Overview

Dataset statistics

Number of variables8
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory68.8 B

Variable types

Categorical1
Text4
Numeric3

Dataset

Description연수구 관내 학교 현황 목록입니다.(공립,사립 초등학교, 중학교, 고등학교 목록과 각 학교별 학생수, 주소, 연락처 등)
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15039731&srcSe=7661IVAWM27C61E190

Alerts

학생수 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 학생수 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도High correlation
학교명 has unique valuesUnique
주소 has unique valuesUnique
교무실 has unique valuesUnique
행정실 has unique valuesUnique

Reproduction

Analysis started2024-04-20 23:10:25.071256
Analysis finished2024-04-20 23:10:28.555654
Duration3.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size688.0 B
초등학교
33 
중학교
19 
고등학교
16 
대안학교
 
1
특수학교
 
1

Length

Max length4
Median length4
Mean length3.7285714
Min length3

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 33
47.1%
중학교 19
27.1%
고등학교 16
22.9%
대안학교 1
 
1.4%
특수학교 1
 
1.4%

Length

2024-04-21T08:10:28.770347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:10:29.100973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 33
47.1%
중학교 19
27.1%
고등학교 16
22.9%
대안학교 1
 
1.4%
특수학교 1
 
1.4%

학교명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2024-04-21T08:10:30.002576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10.5
Mean length6.5
Min length4

Characters and Unicode

Total characters455
Distinct characters70
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

Unique70 ?
Unique (%)100.0%

Sample

1st row능허대초등학교
2nd row동막초등학교
3rd row동춘초등학교
4th row먼우금초등학교
5th row명선초등학교
ValueCountFrequency (%)
인천 2
 
2.8%
능허대초등학교 1
 
1.4%
연수고등학교 1
 
1.4%
청학중학교 1
 
1.4%
청량중학교 1
 
1.4%
인천현송중학교 1
 
1.4%
인천해송중학교 1
 
1.4%
인천중학교 1
 
1.4%
인천예송중학교 1
 
1.4%
옥련여자고등학교 1
 
1.4%
Other values (61) 61
84.7%
2024-04-21T08:10:31.579176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 78
17.1%
교 70
15.4%
등 49
10.8%
초 33
 
7.3%
송 22
 
4.8%
중 20
 
4.4%
인 18
 
4.0%
고 17
 
3.7%
천 17
 
3.7%
연 11
 
2.4%
Other values (60) 120
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
99.6%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 78
17.2%
교 70
15.5%
등 49
10.8%
초 33
 
7.3%
송 22
 
4.9%
중 20
 
4.4%
인 18
 
4.0%
고 17
 
3.8%
천 17
 
3.8%
연 11
 
2.4%
Other values (59) 118
26.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
99.6%
Common 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 78
17.2%
교 70
15.5%
등 49
10.8%
초 33
 
7.3%
송 22
 
4.9%
중 20
 
4.4%
인 18
 
4.0%
고 17
 
3.8%
천 17
 
3.8%
연 11
 
2.4%
Other values (59) 118
26.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
99.6%
ASCII 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 78
17.2%
교 70
15.5%
등 49
10.8%
초 33
 
7.3%
송 22
 
4.9%
중 20
 
4.4%
인 18
 
4.0%
고 17
 
3.8%
천 17
 
3.8%
연 11
 
2.4%
Other values (59) 118
26.0%
ASCII
ValueCountFrequency (%)
2
100.0%

학생수
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean732.87143
Minimum40
Maximum1757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-04-21T08:10:31.978284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile267.35
Q1475
median709
Q3900.25
95-th percentile1314.8
Maximum1757
Range1717
Interquartile range (IQR)425.25

Descriptive statistics

Standard deviation346.07626
Coefficient of variation (CV)0.47221961
Kurtosis0.70651424
Mean732.87143
Median Absolute Deviation (MAD)223
Skewness0.75350112
Sum51301
Variance119768.78
MonotonicityNot monotonic
2024-04-21T08:10:32.416845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
475 2
 
2.9%
850 2
 
2.9%
345 2
 
2.9%
915 1
 
1.4%
320 1
 
1.4%
886 1
 
1.4%
464 1
 
1.4%
291 1
 
1.4%
1034 1
 
1.4%
858 1
 
1.4%
Other values (57) 57
81.4%
ValueCountFrequency (%)
40 1
1.4%
220 1
1.4%
240 1
1.4%
248 1
1.4%
291 1
1.4%
320 1
1.4%
345 2
2.9%
363 1
1.4%
388 1
1.4%
394 1
1.4%
ValueCountFrequency (%)
1757 1
1.4%
1690 1
1.4%
1537 1
1.4%
1349 1
1.4%
1273 1
1.4%
1249 1
1.4%
1233 1
1.4%
1228 1
1.4%
1083 1
1.4%
1072 1
1.4%

