Overview

Dataset statistics

Number of variables15
Number of observations794
Missing cells340
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.4 KiB
Average record size in memory128.2 B

Variable types

Categorical4
Text4
Numeric7

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,독립편성학급수,오후재편성학급수,운영시간,독립편성참여원아수,오후재편성참여원아수,정규교사수,기간제교사수,강사수,공시차수,주소
Author한국교육학술정보원
URLhttps://data.seoul.go.kr/dataList/OA-22297/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
독립편성학급수 is highly overall correlated with 독립편성참여원아수High correlation
오후재편성학급수 is highly overall correlated with 독립편성참여원아수 and 1 other fieldsHigh correlation
독립편성참여원아수 is highly overall correlated with 독립편성학급수 and 1 other fieldsHigh correlation
오후재편성참여원아수 is highly overall correlated with 오후재편성학급수 and 1 other fieldsHigh correlation
정규교사수 is highly overall correlated with 오후재편성참여원아수 and 1 other fieldsHigh correlation
강사수 is highly overall correlated with 정규교사수 and 1 other fieldsHigh correlation
설립유형 is highly overall correlated with 강사수High correlation
공시차수 is highly imbalanced (77.0%)Imbalance
독립편성참여원아수 has 282 (35.5%) missing valuesMissing
오후재편성참여원아수 has 28 (3.5%) missing valuesMissing
유치원코드 has unique valuesUnique
독립편성학급수 has 717 (90.3%) zerosZeros
오후재편성학급수 has 50 (6.3%) zerosZeros
독립편성참여원아수 has 441 (55.5%) zerosZeros
오후재편성참여원아수 has 28 (3.5%) zerosZeros
정규교사수 has 318 (40.1%) zerosZeros
기간제교사수 has 709 (89.3%) zerosZeros
강사수 has 465 (58.6%) zerosZeros

Reproduction

Analysis started2024-04-21 00:21:25.015202
Analysis finished2024-04-21 00:21:33.536830
Duration8.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
서울특별시교육청
794 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시교육청 794
100.0%

Length

2024-04-21T09:21:33.598309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T09:21:33.707894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 794
100.0%

교육지원청명
Categorical

Distinct11
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
강서양천교육지원청
93 
서부교육지원청
91 
북부교육지원청
90 
남부교육지원청
88 
강동송파교육지원청
81 
Other values (6)
351 

Length

Max length9
Median length9
Mean length8.0579345
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남부교육지원청
2nd row강동송파교육지원청
3rd row강동송파교육지원청
4th row동부교육지원청
5th row동부교육지원청

Common Values

ValueCountFrequency (%)
강서양천교육지원청 93
11.7%
서부교육지원청 91
11.5%
북부교육지원청 90
11.3%
남부교육지원청 88
11.1%
강동송파교육지원청 81
10.2%
성북강북교육지원청 66
8.3%
동작관악교육지원청 62
7.8%
동부교육지원청 61
7.7%
강남서초교육지원청 61
7.7%
성동광진교육지원청 57
7.2%

Length

2024-04-21T09:21:33.832671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서양천교육지원청 93
11.7%
서부교육지원청 91
11.5%
북부교육지원청 90
11.3%
남부교육지원청 88
11.1%
강동송파교육지원청 81
10.2%
성북강북교육지원청 66
8.3%
동작관악교육지원청 62
7.8%
동부교육지원청 61
7.7%
강남서초교육지원청 61
7.7%
성동광진교육지원청 57
7.2%

유치원코드
Text

UNIQUE 

Distinct794
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-04-21T09:21:34.044038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters28584
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique794 ?
Unique (%)100.0%

Sample

1st row006b5238-ce41-4471-9ee3-4df8d24b5141
2nd row009c017d-43bd-4d9f-ac64-d217abdd570e
3rd row04a021da-cdd7-4e7e-a434-2b388c2f6b63
4th row0764f8c8-364c-495b-9fbc-b389148b7b4f
5th row076db651-036b-4bee-80ba-09f0edb4a57a
ValueCountFrequency (%)
006b5238-ce41-4471-9ee3-4df8d24b5141 1
 
