Overview

Dataset statistics

Number of variables11
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory92.5 B

Variable types

Categorical1
Text6
Numeric3
DateTime1

Dataset

Description김포시 관내의 초 중 고 등학교(학교급, 학교명, 소재지도로명주소,소재지지번주소, 학교장명,교무실전화번호,행정실전화번호,학급수,학생수,교원수,데이터기준일자)의 데이터현황을 제공하고 있습니다.
Author경기도 김포시
URLhttps://www.data.go.kr/data/15034878/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
학급수 is highly overall correlated with 학생수 and 1 other fieldsHigh correlation
학생수 is highly overall correlated with 학급수 and 1 other fieldsHigh correlation
교원수 is highly overall correlated with 학급수 and 1 other fieldsHigh correlation
학교명 has unique valuesUnique
교무실전화번호 has unique valuesUnique
행정실전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:12:50.358856
Analysis finished2024-04-06 08:12:54.562523
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학교급
Categorical

Distinct4
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
초등학교
47 
중학교
24 
고등학교
15 
특수학교
 
1

Length

Max length4
Median length4
Mean length3.7241379
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 47
54.0%
중학교 24
27.6%
고등학교 15
 
17.2%
특수학교 1
 
1.1%

Length

2024-04-06T17:12:54.690776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:12:54.910390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 47
54.0%
중학교 24
27.6%
고등학교 15
 
17.2%
특수학교 1
 
1.1%

학교명
Text

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:12:55.349618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.1609195
Min length4

Characters and Unicode

Total characters536
Distinct characters79
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

Unique87 ?
Unique (%)100.0%

Sample

1st row가현초등학교
2nd row감정초등학교
3rd row개곡초등학교
4th row걸포초등학교
5th row고창초등학교
ValueCountFrequency (%)
가현초등학교 1
 
1.1%
하성중학교 1
 
1.1%
푸른솔중학교 1
 
1.1%
장기중학교 1
 
1.1%
은여울중학교 1
 
1.1%
운양중학교 1
 
1.1%
양도중학교 1
 
1.1%
신양중학교 1
 
1.1%
마송중학교 1
 
1.1%
대곶중학교 1
 
1.1%
Other values (77) 77
88.5%
2024-04-06T17:12:56.121549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 89
16.6%
교 87
16.2%
등 62
 
11.6%
초 47
 
8.8%
중 25
 
4.7%
고 20
 
3.7%
포 18
 
3.4%
김 17
 
3.2%
양 10
 
1.9%
운 6
 
1.1%
Other values (69) 155
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 536
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 89
16.6%
교 87
16.2%
등 62
 
11.6%
초 47
 
8.8%
중 25
 
4.7%
고 20
 
3.7%
포 18
 
3.4%
김 17
 
3.2%
양 10
 
1.9%
운 6
 
1.1%
Other values (69) 155
28.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 536
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 89
16.6%
교 87
16.2%
등 62
 
11.6%
초 47
 
8.8%
중 25
 
4.7%
고 20
 
3.7%
포 18
 
3.4%
김 17
 
3.2%
양 10
 
1.9%
운 6
 
1.1%
Other values (69) 155
28.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 536
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 89
16.6%
교 87
16.2%
등 62
 
11.6%
초 47
 
8.8%
중 25
 
4.7%
고 20
 
3.7%
포 18
 
3.4%
김 17
 
3.2%
양 10
 
1.9%
운 6
 
1.1%
Other values (69) 155
28.9%

소재지도로명주소
Text

Distinct85
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:12:56.847415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.344828
Min length13

Characters and Unicode

Total characters1683
Distinct characters77
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

Unique83 ?
Unique (%)95.4%

Sample

1st row경기도 김포시 김포한강2로 83
2nd row경기도 김포시 중봉로 11
3rd row경기도 김포시 월곶면 애기봉로 445
4th row경기도 김포시 걸포로 22
5th row경기도 김포시 김포한강1로98번길 35
ValueCountFrequency (%)
경기도 87
22.5%
김포시 87
22.5%
고촌읍 9
 
2.3%
통진읍 9
 
2.3%
김포한강2로 7
 
1.8%
양촌읍 6
 
1.6%
봉화로 5
 
1.3%
대곶면 5
 
1.3%
김포한강11로 5
 
1.3%
하성면 4
 
1.0%
Other values (127) 162
42.0%
2024-04-06T17:12:57.817245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
18.2%
포 120
 
