Overview

Dataset statistics

Number of variables7
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory62.0 B

Variable types

Numeric2
Text4
Categorical1

Dataset

Description인천광역시 부평구 지역아동센터 현황입니다.(번호,시설명,관할동,도로명주소,연락처,정원,아동복지교사,배치인원(파견일수))ex)1,갈산동도토리학교,지역아동센터,갈산1동,인천광역시 부평구 평천로 355 (갈산동),032-527-0933,25,3(4)
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078617&srcSe=7661IVAWM27C61E190

Alerts

번호 has unique valuesUnique
시설명 has unique valuesUnique
도로명주소 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:08:22.810589
Analysis finished2024-03-18 04:08:25.178580
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-18T13:08:25.235420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2024-03-18T13:08:25.374179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

시설명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:08:25.586742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.727273
Min length9

Characters and Unicode

Total characters387
Distinct characters87
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

Unique33 ?
Unique (%)100.0%

Sample

1st row갈산동도토리학교 지역아동센터
2nd row경인비젼스쿨 지역아동센터
3rd row고토 지역아동센터
4th row누리 지역아동센터
5th row다드림 지역아동센터
ValueCountFrequency (%)
지역아동센터 24
35.3%
함께걷기 5
 
7.4%
공부방 3
 
4.4%
인천행복한돌봄 2
 
2.9%
햇살 1
 
1.5%
제일 1
 
1.5%
너른들 1
 
1.5%
부평지역아동센터 1
 
1.5%
삼산해오름 1
 
1.5%
오순도순 1
 
1.5%
Other values (28) 28
41.2%
2024-03-18T13:08:25.869376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 36
 
9.3%
35
 
9.0%
지 34
 
8.8%
아 34
 
8.8%
역 33
 
8.5%
센 33
 
8.5%
터 33
 
8.5%
랑 6
 
1.6%
사 6
 
1.6%
한 5
 
1.3%
Other values (77) 132
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 352
91.0%
Space Separator 35
 
9.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 36
 
10.2%
지 34
 
9.7%
아 34
 
9.7%
역 33
 
9.4%
센 33
 
9.4%
터 33
 
9.4%
랑 6
 
1.7%
사 6
 
1.7%
한 5
 
1.4%
함 5
 
1.4%
Other values (76) 127
36.1%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
91.0%
Common 35
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 36
 
10.2%
지 34
 
9.7%
아 34
 
9.7%
역 33
 
9.4%
센 33
 
9.4%
터 33
 
9.4%
랑 6
 
1.7%
사 6
 
1.7%
한 5
 
1.4%
함 5
 
1.4%
Other values (76) 127
36.1%
Common
ValueCountFrequency (%)
35
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 352
91.0%
ASCII 35
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 36
 
10.2%
지 34
 
9.7%
아 34
 
9.7%
역 33
 
9.4%
센 33
 
9.4%
터 33
 
9.4%
랑 6
 
1.7%
사 6
 
1.7%
한 5
 
1.4%
함 5
 
1.4%
Other values (76) 127
36.1%
ASCII
ValueCountFrequency (%)
35
100.0%

관할동
Text

Distinct17
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:08:26.031629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9393939
Min length3

Characters and Unicode

Total characters130
Distinct characters19
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

Unique6 ?
Unique (%)18.2%

Sample

1st row갈산1동
2nd row부평3동
3rd row부개2동
4th row청천1동
5th row일신동
ValueCountFrequency (%)
청천2동 4
12.1%
부평4동 4
12.1%
십정1동 3
 
9.1%
부평2동 2
 
6.1%
갈산1동 2
 
6.1%
부평3동 2
 
6.1%
삼산1동 2
 
6.1%
갈산2동 2
 
6.1%
일신동 2
 
6.1%
부개2동 2
 
6.1%
Other values (7) 8
24.2%
2024-03-18T13:08:26.287078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 33
25.4%
부 13
 
10.0%
1 11
 
8.5%
2 11
 
8.5%
평 9
 
6.9%
산 9
 
6.9%
천 5
 
3.8%
청 5
 
3.8%
4 5
 
3.8%
정 4
 
3.1%
Other values (9) 25
19.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
76.2%
Decimal Number 31
 
