Overview

Dataset statistics

Number of variables4
Number of observations62
Missing cells16
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory34.1 B

Variable types

Text4

Dataset

Description서울특별시 종로구 관내 안경업소 현황에 관한 데이터입니다. 안경업소의 사업자명, 전화번호, 주소에 대한 정보를 확인할 수 있습니다.
Author서울특별시 종로구
URLhttps://www.data.go.kr/data/15075941/fileData.do

Alerts

전화번호 has 10 (16.1%) missing valuesMissing
지번주소 has 6 (9.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:05:45.104489
Analysis finished2023-12-12 18:05:46.021052
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct61
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T03:05:46.252490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length6.7258065
Min length3

Characters and Unicode

Total characters417
Distinct characters132
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

Unique60 ?
Unique (%)96.8%

Sample

1st row으뜸50안경 동묘앞역점
2nd row경희궁마인즈아이
3rd row명성안경
4th row미소안경 보화보석
5th row블링크안경 혜화점
ValueCountFrequency (%)
명성안경 2
 
2.9%
대학로점 2
 
2.9%
으뜸50안경 2
 
2.9%
현대구내안경원 1
 
1.4%
스타안경원 1
 
1.4%
대학안경 1
 
1.4%
남대문안경 1
 
1.4%
성균관대점 1
 
1.4%
글라스타안경 1
 
1.4%
안경이야기 1
 
1.4%
Other values (57) 57
81.4%
2023-12-13T03:05:46.739784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 53
 
12.7%
안 51
 
12.2%
원 13
 
3.1%
점 12
 
2.9%
로 11
 
2.6%
트 9
 
2.2%
택 8
 
1.9%
콘 8
 
1.9%
보 8
 
1.9%
8
 
1.9%
Other values (122) 236
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
91.4%
Uppercase Letter 10
 
2.4%
Space Separator 8
 
1.9%
Decimal Number 6
 
1.4%
Lowercase Letter 5
 
1.2%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Other Punctuation 2
 
0.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 53
 
13.9%
안 51
 
13.4%
원 13
 
3.4%
점 12
 
3.1%
로 11
 
2.9%
트 9
 
2.4%
택 8
 
2.1%
콘 8
 
2.1%
보 8
 
2.1%
대 8
 
2.1%
Other values (101) 200
52.5%
Uppercase Letter
ValueCountFrequency (%)
N 2
20.0%
A 2
20.0%
D 1
10.0%
R 1
10.0%
B 1
10.0%
I 1
10.0%
L 1
10.0%
P 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
s 1
20.0%
n 1
20.0%
l 1
20.0%
o 1
20.0%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
5 3
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
91.4%
Common 21
 
5.0%
Latin 15
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 53
 
13.9%
안 51
 
13.4%
원 13
 
3.4%
점 12
 
3.1%
로 11
 
2.9%
트 9
 
2.4%
택 8
 
2.1%
콘 8
 
2.1%
보 8
 
2.1%
대 8
 
2.1%
Other values (101) 200
52.5%
Latin
ValueCountFrequency (%)
N 2
13.3%
A 2
13.3%
e 1
 
6.7%
D 1
 
6.7%
R 1
 
6.7%
B 1
 
6.7%
I 1
 
6.7%
L 1
 
6.7%
P 1
 
6.7%
s 1
 
6.7%
Other values (3) 3
20.0%
Common
ValueCountFrequency (%)
8
38.1%
0 3
 
14.3%
5 3
 
14.3%
( 2
 
9.5%
) 2
 
9.5%
. 1
 
4.8%
- 1
 
4.8%
, 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
91.4%
ASCII 36
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 53
 
13.9%
안 51
 
13.4%
원 13
 
3.4%
점 12
 
3.1%
로 11
 
2.9%
트 9
 
2.4%
택 8
 
2.1%
콘 8
 
2.1%
보 8
 
2.1%
대 8
 
2.1%
Other values (101) 200
52.5%
ASCII
ValueCountFrequency (%)
8
22.2%
0 3
 
8.3%
5 3
 
8.3%
N 2
 
5.6%
( 2
 
5.6%
) 2
 
5.6%
A 2
 
5.6%
. 1
 
2.8%
e 1
 
2.8%
D 1
 
2.8%
Other values (11) 11
30.6%

전화번호
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing10
Missing (%)16.1%
Memory size628.0 B
2023-12-13T03:05:47.030227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11.134615
Min length8

