Overview

Dataset statistics

Number of variables7
Number of observations266
Missing cells719
Missing cells (%)38.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory56.5 B

Variable types

Categorical1
Text6

Dataset

Description결혼이민자 대상 한국어교육 운영기관 현황에 관한 데이터로서 시도,시군구,주소,연락처 등의 정보를 제공합니다.
Author여성가족부
URLhttps://www.data.go.kr/data/3077037/fileData.do

Alerts

연락처2 has 219 (82.3%) missing valuesMissing
연락처3 has 245 (92.1%) missing valuesMissing
연락처4 has 255 (95.9%) missing valuesMissing
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 19:06:30.779779
Analysis finished2024-03-14 19:06:32.292191
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct17
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
서울
48 
경기
34 
경북
23 
전남
22 
충남
21 
Other values (12)
118 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
서울 48
18.0%
경기 34
12.8%
경북 23
8.6%
전남 22
8.3%
충남 21
7.9%
경남 19
 
7.1%
강원 18
 
6.8%
부산 17
 
6.4%
전북 14
 
5.3%
충북 12
 
4.5%
Other values (7) 38
14.3%

Length

2024-03-15T04:06:32.506962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 48
18.0%
경기 34
12.8%
경북 23
8.6%
전남 22
8.3%
충남 21
7.9%
경남 19
 
7.1%
강원 18
 
6.8%
부산 17
 
6.4%
전북 14
 
5.3%
충북 12
 
4.5%
Other values (7) 38
14.3%

운영기관명
Text

Distinct231
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-15T04:06:33.463326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.5789474
Min length7

Characters and Unicode

Total characters2016
Distinct characters148
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

Unique213 ?
Unique (%)80.1%

Sample

1st row강남구가족센터
2nd row강동구가족센터
3rd row강북구가족센터
4th row강서구가족센터
5th row관악구가족센터
ValueCountFrequency (%)
송파구가족센터 7
 
2.6%
아산시가족센터 6
 
2.2%
서초구가족센터 4
 
1.5%
성동구가족센터 4
 
1.5%
광진구가족센터 3
 
1.1%
은평구가족센터 3
 
1.1%
동작구가족센터 3
 
1.1%
서대문구가족센터 3
 
1.1%
사하구가족센터 2
 
0.7%
홍성군가족센터 2
 
0.7%
Other values (222) 230
86.1%
2024-03-15T04:06:34.780431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 264
13.1%
족 263
13.0%
센 263
13.0%
터 263
13.0%
구 103
 
5.1%
시 92
 
4.6%
군 86
 
4.3%
산 31
 
1.5%
원 30
 
1.5%
주 26
 
1.3%
Other values (138) 595
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2013
99.9%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 264
13.1%
족 263
13.1%
센 263
13.1%
터 263
13.1%
구 103
 
5.1%
시 92
 
4.6%
군 86
 
4.3%
산 31
 
1.5%
원 30
 
1.5%
주 26
 
1.3%
Other values (135) 592
29.4%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2013
99.9%
Common 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 264
13.1%
족 263
13.1%
센 263
13.1%
터 263
13.1%
구 103
 
5.1%
시 92
 
4.6%
군 86
 
4.3%
산 31
 
1.5%
원 30
 
1.5%
주 26
 
1.3%
Other values (135) 592
29.4%
Common
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2013
99.9%
ASCII 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 264
13.1%
족 263
13.1%
센 263
13.1%
터 263
13.1%
구 103
 
5.1%
시 92
 
4.6%
군 86
 
4.3%
산 31
 
1.5%
원 30
 
1.5%
주 26
 
1.3%
Other values (135) 592
29.4%
ASCII
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

주소
Text

UNIQUE 

Distinct266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-15T04:06:35.789054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length26.766917
Min length13

Characters and Unicode

Total characters7120
Distinct characters337
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique266 ?
Unique (%)100.0%

Sample

1st row서울시 강남구 개포로 617-8
2nd row서울시 강동구 양재대로 1634, 3층
3rd row서울시 강북구 한천로 129길 6
4th row서울시 강서구 강서로 5길 50, 곰달래 문화복지센터 4층
5th row서울시 관악구 신림로 3길 35 김삼준문화복지기념관 3층 사무실
ValueCountFrequency (%)
서울시 48
 
3.1%
2층 39
 
2.5%
3층 34
 
2.2%
경기도 33
 
2.1%
경북 22
 
1.4%
전남 22
 
1.4%
충남 21
 
1.3%
경남 19
 
1.2%
4층 19
 
1.2%
강원도 18
 
1.2%
Other values (1043) 1283
82.3%
2024-03-15T04:06:37.458404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1305
 
