Overview

Dataset statistics

Number of variables7
Number of observations180
Missing cells6
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory57.7 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description전국 사회복지협의회 현황 데이터로 시도 및 시군구 사회복지협의회 설치현황, 소재지, 대표연락처 등 기관 기본정보를 확인할 수 있습니다.
URLhttps://www.data.go.kr/data/15024886/fileData.do

Alerts

우편번호 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 우편번호High correlation
분류 is highly imbalanced (54.9%)Imbalance
팩스번호 has 5 (2.8%) missing valuesMissing
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:56:03.195933
Analysis finished2023-12-12 14:56:04.058920
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
시군구협의회
163 
광역
17 

Length

Max length6
Median length6
Mean length5.6222222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시군구협의회 163
90.6%
광역 17
 
9.4%

Length

2023-12-12T23:56:04.151658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:56:04.304960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군구협의회 163
90.6%
광역 17
 
9.4%

지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
경기도
27 
강원도
19 
서울특별시
17 
경상남도
17 
충청남도
15 
Other values (12)
85 

Length

Max length7
Median length5
Mean length4.0388889
Min length3

Unique

Unique3 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 27
15.0%
강원도 19
10.6%
서울특별시 17
9.4%
경상남도 17
9.4%
충청남도 15
8.3%
전라남도 15
8.3%
전라북도 15
8.3%
경상북도 12
6.7%
충청북도 11
6.1%
인천광역시 9
 
5.0%
Other values (7) 23
12.8%

Length

2023-12-12T23:56:04.446866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 27
15.0%
강원도 19
10.6%
서울특별시 17
9.4%
경상남도 17
9.4%
충청남도 15
8.3%
전라남도 15
8.3%
전라북도 15
8.3%
경상북도 12
6.7%
충청북도 11
6.1%
인천광역시 9
 
5.0%
Other values (7) 23
12.8%

협의회명
Text

Distinct179
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:56:04.683565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length10.533333
Min length10

Characters and Unicode

Total characters1896
Distinct characters129
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

Unique178 ?
Unique (%)98.9%

Sample

1st row구로구사회복지협의회
2nd row동대문구사회복지협의회
3rd row마포구사회복지협의회
4th row서대문구사회복지협의회
5th row영등포구사회복지협의회
ValueCountFrequency (%)
인천 8
 
4.1%
대구 4
 
2.1%
고성군사회복지협의회 2
 
1.0%
북구사회복지협의회 2
 
1.0%
동구사회복지협의회 2
 
1.0%
광주 2
 
1.0%
완주군사회복지협의회 1
 
0.5%
진안군사회복지협의회 1
 
0.5%
무주군사회복지협의회 1
 
0.5%
장수군사회복지협의회 1
 
0.5%
Other values (171) 171
87.7%
2023-12-12T23:56:05.131495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 359
18.9%
의 183
9.7%
사 180
9.5%
복 180
9.5%
지 180
9.5%
협 179
9.4%
시 76
 
4.0%
군 58
 
3.1%
구 51
 
2.7%
천 27
 
1.4%
Other values (119) 423
22.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1881
99.2%
Space Separator 15
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 359
19.1%
의 183
9.7%
사 180
9.6%
복 180
9.6%
지 180
9.6%
협 179
9.5%
시 76
 
4.0%
군 58
 
3.1%
구 51
 
2.7%
천 27
 
1.4%
Other values (118) 408
21.7%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1881
99.2%
Common 15
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 359
19.1%
의 183
9.7%
사 180
9.6%
복 180
9.6%
지 180
9.6%
협 179
9.5%
시 76
 
4.0%
군 58
 
3.1%
구 51
 
2.7%
천 27
 
1.4%
Other values (118) 408
21.7%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1881
99.2%
ASCII 15
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 359
19.1%
의 183
9.7%
사 180
9.6%
복 180
9.6%
지 180
9.6%
협 179
9.5%
시 76
 
4.0%
군 58
 
3.1%
구 51
 
2.7%
천 27
 
1.4%
Other values (118) 408
21.7%
ASCII
ValueCountFrequency (%)
15
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct179
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33217.256
Minimum1229
Maximum63300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T23:56:05.327300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1229
5-th percentile5280.35
Q121348.5
median32237.5
Q351117
95-th percentile58582.7
Maximum63300
Range62071
Interquartile range (IQR)29768.5

