Overview

Dataset statistics

Number of variables7
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory63.0 B

Variable types

Text5
Numeric1
DateTime1

Dataset

Description전라남도내 시군의 보건소현황(보건소명, 전화번호, 도로명 주소, 위치 등)에 관한 데이터를 조회하실 수 있습니다.
URLhttps://www.data.go.kr/data/3068470/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
보건소명 has unique valuesUnique
일반전화 has unique valuesUnique
팩스 has unique valuesUnique
우편번호 has unique valuesUnique
도로명주소 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:06:47.500065
Analysis finished2023-12-11 23:06:48.266816
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보건소명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:06:48.376768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.3181818
Min length6

Characters and Unicode

Total characters139
Distinct characters41
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

Unique22 ?
Unique (%)100.0%

Sample

1st row목포시보건소
2nd row여수시보건소
3rd row순천시보건소
4th row나주시보건소
5th row광양시보건소
ValueCountFrequency (%)
목포시보건소 1
 
4.3%
장흥군보건소 1
 
4.3%
진도군보건소 1
 
4.3%
완도군보건의료원 1
 
4.3%
장성군보건소 1
 
4.3%
영광군보건소 1
 
4.3%
함평군보건소 1
 
4.3%
무안군보건소 1
 
4.3%
영암군보건소 1
 
4.3%
해남군보건소 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T08:06:48.693691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 23
16.5%
건 22
15.8%
소 19
13.7%
군 17
12.2%
시 5
 
3.6%
원 3
 
2.2%
료 3
 
2.2%
의 3
 
2.2%
성 3
 
2.2%
장 2
 
1.4%
Other values (31) 39
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138
99.3%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 23
16.7%
건 22
15.9%
소 19
13.8%
군 17
12.3%
시 5
 
3.6%
원 3
 
2.2%
료 3
 
2.2%
의 3
 
2.2%
성 3
 
2.2%
장 2
 
1.4%
Other values (30) 38
27.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 23
16.7%
건 22
15.9%
소 19
13.8%
군 17
12.3%
시 5
 
3.6%
원 3
 
2.2%
료 3
 
2.2%
의 3
 
2.2%
성 3
 
2.2%
장 2
 
1.4%
Other values (30) 38
27.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 23
16.7%
건 22
15.9%
소 19
13.8%
군 17
12.3%
시 5
 
3.6%
원 3
 
2.2%
료 3
 
2.2%
의 3
 
2.2%
성 3
 
2.2%
장 2
 
1.4%
Other values (30) 38
27.5%
ASCII
ValueCountFrequency (%)
1
100.0%

일반전화
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:06:48.851999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters264
Distinct characters11
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

Unique22 ?
Unique (%)100.0%

Sample

1st row061-277-4000
2nd row061-683-4000
3rd row061-749-6914
4th row061-339-2171
5th row061-797-4023
ValueCountFrequency (%)
061-277-4000 1
 
4.5%
061-683-4000 1
 
4.5%
061-540-6005 1
 
4.5%
061-550-6720 1
 
4.5%
061-390-8302 1
 
4.5%
061-350-5551 1
 
4.5%
061-320-2405 1
 
4.5%
061-450-5014 1
 
4.5%
061-472-4000 1
 
4.5%
061-531-3738 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T08:06:49.101575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62
23.5%
- 44
16.7%
1 30
11.4%
6 29
11.0%
3 23
 
8.7%
5 21
 
8.0%
4 16
 
6.1%
2 13
 
4.9%
7 11
 
4.2%
8 9
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
83.3%
Dash Punctuation 44
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
28.2%
1 30
13.6%
6 29
13.2%
3 23
 
10.5%
5 21
 
9.5%
4 16
 
7.3%
2 13
 
5.9%
7 11
 
5.0%
8 9
 
4.1%
9 6
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62
23.5%
- 44
16.7%
1 30
11.4%
6 29
11.0%
3 23
 
8.7%
5 21
 
8.0%
4 16
 
6.1%
2 13
 
4.9%
7 11
 
4.2%
8 9
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62
23.5%
- 44
16.7%
1 30
11.4%
6 29
11.0%
3 23
 
