Overview

Dataset statistics

Number of variables7
Number of observations67
Missing cells82
Missing cells (%)17.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory61.0 B

Variable types

Numeric3
Text4

Dataset

Description부산광역시북구_노인복지시설현황_20230814
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026030

Alerts

정원 is highly overall correlated with 현원High correlation
현원 is highly overall correlated with 정원High correlation
정원 has 40 (59.7%) missing valuesMissing
현원 has 42 (62.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:12:46.877236
Analysis finished2023-12-10 16:12:48.838578
Duration1.96 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-11T01:12:48.928833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.3
Q117.5
median34
Q350.5
95-th percentile63.7
Maximum67
Range66
Interquartile range (IQR)33

Descriptive statistics

Standard deviation19.485037
Coefficient of variation (CV)0.57308932
Kurtosis-1.2
Mean34
Median Absolute Deviation (MAD)17
Skewness0
Sum2278
Variance379.66667
MonotonicityStrictly increasing
2023-12-11T01:12:49.120514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
44 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
45 1
 
1.5%
43 1
 
1.5%
2 1
 
1.5%
Other values (57) 57
85.1%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%

시설명
Text

Distinct66
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-11T01:12:49.424899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length9.8955224
Min length5

Characters and Unicode

Total characters663
Distinct characters136
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

Unique65 ?
Unique (%)97.0%

Sample

1st row정화양로원
2nd row정화노인요양원
3rd row무지개언덕노인전문요양센터
4th row청록만덕실버센터
5th row동진노인복지센터
ValueCountFrequency (%)
재가복지센터 3
 
3.7%
신기의료기 3
 
3.7%
편안한노인공동요양원 2
 
2.4%
주간보호센터 2
 
2.4%
재활주간보호센터 2
 
2.4%
나눔누리통합재가노인복지센터 1
 
1.2%
행운재가복지센터 1
 
1.2%
그루터기노인주간보호센터 1
 
1.2%
위드 1
 
1.2%
다솜재가복지센터 1
 
1.2%
Other values (65) 65
79.3%
2023-12-11T01:12:49.943622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 54
 
8.1%
센 51
 
7.7%
가 33
 
5.0%
재 33
 
5.0%
지 33
 
5.0%
복 25
 
3.8%
인 23
 
3.5%
노 22
 
3.3%
보 18
 
2.7%
주 17
 
2.6%
Other values (126) 354
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
97.1%
Space Separator 15
 
2.3%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 54
 
8.4%
센 51
 
7.9%
가 33
 
5.1%
재 33
 
5.1%
지 33
 
5.1%
복 25
 
3.9%
인 23
 
3.6%
노 22
 
3.4%
보 18
 
2.8%
주 17
 
2.6%
Other values (123) 335
52.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
97.1%
Common 19
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 54
 
8.4%
센 51
 
7.9%
가 33
 
5.1%
재 33
 
5.1%
지 33
 
5.1%
복 25
 
3.9%
인 23
 
3.6%
노 22
 
3.4%
보 18
 
2.8%
주 17
 
2.6%
Other values (123) 335
52.0%
Common
ValueCountFrequency (%)
15
78.9%
) 2
 
10.5%
( 2
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
97.1%
ASCII 19
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 54
 
8.4%
센 51
 
7.9%
가 33
 
5.1%
재 33
 
5.1%
지 33
 
5.1%
복 25
 
3.9%
인 23
 
3.6%
노 22
 
3.4%
보 18
 
2.8%
주 17
 
2.6%
Other values (123) 335
52.0%
ASCII
ValueCountFrequency (%)
15
78.9%
) 2
 
10.5%
( 2
 
10.5%

소재지
Text

Distinct57
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-11T01:12:50.326311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length29.522388
Min length21

Characters and Unicode

Total characters1978
Distinct characters99
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

Unique50 ?
Unique (%)74.6%

Sample

1st row부산광역시 북구 양달로 55 (화명동)
2nd row부산광역시 북구 양달로 55 (화명동)
3rd row부산광역시 북구 시랑로114번길 45 (구포동)
4th row부산광역시 북구 중리로 32 (만덕동)
5th row부산광역시 북구 덕천로 101-7 (덕천동)
ValueCountFrequency (%)
부산광역시 67
 
