Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory900.0 B
Average record size in memory37.5 B

Variable types

Text3
DateTime1

Dataset

Description영등포구 관내 결혼식장(예식장, 웨딩홀) 현황입니다.
Author서울특별시 영등포구
URLhttps://www.data.go.kr/data/15100839/fileData.do

Alerts

데이터기준일 has constant value ""Constant
시설명 has unique valuesUnique
도로명주소 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:40:34.343437
Analysis finished2023-12-12 12:40:34.651144
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T21:40:34.804460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10.5
Mean length7.7083333
Min length4

Characters and Unicode

Total characters185
Distinct characters91
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row여의도 웨딩컨벤션
2nd row켄싱턴호텔 여의도
3rd row웨딩여율리
4th row루나미엘레
5th row한전웨딩여의프라자
ValueCountFrequency (%)
여의도 2
 
4.8%
호텔 2
 
4.8%
웨딩홀 2
 
4.8%
더 2
 
4.8%
타임스퀘어 1
 
2.4%
컨벤션 1
 
2.4%
영등포점 1
 
2.4%
kr컨벤션웨딩 1
 
2.4%
그랜드컨벤션센터 1
 
2.4%
웨스턴 1
 
2.4%
Other values (28) 28
66.7%
2023-12-12T21:40:35.139576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
9.7%
웨 9
 
4.9%
딩 8
 
4.3%
컨 6
 
3.2%
벤 6
 
3.2%
션 6
 
3.2%
호 5
 
2.7%
텔 5
 
2.7%
더 4
 
2.2%
드 4
 
2.2%
Other values (81) 114
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
87.0%
Space Separator 18
 
9.7%
Uppercase Letter 4
 
2.2%
Decimal Number 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
웨 9
 
5.6%
딩 8
 
5.0%
컨 6
 
3.7%
벤 6
 
3.7%
션 6
 
3.7%
호 5
 
3.1%
텔 5
 
3.1%
더 4
 
2.5%
드 4
 
2.5%
트 4
 
2.5%
Other values (75) 104
64.6%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
J 1
25.0%
R 1
25.0%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
87.0%
Common 20
 
10.8%
Latin 4
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
웨 9
 
5.6%
딩 8
 
5.0%
컨 6
 
3.7%
벤 6
 
3.7%
션 6
 
3.7%
호 5
 
3.1%
텔 5
 
3.1%
더 4
 
2.5%
드 4
 
2.5%
트 4
 
2.5%
Other values (75) 104
64.6%
Common
ValueCountFrequency (%)
18
90.0%
6 1
 
5.0%
3 1
 
5.0%
Latin
ValueCountFrequency (%)
K 2
50.0%
J 1
25.0%
R 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
87.0%
ASCII 24
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
75.0%
K 2
 
8.3%
J 1
 
4.2%
R 1
 
4.2%
6 1
 
4.2%
3 1
 
4.2%
Hangul
ValueCountFrequency (%)
웨 9
 
5.6%
딩 8
 
5.0%
컨 6
 
3.7%
벤 6
 
3.7%
션 6
 
3.7%
호 5
 
3.1%
텔 5
 
3.1%
더 4
 
2.5%
드 4
 
2.5%
트 4
 
2.5%
Other values (75) 104
64.6%

도로명주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T21:40:35.375131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length23.875
Min length17

Characters and Unicode

Total characters573
Distinct characters91
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 여의대로 14 KT
2nd row서울특별시 영등포구 국회대로 76길 16
3rd row서울특별시 영등포구 국제금융로 6길 26 한국노총빌딩 5층
4th row서울특별시 영등포구 여의공원로 101 CCMM빌딩 12층
5th row서울특별시 영등포구 여의동로 7길 5
ValueCountFrequency (%)
서울특별시 24
 
18.8%
영등포구 24
 
18.8%
국회대로 4
 
3.1%
여의대로 3
 
2.3%
164 2
 
1.6%
센터 2
 
1.6%
의사당대로 2
 
1.6%
문래로 2
 
1.6%
영중로 2
 
1.6%
국제금융로 2
 
1.6%
Other values (58) 61
47.7%
2023-12-12T21:40:35.709841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
18.3%
영 26
 
4.5%
서 25
 
4.4%
울 25
 
4.4%
시 24
 
4.2%
포 24
 
4.2%
별 24
 
4.2%
구 24
 
4.2%
로 24
 
4.2%
등 24
 
4.2%
Other values (81) 248
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
68.1%
Space Separator 105
 
18.3%
Decimal Number 68
 
11.9%
Uppercase Letter 10
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 26
 
6.7%
서 25
 
6.4%
울 25
 
6.4%
시 24
 
6.2%
포 24
 
6.2%
별 24
 
6.2%
구 24
 
6.2%
로 24
 
6.2%
등 24
 
6.2%
특 24
 
6.2%
Other values (65) 146
37.4%
Decimal Number
ValueCountFrequency (%)
1 15
22.1%
5 11
16.2%
6 9
13.2%
2 7
10.3%
8 6
 
8.8%
4 6
 
8.8%
0 5
 
7.4%
3 5
 
7.4%
9 2
 
2.9%
7 2
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
K 3
30.0%
S 2
20.0%
M 2
20.0%
C 2
20.0%
T 1
 
10.0%
Space Separator
ValueCountFrequency (%)
105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
68.1%
Common 173
30.2%
Latin 10
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 26
 