0.1%
1ecec08d-08be-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-0b19-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08dd-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08de-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08e0-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08e2-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08f6-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08f7-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08f8-b044-e053-0a32095ab044 1
 
0.1%
Other values (784) 784
98.7%
2024-04-21T09:21:34.371828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4656
16.3%
- 3176
11.1%
4 3127
10.9%
e 2460
8.6%
c 2060
 
7.2%
a 1730
 
6.1%
b 1692
 
5.9%
3 1684
 
5.9%
5 1679
 
5.9%
8 1069
 
3.7%
Other values (7) 5251
18.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16056
56.2%
Lowercase Letter 9352
32.7%
Dash Punctuation 3176
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4656
29.0%
4 3127
19.5%
3 1684
 
10.5%
5 1679
 
10.5%
8 1069
 
6.7%
1 1055
 
6.6%
9 1030
 
6.4%
2 1019
 
6.3%
7 369
 
2.3%
6 368
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
e 2460
26.3%
c 2060
22.0%
a 1730
18.5%
b 1692
18.1%
d 733
 
7.8%
f 677
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 3176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19232
67.3%
Latin 9352
32.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4656
24.2%
- 3176
16.5%
4 3127
16.3%
3 1684
 
8.8%
5 1679
 
8.7%
8 1069
 
5.6%
1 1055
 
5.5%
9 1030
 
5.4%
2 1019
 
5.3%
7 369
 
1.9%
Latin
ValueCountFrequency (%)
e 2460
26.3%
c 2060
22.0%
a 1730
18.5%
b 1692
18.1%
d 733
 
7.8%
f 677
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4656
16.3%
- 3176
11.1%
4 3127
10.9%
e 2460
8.6%
c 2060
 
7.2%
a 1730
 
6.1%
b 1692
 
5.9%
3 1684
 
5.9%
5 1679
 
5.9%
8 1069
 
3.7%
Other values (7) 5251
18.4%

유치원명
Text

Distinct738
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-04-21T09:21:34.614633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.0856423
Min length4

Characters and Unicode

Total characters6420
Distinct characters298
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

Unique688 ?
Unique (%)86.6%

Sample

1st row서울정심초등학교병설유치원
2nd row서울솔방울유치원
3rd row란키즈유치원
4th row서울신현초등학교병설유치원
5th row서울신묵초등학교병설유치원
ValueCountFrequency (%)
사랑유치원 4
 
0.5%
한가람유치원 3
 
0.4%
삼성유치원 3
 
0.4%
예일유치원 3
 
0.4%
돌샘유치원 3
 
0.4%
장미유치원 2
 
0.3%
선경유치원 2
 
0.3%
꿈밭유치원 2
 
0.3%
운현유치원 2
 
0.3%
솔샘유치원 2
 
0.3%
Other values (732) 772
96.7%
2024-04-21T09:21:34.987210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 826
 
12.9%
유 805
 
12.5%
치 795
 
12.4%
서 319
 
5.0%
울 311
 
4.8%
학 267
 
4.2%
교 262
 
4.1%
등 258
 
4.0%
초 252
 
3.9%
설 251
 
3.9%
Other values (288) 2074
32.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6416
99.9%
Space Separator 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 826
 
12.9%
유 805
 
12.5%
치 795
 
12.4%
서 319
 
5.0%
울 311
 
4.8%
학 267
 
4.2%
교 262
 
4.1%
등 258
 
4.0%
초 252
 
3.9%
설 251
 
3.9%
Other values (287) 2070
32.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6416
99.9%
Common 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 826
 
12.9%
유 805
 
12.5%
치 795
 
12.4%
서 319
 
5.0%
울 311
 
4.8%
학 267
 
4.2%
교 262
 
4.1%
등 258
 
4.0%
초 252
 
3.9%
설 251
 
3.9%
Other values (287) 2070
32.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6416
99.9%
ASCII 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 826
 
12.9%
유 805
 
12.5%
치 795
 
12.4%
서 319
 
5.0%
울 311
 
4.8%
학 267
 
4.2%
교 262
 
4.1%
등 258
 
4.0%
초 252
 
3.9%
설 251
 
3.9%
Other values (287) 2070
32.3%
ASCII
ValueCountFrequency (%)
4
100.0%

설립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
사립(사인)
364 
공립(병설)
249 
사립(법인)
132 
공립(단설)
49 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공립(병설)
2nd row공립(단설)
3rd row사립(사인)
4th row공립(병설)
5th row공립(병설)