Characters and Unicode

Total characters579
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row02-743-7779
2nd row1588-9947
3rd row02-766-1017
4th row02-747-5707
5th row02-737-5169
ValueCountFrequency (%)
02-743-7779 1
 
1.9%
1588-9947 1
 
1.9%
02-741-8774 1
 
1.9%
02-744-6006 1
 
1.9%
747-2482 1
 
1.9%
02-2233-9535 1
 
1.9%
02-744-9173 1
 
1.9%
02-763-7297 1
 
1.9%
02-741-0428 1
 
1.9%
02-746-7949 1
 
1.9%
Other values (42) 42
80.8%
2023-12-13T03:05:47.423849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 99
17.1%
2 89
15.4%
0 86
14.9%
7 79
13.6%
3 43
7.4%
4 37
 
6.4%
1 32
 
5.5%
9 30
 
5.2%
6 30
 
5.2%
8 27
 
4.7%
Other values (3) 27
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 478
82.6%
Dash Punctuation 99
 
17.1%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 89
18.6%
0 86
18.0%
7 79
16.5%
3 43
9.0%
4 37
7.7%
1 32
 
6.7%
9 30
 
6.3%
6 30
 
6.3%
8 27
 
5.6%
5 25
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 579
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 99
17.1%
2 89
15.4%
0 86
14.9%
7 79
13.6%
3 43
7.4%
4 37
 
6.4%
1 32
 
5.5%
9 30
 
5.2%
6 30
 
5.2%
8 27
 
4.7%
Other values (3) 27
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 99
17.1%
2 89
15.4%
0 86
14.9%
7 79
13.6%
3 43
7.4%
4 37
 
6.4%
1 32
 
5.5%
9 30
 
5.2%
6 30
 
5.2%
8 27
 
4.7%
Other values (3) 27
 
4.7%

지번주소
Text

MISSING 

Distinct55
Distinct (%)98.2%
Missing6
Missing (%)9.7%
Memory size628.0 B
2023-12-13T03:05:47.758830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35.5
Mean length26.5
Min length17

Characters and Unicode

Total characters1484
Distinct characters126
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

Unique54 ?
Unique (%)96.4%

Sample

1st row서울특별시 종로구 숭인동 310 종로대우디오빌
2nd row서울특별시 종로구 내수동 72 경희궁의아침 3단지 161호
3rd row서울특별시 종로구 창신동 644
4th row서울특별시 종로구 종로5가 98번지 금원빌딩
5th row서울특별시 종로구 혜화동 122번지 4호
ValueCountFrequency (%)
서울특별시 56
 
17.8%
종로구 56
 
17.8%
종로5가 7
 
2.2%
1층 6
 
1.9%
1호 6
 
1.9%
창신동 5
 
1.6%
지하1층 4
 
1.3%
명륜2가 4
 
1.3%
4호 4
 
1.3%
종로2가 4
 
1.3%
Other values (135) 162
51.6%
2023-12-13T03:05:48.233407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
259
 
17.5%
로 80
 
5.4%
종 78
 
5.3%
1 64
 
4.3%
지 63
 
4.2%
서 58
 
3.9%
시 57
 
3.8%
울 57
 
3.8%
구 56
 
3.8%
특 56
 
3.8%
Other values (116) 656
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 969
65.3%
Space Separator 259
 
17.5%
Decimal Number 249
 
16.8%
Other Punctuation 4
 
0.3%
Math Symbol 1
 
0.1%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 80
 
8.3%
종 78
 
8.0%
지 63
 
6.5%
서 58
 
6.0%
시 57
 
5.9%
울 57
 
5.9%
구 56
 
5.8%
특 56
 
5.8%
별 56
 
5.8%
번 49
 
5.1%
Other values (101) 359
37.0%
Decimal Number
ValueCountFrequency (%)
1 64
25.7%
2 47
18.9%
3 31
12.4%
5 23
 
9.2%
4 21
 
8.4%
6 19
 
7.6%
8 17
 
6.8%
0 11
 
4.4%
9 8
 
3.2%
7 8
 
3.2%
Space Separator
ValueCountFrequency (%)
259
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 969
65.3%
Common 514
34.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 80
 
