Overview

Dataset statistics

Number of variables17
Number of observations191
Missing cells30
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.2 KiB
Average record size in memory145.7 B

Variable types

Categorical4
Text4
Numeric8
DateTime1

Dataset

Description인천광역시 미추홀구 어린이집 현황에 대한 데이터로 보육실수, 보육실면적, 놀이터수, 보육교직원수, 정원수 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15086361&srcSe=7661IVAWM27C61E190

Alerts

시군구명 has constant value ""Constant
우편번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 우편번호High correlation
보육실수 is highly overall correlated with 보육실면적_제곱미터 and 3 other fieldsHigh correlation
보육실면적_제곱미터 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
보육교직원수 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
정원수 is highly overall correlated with 보육실수 and 4 other fieldsHigh correlation
현원수 is highly overall correlated with 보육실수 and 3 other fieldsHigh correlation
어린이집유형구분 is highly overall correlated with 통학차량운영High correlation
놀이터수 is highly overall correlated with 정원수High correlation
통학차량운영 is highly overall correlated with 어린이집유형구분High correlation
우편번호 has 2 (1.0%) missing valuesMissing
어린이집팩스번호 has 28 (14.7%) missing valuesMissing
어린이집명 has unique valuesUnique
도로명주소 has unique valuesUnique
연락처 has unique valuesUnique
현원수 has 4 (2.1%) zerosZeros

Reproduction

Analysis started2024-01-28 06:21:56.180102
Analysis finished2024-01-28 06:22:01.697180
Duration5.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
인천광역시 미추홀구
191 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 미추홀구
2nd row인천광역시 미추홀구
3rd row인천광역시 미추홀구
4th row인천광역시 미추홀구
5th row인천광역시 미추홀구

Common Values

ValueCountFrequency (%)
인천광역시 미추홀구 191
100.0%

Length

2024-01-28T15:22:01.743295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:22:02.073583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 191
50.0%
미추홀구 191
50.0%

어린이집명
Text

UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-28T15:22:02.252458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.3193717
Min length5

Characters and Unicode

Total characters1398
Distinct characters247
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)100.0%

Sample

1st rowLH아이세상어린이집
2nd rowSK아이숲어린이집
3rd rowSK해사랑어린이집
4th rowSK행복아이사랑어린이집
5th row가온누리어린이집
ValueCountFrequency (%)
어린이집 2
 
1.0%
lh아이세상어린이집 1
 
0.5%
용현어린이집 1
 
0.5%
웃음어린이집 1
 
0.5%
원일어린이집 1
 
0.5%
유미예능어린이집 1
 
0.5%
은하수어린이집 1
 
0.5%
은하어린이집 1
 
0.5%
이삭어린이집 1
 
0.5%
인천법원어린이집 1
 
0.5%
Other values (183) 183
94.3%
2024-01-28T15:22:02.545076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 214
15.3%
린 192
 
13.7%
어 191
 
13.7%
집 191
 
13.7%
아 20
 
1.4%
나 14
 
1.0%
리 12
 
0.9%
마 11
 
0.8%
랑 11
 
0.8%
사 11
 
0.8%
Other values (237) 531
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1384
99.0%
Uppercase Letter 8
 
0.6%
Space Separator 3
 
0.2%
Decimal Number 2
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 214
15.5%
린 192
 
13.9%
어 191
 
13.8%
집 191
 
13.8%
아 20
 
1.4%
나 14
 
1.0%
리 12
 
0.9%
마 11
 
0.8%
랑 11
 
0.8%
사 11
 
0.8%
Other values (229) 517
37.4%
Uppercase Letter
ValueCountFrequency (%)
K 3
37.5%
S 3
37.5%
L 1
 
12.5%
H 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1384
99.0%
Latin 9
 
0.6%
Common 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 214
15.5%
린 192
 
13.9%
어 191
 
13.8%
집 191
 
13.8%
아 20
 
1.4%
나 14
 
1.0%
리 12
 
0.9%
마 11
 
0.8%
랑 11
 
0.8%
사 11
 
0.8%
Other values (229) 517
37.4%
Latin
ValueCountFrequency (%)
K 3
33.3%
S 3
33.3%
L 1
 
11.1%
e 1
 
11.1%
H 1
 
11.1%
Common
ValueCountFrequency (%)
3
60.0%
4 1
 
20.0%
2 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1384
99.0%
ASCII 14
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 214
15.5%
린 192
 
