Overview

Dataset statistics

Number of variables4
Number of observations86
Missing cells6
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory33.5 B

Variable types

Text3
DateTime1

Dataset

Description서울특별시 관악구에서 운영되고있는 안경업소의 업소명, 소재지 주소 등 현황(안경업소명, 소재지 도로명주소, 소재지 전화번호 등)
URLhttps://www.data.go.kr/data/15048014/fileData.do

Alerts

데이터기준일 has constant value ""Constant
소재지전화번호 has 6 (7.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 11:26:59.638093
Analysis finished2023-12-12 11:27:00.666050
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct85
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T20:27:00.911126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.4883721
Min length4

Characters and Unicode

Total characters730
Distinct characters156
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)97.7%

Sample

1st row으뜸50안경서울대2호점
2nd row뷰맵낙성대스토어
3rd row다비치안경서울대입구역점
4th row스타옵틱앤오렌즈 타임스트림점
5th row다비치안경원 구로디지털단지역점
ValueCountFrequency (%)
안경산책 2
 
2.0%
신림점 2
 
2.0%
오렌즈안경원 2
 
2.0%
낙성대점 2
 
2.0%
로데오안경원 1
 
1.0%
일공공일안경원(봉천점 1
 
1.0%
빠세빠세안경원 1
 
1.0%
르네상스안경원 1
 
1.0%
1001안경콘택트(신대방역점 1
 
1.0%
엑스포안경 1
 
1.0%
Other values (87) 87
86.1%
2023-12-12T20:27:01.476501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 88
 
12.1%
경 88
 
12.1%
원 43
 
5.9%
점 31
 
4.2%
15
 
2.1%
스 15
 
2.1%
대 15
 
2.1%
트 14
 
1.9%
렌 13
 
1.8%
콘 12
 
1.6%
Other values (146) 396
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 660
90.4%
Decimal Number 20
 
2.7%
Space Separator 15
 
2.1%
Close Punctuation 10
 
1.4%
Open Punctuation 10
 
1.4%
Lowercase Letter 7
 
1.0%
Uppercase Letter 7
 
1.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 88
 
13.3%
경 88
 
13.3%
원 43
 
6.5%
점 31
 
4.7%
스 15
 
2.3%
대 15
 
2.3%
트 14
 
2.1%
렌 13
 
2.0%
콘 12
 
1.8%
이 12
 
1.8%
Other values (125) 329
49.8%
Decimal Number
ValueCountFrequency (%)
0 7
35.0%
5 5
25.0%
2 3
15.0%
1 2
 
10.0%
9 2
 
10.0%
3 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
E 2
28.6%
L 1
14.3%
Y 1
14.3%
O 1
14.3%
A 1
14.3%
B 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
y 1
 
14.3%
n 1
 
14.3%
i 1
 
14.3%
o 1
 
14.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 660
90.4%
Common 56
 
7.7%
Latin 14
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 88
 
13.3%
경 88
 
13.3%
원 43
 
6.5%
점 31
 
4.7%
스 15
 
2.3%
대 15
 
2.3%
트 14
 
2.1%
렌 13
 
2.0%
콘 12
 
1.8%
이 12
 
1.8%
Other values (125) 329
49.8%
Latin
ValueCountFrequency (%)
e 3
21.4%
E 2
14.3%
L 1
 
7.1%
Y 1
 
7.1%
O 1
 
7.1%
y 1
 
7.1%
A 1
 
7.1%
n 1
 
7.1%
i 1
 
7.1%
o 1
 
7.1%
Common
ValueCountFrequency (%)
15
26.8%
) 10
17.9%
( 10
17.9%
0 7
12.5%
5 5
 
8.9%
2 3
 
5.4%
1 2
 
3.6%
9 2
 
3.6%
3 1
 
1.8%
, 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 660
90.4%
ASCII 70
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 88
 
13.3%
경 88
 
13.3%
원 43
 
6.5%
점 31
 
4.7%
스 15
 
2.3%
대 15
 
2.3%
트 14
 
2.1%
렌 13
 
2.0%
콘 12
 
1.8%
이 12
 
1.8%
Other values (125) 329
49.8%
ASCII
ValueCountFrequency (%)
15
21.4%
) 10
14.3%
( 10
14.3%
0 7
10.0%
5 5
 
7.1%
e 3
 
4.3%
2 3
 
4.3%
1 2
 
2.9%
9 2
 
2.9%
E 2
 
2.9%
Other values (11) 11
15.7%

소재지도로명주소
Text

Distinct85
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T20:27:01.870984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length27.953488
Min length21

