Overview

Dataset statistics

Number of variables7
Number of observations119
Missing cells25
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory57.1 B

Variable types

Text5
Categorical1
DateTime1

Dataset

Description서울특별시 관악구 관내 공동주택의 명칭, 주소, 연락처 등 관련 현황(아파트명, 행정동명, 해당 공동주택 도로명 주소, 관리사무소 전화번호, 팩스,사용승인일) 정보입니다
Author서울특별시 관악구
URLhttps://www.data.go.kr/data/15039534/fileData.do

Alerts

관리사무소_전화번호 has 5 (4.2%) missing valuesMissing
관리사무소_팩스 has 20 (16.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:26:23.772849
Analysis finished2023-12-12 20:26:24.750977
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct115
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:26:24.963899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.512605
Min length3

Characters and Unicode

Total characters894
Distinct characters167
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)93.3%

Sample

1st row보라매삼성아파트
2nd row해태보라매타워
3rd row해바라기
4th row그린아파트
5th row복권아파트
ValueCountFrequency (%)
제창그로힐아파트 2
 
1.7%
현대아파트 2
 
1.7%
낙성대현대아파트 2
 
1.7%
벽산블루밍 2
 
1.7%
건영아파트 1
 
0.8%
관악산휴먼시아임대단지 1
 
0.8%
관악산휴먼시아 1
 
0.8%
건영아파트(2차 1
 
0.8%
임광관악파크 1
 
0.8%
한라타운아파트 1
 
0.8%
Other values (105) 105
88.2%
2023-12-13T05:26:25.434367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 89
 
10.0%
트 80
 
8.9%
파 78
 
8.7%
대 32
 
3.6%
악 17
 
1.9%
관 17
 
1.9%
동 17
 
1.9%
성 16
 
1.8%
) 15
 
1.7%
( 15
 
1.7%
Other values (157) 518
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 829
92.7%
Decimal Number 26
 
2.9%
Close Punctuation 15
 
1.7%
Open Punctuation 15
 
1.7%
Uppercase Letter 5
 
0.6%
Other Punctuation 3
 
0.3%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 89
 
10.7%
트 80
 
9.7%
파 78
 
9.4%
대 32
 
3.9%
악 17
 
2.1%
관 17
 
2.1%
동 17
 
2.1%
성 16
 
1.9%
신 14
 
1.7%
림 14
 
1.7%
Other values (142) 455
54.9%
Decimal Number
ValueCountFrequency (%)
2 13
50.0%
1 5
 
19.2%
3 4
 
15.4%
4 2
 
7.7%
6 1
 
3.8%
5 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
H 1
20.0%
C 1
20.0%
D 1
20.0%
I 1
20.0%
S 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 829
92.7%
Common 60
 
6.7%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 89
 
10.7%
트 80
 
9.7%
파 78
 
9.4%
대 32
 
3.9%
악 17
 
2.1%
관 17
 
2.1%
동 17
 
2.1%
성 16
 
1.9%
신 14
 
1.7%
림 14
 
1.7%
Other values (142) 455
54.9%
Common
ValueCountFrequency (%)
) 15
25.0%
( 15
25.0%
2 13
21.7%
1 5
 
8.3%
3 4
 
6.7%
, 3
 
5.0%
4 2
 
3.3%
1
 
1.7%
6 1
 
1.7%
5 1
 
1.7%
Latin
ValueCountFrequency (%)
H 1
20.0%
C 1
20.0%
D 1
20.0%
I 1
20.0%
S 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 829
92.7%
ASCII 65
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 89
 
10.7%
트 80
 
9.7%
파 78
 
9.4%
대 32
 
3.9%
악 17
 
2.1%
관 17
 
2.1%
동 17
 
2.1%
성 16
 
1.9%
신 14
 
1.7%
림 14
 
1.7%
Other values (142) 455
54.9%
ASCII
ValueCountFrequency (%)
) 15
23.1%
( 15
23.1%
2 13
20.0%
1 5
 
7.7%
3 4
 
6.2%
, 3
 
4.6%
4 2
 
3.1%
H 1
 
1.5%
C 1
 
1.5%
D 1
 
1.5%
Other values (5) 5
 
7.7%

행정동명
Categorical

Distinct21
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
미성동
12 
남현동
11 
삼성동
10 
대학동
9 
성현동
9 
Other values (16)
68 

