Overview

Dataset statistics

Number of variables9
Number of observations292
Missing cells75
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.9 KiB
Average record size in memory73.5 B

Variable types

Categorical4
Text4
Numeric1

Dataset

Description경상남도 창녕군 마을회관현황에 대한 데이터를 포함하고 있습니다.(마을명, 회관명, 건축년도, 규모, 정원 등)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15054782

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
규모 is highly imbalanced (51.8%)Imbalance
전화번호 has 75 (25.7%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:41:44.094656
Analysis finished2023-12-11 00:41:44.710517
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
경상남도
292 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 292
100.0%

Length

2023-12-11T09:41:44.787620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:41:44.885205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 292
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
창녕군
292 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창녕군 292
100.0%

Length

2023-12-11T09:41:45.024933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:41:45.128406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창녕군 292
100.0%

읍면
Categorical

Distinct14
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
남지읍
38 
창녕읍
31 
대합면
31 
고암면
21 
이방면
21 
Other values (9)
150 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남지읍 38
13.0%
창녕읍 31
10.6%
대합면 31
10.6%
고암면 21
 
7.2%
이방면 21
 
7.2%
장마면 21
 
7.2%
유어면 19
 
6.5%
성산면 18
 
6.2%
대지면 18
 
6.2%
부곡면 18
 
6.2%
Other values (4) 56
19.2%

Length

2023-12-11T09:41:45.241419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남지읍 38
13.0%
창녕읍 31
10.6%
대합면 31
10.6%
고암면 21
 
7.2%
이방면 21
 
7.2%
장마면 21
 
7.2%
유어면 19
 
6.5%
성산면 18
 
6.2%
대지면 18
 
6.2%
부곡면 18
 
6.2%
Other values (4) 56
19.2%

마을명
Text

Distinct261
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T09:41:45.556973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.6506849
Min length2

Characters and Unicode

Total characters774
Distinct characters149
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

Unique245 ?
Unique (%)83.9%

Sample

1st row교리
2nd row갈전
3rd row창서
4th row교상
5th row교하
ValueCountFrequency (%)
남지리 7
 
2.4%
성사리 5
 
1.7%
학계리 4
 
1.4%
마산리 3
 
1.0%
반포리 3
 
1.0%
원동 3
 
1.0%
월하리 3
 
1.0%
신전리 3
 
1.0%
대동 3
 
1.0%
신당 3
 
1.0%
Other values (247) 257
87.4%
2023-12-11T09:41:46.070462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 82
 
10.6%
39
 
5.0%
구 36
 
4.7%
산 26
 
3.4%
곡 23
 
3.0%
동 20
 
2.6%
신 18
 
2.3%
마 18
 
2.3%
대 16
 
2.1%
계 16
 
2.1%
Other values (139) 480
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 707
91.3%
Space Separator 39
 
5.0%
Decimal Number 28
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 82
 
11.6%
구 36
 
5.1%
산 26
 
3.7%
곡 23
 
3.3%
동 20
 
2.8%
신 18
 
2.5%
마 18
 
2.5%
대 16
 
2.3%
계 16
 
2.3%
남 15
 
2.1%
Other values (135) 437
61.8%
Decimal Number
ValueCountFrequency (%)
1 13
46.4%
2 13
46.4%
3 2
 
7.1%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 707
91.3%
Common 67
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 82
 
11.6%
구 36
 
5.1%
산 26
 
3.7%
곡 23
 
3.3%
동 20
 
2.8%
신 18
 
2.5%
마 18
 
2.5%
대 16
 
2.3%
계 16
 
2.3%
남 15
 
2.1%
Other values (135) 437
61.8%
Common
ValueCountFrequency (%)
39
58.2%
1 13
 
19.4%
2 13
 
19.4%
3 2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 707
91.3%
ASCII 67
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 82
 
11.6%
구 36
 
5.1%
산 26
 
3.7%
곡 23
 
3.3%
동 20
 
2.8%
신 18
 
2.5%
마 18
 
2.5%
대 16
 
2.3%
계 16
 
2.3%
남 15
 
2.1%
Other values (135) 437
61.8%
ASCII
ValueCountFrequency (%)
39
58.2%
1 13
 
19.4%
2 13
 
19.4%
3 2
 
3.0%

회관명
Text

Distinct282
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T09:41:46.337825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.7054795
Min length6

