Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory61.5 B

Variable types

Text5
Categorical2

Dataset

Description산청군의 보건지소 및 보건진료소(명칭, 소재지 주소, 전화번호, 진료과목, 관할구역, 위치, 데이터기준일자)에 대한 공공데이터 자료입니다.
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3038009

Alerts

데이터기준일자 has constant value ""Constant
명칭 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique
관할구역 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:33:03.428252
Analysis finished2023-12-10 23:33:04.154258
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:33:04.276947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.75
Min length6

Characters and Unicode

Total characters162
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row덕산통합보건지소
2nd row차황보건지소
3rd row오부보건지소
4th row생초보건지소
5th row금서보건지소
ValueCountFrequency (%)
덕산통합보건지소 1
 
4.2%
차황보건지소 1
 
4.2%
가계보건진료소 1
 
4.2%
신안보건진료소 1
 
4.2%
문대보건진료소 1
 
4.2%
소남보건진료소 1
 
4.2%
입석보건진료소 1
 
4.2%
서부보건진료소 1
 
4.2%
내대보건진료소 1
 
4.2%
중산보건진료소 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T08:33:04.628319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 25
15.4%
보 24
14.8%
건 24
14.8%
료 15
 
9.3%
진 15
 
9.3%
지 9
 
5.6%
신 3
 
1.9%
오 2
 
1.2%
평 2
 
1.2%
안 2
 
1.2%
Other values (34) 41
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 25
15.4%
보 24
14.8%
건 24
14.8%
료 15
 
9.3%
진 15
 
9.3%
지 9
 
5.6%
신 3
 
1.9%
오 2
 
1.2%
평 2
 
1.2%
안 2
 
1.2%
Other values (34) 41
25.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 25
15.4%
보 24
14.8%
건 24
14.8%
료 15
 
9.3%
진 15
 
9.3%
지 9
 
5.6%
신 3
 
1.9%
오 2
 
1.2%
평 2
 
1.2%
안 2
 
1.2%
Other values (34) 41
25.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 25
15.4%
보 24
14.8%
건 24
14.8%
료 15
 
9.3%
진 15
 
9.3%
지 9
 
5.6%
신 3
 
1.9%
오 2
 
1.2%
평 2
 
1.2%
안 2
 
1.2%
Other values (34) 41
25.3%

주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:33:04.843917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length22.416667
Min length18

Characters and Unicode

Total characters538
Distinct characters71
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

Unique24 ?
Unique (%)100.0%

Sample

1st row경상남도 산청군 삼장면 덕산대포로245번길 2
2nd row경상남도 산청군 차황면 친환경로3561번길 22-11
3rd row경상남도 산청군 오부면 오동로 643-7
4th row경상남도 산청군 생초면 새실로 5
5th row경상남도 산청군 금서면 동의보감로 1045-7
ValueCountFrequency (%)
경상남도 24
19.8%
산청군 24
19.8%
단성면 4
 
3.3%
차황면 3
 
2.5%
신안면 3
 
2.5%
5 3
 
2.5%
새실로 2
 
1.7%
30 2
 
1.7%
시천면 2
 
1.7%
생비량면 2
 
1.7%
Other values (45) 52
43.0%
2023-12-11T08:33:05.200911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
18.0%
산 28
 
5.2%
경 26
 
4.8%
면 24
 
4.5%
남 24
 
4.5%
도 24
 
4.5%
청 24
 
4.5%
군 24
 
4.5%
상 24
 
4.5%
로 23
 
4.3%
Other values (61) 220
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
64.7%
Space Separator 97
 
18.0%
Decimal Number 87
 
16.2%
Dash Punctuation 6
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 28
 
8.0%
경 26
 
7.5%
면 24
 
6.9%
남 24
 
6.9%
도 24
 
6.9%
청 24
 
6.9%
군 24
 
6.9%
상 24
 
6.9%
로 23
 
6.6%
길 10
 
2.9%
Other values (49) 117
33.6%
Decimal Number
ValueCountFrequency (%)
1 20
23.0%
3 12
13.8%
2 12
13.8%
5 9
10.3%
0 8
 
9.2%
4 7
 
8.0%
7 6
 
6.9%
9 5
 
5.7%
8 4
 
4.6%
6 4
 
4.6%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
64.7%
Common 190
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 28
 