8.3%
종 78
 
8.0%
지 63
 
6.5%
서 58
 
6.0%
시 57
 
5.9%
울 57
 
5.9%
구 56
 
5.8%
특 56
 
5.8%
별 56
 
5.8%
번 49
 
5.1%
Other values (101) 359
37.0%
Common
ValueCountFrequency (%)
259
50.4%
1 64
 
12.5%
2 47
 
9.1%
3 31
 
6.0%
5 23
 
4.5%
4 21
 
4.1%
6 19
 
3.7%
8 17
 
3.3%
0 11
 
2.1%
9 8
 
1.6%
Other values (4) 14
 
2.7%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 969
65.3%
ASCII 515
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
50.3%
1 64
 
12.4%
2 47
 
9.1%
3 31
 
6.0%
5 23
 
4.5%
4 21
 
4.1%
6 19
 
3.7%
8 17
 
3.3%
0 11
 
2.1%
9 8
 
1.6%
Other values (5) 15
 
2.9%
Hangul
ValueCountFrequency (%)
로 80
 
8.3%
종 78
 
8.0%
지 63
 
6.5%
서 58
 
6.0%
시 57
 
5.9%
울 57
 
5.9%
구 56
 
5.8%
특 56
 
5.8%
별 56
 
5.8%
번 49
 
5.1%
Other values (101) 359
37.0%

도로명주소
Text

Distinct61
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T03:05:48.573945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length40.5
Mean length31.758065
Min length20

Characters and Unicode

Total characters1969
Distinct characters148
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

Unique60 ?
Unique (%)96.8%

Sample

1st row서울특별시 종로구 종로 344, 305호 (숭인동, 종로대우디오빌)
2nd row서울특별시 종로구 사직로8길 34, 경희궁의아침 3단지 161호 (내수동)
3rd row서울특별시 종로구 창신길 75 (창신동)
4th row서울특별시 종로구 종로 207, 금원빌딩 2층 (종로5가)
5th row서울특별시 종로구 창경궁로 271 (혜화동)
ValueCountFrequency (%)
서울특별시 62
 
15.8%
종로구 62
 
15.8%
종로 21
 
5.4%
1층 10
 
2.6%
창신동 8
 
2.0%
종로5가 6
 
1.5%
명륜2가 6
 
1.5%
지하1층 5
 
1.3%
숭인동 4
 
1.0%
성균관로 4
 
1.0%
Other values (165) 204
52.0%
2023-12-13T03:05:49.080621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
331
 
16.8%
로 136
 
6.9%
종 108
 
5.5%
1 74
 
3.8%
서 65
 
3.3%
울 64
 
3.3%
, 64
 
3.3%
시 64
 
3.3%
) 63
 
3.2%
구 62
 
3.1%
Other values (138) 938
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1142
58.0%
Space Separator 331
 
16.8%
Decimal Number 286
 
14.5%
Other Punctuation 64
 
3.3%
Close Punctuation 63
 
3.2%
Open Punctuation 62
 
3.1%
Dash Punctuation 17
 
0.9%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 136
 
11.9%
종 108
 
9.5%
서 65
 
5.7%
울 64
 
5.6%
시 64
 
5.6%
구 62
 
5.4%
특 62
 
5.4%
별 62
 
5.4%
동 46
 
4.0%
가 29
 
2.5%
Other values (120) 444
38.9%
Decimal Number
ValueCountFrequency (%)
1 74
25.9%
2 59
20.6%
3 35
12.2%
5 24
 
8.4%
4 19
 
6.6%
0 18
 
6.3%
9 17
 
5.9%
8 14
 
4.9%
7 14
 
4.9%
6 12
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
331
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1142
58.0%
Common 824
41.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 136
 
11.9%
종 108
 
9.5%
서 65
 
5.7%
울 64
 
5.6%
시 64
 
5.6%
구 62
 
5.4%
특 62
 
5.4%
별 62
 
5.4%
동 46
 
4.0%
가 29
 
2.5%
Other values (120) 444
38.9%
Common
ValueCountFrequency (%)
331
40.2%
1 74
 
9.0%
, 64
 
7.8%
) 63
 
7.6%
( 62
 
7.5%
2 59
 
7.2%
3 35
 
4.2%
5 24
 
2.9%
4 19
 
2.3%
0 18
 
2.2%
Other values (6) 75
 
9.1%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1142
58.0%
ASCII 827
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
40.0%
1 74
 