7.1%
김 118
 
7.0%
기 94
 
5.6%
도 88
 
5.2%
경 87
 
5.2%
로 87
 
5.2%
시 87
 
5.2%
1 60
 
3.6%
2 51
 
3.0%
Other values (67) 584
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1026
61.0%
Decimal Number 341
 
20.3%
Space Separator 307
 
18.2%
Dash Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 120
11.7%
김 118
11.5%
기 94
 
9.2%
도 88
 
8.6%
경 87
 
8.5%
로 87
 
8.5%
시 87
 
8.5%
번 33
 
3.2%
길 33
 
3.2%
강 26
 
2.5%
Other values (55) 253
24.7%
Decimal Number
ValueCountFrequency (%)
1 60
17.6%
2 51
15.0%
3 42
12.3%
5 32
9.4%
8 30
8.8%
4 28
8.2%
7 26
7.6%
6 26
7.6%
0 24
 
7.0%
9 22
 
6.5%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1026
61.0%
Common 657
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 120
11.7%
김 118
11.5%
기 94
 
9.2%
도 88
 
8.6%
경 87
 
8.5%
로 87
 
8.5%
시 87
 
8.5%
번 33
 
3.2%
길 33
 
3.2%
강 26
 
2.5%
Other values (55) 253
24.7%
Common
ValueCountFrequency (%)
307
46.7%
1 60
 
9.1%
2 51
 
7.8%
3 42
 
6.4%
5 32
 
4.9%
8 30
 
4.6%
4 28
 
4.3%
7 26
 
4.0%
6 26
 
4.0%
0 24
 
3.7%
Other values (2) 31
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1026
61.0%
ASCII 657
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
46.7%
1 60
 
9.1%
2 51
 
7.8%
3 42
 
6.4%
5 32
 
4.9%
8 30
 
4.6%
4 28
 
4.3%
7 26
 
4.0%
6 26
 
4.0%
0 24
 
3.7%
Other values (2) 31
 
4.7%
Hangul
ValueCountFrequency (%)
포 120
11.7%
김 118
11.5%
기 94
 
9.2%
도 88
 
8.6%
경 87
 
8.5%
로 87
 
8.5%
시 87
 
8.5%
번 33
 
3.2%
길 33
 
3.2%
강 26
 
2.5%
Other values (55) 253
24.7%

소재지지번주소
Text

Distinct83
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:12:58.245946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.747126
Min length15

Characters and Unicode

Total characters1718
Distinct characters67
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

Unique79 ?
Unique (%)90.8%

Sample

1st row경기도 김포시 장기동2065-3번지
2nd row경기도 김포시 감정동508-13번지
3rd row경기도 김포시 월곶면 개곡리267-2번지
4th row경기도 김포시 걸포동1565번지
5th row경기도 김포시 장기동 1952
ValueCountFrequency (%)
경기도 87
27.5%
김포시 87
27.5%
고촌읍 9
 
2.8%
통진읍 9
 
2.8%
양촌읍 6
 
1.9%
대곶면 5
 
1.6%
월곶면 4
 
1.3%
하성면 4
 
1.3%
장기동 4
 
1.3%
마산동 2
 
0.6%
Other values (93) 99
31.3%
2024-04-06T17:12:58.999081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
299
17.4%
기 100
 
5.8%
포 89
 
5.2%
경 87
 
5.1%
도 87
 
5.1%
김 87
 
5.1%
시 87
 
5.1%
번 69
 
4.0%
지 69
 
4.0%
1 57
 
3.3%
Other values (57) 687
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
60.0%
Decimal Number 337
 
19.6%
Space Separator 299
 
17.4%
Dash Punctuation 51
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 100
 
9.7%
포 89
 
8.6%
경 87
 
8.4%
도 87
 
8.4%
김 87
 
8.4%
시 87
 
8.4%
번 69
 
6.7%
지 69
 
6.7%
동 50
 
4.8%
리 37
 
3.6%
Other values (45) 269
26.1%
Decimal Number
ValueCountFrequency (%)
1 57
16.9%
6 49
14.5%
2 36
10.7%
5 35
10.4%
8 33
9.8%
4 33
9.8%
3 31
9.2%
9 22
 