Common Values

ValueCountFrequency (%)
사립(사인) 364
45.8%
공립(병설) 249
31.4%
사립(법인) 132
 
16.6%
공립(단설) 49
 
6.2%

Length

2024-04-21T09:21:35.114583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T09:21:35.227616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 364
45.8%
공립(병설 249
31.4%
사립(법인 132
 
16.6%
공립(단설 49
 
6.2%

독립편성학급수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)1.3%
Missing6
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.32994924
Minimum0
Maximum14
Zeros717
Zeros (%)90.3%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:35.338081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3405101
Coefficient of variation (CV)4.0627766
Kurtosis39.285442
Mean0.32994924
Median Absolute Deviation (MAD)0
Skewness5.6298731
Sum260
Variance1.7969672
MonotonicityNot monotonic
2024-04-21T09:21:35.452421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 717
90.3%
1 17
 
2.1%
3 15
 
1.9%
2 11
 
1.4%
4 8
 
1.0%
6 8
 
1.0%
5 5
 
0.6%
9 3
 
0.4%
14 2
 
0.3%
8 2
 
0.3%
(Missing) 6
 
0.8%
ValueCountFrequency (%)
0 717
90.3%
1 17
 
2.1%
2 11
 
1.4%
3 15
 
1.9%
4 8
 
1.0%
5 5
 
0.6%
6 8
 
1.0%
8 2
 
0.3%
9 3
 
0.4%
14 2
 
0.3%
ValueCountFrequency (%)
14 2
 
0.3%
9 3
 
0.4%
8 2
 
0.3%
6 8
 
1.0%
5 5
 
0.6%
4 8
 
1.0%
3 15
 
1.9%
2 11
 
1.4%
1 17
 
2.1%
0 717
90.3%

오후재편성학급수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)2.2%
Missing6
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean3.1903553
Minimum0
Maximum38
Zeros50
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:35.573365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile7
Maximum38
Range38
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5022091
Coefficient of variation (CV)0.78430421
Kurtosis49.74127
Mean3.1903553
Median Absolute Deviation (MAD)1
Skewness4.487537
Sum2514
Variance6.2610504
MonotonicityNot monotonic
2024-04-21T09:21:35.734261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 208
26.2%
3 190
23.9%
1 89
11.2%
4 86
10.8%
5 62
 
7.8%
6 53
 
6.7%
0 50
 
6.3%
7 23
 
2.9%
8 7
 
0.9%
10 5
 
0.6%
Other values (7) 15
 
1.9%
(Missing) 6
 
0.8%
ValueCountFrequency (%)
0 50
 
6.3%
1 89
11.2%
2 208
26.2%
3 190
23.9%
4 86
10.8%
5 62
 
7.8%
6 53
 
6.7%
7 23
 
2.9%
8 7
 
0.9%
9 5
 
0.6%
ValueCountFrequency (%)
38 1
 
0.1%
18 1
 
0.1%
14 2
 
0.3%
13 1
 
0.1%
12 3
 
0.4%
11 2
 
0.3%
10 5
 
0.6%
9 5
 
0.6%
8 7
 
0.9%
7 23
2.9%

운영시간
Text

Distinct70
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-04-21T09:21:35.951888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters10322
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)4.0%

Sample

1st row07시30분~19시30분
2nd row07시00분~20시00분
3rd row08시00분~19시00분
4th row07시30분~19시30분
5th row07시30분~19시30분
ValueCountFrequency (%)
07시30분~19시30분 187
23.6%
07시00분~20시00분 103
13.0%
07시00분~19시00분 84
10.6%
09시00분~17시00분 53
 
6.7%
08시00분~19시00분 37
 
4.7%
09시00분~18시00분 36
 
4.5%
08시00분~18시00분 35
 
4.4%
08시00분~18시30분 29
 
3.7%
08시00분~20시00분 25
 
3.1%
07시00분~19시30분 18
 
2.3%
Other values (60) 187
23.6%
2024-04-21T09:21:36.276047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3513
34.0%
시 1588
15.4%
분 1588
15.4%
~ 794
 