8.9%
, 64
 
7.7%
) 63
 
7.6%
( 62
 
7.5%
2 59
 
7.1%
3 35
 
4.2%
5 24
 
2.9%
4 19
 
2.3%
0 18
 
2.2%
Other values (8) 78
 
9.4%
Hangul
ValueCountFrequency (%)
로 136
 
11.9%
종 108
 
9.5%
서 65
 
5.7%
울 64
 
5.6%
시 64
 
5.6%
구 62
 
5.4%
특 62
 
5.4%
별 62
 
5.4%
동 46
 
4.0%
가 29
 
2.5%
Other values (120) 444
38.9%

Correlations

2023-12-13T03:05:49.522114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명전화번호지번주소도로명주소
사업장명1.0001.0000.9970.998
전화번호1.0001.0001.0001.000
지번주소0.9971.0001.0000.997
도로명주소0.9981.0000.9971.000

Missing values

2023-12-13T03:05:45.738229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:05:45.856656image/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.
2023-12-13T03:05:45.971783image/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

사업장명전화번호지번주소도로명주소
0으뜸50안경 동묘앞역점<NA>서울특별시 종로구 숭인동 310 종로대우디오빌서울특별시 종로구 종로 344, 305호 (숭인동, 종로대우디오빌)
1경희궁마인즈아이<NA>서울특별시 종로구 내수동 72 경희궁의아침 3단지 161호서울특별시 종로구 사직로8길 34, 경희궁의아침 3단지 161호 (내수동)
2명성안경<NA>서울특별시 종로구 창신동 644서울특별시 종로구 창신길 75 (창신동)
3미소안경 보화보석<NA>서울특별시 종로구 종로5가 98번지 금원빌딩서울특별시 종로구 종로 207, 금원빌딩 2층 (종로5가)
4블링크안경 혜화점<NA>서울특별시 종로구 혜화동 122번지 4호서울특별시 종로구 창경궁로 271 (혜화동)
5뉴종로안경보청기02-743-7779서울특별시 종로구 종로4가 6번지 4호서울특별시 종로구 종로 197 (종로4가)
6샤인옵티컬1588-9947서울특별시 종로구 종로6가 289번지 57호 동대문종합시장 신관 22~24호서울특별시 종로구 종로 272, 동대문종합시장 신관 22~24호 (종로6가)
7플레인브랜드(PLAIN BRAND)<NA>서울특별시 종로구 명륜2가 38번지 3호서울특별시 종로구 대명길 26, 기영빌딩 1,2층 (명륜2가)
8종로안경콘택트02-766-1017서울특별시 종로구 종로6가 115번지 1호 1,2층서울특별시 종로구 종로 267-1 (종로6가)
9으뜸50안경원종로점<NA>서울특별시 종로구 관철동 16번지 5호서울특별시 종로구 종로 70, 5층 (관철동)
사업장명전화번호지번주소도로명주소
52뉴이태리안경02-2273-3316서울특별시 종로구 종로5가 332번지 18호 한일지하상가서울특별시 종로구 동호로 398 (종로5가, 마전교지하쇼핑센터)
53광화문로얄안경02-736-5807서울특별시 종로구 수송동 80번지 코리안리재보험빌딩서울특별시 종로구 종로5길 68 (수송동, 코리안리재보험빌딩)
54동대문로얄안경02-744-0916서울특별시 종로구 창신2동 687번지 26호서울특별시 종로구 창신길 11 (창신동)
55임마누엘안경마트02-745-0069서울특별시 종로구 창신동 303번지서울특별시 종로구 종로 335-1 (창신동, 명제빌딩)
56광열당안경.콘택트02-732-1500서울특별시 종로구 인사동 194번지 4호 하나로빌딩 지하1층서울특별시 종로구 인사동5길 25 (인사동, 하나로빌딩)
57연세안경02-735-7942서울특별시 종로구 종로2가 12 통일빌딩서울특별시 종로구 종로 77, 통일빌딩 4층 402호 (종로2가)
58보화당안경02-2279-0278서울특별시 종로구 종로5가 332번지 18호 한일지하상가 라-8,9,10호서울특별시 종로구 동호로 398, 라-8,9,10호 (종로5가, 마전교지하쇼핑센터)
59안경선생님02-743-6600서울특별시 종로구 숭인동 191번지서울특별시 종로구 종로 393-1 (숭인동)
60정보당안경원02-2273-4828서울특별시 종로구 종로5가 261번지 2호서울특별시 종로구 종로 252 (종로5가)
61독일안경콘택트02-737-1393서울특별시 종로구 통인동 119번지 1호서울특별시 종로구 자하문로 41 (통인동)