18.3%
1 250
 
3.5%
로 218
 
3.1%
시 212
 
3.0%
2 207
 
2.9%
층 173
 
2.4%
3 152
 
2.1%
구 142
 
2.0%
길 122
 
1.7%
4 108
 
1.5%
Other values (327) 4231
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4293
60.3%
Space Separator 1305
 
18.3%
Decimal Number 1151
 
16.2%
Open Punctuation 101
 
1.4%
Close Punctuation 101
 
1.4%
Other Punctuation 93
 
1.3%
Dash Punctuation 54
 
0.8%
Uppercase Letter 17
 
0.2%
Math Symbol 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 218
 
5.1%
시 212
 
4.9%
층 173
 
4.0%
구 142
 
3.3%
길 122
 
2.8%
동 98
 
2.3%
군 96
 
2.2%
남 93
 
2.2%
터 90
 
2.1%
산 86
 
2.0%
Other values (299) 2963
69.0%
Decimal Number
ValueCountFrequency (%)
1 250
21.7%
2 207
18.0%
3 152
13.2%
4 108
9.4%
5 103
8.9%
0 84
 
7.3%
6 72
 
6.3%
7 71
 
6.2%
9 58
 
5.0%
8 46
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
17.6%
H 2
11.8%
Y 2
11.8%
W 2
11.8%
C 2
11.8%
A 2
11.8%
S 1
 
5.9%
P 1
 
5.9%
F 1
 
5.9%
L 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 90
96.8%
. 2
 
2.2%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
1305
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4293
60.3%
Common 2810
39.5%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 218
 
5.1%
시 212
 
4.9%
층 173
 
4.0%
구 142
 
3.3%
길 122
 
2.8%
동 98
 
2.3%
군 96
 
2.2%
남 93
 
2.2%
터 90
 
2.1%
산 86
 
2.0%
Other values (299) 2963
69.0%
Common
ValueCountFrequency (%)
1305
46.4%
1 250
 
8.9%
2 207
 
7.4%
3 152
 
5.4%
4 108
 
3.8%
5 103
 
3.7%
( 101
 
3.6%
) 101
 
3.6%
, 90
 
3.2%
0 84
 
3.0%
Other values (8) 309
 
11.0%
Latin
ValueCountFrequency (%)
B 3
17.6%
H 2
11.8%
Y 2
11.8%
W 2
11.8%
C 2
11.8%
A 2
11.8%
S 1
 
5.9%
P 1
 
5.9%
F 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4293
60.3%
ASCII 2827
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1305
46.2%
1 250
 
8.8%
2 207
 
7.3%
3 152
 
5.4%
4 108
 
3.8%
5 103
 
3.6%
( 101
 
3.6%
) 101
 
3.6%
, 90
 
3.2%
0 84
 
3.0%
Other values (18) 326
 
11.5%
Hangul
ValueCountFrequency (%)
로 218
 
5.1%
시 212
 
4.9%
층 173
 
4.0%
구 142
 
3.3%
길 122
 
2.8%
동 98
 
2.3%
군 96
 
2.2%
남 93
 
2.2%
터 90
 
2.1%
산 86
 
2.0%
Other values (299) 2963
69.0%

연락처
Text

Distinct255
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-15T04:06:38.364672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length11.951128
Min length11

Characters and Unicode

Total characters3179
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

Unique246 ?
Unique (%)92.5%

Sample

1st row02-3412-2222
2nd row02-471-0812
3rd row02-987-2567
4th row02-2606-2017
5th row02-883-9383
ValueCountFrequency (%)
02-376-3761 3
 
1.1%
02-599-3301 3
 
1.1%
02-3395-9445 2
 
0.7%
031-319-7997 2
 
0.7%
031-793-2993 2
 
0.7%
02-995-6800 2
 
0.7%
02-957-0760 2
 
0.7%
041-548-9775 2
 
0.7%
02-3290-1660 2
 
0.7%
063-561-1366 1
 
0.4%
Other values (246) 246
92.1%
2024-03-15T04:06:39.758708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 532
16.7%
0 456
14.3%
3 402
12.6%
5 309
9.7%
2 257
8.1%
4 254
8.0%
1 250
7.9%
6 186
 
5.9%
7 183
 
5.8%
9 180
 
5.7%
Other values (4) 170
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2640
83.0%
Dash Punctuation 532
 
16.7%
Math Symbol 4
 
0.1%
Space Separator 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 456
17.3%
3 402
15.2%
5 309
11.7%
2 257
9.7%
4 254
9.6%
1 250
9.5%
6 186
7.0%
7 183
6.9%
9 180
 
6.8%
8 163
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 532
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3179
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 532
16.7%
0 456
14.3%
3 402
12.6%
5 309
9.7%
2 257
8.1%
4 254
8.0%
1 250
7.9%
6 186
 
