Overview

Dataset statistics

Number of variables10
Number of observations138
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.0 KiB
Average record size in memory82.0 B

Variable types

Numeric1
Categorical3
Text5
DateTime1

Dataset

Description경기도 화성시 관내 초, 중, 고등학교 학교 현황(급별, 공사립, 학교명, 주소, 전화번호 등)
Author경기도 화성시
URLhttps://www.data.go.kr/data/15052019/fileData.do

Alerts

No. is highly overall correlated with 급별High correlation
급별 is highly overall correlated with No.High correlation
No. has unique valuesUnique
학교명 has unique valuesUnique
교무실 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:10:18.539682
Analysis finished2023-12-12 20:10:19.499178
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.5
Minimum1
Maximum138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T05:10:19.594794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.85
Q135.25
median69.5
Q3103.75
95-th percentile131.15
Maximum138
Range137
Interquartile range (IQR)68.5

Descriptive statistics

Standard deviation39.981246
Coefficient of variation (CV)0.57526972
Kurtosis-1.2
Mean69.5
Median Absolute Deviation (MAD)34.5
Skewness0
Sum9591
Variance1598.5
MonotonicityStrictly increasing
2023-12-13T05:10:19.780584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
96 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
97 1
 
0.7%
105 1
 
0.7%
Other values (128) 128
92.8%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%

급별
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
초
81 
중
34 
고
21 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
초 81
58.7%
중 34
24.6%
고 21
 
15.2%
4 2
 
1.4%

Length

2023-12-13T05:10:19.982241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:20.116823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초 81
58.7%
중 34
24.6%
고 21
 
15.2%
4 2
 
1.4%

공사립
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
공립
121 
사립
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 121
87.7%
사립 17
 
12.3%

Length

2023-12-13T05:10:20.246049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:20.393247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 121
87.7%
사립 17
 
12.3%

학교명
Text

UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T05:10:20.695917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.3550725
Min length3

Characters and Unicode

Total characters463
Distinct characters113
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)100.0%

Sample

1st row갈담초
2nd row갈천초
3rd row고정초
4th row구봉초
5th row기산초
ValueCountFrequency (%)
갈담초 1
 
0.7%
솔빛중 1
 
0.7%
두레자연중 1
 
0.7%
예당중 1
 
0.7%
양감중 1
 
0.7%
안화중 1
 
0.7%
안용중 1
 
0.7%
송산중 1
 
0.7%
장안여중 1
 
0.7%
와우중 1
 
0.7%
Other values (128) 128
92.8%
2023-12-13T05:10:21.158254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 78
 
16.8%
중 36
 
7.8%
화 23
 
5.0%
고 22
 
4.8%
안 15
 
3.2%
동 14
 
3.0%
성 13
 
2.8%
송 9
 
1.9%
봉 9
 
1.9%
남 8
 
1.7%
Other values (103) 236
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 78
 
16.8%
중 36
 
7.8%
화 23
 
5.0%
고 22
 
4.8%
안 15
 
3.2%
동 14
 
3.0%
성 13
 
2.8%
송 9
 
1.9%
봉 9
 
1.9%
남 8
 
1.7%
Other values (103) 236
51.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 78
 
16.8%
중 36
 
7.8%
화 23
 
5.0%
고 22
 
4.8%
안 15
 
3.2%
동 14
 
3.0%
성 13
 
2.8%
송 9
 
1.9%
봉 9
 
1.9%
남 8
 
1.7%
Other values (103) 236
51.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 78
 
16.8%
중 36
 
7.8%
화 23
 
5.0%
고 22
 
4.8%
안 15
 
3.2%
동 14
 
3.0%
성 13
 
2.8%
송 9
 
1.9%
봉 9
 
1.9%
남 8
 
1.7%
Other values (103) 236
51.0%

주소
Text

Distinct134
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T05:10:21.450662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.782609
Min length5

Characters and Unicode

Total characters1488
Distinct characters144
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)94.2%

Sample

1st row봉담읍 갈담초교길 24
2nd row향남읍 발안로 701-23
3rd row송산면 공룡로 326
4th row병점1로 105
5th row동탄지성로 344
ValueCountFrequency (%)
향남읍 17
 
