Overview

Dataset statistics

Number of variables9
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory76.9 B

Variable types

Categorical1
Text3
Numeric3
DateTime2

Dataset

Description제주특별자치도 내 소재하고 있는 노인의료복지시설(요양시설)과 관련한 데이터로 읍면동, 시설명, 정원, 현원, 종사자, 소재지, 설치일, 전화번호 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15056183/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
정원 is highly overall correlated with 현원 and 1 other fieldsHigh correlation
현원 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
종사자 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
시설명 has unique valuesUnique
현원 has 1 (1.4%) zerosZeros
종사자 has 1 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-12 21:24:37.429777
Analysis finished2023-12-12 21:24:39.706251
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct27
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
아라동
6 
영천동
5 
대정읍
5 
오라동
5 
외도동
 
4
Other values (22)
45 

Length

Max length4
Median length3
Mean length3.0857143
Min length2

Unique

Unique9 ?
Unique (%)12.9%

Sample

1st row한림읍
2nd row한림읍
3rd row한림읍
4th row한림읍
5th row애월읍

Common Values

ValueCountFrequency (%)
아라동 6
 
8.6%
영천동 5
 
7.1%
대정읍 5
 
7.1%
오라동 5
 
7.1%
외도동 4
 
5.7%
한림읍 4
 
5.7%
조천읍 4
 
5.7%
일도1동 3
 
4.3%
성산읍 3
 
4.3%
남원읍 3
 
4.3%
Other values (17) 28
40.0%

Length

2023-12-13T06:24:39.785360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아라동 6
 
8.6%
대정읍 5
 
7.1%
오라동 5
 
7.1%
영천동 5
 
7.1%
외도동 4
 
5.7%
한림읍 4
 
5.7%
조천읍 4
 
5.7%
일도1동 3
 
4.3%
성산읍 3
 
4.3%
남원읍 3
 
4.3%
Other values (17) 28
40.0%

시설명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T06:24:39.990801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.7857143
Min length3

Characters and Unicode

Total characters475
Distinct characters130
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

Unique70 ?
Unique (%)100.0%

Sample

1st row성이시돌요양원
2nd row서부요양원
3rd row서부노인요양원
4th row제주대림요양원
5th row제주원광요양원
ValueCountFrequency (%)
성이시돌요양원 1
 
1.4%
아라요양원 1
 
1.4%
남제주요양원 1
 
1.4%
가족요양원 1
 
1.4%
혼디사랑요양원 1
 
1.4%
나눔요양원 1
 
1.4%
성지요양원 1
 
1.4%
제주요양원 1
 
1.4%
위미에덴요양원 1
 
1.4%
해안요양원 1
 
1.4%
Other values (63) 63
86.3%
2023-12-13T06:24:40.312825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 61
 
12.8%
양 56
 
11.8%
요 55
 
11.6%
제 11
 
2.3%
인 11
 
2.3%
노 11
 
2.3%
주 10
 
2.1%
광 8
 
1.7%
성 7
 
1.5%
지 7
 
1.5%
Other values (120) 238
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
97.5%
Decimal Number 6
 
1.3%
Space Separator 3
 
0.6%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 61
 
13.2%
양 56
 
12.1%
요 55
 
11.9%
제 11
 
2.4%
인 11
 
2.4%
노 11
 
2.4%
주 10
 
2.2%
광 8
 
1.7%
성 7
 
1.5%
지 7
 
1.5%
Other values (113) 226
48.8%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
6 2
33.3%
5 2
33.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
O 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
97.5%
Common 9
 
1.9%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 61
 
13.2%
양 56
 
12.1%
요 55
 
11.9%
제 11
 
2.4%
인 11
 
2.4%
노 11
 
2.4%
주 10
 
2.2%
광 8
 
1.7%
성 7
 
1.5%
지 7
 
1.5%
Other values (113) 226
48.8%
Common
ValueCountFrequency (%)
3
33.3%
3 2
22.2%
6 2
22.2%
5 2
22.2%
Latin
ValueCountFrequency (%)
P 1
33.3%
O 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
97.5%
ASCII 12
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 61
 
13.2%
양 56
 
12.1%
요 55
 
11.9%
제 11
 
2.4%
인 11
 
2.4%
노 11
 
2.4%
주 10
 
2.2%
광 8
 
1.7%
성 7
 
1.5%
지 7
 
1.5%
Other values (113) 226
48.8%
ASCII
ValueCountFrequency (%)
3
25.0%
3 2
16.7%
6 2
16.7%
5 2
16.7%
P 1
 