5.9%
7 183
 
5.8%
9 180
 
5.7%
Other values (4) 170
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 532
16.7%
0 456
14.3%
3 402
12.6%
5 309
9.7%
2 257
8.1%
4 254
8.0%
1 250
7.9%
6 186
 
5.9%
7 183
 
5.8%
9 180
 
5.7%
Other values (4) 170
 
5.3%

연락처2
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing219
Missing (%)82.3%
Memory size2.2 KiB
2024-03-15T04:06:40.700327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.085106
Min length12

Characters and Unicode

Total characters568
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row02-6919-9746
2nd row051-506-5765
3rd row051-257-0064
4th row053-637-4374
5th row053-327-2994
ValueCountFrequency (%)
02-6919-9746 1
 
2.1%
061-383-3611 1
 
2.1%
033-344-3459 1
 
2.1%
043-537-5432 1
 
2.1%
041-853-0882 1
 
2.1%
041-830-2954 1
 
2.1%
041-953-3808 1
 
2.1%
041-339-8383 1
 
2.1%
041-944-2334 1
 
2.1%
041-670-2523 1
 
2.1%
Other values (37) 37
78.7%
2024-03-15T04:06:41.891999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 94
16.5%
3 89
15.7%
0 69
12.1%
1 53
9.3%
4 50
8.8%
5 50
8.8%
2 39
6.9%
6 39
6.9%
8 30
 
5.3%
7 27
 
4.8%
Other values (2) 28
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 472
83.1%
Dash Punctuation 94
 
16.5%
Math Symbol 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 89
18.9%
0 69
14.6%
1 53
11.2%
4 50
10.6%
5 50
10.6%
2 39
8.3%
6 39
8.3%
8 30
 
6.4%
7 27
 
5.7%
9 26
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 94
16.5%
3 89
15.7%
0 69
12.1%
1 53
9.3%
4 50
8.8%
5 50
8.8%
2 39
6.9%
6 39
6.9%
8 30
 
5.3%
7 27
 
4.8%
Other values (2) 28
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 94
16.5%
3 89
15.7%
0 69
12.1%
1 53
9.3%
4 50
8.8%
5 50
8.8%
2 39
6.9%
6 39
6.9%
8 30
 
5.3%
7 27
 
4.8%
Other values (2) 28
 
4.9%

연락처3
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing245
Missing (%)92.1%
Memory size2.2 KiB
2024-03-15T04:06:42.705100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.095238
Min length12

Characters and Unicode

Total characters254
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row02-6919-9747
2nd row051-503-3530
3rd row051-241-6252
4th row032-511-1809
5th row044-862-9338
ValueCountFrequency (%)
02-6919-9747 1
 
4.8%
043-537-5433 1
 
4.8%
055-351-4412~3 1
 
4.8%
061-864-4812 1
 
4.8%
061-750-5354 1
 
4.8%
061-383-3612 1
 
4.8%
041-944-2335 1
 
4.8%
041-339-8384 1
 
4.8%
041-953-1911 1
 
4.8%
041-830-2955 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T04:06:43.939833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.5%
3 41
16.1%
0 29
11.4%
1 29
11.4%
5 28
11.0%
4 22
8.7%
9 17
6.7%
2 14
 
5.5%
6 13
 
5.1%
8 10
 
3.9%
Other values (2) 9
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 211
83.1%
Dash Punctuation 42
 
16.5%
Math Symbol 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 41
19.4%
0 29
13.7%
1 29
13.7%
5 28
13.3%
4 22
10.4%
9 17
8.1%
2 14
 
6.6%
6 13
 
6.2%
8 10
 
4.7%
7 8
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 254
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.5%
3 41
16.1%
0 29
11.4%
1 29
11.4%
5 28
11.0%
4 22
8.7%
9 17
6.7%
2 14
 
5.5%
6 13
 
5.1%
8 10
 
3.9%
Other values (2) 9
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.5%
3 41
16.1%
0 29
11.4%
1 29
11.4%
5 28
11.0%
4 22
8.7%
9 17
6.7%
2 14
 
5.5%
6 13
 
5.1%
8 10
 
3.9%
Other values (2) 9
 
3.5%

연락처4
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing255
Missing (%)95.9%
Memory size2.2 KiB
2024-03-15T04:06:44.575120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length13.727273
Min length12

