Overview

Dataset statistics

Number of variables7
Number of observations179
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.3 KiB
Average record size in memory58.7 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description전라남도 내 179개소 민방위 비상급수시설에 대한 정보를 조회하실 수 있습니다- 용도, 시설명칭, 도로명주소, 급수용량, 사용가능 인원 등
Author전라남도
URLhttps://www.data.go.kr/data/15126377/fileData.do

Alerts

급수용량_톤(일) is highly overall correlated with 사용가능 인원_명High correlation
사용가능 인원_명 is highly overall correlated with 급수용량_톤(일)High correlation

Reproduction

Analysis started2024-03-14 20:54:50.289929
Analysis finished2024-03-14 20:54:52.191397
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct22
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
여수시
43 
목포시
28 
순천시
24 
광양시
15 
완도군
8 
Other values (17)
61 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여수시 43
24.0%
목포시 28
15.6%
순천시 24
13.4%
광양시 15
 
8.4%
완도군 8
 
4.5%
화순군 6
 
3.4%
영광군 5
 
2.8%
강진군 5
 
2.8%
고흥군 4
 
2.2%
곡성군 4
 
2.2%
Other values (12) 37
20.7%

Length

2024-03-15T05:54:52.308584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수시 43
24.0%
목포시 28
15.6%
순천시 24
13.4%
광양시 15
 
8.4%
완도군 8
 
4.5%
화순군 6
 
3.4%
영광군 5
 
2.8%
강진군 5
 
2.8%
나주시 4
 
2.2%
보성군 4
 
2.2%
Other values (12) 37
20.7%

읍면동
Text

Distinct95
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-15T05:54:53.466231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.972067
Min length2

Characters and Unicode

Total characters532
Distinct characters100
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

Unique54 ?
Unique (%)30.2%

Sample

1st row군동면
2nd row강진읍
3rd row군동면
4th row도암면
5th row성전면
ValueCountFrequency (%)
화순읍 6
 
3.4%
왕조1동 5
 
2.8%
신기동 5
 
2.8%
광양읍 5
 
2.8%
여서동 5
 
2.8%
상동 5
 
2.8%
국동 5
 
2.8%
마동 4
 
2.2%
삼향동 4
 
2.2%
용당1동 4
 
2.2%
Other values (85) 131
73.2%
2024-03-15T05:54:54.935377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 107
 
20.1%
읍 57
 
10.7%
면 18
 
3.4%
광 11
 
2.1%
도 11
 
2.1%
화 11
 
2.1%
양 10
 
1.9%
산 10
 
1.9%
조 9
 
1.7%
1 9
 
1.7%
Other values (90) 279
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 519
97.6%
Decimal Number 13
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 107
20.6%
읍 57
 
11.0%
면 18
 
3.5%
광 11
 
2.1%
도 11
 
2.1%
화 11
 
2.1%
양 10
 
1.9%
산 10
 
1.9%
조 9
 
1.7%
덕 9
 
1.7%
Other values (88) 266
51.3%
Decimal Number
ValueCountFrequency (%)
1 9
69.2%
2 4
30.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 519
97.6%
Common 13
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 107
20.6%
읍 57
 
11.0%
면 18
 
3.5%
광 11
 
2.1%
도 11
 
2.1%
화 11
 
2.1%
양 10
 
1.9%
산 10
 
1.9%
조 9
 
1.7%
덕 9
 
1.7%
Other values (88) 266
51.3%
Common
ValueCountFrequency (%)
1 9
69.2%
2 4
30.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 519
97.6%
ASCII 13
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 107
20.6%
읍 57
 
11.0%
면 18
 
3.5%
광 11
 
2.1%
도 11
 
2.1%
화 11
 
2.1%
양 10
 
1.9%
산 10
 
1.9%
조 9
 
1.7%
덕 9
 
1.7%
Other values (88) 266
51.3%
ASCII
ValueCountFrequency (%)
1 9
69.2%
2 4
30.8%

용도
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
음용수
95 
생활용수
84 

Length

Max length4
Median length3
Mean length3.4692737
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음용수
2nd row생활용수
3rd row음용수
4th row음용수
5th row음용수

Common Values

ValueCountFrequency (%)
음용수 95
53.1%
생활용수 84
46.9%

Length

2024-03-15T05:54:55.349674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:54:55.687209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음용수 95
53.1%
생활용수 84
46.9%

시설명칭
Text

Distinct178
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-15T05:54:56.862595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length12.692737
Min length9

Characters and Unicode

Total characters2272
Distinct characters214
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)98.9%