8.3%
O 1
 
8.3%
T 1
 
8.3%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.757143
Minimum9
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T06:24:40.445054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9
Q119.5
median56.5
Q387.25
95-th percentile107.15
Maximum200
Range191
Interquartile range (IQR)67.75

Descriptive statistics

Standard deviation39.626677
Coefficient of variation (CV)0.69817955
Kurtosis0.77012352
Mean56.757143
Median Absolute Deviation (MAD)33.5
Skewness0.67202958
Sum3973
Variance1570.2735
MonotonicityNot monotonic
2023-12-13T06:24:40.588086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
9 10
 
14.3%
80 4
 
5.7%
29 3
 
4.3%
81 3
 
4.3%
90 3
 
4.3%
98 2
 
2.9%
84 2
 
2.9%
21 2
 
2.9%
28 2
 
2.9%
48 2
 
2.9%
Other values (34) 37
52.9%
ValueCountFrequency (%)
9 10
14.3%
10 1
 
1.4%
13 1
 
1.4%
14 1
 
1.4%
15 1
 
1.4%
16 1
 
1.4%
17 1
 
1.4%
18 1
 
1.4%
19 1
 
1.4%
21 2
 
2.9%
ValueCountFrequency (%)
200 1
1.4%
134 1
1.4%
128 1
1.4%
113 1
1.4%
100 1
1.4%
98 2
2.9%
96 1
1.4%
95 1
1.4%
93 1
1.4%
92 1
1.4%

현원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.071429
Minimum0
Maximum122
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T06:24:40.753213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.45
Q116
median45.5
Q374
95-th percentile90.2
Maximum122
Range122
Interquartile range (IQR)58

Descriptive statistics

Standard deviation31.644457
Coefficient of variation (CV)0.67226463
Kurtosis-1.1005544
Mean47.071429
Median Absolute Deviation (MAD)29
Skewness0.21817359
Sum3295
Variance1001.3716
MonotonicityNot monotonic
2023-12-13T06:24:40.891778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 5
 
7.1%
8 4
 
5.7%
16 3
 
4.3%
74 3
 
4.3%
81 2
 
2.9%
66 2
 
2.9%
53 2
 
2.9%
18 2
 
2.9%
56 2
 
2.9%
23 2
 
2.9%
Other values (42) 43
61.4%
ValueCountFrequency (%)
0 1
 
1.4%
4 1
 
1.4%
6 1
 
1.4%
7 1
 
1.4%
8 4
5.7%
9 5
7.1%
13 1
 
1.4%
14 1
 
1.4%
15 1
 
1.4%
16 3
4.3%
ValueCountFrequency (%)
122 1
1.4%
115 1
1.4%
97 1
1.4%
92 1
1.4%
88 1
1.4%
86 1
1.4%
85 1
1.4%
84 2
2.9%
83 1
1.4%
81 2
2.9%

종사자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.142857
Minimum0
Maximum85
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T06:24:41.030931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q113
median38
Q351
95-th percentile61.55
Maximum85
Range85
Interquartile range (IQR)38

Descriptive statistics

Standard deviation21.617415
Coefficient of variation (CV)0.65224959
Kurtosis-0.9059478
Mean33.142857
Median Absolute Deviation (MAD)19.5
Skewness0.25580172
Sum2320
Variance467.31263
MonotonicityNot monotonic
2023-12-13T06:24:41.161433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
51 4
 
5.7%
7 4
 
5.7%
6 4
 
5.7%
40 3
 
4.3%
13 3
 
4.3%
50 3
 
4.3%
42 2
 
2.9%
44 2
 
2.9%
38 2
 
2.9%
29 2
 
2.9%
Other values (35) 41
58.6%
ValueCountFrequency (%)
0 1
 
1.4%
4 1
 
1.4%
5 1
 
1.4%
6 4
5.7%
7 4
5.7%
8 1
 
1.4%
9 2
2.9%
10 1
 
1.4%
11 1
 
1.4%
12 1
 
1.4%
ValueCountFrequency (%)
85 1
1.4%
81 1
1.4%
78 1
1.4%
62 1
1.4%
61 1
1.4%
60 1
1.4%
58 2
2.9%
57 1
1.4%
55 1
1.4%
54 2
2.9%

소재지
Text

Distinct67
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T06:24:41.440268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.871429
Min length18

Characters and Unicode

Total characters1601
Distinct characters121
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

