Overview

Dataset statistics

Number of variables13
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory107.8 B

Variable types

Categorical6
Text7

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,교실수,교실면적,체육장,보건/위생공간,조리실/급식공간,기타공간,공시차수,주소
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20643/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
공시차수 is highly imbalanced (52.8%)Imbalance
유치원코드 has unique valuesUnique
유치원명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 09:08:35.037065
Analysis finished2024-03-13 09:08:36.295770
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
서울특별시교육청
48 

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 48
100.0%

Length

2024-03-13T18:08:36.359053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T18:08:36.454303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 48
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
강서양천교육지원청
48 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서양천교육지원청 48
100.0%

Length

2024-03-13T18:08:36.570831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T18:08:36.717447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서양천교육지원청 48
100.0%

유치원코드
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:36.926420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1728
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

Unique48 ?
Unique (%)100.0%

Sample

1st row1ecec08d-05b8-b044-e053-0a32095ab044
2nd row1ecec08d-08bb-b044-e053-0a32095ab044
3rd row1ecec08d-08bc-b044-e053-0a32095ab044
4th row1ecec08d-0913-b044-e053-0a32095ab044
5th row1ecec08d-02b0-b044-e053-0a32095ab044
ValueCountFrequency (%)
1ecec08d-05b8-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-08bb-b044-e053-0a32095ab044 1
 
2.1%
1ecec08c-f649-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-00ac-b044-e053-0a32095ab044 1
 
2.1%
8abcadee-6df5-4c85-9e38-cba5a2d519a5 1
 
2.1%
9c26aa7f-0f07-4613-9136-4984c723803f 1
 
2.1%
a59a057e-4f5c-411a-bb2a-60068691c766 1
 
2.1%
d72d2e90-cf0d-4a9b-8697-a47e692aa3ea 1
 
2.1%
1ecec08c-eec5-b044-e053-0a32095ab044 1
 
2.1%
1ecec08c-ef9d-b044-e053-0a32095ab044 1
 
2.1%
Other values (38) 38
79.2%
2024-03-13T18:08:37.256432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 294
17.0%
- 192
11.1%
4 192
11.1%
e 149
8.6%
c 132
7.6%
a 109
 
6.3%
5 104
 
6.0%
b 99
 
5.7%
3 99
 
5.7%
8 66
 
3.8%
Other values (7) 292
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 967
56.0%
Lowercase Letter 569
32.9%
Dash Punctuation 192
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 294
30.4%
4 192
19.9%
5 104
 
10.8%
3 99
 
10.2%
8 66
 
6.8%
9 63
 
6.5%
2 58
 
6.0%
1 58
 
6.0%
6 20
 
2.1%
7 13
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
e 149
26.2%
c 132
23.2%
a 109
19.2%
b 99
17.4%
d 45
 
7.9%
f 35
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1159
67.1%
Latin 569
32.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 294
25.4%
- 192
16.6%
4 192
16.6%
5 104
 
9.0%
3 99
 
8.5%
8 66
 
5.7%
9 63
 
5.4%
2 58
 
5.0%
1 58
 
5.0%
6 20
 
1.7%
Latin
ValueCountFrequency (%)
e 149
26.2%
c 132
23.2%
a 109
19.2%
b 99
17.4%
d 45
 
7.9%
f 35
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 294
17.0%
- 192
11.1%
4 192
11.1%
e 149
8.6%
c 132
7.6%
a 109
 
6.3%
5 104
 
6.0%
b 99
 
5.7%
3 99
 
5.7%
8 66
 
3.8%
Other values (7) 292
16.9%

유치원명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:37.490972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length7.3125
Min length5

Characters and Unicode

Total characters351
Distinct characters66
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

Unique48 ?
Unique (%)100.0%

Sample

1st row등대유치원
2nd row한서유치원
3rd row해림유치원
4th row신목유치원
5th row서울강신초등학교병설유치원
ValueCountFrequency (%)
등대유치원 1
 
2.1%
한서유치원 1
 
2.1%
서울신원초등학교병설유치원 1
 
2.1%
서울신은초등학교병설유치원 1
 
2.1%
서울양동초등학교병설유치원 1
 
2.1%
꿈꾸는유치원 1
 
2.1%
세신유치원 1
 
2.1%
서울신정유치원 1
 
2.1%
솔샘유치원 1
 
2.1%
솔밭유치원 1
 
2.1%
Other values (38) 38
79.2%
2024-03-13T18:08:37.947441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 51
14.5%
유 48
13.7%
치 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
설 12
 