주소
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2024-04-21T08:10:33.465283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.0714286
Min length6

Characters and Unicode

Total characters635
Distinct characters74
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

Unique70 ?
Unique (%)100.0%

Sample

1st row한진로 12
2nd row원인재로 36
3rd row앵고개로 224
4th row해돋이로84번길 33
5th row컨벤시아대로42번길 64
ValueCountFrequency (%)
원인재로 9
 
6.2%
아카데미로 6
 
4.1%
함박뫼로 6
 
4.1%
먼우금로 4
 
2.8%
앵고개로 3
 
2.1%
송도교육로 3
 
2.1%
12 3
 
2.1%
송도과학로51번길 3
 
2.1%
21 2
 
1.4%
19 2
 
1.4%
Other values (90) 104
71.7%
2024-04-21T08:10:34.604023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
11.8%
로 69
 
10.9%
1 41
 
6.5%
2 41
 
6.5%
4 25
 
3.9%
5 24
 
3.8%
번 22
 
3.5%
길 22
 
3.5%
3 20
 
3.1%
6 19
 
3.0%
Other values (64) 277
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
52.9%
Decimal Number 222
35.0%
Space Separator 75
 
11.8%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 69
20.5%
번 22
 
6.5%
길 22
 
6.5%
대 13
 
3.9%
아 13
 
3.9%
재 10
 
3.0%
인 10
 
3.0%
송 10
 
3.0%
원 9
 
2.7%
도 7
 
2.1%
Other values (52) 151
44.9%
Decimal Number
ValueCountFrequency (%)
1 41
18.5%
2 41
18.5%
4 25
11.3%
5 24
10.8%
3 20
9.0%
6 19
8.6%
7 16
 
7.2%
0 16
 
7.2%
8 12
 
5.4%
9 8
 
3.6%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
52.9%
Common 299
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 69
20.5%
번 22
 
6.5%
길 22
 
6.5%
대 13
 
3.9%
아 13
 
3.9%
재 10
 
3.0%
인 10
 
3.0%
송 10
 
3.0%
원 9
 
2.7%
도 7
 
2.1%
Other values (52) 151
44.9%
Common
ValueCountFrequency (%)
75
25.1%
1 41
13.7%
2 41
13.7%
4 25
 
8.4%
5 24
 
8.0%
3 20
 
6.7%
6 19
 
6.4%
7 16
 
5.4%
0 16
 
5.4%
8 12
 
4.0%
Other values (2) 10
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 336
52.9%
ASCII 299
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
25.1%
1 41
13.7%
2 41
13.7%
4 25
 
8.4%
5 24
 
8.0%
3 20
 
6.7%
6 19
 
6.4%
7 16
 
5.4%
0 16
 
5.4%
8 12
 
4.0%
Other values (2) 10
 
3.3%
Hangul
ValueCountFrequency (%)
로 69
20.5%
번 22
 
6.5%
길 22
 
6.5%
대 13
 
3.9%
아 13
 
3.9%
재 10
 
3.0%
인 10
 
3.0%
송 10
 
3.0%
원 9
 
2.7%
도 7
 
2.1%
Other values (52) 151
44.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.405958
Minimum37.37802
Maximum37.484562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-04-21T08:10:34.849464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.37802
5-th percentile37.37802
Q137.391214
median37.406726
Q337.420929
95-th percentile37.426638
Maximum37.484562
Range0.106542
Interquartile range (IQR)0.02971475

Descriptive statistics

Standard deviation0.018974548
Coefficient of variation (CV)0.00050726003
Kurtosis2.6030473
Mean37.405958
Median Absolute Deviation (MAD)0.0146425
Skewness0.79851314
Sum2618.4171
Variance0.00036003346
MonotonicityNot monotonic
2024-04-21T08:10:35.107324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.383912 7
 
10.0%
37.37802 5
 
7.1%
37.401513 3
 
4.3%
37.392921 2
 
2.9%
37.424084 1
 
1.4%
37.3930421 1
 
1.4%
37.424427 1
 
1.4%
37.418441 1
 
1.4%
37.410367 1
 
1.4%
37.42119 1
 
1.4%
Other values (47) 47
67.1%
ValueCountFrequency (%)
37.37802 5
7.1%
37.379943 1
 
