Overview

Dataset statistics

Number of variables12
Number of observations442
Missing cells180
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.6 KiB
Average record size in memory96.3 B

Variable types

Unsupported6
Categorical2
Text4

Dataset

Description공공데이터한부모가족복지시설현황
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202041

Alerts

Unnamed: 1 is highly overall correlated with Unnamed: 11High correlation
Unnamed: 11 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 11 is highly imbalanced (73.4%)Imbalance
Unnamed: 3 has 17 (3.8%) missing valuesMissing
Unnamed: 4 has 21 (4.8%) missing valuesMissing
Unnamed: 5 has 17 (3.8%) missing valuesMissing
Unnamed: 6 has 28 (6.3%) missing valuesMissing
Unnamed: 7 has 29 (6.6%) missing valuesMissing
Unnamed: 8 has 24 (5.4%) missing valuesMissing
Unnamed: 9 has 25 (5.7%) missing valuesMissing
Unnamed: 10 has 16 (3.6%) missing valuesMissing
전라북도 사회복지(생활)시설 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:22:24.943393
Analysis finished2024-03-14 00:22:25.903885
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 사회복지(생활)시설 현황
Unsupported

REJECTED  UNSUPPORTED 

Missing2
Missing (%)0.5%
Memory size3.6 KiB

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
노인요양시설
162 
노인요양공동생활가정
66 
장애인거주시설
51 
아동공동생활가정
35 
사회복귀시설
19 
Other values (40)
109 

Length

Max length10
Median length9
Mean length7.158371
Min length3

Unique

Unique26 ?
Unique (%)5.9%

Sample

1st row<NA>
2nd row시설구분
3rd row<NA>
4th row전라북도
5th row전주시

Common Values

ValueCountFrequency (%)
노인요양시설 162
36.7%
노인요양공동생활가정 66
14.9%
장애인거주시설 51
 
11.5%
아동공동생활가정 35
 
7.9%
사회복귀시설 19
 
4.3%
장애인 공동생활가정 17
 
3.8%
아동양육시설 14
 
3.2%
노인양로시설 11
 
2.5%
아동 공동생활시설 10
 
2.3%
한부모가족복지시설 7
 
1.6%
Other values (35) 50
 
11.3%

Length

2024-03-14T09:22:25.958421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인요양시설 162
34.0%
노인요양공동생활가정 66
13.8%
장애인거주시설 51
 
10.7%
아동공동생활가정 35
 
7.3%
사회복귀시설 19
 
4.0%
장애인 19
 
4.0%
공동생활가정 17
 
3.6%
아동양육시설 14
 
2.9%
노인양로시설 11
 
2.3%
아동 10
 
2.1%
Other values (37) 73
15.3%

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.6 KiB

Unnamed: 3
Text

MISSING 

Distinct396
Distinct (%)93.2%
Missing17
Missing (%)3.8%
Memory size3.6 KiB
2024-03-14T09:22:26.184759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length10
Mean length9.1247059
Min length5

Characters and Unicode

Total characters3878
Distinct characters21
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)87.8%

Sample

1st row설치신고일
2nd row00.12.08
3rd row11.07.04
4th row15.09.11
5th row02.11.21
ValueCountFrequency (%)
2006.11.10 5
 
1.2%
2009.12.29 3
 
0.7%
2010.03.01 3
 
0.7%
07.03.09 3
 
0.7%
11.04.28 2
 
0.5%
2008.03.10 2
 
0.5%
08.07.31 2
 
0.5%
2006.06.30 2
 
0.5%
2009.10.01 2
 
0.5%
2010.03.16 2
 
0.5%
Other values (386) 400
93.9%
2024-03-14T09:22:26.563028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1006
25.9%
. 854
22.0%
1 599
15.4%
2 501
12.9%
6 154
 
4.0%
3 149
 
3.8%
8 144
 
3.7%
9 126
 
3.2%
7 118
 
3.0%
5 112
 
2.9%
Other values (11) 115
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3004
77.5%
Other Punctuation 856
 
22.1%
Space Separator 10
 
0.3%
Other Letter 5
 
0.1%
Control 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1006
33.5%
1 599
19.9%
2 501
16.7%
6 154
 
5.1%
3 149
 
5.0%
8 144
 
4.8%
9 126
 
4.2%
7 118
 
3.9%
5 112
 
3.7%
4 95
 
3.2%
Other Letter
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 854
99.8%
, 2
 
0.2%
Space Separator
ValueCountFrequency (%)
10
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3873
99.9%
Hangul 5
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1006
26.0%
. 854
22.1%
1 599
15.5%
2 501
12.9%
6 154
 