Characters and Unicode

Total characters1958
Distinct characters155
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

Unique274 ?
Unique (%)93.8%

Sample

1st row교리 마을회관
2nd row갈전 마을회관
3rd row창서 마을회관
4th row교상 마을회관
5th row교하 마을회관
ValueCountFrequency (%)
마을회관 111
27.5%
관동마을회관 3
 
0.7%
원동마을회관 3
 
0.7%
교리 2
 
0.5%
대신마을회관 2
 
0.5%
대동 2
 
0.5%
신당 2
 
0.5%
부곡마을회관 2
 
0.5%
명리마을회관 2
 
0.5%
대초마을회관 1
 
0.2%
Other values (273) 273
67.7%
2023-12-11T09:41:46.876903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 299
15.3%
관 295
15.1%
회 294
15.0%
을 293
15.0%
111
 
5.7%
리 45
 
2.3%
구 35
 
1.8%
산 26
 
1.3%
동 24
 
1.2%
곡 24
 
1.2%
Other values (145) 512
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1821
93.0%
Space Separator 111
 
5.7%
Decimal Number 26
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 299
16.4%
관 295
16.2%
회 294
16.1%
을 293
16.1%
리 45
 
2.5%
구 35
 
1.9%
산 26
 
1.4%
동 24
 
1.3%
곡 24
 
1.3%
대 19
 
1.0%
Other values (141) 467
25.6%
Decimal Number
ValueCountFrequency (%)
2 12
46.2%
1 12
46.2%
3 2
 
7.7%
Space Separator
ValueCountFrequency (%)
111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1821
93.0%
Common 137
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 299
16.4%
관 295
16.2%
회 294
16.1%
을 293
16.1%
리 45
 
2.5%
구 35
 
1.9%
산 26
 
1.4%
동 24
 
1.3%
곡 24
 
1.3%
대 19
 
1.0%
Other values (141) 467
25.6%
Common
ValueCountFrequency (%)
111
81.0%
2 12
 
8.8%
1 12
 
8.8%
3 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1821
93.0%
ASCII 137
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 299
16.4%
관 295
16.2%
회 294
16.1%
을 293
16.1%
리 45
 
2.5%
구 35
 
1.9%
산 26
 
1.4%
동 24
 
1.3%
곡 24
 
1.3%
대 19
 
1.0%
Other values (141) 467
25.6%
ASCII
ValueCountFrequency (%)
111
81.0%
2 12
 
8.8%
1 12
 
8.8%
3 2
 
1.5%

소재지도로명주소
Text

Distinct287
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T09:41:47.261084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.106164
Min length8

Characters and Unicode

Total characters3243
Distinct characters184
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

Unique282 ?
Unique (%)96.6%

Sample

1st row창녕읍 향교길18
2nd row창녕읍 우포로1203
3rd row창녕읍 창서 798-1
4th row창녕읍 교상길 5-5
5th row창녕읍 교하리 263-18
ValueCountFrequency (%)
남지읍 38
 
4.9%
대합면 31
 
4.0%
창녕읍 31
 
4.0%
고암면 21
 
2.7%
장마면 21
 
2.7%
이방면 21
 
2.7%
유어면 19
 
2.4%
성산면 18
 
2.3%
대지면 18
 
2.3%
부곡면 18
 
2.3%
Other values (436) 541
69.6%
2023-12-11T09:41:47.775536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
501
 
15.4%
길 234
 
7.2%
면 223
 
6.9%
1 184
 
5.7%
2 113
 
3.5%
- 90
 
2.8%
3 85
 
2.6%
대 76
 
2.3%
5 73
 
2.3%
산 69
 
2.1%
Other values (174) 1595
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1870
57.7%
Decimal Number 782
24.1%
Space Separator 501
 
15.4%
Dash Punctuation 90
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 234
 
12.5%
면 223
 
11.9%
대 76
 
4.1%
산 69
 
3.7%
읍 69
 
3.7%
지 68
 
3.6%
남 52
 
2.8%
성 51
 
2.7%
곡 50
 
2.7%
리 45
 
2.4%
Other values (162) 933
49.9%
Decimal Number
ValueCountFrequency (%)
1 184
23.5%
2 113
14.5%
3 85
10.9%
5 73
 