7.7%
1 645
 
6.2%
3 550
 
5.3%
9 544
 
5.3%
7 541
 
5.2%
8 330
 
3.2%
2 195
 
1.9%
Other values (3) 34
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6352
61.5%
Other Letter 3176
30.8%
Math Symbol 794
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3513
55.3%
1 645
 
10.2%
3 550
 
8.7%
9 544
 
8.6%
7 541
 
8.5%
8 330
 
5.2%
2 195
 
3.1%
4 17
 
0.3%
5 11
 
0.2%
6 6
 
0.1%
Other Letter
ValueCountFrequency (%)
시 1588
50.0%
분 1588
50.0%
Math Symbol
ValueCountFrequency (%)
~ 794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7146
69.2%
Hangul 3176
30.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3513
49.2%
~ 794
 
11.1%
1 645
 
9.0%
3 550
 
7.7%
9 544
 
7.6%
7 541
 
7.6%
8 330
 
4.6%
2 195
 
2.7%
4 17
 
0.2%
5 11
 
0.2%
Hangul
ValueCountFrequency (%)
시 1588
50.0%
분 1588
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7146
69.2%
Hangul 3176
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3513
49.2%
~ 794
 
11.1%
1 645
 
9.0%
3 550
 
7.7%
9 544
 
7.6%
7 541
 
7.6%
8 330
 
4.6%
2 195
 
2.7%
4 17
 
0.2%
5 11
 
0.2%
Hangul
ValueCountFrequency (%)
시 1588
50.0%
분 1588
50.0%

독립편성참여원아수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct59
Distinct (%)11.5%
Missing282
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean9.7050781
Minimum0
Maximum344
Zeros441
Zeros (%)55.5%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:36.416307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile79.9
Maximum344
Range344
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34.884558
Coefficient of variation (CV)3.5944645
Kurtosis30.622463
Mean9.7050781
Median Absolute Deviation (MAD)0
Skewness5.0058699
Sum4969
Variance1216.9324
MonotonicityNot monotonic
2024-04-21T09:21:36.593868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 441
55.5%
18 4
 
0.5%
13 3
 
0.4%
63 2
 
0.3%
44 2
 
0.3%
3 2
 
0.3%
9 2
 
0.3%
38 2
 
0.3%
23 2
 
0.3%
116 2
 
0.3%
Other values (49) 50
 
6.3%
(Missing) 282
35.5%
ValueCountFrequency (%)
0 441
55.5%
1 1
 
0.1%
3 2
 
0.3%
6 1
 
0.1%
7 1
 
0.1%
8 1
 
0.1%
9 2
 
0.3%
10 1
 
0.1%
11 1
 
0.1%
13 3
 
0.4%
ValueCountFrequency (%)
344 1
0.1%
268 1
0.1%
225 1
0.1%
193 1
0.1%
190 1
0.1%
179 1
0.1%
166 1
0.1%
140 1
0.1%
137 1
0.1%
131 1
0.1%

오후재편성참여원아수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct176
Distinct (%)23.0%
Missing28
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean61.988251
Minimum0
Maximum408
Zeros28
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:36.768404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q129
median50.5
Q383
95-th percentile151
Maximum408
Range408
Interquartile range (IQR)54

Descriptive statistics

Standard deviation49.898392
Coefficient of variation (CV)0.80496532
Kurtosis6.3096877
Mean61.988251
Median Absolute Deviation (MAD)24.5
Skewness1.8850569
Sum47483
Variance2489.8495
MonotonicityNot monotonic
2024-04-21T09:21:36.967776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28
 