6.7%
서 25
 
6.4%
울 25
 
6.4%
시 24
 
6.2%
포 24
 
6.2%
별 24
 
6.2%
구 24
 
6.2%
로 24
 
6.2%
등 24
 
6.2%
특 24
 
6.2%
Other values (65) 146
37.4%
Common
ValueCountFrequency (%)
105
60.7%
1 15
 
8.7%
5 11
 
6.4%
6 9
 
5.2%
2 7
 
4.0%
8 6
 
3.5%
4 6
 
3.5%
0 5
 
2.9%
3 5
 
2.9%
9 2
 
1.2%
Latin
ValueCountFrequency (%)
K 3
30.0%
S 2
20.0%
M 2
20.0%
C 2
20.0%
T 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
68.1%
ASCII 183
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
57.4%
1 15
 
8.2%
5 11
 
6.0%
6 9
 
4.9%
2 7
 
3.8%
8 6
 
3.3%
4 6
 
3.3%
0 5
 
2.7%
3 5
 
2.7%
K 3
 
1.6%
Other values (6) 11
 
6.0%
Hangul
ValueCountFrequency (%)
영 26
 
6.7%
서 25
 
6.4%
울 25
 
6.4%
시 24
 
6.2%
포 24
 
6.2%
별 24
 
6.2%
구 24
 
6.2%
로 24
 
6.2%
등 24
 
6.2%
특 24
 
6.2%
Other values (65) 146
37.4%

연락처
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T21:40:35.889314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.583333
Min length11

Characters and Unicode

Total characters278
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

Unique24 ?
Unique (%)100.0%

Sample

1st row02-761-3800
2nd row02-6670-7332
3rd row02-6277-0777
4th row02-783-8811
5th row02-787-8338
ValueCountFrequency (%)
02-761-3800 1
 
4.2%
02-6670-7332 1
 
4.2%
02-332-9000 1
 
4.2%
02-842-7200 1
 
4.2%
02-841-4114 1
 
4.2%
02-844-0336 1
 
4.2%
02-6297-7000 1
 
4.2%
02-3667-7776 1
 
4.2%
02-2632-2600 1
 
4.2%
02-6246-5000 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T21:40:36.202771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60
21.6%
- 48
17.3%
2 42
15.1%
7 25
9.0%
8 23
 
8.3%
6 22
 
7.9%
3 21
 
7.6%
4 13
 
4.7%
1 11
 
4.0%
9 7
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
82.7%
Dash Punctuation 48
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60
26.1%
2 42
18.3%
7 25
10.9%
8 23
 
10.0%
6 22
 
9.6%
3 21
 
9.1%
4 13
 
5.7%
1 11
 
4.8%
9 7
 
3.0%
5 6
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 278
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60
21.6%
- 48
17.3%
2 42
15.1%
7 25
9.0%
8 23
 
8.3%
6 22
 
7.9%
3 21
 
7.6%
4 13
 
4.7%
1 11
 
4.0%
9 7
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60
21.6%
- 48
17.3%
2 42
15.1%
7 25
9.0%
8 23
 
8.3%
6 22
 
7.9%
3 21
 
7.6%
4 13
 
4.7%
1 11
 
4.0%
9 7
 
2.5%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2022-06-08 00:00:00
Maximum2022-06-08 00:00:00
2023-12-12T21:40:36.322251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:36.403951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T21:40:36.468122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명도로명주소연락처
시설명1.0001.0001.000
도로명주소1.0001.0001.000
연락처1.0001.0001.000

Missing values

2023-12-12T21:40:34.538679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:40:34.617412image/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

시설명도로명주소연락처데이터기준일
0여의도 웨딩컨벤션서울특별시 영등포구 여의대로 14 KT02-761-38002022-06-08
1켄싱턴호텔 여의도서울특별시 영등포구 국회대로 76길 1602-6670-73322022-06-08
2웨딩여율리서울특별시 영등포구 국제금융로 6길 26 한국노총빌딩 5층02-6277-07772022-06-08
3루나미엘레서울특별시 영등포구 여의공원로 101 CCMM빌딩 12층02-783-88112022-06-08
4한전웨딩여의프라자서울특별시 영등포구 여의동로 7길 502-787-83382022-06-08
563컨벤션센터서울특별시 영등포구 63로 50 한화금융센터02-789-57002022-06-08
6전경련플라자서울특별시 영등포구 여의대로 24 컨퍼런스센터 1층02-2055-47802022-06-08
7더 파티움서울특별시 영등포구 은행로 3002-784-00002022-06-08
8콘래드 호텔서울특별시 영등포구 국제금융로 10 서울 국제금융 센터02-6137-72302022-06-08
9국회예식장서울특별시 영등포구 의사당대로 1 국회소통관 내02-6788-39682022-06-08
시설명도로명주소연락처데이터기준일
14코트야드 메리어트 타임스퀘어서울특별시 영등포구 영중로 15 타임스퀘어02-2638-31492022-06-08
15더 컨벤션 영등포점서울특별시 영등포구 국회대로 38길 202-6246-50002022-06-08
16KR컨벤션웨딩서울특별시 영등포구 국회대로 61202-2632-26002022-06-08
17그랜드컨벤션센터서울특별시 영등포구 양평로 58 당산동 그랜드 컨벤션 센터02-3667-77762022-06-08
18웨스턴 베니비스서울특별시 영등포구 국회대로 55802-6297-70002022-06-08
19공군호텔서울특별시 영등포구 여의대방로 259 공군호텔02-844-03362022-06-08
20해군호텔 웨딩홀서울특별시 영등포구 가마산로 53802-841-41142022-06-08
21백악관 웨딩문화원서울특별시 영등포구 신길로 89 백악관웨딩문화원02-842-72002022-06-08
22규수당 문래점서울특별시 영등포구 문래로 164 SK 리더스뷰 2층02-332-90002022-06-08
23JK 아트컨벤션서울특별시 영등포구 문래로 164 SK 리더스뷰 4층02-2628-91002022-06-08