Overview

Dataset statistics

Number of variables9
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory83.0 B

Variable types

Numeric4
Categorical3
Text2

Dataset

Description영양군에서 관리되고 있는 수해대피소에 대한 데이터로 구분, 주소, 경도, 위도, 시설명, 면적, 수용인원 등에 대한 데이터를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15114046/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
면적 is highly overall correlated with 수용인원High correlation
구분 is highly overall correlated with 수용인원High correlation
수용인원 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
주소 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:01:17.838948
Analysis finished2023-12-12 23:01:20.141755
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T08:01:20.208910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2023-12-13T08:01:20.319431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
마을회관
13 
경로당
5 
학교
2 
기타
 
1
관공서
 
1

Length

Max length4
Median length4
Mean length3.4545455
Min length2

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row기타
2nd row경로당
3rd row마을회관
4th row마을회관
5th row관공서

Common Values

ValueCountFrequency (%)
마을회관 13
59.1%
경로당 5
 
22.7%
학교 2
 
9.1%
기타 1
 
4.5%
관공서 1
 
4.5%

Length

2023-12-13T08:01:20.439116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:01:20.548797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회관 13
59.1%
경로당 5
 
22.7%
학교 2
 
9.1%
기타 1
 
4.5%
관공서 1
 
4.5%

주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T08:01:20.747439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.227273
Min length18

Characters and Unicode

Total characters445
Distinct characters64
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

Unique22 ?
Unique (%)100.0%

Sample

1st row경상북도 영양군 입암면 방전2길 25
2nd row경상북도 영양군 입암면 흥구1길 25
3rd row경상북도 영양군 석보면 원리3길 11
4th row경상북도 영양군 수비면 괘벽길 6-1
5th row경상북도 영양군 영양읍 지평길 51
ValueCountFrequency (%)
경상북도 22
20.2%
영양군 22
20.2%
입암면 6
 
5.5%
청기면 6
 
5.5%
영양읍 3
 
2.8%
수비면 2
 
1.8%
청기로 2
 
1.8%
6 2
 
1.8%
2 2
 
1.8%
일월면 2
 
1.8%
Other values (38) 40
36.7%
2023-12-13T08:01:21.061379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
19.8%
영 27
 
6.1%
양 27
 
6.1%
도 23
 
5.2%
경 22
 
4.9%
상 22
 
4.9%
북 22
 
4.9%
군 22
 
4.9%
면 18
 
4.0%
길 16
 
3.6%
Other values (54) 158
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
65.4%
Space Separator 88
 
19.8%
Decimal Number 60
 
13.5%
Dash Punctuation 5
 
1.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 27
 
9.3%
양 27
 
9.3%
도 23
 
7.9%
경 22
 
7.6%
상 22
 
7.6%
북 22
 
7.6%
군 22
 
7.6%
면 18
 
6.2%
길 16
 
5.5%
기 8
 
2.7%
Other values (42) 84
28.9%
Decimal Number
ValueCountFrequency (%)
1 16
26.7%
2 11
18.3%
3 10
16.7%
5 7
11.7%
8 5
 
8.3%
4 4
 
6.7%
6 4
 
6.7%
7 2
 
3.3%
0 1
 
1.7%
Space Separator
ValueCountFrequency (%)
88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
65.4%
Common 154
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 27
 
9.3%
양 27
 
9.3%
도 23
 
7.9%
경 22
 
7.6%
상 22
 
7.6%
북 22
 
7.6%
군 22
 
7.6%
면 18
 
6.2%
길 16
 
5.5%
기 8
 
2.7%
Other values (42) 84
28.9%
Common
ValueCountFrequency (%)
88
57.1%
1 16
 
10.4%
2 11
 
7.1%
3 10
 
6.5%
5 7
 
4.5%
- 5
 
3.2%
8 5
 
3.2%
4 4
 
2.6%
6 4
 
2.6%
7 2
 
1.3%
Other values (2) 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
65.4%
ASCII 154
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
57.1%
1 16
 