8.7%
5 21
 
8.0%
4 16
 
6.1%
2 13
 
4.9%
7 11
 
4.2%
8 9
 
3.4%

팩스
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:06:49.263128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters264
Distinct characters11
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

Unique22 ?
Unique (%)100.0%

Sample

1st row061-270-3597
2nd row061-659-5839
3rd row061-749-4707
4th row061-339-2833
5th row061-797-4151
ValueCountFrequency (%)
061-270-3597 1
 
4.5%
061-659-5839 1
 
4.5%
061-544-0902 1
 
4.5%
061-550-6787 1
 
4.5%
061-390-7598 1
 
4.5%
061-350-5124 1
 
4.5%
061-320-3527 1
 
4.5%
061-450-5134 1
 
4.5%
061-470-6576 1
 
4.5%
061-530-5597 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T08:06:49.522110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
18.2%
- 44
16.7%
6 29
11.0%
1 26
9.8%
5 25
9.5%
3 22
8.3%
7 20
7.6%
9 19
 
7.2%
8 12
 
4.5%
4 11
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
83.3%
Dash Punctuation 44
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
21.8%
6 29
13.2%
1 26
11.8%
5 25
11.4%
3 22
10.0%
7 20
9.1%
9 19
 
8.6%
8 12
 
5.5%
4 11
 
5.0%
2 8
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
18.2%
- 44
16.7%
6 29
11.0%
1 26
9.8%
5 25
9.5%
3 22
8.3%
7 20
7.6%
9 19
 
7.2%
8 12
 
4.5%
4 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
18.2%
- 44
16.7%
6 29
11.0%
1 26
9.8%
5 25
9.5%
3 22
8.3%
7 20
7.6%
9 19
 
7.2%
8 12
 
4.5%
4 11
 
4.2%

우편번호
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58396.136
Minimum57043
Maximum59674
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T08:06:49.623895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57043
5-th percentile57156.3
Q157677.25
median58476.5
Q359090.5
95-th percentile59537.65
Maximum59674
Range2631
Interquartile range (IQR)1413.25

Descriptive statistics

Standard deviation844.59037
Coefficient of variation (CV)0.014463121
Kurtosis-1.3087553
Mean58396.136
Median Absolute Deviation (MAD)749.5
Skewness-0.13993614
Sum1284715
Variance713332.89
MonotonicityNot monotonic
2023-12-12T08:06:49.711330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
58613 1
 
4.5%
59240 1
 
4.5%
58827 1
 
4.5%
58915 1
 
4.5%
59108 1
 
4.5%
57219 1
 
4.5%
57043 1
 
4.5%
57153 1
 
4.5%
58532 1
 
4.5%
58421 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
57043 1
4.5%
57153 1
4.5%
57219 1
4.5%
57335 1
4.5%
57542 1
4.5%
57656 1
4.5%
57741 1
4.5%
57938 1
4.5%
58122 1
4.5%
58274 1
4.5%
ValueCountFrequency (%)
59674 1
4.5%
59542 1
4.5%
59455 1
4.5%
59327 1
4.5%
59240 1
4.5%
59108 1
4.5%
59038 1
4.5%
58915 1
4.5%
58827 1
4.5%
58613 1
4.5%

도로명주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:06:49.893023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length17.5
Min length15

Characters and Unicode

Total characters385
Distinct characters84
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row전남 목포시 원산로45번길 5
2nd row전남 여수시 시청서4길 23
3rd row전남 순천시 중앙로 232(석현동)
4th row전남 나주시 풍물시장 2길 57-32
5th row전남 광양시 인덕로 1100
ValueCountFrequency (%)
전남 22
 
22.2%
영암읍 1
 
1.0%
함평읍 1
 
1.0%
함평군 1
 
1.0%
530 1
 
1.0%
무안로 1
 
1.0%
무안읍 1
 
1.0%
무안군 1
 
1.0%
오리정길39 1
 
1.0%
영암군 1
 
1.0%
Other values (68) 68
68.7%
2023-12-12T08:06:50.190364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
20.0%
남 27
 
7.0%
전 22
 
5.7%
군 17
 
4.4%
읍 16
 
4.2%
1 14
 
3.6%
길 13
 
3.4%
로 11
 
2.9%
4 10
 
2.6%
3 10
 
2.6%
Other values (74) 168
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 237
61.6%
Space Separator 77
 