17.0%
북구 67
 
17.0%
구포동 18
 
4.6%
화명동 13
 
3.3%
만덕동 13
 
3.3%
덕천동 12
 
3.0%
금곡동 9
 
2.3%
2층 8
 
2.0%
1층 7
 
1.8%
백양대로 7
 
1.8%
Other values (115) 173
43.9%
2023-12-11T01:12:50.901824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
327
 
16.5%
1 91
 
4.6%
구 87
 
4.4%
동 74
 
3.7%
시 74
 
3.7%
산 69
 
3.5%
북 68
 
3.4%
부 67
 
3.4%
( 67
 
3.4%
) 67
 
3.4%
Other values (89) 987
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1126
56.9%
Decimal Number 328
 
16.6%
Space Separator 327
 
16.5%
Open Punctuation 67
 
3.4%
Close Punctuation 67
 
3.4%
Other Punctuation 52
 
2.6%
Dash Punctuation 8
 
0.4%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 87
 
7.7%
동 74
 
6.6%
시 74
 
6.6%
산 69
 
6.1%
북 68
 
6.0%
부 67
 
6.0%
광 67
 
6.0%
역 67
 
6.0%
로 65
 
5.8%
덕 43
 
3.8%
Other values (72) 445
39.5%
Decimal Number
ValueCountFrequency (%)
1 91
27.7%
2 46
14.0%
3 37
11.3%
5 31
 
9.5%
4 30
 
9.1%
0 26
 
7.9%
6 22
 
6.7%
7 20
 
6.1%
8 16
 
4.9%
9 9
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
H 1
33.3%
Space Separator
ValueCountFrequency (%)
327
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1126
56.9%
Common 849
42.9%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 87
 
7.7%
동 74
 
6.6%
시 74
 
6.6%
산 69
 
6.1%
북 68
 
6.0%
부 67
 
6.0%
광 67
 
6.0%
역 67
 
6.0%
로 65
 
5.8%
덕 43
 
3.8%
Other values (72) 445
39.5%
Common
ValueCountFrequency (%)
327
38.5%
1 91
 
10.7%
( 67
 
7.9%
) 67
 
7.9%
, 52
 
6.1%
2 46
 
5.4%
3 37
 
4.4%
5 31
 
3.7%
4 30
 
3.5%
0 26
 
3.1%
Other values (5) 75
 
8.8%
Latin
ValueCountFrequency (%)
B 2
66.7%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1126
56.9%
ASCII 852
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
327
38.4%
1 91
 
10.7%
( 67
 
7.9%
) 67
 
7.9%
, 52
 
6.1%
2 46
 
5.4%
3 37
 
4.3%
5 31
 
3.6%
4 30
 
3.5%
0 26
 
3.1%
Other values (7) 78
 
9.2%
Hangul
ValueCountFrequency (%)
구 87
 
7.7%
동 74
 
6.6%
시 74
 
6.6%
산 69
 
6.1%
북 68
 
6.0%
부 67
 
6.0%
광 67
 
6.0%
역 67
 
6.0%
로 65
 
5.8%
덕 43
 
3.8%
Other values (72) 445
39.5%

시설장
Text

Distinct59
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-11T01:12:51.244517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9850746
Min length2

Characters and Unicode

Total characters200
Distinct characters86
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

Unique52 ?
Unique (%)77.6%

Sample

1st row이혜숙
2nd row이세창
3rd row유금숙
4th row최소남
5th row김심선
ValueCountFrequency (%)
진영규 3
 
4.5%
최소남 2
 
3.0%
이세창 2
 
3.0%
설미자 2
 
3.0%
김혜진 2
 
3.0%
공윤석 2
 
3.0%
유금숙 2
 
3.0%
강선영 1
 
1.5%
김말선 1
 
1.5%
김소연 1
 
1.5%
Other values (49) 49
73.1%
2023-12-11T01:12:52.038993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 16
 
8.0%
정 10
 
5.0%
진 9
 
4.5%
영 7
 
3.5%
숙 6
 
3.0%
윤 5
 
2.5%
이 5
 
2.5%
주 5
 
2.5%
혜 5
 
2.5%
원 4
 
2.0%
Other values (76) 128
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 16
 
8.0%
정 10
 
5.0%
진 9
 
4.5%
영 7
 
3.5%
숙 6
 
3.0%
윤 5
 
2.5%
이 5
 
2.5%
주 5
 
2.5%
혜 5
 
2.5%
원 4
 
2.0%
Other values (76) 128
64.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 16
 