6.5%
7 21
 
6.2%
0 20
 
5.9%
Space Separator
ValueCountFrequency (%)
299
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1031
60.0%
Common 687
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 100
 
9.7%
포 89
 
8.6%
경 87
 
8.4%
도 87
 
8.4%
김 87
 
8.4%
시 87
 
8.4%
번 69
 
6.7%
지 69
 
6.7%
동 50
 
4.8%
리 37
 
3.6%
Other values (45) 269
26.1%
Common
ValueCountFrequency (%)
299
43.5%
1 57
 
8.3%
- 51
 
7.4%
6 49
 
7.1%
2 36
 
5.2%
5 35
 
5.1%
8 33
 
4.8%
4 33
 
4.8%
3 31
 
4.5%
9 22
 
3.2%
Other values (2) 41
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
60.0%
ASCII 687
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
299
43.5%
1 57
 
8.3%
- 51
 
7.4%
6 49
 
7.1%
2 36
 
5.2%
5 35
 
5.1%
8 33
 
4.8%
4 33
 
4.8%
3 31
 
4.5%
9 22
 
3.2%
Other values (2) 41
 
6.0%
Hangul
ValueCountFrequency (%)
기 100
 
9.7%
포 89
 
8.6%
경 87
 
8.4%
도 87
 
8.4%
김 87
 
8.4%
시 87
 
8.4%
번 69
 
6.7%
지 69
 
6.7%
동 50
 
4.8%
리 37
 
3.6%
Other values (45) 269
26.1%

학교장명
Text

Distinct84
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:12:59.531514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0229885
Min length3

Characters and Unicode

Total characters263
Distinct characters99
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

Unique81 ?
Unique (%)93.1%

Sample

1st row박재남
2nd row정현학
3rd row위재옥
4th row박성진
5th row이철희
ValueCountFrequency (%)
이종민 2
 
2.3%
이경아 2
 
2.3%
이흥용 2
 
2.3%
차찬규 1
 
1.1%
박윤식 1
 
1.1%
정승화 1
 
1.1%
선원희 1
 
1.1%
석금례 1
 
1.1%
김찬중 1
 
1.1%
조남미 1
 
1.1%
Other values (75) 75
85.2%
2024-04-06T17:13:00.340702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 18
 
6.8%
김 15
 
5.7%
경 14
 
5.3%
박 10
 
3.8%
희 9
 
3.4%
진 8
 
3.0%
성 7
 
2.7%
정 7
 
2.7%
현 6
 
2.3%
재 5
 
1.9%
Other values (89) 164
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 260
98.9%
Space Separator 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
6.9%
김 15
 
5.8%
경 14
 
5.4%
박 10
 
3.8%
희 9
 
3.5%
진 8
 
3.1%
성 7
 
2.7%
정 7
 
2.7%
현 6
 
2.3%
재 5
 
1.9%
Other values (88) 161
61.9%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
98.9%
Common 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
6.9%
김 15
 
5.8%
경 14
 
5.4%
박 10
 
3.8%
희 9
 
3.5%
진 8
 
3.1%
성 7
 
2.7%
정 7
 
2.7%
현 6
 
2.3%
재 5
 
1.9%
Other values (88) 161
61.9%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 260
98.9%
ASCII 3
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 18
 
6.9%
김 15
 
5.8%
경 14
 
5.4%
박 10
 
3.8%
희 9
 
3.5%
진 8
 
3.1%
성 7
 
2.7%
정 7
 
2.7%
현 6
 
2.3%
재 5
 
1.9%
Other values (88) 161
61.9%
ASCII
ValueCountFrequency (%)
3
100.0%

교무실전화번호
Text

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:13:00.791877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.321839
Min length12

Characters and Unicode

Total characters1072
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

Unique87 ?
Unique (%)100.0%

Sample

1st row031-996-1862
2nd row031-982-4233
3rd row031-987-1898
4th row031-987-4891
5th row031-984-3004
ValueCountFrequency (%)
031-996-1862 1
 