4.9%
봉담읍 11
 
3.2%
장안면 7
 
2.0%
우정읍 7
 
2.0%
동탄대로시범길 6
 
1.7%
42 5
 
1.4%
효행로 5
 
1.4%
송산면 5
 
1.4%
정남면 4
 
1.1%
동탄반석로 4
 
1.1%
Other values (218) 278
79.7%
2023-12-13T05:10:21.868369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
 
15.3%
로 102
 
6.9%
1 83
 
5.6%
2 71
 
4.8%
길 66
 
4.4%
3 50
 
3.4%
7 42
 
2.8%
4 41
 
2.8%
동 39
 
2.6%
5 36
 
2.4%
Other values (134) 730
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 801
53.8%
Decimal Number 428
28.8%
Space Separator 228
 
15.3%
Dash Punctuation 27
 
1.8%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 102
 
12.7%
길 66
 
8.2%
동 39
 
4.9%
면 35
 
4.4%
읍 35
 
4.4%
탄 31
 
3.9%
남 22
 
2.7%
정 18
 
2.2%
봉 17
 
2.1%
향 17
 
2.1%
Other values (120) 419
52.3%
Decimal Number
ValueCountFrequency (%)
1 83
19.4%
2 71
16.6%
3 50
11.7%
7 42
9.8%
4 41
9.6%
5 36
8.4%
6 32
 
7.5%
9 28
 
6.5%
0 23
 
5.4%
8 22
 
5.1%
Space Separator
ValueCountFrequency (%)
228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 801
53.8%
Common 687
46.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 102
 
12.7%
길 66
 
8.2%
동 39
 
4.9%
면 35
 
4.4%
읍 35
 
4.4%
탄 31
 
3.9%
남 22
 
2.7%
정 18
 
2.2%
봉 17
 
2.1%
향 17
 
2.1%
Other values (120) 419
52.3%
Common
ValueCountFrequency (%)
228
33.2%
1 83
 
12.1%
2 71
 
10.3%
3 50
 
7.3%
7 42
 
6.1%
4 41
 
6.0%
5 36
 
5.2%
6 32
 
4.7%
9 28
 
4.1%
- 27
 
3.9%
Other values (4) 49
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 801
53.8%
ASCII 687
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
33.2%
1 83
 
12.1%
2 71
 
10.3%
3 50
 
7.3%
7 42
 
6.1%
4 41
 
6.0%
5 36
 
5.2%
6 32
 
4.7%
9 28
 
4.1%
- 27
 
3.9%
Other values (4) 49
 
7.1%
Hangul
ValueCountFrequency (%)
로 102
 
12.7%
길 66
 
8.2%
동 39
 
4.9%
면 35
 
4.4%
읍 35
 
4.4%
탄 31
 
3.9%
남 22
 
2.7%
정 18
 
2.2%
봉 17
 
2.1%
향 17
 
2.1%
Other values (120) 419
52.3%

교무실
Text

UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T05:10:22.116075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length12.318841
Min length12

Characters and Unicode

Total characters1700
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)100.0%

Sample

1st row031-227-1546
2nd row031-352-0510
3rd row031-357-1308
4th row031-225-8328
5th row031-224-9013
ValueCountFrequency (%)
031-227-1546 1
 
0.7%
031-613-1864 1
 
0.7%
031-358-8773 1
 
0.7%
031-8015-5182 1
 
0.7%
031-352-7001 1
 
0.7%
031-221-4732 1
 
0.7%
031-237-4473 1
 
0.7%
031-357-1021 1
 
0.7%
031-351-2082 1
 
0.7%
031-547-8100 1
 
0.7%
Other values (128) 128
92.8%
2023-12-13T05:10:22.513136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 292
17.2%
- 276
16.2%
3 261
15.4%
1 260
15.3%
5 136
8.0%
2 129
7.6%
8 101
 
5.9%
7 78
 
4.6%
4 59
 
3.5%
6 59
 
3.5%
Other values (2) 49
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1422
83.6%
Dash Punctuation 276
 
16.2%
Math Symbol 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 292
20.5%
3 261
18.4%
1 260
18.3%
5 136
9.6%
2 129
9.1%
8 101
 
7.1%
7 78
 
5.5%
4 59
 
4.1%
6 59
 
4.1%
9 47
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 292
17.2%
- 276
16.2%
3 261
15.4%
1 260
15.3%
5 136
8.0%
2 129
7.6%
8 101
 