Descriptive statistics

Standard deviation17380.12
Coefficient of variation (CV)0.52322563
Kurtosis-1.1289531
Mean33217.256
Median Absolute Deviation (MAD)15324
Skewness0.0037747904
Sum5979106
Variance3.0206856 × 108
MonotonicityNot monotonic
2023-12-12T23:56:05.486817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51117 2
 
1.1%
8389 1
 
0.6%
54378 1
 
0.6%
55433 1
 
0.6%
55521 1
 
0.6%
55634 1
 
0.6%
55926 1
 
0.6%
56033 1
 
0.6%
56309 1
 
0.6%
56442 1
 
0.6%
Other values (169) 169
93.9%
ValueCountFrequency (%)
1229 1
0.6%
1330 1
0.6%
2076 1
0.6%
2597 1
0.6%
3058 1
0.6%
3456 1
0.6%
3711 1
0.6%
4103 1
0.6%
4147 1
0.6%
5340 1
0.6%
ValueCountFrequency (%)
63300 1
0.6%
62234 1
0.6%
61253 1
0.6%
61197 1
0.6%
59640 1
0.6%
59535 1
0.6%
59455 1
0.6%
59031 1
0.6%
58919 1
0.6%
58565 1
0.6%

주소
Text

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:56:05.782632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length24.916667
Min length11

Characters and Unicode

Total characters4485
Distinct characters314
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)100.0%

Sample

1st row구로구 디지털로272, 704호(구로동, 한신IT타워)
2nd row동대문구 천호대로65길 17, 5층(답십리동, 구립답십리청소년독서실)
3rd row마포구 신촌로26길 10(노고산동) 지하 1층
4th row서대문구 모래내로 15길 37, 남가좌1동주민센터 지하 1층
5th row영등포구 선유동1로 80, 영등포구사회복지협의회
ValueCountFrequency (%)
2층 32
 
3.5%
3층 14
 
1.5%
1층 14
 
1.5%
담당 12
 
1.3%
업무 12
 
1.3%
내 11
 
1.2%
중앙로 10
 
1.1%
4층 8
 
0.9%
업무담당자 5
 
0.6%
25 4
 
0.4%
Other values (719) 783
86.5%
2023-12-12T23:56:06.338760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
726
 
16.2%
1 176
 
3.9%
로 146
 
3.3%
2 133
 
3.0%
시 95
 
2.1%
지 88
 
2.0%
층 87
 
1.9%
길 83
 
1.9%
3 81
 
1.8%
동 80
 
1.8%
Other values (304) 2790
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2751
61.3%
Decimal Number 766
 
17.1%
Space Separator 726
 
16.2%
Other Punctuation 71
 
1.6%
Close Punctuation 62
 
1.4%
Open Punctuation 62
 
1.4%
Dash Punctuation 32
 
0.7%
Uppercase Letter 14
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 146
 
5.3%
시 95
 
3.5%
지 88
 
3.2%
층 87
 
3.2%
길 83
 
3.0%
동 80
 
2.9%
회 80
 
2.9%
구 78
 
2.8%
복 77
 
2.8%
군 69
 
2.5%
Other values (279) 1868
67.9%
Decimal Number
ValueCountFrequency (%)
1 176
23.0%
2 133
17.4%
3 81
10.6%
0 80
10.4%
4 68
 
8.9%
5 60
 
7.8%
6 49
 
6.4%
9 49
 
6.4%
8 35
 
4.6%
7 35
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
K 2
 
14.3%
G 1
 
7.1%
M 1
 
7.1%
S 1
 
7.1%
I 1
 
7.1%
T 1
 
7.1%
H 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 70
98.6%
. 1
 
1.4%
Space Separator
ValueCountFrequency (%)
726
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2749
61.3%
Common 1720
38.4%
Latin 14
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 146
 
5.3%
시 95
 
3.5%
지 88
 
3.2%
층 87
 
3.2%
길 83
 
3.0%
동 80
 
2.9%
회 80
 
2.9%
구 78
 
2.8%
복 77
 
2.8%
군 69
 
2.5%
Other values (278) 1866
67.9%
Common
ValueCountFrequency (%)
726
42.2%
1 176
 
10.2%
2 133
 
7.7%
3 81
 
4.7%
0 80
 
4.7%
, 70
 
4.1%
4 68
 
4.0%
) 62
 
3.6%
( 62
 
3.6%
5 60
 
3.5%
Other values (7) 202
 
11.7%
Latin
ValueCountFrequency (%)
B 6
42.9%
K 2
 
14.3%
G 1
 
7.1%
M 1
 
7.1%
S 1
 
7.1%
I 1
 
7.1%
T 1
 
7.1%
H 1
 
7.1%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2749
61.3%
ASCII 1734
38.7%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
726
41.9%
1 176
 