3.5%
54 18
 
2.3%
31 16
 
2.0%
36 16
 
2.0%
60 14
 
1.8%
40 12
 
1.5%
33 12
 
1.5%
26 12
 
1.5%
72 11
 
1.4%
42 11
 
1.4%
Other values (166) 616
77.6%
(Missing) 28
 
3.5%
ValueCountFrequency (%)
0 28
3.5%
1 1
 
0.1%
2 5
 
0.6%
3 7
 
0.9%
4 5
 
0.6%
5 3
 
0.4%
6 4
 
0.5%
7 6
 
0.8%
8 1
 
0.1%
10 5
 
0.6%
ValueCountFrequency (%)
408 1
0.1%
366 1
0.1%
280 2
0.3%
276 1
0.1%
258 1
0.1%
245 1
0.1%
240 1
0.1%
233 1
0.1%
228 1
0.1%
221 1
0.1%

정규교사수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)2.3%
Missing6
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean2.3426396
Minimum0
Maximum29
Zeros318
Zeros (%)40.1%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:37.122695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile7
Maximum29
Range29
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0072947
Coefficient of variation (CV)1.2837206
Kurtosis15.374514
Mean2.3426396
Median Absolute Deviation (MAD)1
Skewness2.690958
Sum1846
Variance9.0438212
MonotonicityNot monotonic
2024-04-21T09:21:37.241544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 318
40.1%
3 92
 
11.6%
2 86
 
10.8%
1 78
 
9.8%
4 62
 
7.8%
6 46
 
5.8%
5 46
 
5.8%
7 24
 
3.0%
9 10
 
1.3%
8 9
 
1.1%
Other values (8) 17
 
2.1%
ValueCountFrequency (%)
0 318
40.1%
1 78
 
9.8%
2 86
 
10.8%
3 92
 
11.6%
4 62
 
7.8%
5 46
 
5.8%
6 46
 
5.8%
7 24
 
3.0%
8 9
 
1.1%
9 10
 
1.3%
ValueCountFrequency (%)
29 1
 
0.1%
28 1
 
0.1%
18 1
 
0.1%
14 2
 
0.3%
13 2
 
0.3%
12 3
 
0.4%
11 1
 
0.1%
10 6
0.8%
9 10
1.3%
8 9
1.1%

기간제교사수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.9%
Missing6
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.19416244
Minimum0
Maximum6
Zeros709
Zeros (%)89.3%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:37.354909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.65
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.70871606
Coefficient of variation (CV)3.6501193
Kurtosis26.880486
Mean0.19416244
Median Absolute Deviation (MAD)0
Skewness4.8131295
Sum153
Variance0.50227846
MonotonicityNot monotonic
2024-04-21T09:21:37.472274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 709
89.3%
1 39
 
4.9%
2 24
 
3.0%
3 6
 
0.8%
5 4
 
0.5%
4 4
 
0.5%
6 2
 
0.3%
(Missing) 6
 
0.8%
ValueCountFrequency (%)
0 709
89.3%
1 39
 
4.9%
2 24
 
3.0%
3 6
 
0.8%
4 4
 
0.5%
5 4
 
0.5%
6 2
 
0.3%
ValueCountFrequency (%)
6 2
 
0.3%
5 4
 
0.5%
4 4
 
0.5%
3 6
 
0.8%
2 24
 
3.0%
1 39
 
4.9%
0 709
89.3%

강사수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)1.0%
Missing6
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean1.1941624
Minimum0
Maximum7
Zeros465
Zeros (%)58.6%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-21T09:21:37.595518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6617733
Coefficient of variation (CV)1.3915807
Kurtosis0.12516394
Mean1.1941624
Median Absolute Deviation (MAD)0
Skewness1.1268509
Sum941
Variance2.7614907
MonotonicityNot monotonic
2024-04-21T09:21:37.756445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 465
58.6%
2 98
 
12.3%
4 77
 
9.7%
3 70
 
8.8%
1 44
 
5.5%
5 24
 
3.0%
6 7
 
0.9%
7 3
 
0.4%
(Missing) 6
 
0.8%
ValueCountFrequency (%)
0 465
58.6%
1 44
 
5.5%
2 98
 
12.3%
3 70
 
8.8%
4 77
 
9.7%
5 24
 
3.0%
6 7
 
0.9%
7 3
 
0.4%
ValueCountFrequency (%)
7 3
 
0.4%
6 7
 
0.9%
5 24
 
3.0%
4 77
 
9.7%
3 70
 
8.8%
2 98
 
12.3%
1 44
 
5.5%
0 465
58.6%

공시차수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
20231
750 
20211
 
24
20221
 
20

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231
2nd row20231
3rd row20231
4th row20231
5th row20231