13.9%
어 191
 
13.8%
집 191
 
13.8%
아 20
 
1.4%
나 14
 
1.0%
리 12
 
0.9%
마 11
 
0.8%
랑 11
 
0.8%
사 11
 
0.8%
Other values (229) 517
37.4%
ASCII
ValueCountFrequency (%)
K 3
21.4%
3
21.4%
S 3
21.4%
4 1
 
7.1%
2 1
 
7.1%
L 1
 
7.1%
e 1
 
7.1%
H 1
 
7.1%

어린이집유형구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
민간
82 
가정
64 
국공립
31 
직장
9 
법인·단체등
 
3

Length

Max length6
Median length2
Mean length2.2670157
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가정
2nd row가정
3rd row민간
4th row가정
5th row민간

Common Values

ValueCountFrequency (%)
민간 82
42.9%
가정 64
33.5%
국공립 31
 
16.2%
직장 9
 
4.7%
법인·단체등 3
 
1.6%
사회복지법인 2
 
1.0%

Length

2024-01-28T15:22:02.662073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:22:02.752124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 82
42.9%
가정 64
33.5%
국공립 31
 
16.2%
직장 9
 
4.7%
법인·단체등 3
 
1.6%
사회복지법인 2
 
1.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct78
Distinct (%)41.3%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean22175.688
Minimum22100
Maximum22243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:02.845449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22100
5-th percentile22110
Q122143
median22185
Q322209
95-th percentile22234.6
Maximum22243
Range143
Interquartile range (IQR)66

Descriptive statistics

Standard deviation40.797149
Coefficient of variation (CV)0.0018397242
Kurtosis-1.0933129
Mean22175.688
Median Absolute Deviation (MAD)37
Skewness-0.156568
Sum4191205
Variance1664.4074
MonotonicityNot monotonic
2024-01-28T15:22:02.950348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22189 7
 
3.7%
22168 7
 
3.7%
22188 7
 
3.7%
22185 7
 
3.7%
22143 6
 
3.1%
22222 6
 
3.1%
22203 5
 
2.6%
22175 5
 
2.6%
22114 5
 
2.6%
22229 5
 
2.6%
Other values (68) 129
67.5%
ValueCountFrequency (%)
22100 1
 
0.5%
22101 4
2.1%
22102 1
 
0.5%
22103 2
 
1.0%
22110 3
1.6%
22114 5
2.6%
22115 3
1.6%
22116 2
 
1.0%
22117 2
 
1.0%
22118 2
 
1.0%
ValueCountFrequency (%)
22243 3
1.6%
22241 1
 
0.5%
22240 3
1.6%
22238 2
 
1.0%
22237 1
 
0.5%
22231 5
2.6%
22230 3
1.6%
22229 5
2.6%
22228 3
1.6%
22227 1
 
0.5%

도로명주소
Text

UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-28T15:22:03.197807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length43
Mean length33.162304
Min length19

Characters and Unicode

Total characters6334
Distinct characters206
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

Unique191 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 낙섬동로 135 208동 102호(용현동, LH미추홀퍼스트)
2nd row인천광역시 미추홀구 용정공원로 33 106동 101호(용현동,SK스카이뷰)
3rd row인천광역시 미추홀구 용정공원로 33 sk스카이뷰아파트 관리동 어린이집
4th row인천광역시 미추홀구 용정공원로 33 SK스카이뷰 126동 101호
5th row인천광역시 미추홀구 승학길 77-1
ValueCountFrequency (%)
인천광역시 192
 
17.3%
미추홀구 191
 
17.3%
주안동 28
 
2.5%
용현동 11
 
1.0%
숭의동 11
 
1.0%
도화동 11
 
1.0%
매소홀로 10
 
0.9%
경원대로 10
 
0.9%
관리동 9
 
0.8%
학익동 8
 
0.7%
Other values (396) 626
56.5%
2024-01-28T15:22:03.555439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
917
 
14.5%
1 284
 
4.5%
동 221
 
3.5%
인 219
 
3.5%
홀 219
 
3.5%
미 208
 
3.3%
추 205
 
3.2%
천 200
 
3.2%
광 195
 
3.1%
역 194
 
3.1%
Other values (196) 3472
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3945
62.3%
Decimal Number 1111
 