3.4%
병 12
 
3.4%
교 12
 
3.4%
Other values (56) 109
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 51
14.5%
유 48
13.7%
치 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
설 12
 
3.4%
병 12
 
3.4%
교 12
 
3.4%
Other values (56) 109
31.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 51
14.5%
유 48
13.7%
치 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
설 12
 
3.4%
병 12
 
3.4%
교 12
 
3.4%
Other values (56) 109
31.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 51
14.5%
유 48
13.7%
치 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
설 12
 
3.4%
병 12
 
3.4%
교 12
 
3.4%
Other values (56) 109
31.1%

설립유형
Categorical

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
사립(사인)
29 
공립(병설)
12 
사립(법인)
5 
공립(단설)
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립(사인) 29
60.4%
공립(병설) 12
25.0%
사립(법인) 5
 
10.4%
공립(단설) 2
 
4.2%

Length

2024-03-13T18:08:38.084813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T18:08:38.172277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 29
60.4%
공립(병설 12
25.0%
사립(법인 5
 
10.4%
공립(단설 2
 
4.2%

교실수
Categorical

Distinct10
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
5개
11 
6개
10 
7개
10 
4개
6 
8개
3 
Other values (5)
8 

Length

Max length3
Median length2
Mean length2.0625
Min length2

Unique

Unique3 ?
Unique (%)6.2%

Sample

1st row6개
2nd row7개
3rd row5개
4th row5개
5th row7개

Common Values

ValueCountFrequency (%)
5개 11
22.9%
6개 10
20.8%
7개 10
20.8%
4개 6
12.5%
8개 3
 
6.2%
3개 3
 
6.2%
9개 2
 
4.2%
12개 1
 
2.1%
11개 1
 
2.1%
14개 1
 
2.1%

Length

2024-03-13T18:08:38.281170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T18:08:38.386660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5개 11
22.9%
6개 10
20.8%
7개 10
20.8%
4개 6
12.5%
8개 3
 
6.2%
3개 3
 
6.2%
9개 2
 
4.2%
12개 1
 
2.1%
11개 1
 
2.1%
14개 1
 
2.1%

교실면적
Text

Distinct45
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:38.582053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9791667
Min length3

Characters and Unicode

Total characters191
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)87.5%

Sample

1st row375㎡
2nd row350㎡
3rd row461㎡
4th row346㎡
5th row315㎡
ValueCountFrequency (%)
238㎡ 2
 
4.2%
462㎡ 2
 
4.2%
396㎡ 2
 
4.2%
380㎡ 1
 
2.1%
325㎡ 1
 
2.1%
669㎡ 1
 
2.1%
375㎡ 1
 
2.1%
416㎡ 1
 
2.1%
654㎡ 1
 
2.1%
478㎡ 1
 
2.1%
Other values (35) 35
72.9%
2024-03-13T18:08:38.921725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 48
25.1%
3 26
13.6%
5 19
 
9.9%
2 18
 
9.4%
4 17
 
8.9%
6 15
 
7.9%
0 11
 
5.8%
7 11
 
5.8%
1 10
 
5.2%
8 8
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 143
74.9%
Other Symbol 48
 
25.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 26
18.2%
5 19
13.3%
2 18
12.6%
4 17
11.9%
6 15
10.5%
0 11
7.7%
7 11
7.7%
1 10
 
7.0%
8 8
 
5.6%
9 8
 
5.6%
Other Symbol
ValueCountFrequency (%)
㎡ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 48
25.1%
3 26
13.6%
5 19
 
9.9%
2 18
 
9.4%
4 17
 
8.9%
6 15
 
7.9%
0 11
 
5.8%
7 11
 
5.8%
1 10
 
5.2%
8 8
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143
74.9%
CJK Compat 48
 
25.1%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 48
100.0%
ASCII
ValueCountFrequency (%)
3 26
18.2%
5 19
13.3%
2 18
12.6%
4 17
11.9%
6 15
10.5%
0 11
7.7%
7 11
7.7%
1 10
 
7.0%
8 8
 
5.6%
9 8
 
5.6%

체육장
Categorical

Distinct18
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size516.0 B
㎡
30 
0㎡
 