23.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
33.3%
부 13
 
13.1%
평 9
 
9.1%
산 9
 
9.1%
천 5
 
5.1%
청 5
 
5.1%
정 4
 
4.0%
십 4
 
4.0%
개 4
 
4.0%
갈 4
 
4.0%
Other values (4) 9
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 11
35.5%
2 11
35.5%
4 5
16.1%
3 3
 
9.7%
5 1
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
76.2%
Common 31
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
33.3%
부 13
 
13.1%
평 9
 
9.1%
산 9
 
9.1%
천 5
 
5.1%
청 5
 
5.1%
정 4
 
4.0%
십 4
 
4.0%
개 4
 
4.0%
갈 4
 
4.0%
Other values (4) 9
 
9.1%
Common
ValueCountFrequency (%)
1 11
35.5%
2 11
35.5%
4 5
16.1%
3 3
 
9.7%
5 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
76.2%
ASCII 31
 
23.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 33
33.3%
부 13
 
13.1%
평 9
 
9.1%
산 9
 
9.1%
천 5
 
5.1%
청 5
 
5.1%
정 4
 
4.0%
십 4
 
4.0%
개 4
 
4.0%
갈 4
 
4.0%
Other values (4) 9
 
9.1%
ASCII
ValueCountFrequency (%)
1 11
35.5%
2 11
35.5%
4 5
16.1%
3 3
 
9.7%
5 1
 
3.2%

도로명주소
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:08:26.490729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length28.272727
Min length21

Characters and Unicode

Total characters933
Distinct characters76
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

Unique33 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 평천로 355 (갈산동)
2nd row인천광역시 부평구 마장로 14(십정동)
3rd row인천광역시 부평구 부흥로 380, 2층 (부개동)
4th row인천광역시 부평구 마장로450번길 18, 4층(청천동)
5th row인천광역시 부평구 항동로45번길 8 (일신동)
ValueCountFrequency (%)
인천광역시 33
18.5%
부평구 33
18.5%
2층 10
 
5.6%
십정동 5
 
2.8%
갈산동 4
 
2.2%
3층 4
 
2.2%
부개동 4
 
2.2%
8 2
 
1.1%
3층(청천동 2
 
1.1%
부평동 2
 
1.1%
Other values (72) 79
44.4%
2024-03-18T13:08:26.811345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
15.5%
부 53
 
5.7%
평 44
 
4.7%
천 41
 
4.4%
인 34
 
3.6%
광 34
 
3.6%
역 34
 
3.6%
동 34
 
3.6%
시 33
 
3.5%
구 33
 
3.5%
Other values (66) 448
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 550
58.9%
Space Separator 145
 
15.5%
Decimal Number 144
 
15.4%
Close Punctuation 32
 
3.4%
Open Punctuation 32
 
3.4%
Other Punctuation 25
 
2.7%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 53
 
9.6%
평 44
 
8.0%
천 41
 
7.5%
인 34
 
6.2%
광 34
 
6.2%
역 34
 
6.2%
동 34
 
6.2%
시 33
 
6.0%
구 33
 
6.0%
로 33
 
6.0%
Other values (51) 177
32.2%
Decimal Number
ValueCountFrequency (%)
2 27
18.8%
1 24
16.7%
3 19
13.2%
4 18
12.5%
8 13
9.0%
5 13
9.0%
0 10
 
6.9%
6 7
 
4.9%
7 7
 
4.9%
9 6
 
4.2%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 550
58.9%
Common 383
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 53
 
9.6%
평 44
 
8.0%
천 41
 
7.5%
인 34
 
6.2%
광 34
 
6.2%
역 34
 
6.2%
동 34
 
6.2%
시 33
 
6.0%
구 33
 
6.0%
로 33
 
6.0%
Other values (51) 177
32.2%
Common
ValueCountFrequency (%)
145
37.9%
) 32
 
8.4%
( 32
 
8.4%
2 27
 
7.0%
, 25
 
6.5%
1 24
 
6.3%
3 19
 
5.0%
4 18
 
4.7%
8 13
 
3.4%
5 13
 
3.4%
Other values (5) 35
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 550
58.9%
ASCII 383
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
37.9%
) 32
 