17.5%
Space Separator 917
 
14.5%
Close Punctuation 127
 
2.0%
Open Punctuation 127
 
2.0%
Other Punctuation 56
 
0.9%
Dash Punctuation 30
 
0.5%
Uppercase Letter 13
 
0.2%
Lowercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 221
 
5.6%
인 219
 
5.6%
홀 219
 
5.6%
미 208
 
5.3%
추 205
 
5.2%
천 200
 
5.1%
광 195
 
4.9%
역 194
 
4.9%
시 194
 
4.9%
구 194
 
4.9%
Other values (172) 1896
48.1%
Decimal Number
ValueCountFrequency (%)
1 284
25.6%
0 149
13.4%
2 147
13.2%
3 112
 
10.1%
4 84
 
7.6%
6 78
 
7.0%
7 74
 
6.7%
8 72
 
6.5%
5 65
 
5.9%
9 46
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
30.8%
K 4
30.8%
H 2
15.4%
L 2
15.4%
A 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
k 2
25.0%
s 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 55
98.2%
. 1
 
1.8%
Space Separator
ValueCountFrequency (%)
917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3945
62.3%
Common 2368
37.4%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 221
 
5.6%
인 219
 
5.6%
홀 219
 
5.6%
미 208
 
5.3%
추 205
 
5.2%
천 200
 
5.1%
광 195
 
4.9%
역 194
 
4.9%
시 194
 
4.9%
구 194
 
4.9%
Other values (172) 1896
48.1%
Common
ValueCountFrequency (%)
917
38.7%
1 284
 
12.0%
0 149
 
6.3%
2 147
 
6.2%
) 127
 
5.4%
( 127
 
5.4%
3 112
 
4.7%
4 84
 
3.5%
6 78
 
3.3%
7 74
 
3.1%
Other values (6) 269
 
11.4%
Latin
ValueCountFrequency (%)
S 4
19.0%
K 4
19.0%
e 4
19.0%
k 2
9.5%
s 2
9.5%
H 2
9.5%
L 2
9.5%
A 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3945
62.3%
ASCII 2389
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
917
38.4%
1 284
 
11.9%
0 149
 
6.2%
2 147
 
6.2%
) 127
 
5.3%
( 127
 
5.3%
3 112
 
4.7%
4 84
 
3.5%
6 78
 
3.3%
7 74
 
3.1%
Other values (14) 290
 
12.1%
Hangul
ValueCountFrequency (%)
동 221
 
5.6%
인 219
 
5.6%
홀 219
 
5.6%
미 208
 
5.3%
추 205
 
5.2%
천 200
 
5.1%
광 195
 
4.9%
역 194
 
4.9%
시 194
 
4.9%
구 194
 
4.9%
Other values (172) 1896
48.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct174
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.456794
Minimum37.434371
Maximum37.56647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:03.663682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.434371
5-th percentile37.439815
Q137.446709
median37.455352
Q337.462561
95-th percentile37.473485
Maximum37.56647
Range0.13209907
Interquartile range (IQR)0.0158526

Descriptive statistics

Standard deviation0.017215736
Coefficient of variation (CV)0.00045961584
Kurtosis24.074171
Mean37.456794
Median Absolute Deviation (MAD)0.00763046
Skewness4.0474316
Sum7154.2476
Variance0.00029638156
MonotonicityNot monotonic
2024-01-28T15:22:03.773644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.44278566 3
 
1.6%
37.56647 3
 
1.6%
37.43981545 3
 
1.6%
37.4609903 3
 
1.6%
37.44022384 3
 
1.6%
37.4560325 2
 
1.0%
37.44508305 2
 
1.0%
37.45853374 2
 
1.0%
37.44892382 2
 
1.0%
37.4415019 2
 
1.0%
Other values (164) 166
86.9%
ValueCountFrequency (%)
37.43437093 1
 
0.5%
37.43717965 1
 
0.5%
37.43719482 1
 
0.5%
37.43779415 1
 
0.5%
37.43783647 1
 
0.5%
37.43823929 1
 
0.5%
37.43866232 1
 
0.5%
37.43925843 1
 
0.5%
37.43953455 1
 
0.5%
37.43981545 3
1.6%
ValueCountFrequency (%)
37.56647 3
1.6%
37.47722206 1
 
0.5%
37.47682889 1
 
0.5%
37.47603881 1
 
0.5%
37.47558322 1
 
0.5%
37.47501281 1
 
0.5%
37.47442803 1
 
0.5%
37.47348682 1
 
0.5%
37.47348351 1
 
0.5%
37.47317004 1
 
0.5%

경도
Real number (ℝ)

