Overview

Dataset statistics

Number of variables8
Number of observations1721
Missing cells1808
Missing cells (%)13.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory109.4 KiB
Average record size in memory65.1 B

Variable types

Unsupported4
Categorical2
Text2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2799/F/1/datasetView.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
Unnamed: 0 has 1721 (100.0%) missing valuesMissing
서울시 어린이 보호구역 지정현황 has 28 (1.6%) missing valuesMissing
Unnamed: 5 has 28 (1.6%) missing valuesMissing
Unnamed: 7 has 28 (1.6%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
서울시 어린이 보호구역 지정현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 07:31:58.682434
Analysis finished2024-03-13 07:31:59.451777
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1721
Missing (%)100.0%
Memory size15.3 KiB

서울시 어린이 보호구역 지정현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)1.6%
Memory size13.6 KiB

Unnamed: 2
Categorical

Distinct29
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
노원구
 
116
강남구
 
113
성북구
 
101
송파구
 
90
서초구
 
90
Other values (24)
1211 

Length

Max length6
Median length3
Mean length3.0679837
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row관할 자치구
3rd row<NA>
4th row합계
5th row소계

Common Values

ValueCountFrequency (%)
노원구 116
 
6.7%
강남구 113
 
6.6%
성북구 101
 
5.9%
송파구 90
 
5.2%
서초구 90
 
5.2%
강서구 89
 
5.2%
양천구 87
 
5.1%
강동구 86
 
5.0%
동대문구 73
 
4.2%
관악구 70
 
4.1%
Other values (19) 806
46.8%

Length

2024-03-13T16:31:59.740627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노원구 116
 
6.7%
강남구 113
 
6.6%
성북구 101
 
5.9%
송파구 90
 
5.2%
서초구 90
 
5.2%
강서구 89
 
5.2%
양천구 87
 
5.1%
강동구 86
 
5.0%
동대문구 73
 
4.2%
관악구 70
 
4.1%
Other values (20) 807
46.9%

Unnamed: 3
Text

Distinct443
Distinct (%)25.8%
Missing1
Missing (%)0.1%
Memory size13.6 KiB
2024-03-13T16:32:00.004128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length3.7569767
Min length2

Characters and Unicode

Total characters6462
Distinct characters191
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

Unique76 ?
Unique (%)4.4%

Sample

1st row소재지
2nd row행정동
3rd row서울시
4th row종로구
5th row부암동
ValueCountFrequency (%)
중계본동 17
 
1.0%
장안1동 13
 
0.8%
양재1동 13
 
0.8%
길음1동 13
 
0.8%
신정3동 12
 
0.7%
목5동 12
 
0.7%
대치1동 12
 
0.7%
중계1동 12
 
0.7%
진관동 11
 
0.6%
광장동 10
 
0.6%
Other values (431) 1595
92.7%
2024-03-13T16:32:00.392825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1706
26.4%
1 399
 
6.2%
2 365
 
5.6%
3 186
 
2.9%
신 135
 
2.1%
4 113
 
1.7%
계 101
 
1.6%
상 77
 
1.2%
구 75
 
1.2%
곡 74
 
1.1%
Other values (181) 3231
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5254
81.3%
Decimal Number 1169
 
18.1%
Other Punctuation 37
 
0.6%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1706
32.5%
신 135
 
2.6%
계 101
 
1.9%
상 77
 
1.5%
구 75
 
1.4%
곡 74
 
1.4%
산 67
 
1.3%
화 67
 
1.3%
대 66
 
1.3%
양 65
 
1.2%
Other values (169) 2821
53.7%
Decimal Number
ValueCountFrequency (%)
1 399
34.1%
2 365
31.2%
3 186
15.9%
4 113
 
9.7%
5 44
 
3.8%
7 22
 
1.9%
6 21
 
1.8%
8 10
 
0.9%
0 5
 
0.4%
9 4
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 37
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5254
81.3%
Common 1208
 
18.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1706
32.5%
신 135
 
2.6%
계 101
 
1.9%
상 77
 
1.5%
구 75
 
1.4%
곡 74
 
1.4%
산 67
 
1.3%
화 67
 
1.3%
대 66
 
1.3%
양 65
 
1.2%
Other values (169) 2821
53.7%
Common
ValueCountFrequency (%)
1 399
33.0%
2 365
30.2%
3 186
15.4%
4 113
 