8.4%
( 32
 
8.4%
2 27
 
7.0%
, 25
 
6.5%
1 24
 
6.3%
3 19
 
5.0%
4 18
 
4.7%
8 13
 
3.4%
5 13
 
3.4%
Other values (5) 35
 
9.1%
Hangul
ValueCountFrequency (%)
부 53
 
9.6%
평 44
 
8.0%
천 41
 
7.5%
인 34
 
6.2%
광 34
 
6.2%
역 34
 
6.2%
동 34
 
6.2%
시 33
 
6.0%
구 33
 
6.0%
로 33
 
6.0%
Other values (51) 177
32.2%

연락처
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-18T13:08:27.015288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.060606
Min length12

Characters and Unicode

Total characters398
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

Unique33 ?
Unique (%)100.0%

Sample

1st row032-527-0933
2nd row070-8288-4347
3rd row032-330-1135
4th row032-514-1388
5th row032-511-8291
ValueCountFrequency (%)
032-527-0933 1
 
3.0%
032-429-8485 1
 
3.0%
032-512-3770 1
 
3.0%
032-522-7520 1
 
3.0%
032-519-2525 1
 
3.0%
032-503-7598 1
 
3.0%
032-504-5477 1
 
3.0%
032-528-6500 1
 
3.0%
032-511-9065 1
 
3.0%
032-527-7581 1
 
3.0%
Other values (23) 23
69.7%
2024-03-18T13:08:27.327316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 66
16.6%
2 63
15.8%
0 62
15.6%
3 56
14.1%
5 44
11.1%
1 25
 
6.3%
7 22
 
5.5%
8 19
 
4.8%
4 18
 
4.5%
6 12
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 332
83.4%
Dash Punctuation 66
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 63
19.0%
0 62
18.7%
3 56
16.9%
5 44
13.3%
1 25
 
7.5%
7 22
 
6.6%
8 19
 
5.7%
4 18
 
5.4%
6 12
 
3.6%
9 11
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 398
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 66
16.6%
2 63
15.8%
0 62
15.6%
3 56
14.1%
5 44
11.1%
1 25
 
6.3%
7 22
 
5.5%
8 19
 
4.8%
4 18
 
4.5%
6 12
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 66
16.6%
2 63
15.8%
0 62
15.6%
3 56
14.1%
5 44
11.1%
1 25
 
6.3%
7 22
 
5.5%
8 19
 
4.8%
4 18
 
4.5%
6 12
 
3.0%

정원
Real number (ℝ)

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.848485
Minimum19
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-18T13:08:27.439959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile19
Q119
median29
Q335
95-th percentile35
Maximum35
Range16
Interquartile range (IQR)16

Descriptive statistics

Standard deviation6.5293626
Coefficient of variation (CV)0.24319296
Kurtosis-1.588511
Mean26.848485
Median Absolute Deviation (MAD)6
Skewness-0.024710867
Sum886
Variance42.632576
MonotonicityNot monotonic
2024-03-18T13:08:27.532480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
19 11
33.3%
35 9
27.3%
29 6
18.2%
25 5
15.2%
32 1
 
3.0%
31 1
 
3.0%
ValueCountFrequency (%)
19 11
33.3%
25 5
15.2%
29 6
18.2%
31 1
 
3.0%
32 1
 
3.0%
35 9
27.3%
ValueCountFrequency (%)
35 9
27.3%
32 1
 
3.0%
31 1
 
3.0%
29 6
18.2%
25 5
15.2%
19 11
33.3%

아동복지교사 배치인원(파견일수)
Categorical

Distinct10
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
3(5)
12 
2(4)
6 
2(3)
4 
4(5)
3 
3(4)
2 
Other values (5)
6 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st row3(4)
2nd row3(5)
3rd row2(4)
4th row3(5)
5th row3(5)

Common Values

ValueCountFrequency (%)
3(5) 12
36.4%
2(4) 6
18.2%
2(3) 4
 
12.1%
4(5) 3
 
9.1%
3(4) 2
 
6.1%
2(5) 2
 
6.1%
4(4) 1
 
3.0%
1(2) 1
 
3.0%
3(3) 1
 
3.0%
1(3) 1
 
3.0%

Length

2024-03-18T13:08:27.663664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:08:27.793769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3(5 12
36.4%
2(4 6
18.2%
2(3 4
 