4.0%
3 149
 
3.8%
8 144
 
3.7%
9 126
 
3.3%
7 118
 
3.0%
5 112
 
2.9%
Other values (6) 110
 
2.8%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3873
99.9%
Hangul 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1006
26.0%
. 854
22.1%
1 599
15.5%
2 501
12.9%
6 154
 
4.0%
3 149
 
3.8%
8 144
 
3.7%
9 126
 
3.3%
7 118
 
3.0%
5 112
 
2.9%
Other values (6) 110
 
2.8%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Unnamed: 4
Text

MISSING 

Distinct396
Distinct (%)94.1%
Missing21
Missing (%)4.8%
Memory size3.6 KiB
2024-03-14T09:22:26.860789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.064133
Min length2

Characters and Unicode

Total characters1290
Distinct characters176
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

Unique372 ?
Unique (%)88.4%

Sample

1st row시설장
2nd row박헌수
3rd row최유영
4th row김미경
5th row김성은
ValueCountFrequency (%)
정란희 3
 
0.7%
추교인 2
 
0.5%
김혜란 2
 
0.5%
김인숙 2
 
0.5%
강옥선 2
 
0.5%
김혜자 2
 
0.5%
김은희 2
 
0.5%
김선자 2
 
0.5%
정영순 2
 
0.5%
박용민 2
 
0.5%
Other values (391) 405
95.1%
2024-03-14T09:22:27.279223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 92
 
7.1%
이 63
 
4.9%
정 51
 
4.0%
영 47
 
3.6%
희 37
 
2.9%
숙 32
 
2.5%
박 31
 
2.4%
순 29
 
2.2%
최 29
 
2.2%
성 26
 
2.0%
Other values (166) 853
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1266
98.1%
Space Separator 24
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 92
 
7.3%
이 63
 
5.0%
정 51
 
4.0%
영 47
 
3.7%
희 37
 
2.9%
숙 32
 
2.5%
박 31
 
2.4%
순 29
 
2.3%
최 29
 
2.3%
성 26
 
2.1%
Other values (165) 829
65.5%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1266
98.1%
Common 24
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 92
 
7.3%
이 63
 
5.0%
정 51
 
4.0%
영 47
 
3.7%
희 37
 
2.9%
숙 32
 
2.5%
박 31
 
2.4%
순 29
 
2.3%
최 29
 
2.3%
성 26
 
2.1%
Other values (165) 829
65.5%
Common
ValueCountFrequency (%)
24
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1266
98.1%
ASCII 24
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 92
 
7.3%
이 63
 
5.0%
정 51
 
4.0%
영 47
 
3.7%
희 37
 
2.9%
숙 32
 
2.5%
박 31
 
2.4%
순 29
 
2.3%
최 29
 
2.3%
성 26
 
2.1%
Other values (165) 829
65.5%
ASCII
ValueCountFrequency (%)
24
100.0%

Unnamed: 5
Text

MISSING 

Distinct411
Distinct (%)96.7%
Missing17
Missing (%)3.8%
Memory size3.6 KiB
2024-03-14T09:22:27.576286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length15.830588
Min length3

Characters and Unicode

Total characters6728
Distinct characters275
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique397 ?
Unique (%)93.4%

Sample

1st row주 소
2nd row전주시 완산구 물왕멀2길 20-29
3rd row전주시 완산구 물왕멀2길 25
4th row전주시 완산구 물왕멀2길 20-17
5th row전주시 덕진구 아중7길 9-5
ValueCountFrequency (%)
익산시 82
 
5.7%
완산구 60
 
4.1%
전주시 57
 
3.9%
덕진구 35
 
2.4%
군산시 29
 
2.0%
전북 21
 
1.4%
완주군 18
 
1.2%
김제시 11
 
0.8%
정읍시 10
 
0.7%
남원시 9
 
0.6%
Other values (834) 1119
77.1%
2024-03-14T09:22:27.972198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1063
 
15.8%
1 390
 
5.8%
산 267
 
4.0%
2 246
 
3.7%
길 231
 
3.4%
시 202
 
3.0%
로 186
 
2.8%
3 183
 
2.7%
- 180
 
2.7%
면 175
 
2.6%
Other values (265) 3605
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3565
53.0%
Decimal Number 1664
24.7%
Space Separator 1065
 
15.8%
Dash Punctuation 180
 
2.7%
Close Punctuation 95
 
1.4%
Open Punctuation 95
 
1.4%
Other Punctuation 56
 
0.8%
Control 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 267
 
7.5%
길 231
 
6.5%
시 202
 
5.7%
로 186
 
5.2%
면 175
 
4.9%
동 126
 
3.5%
구 119
 
3.3%
익 92
 
2.6%
주 92
 
2.6%
군 86
 
2.4%
Other values (241) 1989
55.8%
Decimal Number
ValueCountFrequency (%)
1 390
23.4%
2 246
14.8%
3 183
11.0%
4 146
 