8.0%
경 26
 
7.5%
면 24
 
6.9%
남 24
 
6.9%
도 24
 
6.9%
청 24
 
6.9%
군 24
 
6.9%
상 24
 
6.9%
로 23
 
6.6%
길 10
 
2.9%
Other values (49) 117
33.6%
Common
ValueCountFrequency (%)
97
51.1%
1 20
 
10.5%
3 12
 
6.3%
2 12
 
6.3%
5 9
 
4.7%
0 8
 
4.2%
4 7
 
3.7%
7 6
 
3.2%
- 6
 
3.2%
9 5
 
2.6%
Other values (2) 8
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
64.7%
ASCII 190
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
51.1%
1 20
 
10.5%
3 12
 
6.3%
2 12
 
6.3%
5 9
 
4.7%
0 8
 
4.2%
4 7
 
3.7%
7 6
 
3.2%
- 6
 
3.2%
9 5
 
2.6%
Other values (2) 8
 
4.2%
Hangul
ValueCountFrequency (%)
산 28
 
8.0%
경 26
 
7.5%
면 24
 
6.9%
남 24
 
6.9%
도 24
 
6.9%
청 24
 
6.9%
군 24
 
6.9%
상 24
 
6.9%
로 23
 
6.6%
길 10
 
2.9%
Other values (49) 117
33.6%

전화번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:33:05.380014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row055-970-7651
2nd row055-970-7652
3rd row055-970-7653
4th row055-970-7654
5th row055-970-7655
ValueCountFrequency (%)
055-970-7651 1
 
4.2%
055-970-7652 1
 
4.2%
055-970-7693 1
 
4.2%
055-970-7692 1
 
4.2%
055-970-7691 1
 
4.2%
055-970-7690 1
 
4.2%
055-970-7689 1
 
4.2%
055-970-7688 1
 
4.2%
055-970-7687 1
 
4.2%
055-970-7686 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T08:33:05.681956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 60
20.8%
7 50
17.4%
0 49
17.0%
- 48
16.7%
9 32
11.1%
6 26
9.0%
8 11
 
3.8%
1 3
 
1.0%
2 3
 
1.0%
3 3
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 60
25.0%
7 50
20.8%
0 49
20.4%
9 32
13.3%
6 26
10.8%
8 11
 
4.6%
1 3
 
1.2%
2 3
 
1.2%
3 3
 
1.2%
4 3
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 60
20.8%
7 50
17.4%
0 49
17.0%
- 48
16.7%
9 32
11.1%
6 26
9.0%
8 11
 
3.8%
1 3
 
1.0%
2 3
 
1.0%
3 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 60
20.8%
7 50
17.4%
0 49
17.0%
- 48
16.7%
9 32
11.1%
6 26
9.0%
8 11
 
3.8%
1 3
 
1.0%
2 3
 
1.0%
3 3
 
1.0%

진료과목
Categorical

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
15 
내과
5 
내과, 한방과
3 
내과, 치과
 
1

Length

Max length7
Median length4
Mean length4.0416667
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row내과, 한방과
2nd row내과
3rd row내과
4th row내과
5th row내과

Common Values

ValueCountFrequency (%)
<NA> 15
62.5%
내과 5
 
20.8%
내과, 한방과 3
 
12.5%
내과, 치과 1
 
4.2%

Length

2023-12-11T08:33:05.828019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:33:05.917248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
53.6%
내과 9
32.1%
한방과 3
 
10.7%
치과 1
 
3.6%

관할구역
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:33:06.105927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length10.5
Min length3

Characters and Unicode

Total characters252
Distinct characters78
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row시천면, 삼장면
2nd row차황면
3rd row오부면
4th row생초면
5th row금서면
ValueCountFrequency (%)
길리 2
 
3.3%
단성면 2
 
3.3%
향양리 2
 
3.3%
시천면 1
 
1.7%
관정리 1
 
1.7%
호리 1
 
1.7%
당산리 1
 
1.7%
창촌리,백운리 1
 
1.7%
자양리 1
 
1.7%
청계리 1
 
1.7%
Other values (47) 47
78.3%
2023-12-11T08:33:06.425364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 48
19.0%
38
 
15.1%
, 35
 
13.9%
면 11
 
4.4%
평 5
 
2.0%
양 4
 
1.6%
장 4
 
1.6%
촌 4
 
1.6%
신 3
 
1.2%
계 3
 
1.2%
Other values (68) 97
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
71.0%
Space Separator 38
 