Distinct174
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.67102
Minimum126.63303
Maximum126.97796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:03.879138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63303
5-th percentile126.63742
Q1126.65116
median126.66632
Q3126.68325
95-th percentile126.69377
Maximum126.97796
Range0.3449347
Interquartile range (IQR)0.03209175

Descriptive statistics

Standard deviation0.042754258
Coefficient of variation (CV)0.000337522
Kurtosis40.316659
Mean126.67102
Median Absolute Deviation (MAD)0.0161771
Skewness5.8339705
Sum24194.166
Variance0.0018279266
MonotonicityNot monotonic
2024-01-28T15:22:03.981375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6615216 3
 
1.6%
126.977963 3
 
1.6%
126.6641125 3
 
1.6%
126.69058 3
 
1.6%
126.6726086 3
 
1.6%
126.6421685 2
 
1.0%
126.6423857 2
 
1.0%
126.6378621 2
 
1.0%
126.6362565 2
 
1.0%
126.6596314 2
 
1.0%
Other values (164) 166
86.9%
ValueCountFrequency (%)
126.6330283 1
0.5%
126.6333351 1
0.5%
126.6350653 1
0.5%
126.6360895 1
0.5%
126.6361884 1
0.5%
126.6362565 2
1.0%
126.6366023 1
0.5%
126.6368868 1
0.5%
126.6369991 1
0.5%
126.6378399 1
0.5%
ValueCountFrequency (%)
126.977963 3
1.6%
126.6968583 1
 
0.5%
126.6956159 1
 
0.5%
126.6955368 1
 
0.5%
126.695336 1
 
0.5%
126.6942154 1
 
0.5%
126.6940924 1
 
0.5%
126.6938988 1
 
0.5%
126.6936397 1
 
0.5%
126.693322 2
1.0%

연락처
Text

UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-28T15:22:04.189927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.026178
Min length12

Characters and Unicode

Total characters2297
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

Unique191 ?
Unique (%)100.0%

Sample

1st row032-881-7967
2nd row032-204-5080
3rd row032-888-7550
4th row032-888-0813
5th row032-425-4557
ValueCountFrequency (%)
032-881-7967 1
 
0.5%
032-721-0590 1
 
0.5%
032-875-4848 1
 
0.5%
032-238-3900 1
 
0.5%
032-883-0898 1
 
0.5%
032-864-7667 1
 
0.5%
032-884-3472 1
 
0.5%
032-875-3007 1
 
0.5%
032-214-3885 1
 
0.5%
070-8192-3000 1
 
0.5%
Other values (181) 181
94.8%
2024-01-28T15:22:04.497955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 382
16.6%
2 356
15.5%
0 318
13.8%
3 310
13.5%
8 229
10.0%
7 153
6.7%
4 138
 
6.0%
6 126
 
5.5%
1 101
 
4.4%
5 101
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1915
83.4%
Dash Punctuation 382
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 356
18.6%
0 318
16.6%
3 310
16.2%
8 229
12.0%
7 153
8.0%
4 138
 
7.2%
6 126
 
6.6%
1 101
 
5.3%
5 101
 
5.3%
9 83
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 382
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2297
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 382
16.6%
2 356
15.5%
0 318
13.8%
3 310
13.5%
8 229
10.0%
7 153
6.7%
4 138
 
6.0%
6 126
 
5.5%
1 101
 
4.4%
5 101
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2297
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 382
16.6%
2 356
15.5%
0 318
13.8%
3 310
13.5%
8 229
10.0%
7 153
6.7%
4 138
 
6.0%
6 126
 
5.5%
1 101
 
4.4%
5 101
 
4.4%

어린이집팩스번호
Text

MISSING 

Distinct162
Distinct (%)99.4%
Missing28
Missing (%)14.7%
Memory size1.6 KiB
2024-01-28T15:22:04.703433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.110429
Min length12

Characters and Unicode

Total characters1974
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

Unique161 ?
Unique (%)98.8%

Sample

1st row032-881-7967
2nd row032-204-5082
3rd row032-888-7553
4th row032-888-0813
5th row032-425-4558
ValueCountFrequency (%)
032-429-4177 2
 