1.1%
031-988-7263 1
 
1.1%
031-996-1673 1
 
1.1%
031-986-7301 1
 
1.1%
031-996-7354 1
 
1.1%
031-985-2652 1
 
1.1%
031-986-2315 1
 
1.1%
031-980-8410 1
 
1.1%
031-983-6843 1
 
1.1%
031-987-0148 1
 
1.1%
Other values (77) 77
88.5%
2024-04-06T17:13:01.586356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 174
16.2%
0 151
14.1%
1 151
14.1%
3 132
12.3%
9 132
12.3%
8 88
8.2%
6 68
 
6.3%
2 47
 
4.4%
7 46
 
4.3%
4 38
 
3.5%
Other values (2) 45
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 888
82.8%
Dash Punctuation 174
 
16.2%
Math Symbol 10
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 151
17.0%
1 151
17.0%
3 132
14.9%
9 132
14.9%
8 88
9.9%
6 68
7.7%
2 47
 
5.3%
7 46
 
5.2%
4 38
 
4.3%
5 35
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 174
16.2%
0 151
14.1%
1 151
14.1%
3 132
12.3%
9 132
12.3%
8 88
8.2%
6 68
 
6.3%
2 47
 
4.4%
7 46
 
4.3%
4 38
 
3.5%
Other values (2) 45
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 174
16.2%
0 151
14.1%
1 151
14.1%
3 132
12.3%
9 132
12.3%
8 88
8.2%
6 68
 
6.3%
2 47
 
4.4%
7 46
 
4.3%
4 38
 
3.5%
Other values (2) 45
 
4.2%

행정실전화번호
Text

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T17:13:02.104750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.137931
Min length12

Characters and Unicode

Total characters1056
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

Unique87 ?
Unique (%)100.0%

Sample

1st row031-996-1866
2nd row031-982-4232
3rd row031-989-5421
4th row031-987-4892
5th row031-985-5109
ValueCountFrequency (%)
031-996-1866 1
 
1.1%
031-988-7262 1
 
1.1%
031-996-1671 1
 
1.1%
031-986-7304 1
 
1.1%
031-996-7351 1
 
1.1%
031-984-0040 1
 
1.1%
031-986-2316 1
 
1.1%
031-980-8404 1
 
1.1%
031-983-6842 1
 
1.1%
031-987-0149 1
 
1.1%
Other values (77) 77
88.5%
2024-04-06T17:13:02.937201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 174
16.5%
9 145
13.7%
1 136
12.9%
0 135
12.8%
3 121
11.5%
8 90
8.5%
6 69
 
6.5%
7 59
 
5.6%
4 49
 
4.6%
2 45
 
4.3%
Other values (2) 33
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 880
83.3%
Dash Punctuation 174
 
16.5%
Math Symbol 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 145
16.5%
1 136
15.5%
0 135
15.3%
3 121
13.8%
8 90
10.2%
6 69
7.8%
7 59
6.7%
4 49
 
5.6%
2 45
 
5.1%
5 31
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1056
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 174
16.5%
9 145
13.7%
1 136
12.9%
0 135
12.8%
3 121
11.5%
8 90
8.5%
6 69
 
6.5%
7 59
 
5.6%
4 49
 
4.6%
2 45
 
4.3%
Other values (2) 33
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 174
16.5%
9 145
13.7%
1 136
12.9%
0 135
12.8%
3 121
11.5%
8 90
8.5%
6 69
 
6.5%
7 59
 
5.6%
4 49
 
4.6%
2 45
 
4.3%
Other values (2) 33
 
3.1%

학급수
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.275862
Minimum3
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T17:13:03.254020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q114
median28
Q337
95-th percentile57.7
Maximum68
Range65
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.160309
Coefficient of variation (CV)0.57152311
Kurtosis-0.37628808
Mean28.275862
Median Absolute Deviation (MAD)10
Skewness0.47882076
Sum2460
Variance261.15557
MonotonicityNot monotonic
2024-04-06T17:13:03.643775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
6 6
 
6.9%
33 5
 
5.7%
28 4
 
4.6%
23 4
 
4.6%
37 4
 
4.6%
10 3
 
3.4%
36 3
 
3.4%
24 3
 
3.4%
14 3
 
3.4%
32 3
 
3.4%
Other values (36) 49
56.3%
ValueCountFrequency (%)
3 1
 
1.1%
6 6
6.9%
7 3
3.4%
8 2
 
2.3%
10 3
3.4%
11 1
 
1.1%
12 3
3.4%
13 1
 
1.1%
14 3
3.4%
15 2
 
2.3%
ValueCountFrequency (%)
68 1
1.1%
67 1
1.1%
64 1
1.1%
59 1
1.1%
58 1
1.1%
57 1
1.1%
55 2
2.3%
52 1
1.1%
51 1
1.1%
50 2
2.3%