Common Values

ValueCountFrequency (%)
20231 750
94.5%
20211 24
 
3.0%
20221 20
 
2.5%

Length

2024-04-21T09:21:37.897141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T09:21:37.997763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231 750
94.5%
20211 24
 
3.0%
20221 20
 
2.5%

주소
Text

Distinct789
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-04-21T09:21:38.267829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.736776
Min length15

Characters and Unicode

Total characters14877
Distinct characters250
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

Unique785 ?
Unique (%)98.9%

Sample

1st row서울특별시 금천구 독산로78다길 89
2nd row서울특별시 송파구 오금로24길 25
3rd row서울특별시 송파구 새말로8길 22-5
4th row서울특별시 중랑구 봉화산로 188
5th row서울특별시 중랑구 동일로149길 46
ValueCountFrequency (%)
서울특별시 794
25.0%
노원구 61
 
1.9%
강서구 54
 
1.7%
송파구 48
 
1.5%
성북구 47
 
1.5%
은평구 42
 
1.3%
영등포구 39
 
1.2%
양천구 39
 
1.2%
강남구 36
 
1.1%
중랑구 34
 
1.1%
Other values (990) 1982
62.4%
2024-04-21T09:21:38.663946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2382
16.0%
서 940
 
6.3%
구 842
 
5.7%
시 806
 
5.4%
로 800
 
5.4%
울 795
 
5.3%
별 794
 
5.3%
특 794
 
5.3%
1 572
 
3.8%
길 504
 
3.4%
Other values (240) 5648
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9668
65.0%
Decimal Number 2753
 
18.5%
Space Separator 2382
 
16.0%
Dash Punctuation 74
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 940
 
9.7%
구 842
 
8.7%
시 806
 
8.3%
로 800
 
8.3%
울 795
 
8.2%
별 794
 
8.2%
특 794
 
8.2%
길 504
 
5.2%
동 192
 
2.0%
강 156
 
1.6%
Other values (228) 3045
31.5%
Decimal Number
ValueCountFrequency (%)
1 572
20.8%
2 409
14.9%
3 318
11.6%
4 275
10.0%
6 251
9.1%
5 249
9.0%
0 182
 
6.6%
7 175
 
6.4%
9 161
 
5.8%
8 161
 
5.8%
Space Separator
ValueCountFrequency (%)
2382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9668
65.0%
Common 5209
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 940
 
9.7%
구 842
 
8.7%
시 806
 
8.3%
로 800
 
8.3%
울 795
 
8.2%
별 794
 
8.2%
특 794
 
8.2%
길 504
 
5.2%
동 192
 
2.0%
강 156
 
1.6%
Other values (228) 3045
31.5%
Common
ValueCountFrequency (%)
2382
45.7%
1 572
 
11.0%
2 409
 
7.9%
3 318
 
6.1%
4 275
 
5.3%
6 251
 
4.8%
5 249
 
4.8%
0 182
 
3.5%
7 175
 
3.4%
9 161
 
3.1%
Other values (2) 235
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9668
65.0%
ASCII 5209
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2382
45.7%
1 572
 