9.3%
4 68
 
8.7%
0 58
 
7.4%
7 55
 
7.0%
9 52
 
6.6%
6 48
 
6.1%
8 46
 
5.9%
Space Separator
ValueCountFrequency (%)
501
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1870
57.7%
Common 1373
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 234
 
12.5%
면 223
 
11.9%
대 76
 
4.1%
산 69
 
3.7%
읍 69
 
3.7%
지 68
 
3.6%
남 52
 
2.8%
성 51
 
2.7%
곡 50
 
2.7%
리 45
 
2.4%
Other values (162) 933
49.9%
Common
ValueCountFrequency (%)
501
36.5%
1 184
 
13.4%
2 113
 
8.2%
- 90
 
6.6%
3 85
 
6.2%
5 73
 
5.3%
4 68
 
5.0%
0 58
 
4.2%
7 55
 
4.0%
9 52
 
3.8%
Other values (2) 94
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1870
57.7%
ASCII 1373
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
501
36.5%
1 184
 
13.4%
2 113
 
8.2%
- 90
 
6.6%
3 85
 
6.2%
5 73
 
5.3%
4 68
 
5.0%
0 58
 
4.2%
7 55
 
4.0%
9 52
 
3.8%
Other values (2) 94
 
6.8%
Hangul
ValueCountFrequency (%)
길 234
 
12.5%
면 223
 
11.9%
대 76
 
4.1%
산 69
 
3.7%
읍 69
 
3.7%
지 68
 
3.6%
남 52
 
2.8%
성 51
 
2.7%
곡 50
 
2.7%
리 45
 
2.4%
Other values (162) 933
49.9%

건축년도
Real number (ℝ)

Distinct42
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.4212
Minimum1938
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T09:41:47.932986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1938
5-th percentile1979
Q11997
median2002
Q32006
95-th percentile2010.45
Maximum2015
Range77
Interquartile range (IQR)9

Descriptive statistics

Standard deviation9.2630865
Coefficient of variation (CV)0.004630568
Kurtosis7.6411476
Mean2000.4212
Median Absolute Deviation (MAD)4
Skewness-2.0373746
Sum584123
Variance85.804771
MonotonicityNot monotonic
2023-12-11T09:41:48.142135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2004 31
 
10.6%
2009 22
 
7.5%
2005 20
 
6.8%
2007 19
 
6.5%
2002 18
 
6.2%
2000 17
 
5.8%
2003 14
 
4.8%
1995 14
 
4.8%
1999 13
 
4.5%
1998 13
 
4.5%
Other values (32) 111
38.0%
ValueCountFrequency (%)
1938 1
 
0.3%
1972 1
 
0.3%
1974 4
1.4%
1975 1
 
0.3%
1976 1
 
0.3%
1977 2
0.7%
1978 3
1.0%
1979 4
1.4%
1980 1
 
0.3%
1981 2
0.7%
ValueCountFrequency (%)
2015 3
 
1.0%
2014 3
 
1.0%
2013 4
 
1.4%
2012 3
 
1.0%
2011 2
 
0.7%
2010 4
 
1.4%
2009 22
7.5%
2008 10
3.4%
2007 19
6.5%
2006 9
3.1%

규모
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
지상1층
216 
지상2층
57 
1층
 
10
2층
 
8
지상3층
 
1

Length

Max length4
Median length4
Mean length3.8767123
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row지상1층
2nd row지상1층
3rd row지상2층
4th row지상2층
5th row지상2층

Common Values

ValueCountFrequency (%)
지상1층 216
74.0%
지상2층 57
 
19.5%
1층 10
 
3.4%
2층 8
 
2.7%
지상3층 1
 
0.3%

Length

2023-12-11T09:41:48.348819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:41:48.795710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상1층 216
74.0%
지상2층 57
 
19.5%
1층 10
 
3.4%
2층 8
 
2.7%
지상3층 1
 
0.3%

전화번호
Text

MISSING 

Distinct215
Distinct (%)99.1%
Missing75
Missing (%)25.7%
Memory size2.4 KiB
2023-12-11T09:41:49.044766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2604
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

Unique213 ?
Unique (%)98.2%

Sample

1st row055-533-2102
2nd row055-533-7689
3rd row055-532-8416
4th row055-533-6164
5th row055-533-3446
ValueCountFrequency (%)
055-536-8534 2
 