학생수
Real number (ℝ)

HIGH CORRELATION 

Distinct85
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean743.4023
Minimum40
Maximum1959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T17:13:03.982490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile70.8
Q1289.5
median715
Q31091.5
95-th percentile1523
Maximum1959
Range1919
Interquartile range (IQR)802

Descriptive statistics

Standard deviation482.90002
Coefficient of variation (CV)0.64958102
Kurtosis-0.67508967
Mean743.4023
Median Absolute Deviation (MAD)383
Skewness0.32588169
Sum64676
Variance233192.43
MonotonicityNot monotonic
2024-04-06T17:13:04.359869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250 2
 
2.3%
540 2
 
2.3%
1298 1
 
1.1%
144 1
 
1.1%
1153 1
 
1.1%
1040 1
 
1.1%
1189 1
 
1.1%
1019 1
 
1.1%
1166 1
 
1.1%
813 1
 
1.1%
Other values (75) 75
86.2%
ValueCountFrequency (%)
40 1
1.1%
51 1
1.1%
57 1
1.1%
62 1
1.1%
69 1
1.1%
75 1
1.1%
77 1
1.1%
92 1
1.1%
109 1
1.1%
127 1
1.1%
ValueCountFrequency (%)
1959 1
1.1%
1923 1
1.1%
1698 1
1.1%
1560 1
1.1%
1532 1
1.1%
1502 1
1.1%
1490 1
1.1%
1457 1
1.1%
1327 1
1.1%
1317 1
1.1%

교원수
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.597701
Minimum9
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T17:13:05.113868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile12.6
Q129
median51
Q372.5
95-th percentile86
Maximum99
Range90
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation25.085185
Coefficient of variation (CV)0.49577717
Kurtosis-1.2581306
Mean50.597701
Median Absolute Deviation (MAD)22
Skewness-0.015621969
Sum4402
Variance629.26651
MonotonicityNot monotonic
2024-04-06T17:13:05.506548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71 5
 
5.7%
76 4
 
4.6%
34 4
 
4.6%
29 3
 
3.4%
14 3
 
3.4%
42 3
 
3.4%
80 3
 
3.4%
36 3
 
3.4%
12 2
 
2.3%
19 2
 
2.3%
Other values (44) 55
63.2%
ValueCountFrequency (%)
9 1
 
1.1%
10 1
 
1.1%
11 1
 
1.1%
12 2
2.3%
14 3
3.4%
15 1
 
1.1%
17 1
 
1.1%
19 2
2.3%
20 2
2.3%
21 1
 
1.1%
ValueCountFrequency (%)
99 1
 
1.1%
94 1
 
1.1%
91 1
 
1.1%
89 1
 
1.1%
86 2
2.3%
85 1
 
1.1%
84 2
2.3%
83 1
 
1.1%
80 3
3.4%
78 1
 
1.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
Minimum2024-03-27 00:00:00
Maximum2024-03-27 00:00:00
2024-04-06T17:13:05.702171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:05.873299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:12:53.227596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:52.228562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:52.710057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:53.430846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:52.383653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:52.874172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:53.613347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:52.559750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:12:53.058442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:13:06.023537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교급학교명소재지도로명주소소재지지번주소학교장명교무실전화번호행정실전화번호학급수학생수교원수
학교급1.0001.0000.6920.0000.0001.0001.0000.3570.3110.486
학교명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.6921.0001.0001.0000.9981.0001.0000.9540.9600.933
소재지지번주소0.0001.0001.0001.0000.9991.0001.0000.9280.9170.805
학교장명0.0001.0000.9980.9991.0001.0001.0000.9310.9690.844
교무실전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정실전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
학급수0.3571.0000.9540.9280.9311.0001.0001.0000.9620.914
학생수0.3111.0000.9600.9170.9691.0001.0000.9621.0000.934
교원수0.4861.0000.9330.8050.8441.0001.0000.9140.9341.000
2024-04-06T17:13:06.268769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학급수학생수교원수학교급
학급수1.0000.9480.9290.226
학생수0.9481.0000.9210.180
교원수0.9290.9211.0000.298
학교급0.2260.1800.2981.000