Length

Max length4
Median length3
Mean length3.0168067
Min length3

Unique

Unique2 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
미성동 12
 
10.1%
남현동 11
 
9.2%
삼성동 10
 
8.4%
대학동 9
 
7.6%
성현동 9
 
7.6%
청룡동 9
 
7.6%
조원동 8
 
6.7%
은천동 6
 
5.0%
행운동 6
 
5.0%
인헌동 5
 
4.2%
Other values (11) 34
28.6%

Length

2023-12-13T05:26:25.611328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미성동 12
 
10.1%
남현동 11
 
9.2%
삼성동 10
 
8.4%
대학동 9
 
7.6%
성현동 9
 
7.6%
청룡동 9
 
7.6%
조원동 8
 
6.7%
은천동 6
 
5.0%
행운동 6
 
5.0%
보라매 5
 
4.2%
Other values (11) 34
28.6%

지번
Text

Distinct99
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:26:25.936035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.7983193
Min length3

Characters and Unicode

Total characters571
Distinct characters18
Distinct categories5 ?
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 (%)66.4%

Sample

1st row1698-1
2nd row729-32
3rd row1500
4th row1702
5th row645-87
ValueCountFrequency (%)
1700 2
 
1.7%
1712 2
 
1.7%
1703-1 2
 
1.7%
1717 2
 
1.7%
1705 2
 
1.7%
1727 2
 
1.7%
1553-1 2
 
1.7%
1723 2
 
1.7%
1719 2
 
1.7%
1716 2
 
1.7%
Other values (90) 100
83.3%
2023-12-13T05:26:26.409715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 168
29.4%
7 90
15.8%
3 47
 
8.2%
2 47
 
8.2%
- 41
 
7.2%
6 40
 
7.0%
0 37
 
6.5%
5 34
 
6.0%
9 23
 
4.0%
8 19
 
3.3%
Other values (8) 25
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 523
91.6%
Dash Punctuation 41
 
7.2%
Other Letter 4
 
0.7%
Other Punctuation 2
 
0.4%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 168
32.1%
7 90
17.2%
3 47
 
9.0%
2 47
 
9.0%
6 40
 
7.6%
0 37
 
7.1%
5 34
 
6.5%
9 23
 
4.4%
8 19
 
3.6%
4 18
 
3.4%
Other Letter
ValueCountFrequency (%)
번 1
25.0%
지 1
25.0%
호 1
25.0%
산 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
/ 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 567
99.3%
Hangul 4
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 168
29.6%
7 90
15.9%
3 47
 
8.3%
2 47
 
8.3%
- 41
 
7.2%
6 40
 
7.1%
0 37
 
6.5%
5 34
 
6.0%
9 23
 
4.1%
8 19
 
3.4%
Other values (4) 21
 
3.7%
Hangul
ValueCountFrequency (%)
번 1
25.0%
지 1
25.0%
호 1
25.0%
산 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 567
99.3%
Hangul 4
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 168
29.6%
7 90
15.9%
3 47
 
8.3%
2 47
 
8.3%
- 41
 
7.2%
6 40
 
7.1%
0 37
 
6.5%
5 34
 
6.0%
9 23
 
4.1%
8 19
 
3.4%
Other values (4) 21
 
3.7%
Hangul
ValueCountFrequency (%)
번 1
25.0%
지 1
25.0%
호 1
25.0%
산 1
25.0%

새주소
Text

Distinct118
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:26:26.752942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length16.226891
Min length14

Characters and Unicode

Total characters1931
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

Unique117 ?
Unique (%)98.3%

Sample

1st row서울시 관악구 보라매로 62
2nd row서울시 관악구 보라매로3길 29
3rd row서울시 관악구 보라매로6길 33
4th row서울시 관악구 봉천로23다길 13
5th row서울시 관악구 은천로5길 39
ValueCountFrequency (%)
서울시 119
25.0%
관악구 119
25.0%
16 5
 
1.1%
호암로 5
 
1.1%
난곡로 5
 
1.1%
관악로 5
 
1.1%
남현길 4
 
0.8%
신림로3가길 3
 
0.6%
7 3
 
0.6%
조원로13길 3
 
0.6%
Other values (158) 205
43.1%
2023-12-13T05:26:27.340832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
357
18.5%
관 133
 
6.9%
악 130
 
6.7%
구 121
 
6.3%
서 119
 
6.2%
울 119
 
6.2%
시 119
 
6.2%
길 88
 
4.6%
1 86
 
4.5%
로 82
 
4.2%
Other values (57) 577
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1162
60.2%
Decimal Number 402
 