1.2%
032-886-0074 1
 
0.6%
032-000-0000 1
 
0.6%
070-8192-3005 1
 
0.6%
032-881-7967 1
 
0.6%
032-862-6066 1
 
0.6%
032-875-2797 1
 
0.6%
032-882-0522 1
 
0.6%
032-876-7667 1
 
0.6%
032-884-3472 1
 
0.6%
Other values (152) 152
93.3%
2024-01-28T15:22:04.992575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 326
16.5%
0 290
14.7%
2 290
14.7%
3 254
12.9%
8 181
9.2%
7 132
6.7%
4 124
 
6.3%
6 120
 
6.1%
5 90
 
4.6%
9 85
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1648
83.5%
Dash Punctuation 326
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 290
17.6%
2 290
17.6%
3 254
15.4%
8 181
11.0%
7 132
8.0%
4 124
7.5%
6 120
7.3%
5 90
 
5.5%
9 85
 
5.2%
1 82
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 326
16.5%
0 290
14.7%
2 290
14.7%
3 254
12.9%
8 181
9.2%
7 132
6.7%
4 124
 
6.3%
6 120
 
6.1%
5 90
 
4.6%
9 85
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 326
16.5%
0 290
14.7%
2 290
14.7%
3 254
12.9%
8 181
9.2%
7 132
6.7%
4 124
 
6.3%
6 120
 
6.1%
5 90
 
4.6%
9 85
 
4.3%

보육실수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.026178
Minimum2
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:05.087384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median4
Q36
95-th percentile9
Maximum15
Range13
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3270369
Coefficient of variation (CV)0.46298338
Kurtosis2.1935159
Mean5.026178
Median Absolute Deviation (MAD)1
Skewness1.3305196
Sum960
Variance5.4151006
MonotonicityNot monotonic
2024-01-28T15:22:05.171176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 63
33.0%
5 30
15.7%
4 29
15.2%
6 18
 
9.4%
7 17
 
8.9%
8 13
 
6.8%
9 10
 
5.2%
2 5
 
2.6%
12 2
 
1.0%
14 1
 
0.5%
Other values (3) 3
 
1.6%
ValueCountFrequency (%)
2 5
 
2.6%
3 63
33.0%
4 29
15.2%
5 30
15.7%
6 18
 
9.4%
7 17
 
8.9%
8 13
 
6.8%
9 10
 
5.2%
10 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
15 1
 
0.5%
14 1
 
0.5%
12 2
 
1.0%
11 1
 
0.5%
10 1
 
0.5%
9 10
 
5.2%
8 13
6.8%
7 17
8.9%
6 18
9.4%
5 30
15.7%

보육실면적_제곱미터
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.20942
Minimum33
Maximum595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:05.283753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile55.5
Q184
median157
Q3263.5
95-th percentile380.5
Maximum595
Range562
Interquartile range (IQR)179.5

Descriptive statistics

Standard deviation117.69567
Coefficient of variation (CV)0.6389232
Kurtosis0.54791054
Mean184.20942
Median Absolute Deviation (MAD)81
Skewness0.93094184
Sum35184
Variance13852.272
MonotonicityNot monotonic
2024-01-28T15:22:05.376681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 11
 
5.8%
58 5
 
2.6%
316 4
 
2.1%
56 3
 
1.6%
213 3
 
1.6%
54 3
 
1.6%
85 3
 
1.6%
59 3
 
1.6%
119 3
 
1.6%
125 3
 
1.6%
Other values (121) 150
78.5%
ValueCountFrequency (%)
33 1
 
0.5%
47 1
 
0.5%
48 1
 
0.5%
53 2
 
1.0%
54 3
1.6%
55 2
 
1.0%
56 3
1.6%
57 1
 
0.5%
58 5
2.6%
59 3
1.6%
ValueCountFrequency (%)
595 1
0.5%
593 1
0.5%
504 1
0.5%
488 1
0.5%
463 2
1.0%
459 1
0.5%
407 1
0.5%
399 1
0.5%
385 1
0.5%
376 1
0.5%

놀이터수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
94 
1
62 
2
30 
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row2

Common Values

ValueCountFrequency (%)
0 94
49.2%
1 62
32.5%
2 30
 
15.7%
3 5
 
2.6%

Length

2024-01-28T15:22:05.470962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:22:05.544951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 94
49.2%
1 62
32.5%
2 30
 
