Overview

Dataset statistics

Number of variables8
Number of observations36
Missing cells11
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory70.7 B

Variable types

Categorical1
Text3
Numeric3
DateTime1

Dataset

Description부산광역시_서구_사회복지시설현황_20220405
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081345

Alerts

종사자수 is highly overall correlated with 정원High correlation
정원 is highly overall correlated with 종사자수 and 2 other fieldsHigh correlation
현원 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
시설종별 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
전화번호 has 1 (2.8%) missing valuesMissing
정원 has 5 (13.9%) missing valuesMissing
현원 has 5 (13.9%) missing valuesMissing
시설명 has unique valuesUnique
현원 has 1 (2.8%) zerosZeros

Reproduction

Analysis started2023-12-10 16:36:35.040690
Analysis finished2023-12-10 16:36:36.524702
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종별
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
장애인복지시설
9 
지역아동센터
4 
한부모가족복지시설
3 
성매매피해자지원시설
3 
다함께돌봄센터
3 
Other values (9)
14 

Length

Max length14
Median length10
Mean length7.4722222
Min length5

Unique

Unique5 ?
Unique (%)13.9%

Sample

1st row사회복지관
2nd row사회복지관
3rd row한부모가족복지시설
4th row한부모가족복지시설
5th row한부모가족복지시설

Common Values

ValueCountFrequency (%)
장애인복지시설 9
25.0%
지역아동센터 4
11.1%
한부모가족복지시설 3
 
8.3%
성매매피해자지원시설 3
 
8.3%
다함께돌봄센터 3
 
8.3%
노인의료복지시설 3
 
8.3%
사회복지관 2
 
5.6%
아동양육시설 2
 
5.6%
노인복지관 2
 
5.6%
미혼모자가족복지시설 1
 
2.8%
Other values (4) 4
11.1%

Length

2023-12-11T01:36:36.583032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장애인복지시설 9
25.0%
지역아동센터 4
11.1%
한부모가족복지시설 3
 
8.3%
성매매피해자지원시설 3
 
8.3%
다함께돌봄센터 3
 
8.3%
노인의료복지시설 3
 
8.3%
사회복지관 2
 
5.6%
아동양육시설 2
 
5.6%
노인복지관 2
 
5.6%
미혼모자가족복지시설 1
 
2.8%
Other values (4) 4
11.1%

시설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T01:36:36.786394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length7.7222222
Min length2

Characters and Unicode

Total characters278
Distinct characters110
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

Unique36 ?
Unique (%)100.0%

Sample

1st row서구종합사회복지관
2nd row기독교종합사회복지관
3rd row다비다모자원
4th row은애모자원
5th row안나모자원
ValueCountFrequency (%)
사)여성인권지원센터 2
 
4.4%
살림 2
 
4.4%
부설 2
 
4.4%
서구장애인복지관 2
 
4.4%
서구종합사회복지관 1
 
2.2%
꿈나래 1
 
2.2%
해강 1
 
2.2%
나라단기거주시설 1
 
2.2%
천마재활원 1
 
2.2%
부산라이트하우스 1
 
2.2%
Other values (31) 31
68.9%
2023-12-11T01:36:37.129940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 12
 
4.3%
센 11
 
4.0%
원 10
 
3.6%
인 10
 
3.6%
지 10
 
3.6%
서 9
 
3.2%
구 9
 
3.2%
9
 
3.2%
부 7
 
2.5%
관 6
 
2.2%
Other values (100) 185
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 265
95.3%
Space Separator 9
 
3.2%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 12
 
4.5%
센 11
 
4.2%
원 10
 
3.8%
인 10
 
3.8%
지 10
 
3.8%
서 9
 
3.4%
구 9
 
3.4%
부 7
 
2.6%
관 6
 
2.3%
나 6
 
2.3%
Other values (97) 175
66.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 265
95.3%
Common 13
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 12
 
4.5%
센 11
 
4.2%
원 10
 
3.8%
인 10
 
3.8%
지 10
 
3.8%
서 9
 
3.4%
구 9
 
3.4%
부 7
 
2.6%
관 6
 
2.3%
나 6
 
2.3%
Other values (97) 175
66.0%
Common
ValueCountFrequency (%)
9
69.2%
( 2
 
15.4%
) 2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 265
95.3%
ASCII 13
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 12
 
