Overview

Dataset statistics

Number of variables8
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory71.6 B

Variable types

Numeric3
Text4
Categorical1

Dataset

Description경상북도 내 노인 관련 복지시설 정보를 제공합니다(경상북도 노인주거복지시설의 시군구, 시설종류, 시설명, 시설 소재지, 연락처, 정원, 현원)
Author경상북도
URLhttps://www.data.go.kr/data/15052028/fileData.do

Alerts

정원 is highly overall correlated with 현원High correlation
현원 is highly overall correlated with 정원High correlation
시설종류 is highly imbalanced (56.4%)Imbalance
연번 has unique valuesUnique
시설명 has unique valuesUnique
소재지 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:16:56.978617
Analysis finished2023-12-12 09:16:58.564195
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:16:58.663941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2023-12-12T18:16:58.826492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

시군
Text

Distinct17
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T18:16:59.014665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters87
Distinct characters27
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

Unique9 ?
Unique (%)31.0%

Sample

1st row포항시
2nd row포항시
3rd row경주시
4th row경주시
5th row경주시
ValueCountFrequency (%)
칠곡군 4
13.8%
안동시 3
10.3%
경주시 3
10.3%
포항시 2
 
6.9%
문경시 2
 
6.9%
고령군 2
 
6.9%
청도군 2
 
6.9%
경산시 2
 
6.9%
상주시 1
 
3.4%
군위군 1
 
3.4%
Other values (7) 7
24.1%
2023-12-12T18:16:59.312313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 16
18.4%
군 14
16.1%
경 7
 
8.0%
주 6
 
6.9%
칠 4
 
4.6%
곡 4
 
4.6%
동 3
 
3.4%
청 3
 
3.4%
안 3
 
3.4%
포 2
 
2.3%
Other values (17) 25
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
18.4%
군 14
16.1%
경 7
 
8.0%
주 6
 
6.9%
칠 4
 
4.6%
곡 4
 
4.6%
동 3
 
3.4%
청 3
 
3.4%
안 3
 
3.4%
포 2
 
2.3%
Other values (17) 25
28.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
18.4%
군 14
16.1%
경 7
 
8.0%
주 6
 
6.9%
칠 4
 
4.6%
곡 4
 
4.6%
동 3
 
3.4%
청 3
 
3.4%
안 3
 
3.4%
포 2
 
2.3%
Other values (17) 25
28.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 16
18.4%
군 14
16.1%
경 7
 
8.0%
주 6
 
6.9%
칠 4
 
4.6%
곡 4
 
4.6%
동 3
 
3.4%
청 3
 
3.4%
안 3
 
3.4%
포 2
 
2.3%
Other values (17) 25
28.7%

시설종류
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
양로시설
25 
노인공동생활가정
3 
양로시설
 
1

Length

Max length8
Median length4
Mean length4.4482759
Min length4

Unique

Unique1 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
양로시설 25
86.2%
노인공동생활가정 3
 
10.3%
양로시설 1
 
3.4%

Length

2023-12-12T18:16:59.459437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:59.577643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양로시설 26
89.7%
노인공동생활가정 3
 
10.3%

시설명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T18:16:59.778233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.5172414
Min length3

Characters and Unicode

Total characters160
Distinct characters76
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

Unique29 ?
Unique (%)100.0%

Sample

1st row상락원
2nd row엘림믿음의집
3rd row나자레원
4th row천우자애원
5th row경주실버타운
ValueCountFrequency (%)
상락원 1
 
3.3%
엘림믿음의집 1
 
3.3%
분도노인마을 1
 
3.3%
칠곡실버타운 1
 
3.3%
성모애덕의집 1
 
3.3%
성가양로원 1
 
3.3%
복지마을 1
 
3.3%
고령성가의집 1
 
3.3%
대창양로원 1
 
3.3%
오복노인의집 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T18:17:00.144987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 11
 