15.7%
3 5
 
2.6%

보육교직원수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.842932
Minimum0
Maximum32
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:05.624132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median10
Q314
95-th percentile22.5
Maximum32
Range32
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.018956
Coefficient of variation (CV)0.5551041
Kurtosis1.2624696
Mean10.842932
Median Absolute Deviation (MAD)4
Skewness1.0098006
Sum2071
Variance36.227831
MonotonicityNot monotonic
2024-01-28T15:22:05.709788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
7 25
13.1%
13 17
 
8.9%
6 16
 
8.4%
10 16
 
8.4%
5 13
 
6.8%
8 12
 
6.3%
12 10
 
5.2%
9 9
 
4.7%
15 8
 
4.2%
17 7
 
3.7%
Other values (18) 58
30.4%
ValueCountFrequency (%)
0 1
 
0.5%
1 4
 
2.1%
2 1
 
0.5%
3 6
 
3.1%
4 5
 
2.6%
5 13
6.8%
6 16
8.4%
7 25
13.1%
8 12
6.3%
9 9
 
4.7%
ValueCountFrequency (%)
32 2
 
1.0%
31 1
 
0.5%
26 2
 
1.0%
25 2
 
1.0%
24 1
 
0.5%
23 2
 
1.0%
22 1
 
0.5%
20 4
2.1%
19 4
2.1%
18 6
3.1%

정원수
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.089005
Minimum11
Maximum220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:05.815347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile18.5
Q120
median45
Q374.5
95-th percentile121.5
Maximum220
Range209
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation38.288482
Coefficient of variation (CV)0.72121302
Kurtosis2.8164084
Mean53.089005
Median Absolute Deviation (MAD)25
Skewness1.4564489
Sum10140
Variance1466.0078
MonotonicityNot monotonic
2024-01-28T15:22:05.908018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 50
26.2%
49 9
 
4.7%
19 8
 
4.2%
84 5
 
2.6%
73 4
 
2.1%
67 3
 
1.6%
37 3
 
1.6%
94 3
 
1.6%
77 3
 
1.6%
50 3
 
1.6%
Other values (69) 100
52.4%
ValueCountFrequency (%)
11 2
 
1.0%
12 1
 
0.5%
14 1
 
0.5%
16 2
 
1.0%
17 2
 
1.0%
18 2
 
1.0%
19 8
 
4.2%
20 50
26.2%
22 1
 
0.5%
23 1
 
0.5%
ValueCountFrequency (%)
220 1
0.5%
205 1
0.5%
184 1
0.5%
159 1
0.5%
156 2
1.0%
136 1
0.5%
129 2
1.0%
123 1
0.5%
120 1
0.5%
118 1
0.5%

현원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.424084
Minimum0
Maximum173
Zeros4
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T15:22:05.999781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q116
median27
Q353
95-th percentile90
Maximum173
Range173
Interquartile range (IQR)37

Descriptive statistics

Standard deviation30.39171
Coefficient of variation (CV)0.81208963
Kurtosis3.4739757
Mean37.424084
Median Absolute Deviation (MAD)14
Skewness1.6250224
Sum7148
Variance923.65605
MonotonicityNot monotonic
2024-01-28T15:22:06.101120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17 11
 
5.8%
16 10
 
5.2%
20 10
 
5.2%
19 9
 
4.7%
18 7
 
3.7%
15 6
 
3.1%
12 6
 
3.1%
14 5
 
2.6%
27 4
 
2.1%
58 4
 
2.1%
Other values (67) 119
62.3%
ValueCountFrequency (%)
0 4
2.1%
1 2
 
1.0%
2 1
 
0.5%
4 1
 
0.5%
5 3
1.6%
8 3
1.6%
9 2
 
1.0%
10 1
 
0.5%
11 1
 
0.5%
12 6
3.1%
ValueCountFrequency (%)
173 1
0.5%
165 1
0.5%
139 1
0.5%
129 2
1.0%
111 1
0.5%
99 1
0.5%
97 1
0.5%
92 1
0.5%
91 1
0.5%
89 1
0.5%

인가일자
Date

Distinct172
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1982-05-15 00:00:00
Maximum2023-05-24 00:00:00
2024-01-28T15:22:06.201041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:06.321862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

통학차량운영
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
미운영
119 
운영(신고)
72 

Length

Max length6
Median length3
Mean length4.1308901
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미운영
2nd row미운영
3rd row미운영
4th row미운영
5th row운영(신고)