4.5%
센 11
 
4.2%
원 10
 
3.8%
인 10
 
3.8%
지 10
 
3.8%
서 9
 
3.4%
구 9
 
3.4%
부 7
 
2.6%
관 6
 
2.3%
나 6
 
2.3%
Other values (97) 175
66.0%
ASCII
ValueCountFrequency (%)
9
69.2%
( 2
 
15.4%
) 2
 
15.4%

소재지주소
Text

Distinct32
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T01:36:37.326413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length25
Mean length20.722222
Min length15

Characters and Unicode

Total characters746
Distinct characters70
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)80.6%

Sample

1st row부산광역시 서구 망양로 193번길 104
2nd row부산광역시 서구 까치고개로229번길40
3rd row부산광역시 서구 꽃마을로 24
4th row부산광역시 서구 장군산로 103번길 6
5th row부산광역시 서구 꽃마을로163번길 40
ValueCountFrequency (%)
부산광역시 36
22.0%
서구 36
22.0%
구덕로 6
 
3.7%
천해로 3
 
1.8%
7번길 3
 
1.8%
55-10 3
 
1.8%
보수대로154번길 3
 
1.8%
192 3
 
1.8%
40 2
 
1.2%
104 2
 
1.2%
Other values (58) 67
40.9%
2023-12-11T01:36:37.625894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
17.2%
구 43
 
5.8%
시 39
 
5.2%
산 38
 
5.1%
부 37
 
5.0%
광 36
 
4.8%
역 36
 
4.8%
서 36
 
4.8%
로 36
 
4.8%
1 35
 
4.7%
Other values (60) 282
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
59.5%
Decimal Number 155
 
20.8%
Space Separator 128
 
17.2%
Dash Punctuation 8
 
1.1%
Other Punctuation 8
 
1.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 43
9.7%
시 39
 
8.8%
산 38
 
8.6%
부 37
 
8.3%
광 36
 
8.1%
역 36
 
8.1%
서 36
 
8.1%
로 36
 
8.1%
번 21
 
4.7%
길 21
 
4.7%
Other values (44) 101
22.7%
Decimal Number
ValueCountFrequency (%)
1 35
22.6%
3 21
13.5%
4 21
13.5%
5 15
9.7%
2 14
 
9.0%
0 14
 
9.0%
7 13
 
8.4%
6 10
 
6.5%
9 10
 
6.5%
8 2
 
1.3%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
59.5%
Common 301
40.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 43
9.7%
시 39
 
8.8%
산 38
 
8.6%
부 37
 
8.3%
광 36
 
8.1%
역 36
 
8.1%
서 36
 
8.1%
로 36
 
8.1%
번 21
 
4.7%
길 21
 
4.7%
Other values (44) 101
22.7%
Common
ValueCountFrequency (%)
128
42.5%
1 35
 
11.6%
3 21
 
7.0%
4 21
 
7.0%
5 15
 
5.0%
2 14
 
4.7%
0 14
 
4.7%
7 13
 
4.3%
6 10
 
3.3%
9 10
 
3.3%
Other values (5) 20
 
6.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
59.5%
ASCII 302
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
42.4%
1 35
 
11.6%
3 21
 
7.0%
4 21
 
7.0%
5 15
 
5.0%
2 14
 
4.6%
0 14
 
4.6%
7 13
 
4.3%
6 10
 
3.3%
9 10
 
3.3%
Other values (6) 21
 
7.0%
Hangul
ValueCountFrequency (%)
구 43
9.7%
시 39
 
8.8%
산 38
 
8.6%
부 37
 
8.3%
광 36
 
8.1%
역 36
 
8.1%
서 36
 
8.1%
로 36
 
8.1%
번 21
 
4.7%
길 21
 
4.7%
Other values (44) 101
22.7%

전화번호
Text

MISSING 

Distinct33
Distinct (%)94.3%
Missing1
Missing (%)2.8%
Memory size420.0 B
2023-12-11T01:36:37.798032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.057143
Min length12

Characters and Unicode

Total characters422
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

Unique31 ?
Unique (%)88.6%

Sample

1st row051-253-1922
2nd row051-257-9404
3rd row051-244-2508
4th row051-241-1133
5th row051-241-2421
ValueCountFrequency (%)
051-253-1922 2
 
5.7%
051-242-3930 2
 
5.7%
051-715-1511 1
 
2.9%
051-247-1161 1
 
2.9%
051-247-4084 1
 
2.9%
051-256-3096 1
 
2.9%
051-246-4084 1
 
2.9%
070-8915-3973 1
 
2.9%
051-241-5681 1
 
2.9%
051-257-9404 1
 
2.9%
Other values (23) 23
65.7%
2023-12-11T01:36:38.087921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 70
16.6%
- 70
16.6%
0 61
14.5%
1 59
14.0%
2 48
11.4%
4 36
8.5%
3 23
 