20.0%
Decimal Number 65
 
16.9%
Dash Punctuation 4
 
1.0%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 27
 
11.4%
전 22
 
9.3%
군 17
 
7.2%
읍 16
 
6.8%
길 13
 
5.5%
로 11
 
4.6%
성 8
 
3.4%
시 7
 
3.0%
장 5
 
2.1%
흥 5
 
2.1%
Other values (60) 106
44.7%
Decimal Number
ValueCountFrequency (%)
1 14
21.5%
4 10
15.4%
3 10
15.4%
0 8
12.3%
5 8
12.3%
2 6
9.2%
9 3
 
4.6%
6 2
 
3.1%
8 2
 
3.1%
7 2
 
3.1%
Space Separator
ValueCountFrequency (%)
77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 237
61.6%
Common 148
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 27
 
11.4%
전 22
 
9.3%
군 17
 
7.2%
읍 16
 
6.8%
길 13
 
5.5%
로 11
 
4.6%
성 8
 
3.4%
시 7
 
3.0%
장 5
 
2.1%
흥 5
 
2.1%
Other values (60) 106
44.7%
Common
ValueCountFrequency (%)
77
52.0%
1 14
 
9.5%
4 10
 
6.8%
3 10
 
6.8%
0 8
 
5.4%
5 8
 
5.4%
2 6
 
4.1%
- 4
 
2.7%
9 3
 
2.0%
6 2
 
1.4%
Other values (4) 6
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 237
61.6%
ASCII 148
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
52.0%
1 14
 
9.5%
4 10
 
6.8%
3 10
 
6.8%
0 8
 
5.4%
5 8
 
5.4%
2 6
 
4.1%
- 4
 
2.7%
9 3
 
2.0%
6 2
 
1.4%
Other values (4) 6
 
4.1%
Hangul
ValueCountFrequency (%)
남 27
 
11.4%
전 22
 
9.3%
군 17
 
7.2%
읍 16
 
6.8%
길 13
 
5.5%
로 11
 
4.6%
성 8
 
3.4%
시 7
 
3.0%
장 5
 
2.1%
흥 5
 
2.1%
Other values (60) 106
44.7%

위치
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:06:50.345236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length9.2272727
Min length4

Characters and Unicode

Total characters203
Distinct characters93
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row서부초등옆
2nd row시청 옆
3rd row순천대학교 맞은편
4th row풍물시장 옆
5th row광양시 제2청사 내
ValueCountFrequency (%)
옆 10
 
20.0%
군청 2
 
4.0%
축협하나로마트 1
 
2.0%
마켓 1
 
2.0%
뒤 1
 
2.0%
해남동초등학교 1
 
2.0%
영암터미널앞 1
 
2.0%
100미터 1
 
2.0%
무안군청 1
 
2.0%
함평공용터미널 1
 
2.0%
Other values (30) 30
60.0%
2023-12-12T08:06:50.605696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
14.3%
옆 11
 
5.4%
0 9
 
4.4%
터 7
 
3.4%
미 7
 
3.4%
청 6
 
3.0%
서 5
 
2.5%
군 5
 
2.5%
편 3
 
1.5%
마 3
 
1.5%
Other values (83) 118
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157
77.3%
Space Separator 29
 
14.3%
Decimal Number 15
 
7.4%
Lowercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옆 11
 
7.0%
터 7
 
4.5%
미 7
 
4.5%
청 6
 
3.8%
서 5
 
3.2%
군 5
 
3.2%
편 3
 
1.9%
마 3
 
1.9%
에 3
 
1.9%
로 3
 
1.9%
Other values (74) 104
66.2%
Decimal Number
ValueCountFrequency (%)
0 9
60.0%
1 2
 