Sample

1st row강진종합운동장 비상급수시설
2nd row고성사 비상급수시설
3rd row군동면 비상급수시설
4th row도암면 비상급수시설
5th row성전면 비상급수시설
ValueCountFrequency (%)
비상급수시설 178
48.8%
전라남도 3
 
0.8%
무등산골프장(서태리 2
 
0.5%
금호아파트 2
 
0.5%
832 1
 
0.3%
장미아파트 1
 
0.3%
미평동주민센터 1
 
0.3%
복지회관 1
 
0.3%
신기어린이소공원 1
 
0.3%
미평주공아파트 1
 
0.3%
Other values (174) 174
47.7%
2024-03-15T05:54:58.605221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
8.3%
수 188
 
8.3%
시 182
 
8.0%
상 180
 
7.9%
설 180
 
7.9%
급 178
 
7.8%
비 178
 
7.8%
공 32
 
1.4%
파 32
 
1.4%
아 31
 
1.4%
Other values (204) 902
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2032
89.4%
Space Separator 189
 
8.3%
Decimal Number 25
 
1.1%
Close Punctuation 9
 
0.4%
Open Punctuation 9
 
0.4%
Uppercase Letter 4
 
0.2%
Dash Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 188
 
9.3%
시 182
 
9.0%
상 180
 
8.9%
설 180
 
8.9%
급 178
 
8.8%
비 178
 
8.8%
공 32
 
1.6%
파 32
 
1.6%
아 31
 
1.5%
트 30
 
1.5%
Other values (190) 821
40.4%
Decimal Number
ValueCountFrequency (%)
3 7
28.0%
2 6
24.0%
1 6
24.0%
9 2
 
8.0%
8 2
 
8.0%
5 1
 
4.0%
0 1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
A 2
50.0%
Space Separator
ValueCountFrequency (%)
189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2032
89.4%
Common 236
 
10.4%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 188
 
9.3%
시 182
 
9.0%
상 180
 
8.9%
설 180
 
8.9%
급 178
 
8.8%
비 178
 
8.8%
공 32
 
1.6%
파 32
 
1.6%
아 31
 
1.5%
트 30
 
1.5%
Other values (190) 821
40.4%
Common
ValueCountFrequency (%)
189
80.1%
) 9
 
3.8%
( 9
 
3.8%
3 7
 
3.0%
2 6
 
2.5%
1 6
 
2.5%
- 3
 
1.3%
9 2
 
0.8%
8 2
 
0.8%
~ 1
 
0.4%
Other values (2) 2
 
0.8%
Latin
ValueCountFrequency (%)
B 2
50.0%
A 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2032
89.4%
ASCII 240
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
78.8%
) 9
 
3.8%
( 9
 
3.8%
3 7
 
2.9%
2 6
 
2.5%
1 6
 
2.5%
- 3
 
1.2%
9 2
 
0.8%
8 2
 
0.8%
B 2
 
0.8%
Other values (4) 5
 
2.1%
Hangul
ValueCountFrequency (%)
수 188
 
9.3%
시 182
 
9.0%
상 180
 
8.9%
설 180
 
8.9%
급 178
 
8.8%
비 178
 
8.8%
공 32
 
1.6%
파 32
 
1.6%
아 31
 
1.5%
트 30
 
1.5%
Other values (190) 821
40.4%

도로명 주소
Text

Distinct177
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-15T05:55:00.144602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length21.290503
Min length14

Characters and Unicode

Total characters3811
Distinct characters195
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)97.8%

Sample

1st row전라남도 강진군 군동면 종합운동장길 85
2nd row전라남도 강진군 강진읍 고성길 36
3rd row전라남도 강진군 군동면 진흥로 315
4th row전라남도 강진군 도암면 도암중앙로 73
5th row전라남도 강진군 성전면 예향로 16
ValueCountFrequency (%)
전라남도 179
 
20.6%
여수시 43
 
4.9%
목포시 28
 
3.2%
순천시 24
 
2.8%
광양시 15
 
1.7%
완도군 8
 
0.9%
화순군 6
 
0.7%
화순읍 6
 
0.7%
영광군 5
 
0.6%
광양읍 5
 
0.6%
Other values (413) 551
63.3%
2024-03-15T05:55:02.276452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
693
 
18.2%
도 203
 
5.3%
남 196
 
5.1%
전 184
 
4.8%
라 180
 
4.7%
1 127
 
3.3%
시 115
 
3.0%
로 95
 
2.5%
길 76
 
2.0%
2 75
 
2.0%
Other values (185) 1867
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2387
62.6%
Space Separator 693
 