Common Values

ValueCountFrequency (%)
미운영 119
62.3%
운영(신고) 72
37.7%

Length

2024-01-28T15:22:06.425869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:22:06.502028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미운영 119
62.3%
운영(신고 72
37.7%

Interactions

2024-01-28T15:22:00.822535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:56.800900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.403759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.205873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.726489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.228303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.778798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.308564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.901635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:56.874036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.507780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.275516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.792864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.293248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.845564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.371511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.981675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:56.954995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.578071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.341479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.858296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.363858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.911004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.434130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:01.052989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.044730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.844977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.406328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.924187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.434329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.979216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.495125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:01.116944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.134938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.910366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.469554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.986555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.515888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.046061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.558784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:01.178195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.202363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.987058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.533586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.045631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.581720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.108264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.634597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:01.243868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.270276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.067386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.600840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.108329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.646655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.172520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.707273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:01.299491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:57.329612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.139276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:58.657519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.162793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:21:59.706978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.232680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:22:00.761212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:22:06.558604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어린이집유형구분우편번호위도경도보육실수보육실면적_제곱미터놀이터수보육교직원수정원수현원수통학차량운영
어린이집유형구분1.0000.2590.1520.1960.6730.6890.4950.5590.7260.4850.898
우편번호0.2591.0000.8800.7620.0000.0350.1680.3050.1610.3440.222
위도0.1520.8801.0000.7350.0000.0000.0700.1890.0000.0000.064
경도0.1960.7620.7351.0000.0000.1110.1630.0000.0000.0000.068
보육실수0.6730.0000.0000.0001.0000.8060.6070.6970.8180.7480.478
보육실면적_제곱미터0.6890.0350.0000.1110.8061.0000.6910.8250.9500.8680.599
놀이터수0.4950.1680.0700.1630.6070.6911.0000.6040.7330.7020.473
보육교직원수0.5590.3050.1890.0000.6970.8250.6041.0000.8660.9130.414
정원수0.7260.1610.0000.0000.8180.9500.7330.8661.0000.9220.550
현원수0.4850.3440.0000.0000.7480.8680.7020.9130.9221.0000.488
통학차량운영0.8980.2220.0640.0680.4780.5990.4730.4140.5500.4881.000
2024-01-28T15:22:06.656528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어린이집유형구분통학차량운영놀이터수
어린이집유형구분1.0000.7090.339
통학차량운영0.7091.0000.318
놀이터수0.3390.3181.000
2024-01-28T15:22:06.725772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호위도경도보육실수보육실면적_제곱미터보육교직원수정원수현원수어린이집유형구분놀이터수통학차량운영
우편번호1.000-0.8540.0620.0060.033-0.1230.002-0.1580.1310.1000.173
위도-0.8541.0000.0280.040-0.0090.1170.0330.1440.1020.0560.076
경도0.0620.0281.0000.1240.1190.0650.1330.0440.0810.1530.112
보육실수0.0060.0400.1241.0000.8250.6820.8660.7480.4080.4320.470
보육실면적_제곱미터0.033-0.0090.1190.8251.0000.7450.9180.7730.4470.4840.453
보육교직원수-0.1230.1170.0650.6820.7451.0000.7690.9040.3390.4130.309
정원수0.0020.0330.1330.8660.9180.7691.0000.8530.4880.5300.415
현원수-0.1580.1440.0440.7480.7730.9040.8531.0000.2770.4950.367
어린이집유형구분0.1310.1020.0810.4080.4470.3390.4880.2771.0000.3390.709
놀이터수0.1000.0560.1530.4320.4840.4130.5300.4950.3391.0000.318
통학차량운영0.1730.0760.1120.4700.4530.3090.4150.3670.7090.3181.000

Missing values

2024-01-28T15:22:01.416908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:22:01.570316image/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.
2024-01-28T15:22:01.660861image/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