11.0%
2 409
 
7.9%
3 318
 
6.1%
4 275
 
5.3%
6 251
 
4.8%
5 249
 
4.8%
0 182
 
3.5%
7 175
 
3.4%
9 161
 
3.1%
Other values (2) 235
 
4.5%
Hangul
ValueCountFrequency (%)
서 940
 
9.7%
구 842
 
8.7%
시 806
 
8.3%
로 800
 
8.3%
울 795
 
8.2%
별 794
 
8.2%
특 794
 
8.2%
길 504
 
5.2%
동 192
 
2.0%
강 156
 
1.6%
Other values (228) 3045
31.5%

Interactions

2024-04-21T09:21:32.326447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:27.499558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.328535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.046490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.783390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.588151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.347666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.428899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:27.669783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.432669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.155385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.910567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.690128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.486360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.531203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:27.782251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.541341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.273854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.026533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.833493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.597214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.626898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:27.892472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.641874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.373245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.165174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.926365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.706087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.734317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.007321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.755657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.469446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.266663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.026883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.813482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.828531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.119381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.852742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.574587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.375996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.135990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.908421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.923401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.223498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:28.949198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:29.676691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:30.479091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:31.239963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T09:21:32.222044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T09:21:38.769005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육지원청명설립유형독립편성학급수오후재편성학급수운영시간독립편성참여원아수오후재편성참여원아수정규교사수기간제교사수강사수공시차수
교육지원청명1.0000.1530.1210.1420.4010.0000.1600.0770.1240.0870.000
설립유형0.1531.0000.1020.3460.6950.1190.4380.4490.2100.8650.101
독립편성학급수0.1210.1021.0000.2070.3640.8880.0000.5180.1370.0000.000
오후재편성학급수0.1420.3460.2071.0000.0790.3030.9020.8300.0000.2720.130
운영시간0.4010.6950.3640.0791.0000.4880.5430.4300.4280.5550.566
독립편성참여원아수0.0000.1190.8880.3030.4881.0000.0000.6180.0000.0000.000
오후재편성참여원아수0.1600.4380.0000.9020.5430.0001.0000.8460.0000.3970.218
정규교사수0.0770.4490.5180.8300.4300.6180.8461.0000.0000.3640.056
기간제교사수0.1240.2100.1370.0000.4280.0000.0000.0001.0000.0000.000
강사수0.0870.8650.0000.2720.5550.0000.3970.3640.0001.0000.064
공시차수0.0000.1010.0000.1300.5660.0000.2180.0560.0000.0641.000
2024-04-21T09:21:38.896950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립유형공시차수교육지원청명
설립유형1.0000.0960.092
공시차수0.0961.0000.000
교육지원청명0.0920.0001.000
2024-04-21T09:21:39.214108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
독립편성학급수오후재편성학급수독립편성참여원아수오후재편성참여원아수정규교사수기간제교사수강사수교육지원청명설립유형공시차수
독립편성학급수1.000-0.4220.999-0.3280.1220.056-0.0680.0570.0460.000
오후재편성학급수-0.4221.000-0.5110.8130.391-0.023-0.0030.0730.2290.054
독립편성참여원아수0.999-0.5111.000-0.3980.1800.073-0.1140.0000.0760.000
오후재편성참여원아수-0.3280.813-0.3981.0000.537-0.002-0.2050.0720.2940.097
정규교사수0.1220.3910.1800.5371.000-0.065-0.6950.0380.3240.037
기간제교사수0.056-0.0230.073-0.002-0.0651.000-0.1290.0610.1450.000
강사수-0.068-0.003-0.114-0.205-0.695-0.1291.0000.0410.5430.040
교육지원청명0.0570.0730.0000.0720.0380.0610.0411.0000.0920.000
설립유형0.0460.2290.0760.2940.3240.1450.5430.0921.0000.096
공시차수0.0000.0540.0000.0970.0370.0000.0400.0000.0961.000

Missing values

2024-04-21T09:21:33.072347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T09:21:33.273926image/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.
2024-04-21T09:21:33.434742image/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