2
22㎡
 
1
108㎡
 
1
133㎡
 
1
Other values (13)
13 

Length

Max length4
Median length1
Mean length1.9166667
Min length1

Unique

Unique16 ?
Unique (%)33.3%

Sample

1st row30㎡
2nd row㎡
3rd row㎡
4th row㎡
5th row㎡

Common Values

ValueCountFrequency (%)
㎡ 30
62.5%
0㎡ 2
 
4.2%
22㎡ 1
 
2.1%
108㎡ 1
 
2.1%
133㎡ 1
 
2.1%
135㎡ 1
 
2.1%
193㎡ 1
 
2.1%
66㎡ 1
 
2.1%
634㎡ 1
 
2.1%
84㎡ 1
 
2.1%
Other values (8) 8
 
16.7%

Length

2024-03-13T18:08:39.083276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
㎡ 30
62.5%
0㎡ 2
 
4.2%
30㎡ 1
 
2.1%
96㎡ 1
 
2.1%
227㎡ 1
 
2.1%
164㎡ 1
 
2.1%
86㎡ 1
 
2.1%
323㎡ 1
 
2.1%
450㎡ 1
 
2.1%
84㎡ 1
 
2.1%
Other values (8) 8
 
16.7%

보건/위생공간
Text

Distinct27
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:39.265208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.875
Min length2

Characters and Unicode

Total characters138
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)39.6%

Sample

1st row50㎡
2nd row40㎡
3rd row0㎡
4th row14㎡
5th row40㎡
ValueCountFrequency (%)
0㎡ 8
16.7%
40㎡ 6
 
12.5%
50㎡ 3
 
6.2%
60㎡ 3
 
6.2%
33㎡ 3
 
6.2%
66㎡ 2
 
4.2%
10㎡ 2
 
4.2%
92㎡ 2
 
4.2%
12㎡ 1
 
2.1%
47㎡ 1
 
2.1%
Other values (17) 17
35.4%
2024-03-13T18:08:39.620463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 48
34.8%
0 26
18.8%
4 12
 
8.7%
3 10
 
7.2%
6 9
 
6.5%
1 9
 
6.5%
2 8
 
5.8%
7 5
 
3.6%
9 4
 
2.9%
8 4
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
65.2%
Other Symbol 48
34.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
28.9%
4 12
13.3%
3 10
 
11.1%
6 9
 
10.0%
1 9
 
10.0%
2 8
 
8.9%
7 5
 
5.6%
9 4
 
4.4%
8 4
 
4.4%
5 3
 
3.3%
Other Symbol
ValueCountFrequency (%)
㎡ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 48
34.8%
0 26
18.8%
4 12
 
8.7%
3 10
 
7.2%
6 9
 
6.5%
1 9
 
6.5%
2 8
 
5.8%
7 5
 
3.6%
9 4
 
2.9%
8 4
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
65.2%
CJK Compat 48
34.8%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 48
100.0%
ASCII
ValueCountFrequency (%)
0 26
28.9%
4 12
13.3%
3 10
 
11.1%
6 9
 
10.0%
1 9
 
10.0%
2 8
 
8.9%
7 5
 
5.6%
9 4
 
4.4%
8 4
 
4.4%
5 3
 
3.3%

조리실/급식공간
Text

Distinct40
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:39.850753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2708333
Min length2

Characters and Unicode

Total characters157
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)77.1%

Sample

1st row225㎡
2nd row201㎡
3rd row40㎡
4th row36㎡
5th row106㎡
ValueCountFrequency (%)
0㎡ 7
 
14.6%
23㎡ 2
 
4.2%
33㎡ 2
 
4.2%
757㎡ 1
 
2.1%
10㎡ 1
 
2.1%
580㎡ 1
 
2.1%
165㎡ 1
 
2.1%
225㎡ 1
 
2.1%
56㎡ 1
 
2.1%
132㎡ 1
 
2.1%
Other values (30) 30
62.5%
2024-03-13T18:08:40.240529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 48
30.6%
0 21
13.4%
2 17
 
10.8%
1 16
 
10.2%
3 15
 
9.6%
6 8
 
5.1%
8 8
 
5.1%
5 7
 
4.5%
4 6
 
3.8%
7 6
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 109
69.4%
Other Symbol 48
30.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
19.3%
2 17
15.6%
1 16
14.7%
3 15
13.8%
6 8
 