18.2%
Decimal Number 554
 
14.5%
Close Punctuation 58
 
1.5%
Open Punctuation 58
 
1.5%
Dash Punctuation 46
 
1.2%
Other Punctuation 11
 
0.3%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 203
 
8.5%
남 196
 
8.2%
전 184
 
7.7%
라 180
 
7.5%
시 115
 
4.8%
로 95
 
4.0%
길 76
 
3.2%
군 69
 
2.9%
동 58
 
2.4%
읍 58
 
2.4%
Other values (169) 1153
48.3%
Decimal Number
ValueCountFrequency (%)
1 127
22.9%
2 75
13.5%
3 66
11.9%
5 50
 
9.0%
0 47
 
8.5%
7 45
 
8.1%
4 41
 
7.4%
9 39
 
7.0%
6 35
 
6.3%
8 29
 
5.2%
Space Separator
ValueCountFrequency (%)
693
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2387
62.6%
Common 1420
37.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 203
 
8.5%
남 196
 
8.2%
전 184
 
7.7%
라 180
 
7.5%
시 115
 
4.8%
로 95
 
4.0%
길 76
 
3.2%
군 69
 
2.9%
동 58
 
2.4%
읍 58
 
2.4%
Other values (169) 1153
48.3%
Common
ValueCountFrequency (%)
693
48.8%
1 127
 
8.9%
2 75
 
5.3%
3 66
 
4.6%
) 58
 
4.1%
( 58
 
4.1%
5 50
 
3.5%
0 47
 
3.3%
- 46
 
3.2%
7 45
 
3.2%
Other values (5) 155
 
10.9%
Latin
ValueCountFrequency (%)
C 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2387
62.6%
ASCII 1424
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
693
48.7%
1 127
 
8.9%
2 75
 
5.3%
3 66
 
4.6%
) 58
 
4.1%
( 58
 
4.1%
5 50
 
3.5%
0 47
 
3.3%
- 46
 
3.2%
7 45
 
3.2%
Other values (6) 159
 
11.2%
Hangul
ValueCountFrequency (%)
도 203
 
8.5%
남 196
 
8.2%
전 184
 
7.7%
라 180
 
7.5%
시 115
 
4.8%
로 95
 
4.0%
길 76
 
3.2%
군 69
 
2.9%
동 58
 
2.4%
읍 58
 
2.4%
Other values (169) 1153
48.3%

급수용량_톤(일)
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199.8324
Minimum50
Maximum635
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-15T05:55:02.965413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile80
Q1108
median160
Q3250
95-th percentile500
Maximum635
Range585
Interquartile range (IQR)142

Descriptive statistics

Standard deviation117.36017
Coefficient of variation (CV)0.587293
Kurtosis1.9098215
Mean199.8324
Median Absolute Deviation (MAD)60
Skewness1.4252741
Sum35770
Variance13773.41
MonotonicityNot monotonic
2024-03-15T05:55:03.428117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 27
15.1%
300 20
 
11.2%
200 18
 
10.1%
150 17
 
9.5%
500 9
 
5.0%
250 8
 
4.5%
120 7
 
3.9%
160 6
 
3.4%
80 4
 
2.2%
50 4
 
2.2%
Other values (42) 59
33.0%
ValueCountFrequency (%)
50 4
 
2.2%
60 4
 
2.2%
80 4
 
2.2%
81 1
 
0.6%
90 1
 
0.6%
100 27
15.1%
103 1
 
0.6%
105 1
 
0.6%
106 2
 
1.1%
110 2
 
1.1%
ValueCountFrequency (%)
635 1
 
0.6%
580 1
 
0.6%
542 1
 
0.6%
500 9
5.0%
440 1
 
0.6%
400 2
 
1.1%
350 1
 
0.6%
322 1
 
0.6%
318 1
 
0.6%
315 1
 
0.6%

사용가능 인원_명
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17508.173
Minimum3125
Maximum64444
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-15T05:55:03.930899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3125
5-th percentile5555
Q19562.5
median13333
Q322222
95-th percentile33387.2
Maximum64444
Range61319
Interquartile range (IQR)12659.5

Descriptive statistics

Standard deviation11274.865
Coefficient of variation (CV)0.64397723
Kurtosis2.880195
Mean17508.173
Median Absolute Deviation (MAD)5417
Skewness1.5437107
Sum3133963
Variance1.2712258 × 108
MonotonicityNot monotonic
2024-03-15T05:55:04.384383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11111 15
 