10.1%
2 133
 
7.7%
3 81
 
4.7%
0 80
 
4.6%
, 70
 
4.0%
4 68
 
3.9%
) 62
 
3.6%
( 62
 
3.6%
5 60
 
3.5%
Other values (15) 216
 
12.5%
Hangul
ValueCountFrequency (%)
로 146
 
5.3%
시 95
 
3.5%
지 88
 
3.2%
층 87
 
3.2%
길 83
 
3.0%
동 80
 
2.9%
회 80
 
2.9%
구 78
 
2.8%
복 77
 
2.8%
군 69
 
2.5%
Other values (278) 1866
67.9%
CJK
ValueCountFrequency (%)
內 2
100.0%

대표연락처
Text

Distinct178
Distinct (%)99.4%
Missing1
Missing (%)0.6%
Memory size1.5 KiB
2023-12-12T23:56:06.609767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.994413
Min length11

Characters and Unicode

Total characters2147
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)98.9%

Sample

1st row02-869-9555
2nd row02-2217-8837~9
3rd row02-3273-2251
4th row02-3144-0740
5th row02-2670-4196
ValueCountFrequency (%)
055-298-2900 2
 
1.1%
061-544-3888 1
 
0.6%
063-247-7532 1
 
0.6%
061-333-8946 1
 
0.6%
063-546-1072 1
 
0.6%
063-432-1966 1
 
0.6%
063-324-1072 1
 
0.6%
063-784-7070 1
 
0.6%
063-644-8255 1
 
0.6%
063-653-9120 1
 
0.6%
Other values (168) 168
93.9%
2023-12-12T23:56:06.985859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 356
16.6%
0 308
14.3%
3 265
12.3%
4 194
9.0%
5 193
9.0%
2 178
8.3%
1 170
7.9%
6 146
6.8%
7 125
 
5.8%
8 106
 
4.9%
Other values (3) 106
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1788
83.3%
Dash Punctuation 356
 
16.6%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 308
17.2%
3 265
14.8%
4 194
10.9%
5 193
10.8%
2 178
10.0%
1 170
9.5%
6 146
8.2%
7 125
7.0%
8 106
 
5.9%
9 103
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 356
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 356
16.6%
0 308
14.3%
3 265
12.3%
4 194
9.0%
5 193
9.0%
2 178
8.3%
1 170
7.9%
6 146
6.8%
7 125
 
5.8%
8 106
 
4.9%
Other values (3) 106
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 356
16.6%
0 308
14.3%
3 265
12.3%
4 194
9.0%
5 193
9.0%
2 178
8.3%
1 170
7.9%
6 146
6.8%
7 125
 
5.8%
8 106
 
4.9%
Other values (3) 106
 
4.9%

팩스번호
Text

MISSING 

Distinct175
Distinct (%)100.0%
Missing5
Missing (%)2.8%
Memory size1.5 KiB
2023-12-12T23:56:07.254415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.982857
Min length11

Characters and Unicode

Total characters2097
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)100.0%

Sample

1st row02-2108-7215
2nd row02-2217-8840
3rd row02-3273-2254
4th row02-3144-0833
5th row02-2671-1378
ValueCountFrequency (%)
02-2108-7215 1
 
0.6%
02-804-4059 1
 
0.6%
061-333-8947 1
 
0.6%
063-547-1072 1
 
0.6%
063-433-1410 1
 
0.6%
063-324-1073 1
 
0.6%
063-784-7071 1
 
0.6%
063-644-8253 1
 
0.6%
063-652-0308 1
 
0.6%
063-580-7651 1
 
0.6%
Other values (166) 166
94.3%
2023-12-12T23:56:07.728934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 345
16.5%
3 280
13.4%
0 274
13.1%
5 203
9.7%
4 186
8.9%
2 174
8.3%
1 156
7.4%
6 142
6.8%
7 119
 
5.7%
8 117
 
5.6%
Other values (4) 101
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1748
83.4%
Dash Punctuation 345
 