7.3%
8 8
 
7.3%
5 7
 
6.4%
4 6
 
5.5%
7 6
 
5.5%
9 5
 
4.6%
Other Symbol
ValueCountFrequency (%)
㎡ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 48
30.6%
0 21
13.4%
2 17
 
10.8%
1 16
 
10.2%
3 15
 
9.6%
6 8
 
5.1%
8 8
 
5.1%
5 7
 
4.5%
4 6
 
3.8%
7 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109
69.4%
CJK Compat 48
30.6%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 48
100.0%
ASCII
ValueCountFrequency (%)
0 21
19.3%
2 17
15.6%
1 16
14.7%
3 15
13.8%
6 8
 
7.3%
8 8
 
7.3%
5 7
 
6.4%
4 6
 
5.5%
7 6
 
5.5%
9 5
 
4.6%

기타공간
Text

Distinct31
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:40.445189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.125
Min length2

Characters and Unicode

Total characters150
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)41.7%

Sample

1st row10㎡
2nd row30㎡
3rd row10㎡
4th row18㎡
5th row41㎡
ValueCountFrequency (%)
10㎡ 4
 
8.3%
20㎡ 4
 
8.3%
33㎡ 4
 
8.3%
40㎡ 2
 
4.2%
14㎡ 2
 
4.2%
22㎡ 2
 
4.2%
35㎡ 2
 
4.2%
0㎡ 2
 
4.2%
11㎡ 2
 
4.2%
18㎡ 2
 
4.2%
Other values (21) 22
45.8%
2024-03-13T18:08:40.811343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 48
32.0%
1 25
16.7%
3 15
 
10.0%
0 14
 
9.3%
2 14
 
9.3%
4 10
 
6.7%
5 6
 
4.0%
8 5
 
3.3%
6 5
 
3.3%
7 4
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
68.0%
Other Symbol 48
32.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
24.5%
3 15
14.7%
0 14
13.7%
2 14
13.7%
4 10
 
9.8%
5 6
 
5.9%
8 5
 
4.9%
6 5
 
4.9%
7 4
 
3.9%
9 4
 
3.9%
Other Symbol
ValueCountFrequency (%)
㎡ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 48
32.0%
1 25
16.7%
3 15
 
10.0%
0 14
 
9.3%
2 14
 
9.3%
4 10
 
6.7%
5 6
 
4.0%
8 5
 
3.3%
6 5
 
3.3%
7 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102
68.0%
CJK Compat 48
32.0%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 48
100.0%
ASCII
ValueCountFrequency (%)
1 25
24.5%
3 15
14.7%
0 14
13.7%
2 14
13.7%
4 10
 
9.8%
5 6
 
5.9%
8 5
 
4.9%
6 5
 
4.9%
7 4
 
3.9%
9 4
 
3.9%

공시차수
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
20231
38 
20181
4 
20191
4 
20201
 
1
20221
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
20231 38
79.2%
20181 4
 
8.3%
20191 4
 
8.3%
20201 1
 
2.1%
20221 1
 
2.1%

Length

2024-03-13T18:08:40.939706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T18:08:41.043017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231 38
79.2%
20181 4
 
8.3%
20191 4
 
8.3%
20201 1
 
2.1%
20221 1
 
2.1%

주소
Text

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T18:08:41.321160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length19.041667
Min length16

Characters and Unicode

Total characters914
Distinct characters43
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

Unique46 ?
Unique (%)95.8%

Sample

1st row서울특별시 양천구 목동동로12길 60
2nd row서울특별시 양천구 목동동로 430
3rd row서울특별시 양천구 목동서로2길 22
4th row서울특별시 양천구 목동중앙북로10길 7-10
5th row서울특별시 양천구 월정로 280
ValueCountFrequency (%)
서울특별시 48
25.0%
양천구 48
25.0%
목동서로 5
 
2.6%
목동동로 4
 
2.1%
22 3
 
1.6%
30 3
 
1.6%
81-4 2
 
1.0%
130 2
 
1.0%
280 2
 
1.0%
38 2
 
1.0%
Other values (67) 73
38.0%
2024-03-13T18:08:41.774879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
15.8%
서 54
 
