Overview

Dataset statistics

Number of variables7
Number of observations46
Missing cells27
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory58.9 B

Variable types

Categorical2
Text4
DateTime1

Dataset

Description2024년 1월 8일 기준, 산청군 관내 시설구분(문화, 체육, 복지), 시설명, 전화번호, 도로명주소, 홈페이지주소에 대한 자료입니다.
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15041746

Alerts

데이터기준일자 has constant value ""Constant
시설구분 is highly overall correlated with 담당부서High correlation
담당부서 is highly overall correlated with 시설구분High correlation
전화번호 has 4 (8.7%) missing valuesMissing
홈페이지 has 23 (50.0%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 00:09:36.938282
Analysis finished2024-03-13 00:09:37.744933
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
복지시설
33 
체육시설
7 
문화시설
 
3
교육시설
 
2
복지시설
 
1

Length

Max length5
Median length4
Mean length4.0217391
Min length4

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
복지시설 33
71.7%
체육시설 7
 
15.2%
문화시설 3
 
6.5%
교육시설 2
 
4.3%
복지시설 1
 
2.2%

Length

2024-03-13T09:09:37.795003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:09:37.881118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지시설 34
73.9%
체육시설 7
 
15.2%
문화시설 3
 
6.5%
교육시설 2
 
4.3%

시설명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-13T09:09:38.050056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.2608696
Min length3

Characters and Unicode

Total characters380
Distinct characters103
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

Unique46 ?
Unique (%)100.0%

Sample

1st row성심인애원
2nd row이레마을
3rd row산청복음전문요양원
4th row산청복음실버타운
5th row산청예심소규모노인종합센터
ValueCountFrequency (%)
성심인애원 1
 
2.1%
덕산문화의집 1
 
2.1%
산청복지센터 1
 
2.1%
가현누리실버타운 1
 
2.1%
덕산복지센터 1
 
2.1%
경남산청재가지원센터 1
 
2.1%
산청누리복지센터 1
 
2.1%
드림재가복지센터 1
 
2.1%
혜림노인복지센터 1
 
2.1%
원지노인복지센터 1
 
2.1%
Other values (37) 37
78.7%
2024-03-13T09:09:38.360198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 32
 
8.4%
청 28
 
7.4%
터 22
 
5.8%
센 22
 
5.8%
지 19
 
5.0%
인 18
 
4.7%
복 17
 
4.5%
원 16
 
4.2%
노 15
 
3.9%
가 6
 
1.6%
Other values (93) 185
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
98.9%
Uppercase Letter 2
 
0.5%
Space Separator 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
 
8.5%
청 28
 
7.4%
터 22
 
5.9%
센 22
 
5.9%
지 19
 
5.1%
인 18
 
4.8%
복 17
 
4.5%
원 16
 
4.3%
노 15
 
4.0%
가 6
 
1.6%
Other values (89) 181
48.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
98.9%
Common 2
 
0.5%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
 
8.5%
청 28
 
7.4%
터 22
 
5.9%
센 22
 
5.9%
지 19
 
5.1%
인 18
 
4.8%
복 17
 
4.5%
원 16
 
4.3%
노 15
 
4.0%
가 6
 
1.6%
Other values (89) 181
48.1%
Common
ValueCountFrequency (%)
1
50.0%
& 1
50.0%
Latin
ValueCountFrequency (%)
I 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
98.9%
ASCII 4
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 32
 
8.5%
청 28
 
7.4%
터 22
 
5.9%
센 22
 
5.9%
지 19
 
5.1%
인 18
 
4.8%
복 17
 
4.5%
원 16
 
4.3%
노 15
 
4.0%
가 6
 
1.6%
Other values (89) 181
48.1%
ASCII
ValueCountFrequency (%)
1
25.0%
I 1
25.0%
& 1
25.0%
B 1
25.0%

전화번호
Text

MISSING 

Distinct40
Distinct (%)95.2%
Missing4
Missing (%)8.7%
Memory size500.0 B
2024-03-13T09:09:38.542781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters504
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

Unique38 ?
Unique (%)90.5%

Sample

1st row055-973-6966
2nd row055-974-0998
3rd row055-973-3000
4th row055-973-0880
5th row055-974-0675
ValueCountFrequency (%)
055-974-0094 2
 