15.1%
Other Punctuation 35
 
13.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 48
26.8%
면 11
 
6.1%
평 5
 
2.8%
양 4
 
2.2%
장 4
 
2.2%
촌 4
 
2.2%
신 3
 
1.7%
계 3
 
1.7%
중 3
 
1.7%
안 3
 
1.7%
Other values (66) 91
50.8%
Space Separator
ValueCountFrequency (%)
38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
71.0%
Common 73
29.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 48
26.8%
면 11
 
6.1%
평 5
 
2.8%
양 4
 
2.2%
장 4
 
2.2%
촌 4
 
2.2%
신 3
 
1.7%
계 3
 
1.7%
중 3
 
1.7%
안 3
 
1.7%
Other values (66) 91
50.8%
Common
ValueCountFrequency (%)
38
52.1%
, 35
47.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
71.0%
ASCII 73
29.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 48
26.8%
면 11
 
6.1%
평 5
 
2.8%
양 4
 
2.2%
장 4
 
2.2%
촌 4
 
2.2%
신 3
 
1.7%
계 3
 
1.7%
중 3
 
1.7%
안 3
 
1.7%
Other values (66) 91
50.8%
ASCII
ValueCountFrequency (%)
38
52.1%
, 35
47.9%

위치
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:33:06.628244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length20
Mean length14.791667
Min length6

Characters and Unicode

Total characters355
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row삼장면사무소 옆
2nd row차황복지회관 옆
3rd row오부초등학교에서 100m 남쪽
4th row생초복지회관 옆
5th row농협서하출장소에서 100m 남쪽
ValueCountFrequency (%)
옆 6
 
9.0%
북쪽 5
 
7.5%
남쪽 3
 
4.5%
서쪽 3
 
4.5%
50m 3
 
4.5%
100m 2
 
3.0%
앞 2
 
3.0%
삼장면사무소 1
 
1.5%
구)호암농협 1
 
1.5%
대원사입구 1
 
1.5%
Other values (40) 40
59.7%
2023-12-11T08:33:06.999899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
 
16.3%
서 20
 
5.6%
m 14
 
3.9%
에 14
 
3.9%
0 13
 
3.7%
쪽 12
 
3.4%
소 10
 
2.8%
구 9
 
2.5%
등 6
 
1.7%
옆 6
 
1.7%
Other values (80) 193
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 240
67.6%
Space Separator 58
 
16.3%
Decimal Number 28
 
7.9%
Lowercase Letter 18
 
5.1%
Open Punctuation 5
 
1.4%
Close Punctuation 5
 
1.4%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 20
 
8.3%
에 14
 
5.8%
쪽 12
 
5.0%
소 10
 
4.2%
구 9
 
3.8%
등 6
 
2.5%
옆 6
 
2.5%
북 6
 
2.5%
초 5
 
2.1%
장 5
 
2.1%
Other values (66) 147
61.3%
Decimal Number
ValueCountFrequency (%)
0 13
46.4%
5 4
 
14.3%
1 4
 
14.3%
4 2
 
7.1%
2 2
 
7.1%
8 1
 
3.6%
7 1
 
3.6%
3 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
m 14
77.8%
k 4
 
22.2%
Space Separator
ValueCountFrequency (%)
58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 240
67.6%
Common 97
27.3%
Latin 18
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 20
 
8.3%
에 14
 
5.8%
쪽 12
 
5.0%
소 10
 
4.2%
구 9
 
3.8%
등 6
 
2.5%
옆 6
 
2.5%
북 6
 
2.5%
초 5
 
2.1%
장 5
 
2.1%
Other values (66) 147
61.3%
Common
ValueCountFrequency (%)
58
59.8%
0 13
 
13.4%
( 5
 
5.2%
) 5
 
5.2%
5 4
 
4.1%
1 4
 
4.1%
4 2
 
2.1%
2 2
 
2.1%
8 1
 
1.0%
7 1
 
1.0%
Other values (2) 2
 
2.1%
Latin
ValueCountFrequency (%)
m 14
77.8%
k 4
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 240
67.6%
ASCII 115
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
50.4%
m 14
 
12.2%
0 13
 
11.3%
( 5
 
4.3%
) 5
 
4.3%
5 4
 
3.5%
k 4
 
3.5%
1 4
 
3.5%
4 2
 
1.7%
2 2
 
1.7%
Other values (4) 4
 
3.5%
Hangul
ValueCountFrequency (%)
서 20
 
8.3%
에 14
 
5.8%
쪽 12
 
5.0%
소 10
 
4.2%
구 9
 
3.8%
등 6
 
2.5%
옆 6
 
2.5%
북 6
 
2.5%
초 5
 
2.1%
장 5
 
2.1%
Other values (66) 147
61.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2020-06-19
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-06-19
2nd row2020-06-19
3rd row2020-06-19
4th row2020-06-19
5th row2020-06-19