시군구명어린이집명어린이집유형구분우편번호도로명주소위도경도연락처어린이집팩스번호보육실수보육실면적_제곱미터놀이터수보육교직원수정원수현원수인가일자통학차량운영
0인천광역시 미추홀구LH아이세상어린이집가정22176인천광역시 미추홀구 낙섬동로 135 208동 102호(용현동, LH미추홀퍼스트)37.458556126.639218032-881-7967032-881-79673470617162007-10-29미운영
1인천광역시 미추홀구SK아이숲어린이집가정22188인천광역시 미추홀구 용정공원로 33 106동 101호(용현동,SK스카이뷰)37.449455126.643375032-204-5080032-204-50823580720202016-11-22미운영
2인천광역시 미추홀구SK해사랑어린이집민간22188인천광역시 미추홀구 용정공원로 33 sk스카이뷰아파트 관리동 어린이집37.452015126.645063032-888-7550032-888-7553828511699992017-03-14미운영
3인천광역시 미추홀구SK행복아이사랑어린이집가정22188인천광역시 미추홀구 용정공원로 33 SK스카이뷰 126동 101호37.45083126.645301032-888-0813032-888-08133560720172016-09-30미운영
4인천광역시 미추홀구가온누리어린이집민간22231인천광역시 미추홀구 승학길 77-137.442913126.67934032-425-4557032-425-4558725321592572000-02-28운영(신고)
5인천광역시 미추홀구개나리어린이집국공립22210인천광역시 미추홀구 재넘이길19번길 18 (학익동)37.446691126.665509032-863-5302032-863-5301731031896691986-09-20미운영
6인천광역시 미추홀구고은별어린이집가정22143인천광역시 미추홀구 경원대로 884 더월드스테이트아파트 106동 101호37.46099126.69058032-429-7942032-446-79423540620192008-07-10미운영
7인천광역시 미추홀구곰돌이어린이집가정22222인천광역시 미추홀구 매소홀로475번길 18 18동 107호(학익동, 신동아아파트)37.440224126.672609032-863-0976070-8192-99243841619132005-01-29미운영
8인천광역시 미추홀구곰아저씨와친구들어린이집가정22186인천광역시 미추홀구 토금북로28번길 8 (용현동)37.454212126.636999070-7533-2764032-203-9009384111902009-09-21미운영
9인천광역시 미추홀구관교어린이집민간22243인천광역시 미추홀구 경원대로658번길 29-1237.443044126.693899032-425-4177032-429-4177531621273452001-01-02미운영
시군구명어린이집명어린이집유형구분우편번호도로명주소위도경도연락처어린이집팩스번호보육실수보육실면적_제곱미터놀이터수보육교직원수정원수현원수인가일자통학차량운영
181인천광역시 미추홀구해맑은어린이집가정22226인천광역시 미추홀구 소성로 240 5동 101호(학익동, 영남아파트)37.438239126.67393032-872-5520<NA>360011412003-02-11미운영
182인천광역시 미추홀구해솔어린이집국공립22186인천광역시 미추홀구 토금남로27번길 22 구립해솔어린이집37.45261126.636188032-882-4223032-882-4226725822097882007-12-01미운영
183인천광역시 미추홀구해오름어린이집민간22229인천광역시 미추홀구 인하로330번길 29 (주안동)37.446386126.685738032-433-6400032-433-6400623212084671996-03-01운영(신고)
184인천광역시 미추홀구해피아이어린이집가정22142인천광역시 미추홀구 주안로193번길 12-25 103호(주안동, 대한빌라)37.464143126.692238032-428-8623032-423-8623233031212009-03-03운영(신고)
185인천광역시 미추홀구행복한용마루어린이집국공립22176인천광역시 미추홀구 낙섬중로 12937.458588126.642213032-891-7945032-891-7940421311357532019-02-19미운영
186인천광역시 미추홀구현광어린이집가정22225인천광역시 미추홀구 매소홀로418번길 14-13 101동 106호(학익동, 학익현광2차아파트)37.437836126.654315032-867-0133032-867-01333620920172008-03-20미운영
187인천광역시 미추홀구현대아이사랑어린이집가정22140인천광역시 미추홀구 경인로 395 1동 104호(주안동, 현대아파트)37.45923126.683701032-446-0365032-446-03653840620202010-03-08운영(신고)
188인천광역시 미추홀구호산나어린이집민간22148인천광역시 미추홀구 동주길119번길 15-3237.455891126.683948032-434-0650032-434-065162200749172004-01-28미운영
189인천광역시 미추홀구휴먼빌어린이집가정22156인천광역시 미추홀구 한나루로550번길 63 101동 106호(주안동, 휴먼빌A 101동)37.455352126.673605032-875-5432032-872-66893790620162007-03-02미운영
190인천광역시 미추홀구흰돌어린이집민간22114인천광역시 미추홀구 숙골로112번길 12 관리동어린이집37.471976126.663552032-862-2218<NA>511901345402017-05-01미운영