Characters and Unicode

Total characters151
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row02-6919-9748~50
2nd row031-599-1703~16
3rd row031-677-9337
4th row031-949-9164
5th row033-535-0186
ValueCountFrequency (%)
02-6919-9748~50 1
9.1%
031-599-1703~16 1
9.1%
031-677-9337 1
9.1%
031-949-9164 1
9.1%
033-535-0186 1
9.1%
043-537-5434~5 1
9.1%
041-339-8385~9 1
9.1%
061-383-3613~3616 1
9.1%
061-750-5355~7 1
9.1%
061-864-4813~5 1
9.1%
2024-03-15T04:06:45.485703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 23
15.2%
- 22
14.6%
0 16
10.6%
1 16
10.6%
5 16
10.6%
6 13
8.6%
9 11
7.3%
7 9
 
6.0%
4 9
 
6.0%
8 7
 
4.6%
Other values (2) 9
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 122
80.8%
Dash Punctuation 22
 
14.6%
Math Symbol 7
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 23
18.9%
0 16
13.1%
1 16
13.1%
5 16
13.1%
6 13
10.7%
9 11
9.0%
7 9
 
7.4%
4 9
 
7.4%
8 7
 
5.7%
2 2
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 23
15.2%
- 22
14.6%
0 16
10.6%
1 16
10.6%
5 16
10.6%
6 13
8.6%
9 11
7.3%
7 9
 
6.0%
4 9
 
6.0%
8 7
 
4.6%
Other values (2) 9
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 23
15.2%
- 22
14.6%
0 16
10.6%
1 16
10.6%
5 16
10.6%
6 13
8.6%
9 11
7.3%
7 9
 
6.0%
4 9
 
6.0%
8 7
 
4.6%
Other values (2) 9
 
6.0%

Correlations

2024-03-15T04:06:45.710953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도연락처2연락처3연락처4
시도1.0001.0001.0001.000
연락처21.0001.0001.0001.000
연락처31.0001.0001.0001.000
연락처41.0001.0001.0001.000

Missing values

2024-03-15T04:06:31.454386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:06:31.839165image/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.
2024-03-15T04:06:32.147001image/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

시도운영기관명주소연락처연락처2연락처3연락처4
0서울강남구가족센터서울시 강남구 개포로 617-802-3412-2222<NA><NA><NA>
1서울강동구가족센터서울시 강동구 양재대로 1634, 3층02-471-0812<NA><NA><NA>
2서울강북구가족센터서울시 강북구 한천로 129길 602-987-2567<NA><NA><NA>
3서울강서구가족센터서울시 강서구 강서로 5길 50, 곰달래 문화복지센터 4층02-2606-2017<NA><NA><NA>
4서울관악구가족센터서울시 관악구 신림로 3길 35 김삼준문화복지기념관 3층 사무실02-883-9383<NA><NA><NA>
5서울광진구가족센터서울시 광진구 능동로 30길 23, 새마을회관 2층(1센터)02-458-0622<NA><NA><NA>
6서울광진구가족센터서울시 광진구 아차산로 24길 17, 자양공공힐링센터 5층(2센터)02-458-0666<NA><NA><NA>
7서울광진구가족센터서울시 광진구 자양로 15길 60, 평생할습센터 1층(공동육아나눔터)02-458-0623<NA><NA><NA>
8서울구로구가족센터서울시 구로구 우마2길 35, 구로구가족통합지원센터 2,3층02-869-0317<NA><NA><NA>
9서울금천구가족센터서울시 금천구 금하로 11길 4002-803-7747<NA><NA><NA>
시도운영기관명주소연락처연락처2연락처3연락처4
256경남창원시가족센터경남 창원시 성산구 대정로20번길 11, 1층(가음동, 여성회관 창원관)055-225-3951<NA><NA><NA>
257경남창원시마산가족센터경남 창원시 마산합포구 중앙북5길 20. 마산YWCA 지하1층055-244-8745<NA><NA><NA>
258경남통영시가족센터경남 통영시 신죽2길 130055-640-7900<NA><NA><NA>
259경남하동군가족센터경남 하동군 섬진강대로 2214 종합사회복지관4층055-880-6522<NA><NA><NA>
260경남함안군가족센터경남 함안군 산인면 가야로 217 산인면종합복지관 1층055-583-5430<NA><NA><NA>
261경남함양군가족센터경남 함양군 함양읍 함양여중길 10055-963-5014<NA><NA><NA>
262경남합천군가족센터경남 합천군 합천읍 옥산로 96-7 2층055-930-4732<NA><NA><NA>
263제주서귀포시가족센터제주도 서귀포시 서호남로12064-732-6482064-762-1141<NA><NA>
264제주제주시가족센터제주도 제주시 중앙로 14길 15(삼도이동) 2,3,4층064-725-8005<NA><NA><NA>
265제주제주시가족센터제주도 제주시 중앙로 198 7,8층(해와달빌딩)064-712-1140<NA><NA><NA>