1.4%
37.380811 1
 
1.4%
37.382244 1
 
1.4%
37.383912 7
10.0%
37.389431 1
 
1.4%
37.389889 1
 
1.4%
37.390984 1
 
1.4%
37.391905 1
 
1.4%
37.392921 2
 
2.9%
ValueCountFrequency (%)
37.484562 1
1.4%
37.431319 1
1.4%
37.429155 1
1.4%
37.42668 1
1.4%
37.426586 1
1.4%
37.426219 1
1.4%
37.425903 1
1.4%
37.425555 1
1.4%
37.424427 1
1.4%
37.424146 1
1.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6659
Minimum126.61959
Maximum127.13037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-04-21T08:10:35.359950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.61959
5-th percentile126.6287
Q1126.64476
median126.65687
Q3126.67428
95-th percentile126.69255
Maximum127.13037
Range0.5107735
Interquartile range (IQR)0.0295225

Descriptive statistics

Standard deviation0.059335423
Coefficient of variation (CV)0.00046844039
Kurtosis56.254738
Mean126.6659
Median Absolute Deviation (MAD)0.013015
Skewness7.1262258
Sum8866.6129
Variance0.0035206924
MonotonicityNot monotonic
2024-04-21T08:10:35.620026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.643855 7
 
10.0%
126.628698 5
 
7.1%
126.64725 3
 
4.3%
126.646044 2
 
2.9%
126.648761 1
 
1.4%
126.6195935 1
 
1.4%
126.661515 1
 
1.4%
126.670482 1
 
1.4%
126.673046 1
 
1.4%
126.688931 1
 
1.4%
Other values (47) 47
67.1%
ValueCountFrequency (%)
126.6195935 1
 
1.4%
126.628698 5
7.1%
126.640779 1
 
1.4%
126.640813 1
 
1.4%
126.642392 1
 
1.4%
126.643855 7
10.0%
126.644336 1
 
1.4%
126.644402 1
 
1.4%
126.645844 1
 
1.4%
126.645852 1
 
1.4%
ValueCountFrequency (%)
127.130367 1
1.4%
126.700182 1
1.4%
126.698289 1
1.4%
126.694589 1
1.4%
126.690052 1
1.4%
126.688931 1
1.4%
126.688387 1
1.4%
126.686451 1
1.4%
126.681603 1
1.4%
126.680325 1
1.4%

교무실
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2024-04-21T08:10:36.504550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters840
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

Unique70 ?
Unique (%)100.0%

Sample

1st row032-837-7299
2nd row032-814-2149
3rd row032-812-5561
4th row032-629-6310
5th row032-629-7175
ValueCountFrequency (%)
032-837-7299 1
 
1.4%
032-629-9413 1
 
1.4%
032-819-8148 1
 
1.4%
032-610-6124 1
 
1.4%
032-851-6831 1
 
1.4%
032-812-1946 1
 
1.4%
032-340-8564 1
 
1.4%
032-650-3075 1
 
1.4%
032-456-3100 1
 
1.4%
032-831-1461 1
 
1.4%
Other values (60) 60
85.7%
2024-04-21T08:10:37.839386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 140
16.7%
0 138
16.4%
2 121
14.4%
3 102
12.1%
8 68
8.1%
1 59
7.0%
5 55
 
6.5%
6 52
 
6.2%
7 35
 
4.2%
9 35
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
83.3%
Dash Punctuation 140
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 138
19.7%
2 121
17.3%
3 102
14.6%
8 68
9.7%
1 59
8.4%
5 55
 
7.9%
6 52
 
7.4%
7 35
 
5.0%
9 35
 
5.0%
4 35
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 140
16.7%
0 138
16.4%
2 121
14.4%
3 102
12.1%
8 68
8.1%
1 59
7.0%
5 55
 
6.5%
6 52
 
6.2%
7 35
 
4.2%
9 35
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 140
16.7%
0 138
16.4%
2 121
14.4%
3 102
12.1%
8 68
8.1%
1 59
7.0%
5 55
 
6.5%
6 52
 
6.2%
7 35
 
4.2%
9 35
 
4.2%

행정실
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2024-04-21T08:10:38.726329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters840
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

Unique70 ?
Unique (%)100.0%

Sample

1st row032-837-7113
2nd row032-814-2149
3rd row032-821-7156
4th row032-629-6242
5th row032-629-7179
ValueCountFrequency (%)
032-837-7113 1
 