20.8%
Space Separator 357
 
18.5%
Dash Punctuation 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 133
11.4%
악 130
11.2%
구 121
10.4%
서 119
10.2%
울 119
10.2%
시 119
10.2%
길 88
7.6%
로 82
 
7.1%
남 18
 
1.5%
신 14
 
1.2%
Other values (45) 219
18.8%
Decimal Number
ValueCountFrequency (%)
1 86
21.4%
2 49
12.2%
3 48
11.9%
6 42
10.4%
5 41
10.2%
4 32
 
8.0%
7 30
 
7.5%
0 29
 
7.2%
9 24
 
6.0%
8 21
 
5.2%
Space Separator
ValueCountFrequency (%)
357
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1162
60.2%
Common 769
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 133
11.4%
악 130
11.2%
구 121
10.4%
서 119
10.2%
울 119
10.2%
시 119
10.2%
길 88
7.6%
로 82
 
7.1%
남 18
 
1.5%
신 14
 
1.2%
Other values (45) 219
18.8%
Common
ValueCountFrequency (%)
357
46.4%
1 86
 
11.2%
2 49
 
6.4%
3 48
 
6.2%
6 42
 
5.5%
5 41
 
5.3%
4 32
 
4.2%
7 30
 
3.9%
0 29
 
3.8%
9 24
 
3.1%
Other values (2) 31
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1162
60.2%
ASCII 769
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
357
46.4%
1 86
 
11.2%
2 49
 
6.4%
3 48
 
6.2%
6 42
 
5.5%
5 41
 
5.3%
4 32
 
4.2%
7 30
 
3.9%
0 29
 
3.8%
9 24
 
3.1%
Other values (2) 31
 
4.0%
Hangul
ValueCountFrequency (%)
관 133
11.4%
악 130
11.2%
구 121
10.4%
서 119
10.2%
울 119
10.2%
시 119
10.2%
길 88
7.6%
로 82
 
7.1%
남 18
 
1.5%
신 14
 
1.2%
Other values (45) 219
18.8%

관리사무소_전화번호
Text

MISSING 

Distinct112
Distinct (%)98.2%
Missing5
Missing (%)4.2%
Memory size1.1 KiB
2023-12-13T05:26:27.662541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.087719
Min length11

Characters and Unicode

Total characters1264
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

Unique111 ?
Unique (%)97.4%

Sample

1st row02-885-4777
2nd row02-836-0020
3rd row02-871-0534
4th row02-883-3303
5th row02-3285-0168
ValueCountFrequency (%)
02-598-1154 3
 
2.6%
02-871-8982 1
 
0.9%
02-885-4777 1
 
0.9%
02-858-6674 1
 
0.9%
02-865-5757 1
 
0.9%
02-854-2228 1
 
0.9%
02-861-0020 1
 
0.9%
02-868-4586 1
 
0.9%
02-830-7227 1
 
0.9%
02-853-6395 1
 
0.9%
Other values (102) 102
89.5%
2023-12-13T05:26:28.102966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 228
18.0%
8 197
15.6%
2 182
14.4%
0 159
12.6%
7 101
8.0%
5 80
 
6.3%
1 71
 
5.6%
4 69
 
5.5%
3 67
 
5.3%
6 56
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1036
82.0%
Dash Punctuation 228
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 197
19.0%
2 182
17.6%
0 159
15.3%
7 101
9.7%
5 80
7.7%
1 71
 
6.9%
4 69
 
6.7%
3 67
 
6.5%
6 56
 
5.4%
9 54
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 228
18.0%
8 197
15.6%
2 182
14.4%
0 159
12.6%
7 101
8.0%
5 80
 
6.3%
1 71
 
5.6%
4 69
 
5.5%
3 67
 
5.3%
6 56
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 228
18.0%
8 197
15.6%
2 182
14.4%
0 159
12.6%
7 101
8.0%
5 80
 
6.3%
1 71
 
5.6%
4 69
 
5.5%
3 67
 
5.3%
6 56
 
4.4%

관리사무소_팩스
Text

MISSING 

Distinct95
Distinct (%)96.0%
Missing20
Missing (%)16.8%
Memory size1.1 KiB
2023-12-13T05:26:28.397457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.20202
Min length11

Characters and Unicode

Total characters1109
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

Unique93 ?
Unique (%)93.9%

Sample

1st row02-885-4778
2nd row02-844-6110
3rd row02-3285-0169
4th row02-3285-4236
5th row02-877-9862
ValueCountFrequency (%)
02-598-1153 4
 