8.4%
33333 14
 
7.8%
6250 12
 
6.7%
22222 12
 
6.7%
16666 9
 
5.0%
9375 8
 
4.5%
18750 6
 
3.4%
12500 6
 
3.4%
31250 5
 
2.8%
13333 5
 
2.8%
Other values (56) 87
48.6%
ValueCountFrequency (%)
3125 1
 
0.6%
3750 1
 
0.6%
5000 4
 
2.2%
5062 1
 
0.6%
5555 3
 
1.7%
6250 12
6.7%
6625 1
 
0.6%
6666 3
 
1.7%
6875 1
 
0.6%
7187 2
 
1.1%
ValueCountFrequency (%)
64444 1
 
0.6%
55555 4
 
2.2%
48888 1
 
0.6%
39687 1
 
0.6%
35333 1
 
0.6%
33875 1
 
0.6%
33333 14
7.8%
31250 5
 
2.8%
31111 1
 
0.6%
28888 1
 
0.6%

Interactions

2024-03-15T05:54:51.442999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:54:50.941675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:54:51.595340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:54:51.236919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:55:04.702278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명읍면동용도급수용량_톤(일)사용가능 인원_명
시군명1.0001.0000.3210.0000.000
읍면동1.0001.0000.5080.0000.000
용도0.3210.5081.0000.0000.433
급수용량_톤(일)0.0000.0000.0001.0000.885
사용가능 인원_명0.0000.0000.4330.8851.000
2024-03-15T05:55:05.035210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도시군명
용도1.0000.238
시군명0.2381.000
2024-03-15T05:55:05.411716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수용량_톤(일)사용가능 인원_명시군명용도
급수용량_톤(일)1.0000.8780.0000.000
사용가능 인원_명0.8781.0000.0000.429
시군명0.0000.0001.0000.238
용도0.0000.4290.2381.000

Missing values

2024-03-15T05:54:51.796594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:54:52.110557image/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

시군명읍면동용도시설명칭도로명 주소급수용량_톤(일)사용가능 인원_명
0강진군군동면음용수강진종합운동장 비상급수시설전라남도 강진군 군동면 종합운동장길 8520522777
1강진군강진읍생활용수고성사 비상급수시설전라남도 강진군 강진읍 고성길 3616710437
2강진군군동면음용수군동면 비상급수시설전라남도 강진군 군동면 진흥로 31530033333
3강진군도암면음용수도암면 비상급수시설전라남도 강진군 도암면 도암중앙로 7315016666
4강진군성전면음용수성전면 비상급수시설전라남도 강진군 성전면 예향로 1615617333
5고흥군고흥읍생활용수고흥읍사무소 비상급수시설전라남도 고흥군 고흥읍 터미널길 11-0 (고흥읍사무소)30018750
6고흥군도양읍생활용수도양관하마을 비상급수시설전라남도 고흥군 도양읍 관리 1917번지20012500
7고흥군도화면음용수도화면신호 비상급수시설전라남도 고흥군 도화면 신호리 470번지 1호20022222
8고흥군풍양면음용수참샘의물 비상급수시설전라남도 고흥군 풍양면 한동리 38번지20022222
9곡성군곡성읍생활용수전라남도 곡성군민회관 비상급수시설전라남도 곡성군 곡성읍 중앙로 5930018750
시군명읍면동용도시설명칭도로명 주소급수용량_톤(일)사용가능 인원_명
169함평군해보면음용수해보면 비상급수시설전라남도 함평군 해보면 밀재로 1264-7 (해보면사무소)15016666
170해남군해남읍음용수금강곡 비상급수시설전라남도 해남군 해남읍 해리 산 57-131835333
171해남군해남읍음용수서림공원 비상급수시설전라남도 해남군 해남읍 구교리 372번지 2호20022222
172해남군해남읍음용수우슬체육공원 비상급수시설전라남도 해남군 해남읍 해리 4번지 45호20022222
173화순군화순읍음용수광덕택지어린이놀이터 비상급수시설전라남도 화순군 화순읍 일심4길 7-730033333
174화순군화순읍음용수무등산골프장(서태리 820) 비상급수시설전라남도 화순군 화순읍 오성로 292-90 (무등산CC)20022222
175화순군화순읍생활용수무등산골프장(서태리 832) 비상급수시설전라남도 화순군 화순읍 오성로 292-90 (무등산CC)40025000
176화순군화순읍음용수화순 (구)119안전센터 비상급수시설전라남도 화순군 화순읍 충의로 100 (구 119 안전센터)30033333
177화순군화순읍음용수화순소방서 비상급수시설전라남도 화순군 화순읍 학포로 2750 (화순소방서)10011111
178화순군화순읍생활용수화순초등학교 비상급수시설전라남도 화순군 화순읍 동헌길 9-7 (화순초등학교)1006250