6.9%
집 10
 
6.2%
로 8
 
5.0%
의 8
 
5.0%
양 7
 
4.4%
성 5
 
3.1%
을 4
 
2.5%
복 4
 
2.5%
인 4
 
2.5%
마 4
 
2.5%
Other values (66) 95
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159
99.4%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 11
 
6.9%
집 10
 
6.3%
로 8
 
5.0%
의 8
 
5.0%
양 7
 
4.4%
성 5
 
3.1%
을 4
 
2.5%
복 4
 
2.5%
인 4
 
2.5%
마 4
 
2.5%
Other values (65) 94
59.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159
99.4%
Common 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 11
 
6.9%
집 10
 
6.3%
로 8
 
5.0%
의 8
 
5.0%
양 7
 
4.4%
성 5
 
3.1%
을 4
 
2.5%
복 4
 
2.5%
인 4
 
2.5%
마 4
 
2.5%
Other values (65) 94
59.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159
99.4%
ASCII 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 11
 
6.9%
집 10
 
6.3%
로 8
 
5.0%
의 8
 
5.0%
양 7
 
4.4%
성 5
 
3.1%
을 4
 
2.5%
복 4
 
2.5%
인 4
 
2.5%
마 4
 
2.5%
Other values (65) 94
59.1%
ASCII
ValueCountFrequency (%)
1
100.0%

소재지
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T18:17:00.430211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length17.241379
Min length13

Characters and Unicode

Total characters500
Distinct characters112
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

Unique29 ?
Unique (%)100.0%

Sample

1st row포항시 남구 장기면 산서길 54
2nd row포항시 북구 송라면 동해대로 2792-97
3rd row경주시 천사2길 22-1 (구정동)
4th row경주시 현곡면 가막골길 141-30
5th row경주시 충효천길 66-12
ValueCountFrequency (%)
칠곡군 4
 
3.5%
안동시 3
 
2.6%
경주시 3
 
2.6%
포항시 2
 
1.7%
왜관읍 2
 
1.7%
경산시 2
 
1.7%
문경시 2
 
1.7%
청도군 2
 
1.7%
고령군 2
 
1.7%
동명면 2
 
1.7%
Other values (90) 91
79.1%
2023-12-12T18:17:00.806648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
17.4%
1 28
 
5.6%
길 23
 
4.6%
2 19
 
3.8%
면 18
 
3.6%
- 17
 
3.4%
4 16
 
3.2%
시 16
 
3.2%
군 14
 
2.8%
동 12
 
2.4%
Other values (102) 250
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
54.0%
Decimal Number 122
24.4%
Space Separator 87
 
17.4%
Dash Punctuation 17
 
3.4%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 23
 
8.5%
면 18
 
6.7%
시 16
 
5.9%
군 14
 
5.2%
동 12
 
4.4%
로 9
 
3.3%
남 8
 
3.0%
경 7
 
2.6%
주 7
 
2.6%
안 6
 
2.2%
Other values (88) 150
55.6%
Decimal Number
ValueCountFrequency (%)
1 28
23.0%
2 19
15.6%
4 16
13.1%
3 11
 
9.0%
7 9
 
7.4%
0 8
 
6.6%
9 8
 
6.6%
8 8
 
6.6%
6 8
 
6.6%
5 7
 
5.7%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
54.0%
Common 230
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 23
 
8.5%
면 18
 
6.7%
시 16
 
5.9%
군 14
 
5.2%
동 12
 
4.4%
로 9
 
3.3%
남 8
 
3.0%
경 7
 
2.6%
주 7
 
2.6%
안 6
 
2.2%
Other values (88) 150
55.6%
Common
ValueCountFrequency (%)
87
37.8%
1 28
 
12.2%
2 19
 
8.3%
- 17
 
7.4%
4 16
 
7.0%
3 11
 
4.8%
7 9
 
3.9%
0 8
 
3.5%
9 8
 
3.5%
8 8
 
3.5%
Other values (4) 19
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
54.0%
ASCII 230
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
37.8%
1 28
 