16.5%
Other Punctuation 2
 
0.1%
Space Separator 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 280
16.0%
0 274
15.7%
5 203
11.6%
4 186
10.6%
2 174
10.0%
1 156
8.9%
6 142
8.1%
7 119
6.8%
8 117
6.7%
9 97
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 345
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2097
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 345
16.5%
3 280
13.4%
0 274
13.1%
5 203
9.7%
4 186
8.9%
2 174
8.3%
1 156
7.4%
6 142
6.8%
7 119
 
5.7%
8 117
 
5.6%
Other values (4) 101
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 345
16.5%
3 280
13.4%
0 274
13.1%
5 203
9.7%
4 186
8.9%
2 174
8.3%
1 156
7.4%
6 142
6.8%
7 119
 
5.7%
8 117
 
5.6%
Other values (4) 101
 
4.8%

Interactions

2023-12-12T23:56:03.608748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:56:07.838216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류지역우편번호
분류1.0000.4020.000
지역0.4021.0000.958
우편번호0.0000.9581.000
2023-12-12T23:56:07.927128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류
지역1.0000.345
분류0.3451.000
2023-12-12T23:56:08.006156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호분류지역
우편번호1.0000.0000.799
분류0.0001.0000.345
지역0.7990.3451.000

Missing values

2023-12-12T23:56:03.756794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:56:03.897665image/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.
2023-12-12T23:56:04.002166image/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

분류지역협의회명우편번호주소대표연락처팩스번호
0시군구협의회서울특별시구로구사회복지협의회8389구로구 디지털로272, 704호(구로동, 한신IT타워)02-869-955502-2108-7215
1시군구협의회서울특별시동대문구사회복지협의회2597동대문구 천호대로65길 17, 5층(답십리동, 구립답십리청소년독서실)02-2217-8837~902-2217-8840
2시군구협의회서울특별시마포구사회복지협의회4103마포구 신촌로26길 10(노고산동) 지하 1층02-3273-225102-3273-2254
3시군구협의회서울특별시서대문구사회복지협의회3711서대문구 모래내로 15길 37, 남가좌1동주민센터 지하 1층02-3144-074002-3144-0833
4시군구협의회서울특별시영등포구사회복지협의회7256영등포구 선유동1로 80, 영등포구사회복지협의회02-2670-419602-2671-1378
5시군구협의회서울특별시종로구사회복지협의회3058종로구 율곡로89 웰니스센터 B101호02-734-066102-734-0667
6시군구협의회서울특별시중랑구사회복지협의회2076중랑구 봉화산로 190 관상복합청사 4층02-2094-096502-3423-1323
7시군구협의회서울특별시강남구사회복지기관협의회6143강남구 봉은사로50길 6 청음복지관02-556-349302-555-4241
8시군구협의회서울특별시강동구사회복지협의회5340강동구 천호대로 1073, 620호(천호동, 힐탑프라자)02-489-069702-489-0698
9시군구협의회서울특별시강북구복지발전협의회1229강북구 한천로 105길24 202동 번동2단지종합사회복지관02-987-507702-987-5051
분류지역협의회명우편번호주소대표연락처팩스번호
170광역세종특별자치시세종특별자치시사회복지협의회30016조치원읍 터미널안길 60, 6-2호(세종시고용복지플러스센터)044-862-0404044-866-4040
171광역경기도경기도사회복지협의회16360수원시 장안구 서부로 2139 SK허브블루 6003호(율전동)031-213-8551031-213-8557
172광역강원도강원특별자치도사회복지협의회24209춘천시 동면 소양강로 110, 5층033-251-3327033-251-3337
173광역충청북도충청북도사회복지협의회28583청주시 흥덕구 공단로 87(충청북도종합사회복지센터)043-234-0840043-234-0849
174광역충청남도충청남도사회복지협의회32231홍성군 홍북읍 상하천로 50, 충남보훈회관 1층041-634-0875041-634-0862
175광역전라북도전라북도사회복지협의회54932전주시 덕진구 전주천동로 483(전북사회복지관)063-224-1861063-224-1863
176광역전라남도전라남도사회복지협의회58565무안군 삼향읍 오룡3길 22, 전남사회복지회관 1층061-285-8945061-285-8948
177광역경상북도경상북도사회복지협의회36664안동시 광명로 166, 한양빌딩 7층054-843-8550054)853-8577
178광역경상남도경상남도사회복지협의회51117창원시 의창구 동읍 동읍로 457번길 48, 경남사회복지센터 1층055-298-2900055-237-2873
179광역제주특별자치도제주특별자치도사회복지협의회63300제주시 청풍남8길 12-1, 사회복지협의회 회관064-702-3784064-702-3383