22:38:27.788219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로(기능별 68
 
8.3%
공원 66
 
8.1%
학교 62
 
7.6%
도로 48
 
5.9%
수도공급설비 40
 
4.9%
도로(사용형태별 37
 
4.5%
광장 35
 
4.3%
체육시설 31
 
3.8%
녹지 29
 
3.6%
하천 28
 
3.4%
Other values (33) 371
45.5%

시설의 세분
Text

Distinct119
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-03-14T22:38:28.810572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.0589777
Min length2

Characters and Unicode

Total characters3860
Distinct characters143
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

Unique17 ?
Unique (%)2.2%

Sample

1st row광로
2nd row대로
3rd row중로
4th row소로
5th row일반도로
ValueCountFrequency (%)
공공체육시설 14
 
1.8%
일반도로 14
 
1.8%
노외주차장 14
 
1.8%
고등학교 14
 
1.8%
중학교 14
 
1.8%
초등학교 14
 
1.8%
대로 14
 
1.8%
지방하천 14
 
1.8%
여객자동차터미널 14
 
1.8%
근린공원 14
 
1.8%
Other values (110) 629
81.8%
2024-03-14T22:38:30.350415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
설 242
 
6.3%
시 236
 
6.1%
공 202
 
5.2%
로 159
 
4.1%
도 137
 
3.5%
수 119
 
3.1%
지 115
 
3.0%
장 93
 
2.4%
원 88
 
2.3%
자 74
 
1.9%
Other values (133) 2395
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3794
98.3%
Open Punctuation 25
 
0.6%
Close Punctuation 25
 
0.6%
Decimal Number 10
 
0.3%
Space Separator 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 242
 
6.4%
시 236
 
6.2%
공 202
 
5.3%
로 159
 
4.2%
도 137
 
3.6%
수 119
 
3.1%
지 115
 
3.0%
장 93
 
2.5%
원 88
 
2.3%
자 74
 
2.0%
Other values (129) 2329
61.4%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Decimal Number
ValueCountFrequency (%)
9 10
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3794
98.3%
Common 66
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 242
 
6.4%
시 236
 
6.2%
공 202
 
5.3%
로 159
 
4.2%
도 137
 
3.6%
수 119
 
3.1%
지 115
 
3.0%
장 93
 
2.5%
원 88
 
2.3%
자 74
 
2.0%
Other values (129) 2329
61.4%
Common
ValueCountFrequency (%)
( 25
37.9%
) 25
37.9%
9 10
 
15.2%
6
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3794
98.3%
ASCII 66
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
설 242
 
6.4%
시 236
 
6.2%
공 202
 
5.3%
로 159
 
4.2%
도 137
 
3.6%
수 119
 
3.1%
지 115
 
3.0%
장 93
 
2.5%
원 88
 
2.3%
자 74
 
2.0%
Other values (129) 2329
61.4%
ASCII
ValueCountFrequency (%)
( 25
37.9%
) 25
37.9%
9 10
 
15.2%
6
 
9.1%

결정 시설수
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.184797
Minimum1
Maximum3052
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-03-14T22:38:30.652473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q315.5
95-th percentile212.9
Maximum3052
Range3051
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation250.09445
Coefficient of variation (CV)4.2982782
Kurtosis79.579503
Mean58.184797
Median Absolute Deviation (MAD)2
Skewness8.1949952
Sum44395
Variance62547.232
MonotonicityNot monotonic
2024-03-14T22:38:31.086122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 243
31.8%
2 101
13.2%
3 45
 
5.9%
4 37
 
4.8%
5 30
 
3.9%
8 26
 
3.4%
6 19
 
2.5%
9 13
 
1.7%
10 12
 
1.6%
15 10
 
1.3%
Other values (127) 227
29.8%
ValueCountFrequency (%)
1 243
31.8%
2 101
13.2%
3 45
 
5.9%
4 37
 
4.8%
5 30
 
3.9%
6 19
 
2.5%
7 7
 
0.9%
8 26
 
3.4%
9 13
 
1.7%
10 12
 
1.6%
ValueCountFrequency (%)
3052 1
0.1%
3042 1
0.1%
2596 1
0.1%
2122 1
0.1%
1865 1
0.1%
1599 1
0.1%
1283 1
0.1%
1214 1
0.1%
1055 1
0.1%
1035 1
0.1%

결정 면적
Real number (ℝ)

HIGH CORRELATION 

Distinct750
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean839392.48
Minimum0
Maximum14508661
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-03-14T22:38:31.496912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1979.8
Q117920
median87185
Q3606973
95-th percentile4476996.8
Maximum14508661
Range14508661
Interquartile range (IQR)589053