5.5%
7 21
 
5.0%
9 14
 
3.3%
8 10
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 352
83.4%
Dash Punctuation 70
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 70
19.9%
0 61
17.3%
1 59
16.8%
2 48
13.6%
4 36
10.2%
3 23
 
6.5%
7 21
 
6.0%
9 14
 
4.0%
8 10
 
2.8%
6 10
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 70
16.6%
- 70
16.6%
0 61
14.5%
1 59
14.0%
2 48
11.4%
4 36
8.5%
3 23
 
5.5%
7 21
 
5.0%
9 14
 
3.3%
8 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 70
16.6%
- 70
16.6%
0 61
14.5%
1 59
14.0%
2 48
11.4%
4 36
8.5%
3 23
 
5.5%
7 21
 
5.0%
9 14
 
3.3%
8 10
 
2.4%

종사자수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.888889
Minimum2
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T01:36:38.218984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.75
median8
Q320.25
95-th percentile45
Maximum53
Range51
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation14.538182
Coefficient of variation (CV)1.0467491
Kurtosis0.91871031
Mean13.888889
Median Absolute Deviation (MAD)5.5
Skewness1.4088101
Sum500
Variance211.35873
MonotonicityNot monotonic
2023-12-11T01:36:38.325335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 5
13.9%
3 4
 
11.1%
4 4
 
11.1%
8 3
 
8.3%
5 2
 
5.6%
9 2
 
5.6%
45 2
 
5.6%
21 1
 
2.8%
15 1
 
2.8%
14 1
 
2.8%
Other values (11) 11
30.6%
ValueCountFrequency (%)
2 5
13.9%
3 4
11.1%
4 4
11.1%
5 2
 
5.6%
6 1
 
2.8%
7 1
 
2.8%
8 3
8.3%
9 2
 
5.6%
10 1
 
2.8%
14 1
 
2.8%
ValueCountFrequency (%)
53 1
2.8%
45 2
5.6%
43 1
2.8%
37 1
2.8%
30 1
2.8%
24 1
2.8%
23 1
2.8%
21 1
2.8%
20 1
2.8%
17 1
2.8%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)64.5%
Missing5
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean88.129032
Minimum10
Maximum722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T01:36:38.424980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q120
median30
Q373
95-th percentile435
Maximum722
Range712
Interquartile range (IQR)53

Descriptive statistics

Standard deviation172.77302
Coefficient of variation (CV)1.9604552
Kurtosis11.356341
Mean88.129032
Median Absolute Deviation (MAD)15
Skewness3.4651447
Sum2732
Variance29850.516
MonotonicityNot monotonic
2023-12-11T01:36:38.513404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20 4
 
11.1%
29 4
 
11.1%
15 4
 
11.1%
30 3
 
8.3%
10 1
 
2.8%
722 1
 
2.8%
720 1
 
2.8%
86 1
 
2.8%
49 1
 
2.8%
150 1
 
2.8%
Other values (10) 10
27.8%
(Missing) 5
13.9%
ValueCountFrequency (%)
10 1
 
2.8%
15 4
11.1%
16 1
 
2.8%
20 4
11.1%
25 1
 
2.8%
29 4
11.1%
30 3
8.3%
36 1
 
2.8%
41 1
 
2.8%
45 1
 
2.8%
ValueCountFrequency (%)
722 1
2.8%
720 1
2.8%
150 1
2.8%
130 1
2.8%
110 1
2.8%
100 1
2.8%
86 1
2.8%
80 1
2.8%
66 1
2.8%
49 1
2.8%

현원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct23
Distinct (%)74.2%
Missing5
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean86.580645
Minimum0
Maximum722
Zeros1
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T01:36:38.600260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q118.5
median25
Q366.5
95-th percentile525
Maximum722
Range722
Interquartile range (IQR)48

Descriptive statistics

Standard deviation179.18571
Coefficient of variation (CV)2.0695816
Kurtosis9.63071
Mean86.580645
Median Absolute Deviation (MAD)10
Skewness3.2107246
Sum2684
Variance32107.518
MonotonicityNot monotonic
2023-12-11T01:36:38.711114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
15 3
 