12.2%
2 19
 
8.3%
- 17
 
7.4%
4 16
 
7.0%
3 11
 
4.8%
7 9
 
3.9%
0 8
 
3.5%
9 8
 
3.5%
8 8
 
3.5%
Other values (4) 19
 
8.3%
Hangul
ValueCountFrequency (%)
길 23
 
8.5%
면 18
 
6.7%
시 16
 
5.9%
군 14
 
5.2%
동 12
 
4.4%
로 9
 
3.3%
남 8
 
3.0%
경 7
 
2.6%
주 7
 
2.6%
안 6
 
2.2%
Other values (88) 150
55.6%

연락처
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T18:17:01.072871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row054-614-2233
2nd row054-254-0691
3rd row054-746-4827
4th row054-745-4900
5th row054-772-1114
ValueCountFrequency (%)
054-614-2233 1
 
3.4%
053-851-1408 1
 
3.4%
054-976-7575 1
 
3.4%
054-976-2080 1
 
3.4%
054-972-6219 1
 
3.4%
054-974-8122 1
 
3.4%
054-933-8050 1
 
3.4%
054-954-1824 1
 
3.4%
054-955-0038 1
 
3.4%
054-371-0038 1
 
3.4%
Other values (19) 19
65.5%
2023-12-12T18:17:01.462396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
16.7%
5 52
14.9%
0 50
14.4%
4 48
13.8%
2 26
7.5%
1 24
6.9%
3 24
6.9%
7 20
 
5.7%
8 19
 
5.5%
6 14
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 52
17.9%
0 50
17.2%
4 48
16.6%
2 26
9.0%
1 24
8.3%
3 24
8.3%
7 20
 
6.9%
8 19
 
6.6%
6 14
 
4.8%
9 13
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
16.7%
5 52
14.9%
0 50
14.4%
4 48
13.8%
2 26
7.5%
1 24
6.9%
3 24
6.9%
7 20
 
5.7%
8 19
 
5.5%
6 14
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
16.7%
5 52
14.9%
0 50
14.4%
4 48
13.8%
2 26
7.5%
1 24
6.9%
3 24
6.9%
7 20
 
5.7%
8 19
 
5.5%
6 14
 
4.0%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.37931
Minimum9
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:17:01.612177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9
Q124
median49
Q360
95-th percentile71.2
Maximum80
Range71
Interquartile range (IQR)36

Descriptive statistics

Standard deviation23.016165
Coefficient of variation (CV)0.55622398
Kurtosis-1.4632988
Mean41.37931
Median Absolute Deviation (MAD)21
Skewness0.10169781
Sum1200
Variance529.74384
MonotonicityNot monotonic
2023-12-12T18:17:01.817473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
70 5
17.2%
50 5
17.2%
9 3
10.3%
60 2
 
6.9%
17 2
 
6.9%
25 2
 
6.9%
24 2
 
6.9%
27 1
 
3.4%
72 1
 
3.4%
29 1
 
3.4%
Other values (5) 5
17.2%
ValueCountFrequency (%)
9 3
10.3%
13 1
 
3.4%
17 2
6.9%
21 1
 
3.4%
24 2
6.9%
25 2
6.9%
27 1
 
3.4%
29 1
 
3.4%
30 1
 
3.4%
49 1
 
3.4%
ValueCountFrequency (%)
80 1
 
3.4%
72 1
 
3.4%
70 5
17.2%
60 2
 
6.9%
50 5
17.2%
49 1
 
3.4%
30 1
 
3.4%
29 1
 
3.4%
27 1
 
3.4%
25 2
 
6.9%

현원
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.793103
Minimum2
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:17:01.983370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.4
Q113
median23
Q342
95-th percentile56.6
Maximum67
Range65
Interquartile range (IQR)29

Descriptive statistics

Standard deviation18.85732
Coefficient of variation (CV)0.70381246
Kurtosis-0.92644797
Mean26.793103
Median Absolute Deviation (MAD)16
Skewness0.41441988
Sum777
Variance355.59852
MonotonicityNot monotonic
2023-12-12T18:17:02.162707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
36 3
 