10.4%
2 11
 
7.1%
3 10
 
6.5%
5 7
 
4.5%
- 5
 
3.2%
8 5
 
3.2%
4 4
 
2.6%
6 4
 
2.6%
7 2
 
1.3%
Other values (2) 2
 
1.3%
Hangul
ValueCountFrequency (%)
영 27
 
9.3%
양 27
 
9.3%
도 23
 
7.9%
경 22
 
7.6%
상 22
 
7.6%
북 22
 
7.6%
군 22
 
7.6%
면 18
 
6.2%
길 16
 
5.5%
기 8
 
2.7%
Other values (42) 84
28.9%

경도
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.659598
Minimum36.548273
Maximum36.787309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T08:01:21.205650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.548273
5-th percentile36.555977
Q136.59851
median36.654529
Q336.72391
95-th percentile36.775224
Maximum36.787309
Range0.23903611
Interquartile range (IQR)0.12539999

Descriptive statistics

Standard deviation0.077999792
Coefficient of variation (CV)0.0021276772
Kurtosis-1.2606168
Mean36.659598
Median Absolute Deviation (MAD)0.066937845
Skewness0.21807511
Sum806.51115
Variance0.0060839675
MonotonicityNot monotonic
2023-12-13T08:01:21.351899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
36.55559115 1
 
4.5%
36.71658053 1
 
4.5%
36.77552973 1
 
4.5%
36.75693536 1
 
4.5%
36.57986461 1
 
4.5%
36.61338494 1
 
4.5%
36.61191984 1
 
4.5%
36.65646798 1
 
4.5%
36.56646762 1
 
4.5%
36.69587453 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
36.54827289 1
4.5%
36.55559115 1
4.5%
36.56330887 1
4.5%
36.56646762 1
4.5%
36.57986461 1
4.5%
36.59404033 1
4.5%
36.61191984 1
4.5%
36.61338494 1
4.5%
36.61853878 1
4.5%
36.63746043 1
4.5%
ValueCountFrequency (%)
36.787309 1
4.5%
36.77552973 1
4.5%
36.76940742 1
4.5%
36.75693536 1
4.5%
36.75387922 1
4.5%
36.72635342 1
4.5%
36.71658053 1
4.5%
36.69587453 1
4.5%
36.67035193 1
4.5%
36.66102077 1
4.5%

위도
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.09351
Minimum129.01057
Maximum129.22197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T08:01:21.466680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.01057
5-th percentile129.01356
Q1129.03858
median129.08972
Q3129.12901
95-th percentile129.19711
Maximum129.22197
Range0.2113977
Interquartile range (IQR)0.090427075

Descriptive statistics

Standard deviation0.060940503
Coefficient of variation (CV)0.00047206481
Kurtosis-0.63211697
Mean129.09351
Median Absolute Deviation (MAD)0.0483524
Skewness0.42594477
Sum2840.0572
Variance0.0037137449
MonotonicityNot monotonic
2023-12-13T08:01:21.572068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
129.0862543 1
 
4.5%
129.0267975 1
 
4.5%
129.1984406 1
 
4.5%
129.0300747 1
 
4.5%
129.1011365 1
 
4.5%
129.0129554 1
 
4.5%
129.124563 1
 
4.5%
129.0249867 1
 
4.5%
129.171743 1
 
4.5%
129.037216 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
129.0105723 1
4.5%
129.0129554 1
4.5%
129.0249867 1
4.5%
129.0267975 1
4.5%
129.0300747 1
4.5%
129.037216 1
4.5%
129.0426739 1
4.5%
129.0532074 1
4.5%
129.0705002 1
4.5%
129.0833069 1
4.5%
ValueCountFrequency (%)
129.22197 1
4.5%
129.1984406 1
4.5%
129.171743 1
4.5%
129.1535565 1
4.5%
129.1393787 1
4.5%
129.1299987 1
4.5%
129.1260341 1
4.5%
129.124563 1
4.5%
129.1186685 1
4.5%
129.1011365 1
4.5%

시설명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T08:01:21.759767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.5909091
Min length3

Characters and Unicode

Total characters189
Distinct characters68
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

Unique22 ?
Unique (%)100.0%

Sample

1st row천문사
2nd row흥구리 노인사랑방
3rd row원리1리 마을회관
4th row수하1리 마을회관
5th row영양군 농업기술센터
ValueCountFrequency (%)
마을회관 10
23.3%
경로당 2
 