0.9%
055-536-3928 2
 
0.9%
055-536-5587 1
 
0.5%
055-533-0332 1
 
0.5%
055-536-7414 1
 
0.5%
055-532-9491 1
 
0.5%
055-533-6744 1
 
0.5%
055-533-1042 1
 
0.5%
055-532-0856 1
 
0.5%
055-533-9180 1
 
0.5%
Other values (205) 205
94.5%
2023-12-11T09:41:49.457390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 753
28.9%
- 434
16.7%
3 310
11.9%
0 302
11.6%
2 200
 
7.7%
6 167
 
6.4%
1 117
 
4.5%
9 88
 
3.4%
4 82
 
3.1%
8 79
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2170
83.3%
Dash Punctuation 434
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 753
34.7%
3 310
14.3%
0 302
13.9%
2 200
 
9.2%
6 167
 
7.7%
1 117
 
5.4%
9 88
 
4.1%
4 82
 
3.8%
8 79
 
3.6%
7 72
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 434
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 753
28.9%
- 434
16.7%
3 310
11.9%
0 302
11.6%
2 200
 
7.7%
6 167
 
6.4%
1 117
 
4.5%
9 88
 
3.4%
4 82
 
3.1%
8 79
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 753
28.9%
- 434
16.7%
3 310
11.9%
0 302
11.6%
2 200
 
7.7%
6 167
 
6.4%
1 117
 
4.5%
9 88
 
3.4%
4 82
 
3.1%
8 79
 
3.0%

Interactions

2023-12-11T09:41:44.435307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:41:49.558659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면건축년도규모
읍면1.0000.4000.727
건축년도0.4001.0000.216
규모0.7270.2161.000
2023-12-11T09:41:49.660096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모읍면
규모1.0000.480
읍면0.4801.000
2023-12-11T09:41:49.754143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축년도읍면규모
건축년도1.0000.1910.217
읍면0.1911.0000.480
규모0.2170.4801.000

Missing values

2023-12-11T09:41:44.540854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:41:44.660116image/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

시도명시군구명읍면마을명회관명소재지도로명주소건축년도규모전화번호
0경상남도창녕군창녕읍교리교리 마을회관창녕읍 향교길181995지상1층<NA>
1경상남도창녕군창녕읍갈전갈전 마을회관창녕읍 우포로12032001지상1층055-533-2102
2경상남도창녕군창녕읍창서창서 마을회관창녕읍 창서 798-11994지상2층055-533-7689
3경상남도창녕군창녕읍교상교상 마을회관창녕읍 교상길 5-51994지상2층055-532-8416
4경상남도창녕군창녕읍교하교하 마을회관창녕읍 교하리 263-182005지상2층055-533-6164
5경상남도창녕군창녕읍옥만옥만 마을회관창녕읍 교하새갈502011지상1층<NA>
6경상남도창녕군창녕읍학천학천 마을회관창녕읍 학천리 227-12004지상2층055-533-3446
7경상남도창녕군창녕읍봉천봉천 마을회관창녕읍 봉천리 247-21988지상1층055-533-7793
8경상남도창녕군창녕읍말흘말흘리 마을회관창녕읍 말흘 1길182015지상2층055-533-1755
9경상남도창녕군창녕읍낙영낙영 마을회관창녕읍 낙영 7362004지상1층055-533-0062
시도명시군구명읍면마을명회관명소재지도로명주소건축년도규모전화번호
282경상남도창녕군부곡면차실차실마을회관부곡면 차실길36-32005지상1층<NA>
283경상남도창녕군부곡면청암청암마을회관부곡면 청암1길221998지상1층<NA>
284경상남도창녕군부곡면노리노리마을회관부곡면 노리2길42006지상1층<NA>
285경상남도창녕군부곡면신포신포마을회관부곡면 신포길312007지상1층<NA>
286경상남도창녕군부곡면학포학포마을회관부곡면 학포1길40-11993지상1층<NA>
287경상남도창녕군부곡면구산구산마을회관부곡면 구산1길91998지상1층<NA>
288경상남도창녕군부곡면유촌구산유촌마을회관부곡면 유촌길 21996지상1층<NA>
289경상남도창녕군부곡면비봉비봉마을회관부곡면 비봉길772007지상1층<NA>
290경상남도창녕군부곡면수다수다마을회관부곡면 수다리232015지상1층055-521-2836
291경상남도창녕군부곡면수성수성마을회관부곡면 수성길29-42014지상1층<NA>