Descriptive statistics

Standard deviation1894311.2
Coefficient of variation (CV)2.2567646
Kurtosis16.242781
Mean839392.48
Median Absolute Deviation (MAD)81246
Skewness3.7003046
Sum6.4045646 × 108
Variance3.5884151 × 1012
MonotonicityNot monotonic
2024-03-14T22:38:31.950567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29248 2
 
0.3%
1005 2
 
0.3%
5995 2
 
0.3%
4570 2
 
0.3%
92 2
 
0.3%
624 2
 
0.3%
39877 2
 
0.3%
23598 2
 
0.3%
1036450 2
 
0.3%
3171 2
 
0.3%
Other values (740) 743
97.4%
ValueCountFrequency (%)
0 1
0.1%
67 1
0.1%
92 2
0.3%
207 1
0.1%
210 1
0.1%
270 1
0.1%
282 1
0.1%
371 1
0.1%
437 1
0.1%
442 1
0.1%
ValueCountFrequency (%)
14508661 1
0.1%
13565358 1
0.1%
12509811 1
0.1%
11996064 1
0.1%
11927499 1
0.1%
11089856 1
0.1%
10857506 1
0.1%
10435944 1
0.1%
10105081 1
0.1%
9613055 1
0.1%

결정 연장
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct243
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39896.659
Minimum0
Maximum1563500
Zeros513
Zeros (%)67.2%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-03-14T22:38:32.374709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34990
95-th percentile245219.5
Maximum1563500
Range1563500
Interquartile range (IQR)4990

Descriptive statistics

Standard deviation119734.24
Coefficient of variation (CV)3.0011094
Kurtosis45.330424
Mean39896.659
Median Absolute Deviation (MAD)0
Skewness5.4865561
Sum30441151
Variance1.4336288 × 1010
MonotonicityNot monotonic
2024-03-14T22:38:32.778836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 513
67.2%
164 2
 
0.3%
34721 2
 
0.3%
914 2
 
0.3%
5412 2
 
0.3%
946 2
 
0.3%
23 2
 
0.3%
3614 2
 
0.3%
104 2
 
0.3%
29555 1
 
0.1%
Other values (233) 233
30.5%
ValueCountFrequency (%)
0 513
67.2%
1 1
 
0.1%
3 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%
11 1
 
0.1%
12 1
 
0.1%
23 2
 
0.3%
24 1
 
0.1%
46 1
 
0.1%
ValueCountFrequency (%)
1563500 1
0.1%
872621 1
0.1%
818814 1
0.1%
778928 1
0.1%
675689 1
0.1%
625216 1
0.1%
588493 1
0.1%
567339 1
0.1%
534284 1
0.1%
530444 1
0.1%

미집행 시설수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6579292
Minimum0
Maximum639
Zeros571
Zeros (%)74.8%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-03-14T22:38:33.119322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile9.9
Maximum639
Range639
Interquartile range (IQR)1

Descriptive statistics

Standard deviation34.618955
Coefficient of variation (CV)7.4322631
Kurtosis201.63776
Mean4.6579292
Median Absolute Deviation (MAD)0
Skewness13.194217
Sum3554
Variance1198.4721
MonotonicityNot monotonic
2024-03-14T22:38:33.531973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 571
74.8%
1 75
 
9.8%
2 30
 
3.9%
3 13
 
1.7%
5 8
 
1.0%
9 8
 
1.0%
4 7
 
0.9%
6 6
 
0.8%
13 4
 
0.5%
7 3
 
0.4%
Other values (28) 38
 
5.0%
ValueCountFrequency (%)
0 571
74.8%
1 75
 
9.8%
2 30
 
3.9%
3 13
 
1.7%
4 7
 
0.9%
5 8
 
1.0%
6 6
 
0.8%
7 3
 
0.4%
8 3
 
0.4%
9 8
 
1.0%
ValueCountFrequency (%)
639 1
0.1%
428 1
0.1%
401 1
0.1%
185 1
0.1%
173 1
0.1%
169 1
0.1%
154 1
0.1%
129 1
0.1%
101 1
0.1%
86 1
0.1%

미집행 면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct194
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70361.536
Minimum0
Maximum8430217
Zeros570
Zeros (%)74.7%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-03-14T22:38:33.953436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3223
95-th percentile269608.6
Maximum8430217
Range8430217
Interquartile range (IQR)223