Common Values

ValueCountFrequency (%)
2020-06-19 24
100.0%

Length

2023-12-11T08:33:07.113117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:33:07.190934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-06-19 24
100.0%

Correlations

2023-12-11T08:33:07.247672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭주소전화번호진료과목관할구역위치
명칭1.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
진료과목1.0001.0001.0001.0001.0001.000
관할구역1.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T08:33:04.007860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:33:04.115535image/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

명칭주소전화번호진료과목관할구역위치데이터기준일자
0덕산통합보건지소경상남도 산청군 삼장면 덕산대포로245번길 2055-970-7651내과, 한방과시천면, 삼장면삼장면사무소 옆2020-06-19
1차황보건지소경상남도 산청군 차황면 친환경로3561번길 22-11055-970-7652내과차황면차황복지회관 옆2020-06-19
2오부보건지소경상남도 산청군 오부면 오동로 643-7055-970-7653내과오부면오부초등학교에서 100m 남쪽2020-06-19
3생초보건지소경상남도 산청군 생초면 새실로 5055-970-7654내과생초면생초복지회관 옆2020-06-19
4금서보건지소경상남도 산청군 금서면 동의보감로 1045-7055-970-7655내과금서면농협서하출장소에서 100m 남쪽2020-06-19
5단성보건지소경상남도 산청군 단성면 목화로 991번길 17055-970-7656내과단성면단성면사무소에서 200m 북쪽2020-06-19
6신안보건지소경상남도 산청군 신안면 원지로 11-9055-970-7657내과, 치과신안면, 단성면신안면사무소 옆2020-06-19
7생비량보건지소경상남도 산청군 생비량면 비량로 38055-970-7658내과, 한방과생비량면생비량파출소에서 70m 북쪽2020-06-19
8신등보건지소경상남도 산청군 신등면 신등가회로 10055-970-7659내과, 한방과신등면농협신등지소에서 20m 북쪽2020-06-19
9상중보건진료소경상남도 산청군 차황면 신차로2006번길 2055-970-7681<NA>상중리, 실매리, 장박리차황면사무소에서 신원방향으로 3km 상중마을회관 입구2020-06-19
명칭주소전화번호진료과목관할구역위치데이터기준일자
14평촌보건진료소경상남도 산청군 삼장면 평촌유평로 18055-970-7685<NA>석남리, 평촌리, 홍계리, 유평리대원사입구 명상마을 옆2020-06-19
15중산보건진료소경상남도 산청군 시천면 지리산대로 530055-970-7686<NA>중산리, 동당리중산리주차장2020-06-19
16내대보건진료소경상남도 산청군 시천면 삼신봉로679번길 7055-970-7687<NA>내대리내대주차장에서 50m 북쪽2020-06-19
17서부보건진료소경상남도 산청군 단성면 옥단로2074번길 32-1055-970-7688<NA>길리, 호리, 당산리, 창촌리,백운리, 자양리단성면 (구)서부출장소2020-06-19
18입석보건진료소경상남도 산청군 단성면 석대로 5055-970-7689<NA>청계리, 운리, 입석리, 길리 매화정, 방목리입석리 (구)호암농협 앞2020-06-19
19소남보건진료소경상남도 산청군 단성면 목화로341번길 30055-970-7690<NA>소남리, 관정리소남청소년수련원에서 1km 서쪽2020-06-19
20문대보건진료소경상남도 산청군 신안면 신차로 3055-970-7691<NA>문대리, 장죽리, 소이리, 외고리, 중촌리원지에서 합천방향 4km 문대삼거리2020-06-19
21신안보건진료소경상남도 산청군 신안면 수월로 30055-970-7692<NA>신안리, 안봉리, 외송리산청유치원 앞2020-06-19
22가계보건진료소경상남도 산청군 생비량면 송계새길 12055-970-7693<NA>가계리, 화현리, 제보리송계고등학교에서 80m 서쪽2020-06-19
23법물보건진료소경상남도 산청군 신등면 황매산로 183-3055-970-7694<NA>평지리, 장천리(구)법물초등학교에서 1.5km 북쪽2020-06-19