Missing values

2024-04-06T17:12:53.877529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:12:54.356238image/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

학교급학교명소재지도로명주소소재지지번주소학교장명교무실전화번호행정실전화번호학급수학생수교원수데이터기준일자
0초등학교가현초등학교경기도 김포시 김포한강2로 83경기도 김포시 장기동2065-3번지박재남031-996-1862031-996-1866491298762024-03-27
1초등학교감정초등학교경기도 김포시 중봉로 11경기도 김포시 감정동508-13번지정현학031-982-4233031-982-423237845562024-03-27
2초등학교개곡초등학교경기도 김포시 월곶면 애기봉로 445경기도 김포시 월곶면 개곡리267-2번지위재옥031-987-1898031-989-5421692102024-03-27
3초등학교걸포초등학교경기도 김포시 걸포로 22경기도 김포시 걸포동1565번지박성진031-987-4891031-987-489222500362024-03-27
4초등학교고창초등학교경기도 김포시 김포한강1로98번길 35경기도 김포시 장기동 1952이철희031-984-3004031-985-510929715432024-03-27
5초등학교고촌초등학교경기도 김포시 고촌읍 신곡로29번길 30경기도 김포시 고촌읍 신곡리1101번지김영만031-986-1241031-986-012822552362024-03-27
6초등학교금란초등학교경기도 김포시 고촌읍 장곡로 42경기도 김포시 고촌읍 풍곡리466-2번지김홍섭031-986-4252031-985-19706127172024-03-27
7초등학교금성초등학교경기도 김포시 하성면 하성로795번길 26경기도 김포시 하성면 마조리434번지정현수031-988-3105031-988-3106657122024-03-27
8초등학교금파초등학교경기도 김포시 김포대로926번길 74경기도 김포시 북변동809번지이유경031-998-4071031-998-407423530342024-03-27
9초등학교김포구래초등학교경기도 김포시 김포한강9로12번길 77경기도 김포시 구래동 6891-10서재민031-8049-2202031-8049-229038932552024-03-27
학교급학교명소재지도로명주소소재지지번주소학교장명교무실전화번호행정실전화번호학급수학생수교원수데이터기준일자
77고등학교솔터고등학교경기도 김포시 김포한강7로22번길 109경기도 김포시 마산동 615-6이혜련031-996-9646031-996-9643331087852024-03-27
78고등학교운양고등학교경기도 김포시 김포한강11로 58경기도 김포시 운양동 1325-6박기일031-996-6285031-996-6282331074842024-03-27
79고등학교운유고등학교경기도 김포시 김포한강2로 236경기도 김포시 장기동 1886-3이성미031-5186-5000031-5186-507415491342024-03-27
80고등학교장기고등학교경기도 김포시 김포한강2로 131경기도 김포시 장기동 1654정미경031-984-1852031-984-5359351069722024-03-27
81고등학교풍무고등학교경기도 김포시 풍무로93번길 53경기도 김포시 풍무동 411-5김지영031-996-4383031-996-4382371179802024-03-27
82고등학교하성고등학교경기도 김포시 하성면 애기봉로806번길 30경기도 김포시 하성면 마곡리 640-1이종민031-988-7265031-988-726114223352024-03-27
83고등학교김포외국어고등학교경기도 김포시 월곶면 김포대로 2537경기도 김포시 월곶면 갈산리465-33번지김진성031-996-7700031-996-770224540452024-03-27
84고등학교양곡고등학교경기도 김포시 양촌읍 양곡4로 138경기도 김포시 양촌읍 양곡리 286-1박윤식031-981-0138031-981-013723747532024-03-27
85고등학교통진고등학교경기도 김포시 통진읍 김포대로 2165경기도 김포시 통진읍 마송리 14-15차찬규031-987-0127031-987-012431837702024-03-27
86특수학교새솔학교경기도 김포시 김포한강3로 315경기도 김포시 장기동 1888-11김기매031-999-9101031-999-910438214912024-03-27