8.3%
29 3
 
8.3%
24 3
 
8.3%
20 2
 
5.6%
21 2
 
5.6%
14 1
 
2.8%
330 1
 
2.8%
722 1
 
2.8%
720 1
 
2.8%
68 1
 
2.8%
Other values (13) 13
36.1%
(Missing) 5
 
13.9%
ValueCountFrequency (%)
0 1
 
2.8%
2 1
 
2.8%
8 1
 
2.8%
14 1
 
2.8%
15 3
8.3%
17 1
 
2.8%
20 2
5.6%
21 2
5.6%
24 3
8.3%
25 1
 
2.8%
ValueCountFrequency (%)
722 1
2.8%
720 1
2.8%
330 1
2.8%
100 1
2.8%
83 1
2.8%
71 1
2.8%
69 1
2.8%
68 1
2.8%
65 1
2.8%
40 1
2.8%

시설인가일
Date

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum1955-10-15 00:00:00
Maximum2023-03-01 00:00:00
2023-12-11T01:36:38.809274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:38.902494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

Interactions

2023-12-11T01:36:35.977702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.445812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.703150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:36.054523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.521082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.791223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:36.139479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.611959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:35.893605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:36:38.970167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종별시설명소재지주소전화번호종사자수정원현원시설인가일
시설종별1.0001.0000.9680.9830.7760.9070.8711.000
시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지주소0.9681.0001.0000.9880.8580.7630.0000.958
전화번호0.9831.0000.9881.0000.7810.8200.0000.986
종사자수0.7761.0000.8580.7811.0000.9170.8040.953
정원0.9071.0000.7630.8200.9171.0000.8040.813
현원0.8711.0000.0000.0000.8040.8041.0000.000
시설인가일1.0001.0000.9580.9860.9530.8130.0001.000
2023-12-11T01:36:39.057751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종사자수정원현원시설종별
종사자수1.0000.5370.4750.412
정원0.5371.0000.9120.717
현원0.4750.9121.0000.636
시설종별0.4120.7170.6361.000

Missing values

2023-12-11T01:36:36.277677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:36:36.390864image/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.
2023-12-11T01:36:36.476295image/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

시설종별시설명소재지주소전화번호종사자수정원현원시설인가일
0사회복지관서구종합사회복지관부산광역시 서구 망양로 193번길 104051-253-19222416241993-01-19
1사회복지관기독교종합사회복지관부산광역시 서구 까치고개로229번길40051-257-94041715171986-12-18
2한부모가족복지시설다비다모자원부산광역시 서구 꽃마을로 24051-244-2508545371958-07-02
3한부모가족복지시설은애모자원부산광역시 서구 장군산로 103번길 6051-241-1133430211957-08-29
4한부모가족복지시설안나모자원부산광역시 서구 꽃마을로163번길 40051-241-2421430211959-05-04
5미혼모자가족복지시설마리아모성원부산광역시 서구 천해남로 7051-253-7543915141985-04-13
6성매매피해자지원시설신나는디딤터부산광역시 서구 구덕로185번길 47051-253-02701025151997-01-31
7성매매피해자지원시설웨슬리마을 해뜨는집부산광역시 서구 구덕로 336-7051-257-905681582001-12-26
8성매매피해자지원시설(사)여성인권지원센터 살림 부설 자활지원센터 숲부산광역시 서구 천마로 192, 501호051-256-82976<NA><NA>2010-12-30
9성매매피해자상담소(사)여성인권지원센터 살림 부설 살림상담소부산광역시 서구 천마로 192, 502호051-257-82978<NA><NA>2002-11-21
시설종별시설명소재지주소전화번호종사자수정원현원시설인가일
26장애인복지시설나라단기거주시설부산광역시 서구 천해로 7번길 55-10051-715-151141022019-01-10
27장애인복지시설서구장애인복지관 주간보호센터부산광역시 서구 보수대로154번길 36051-242-3930320152018-08-31
28장애인복지시설서구수어통역센터부산광역시 서구 대청로6번길 41-1051-244-97705<NA><NA>2009-02-05
29노인의료복지시설안나노인건강센터부산광역시 서구 꽃마을로 163번길 94-16051-245-00354580712005-03-21
30노인의료복지시설실버웰요양센터부산광역시 서구 시약로 35051-242-805037150692013-01-01
31노인의료복지시설인창서구그린빌노인요양원부산광역시 서구 대영로 73번길 111051-255-09043049272012-03-23
32노인일자리지원기관부산서구시니어클럽부산광역시 서구 구덕로 345번길 24051-244-67008<NA><NA>2002-07-01
33지역자활센터서구지역자활센터부산광역시 서구 대영로45번길 102, 3층051-253-1957986682001-07-01
34노인복지관부민노인복지관부산광역시 서구 부용로 30051-243-3531147207201998-07-31
35노인복지관서구노인복지관부산광역시 서구 장군산로 46번길 21051-244-3541157227222010-02-17