Characters and Unicode

Total characters2404
Distinct characters124
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)97.7%

Sample

1st row서울특별시 관악구 관악로 199, 2층 202호 (봉천동)
2nd row서울특별시 관악구 남부순환로 1921, 금강빌딩 1층 (봉천동)
3rd row서울특별시 관악구 남부순환로 1835, 1,2층 (봉천동)
4th row서울특별시 관악구 신림로 330, 포도몰 지하1층 (신림동)
5th row서울특별시 관악구 시흥대로 570, 1, 2층 (신림동)
ValueCountFrequency (%)
서울특별시 86
17.3%
관악구 86
17.3%
신림동 46
 
9.3%
봉천동 35
 
7.1%
남부순환로 19
 
3.8%
신림로 16
 
3.2%
1층 11
 
2.2%
관악로 8
 
1.6%
은천로 7
 
1.4%
남현동 5
 
1.0%
Other values (152) 177
35.7%
2023-12-12T20:27:02.636005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
410
 
17.1%
악 95
 
4.0%
1 95
 
4.0%
관 95
 
4.0%
서 88
 
3.7%
울 87
 
3.6%
구 87
 
3.6%
동 87
 
3.6%
시 87
 
3.6%
( 86
 
3.6%
Other values (114) 1187
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1425
59.3%
Space Separator 410
 
17.1%
Decimal Number 333
 
13.9%
Open Punctuation 86
 
3.6%
Close Punctuation 86
 
3.6%
Other Punctuation 56
 
2.3%
Dash Punctuation 4
 
0.2%
Uppercase Letter 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
악 95
 
6.7%
관 95
 
6.7%
서 88
 
6.2%
울 87
 
6.1%
구 87
 
6.1%
동 87
 
6.1%
시 87
 
6.1%
별 86
 
6.0%
특 86
 
6.0%
로 78
 
5.5%
Other values (95) 549
38.5%
Decimal Number
ValueCountFrequency (%)
1 95
28.5%
2 37
 
11.1%
0 36
 
10.8%
3 36
 
10.8%
4 26
 
7.8%
6 25
 
7.5%
9 24
 
7.2%
5 21
 
6.3%
7 21
 
6.3%
8 12
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
W 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1425
59.3%
Common 975
40.6%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
악 95
 
6.7%
관 95
 
6.7%
서 88
 
6.2%
울 87
 
6.1%
구 87
 
6.1%
동 87
 
6.1%
시 87
 
6.1%
별 86
 
6.0%
특 86
 
6.0%
로 78
 
5.5%
Other values (95) 549
38.5%
Common
ValueCountFrequency (%)
410
42.1%
1 95
 
9.7%
( 86
 
8.8%
) 86
 
8.8%
, 56
 
5.7%
2 37
 
3.8%
0 36
 
3.7%
3 36
 
3.7%
4 26
 
2.7%
6 25
 
2.6%
Other values (5) 82
 
8.4%
Latin
ValueCountFrequency (%)
S 1
25.0%
W 1
25.0%
s 1
25.0%
k 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1425
59.3%
ASCII 979
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
410
41.9%
1 95
 
9.7%
( 86
 
8.8%
) 86
 
8.8%
, 56
 
5.7%
2 37
 
3.8%
0 36
 
3.7%
3 36
 
3.7%
4 26
 
2.7%
6 25
 
2.6%
Other values (9) 86
 
8.8%
Hangul
ValueCountFrequency (%)
악 95
 
6.7%
관 95
 
6.7%
서 88
 
6.2%
울 87
 
6.1%
구 87
 
6.1%
동 87
 
6.1%
시 87
 
6.1%
별 86
 
6.0%
특 86
 
6.0%
로 78
 
5.5%
Other values (95) 549
38.5%

소재지전화번호
Text

MISSING 

Distinct78
Distinct (%)97.5%
Missing6
Missing (%)7.0%
Memory size820.0 B
2023-12-12T20:27:03.047969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.55
Min length11

Characters and Unicode

Total characters924
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

Unique76 ?
Unique (%)95.0%

Sample

1st row0507-1443-5060
2nd row070-8691-3583
3rd row02-875-1357
4th row0507-1412-7078
5th row02-586-9898
ValueCountFrequency (%)
02-884-3431 2
 