4.7%
천문사 1
 
2.3%
구매1리 1
 
2.3%
상청 1
 
2.3%
1리 1
 
2.3%
토구리 1
 
2.3%
요원1리 1
 
2.3%
경로회관 1
 
2.3%
양항리 1
 
2.3%
Other values (23) 23
53.5%
2023-12-13T08:01:22.066907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
11.1%
리 19
 
10.1%
관 14
 
7.4%
회 14
 
7.4%
을 13
 
6.9%
마 13
 
6.9%
1 7
 
3.7%
경 4
 
2.1%
구 4
 
2.1%
로 4
 
2.1%
Other values (58) 76
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159
84.1%
Space Separator 21
 
11.1%
Decimal Number 9
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 19
 
11.9%
관 14
 
8.8%
회 14
 
8.8%
을 13
 
8.2%
마 13
 
8.2%
경 4
 
2.5%
구 4
 
2.5%
로 4
 
2.5%
양 3
 
1.9%
교 3
 
1.9%
Other values (54) 68
42.8%
Decimal Number
ValueCountFrequency (%)
1 7
77.8%
3 1
 
11.1%
2 1
 
11.1%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159
84.1%
Common 30
 
15.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 19
 
11.9%
관 14
 
8.8%
회 14
 
8.8%
을 13
 
8.2%
마 13
 
8.2%
경 4
 
2.5%
구 4
 
2.5%
로 4
 
2.5%
양 3
 
1.9%
교 3
 
1.9%
Other values (54) 68
42.8%
Common
ValueCountFrequency (%)
21
70.0%
1 7
 
23.3%
3 1
 
3.3%
2 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159
84.1%
ASCII 30
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
70.0%
1 7
 
23.3%
3 1
 
3.3%
2 1
 
3.3%
Hangul
ValueCountFrequency (%)
리 19
 
11.9%
관 14
 
8.8%
회 14
 
8.8%
을 13
 
8.2%
마 13
 
8.2%
경 4
 
2.5%
구 4
 
2.5%
로 4
 
2.5%
양 3
 
1.9%
교 3
 
1.9%
Other values (54) 68
42.8%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.95455
Minimum55
Maximum750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T08:01:22.168966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55
5-th percentile100
Q1100
median105
Q3120
95-th percentile671.5
Maximum750
Range695
Interquartile range (IQR)20

Descriptive statistics

Standard deviation182.72187
Coefficient of variation (CV)1.1213058
Kurtosis8.0245187
Mean162.95455
Median Absolute Deviation (MAD)10
Skewness3.0284458
Sum3585
Variance33387.284
MonotonicityNot monotonic
2023-12-13T08:01:22.271714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
100 10
45.5%
120 7
31.8%
110 1
 
4.5%
55 1
 
4.5%
130 1
 
4.5%
750 1
 
4.5%
700 1
 
4.5%
ValueCountFrequency (%)
55 1
 
4.5%
100 10
45.5%
110 1
 
4.5%
120 7
31.8%
130 1
 
4.5%
700 1
 
4.5%
750 1
 
4.5%
ValueCountFrequency (%)
750 1
 
4.5%
700 1
 
4.5%
130 1
 
4.5%
120 7
31.8%
110 1
 
4.5%
100 10
45.5%
55 1
 
4.5%

수용인원
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
20
10 
30
9 
50
 
1
100
 
1
150
 
1

Length

Max length3
Median length2
Mean length2.0909091
Min length2

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row30
2nd row30
3rd row30
4th row50
5th row100

Common Values

ValueCountFrequency (%)
20 10
45.5%
30 9
40.9%
50 1
 
4.5%
100 1
 
4.5%
150 1
 
4.5%

Length

2023-12-13T08:01:22.388722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:01:22.483436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 10
45.5%
30 9
40.9%
50 1
 
4.5%
100 1
 
4.5%
150 1
 
4.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-05-26
22 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-26
2nd row2023-05-26
3rd row2023-05-26
4th row2023-05-26
5th row2023-05-26