1.4%
032-629-9393 1
 
1.4%
032-819-8149 1
 
1.4%
032-610-6174 1
 
1.4%
032-851-6832 1
 
1.4%
032-811-3621 1
 
1.4%
032-340-8569 1
 
1.4%
032-650-3000 1
 
1.4%
032-456-3100 1
 
1.4%
032-831-1462 1
 
1.4%
Other values (60) 60
85.7%
2024-04-21T08:10:39.819162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 140
16.7%
0 134
16.0%
2 126
15.0%
3 110
13.1%
1 57
6.8%
8 56
 
6.7%
6 55
 
6.5%
5 46
 
5.5%
9 43
 
5.1%
7 39
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
83.3%
Dash Punctuation 140
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 134
19.1%
2 126
18.0%
3 110
15.7%
1 57
8.1%
8 56
8.0%
6 55
7.9%
5 46
 
6.6%
9 43
 
6.1%
7 39
 
5.6%
4 34
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 140
16.7%
0 134
16.0%
2 126
15.0%
3 110
13.1%
1 57
6.8%
8 56
 
6.7%
6 55
 
6.5%
5 46
 
5.5%
9 43
 
5.1%
7 39
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 140
16.7%
0 134
16.0%
2 126
15.0%
3 110
13.1%
1 57
6.8%
8 56
 
6.7%
6 55
 
6.5%
5 46
 
5.5%
9 43
 
5.1%
7 39
 
4.6%

Interactions

2024-04-21T08:10:27.157122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:25.663132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:26.417045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:27.408632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:25.916087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:26.671717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:27.653795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:26.167549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:10:26.911566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:10:39.983535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분학교명학생수주소위도경도교무실행정실
구분1.0001.0000.8211.0000.0000.0001.0001.000
학교명1.0001.0001.0001.0001.0001.0001.0001.000
학생수0.8211.0001.0001.0000.3030.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.000
위도0.0001.0000.3031.0001.0000.8291.0001.000
경도0.0001.0000.0001.0000.8291.0001.0001.000
교무실1.0001.0001.0001.0001.0001.0001.0001.000
행정실1.0001.0001.0001.0001.0001.0001.0001.000
2024-04-21T08:10:40.237824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학생수위도경도구분
학생수1.000-0.513-0.4520.460
위도-0.5131.0000.5690.000
경도-0.4520.5691.0000.000
구분0.4600.0000.0001.000

Missing values

2024-04-21T08:10:27.992152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:10:28.402140image/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

구분학교명학생수주소위도경도교무실행정실
0초등학교능허대초등학교858한진로 1237.424084126.648761032-837-7299032-837-7113
1초등학교동막초등학교484원인재로 3637.40267126.674402032-814-2149032-814-2149
2초등학교동춘초등학교629앵고개로 22437.409803126.668643032-812-5561032-821-7156
3초등학교먼우금초등학교798해돋이로84번길 3337.392941126.65432032-629-6310032-629-6242
4초등학교명선초등학교1043컨벤시아대로42번길 6437.401513126.64725032-629-7175032-629-7179
5초등학교문남초등학교610먼우금로 27337.42098126.679399032-815-2078032-815-2079
6초등학교미송초등학교1690아카데미로 66737.37802126.628698032-509-1004032-509-1000
7초등학교박문초등학교485봉재산로 138-2237.403033126.665469032-810-8595032-810-8591
8초등학교새봄초등학교499앵고개로 104번길 3437.412785126.656922032-455-8845032-455-8811
9초등학교서면초등학교475먼우금로 5437.403746126.670646032-819-0291032-819-0294
구분학교명학생수주소위도경도교무실행정실
60고등학교인천생활과학고등학교533함박뫼로 10337.423678126.67823032-820-6525032-820-6505
61고등학교인천해양과학고등학교449능허대로 7137.425903126.640813032-627-6867032-627-6852
62고등학교인천바이오과학고등학교412용담로 1237.420478126.668551032-817-0121032-817-0124
63고등학교인천과학예술영재학교240아카데미로 19237.37802126.628698032-890-6752032-890-6714
64고등학교박문여자고등학교744송도과학로51번길 1637.383912126.643855032-621-4663032-550-1940
65고등학교송도고등학교841독배로 9137.429155126.644336032-627-4080032-627-4080
66고등학교인천대건고등학교850능허대로 43737.402253126.665351032-822-0451032-822-0451
67고등학교인천 포스코고등학교689컨벤시아대로42번길 5037.401513126.64725032-850-8620032-850-8610
68대안학교인천 청담고등학교40앵고개로 13237.411807126.664996032-833-2014032-833-2014
69특수학교연일학교248함박뫼로 20837.420293126.688387032-816-6473032-816-6472