9.4%
5 44
 
3.6%
. 37
 
3.1%
7 22
 
1.8%
6 21
 
1.7%
8 10
 
0.8%
0 5
 
0.4%
Other values (2) 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5254
81.3%
ASCII 1208
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1706
32.5%
신 135
 
2.6%
계 101
 
1.9%
상 77
 
1.5%
구 75
 
1.4%
곡 74
 
1.4%
산 67
 
1.3%
화 67
 
1.3%
대 66
 
1.3%
양 65
 
1.2%
Other values (169) 2821
53.7%
ASCII
ValueCountFrequency (%)
1 399
33.0%
2 365
30.2%
3 186
15.4%
4 113
 
9.4%
5 44
 
3.6%
. 37
 
3.1%
7 22
 
1.8%
6 21
 
1.7%
8 10
 
0.8%
0 5
 
0.4%
Other values (2) 6
 
0.5%

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing2
Missing (%)0.1%
Memory size13.6 KiB

Unnamed: 5
Text

MISSING 

Distinct1643
Distinct (%)97.0%
Missing28
Missing (%)1.6%
Memory size13.6 KiB
2024-03-13T16:32:00.578853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length7.7501477
Min length3

Characters and Unicode

Total characters13121
Distinct characters434
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1599 ?
Unique (%)94.4%

Sample

1st row시설명
2nd row상명대학교사범대학부속초등학교
3rd row서울교동초등학교
4th row서울대학교사범대학부설초등학교
5th row서울독립문초등학교
ValueCountFrequency (%)
구립 53
 
3.0%
사랑유치원 4
 
0.2%
이화어린이집 4
 
0.2%
행복한어린이집 3
 
0.2%
선재어린이집 3
 
0.2%
예일유치원 3
 
0.2%
사랑의어린이집 2
 
0.1%
미담어린이집 2
 
0.1%
오르다어린이집 2
 
0.1%
어린왕자어린이집 2
 
0.1%
Other values (1640) 1681
95.6%
2024-03-13T16:32:00.899515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 864
 
6.6%
서 812
 
6.2%
교 809
 
6.2%
울 771
 
5.9%
초 758
 
5.8%
등 756
 
5.8%
원 629
 
4.8%
이 547
 
4.2%
유 521
 
4.0%
치 513
 
3.9%
Other values (424) 6141
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12956
98.7%
Space Separator 66
 
0.5%
Decimal Number 47
 
0.4%
Uppercase Letter 24
 
0.2%
Open Punctuation 14
 
0.1%
Close Punctuation 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 864
 
6.7%
서 812
 
6.3%
교 809
 
6.2%
울 771
 
6.0%
초 758
 
5.9%
등 756
 
5.8%
원 629
 
4.9%
이 547
 
4.2%
유 521
 
4.0%
치 513
 
4.0%
Other values (399) 5976
46.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
16.7%
E 3
12.5%
K 3
12.5%
G 2
8.3%
O 2
8.3%
L 2
8.3%
T 2
8.3%
B 1
 
4.2%
D 1
 
4.2%
C 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
2 13
27.7%
1 8
17.0%
3 7
14.9%
4 7
14.9%
5 4
 
8.5%
0 3
 
6.4%
9 3
 
6.4%
8 1
 
2.1%
6 1
 
2.1%
Space Separator
ValueCountFrequency (%)
66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12956
98.7%
Common 141
 
1.1%
Latin 24
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 864
 
6.7%
서 812
 
6.3%
교 809
 
6.2%
울 771
 
6.0%
초 758
 
5.9%
등 756
 
5.8%
원 629
 
4.9%
이 547
 
4.2%
유 521
 
4.0%
치 513
 
4.0%
Other values (399) 5976
46.1%
Latin
ValueCountFrequency (%)
S 4
16.7%
E 3
12.5%
K 3
12.5%
G 2
8.3%
O 2
8.3%
L 2
8.3%
T 2
8.3%
B 1
 
4.2%
D 1
 
4.2%
C 1
 
4.2%
Other values (3) 3
12.5%
Common
ValueCountFrequency (%)
66
46.8%
( 14
 
9.9%
) 14
 
9.9%
2 13
 
9.2%
1 8
 
5.7%
3 7
 
5.0%
4 7
 
5.0%
5 4
 
2.8%
0 3
 
2.1%
9 3
 
2.1%
Other values (2) 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12956
98.7%
ASCII 165
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 864
 