4.8%
055-974-1991 2
 
4.8%
055-972-1993 1
 
2.4%
055-973-6966 1
 
2.4%
055-970-6591 1
 
2.4%
055-972-7676 1
 
2.4%
055-974-1199 1
 
2.4%
055-974-0444 1
 
2.4%
055-973-9258 1
 
2.4%
055-973-0749 1
 
2.4%
Other values (30) 30
71.4%
2024-03-13T09:09:38.814926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 100
19.8%
- 84
16.7%
0 83
16.5%
9 67
13.3%
7 49
9.7%
4 37
 
7.3%
3 24
 
4.8%
1 20
 
4.0%
2 17
 
3.4%
6 12
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
83.3%
Dash Punctuation 84
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 100
23.8%
0 83
19.8%
9 67
16.0%
7 49
11.7%
4 37
 
8.8%
3 24
 
5.7%
1 20
 
4.8%
2 17
 
4.0%
6 12
 
2.9%
8 11
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 100
19.8%
- 84
16.7%
0 83
16.5%
9 67
13.3%
7 49
9.7%
4 37
 
7.3%
3 24
 
4.8%
1 20
 
4.0%
2 17
 
3.4%
6 12
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 100
19.8%
- 84
16.7%
0 83
16.5%
9 67
13.3%
7 49
9.7%
4 37
 
7.3%
3 24
 
4.8%
1 20
 
4.0%
2 17
 
3.4%
6 12
 
2.4%

소재지도로명주소
Text

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-13T09:09:39.034603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length23.869565
Min length18

Characters and Unicode

Total characters1098
Distinct characters71
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

Unique29 ?
Unique (%)63.0%

Sample

1st row경상남도 산청군 산청읍 산청대로1381번길 17
2nd row경상남도 산청군 산청읍 동의보감로312번길 176-57
3rd row경상남도 산청군 단성면 강누방목로401번길 79
4th row경상남도 산청군 단성면 강누방목로401번길 79
5th row경상남도 산청군 금서면 동의보감로312번길 11-10
ValueCountFrequency (%)
경상남도 46
20.0%
산청군 46
20.0%
산청읍 14
 
6.1%
금서면 9
 
3.9%
단성면 9
 
3.9%
신안면 6
 
2.6%
친환경로 4
 
1.7%
동의보감로312번길 4
 
1.7%
생비량면 3
 
1.3%
7 3
 
1.3%
Other values (66) 86
37.4%
2024-03-13T09:09:39.391291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
16.8%
산 70
 
6.4%
청 64
 
5.8%
경 54
 
4.9%
남 49
 
4.5%
상 47
 
4.3%
도 46
 
4.2%
군 46
 
4.2%
로 43
 
3.9%
1 40
 
3.6%
Other values (61) 455
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 698
63.6%
Decimal Number 202
 
18.4%
Space Separator 184
 
16.8%
Dash Punctuation 13
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 70
 
10.0%
청 64
 
9.2%
경 54
 
7.7%
남 49
 
7.0%
상 47
 
6.7%
도 46
 
6.6%
군 46
 
6.6%
로 43
 
6.2%
면 32
 
4.6%
길 28
 
4.0%
Other values (48) 219
31.4%
Decimal Number
ValueCountFrequency (%)
1 40
19.8%
2 29
14.4%
7 23
11.4%
3 23
11.4%
6 21
10.4%
4 16
 
7.9%
9 15
 
7.4%
0 14
 
6.9%
8 11
 
5.4%
5 10
 
5.0%
Space Separator
ValueCountFrequency (%)
184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 698
63.6%
Common 400
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 70
 
10.0%
청 64
 
9.2%
경 54
 
7.7%
남 49
 
7.0%
상 47
 
6.7%
도 46
 
6.6%
군 46
 
6.6%
로 43
 
6.2%
면 32
 
4.6%
길 28
 
4.0%
Other values (48) 219
31.4%
Common
ValueCountFrequency (%)
184
46.0%
1 40
 
10.0%
2 29
 
7.2%
7 23
 
5.8%
3 23
 
5.8%
6 21
 
5.2%
4 16
 
4.0%
9 15
 
3.8%
0 14
 
3.5%
- 13
 
3.2%
Other values (3) 22
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 698
63.6%
ASCII 400
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
46.0%
1 40
 