12.1%
4(5 3
 
9.1%
3(4 2
 
6.1%
2(5 2
 
6.1%
4(4 1
 
3.0%
1(2 1
 
3.0%
3(3 1
 
3.0%
1(3 1
 
3.0%

Interactions

2024-03-18T13:08:24.804400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:08:24.569268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:08:24.911000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:08:24.692734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:08:27.875190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시설명관할동도로명주소연락처정원아동복지교사 배치인원(파견일수)
번호1.0001.0000.0001.0001.0000.3680.000
시설명1.0001.0001.0001.0001.0001.0001.000
관할동0.0001.0001.0001.0001.0000.0000.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.000
정원0.3681.0000.0001.0001.0001.0000.000
아동복지교사 배치인원(파견일수)0.0001.0000.0001.0001.0000.0001.000
2024-03-18T13:08:27.977103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호정원아동복지교사 배치인원(파견일수)
번호1.0000.0710.000
정원0.0711.0000.000
아동복지교사 배치인원(파견일수)0.0000.0001.000

Missing values

2024-03-18T13:08:25.020721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:08:25.134839image/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.

Sample

번호시설명관할동도로명주소연락처정원아동복지교사 배치인원(파견일수)
01갈산동도토리학교 지역아동센터갈산1동인천광역시 부평구 평천로 355 (갈산동)032-527-0933253(4)
12경인비젼스쿨 지역아동센터부평3동인천광역시 부평구 마장로 14(십정동)070-8288-4347193(5)
23고토 지역아동센터부개2동인천광역시 부평구 부흥로 380, 2층 (부개동)032-330-1135252(4)
34누리 지역아동센터청천1동인천광역시 부평구 마장로450번길 18, 4층(청천동)032-514-1388193(5)
45다드림 지역아동센터일신동인천광역시 부평구 항동로45번길 8 (일신동)032-511-8291353(5)
56무지개 지역아동센터부평5동인천광역시 부평구 부평문화로127(부평동,청아빌딩4층)032-330-1641353(5)
67사랑의 지역아동센터산곡4동인천광역시 부평구 원길로11번길 45, 2층(산곡동)032-512-9090253(5)
78산곡 지역아동센터산곡1동인천광역시 부평구 원적로309번길 32-1, 2층 (산곡동)032-523-3790294(4)
89새빛행복한홈스쿨 지역아동센터갈산2동인천광역시 부평구 주부토로 146, 3층 (갈산동)032-525-2710194(5)
910생명 지역아동센터부평4동인천광역시 부평구 부흥북로58번길 16, 2층 (부평동)032-512-9063293(5)
번호시설명관할동도로명주소연락처정원아동복지교사 배치인원(파견일수)
2324지역아동센터 햇살 공부방청천2동인천광역시 부평구 세월천로 11-8 3층(청천동)032-504-6308192(4)
2425카리타스지역아동센터갈산2동인천광역시 부평구 주부토로 206 (갈산동, 주공2단지아파트)032-527-7581352(4)
2526한사랑 지역아동센터부평4동인천광역시 부평구 길주남로 78, 2층 (부평동)032-511-9065313(5)
2627한우리 지역아동센터삼산1동인천광역시 부평구 영성로 38, 2층 (삼산동)032-528-6500294(5)
2728함께걷기 다정지역아동센터산곡3동인천광역시 부평구 화랑남로5번길 20, 2층 (산곡동)032-504-5477353(5)
2829함께걷기 보아스지역아동센터부평3동인천광역시 부평구 마장로72번길 8, 2층 (십정동)032-503-7598192(3)
2930함께걷기 소망지역아동센터청천2동인천광역시 부평구 마장로 412, 2층(청천동)032-519-2525351(3)
3031함께걷기 참사랑지역아동센터부평4동인천광역시 부평구 부흥로 315번길 18-5032-522-7520192(3)
3132함께걷기 큰사랑지역아동센터청천2동인천광역시 부평구 평천로 145, 2층(청천동)032-512-3770352(4)
3233해님 지역아동센터십정1동인천광역시 부평구 백범로 482, 2층 (십정동)032-437-6049193(4)