10.3%
4 2
 
6.9%
23 2
 
6.9%
6 2
 
6.9%
44 2
 
6.9%
18 1
 
3.4%
13 1
 
3.4%
42 1
 
3.4%
67 1
 
3.4%
22 1
 
3.4%
Other values (13) 13
44.8%
ValueCountFrequency (%)
2 1
3.4%
3 1
3.4%
4 2
6.9%
6 2
6.9%
7 1
3.4%
13 1
3.4%
14 1
3.4%
15 1
3.4%
16 1
3.4%
17 1
3.4%
ValueCountFrequency (%)
67 1
 
3.4%
57 1
 
3.4%
56 1
 
3.4%
53 1
 
3.4%
46 1
 
3.4%
44 2
6.9%
42 1
 
3.4%
38 1
 
3.4%
36 3
10.3%
29 1
 
3.4%

Interactions

2023-12-12T18:16:58.011952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.381990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.699672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:58.095851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.486582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.796819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:58.185309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.591861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:57.913091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:17:02.307010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군시설종류시설명소재지연락처정원현원
연번1.0000.9330.0001.0001.0001.0000.0000.564
시군0.9331.0000.0001.0001.0001.0000.6700.766
시설종류0.0000.0001.0001.0001.0001.0000.6160.000
시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
정원0.0000.6700.6161.0001.0001.0001.0000.659
현원0.5640.7660.0001.0001.0001.0000.6591.000
2023-12-12T18:17:02.799644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번정원현원시설종류
연번1.000-0.1690.1180.000
정원-0.1691.0000.7410.464
현원0.1180.7411.0000.000
시설종류0.0000.4640.0001.000

Missing values

2023-12-12T18:16:58.342211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:16:58.501020image/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

연번시군시설종류시설명소재지연락처정원현원
01포항시양로시설상락원포항시 남구 장기면 산서길 54054-614-22337036
12포항시양로시설엘림믿음의집포항시 북구 송라면 동해대로 2792-97054-254-06917044
23경주시양로시설나자레원경주시 천사2길 22-1 (구정동)054-746-4827504
34경주시양로시설천우자애원경주시 현곡면 가막골길 141-30054-745-49005046
45경주시양로시설경주실버타운경주시 충효천길 66-12054-772-11142715
56안동시양로시설설송양로원안동시 풍산읍 죽전길 139-76054-857-42437214
67안동시양로시설우리집안동시 노하동4길 114-65054-852-4815292
78안동시노인공동생활가정동인복지타운안동시 남후면 검암대실길 47054-852-232396
89구미시양로시설성심셀린의집구미시 선주로11길 14054-482-10015038
910영주시양로시설영주시립양로원 만수촌영주시 조와로277번길 298(조와동)054-635-35426053
연번시군시설종류시설명소재지연락처정원현원
1920청도군노인공동생활가정가은원청도군 각남면 함박길 194054-371-097393
2021청도군노인공동생활가정오복노인의집청도군 청도읍 고수동 3길 38-25054-371-003896
2122고령군양로시설대창양로원고령군 쌍림면 매촌1길 157054-955-00388056
2223고령군양로시설고령성가의집고령군 쌍림면 월막길 108054-954-18242522
2324성주군양로시설복지마을성주군 선남면 관용로 401-141054-933-80505023
2425칠곡군양로시설성가양로원칠곡군 동명면 한티로 140054-974-81227067
2526칠곡군양로시설성모애덕의집칠곡군 동명면 남원로 487054-972-62192423
2627칠곡군양로시설칠곡실버타운칠곡군 왜관읍 금남3길 27-30054-976-20807044
2728칠곡군양로시설분도노인마을칠곡군 왜관읍 금남4길 39054-976-75756042
2829울릉군양로시설송담양로원울릉군 서면 학포길 36054-791-61211313