5.9%
양 49
 
5.4%
천 49
 
5.4%
특 48
 
5.3%
별 48
 
5.3%
시 48
 
5.3%
구 48
 
5.3%
울 48
 
5.3%
로 48
 
5.3%
Other values (33) 330
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 603
66.0%
Decimal Number 160
 
17.5%
Space Separator 144
 
15.8%
Dash Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 54
9.0%
양 49
 
8.1%
천 49
 
8.1%
특 48
 
8.0%
별 48
 
8.0%
시 48
 
8.0%
구 48
 
8.0%
울 48
 
8.0%
로 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%
Decimal Number
ValueCountFrequency (%)
1 28
17.5%
2 27
16.9%
3 22
13.8%
0 22
13.8%
4 13
8.1%
8 12
7.5%
9 11
 
6.9%
7 10
 
6.2%
6 8
 
5.0%
5 7
 
4.4%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 603
66.0%
Common 311
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 54
9.0%
양 49
 
8.1%
천 49
 
8.1%
특 48
 
8.0%
별 48
 
8.0%
시 48
 
8.0%
구 48
 
8.0%
울 48
 
8.0%
로 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%
Common
ValueCountFrequency (%)
144
46.3%
1 28
 
9.0%
2 27
 
8.7%
3 22
 
7.1%
0 22
 
7.1%
4 13
 
4.2%
8 12
 
3.9%
9 11
 
3.5%
7 10
 
3.2%
6 8
 
2.6%
Other values (2) 14
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 603
66.0%
ASCII 311
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
46.3%
1 28
 
9.0%
2 27
 
8.7%
3 22
 
7.1%
0 22
 
7.1%
4 13
 
4.2%
8 12
 
3.9%
9 11
 
3.5%
7 10
 
3.2%
6 8
 
2.6%
Other values (2) 14
 
4.5%
Hangul
ValueCountFrequency (%)
서 54
9.0%
양 49
 
8.1%
천 49
 
8.1%
특 48
 
8.0%
별 48
 
8.0%
시 48
 
8.0%
구 48
 
8.0%
울 48
 
8.0%
로 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%

Correlations

2024-03-13T18:08:41.897462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
유치원코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립유형1.0001.0001.0000.5790.0000.4970.0000.8620.8820.0000.000
교실수1.0001.0000.5791.0000.9630.8520.6870.8740.8500.2950.000
교실면적1.0001.0000.0000.9631.0000.9650.9510.9740.9451.0000.987
체육장1.0001.0000.4970.8520.9651.0000.0000.9520.0000.0000.000
보건/위생공간1.0001.0000.0000.6870.9510.0001.0000.9710.0000.7850.954
조리실/급식공간1.0001.0000.8620.8740.9740.9520.9711.0000.0000.0000.990
기타공간1.0001.0000.8820.8500.9450.0000.0000.0001.0000.0000.927
공시차수1.0001.0000.0000.2951.0000.0000.7850.0000.0001.0000.703
주소1.0001.0000.0000.0000.9870.0000.9540.9900.9270.7031.000
2024-03-13T18:08:42.034330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시차수설립유형체육장교실수
공시차수1.0000.0000.0000.100
설립유형0.0001.0000.2270.354
체육장0.0000.2271.0000.475
교실수0.1000.3540.4751.000
2024-03-13T18:08:42.161779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립유형교실수체육장공시차수
설립유형1.0000.3540.2270.000
교실수0.3541.0000.4750.100
체육장0.2270.4751.0000.000
공시차수0.0000.1000.0001.000

Missing values

2024-03-13T18:08:35.718376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:08:36.232949image/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