10.0%
2 29
 
7.2%
7 23
 
5.8%
3 23
 
5.8%
6 21
 
5.2%
4 16
 
4.0%
9 15
 
3.8%
0 14
 
3.5%
- 13
 
3.2%
Other values (3) 22
 
5.5%
Hangul
ValueCountFrequency (%)
산 70
 
10.0%
청 64
 
9.2%
경 54
 
7.7%
남 49
 
7.0%
상 47
 
6.7%
도 46
 
6.6%
군 46
 
6.6%
로 43
 
6.2%
면 32
 
4.6%
길 28
 
4.0%
Other values (48) 219
31.4%

홈페이지
Text

MISSING 

Distinct20
Distinct (%)87.0%
Missing23
Missing (%)50.0%
Memory size500.0 B
2024-03-13T09:09:39.572922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length29
Mean length27.782609
Min length15

Characters and Unicode

Total characters639
Distinct characters52
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st rowhttps://blog.naver.com/ohmark/221302235810
2nd rowhttp://www.iregdc.com/
3rd rowhttp://ssgh.or.kr/
4th rowhttp://sgst.or.kr/
5th rowhttp://예심요양원.kr
ValueCountFrequency (%)
http://www.sungsim1.or.kr 2
 
8.7%
http://예심요양원.kr 2
 
8.7%
http://www.iregdc.com 2
 
8.7%
http://knangels1004.modoo.at 1
 
4.3%
https://blog.naver.com/ohmark/221302235810 1
 
4.3%
http://cafe.naver.com/daonsenir 1
 
4.3%
http://blog.naver.com/postlist.nhn?blogid=sancheong_youth&skintype=&skinid=&from=menu 1
 
4.3%
https://cafe.naver.com/wonjisilver 1
 
4.3%
https://blog.naver.com/kos1805 1
 
4.3%
http://www.nuricare.co.kr 1
 
4.3%
Other values (10) 10
43.5%
2024-03-13T09:09:39.857400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 66
 
10.3%
t 53
 
8.3%
. 51
 
8.0%
r 38
 
5.9%
o 36
 
5.6%
h 31
 
4.9%
w 30
 
4.7%
n 26
 
4.1%
e 25
 
3.9%
s 24
 
3.8%
Other values (42) 259
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 446
69.8%
Other Punctuation 144
 
22.5%
Decimal Number 26
 
4.1%
Other Letter 10
 
1.6%
Uppercase Letter 6
 
0.9%
Math Symbol 4
 
0.6%
Connector Punctuation 1
 
0.2%
Space Separator 1
 
0.2%
Control 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 53
 
11.9%
r 38
 
8.5%
o 36
 
8.1%
h 31
 
7.0%
w 30
 
6.7%
n 26
 
5.8%
e 25
 
5.6%
s 24
 
5.4%
p 24
 
5.4%
a 21
 
4.7%
Other values (14) 138
30.9%
Decimal Number
ValueCountFrequency (%)
1 8
30.8%
0 5
19.2%
2 4
15.4%
5 2
 
7.7%
8 2
 
7.7%
3 2
 
7.7%
9 1
 
3.8%
4 1
 
3.8%
6 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 66
45.8%
. 51
35.4%
: 23
 
16.0%
& 3
 
2.1%
? 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
I 2
33.3%
T 1
16.7%
P 1
16.7%
D 1
16.7%
L 1
16.7%
Other Letter
ValueCountFrequency (%)
예 2
20.0%
심 2
20.0%
요 2
20.0%
양 2
20.0%
원 2
20.0%
Math Symbol
ValueCountFrequency (%)
= 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 452
70.7%
Common 177
 
27.7%
Hangul 10
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 53
 
11.7%
r 38
 
8.4%
o 36
 
8.0%
h 31
 
6.9%
w 30
 
6.6%
n 26
 
5.8%
e 25
 
5.5%
s 24
 
5.3%
p 24
 
5.3%
a 21
 
4.6%
Other values (19) 144
31.9%
Common
ValueCountFrequency (%)
/ 66
37.3%
. 51
28.8%
: 23
 
13.0%
1 8
 
4.5%
0 5
 
2.8%
2 4
 
2.3%
= 4
 
2.3%
& 3
 
1.7%
5 2
 
1.1%
8 2
 
1.1%
Other values (8) 9
 
5.1%
Hangul
ValueCountFrequency (%)
예 2
20.0%
심 2
20.0%
요 2
20.0%
양 2
20.0%
원 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 629
98.4%
Hangul 10
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 66
 
10.5%
t 53
 
8.4%
. 51
 
8.1%
r 38
 
6.0%
o 36
 
5.7%
h 31
 
4.9%
w 30
 
4.8%
n 26
 
4.1%
e 25
 
4.0%
s 24
 
3.8%
Other values (37) 249
39.6%
Hangul
ValueCountFrequency (%)
예 2
20.0%
심 2
20.0%
요 2
20.0%
양 2
20.0%
원 2
20.0%