8.8%
0 135
 
8.1%
5 128
 
7.7%
7 119
 
7.2%
6 117
 
7.0%
8 102
 
6.1%
9 98
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 27
48.2%
/ 13
23.2%
@ 11
19.6%
. 5
 
8.9%
Space Separator
ValueCountFrequency (%)
1063
99.8%
  2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 180
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3565
53.0%
Common 3160
47.0%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 267
 
7.5%
길 231
 
6.5%
시 202
 
5.7%
로 186
 
5.2%
면 175
 
4.9%
동 126
 
3.5%
구 119
 
3.3%
익 92
 
2.6%
주 92
 
2.6%
군 86
 
2.4%
Other values (241) 1989
55.8%
Common
ValueCountFrequency (%)
1063
33.6%
1 390
 
12.3%
2 246
 
7.8%
3 183
 
5.8%
- 180
 
5.7%
4 146
 
4.6%
0 135
 
4.3%
5 128
 
4.1%
7 119
 
3.8%
6 117
 
3.7%
Other values (11) 453
14.3%
Latin
ValueCountFrequency (%)
a 1
33.3%
A 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3565
53.0%
ASCII 3161
47.0%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1063
33.6%
1 390
 
12.3%
2 246
 
7.8%
3 183
 
5.8%
- 180
 
5.7%
4 146
 
4.6%
0 135
 
4.3%
5 128
 
4.0%
7 119
 
3.8%
6 117
 
3.7%
Other values (13) 454
14.4%
Hangul
ValueCountFrequency (%)
산 267
 
7.5%
길 231
 
6.5%
시 202
 
5.7%
로 186
 
5.2%
면 175
 
4.9%
동 126
 
3.5%
구 119
 
3.3%
익 92
 
2.6%
주 92
 
2.6%
군 86
 
2.4%
Other values (241) 1989
55.8%
None
ValueCountFrequency (%)
  2
100.0%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)6.3%
Memory size3.6 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)6.6%
Memory size3.6 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)5.4%
Memory size3.6 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25
Missing (%)5.7%
Memory size3.6 KiB

Unnamed: 10
Text

MISSING 

Distinct151
Distinct (%)35.4%
Missing16
Missing (%)3.6%
Memory size3.6 KiB
2024-03-14T09:22:28.133644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length5.2300469
Min length2

Characters and Unicode

Total characters2228
Distinct characters192
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)26.3%

Sample

1st row2016년 12월말
2nd row운영주체(법인명)
3rd row마음건강복지재단
4th row마음건강복지재단
5th row마음건강복지재단
ValueCountFrequency (%)
개인 193
40.0%
사회복지법인 35
 
7.3%
삼동회 9
 
1.9%
사복)중도원 6
 
1.2%
한기장복지재단 6
 
1.2%
한 5
 
1.0%
울 5
 
1.0%
안 5
 
1.0%
원광효도마을 5
 
1.0%
전주가톨릭사회복지회 4
 
0.8%
Other values (158) 209
43.4%
2024-03-14T09:22:28.396681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 263
 
11.8%
개 198
 
8.9%
복 174
 
7.8%
지 133
 
6.0%
사 121
 
5.4%
111
 
5.0%
회 102
 
4.6%
재 77
 
3.5%
단 77
 
3.5%
) 74
 
3.3%
Other values (182) 898
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2013
90.4%
Space Separator 111
 
5.0%
Close Punctuation 74
 
3.3%
Open Punctuation 19
 
0.9%
Decimal Number 6
 
0.3%
Uppercase Letter 4
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 263
 
13.1%
개 198
 
9.8%
복 174
 
8.6%
지 133
 
6.6%
사 121
 
6.0%
회 102
 
5.1%
재 77
 
3.8%
단 77
 
3.8%
원 60
 
3.0%
법 52
 
2.6%
Other values (170) 756
37.6%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 2
33.3%
6 1
16.7%
0 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
Y 1
25.0%
W 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2013
90.4%
Common 211
 
9.5%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 263
 
13.1%
개 198
 
9.8%
복 174
 
8.6%
지 133
 
6.6%
사 121
 
6.0%
회 102
 
5.1%
재 77
 
3.8%
단 77
 
3.8%
원 60
 
3.0%
법 52
 
2.6%
Other values (170) 756
37.6%
Common
ValueCountFrequency (%)
111
52.6%
) 74
35.1%
( 19
 
9.0%
1 2
 
0.9%
2 2
 
0.9%
6 1
 
0.5%
0 1
 
0.5%
, 1
 
0.5%
Latin
ValueCountFrequency (%)
C 1
25.0%
Y 1
25.0%
W 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2013
90.4%
ASCII 215
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 263
 