교육청명교육지원청명유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
0서울특별시교육청강서양천교육지원청1ecec08d-05b8-b044-e053-0a32095ab044등대유치원사립(사인)6개375㎡30㎡50㎡225㎡10㎡20231서울특별시 양천구 목동동로12길 60
1서울특별시교육청강서양천교육지원청1ecec08d-08bb-b044-e053-0a32095ab044한서유치원사립(사인)7개350㎡㎡40㎡201㎡30㎡20231서울특별시 양천구 목동동로 430
2서울특별시교육청강서양천교육지원청1ecec08d-08bc-b044-e053-0a32095ab044해림유치원사립(사인)5개461㎡㎡0㎡40㎡10㎡20231서울특별시 양천구 목동서로2길 22
3서울특별시교육청강서양천교육지원청1ecec08d-0913-b044-e053-0a32095ab044신목유치원사립(사인)5개346㎡㎡14㎡36㎡18㎡20231서울특별시 양천구 목동중앙북로10길 7-10
4서울특별시교육청강서양천교육지원청1ecec08d-02b0-b044-e053-0a32095ab044서울강신초등학교병설유치원공립(병설)7개315㎡㎡40㎡106㎡41㎡20231서울특별시 양천구 월정로 280
5서울특별시교육청강서양천교육지원청1ecec08d-0c03-b044-e053-0a32095ab044빛나유치원사립(사인)6개238㎡22㎡24㎡126㎡11㎡20231서울특별시 양천구 목동로 212
6서울특별시교육청강서양천교육지원청1ecec08c-ed80-b044-e053-0a32095ab044샘터유치원사립(사인)5개300㎡㎡30㎡88㎡10㎡20231서울특별시 양천구 신월로 99
7서울특별시교육청강서양천교육지원청1ecec08d-0c04-b044-e053-0a32095ab044서울신기초등학교병설유치원공립(병설)5개337㎡108㎡0㎡49㎡0㎡20231서울특별시 양천구 신정로 292
8서울특별시교육청강서양천교육지원청1ecec08d-0e6c-b044-e053-0a32095ab044경성유치원사립(사인)8개462㎡0㎡180㎡308㎡33㎡20231서울특별시 양천구 목동로3길 57
9서울특별시교육청강서양천교육지원청1ecec08d-0e6d-b044-e053-0a32095ab044등촌유치원사립(사인)5개290㎡133㎡0㎡272㎡99㎡20231서울특별시 양천구 목동중앙북로8길 46
교육청명교육지원청명유치원코드유치원명설립유형교실수교실면적체육장보건/위생공간조리실/급식공간기타공간공시차수주소
38서울특별시교육청강서양천교육지원청1ecec08c-f883-b044-e053-0a32095ab044서울양목초등학교병설유치원공립(병설)7개396㎡㎡33㎡0㎡35㎡20231서울특별시 양천구 목동로11길 30
39서울특별시교육청강서양천교육지원청1ecec08c-f884-b044-e053-0a32095ab044세진유치원사립(사인)3개213㎡㎡16㎡13㎡141㎡20191서울특별시 양천구 월정로46길 9
40서울특별시교육청강서양천교육지원청1ecec08c-f885-b044-e053-0a32095ab044신정유치원사립(사인)14개725㎡227㎡92㎡33㎡342㎡20191서울특별시 양천구 신정로7길 81-4
41서울특별시교육청강서양천교육지원청1ecec08c-f8f6-b044-e053-0a32095ab044목동다솜유치원사립(사인)9개445㎡㎡60㎡203㎡92㎡20231서울특별시 양천구 월정로9길 23-4
42서울특별시교육청강서양천교육지원청1ecec08c-fae5-b044-e053-0a32095ab044신예유치원사립(사인)6개238㎡㎡0㎡0㎡13㎡20231서울특별시 양천구 신정로 290
43서울특별시교육청강서양천교육지원청1ecec08c-fe4b-b044-e053-0a32095ab044아란유치원사립(사인)5개325㎡㎡26㎡181㎡10㎡20231서울특별시 양천구 목동서로 100
44서울특별시교육청강서양천교육지원청1ecec08c-fada-b044-e053-0a32095ab044사슴유치원사립(사인)5개380㎡180㎡10㎡10㎡33㎡20181서울특별시 양천구 곰달래로9길 12
45서울특별시교육청강서양천교육지원청1ecec08d-0121-b044-e053-0a32095ab044어린이의정원유치원사립(사인)9개548㎡㎡70㎡757㎡20㎡20231서울특별시 양천구 목동남로4길 6-46
46서울특별시교육청강서양천교육지원청1ecec08d-018d-b044-e053-0a32095ab044광영유치원사립(법인)7개443㎡0㎡50㎡165㎡11㎡20231서울특별시 양천구 남부순환로30길 17
47서울특별시교육청강서양천교육지원청1ecec08d-04c8-b044-e053-0a32095ab044레인보우유치원사립(법인)6개244㎡㎡60㎡26㎡213㎡20191서울특별시 양천구 목동중앙북로24길 19-8