교육청명교육지원청명유치원코드유치원명설립유형독립편성학급수오후재편성학급수운영시간독립편성참여원아수오후재편성참여원아수정규교사수기간제교사수강사수공시차수주소
0서울특별시교육청남부교육지원청006b5238-ce41-4471-9ee3-4df8d24b5141서울정심초등학교병설유치원공립(병설)0207시30분~19시30분03000220231서울특별시 금천구 독산로78다길 89
1서울특별시교육청강동송파교육지원청009c017d-43bd-4d9f-ac64-d217abdd570e서울솔방울유치원공립(단설)0507시00분~20시00분<NA>8902320231서울특별시 송파구 오금로24길 25
2서울특별시교육청강동송파교육지원청04a021da-cdd7-4e7e-a434-2b388c2f6b63란키즈유치원사립(사인)0308시00분~19시00분07330020231서울특별시 송파구 새말로8길 22-5
3서울특별시교육청동부교육지원청0764f8c8-364c-495b-9fbc-b389148b7b4f서울신현초등학교병설유치원공립(병설)0207시30분~19시30분<NA>3601120231서울특별시 중랑구 봉화산로 188
4서울특별시교육청동부교육지원청076db651-036b-4bee-80ba-09f0edb4a57a서울신묵초등학교병설유치원공립(병설)0207시30분~19시30분02400220231서울특별시 중랑구 동일로149길 46
5서울특별시교육청서부교육지원청0783b5eb-4c00-4161-9c47-664336825e5a다우림유치원사립(사인)0308시00분~20시00분06030020221서울특별시 은평구 증산로21길 22
6서울특별시교육청서부교육지원청08d485cb-06c8-4964-bf03-ed1b178ef3fd서울소의초등학교병설유치원공립(병설)0207시00분~19시30분03400220231서울특별시 마포구 마포대로24길 42
7서울특별시교육청북부교육지원청0c4bc461-9f36-4d28-94e3-3dfb9c6cd4e3서울상계초등학교병설유치원공립(병설)0107시00분~19시30분01200120231서울특별시 노원구 상계로9길 39
8서울특별시교육청강동송파교육지원청0f7d2827-8bb2-4a0c-9926-77fca1f60a54서울송파위례유치원공립(단설)0407시00분~20시00분08000420231서울특별시 송파구 위례송파로 121
9서울특별시교육청북부교육지원청12c109c2-23b7-4e98-a3e1-57e391f3a55a서울월천초등학교병설유치원공립(병설)0207시30분~19시30분02200220231서울특별시 도봉구 노해로70길 96
교육청명교육지원청명유치원코드유치원명설립유형독립편성학급수오후재편성학급수운영시간독립편성참여원아수오후재편성참여원아수정규교사수기간제교사수강사수공시차수주소
784서울특별시교육청서부교육지원청e7796971-1ca3-445b-a672-a03730995574서울역촌유치원공립(단설)0207시00분~19시00분02000220231서울특별시 은평구 진흥로7길 25
785서울특별시교육청동작관악교육지원청ea0748a1-62aa-47ee-abcf-784398d6646d서울신림초등학교병설유치원공립(병설)0207시30분~19시30분<NA>2900220231서울특별시 관악구 문성로28길 31
786서울특별시교육청서부교육지원청eb8cde61-5718-4f14-ab59-7df432e254ee서울한서초등학교병설유치원공립(병설)0207시00분~19시00분02800220231서울특별시 마포구 대흥로24바길 27
787서울특별시교육청동부교육지원청f10d3393-f828-460a-a5ed-0a134f8ddd34라온유치원사립(사인)0208시00분~17시00분<NA>4411020231서울특별시 동대문구 답십리로48길 56
788서울특별시교육청북부교육지원청f989a1f7-1610-4bc9-8ead-ddb5fdfdfe1e서울태릉초등학교병설유치원공립(병설)0207시00분~20시00분02400220231서울특별시 노원구 노원로1길 36
789서울특별시교육청성동광진교육지원청f9b5d3fc-3b2c-4803-b37a-481ad5a11f4b서울무학초등학교병설유치원공립(병설)0207시30분~19시30분02800220231서울특별시 성동구 무학봉15길 21
790서울특별시교육청강남서초교육지원청fccf9482-0b1c-4f4b-a7e7-cffe7f40b07b서울학동초등학교병설유치원공립(병설)0207시00분~20시00분<NA>2700220231서울특별시 강남구 선릉로115길 42
791서울특별시교육청강서양천교육지원청fd885965-9f40-46c1-879e-82acd096a57e서울가양초등학교병설유치원공립(병설)0207시30분~19시30분<NA>3100220231서울특별시 강서구 허준로 186
792서울특별시교육청강동송파교육지원청fd8c9e02-86d2-48a2-a655-ca442ef5cde8서울송파초등학교병설유치원공립(병설)0207시30분~19시30분<NA>2300220231서울특별시 송파구 백제고분로 400
793서울특별시교육청강서양천교육지원청fe178e0b-2595-4d65-863b-0d8924203e02서울등명초등학교병설유치원공립(병설)0207시30분~19시30분01800220231서울특별시 강서구 강서로56나길 34