13.1%
개 198
 
9.8%
복 174
 
8.6%
지 133
 
6.6%
사 121
 
6.0%
회 102
 
5.1%
재 77
 
3.8%
단 77
 
3.8%
원 60
 
3.0%
법 52
 
2.6%
Other values (170) 756
37.6%
ASCII
ValueCountFrequency (%)
111
51.6%
) 74
34.4%
( 19
 
8.8%
1 2
 
0.9%
2 2
 
0.9%
C 1
 
0.5%
Y 1
 
0.5%
W 1
 
0.5%
A 1
 
0.5%
6 1
 
0.5%
Other values (2) 2
 
0.9%

Unnamed: 11
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
373 
지적
 
24
종합시설
 
10
중증
 
8
지적
 
5
Other values (14)
 
22

Length

Max length11
Median length4
Mean length3.8552036
Min length2

Unique

Unique10 ?
Unique (%)2.3%

Sample

1st row<NA>
2nd row비고
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 373
84.4%
지적 24
 
5.4%
종합시설 10
 
2.3%
중증 8
 
1.8%
지적 5
 
1.1%
지체 4
 
0.9%
<미지원시설> 3
 
0.7%
휴지 3
 
0.7%
중증실비 2
 
0.5%
영유아 1
 
0.2%
Other values (9) 9
 
2.0%

Length

2024-03-14T09:22:28.516842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 373
83.8%
지적 30
 
6.7%
종합시설 10
 
2.2%
중증 8
 
1.8%
지체 4
 
0.9%
미지원시설 3
 
0.7%
휴지 3
 
0.7%
지적(여 2
 
0.4%
중증실비 2
 
0.4%
비고 1
 
0.2%
Other values (9) 9
 
2.0%

Correlations

2024-03-14T09:22:28.598163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 11
Unnamed: 11.0000.950
Unnamed: 110.9501.000
2024-03-14T09:22:28.698587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 11
Unnamed: 11.0000.744
Unnamed: 110.7441.000
2024-03-14T09:22:28.795490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 11
Unnamed: 11.0000.744
Unnamed: 110.7441.000

Missing values

2024-03-14T09:22:25.337096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:22:25.465175image/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.
2024-03-14T09:22:25.799256image/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

전라북도 사회복지(생활)시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0NaN<NA>NaN<NA><NA><NA>NaNNaNNaNNaN2016년 12월말<NA>
1연번시설구분시 설 일 반 현 황<NA><NA><NA>종사자NaN생활인NaN운영주체(법인명)비고
2NaN<NA>시설명설치신고일시설장주 소정원현원정원현원<NA><NA>
3총계전라북도424<NA><NA><NA>612159191382111223<NA><NA>
4소계전주시100<NA><NA><NA>NaNNaNNaNNaN<NA><NA>
51사회복귀시설마음건강복지관00.12.08박헌수전주시 완산구 물왕멀2길 20-2910102626마음건강복지재단종합시설
62사회복귀시설마음건강회복홈11.07.04최유영전주시 완산구 물왕멀2길 251144마음건강복지재단<NA>
73사회복귀시설마음건강힐링홈15.09.11<NA>전주시 완산구 물왕멀2길 20-17NaNNaN44마음건강복지재단<미지원시설>
84사회복귀시설아름다운세상02.11.21김미경전주시 덕진구 아중7길 9-5772021인산의료재단종합시설
95사회복귀시설아름다운집11.05.26김성은전주시 덕진구 인교9길 11 (401호)2243인산의료재단<NA>
전라북도 사회복지(생활)시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
432소계부안군9<NA><NA><NA>NaNNaNNaNNaN<NA><NA>
4331노인요양시설송산효도마을2005.09.08하정만주산면 화봉길 8-3049499079한 울 안<NA>
4342노인요양시설은총의 집2006.09.29주혜숙상서면 부안로 1539-2118182324개인<NA>
4353노인요양시설해성요양원2016.02.15.이병협해안면 월륜길 515151819개인<NA>
4364노인요양시설로댐실버케어2011.07.29유희성하서면 고인돌로 34730304041개인<NA>
4375노인요양시설부안군노인요양원2010.03.11송용기부안읍 봉두길 52772015사복)한국장로교복지재단<NA>
4386노인요양시설산타요양원2015.02.13김성일부안읍 매창로 287-43NaNNaNNaNNaN개인<NA>
4397노인요양공동생활가정부안군재가노인지원센터(입소)2011.05.18이주재부안읍 봉두길 528899사복)한국장로교복지재단<NA>
4408노인요양공동생활가정섬김요양원2014.12.22박난주동진면 동진로 1718899개인<NA>
4419장애인거주시설둥근마음보금자리16.12.30하정만부안군 주산면 화봉길 8-186600한울안신규