8.0%
정 10
 
5.0%
진 9
 
4.5%
영 7
 
3.5%
숙 6
 
3.0%
윤 5
 
2.5%
이 5
 
2.5%
주 5
 
2.5%
혜 5
 
2.5%
원 4
 
2.0%
Other values (76) 128
64.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 16
 
8.0%
정 10
 
5.0%
진 9
 
4.5%
영 7
 
3.5%
숙 6
 
3.0%
윤 5
 
2.5%
이 5
 
2.5%
주 5
 
2.5%
혜 5
 
2.5%
원 4
 
2.0%
Other values (76) 128
64.0%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)77.8%
Missing40
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean53.518519
Minimum9
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-11T01:12:52.394460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile17.4
Q137.5
median49
Q372
95-th percentile81.4
Maximum113
Range104
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation24.412119
Coefficient of variation (CV)0.4561434
Kurtosis-0.15640534
Mean53.518519
Median Absolute Deviation (MAD)19
Skewness0.25824362
Sum1445
Variance595.95157
MonotonicityNot monotonic
2023-12-11T01:12:52.662544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
80 3
 
4.5%
68 2
 
3.0%
60 2
 
3.0%
42 2
 
3.0%
43 2
 
3.0%
47 1
 
1.5%
39 1
 
1.5%
82 1
 
1.5%
59 1
 
1.5%
77 1
 
1.5%
Other values (11) 11
 
16.4%
(Missing) 40
59.7%
ValueCountFrequency (%)
9 1
1.5%
15 1
1.5%
23 1
1.5%
28 1
1.5%
29 1
1.5%
30 1
1.5%
36 1
1.5%
39 1
1.5%
42 2
3.0%
43 2
3.0%
ValueCountFrequency (%)
113 1
 
1.5%
82 1
 
1.5%
80 3
4.5%
77 1
 
1.5%
76 1
 
1.5%
68 2
3.0%
67 1
 
1.5%
60 2
3.0%
59 1
 
1.5%
49 1
 
1.5%

현원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)84.0%
Missing42
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean53.76
Minimum12
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-11T01:12:52.822846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile23.6
Q139
median49
Q374
95-th percentile81.6
Maximum111
Range99
Interquartile range (IQR)35

Descriptive statistics

Standard deviation23.631335
Coefficient of variation (CV)0.43957097
Kurtosis-0.17012718
Mean53.76
Median Absolute Deviation (MAD)19
Skewness0.41597585
Sum1344
Variance558.44
MonotonicityNot monotonic
2023-12-11T01:12:52.987722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
80 3
 
4.5%
49 2
 
3.0%
42 2
 
3.0%
30 1
 
1.5%
43 1
 
1.5%
39 1
 
1.5%
82 1
 
1.5%
59 1
 
1.5%
77 1
 
1.5%
67 1
 
1.5%
Other values (11) 11
 
16.4%
(Missing) 42
62.7%
ValueCountFrequency (%)
12 1
1.5%
23 1
1.5%
26 1
1.5%
29 1
1.5%
30 1
1.5%
32 1
1.5%
39 1
1.5%
42 2
3.0%
43 1
1.5%
47 1
1.5%
ValueCountFrequency (%)
111 1
 
1.5%
82 1
 
1.5%
80 3
4.5%
77 1
 
1.5%
74 1
 
1.5%
70 1
 
1.5%
67 1
 
1.5%
59 1
 
1.5%
53 1
 
1.5%
49 2
3.0%

연락처
Text

Distinct61
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-11T01:12:53.300302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.044776
Min length12

Characters and Unicode

Total characters807
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

Unique55 ?
Unique (%)82.1%

Sample

1st row051-332-3996
2nd row051-332-6810
3rd row051-338-5788
4th row051-337-0660
5th row051-336-5300
ValueCountFrequency (%)
051-343-5685 2
 
3.0%
051-332-6810 2
 
3.0%
051-337-1273 2
 
3.0%
051-334-5711 2
 
3.0%
051-711-3859 2
 
3.0%
051-337-0660 2
 
3.0%
051-710-7581 1
 
1.5%
051-343-0606 1
 
1.5%
070-4142-1177 1
 
1.5%
051-338-9713 1
 
1.5%
Other values (51) 51
76.1%
2023-12-11T01:12:53.788097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 134
16.6%
3 121
15.0%
0 119
14.7%
1 116
14.4%
5 102
12.6%
8 50
 