6.7%
서 812
 
6.3%
교 809
 
6.2%
울 771
 
6.0%
초 758
 
5.9%
등 756
 
5.8%
원 629
 
4.9%
이 547
 
4.2%
유 521
 
4.0%
치 513
 
4.0%
Other values (399) 5976
46.1%
ASCII
ValueCountFrequency (%)
66
40.0%
( 14
 
8.5%
) 14
 
8.5%
2 13
 
7.9%
1 8
 
4.8%
3 7
 
4.2%
4 7
 
4.2%
S 4
 
2.4%
5 4
 
2.4%
0 3
 
1.8%
Other values (15) 25
 
15.2%

Unnamed: 6
Categorical

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
초등학교
606 
유치원
503 
어린이집
485 
학원
 
58
특수학교
 
28
Other values (4)
 
41

Length

Max length18
Median length4
Mean length3.6554329
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row(기준일 : 2023-06-30)
2nd row시설유형
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
초등학교 606
35.2%
유치원 503
29.2%
어린이집 485
28.2%
학원 58
 
3.4%
특수학교 28
 
1.6%
<NA> 27
 
1.6%
외국인학교 12
 
0.7%
(기준일 : 2023-06-30) 1
 
0.1%
시설유형 1
 
0.1%

Length

2024-03-13T16:32:01.024729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:32:01.144019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 606
35.2%
유치원 503
29.2%
어린이집 485
28.1%
학원 58
 
3.4%
특수학교 28
 
1.6%
na 27
 
1.6%
외국인학교 12
 
0.7%
기준일 1
 
0.1%
1
 
0.1%
2023-06-30 1
 
0.1%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)1.6%
Memory size13.6 KiB

Correlations

2024-03-13T16:32:01.227600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 6
Unnamed: 21.0000.746
Unnamed: 60.7461.000
2024-03-13T16:32:01.302460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 6Unnamed: 2
Unnamed: 61.0000.432
Unnamed: 20.4321.000
2024-03-13T16:32:01.392497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 6
Unnamed: 21.0000.432
Unnamed: 60.4321.000

Missing values

2024-03-13T16:31:59.084870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T16:31:59.235982image/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.
2024-03-13T16:31:59.376698image/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

Unnamed: 0서울시 어린이 보호구역 지정현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0<NA>NaN<NA><NA>NaN<NA>(기준일 : 2023-06-30)NaN
1<NA>연번관할 자치구소재지NaN시설명시설유형지정연도
2<NA>NaN<NA>행정동도로명 주소<NA><NA>NaN
3<NA>NaN합계서울시1692<NA><NA>NaN
4<NA>NaN소계종로구46<NA><NA>NaN
5<NA>1종로구부암동홍지문2길1상명대학교사범대학부속초등학교초등학교2006
6<NA>2종로구종로1.2.3.4가동삼일대로446서울교동초등학교초등학교2006
7<NA>3종로구이화동대학로64서울대학교사범대학부설초등학교초등학교1995
8<NA>4종로구무악동통일로12길23서울독립문초등학교초등학교2005
9<NA>5종로구사직동사직로9길19서울매동초등학교초등학교2005
Unnamed: 0서울시 어린이 보호구역 지정현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
1711<NA>1683강동구암사1동상암로89예꿈어린이집어린이집2015-06-16 00:00:00
1712<NA>1684강동구천호3동성안로31마길6예은어린이집어린이집2010-12-09 00:00:00
1713<NA>1685강동구성내3동양재대로1305예일어린이집어린이집2010-12-09 00:00:00
1714<NA>1686강동구길동천호대로1239자이맘어린이집어린이집2020-10-08 00:00:00
1715<NA>1687강동구명일2동동남로67길42푸른숲어린이집어린이집2015-06-16 00:00:00
1716<NA>1688강동구상일1동상암로369주몽학교특수학교1997-02-24 00:00:00
1717<NA>1689강동구고덕2동고덕로295-59한국구화학교특수학교1997-02-24 00:00:00
1718<NA>1690강동구길동천호대로187길73-10예크트리(YEK TREE)학원학원2021-03-29 00:00:00
1719<NA>1691강동구암사3동올림픽로104길36오르다샘앤클래스암사학원학원2021-03-29 00:00:00
1720<NA>1692강동구고덕2동고덕로83길154피아제키즈아카데미학원학원2023

Duplicate rows

Most frequently occurring

Unnamed: 2Unnamed: 3Unnamed: 5Unnamed: 6# duplicates
0노원구중계본동하이레벨수학전문학원학원2