2.5%
02-872-1001 2
 
2.5%
02-871-6267 1
 
1.2%
02-883-1999 1
 
1.2%
0507-1443-5060 1
 
1.2%
02-598-3456 1
 
1.2%
02-6299-7143 1
 
1.2%
02-856-1001 1
 
1.2%
02-868-0871 1
 
1.2%
02-862-5696 1
 
1.2%
Other values (68) 68
85.0%
2023-12-12T20:27:04.205401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 171
18.5%
- 160
17.3%
8 133
14.4%
2 111
12.0%
1 62
 
6.7%
7 61
 
6.6%
3 58
 
6.3%
5 51
 
5.5%
9 42
 
4.5%
6 39
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 764
82.7%
Dash Punctuation 160
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171
22.4%
8 133
17.4%
2 111
14.5%
1 62
 
8.1%
7 61
 
8.0%
3 58
 
7.6%
5 51
 
6.7%
9 42
 
5.5%
6 39
 
5.1%
4 36
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 924
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171
18.5%
- 160
17.3%
8 133
14.4%
2 111
12.0%
1 62
 
6.7%
7 61
 
6.6%
3 58
 
6.3%
5 51
 
5.5%
9 42
 
4.5%
6 39
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 924
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171
18.5%
- 160
17.3%
8 133
14.4%
2 111
12.0%
1 62
 
6.7%
7 61
 
6.6%
3 58
 
6.3%
5 51
 
5.5%
9 42
 
4.5%
6 39
 
4.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
Minimum2022-08-10 00:00:00
Maximum2022-08-10 00:00:00
2023-12-12T20:27:04.404215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:27:04.562443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T20:27:04.699450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지도로명주소소재지전화번호
업소명1.0000.9991.000
소재지도로명주소0.9991.0000.996
소재지전화번호1.0000.9961.000

Missing values

2023-12-12T20:27:00.491942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:27:00.610796image/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

업소명소재지도로명주소소재지전화번호데이터기준일
0으뜸50안경서울대2호점서울특별시 관악구 관악로 199, 2층 202호 (봉천동)0507-1443-50602022-08-10
1뷰맵낙성대스토어서울특별시 관악구 남부순환로 1921, 금강빌딩 1층 (봉천동)070-8691-35832022-08-10
2다비치안경서울대입구역점서울특별시 관악구 남부순환로 1835, 1,2층 (봉천동)02-875-13572022-08-10
3스타옵틱앤오렌즈 타임스트림점서울특별시 관악구 신림로 330, 포도몰 지하1층 (신림동)<NA>2022-08-10
4다비치안경원 구로디지털단지역점서울특별시 관악구 시흥대로 570, 1, 2층 (신림동)0507-1412-70782022-08-10
5오렌즈사당점서울특별시 관악구 과천대로 951, 연송빌딩 (남현동)02-586-98982022-08-10
6으뜸플러스안경 서울신림점서울특별시 관악구 신원로 35, 삼모 더 프라임 타워 2층 201호 (신림동)0507-1464-70242022-08-10
7그랑프리안경원서울특별시 관악구 대학길 6 (신림동)02-3285-24252022-08-10
8보이네안경(낙성대2호점)서울특별시 관악구 남부순환로 1944, 1층 (봉천동)0507-1328-24192022-08-10
9으뜸50안경서울대점서울특별시 관악구 관악로 164, 209호 (봉천동, 대우디오슈페리움1단지)02-877-50602022-08-10
업소명소재지도로명주소소재지전화번호데이터기준일
76안경미인서울특별시 관악구 양녕로 30 (봉천동)<NA>2022-08-10
77서울대학교구내안경부서울특별시 관악구 관악로 1 (신림동, 서울대학교 구내)<NA>2022-08-10
78오렌지안경원서울특별시 관악구 관악로 168, 1층 (봉천동, 대오디오슈페리움2)02-873-51052022-08-10
79아이데코안경(서울대입구역점)서울특별시 관악구 관악로 230 (봉천동)02-885-33732022-08-10
80에그엘로우안경원서울특별시 관악구 남부순환로 1820, 에그엘로우 (봉천동)02-889-44372022-08-10
81안경박사안경서울특별시 관악구 신림로 301 (신림동)02-877-00132022-08-10
82한독안경원서울특별시 관악구 남부순환로 1740, 명당빌딩 (봉천동)02-885-70072022-08-10
83안경산책서울특별시 관악구 은천로 35 (봉천동)02-884-34312022-08-10
84신림안경원서울특별시 관악구 신림로 307 (신림동)0507-1422-77522022-08-10
85이태리안경원서울특별시 관악구 신림로 327, 1층 (신림동)02-888-48492022-08-10