4.0%
02-6084-9878 2
 
2.0%
02-883-9423 1
 
1.0%
02-868-1872 1
 
1.0%
02-6334-4586 1
 
1.0%
02-868-4535 1
 
1.0%
02-859-3415 1
 
1.0%
02-838-1813 1
 
1.0%
02-869-7286 1
 
1.0%
02-854-3728 1
 
1.0%
Other values (85) 85
85.9%
2023-12-13T05:26:28.839482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 198
17.9%
2 166
15.0%
8 161
14.5%
0 136
12.3%
7 80
7.2%
5 71
 
6.4%
1 63
 
5.7%
3 63
 
5.7%
6 62
 
5.6%
4 56
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 911
82.1%
Dash Punctuation 198
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 166
18.2%
8 161
17.7%
0 136
14.9%
7 80
8.8%
5 71
7.8%
1 63
 
6.9%
3 63
 
6.9%
6 62
 
6.8%
4 56
 
6.1%
9 53
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 198
17.9%
2 166
15.0%
8 161
14.5%
0 136
12.3%
7 80
7.2%
5 71
 
6.4%
1 63
 
5.7%
3 63
 
5.7%
6 62
 
5.6%
4 56
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 198
17.9%
2 166
15.0%
8 161
14.5%
0 136
12.3%
7 80
7.2%
5 71
 
6.4%
1 63
 
5.7%
3 63
 
5.7%
6 62
 
5.6%
4 56
 
5.0%

사용승인일
Date

Distinct110
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1971-11-15 00:00:00
Maximum2022-08-29 00:00:00
2023-12-13T05:26:29.027650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:26:29.230052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-13T05:26:29.349695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명지번관리사무소_팩스
행정동명1.0000.0001.000
지번0.0001.0000.603
관리사무소_팩스1.0000.6031.000

Missing values

2023-12-13T05:26:24.369322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:26:24.525511image/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.
2023-12-13T05:26:24.691685image/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

아파트명행정동명지번새주소관리사무소_전화번호관리사무소_팩스사용승인일
0보라매삼성아파트보라매1698-1서울시 관악구 보라매로 6202-885-477702-885-47781996-04-25
1해태보라매타워보라매729-32서울시 관악구 보라매로3길 2902-836-002002-844-61101996-10-18
2해바라기보라매1500서울시 관악구 보라매로6길 3302-871-0534<NA>1978-08-20
3그린아파트보라매1702서울시 관악구 봉천로23다길 13<NA><NA>1999-11-19
4복권아파트보라매645-87서울시 관악구 은천로5길 3902-883-3303<NA>1971-11-15
5두산아파트은천동1708-1서울시 관악구 은천로 8602-3285-016802-3285-01692000-12-28
6두산아파트(임대)은천동1708-2서울시 관악구 양녕로 3102-3285-423502-3285-42362000-12-28
7벽산블루밍은천동1718서울시 관악구 은천로 9302-877-986402-877-98622005-06-30
8벽산블루밍(임대)은천동1718-1서울시 관악구 양녕로11702-3285-961402-3285-96152005-06-30
9벽산블루밍3차은천동1720서울시 관악구 은천로15길 2402-887-375102-887-37522004-12-20
아파트명행정동명지번새주소관리사무소_전화번호관리사무소_팩스사용승인일
109청화아파트삼성동1729서울시 관악구 호암로16길 1102-887-050802-887-05082004-09-24
110건영아파트(3차)대학동1703-1서울시 관악구 신림로3길 4002-872-964302-871-16951996-06-18
111금호타운대학동1705서울시 관악구 대학18길 902-889-651202-873-94431997-05-03
112대학동현대아파트대학동255-189서울시 관악구 대학20길 2702-873-625002-6278-62501991-10-12
113금호2타운대학동1706서울시 관악구 신림로3가길 702-876-733102-6083-73341999-06-01
114청광아파트대학동1716서울시 관악구 신림로3가길 45-2402-884-960302-884-96032000-01-15
115서초그린아파트대학동1732서울시 관악구 신림로7길 3402-871-7979<NA>2005-06-07
116건영신림5차아파트대학동233-11서울시 관악구 신림로3가길 45-1002-877-408702-877-40871995-03-27
117관악아파트대학동244서울시 관악구 대학7길 2602-885-8441<NA>1983-12-20
118신동아아파트대학동산28-9서울시 관악구 신림로11길 15102-876-191202-876-19121994-01-04