Descriptive statistics

Standard deviation421323.23
Coefficient of variation (CV)5.9879766
Kurtosis217.30923
Mean70361.536
Median Absolute Deviation (MAD)0
Skewness12.788942
Sum53685852
Variance1.7751326 × 1011
MonotonicityNot monotonic
2024-03-14T22:38:34.393745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 570
74.7%
53707 1
 
0.1%
3120 1
 
0.1%
99511 1
 
0.1%
359129 1
 
0.1%
420 1
 
0.1%
86877 1
 
0.1%
81808 1
 
0.1%
6010 1
 
0.1%
9400 1
 
0.1%
Other values (184) 184
 
24.1%
ValueCountFrequency (%)
0 570
74.7%
122 1
 
0.1%
215 1
 
0.1%
231 1
 
0.1%
294 1
 
0.1%
321 1
 
0.1%
338 1
 
0.1%
351 1
 
0.1%
370 1
 
0.1%
394 1
 
0.1%
ValueCountFrequency (%)
8430217 1
0.1%
3237479 1
0.1%
3112490 1
0.1%
2597194 1
0.1%
2463988 1
0.1%
2393276 1
0.1%
2300644 1
0.1%
2065387 1
0.1%
1983573 1
0.1%
1974768 1
0.1%

Interactions

2024-03-14T22:38:24.899416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:19.405258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:20.771299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:22.156307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:23.558561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:25.061272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:19.672193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:21.047158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:22.432706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:23.819029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:25.233328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:19.954364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:21.326158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:22.732717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:24.096576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:25.409678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:20.243207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:21.619409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:23.020915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:24.378096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:25.572684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:20.514638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:21.896346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:23.294820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:38:24.643197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:38:34.659642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구시설 종류결정 시설수결정 면적결정 연장미집행 시설수미집행 면적
시군구1.0000.0000.1470.0000.0000.0000.000
시설 종류0.0001.0000.0000.4560.5200.1510.289
결정 시설수0.1470.0001.0000.6470.7510.6430.276
결정 면적0.0000.4560.6471.0000.7410.4030.747
결정 연장0.0000.5200.7510.7411.0000.4580.205
미집행 시설수0.0000.1510.6430.4030.4581.0000.650
미집행 면적0.0000.2890.2760.7470.2050.6501.000
2024-03-14T22:38:34.934162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구시설 종류
시군구1.0000.000
시설 종류0.0001.000
2024-03-14T22:38:35.181619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결정 시설수결정 면적결정 연장미집행 시설수미집행 면적시군구시설 종류
결정 시설수1.0000.5980.5460.3080.2740.0620.000
결정 면적0.5981.0000.4690.2780.3000.0000.171
결정 연장0.5460.4691.0000.0310.0140.0000.236
미집행 시설수0.3080.2780.0311.0000.9830.0000.068
미집행 면적0.2740.3000.0140.9831.0000.0000.135
시군구0.0620.0000.0000.0000.0001.0000.000
시설 종류0.0000.1710.2360.0680.1350.0001.000

Missing values

2024-03-14T22:38:25.793469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:38:26.260684image/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

시도시군구시설 종류시설의 세분결정 시설수결정 면적결정 연장미집행 시설수미집행 면적
0전라북도전주시도로광로4143665529555153707
1전라북도전주시도로대로70515067016399711106403
2전라북도전주시도로중로471532880428201546341590
3전라북도전주시도로소로30423539837460000129111577
4전라북도전주시도로(사용형태별)일반도로30521450866187262100
5전라북도전주시도로(사용형태별)자동차전용도로37824183725800
6전라북도전주시도로(사용형태별)보행자전용도로5311634532473200
7전라북도전주시도로(사용형태별)자전거전용도로1143495600
8전라북도전주시도로(기능별)주간선도로58689592621446800
9전라북도전주시도로(기능별)보조간선도로213385892318417800
시도시군구시설 종류시설의 세분결정 시설수결정 면적결정 연장미집행 시설수미집행 면적
753전라북도부안군하천지방하천2540442528710300
754전라북도부안군하천소하천6712385927834300
755전라북도부안군유수지유수시설86821010238800
756전라북도부안군유수지저류시설12799279900
757전라북도부안군도축장도축장11805000
758전라북도부안군하수도공공하수도중 간선하수관43825172400
759전라북도부안군하수도공공하수처리시설1194969805000
760전라북도부안군폐기물처리 및 재활용시설최종처분시설188072000
761전라북도부안군수질오염방지시설폐수종말처리시설22260529300
762전라북도부안군수질오염방지시설분뇨처리시설19992000