담당부서
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
복지지원과
34 
문화체육과
11 
보건정책과
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
복지지원과 34
73.9%
문화체육과 11
 
23.9%
보건정책과 1
 
2.2%

Length

2024-03-13T09:09:39.963987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:09:40.047531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지지원과 34
73.9%
문화체육과 11
 
23.9%
보건정책과 1
 
2.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2022-12-21 00:00:00
Maximum2022-12-21 00:00:00
2024-03-13T09:09:40.120754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:09:40.200495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-03-13T09:09:40.258705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분시설명전화번호소재지도로명주소홈페이지담당부서
시설구분1.0001.0001.0000.6430.0000.936
시설명1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
소재지도로명주소0.6431.0001.0001.0000.9870.000
홈페이지0.0001.0001.0000.9871.0000.000
담당부서0.9361.0001.0000.0000.0001.000
2024-03-13T09:09:40.343890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분담당부서
시설구분1.0000.960
담당부서0.9601.000
2024-03-13T09:09:40.411160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분담당부서
시설구분1.0000.960
담당부서0.9601.000

Missing values

2024-03-13T09:09:37.529102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:09:37.618524image/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.
2024-03-13T09:09:37.700145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시설구분시설명전화번호소재지도로명주소홈페이지담당부서데이터기준일자
0복지시설성심인애원055-973-6966경상남도 산청군 산청읍 산청대로1381번길 17https://blog.naver.com/ohmark/221302235810복지지원과2022-12-21
1복지시설이레마을055-974-0998경상남도 산청군 산청읍 동의보감로312번길 176-57http://www.iregdc.com/복지지원과2022-12-21
2복지시설산청복음전문요양원055-973-3000경상남도 산청군 단성면 강누방목로401번길 79http://ssgh.or.kr/복지지원과2022-12-21
3복지시설산청복음실버타운055-973-0880경상남도 산청군 단성면 강누방목로401번길 79http://sgst.or.kr/복지지원과2022-12-21
4복지시설산청예심소규모노인종합센터055-974-0675경상남도 산청군 금서면 동의보감로312번길 11-10http://예심요양원.kr복지지원과2022-12-21
5복지시설산청우리요양원055-974-0980경상남도 산청군 단성면 사직단로257번길 8-7http://www.withangel.co.kr/복지지원과2022-12-21
6복지시설산청성모요양원055-974-0093경상남도 산청군 금서면 친환경로 2016http://www.koryeo.or.kr/복지지원과2022-12-21
7복지시설한일노인요양원055-974-1204경상남도 산청군 산청읍 웅석봉로67번길 26http://www.hanill.or.kr/복지지원과2022-12-21
8복지시설산청선문노인요양원055-974-1991경상남도 산청군 생비량면 비량로 29<NA>복지지원과2022-12-21
9복지시설산청한방실버타운055-974-0094경상남도 산청군 금서면 친환경로 2016<NA>복지지원과2022-12-21
시설구분시설명전화번호소재지도로명주소홈페이지담당부서데이터기준일자
36문화시설산청문화예술회관055-970-6481경상남도 산청군 금서면 친환경로2631번길 12<NA>문화체육과2022-12-21
37문화시설기산국악당055-972-4549경상남도 산청군 단성면 상동길 69<NA>문화체육과2022-12-21
38체육시설산청공설운동장<NA>경상남도 산청군 금서면 친환경로2631번길 39<NA>문화체육과2022-12-21
39체육시설산청 국민체육센터055-970-6485경상남도 산청군 금서면 친환경로2605번길 22<NA>문화체육과2022-12-21
40체육시설산청실내수영장055-974-0412경상남도 산청군 금서면 친환경로2631번길 12<NA>문화체육과2022-12-21
41체육시설생초체육공원<NA>경상남도 산청군 생초면 생초로 10<NA>문화체육과2022-12-21
42체육시설남부생활체육공원<NA>경상남도 산청군 신안면 하정리 581<NA>문화체육과2022-12-21
43체육시설조산공원다목적구장055-973-0038경상남도 산청군 산청읍 웅석봉로86번길 7<NA>문화체육과2022-12-21
44체육시설산청군체육회관<NA>경상남도 산청군 산청읍 웅석봉로86번길 7<NA>문화체육과2022-12-21
45복지시설성심원055-972-0075경상남도 산청군 산청읍 산청대로1381번길 17http://www.sungsim1.or.kr/보건정책과2022-12-21