6.2%
6 42
 
5.2%
7 38
 
4.7%
2 30
 
3.7%
9 30
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 673
83.4%
Dash Punctuation 134
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 121
18.0%
0 119
17.7%
1 116
17.2%
5 102
15.2%
8 50
7.4%
6 42
 
6.2%
7 38
 
5.6%
2 30
 
4.5%
9 30
 
4.5%
4 25
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 807
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 134
16.6%
3 121
15.0%
0 119
14.7%
1 116
14.4%
5 102
12.6%
8 50
 
6.2%
6 42
 
5.2%
7 38
 
4.7%
2 30
 
3.7%
9 30
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 807
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 134
16.6%
3 121
15.0%
0 119
14.7%
1 116
14.4%
5 102
12.6%
8 50
 
6.2%
6 42
 
5.2%
7 38
 
4.7%
2 30
 
3.7%
9 30
 
3.7%

Interactions

2023-12-11T01:12:48.137957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.578039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.879533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.245732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.692168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.961806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.358189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.778543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.044753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:12:53.929399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명소재지시설장정원현원연락처
연번1.0000.9420.7870.7900.0000.0000.855
시설명0.9421.0000.9891.0001.0001.0000.996
소재지0.7870.9891.0000.9960.0000.7760.999
시설장0.7901.0000.9961.0000.0000.7230.997
정원0.0001.0000.0000.0001.0000.9970.000
현원0.0001.0000.7760.7230.9971.0000.723
연락처0.8550.9960.9990.9970.0000.7231.000
2023-12-11T01:12:54.080984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번정원현원
연번1.0000.0090.006
정원0.0091.0000.995
현원0.0060.9951.000

Missing values

2023-12-11T01:12:48.503973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:12:48.659929image/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.
2023-12-11T01:12:48.780308image/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

연번시설명소재지시설장정원현원연락처
01정화양로원부산광역시 북구 양달로 55 (화명동)이혜숙6049051-332-3996
12정화노인요양원부산광역시 북구 양달로 55 (화명동)이세창113111051-332-6810
23무지개언덕노인전문요양센터부산광역시 북구 시랑로114번길 45 (구포동)유금숙7674051-338-5788
34청록만덕실버센터부산광역시 북구 중리로 32 (만덕동)최소남4348051-337-0660
45동진노인복지센터부산광역시 북구 덕천로 101-7 (덕천동)김심선2826051-336-5300
56성문소규모요양시설부산광역시 북구 금곡대로550번길 22 (금곡동)민영란1512051-362-5508
67로뎀노인요양원부산광역시 북구 의성로 130 (덕천동)설미자6870051-338-9112
78만덕노인요양원부산광역시 북구 상학산복길 145 (만덕동)정소희2929051-337-1273
89연우 어르신의 집부산광역시 북구 덕천로381번길 17-27 (만덕동)김정두6053051-337-5200
910해뜨락요양원부산광역시 북구 덕천로381번길 14 (만덕동)전경욱3632051-341-1201
연번시설명소재지시설장정원현원연락처
5758구포시장 재가복지센터부산광역시 북구 백양대로 1155, 3층 (구포동)강만신<NA><NA>051-343-5690
5859황제재가노인복지센터부산광역시 북구 의성로121번길 79, 2층 (덕천동)신오동<NA><NA>051-337-4876
5960누가복지용구부산광역시 북구 금곡대로638번길 15, 1층 (금곡동)허병우<NA><NA>051-363-1153
6061미래재가방문요양센터부산광역시 북구 낙동북로 660, 2층 (구포동)황혜원<NA><NA>051-928-1004
6162만덕노인재가복지센터부산광역시 북구 상학산복길 145 (만덕동)문명순<NA><NA>051-337-1273
6263신기의료기 만덕점부산광역시 북구 상리로 79, 1층 (만덕동)박혜린<NA><NA>051-343-6300
6364화명은혜주간보호센터부산광역시 북구 금곡대로285번길 16, 7층 (화명동, 메인프라자)공윤석<NA><NA>051-711-3859
6465다솜재가복지센터부산광역시 북구 덕천로 136-1, 202호 (덕천동)김혜진<NA><NA>051-338-1005
6566편안한노인공동요양원부산광역시 북구 만덕대로127번길 4 (덕천동)진영규<NA><NA>051-334-5711
6667화명은혜공동생활가정부산광역시 북구 금곡대로285번길 16, 7층 (화명동, 메인프라자)공윤석<NA><NA>051-711-3859