5.9%
7 78
 
4.6%
4 59
 
3.5%
6 59
 
3.5%
Other values (2) 49
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 292
17.2%
- 276
16.2%
3 261
15.4%
1 260
15.3%
5 136
8.0%
2 129
7.6%
8 101
 
5.9%
7 78
 
4.6%
4 59
 
3.5%
6 59
 
3.5%
Other values (2) 49
 
2.9%

행정실
Text

Distinct133
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T05:10:22.825168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.275362
Min length12

Characters and Unicode

Total characters1694
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

Unique128 ?
Unique (%)92.8%

Sample

1st row031-227-9144
2nd row031-352-0516
3rd row031-357-1309
4th row031-225-8329
5th row031-224-9014
ValueCountFrequency (%)
031-352-8496 2
 
1.4%
031-358-1155 2
 
1.4%
031-352-8429 2
 
1.4%
031-351-3638 2
 
1.4%
031-357-5083 2
 
1.4%
031-237-4471 1
 
0.7%
031-298-5817 1
 
0.7%
031-351-2081 1
 
0.7%
031-547-8200 1
 
0.7%
031-8015-5181 1
 
0.7%
Other values (123) 123
89.1%
2023-12-13T05:10:23.222039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 276
16.3%
3 274
16.2%
0 265
15.6%
1 230
13.6%
5 140
8.3%
2 126
7.4%
8 106
 
6.3%
7 87
 
5.1%
9 69
 
4.1%
4 66
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1418
83.7%
Dash Punctuation 276
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 274
19.3%
0 265
18.7%
1 230
16.2%
5 140
9.9%
2 126
8.9%
8 106
 
7.5%
7 87
 
6.1%
9 69
 
4.9%
4 66
 
4.7%
6 55
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1694
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 276
16.3%
3 274
16.2%
0 265
15.6%
1 230
13.6%
5 140
8.3%
2 126
7.4%
8 106
 
6.3%
7 87
 
5.1%
9 69
 
4.1%
4 66
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 276
16.3%
3 274
16.2%
0 265
15.6%
1 230
13.6%
5 140
8.3%
2 126
7.4%
8 106
 
6.3%
7 87
 
5.1%
9 69
 
4.1%
4 66
 
3.9%

FAX
Text

Distinct136
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T05:10:23.805716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.253623
Min length12

Characters and Unicode

Total characters1691
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

Unique134 ?
Unique (%)97.1%

Sample

1st row031-297-9143
2nd row031-352-4940
3rd row031-357-6135
4th row031-225-8544
5th row031-224-9024
ValueCountFrequency (%)
031-352-6913 2
 
1.4%
031-356-0792 2
 
1.4%
031-352-3974 1
 
0.7%
031-8015-5184 1
 
0.7%
031-221-4735 1
 
0.7%
031-237-4472 1
 
0.7%
031-357-0090 1
 
0.7%
031-613-1863 1
 
0.7%
031-613-1132 1
 
0.7%
031-355-0786 1
 
0.7%
Other values (126) 126
91.3%
2023-12-13T05:10:24.249030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 276
16.3%
3 270
16.0%
0 250
14.8%
1 223
13.2%
5 143
8.5%
2 115
6.8%
8 107
 
6.3%
7 86
 
5.1%
4 78
 
4.6%
9 74
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1415
83.7%
Dash Punctuation 276
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 270
19.1%
0 250
17.7%
1 223
15.8%
5 143
10.1%
2 115
8.1%
8 107
 
7.6%
7 86
 
6.1%
4 78
 
5.5%
9 74
 
5.2%
6 69
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1691
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 276
16.3%
3 270
16.0%
0 250
14.8%
1 223
13.2%
5 143
8.5%
2 115
6.8%
8 107
 
6.3%
7 86
 
5.1%
4 78
 
4.6%
9 74
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1691
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 276
16.3%
3 270
16.0%
0 250
14.8%
1 223
13.2%
5 143
8.5%
2 115
6.8%
8 107
 
6.3%
7 86
 
5.1%
4 78
 
4.6%
9 74
 
4.4%

행정동
Categorical

Distinct24
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
향남읍
17 
동탄4동
11 
봉담읍
11 
동탄1동
10 
동탄2동
 
8
Other values (19)
81 

Length

Max length4
Median length3
Mean length3.3188406
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row봉담읍
2nd row향남읍
3rd row송산면
4th row병점2동
5th row반월동