Unique64 ?
Unique (%)91.4%

Sample

1st row제주특별자치도 제주시 한림읍 산록남로60
2nd row제주특별자치도 제주시 한림읍 한림중앙로 285
3rd row제주특별자치도 제주시 한림읍 한림중앙로 285
4th row제주특별자치도 제주시 한림읍 한수풀로 60
5th row제주특별자치도 제주시 애월읍 고성남길 101
ValueCountFrequency (%)
제주특별자치도 70
22.4%
제주시 49
 
15.7%
서귀포시 21
 
6.7%
대정읍 5
 
1.6%
한림읍 4
 
1.3%
조천읍 4
 
1.3%
애월읍 3
 
1.0%
오라남로 3
 
1.0%
남원읍 3
 
1.0%
동문로 3
 
1.0%
Other values (123) 147
47.1%
2023-12-13T06:24:41.872966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
 
15.1%
주 122
 
7.6%
제 119
 
7.4%
자 72
 
4.5%
도 72
 
4.5%
특 70
 
4.4%
별 70
 
4.4%
치 70
 
4.4%
시 70
 
4.4%
1 55
 
3.4%
Other values (111) 639
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1092
68.2%
Decimal Number 245
 
15.3%
Space Separator 242
 
15.1%
Dash Punctuation 22
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 122
 
11.2%
제 119
 
10.9%
자 72
 
6.6%
도 72
 
6.6%
특 70
 
6.4%
별 70
 
6.4%
치 70
 
6.4%
시 70
 
6.4%
길 44
 
4.0%
로 42
 
3.8%
Other values (99) 341
31.2%
Decimal Number
ValueCountFrequency (%)
1 55
22.4%
2 38
15.5%
6 27
11.0%
5 22
 
9.0%
8 21
 
8.6%
4 19
 
7.8%
7 19
 
7.8%
3 15
 
6.1%
0 15
 
6.1%
9 14
 
5.7%
Space Separator
ValueCountFrequency (%)
242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1092
68.2%
Common 509
31.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 122
 
11.2%
제 119
 
10.9%
자 72
 
6.6%
도 72
 
6.6%
특 70
 
6.4%
별 70
 
6.4%
치 70
 
6.4%
시 70
 
6.4%
길 44
 
4.0%
로 42
 
3.8%
Other values (99) 341
31.2%
Common
ValueCountFrequency (%)
242
47.5%
1 55
 
10.8%
2 38
 
7.5%
6 27
 
5.3%
5 22
 
4.3%
- 22
 
4.3%
8 21
 
4.1%
4 19
 
3.7%
7 19
 
3.7%
3 15
 
2.9%
Other values (2) 29
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1092
68.2%
ASCII 509
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
47.5%
1 55
 
10.8%
2 38
 
7.5%
6 27
 
5.3%
5 22
 
4.3%
- 22
 
4.3%
8 21
 
4.1%
4 19
 
3.7%
7 19
 
3.7%
3 15
 
2.9%
Other values (2) 29
 
5.7%
Hangul
ValueCountFrequency (%)
주 122
 
11.2%
제 119
 
10.9%
자 72
 
6.6%
도 72
 
6.6%
특 70
 
6.4%
별 70
 
6.4%
치 70
 
6.4%
시 70
 
6.4%
길 44
 
4.0%
로 42
 
3.8%
Other values (99) 341
31.2%

설치일
Date

Distinct66
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
Minimum1988-04-01 00:00:00
Maximum2022-09-23 00:00:00
2023-12-13T06:24:42.053236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:42.192188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

Distinct69
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T06:24:42.412143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters840
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

Unique68 ?
Unique (%)97.1%

Sample

1st row064-796-0037
2nd row064-796-6780
3rd row064-796-6780
4th row064-796-9000
5th row064-799-3999
ValueCountFrequency (%)
064-796-6780 2
 
2.9%
064-764-8254 1
 
1.4%
064-794-2232 1
 
1.4%
064-792-7662 1
 
1.4%
064-746-5700 1
 
1.4%
064-712-8383 1
 
1.4%
064-713-5405 1
 
1.4%
064-747-8338 1
 
1.4%
064-712-7769 1
 
1.4%
064-746-6668 1
 
1.4%
Other values (59) 59
84.3%
2023-12-13T06:24:42.850392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 140
16.7%
0 121
14.4%
6 118
14.0%
7 102
12.1%
4 99
11.8%
2 58
6.9%
9 53
 
6.3%
3 42
 
5.0%
5 39
 
4.6%
8 38
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
83.3%
Dash Punctuation 140
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 121
17.3%
6 118
16.9%
7 102
14.6%
4 99
14.1%
2 58
8.3%
9 53
7.6%
3 42
 