Common Values

ValueCountFrequency (%)
2023-05-26 22
100.0%

Length

2023-12-13T08:01:22.578171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:01:22.658501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-26 22
100.0%

Interactions

2023-12-13T08:01:19.567673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.235612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.572503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.210888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.655845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.317302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.660657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.286164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.741518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.411407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.032749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.382933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.843597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:18.483873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.110035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:01:19.461881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:01:22.719872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분주소경도위도시설명면적수용인원
연번1.0000.0001.0000.8230.6601.0000.0000.873
구분0.0001.0001.0000.0000.0001.0000.5460.869
주소1.0001.0001.0001.0001.0001.0001.0001.000
경도0.8230.0001.0001.0000.6461.0000.0000.000
위도0.6600.0001.0000.6461.0001.0000.0000.860
시설명1.0001.0001.0001.0001.0001.0001.0001.000
면적0.0000.5461.0000.0000.0001.0001.0000.679
수용인원0.8730.8691.0000.0000.8601.0000.6791.000
2023-12-13T08:01:22.809381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수용인원
구분1.0000.506
수용인원0.5061.000
2023-12-13T08:01:22.880855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도면적구분수용인원
연번1.0000.308-0.2220.2060.0000.441
경도0.3081.0000.0940.1620.0000.000
위도-0.2220.0941.0000.1390.0000.421
면적0.2060.1620.1391.0000.4530.615
구분0.0000.0000.0000.4531.0000.506
수용인원0.4410.0000.4210.6150.5061.000

Missing values

2023-12-13T08:01:19.957435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:01:20.084059image/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

연번구분주소경도위도시설명면적수용인원데이터기준일자
01기타경상북도 영양군 입암면 방전2길 2536.555591129.086254천문사110302023-05-26
12경로당경상북도 영양군 입암면 흥구1길 2536.548273129.0705흥구리 노인사랑방55302023-05-26
23마을회관경상북도 영양군 석보면 원리3길 1136.563309129.118669원리1리 마을회관130302023-05-26
34마을회관경상북도 영양군 수비면 괘벽길 6-136.787309129.22197수하1리 마을회관120502023-05-26
45관공서경상북도 영양군 영양읍 지평길 5136.65259129.153557영양군 농업기술센터7501002023-05-26
56마을회관경상북도 영양군 영양읍?감천2길 2436.618539129.09318감천1리 새마을회관100202023-05-26
67마을회관경상북도 영양군 영양읍 낙원로 5336.63746129.126034현 3리 마을회관100202023-05-26
78학교경상북도 영양군 영양읍 영양창수로 14136.661021129.139379영양여자고등학교100202023-05-26
89마을회관경상북도 영양군 입암면 후평길 236.59404129.010572산해 2리 마을회관100202023-05-26
910마을회관경상북도 영양군 일월면 섬촌1길 27-836.726353129.129999섬촌리 마을회관100202023-05-26
연번구분주소경도위도시설명면적수용인원데이터기준일자
1213마을회관경상북도 영양군 청기면 창마을길 636.716581129.026797사리마을회관100202023-05-26
1314경로당경상북도 영양군 청기면 청기로 58136.670352129.042674상청 1리 경로당100202023-05-26
1415마을회관경상북도 영양군 청기면 청기로 160836.695875129.037216토구리 마을회관100202023-05-26
1516경로당경상북도 영양군 석보면 원요로 45736.566468129.171743요원1리 경로회관100202023-05-26
1617마을회관경상북도 영양군 청기면 여미1길 1336.656468129.024987구매1리 마을회관120302023-05-26
1718마을회관경상북도 영양군 입암면 약수탕길 28-336.61192129.124563양항리 약수마을회관120302023-05-26
1819경로당경상북도 영양군 입암면 대천길 25136.613385129.012955대천리 산박골 경로당120302023-05-26
1920마을회관경상북도 영양군 입암면 노달1길 236.579865129.101136노달리 마을회관120302023-05-26
2021마을회관경상북도 영양군 청기면 맹촌길 636.756935129.030075무진리 마을회관120302023-05-26
2122마을회관경상북도 영양군 수비면 금촌길 1436.77553129.198441발리1리 마을회관120302023-05-26