Common Values

ValueCountFrequency (%)
향남읍 17
 
12.3%
동탄4동 11
 
8.0%
봉담읍 11
 
8.0%
동탄1동 10
 
7.2%
동탄2동 8
 
5.8%
병점2동 7
 
5.1%
반월동 7
 
5.1%
우정읍 7
 
5.1%
장안면 7
 
5.1%
동탄3동 6
 
4.3%
Other values (14) 47
34.1%

Length

2023-12-13T05:10:24.400987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
향남읍 17
 
12.3%
봉담읍 11
 
8.0%
동탄4동 11
 
8.0%
동탄1동 10
 
7.2%
동탄2동 8
 
5.8%
병점2동 7
 
5.1%
반월동 7
 
5.1%
우정읍 7
 
5.1%
장안면 7
 
5.1%
동탄3동 6
 
4.3%
Other values (14) 47
34.1%

개교년월일
Date

Distinct87
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1898-10-01 00:00:00
Maximum2015-09-01 00:00:00
2023-12-13T05:10:24.541037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:24.718434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T05:10:19.087223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:10:24.824556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No.급별공사립행정동개교년월일
No.1.0000.8780.5950.0000.377
급별0.8781.0000.7060.0000.620
공사립0.5950.7061.0000.4690.972
행정동0.0000.0000.4691.0000.924
개교년월일0.3770.6200.9720.9241.000
2023-12-13T05:10:24.932484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급별공사립행정동
급별1.0000.4980.000
공사립0.4981.0000.340
행정동0.0000.3401.000
2023-12-13T05:10:25.051585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No.급별공사립행정동
No.1.0000.7260.4460.000
급별0.7261.0000.4980.000
공사립0.4460.4981.0000.340
행정동0.0000.0000.3401.000

Missing values

2023-12-13T05:10:19.259953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:10:19.431408image/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

No.급별공사립학교명주소교무실행정실FAX행정동개교년월일
01초공립갈담초봉담읍 갈담초교길 24031-227-1546031-227-9144031-297-9143봉담읍1949-12-02
12초공립갈천초향남읍 발안로 701-23031-352-0510031-352-0516031-352-4940향남읍1961-03-10
23초공립고정초송산면 공룡로 326031-357-1308031-357-1309031-357-6135송산면1964-10-25
34초공립구봉초병점1로 105031-225-8328031-225-8329031-225-8544병점2동2004-09-01
45초공립기산초동탄지성로 344031-224-9013031-224-9014031-224-9024반월동2004-09-15
56초공립기안초기안길 18031-222-0046031-222-0781031-222-9859기배동1968-03-04
67초공립남양초남양시장로 55번길 7031-356-2014031-356-3576031-356-7289남양동1898-10-01
78초공립노진초장안면 화곡로 166031-351-2192031-351-2193031-351-7341장안면1971-03-01
89초공립능동초동탄원천로 315-27031-613-4205031-613-4206031-613-4221동탄3동2008-03-01
910초공립대방분교팔탄면 노하길 398031-354-8581031-352-8496031-354-5580팔탄면1966-09-02
No.급별공사립학교명주소교무실행정실FAX행정동개교년월일
128129고사립송산고송산면 송산포도로 102-21031-357-1116031-357-1117031-355-2558송산면1961-04-08
129130고사립홍익디자인고효행로 387031-8055-3012031-8055-3004031-222-3900기배동1973-03-05
130131고공립안화고병점3로 132-19031-220-0300031-220-0390031-220-0305병점2동2007-03-01
131132고공립예당고삼성1로 47031-8055-6300031-8055-6200031-8055-6220동탄3동2008-03-01
132133고공립향남고향남읍 행정동로49031-8059-9202031-8059-9301031-8059-1091향남읍2009-03-01
133134고공립향일고향남읍 행정중앙2로 28031-8077-8600031-8077-8500031-8077-8510향남읍2012-03-01
134135고공립화성반월고효행로 1281-66(반월동)031-8019-2520031-8019-2506031-8019-2510반월동2015-03-01
135136고사립화성고향남읍 장짐길 4031-350-8311031-350-8303031-352-7811향남읍1979-05-18
1361374사립한우리학교정남면 관항길 243031-354-3089031-352-3090031-352-3091정남면2001-03-01
1371384사립해원학교장안면 은골길30번길 43031-351-0806031-351-0805031-351-0807장안면2000-03-01