6.0%
5 39
 
5.6%
8 38
 
5.4%
1 30
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 140
16.7%
0 121
14.4%
6 118
14.0%
7 102
12.1%
4 99
11.8%
2 58
6.9%
9 53
 
6.3%
3 42
 
5.0%
5 39
 
4.6%
8 38
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 140
16.7%
0 121
14.4%
6 118
14.0%
7 102
12.1%
4 99
11.8%
2 58
6.9%
9 53
 
6.3%
3 42
 
5.0%
5 39
 
4.6%
8 38
 
4.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T06:24:43.013763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:43.123041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:24:39.173875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:38.481910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:38.874986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:39.263075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:38.597233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:38.987896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:39.360159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:38.731302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:39.090288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:24:43.214991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동시설명정원현원종사자소재지설치일전화번호
읍면동1.0001.0000.0000.0000.4721.0000.9711.000
시설명1.0001.0001.0001.0001.0001.0001.0001.000
정원0.0001.0001.0000.8380.7730.9800.9871.000
현원0.0001.0000.8381.0000.9660.9550.8751.000
종사자0.4721.0000.7730.9661.0000.9410.7801.000
소재지1.0001.0000.9800.9550.9411.0000.9791.000
설치일0.9711.0000.9870.8750.7800.9791.0000.994
전화번호1.0001.0001.0001.0001.0001.0000.9941.000
2023-12-13T06:24:43.401932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원현원종사자읍면동
정원1.0000.9350.9300.000
현원0.9351.0000.9820.000
종사자0.9300.9821.0000.155
읍면동0.0000.0000.1551.000

Missing values

2023-12-13T06:24:39.509796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:24:39.652004image/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

읍면동시설명정원현원종사자소재지설치일전화번호데이터기준일자
0한림읍성이시돌요양원858651제주특별자치도 제주시 한림읍 산록남로602003-06-30064-796-00372022-12-31
1한림읍서부요양원987제주특별자치도 제주시 한림읍 한림중앙로 2852011-10-18064-796-67802022-12-31
2한림읍서부노인요양원987제주특별자치도 제주시 한림읍 한림중앙로 2852011-11-21064-796-67802022-12-31
3한림읍제주대림요양원291612제주특별자치도 제주시 한림읍 한수풀로 602021-05-12064-796-90002022-12-31
4애월읍제주원광요양원2007458제주특별자치도 제주시 애월읍 고성남길 1011988-04-01064-799-39992022-12-31
5애월읍주사랑요양원845741제주특별자치도 제주시 애월읍 애상로 76-262004-05-04064-799-98892022-12-31
6애월읍주사랑소규모요양원232316제주특별자치도 제주시 애월읍 애상로 76-262009-02-05064-799-08552022-12-31
7구좌읍세화요양원817452제주특별자치도 제주시 구좌읍 세화서길7-12005-07-28064-782-15952022-12-31
8구좌읍소망요양원817150제주특별자치도 제주시 구좌읍 동김길 1502004-05-04064-782-05552022-12-31
9조천읍은빛마을노인복지센터282618제주특별자치도 제주시 조천읍 함덕20길 422008-10-31064-784-39992022-12-31
읍면동시설명정원현원종사자소재지설치일전화번호데이터기준일자
60안덕면동광효도마을907246제주특별자치도 서귀포시 안덕면 한창로 6192008-06-13064-792-03612022-12-31
61표선면예담노인전문요양원807654제주특별자치도 서귀포시 표선면 번영로3428번길 1072013-05-30064-787-94922022-12-31
62영천동경천전문요양원806949제주특별자치도 서귀포시 토평로 1702008-05-28064-732-90092022-12-31
63영천동기로회요양원807051제주특별자치도 서귀포시 상효로 74-82016-03-01064-767-09252022-12-31
64영천동성요셉요양원685643제주특별자치도 서귀포시 배낭골로 812006-03-01064-732-76072022-12-31
65영천동제일요양원929260제주특별자치도 서귀포시 정방연로 52-82008-06-19064-733-25872022-12-31
66영천동평안전문요양원908358제주특별자치도 서귀포시 토평로 1722017-07-01064-733-90052022-12-31
67서홍동서귀원광노인복지센터181814제주특별자치도 서귀포시 서홍로69번길 129-22010-06-10064-763-24562022-12-31
68대륜동서호요양원888562제주특별자치도 서귀포시 서호호근로238번길 102009-10-05064-739-99112022-12-31
69중문동중문요양원393122제주특별자치도 서귀포시 일주서로728번길 742013-03-29064-738-20102022-12-31