13.3%
5 1
 
6.7%
2 1
 
6.7%
3 1
 
6.7%
8 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157
77.3%
Common 44
 
21.7%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옆 11
 
7.0%
터 7
 
4.5%
미 7
 
4.5%
청 6
 
3.8%
서 5
 
3.2%
군 5
 
3.2%
편 3
 
1.9%
마 3
 
1.9%
에 3
 
1.9%
로 3
 
1.9%
Other values (74) 104
66.2%
Common
ValueCountFrequency (%)
29
65.9%
0 9
 
20.5%
1 2
 
4.5%
5 1
 
2.3%
2 1
 
2.3%
3 1
 
2.3%
8 1
 
2.3%
Latin
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157
77.3%
ASCII 46
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
63.0%
0 9
 
19.6%
1 2
 
4.3%
5 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
8 1
 
2.2%
s 1
 
2.2%
k 1
 
2.2%
Hangul
ValueCountFrequency (%)
옆 11
 
7.0%
터 7
 
4.5%
미 7
 
4.5%
청 6
 
3.8%
서 5
 
3.2%
군 5
 
3.2%
편 3
 
1.9%
마 3
 
1.9%
에 3
 
1.9%
로 3
 
1.9%
Other values (74) 104
66.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-12T08:06:50.696124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:50.773952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:06:47.778470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:06:50.832616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보건소명일반전화팩스우편번호도로명주소위치
보건소명1.0001.0001.0001.0001.0001.000
일반전화1.0001.0001.0001.0001.0001.000
팩스1.0001.0001.0001.0001.0001.000
우편번호1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T08:06:48.133742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:06:48.227765image/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

보건소명일반전화팩스우편번호도로명주소위치데이터기준일자
0목포시보건소061-277-4000061-270-359758613전남 목포시 원산로45번길 5서부초등옆2023-08-01
1여수시보건소061-683-4000061-659-583959674전남 여수시 시청서4길 23시청 옆2023-08-01
2순천시보건소061-749-6914061-749-470757938전남 순천시 중앙로 232(석현동)순천대학교 맞은편2023-08-01
3나주시보건소061-339-2171061-339-283358274전남 나주시 풍물시장 2길 57-32풍물시장 옆2023-08-01
4광양시보건소061-797-4023061-797-415157741전남 광양시 인덕로 1100광양시 제2청사 내2023-08-01
5담양군보건소061-383-4000061-380-399057335전남 담양군 담양읍 완동길 10-11여성회관 옆2023-08-01
6곡성군보건의료원061-362-4000061-360-859757542전남 곡성군 곡성읍 곡성로 854군청 뒤편 300미터 지점2023-08-01
7구례군보건의료원061-780-2003061-780-277057656전남 구례군구례읍 동편제길 30군청에서 남원방향 80미터2023-08-01
8고흥군보건소061-830-5321061-830-559359542전남 고흥군 고흥읍등암3길5등암sk가스충전소에서100미터2023-08-01
9보성군 보건소061-850-5651061-850-569959455전남 보성군 보성읍 송재로 153군청 옆2023-08-01
보건소명일반전화팩스우편번호도로명주소위치데이터기준일자
12강진군보건소061-430-3530061-430-353959240전남 강진군 강진읍 목리길 11농협파머스 마켓 뒤2023-08-01
13해남군보건소061-531-3738061-530-559759038전남 해남군 해남읍 해남로 46해남동초등학교 옆2023-08-01
14영암군보건소061-472-4000061-470-657658421전남 영암군 영암읍 오리정길39영암터미널앞 100미터2023-08-01
15무안군보건소061-450-5014061-450-513458532전남 무안군 무안읍 무안로 530무안군청 옆2023-08-01
16함평군보건소061-320-2405061-320-352757153전남 함평군 함평읍 중앙길 54-8함평공용터미널 뒷편2023-08-01
17영광군보건소061-350-5551061-350-512457043전남 영광군 영광읍 신남로 4길 17축협하나로마트 옆2023-08-01
18장성군보건소061-390-8302061-390-759857219전남 장성군 장성읍 청운11길 13장성역에서 북쪽으로 500미터2023-08-01
19완도군보건의료원061-550-6720061-550-678759108전남 완도군 완도읍 농공단지길34완도경찰서 옆2023-08-01
20진도군보건소061-540-6005061-544-090258915전남 진도군 남동1길 40-9농협하나로마트 옆2023-08-01
21신안군보건소061-243-8550061-240-800058827전남 신안군 압해읍 천사로 1004압해대교 끝 좌회전2023-08-01