Overview

Dataset statistics

Number of variables4
Number of observations439
Missing cells63
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.8 KiB
Average record size in memory32.3 B

Variable types

Text3
DateTime1

Dataset

Description제주특별자치도 내 소재하고 있는 공중위생업소 세탁업에 관련한 데이터로 업소명, 소재지, 전화번호 등의 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15056149/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 61 (13.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 17:42:33.138020
Analysis finished2023-12-12 17:42:33.647273
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct432
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T02:42:33.830902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length4.6970387
Min length1

Characters and Unicode

Total characters2062
Distinct characters303
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

Unique425 ?
Unique (%)96.8%

Sample

1st row단성사
2nd row미미
3rd row현대
4th row서울
5th row인화사
ValueCountFrequency (%)
주식회사 4
 
0.9%
크린에이드 3
 
0.7%
태양사 2
 
0.4%
미광세탁소 2
 
0.4%
2
 
0.4%
천광사 2
 
0.4%
삼양 2
 
0.4%
백양사 2
 
0.4%
동양사 2
 
0.4%
동명세탁소 2
 
0.4%
Other values (436) 437
95.0%
2023-12-13T02:42:34.211929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
5.6%
112
 
5.4%
87
 
4.2%
68
 
3.3%
51
 
2.5%
51
 
2.5%
44
 
2.1%
40
 
1.9%
38
 
1.8%
34
 
1.6%
Other values (293) 1421
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2001
97.0%
Space Separator 21
 
1.0%
Close Punctuation 14
 
0.7%
Open Punctuation 12
 
0.6%
Decimal Number 10
 
0.5%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
116
 
5.8%
112
 
5.6%
87
 
4.3%
68
 
3.4%
51
 
2.5%
51
 
2.5%
44
 
2.2%
40
 
2.0%
38
 
1.9%
34
 
1.7%
Other values (281) 1360
68.0%
Decimal Number
ValueCountFrequency (%)
0 3
30.0%
2 2
20.0%
4 2
20.0%
7 2
20.0%
1 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
V 1
25.0%
P 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2001
97.0%
Common 57
 
2.8%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
116
 
5.8%
112
 
5.6%
87
 
4.3%
68
 
3.4%
51
 
2.5%
51
 
2.5%
44
 
2.2%
40
 
2.0%
38
 
1.9%
34
 
1.7%
Other values (281) 1360
68.0%
Common
ValueCountFrequency (%)
21
36.8%
) 14
24.6%
( 12
21.1%
0 3
 
5.3%
2 2
 
3.5%
4 2
 
3.5%
7 2
 
3.5%
1 1
 
1.8%
Latin
ValueCountFrequency (%)
M 1
25.0%
V 1
25.0%
P 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2001
97.0%
ASCII 61
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
116
 
5.8%
112
 
5.6%
87
 
4.3%
68
 
3.4%
51
 
2.5%
51
 
2.5%
44
 
2.2%
40
 
2.0%
38
 
1.9%
34
 
1.7%
Other values (281) 1360
68.0%
ASCII
ValueCountFrequency (%)
21
34.4%
) 14
23.0%
( 12
19.7%
0 3
 
4.9%
2 2
 
3.3%
4 2
 
3.3%
7 2
 
3.3%
1 1
 
1.6%
M 1
 
1.6%
V 1
 
1.6%
Other values (2) 2
 
3.3%
Distinct437
Distinct (%)100.0%
Missing2
Missing (%)0.5%
Memory size3.6 KiB
2023-12-13T02:42:34.444309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length21.20595
Min length17

Characters and Unicode

Total characters9267
Distinct characters177
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

Unique437 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 신산로7길 4
2nd row제주특별자치도 제주시 삼성로5길 11
3rd row제주특별자치도 제주시 동문로 37
4th row제주특별자치도 제주시 신산로 11
5th row제주특별자치도 제주시 고마로11길 54
ValueCountFrequency (%)
제주특별자치도 437
23.8%
제주시 327
 
17.8%
서귀포시 110
 
6.0%
애월읍 23
 
1.3%
12 14
 
0.8%
11 12
 
0.7%
대정읍 12
 
0.7%
한림읍 11
 
0.6%
4 11
 
0.6%
8 11
 
0.6%
Other values (538) 866
47.2%
2023-12-13T02:42:34.843218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1416
15.3%
774
 
8.4%
768
 
8.3%
449
 
4.8%
437
 
4.7%
437
 
4.7%
437
 
4.7%
437
 
4.7%
437
 
4.7%
325
 
3.5%
Other values (167) 3350
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6413
69.2%
Space Separator 1416
 
15.3%
Decimal Number 1346
 
14.5%
Dash Punctuation 92
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
774
12.1%
768
12.0%
449
 
7.0%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
325
 
5.1%
267
 
4.2%
Other values (155) 1645
25.7%
Decimal Number
ValueCountFrequency (%)
1 322
23.9%
2 219
16.3%
3 155
11.5%
4 119
 
8.8%
5 103
 
7.7%
6 95
 
7.1%
8 91
 
6.8%
7 88
 
6.5%
9 78
 
5.8%
0 76
 
5.6%
Space Separator
ValueCountFrequency (%)
1416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6413
69.2%
Common 2854
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
774
12.1%
768
12.0%
449
 
7.0%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
325
 
5.1%
267
 
4.2%
Other values (155) 1645
25.7%
Common
ValueCountFrequency (%)
1416
49.6%
1 322
 
11.3%
2 219
 
7.7%
3 155
 
5.4%
4 119
 
4.2%
5 103
 
3.6%
6 95
 
3.3%
- 92
 
3.2%
8 91
 
3.2%
7 88
 
3.1%
Other values (2) 154
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6413
69.2%
ASCII 2854
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1416
49.6%
1 322
 
11.3%
2 219
 
7.7%
3 155
 
5.4%
4 119
 
4.2%
5 103
 
3.6%
6 95
 
3.3%
- 92
 
3.2%
8 91
 
3.2%
7 88
 
3.1%
Other values (2) 154
 
5.4%
Hangul
ValueCountFrequency (%)
774
12.1%
768
12.0%
449
 
7.0%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
437
 
6.8%
325
 
5.1%
267
 
4.2%
Other values (155) 1645
25.7%

전화번호
Text

MISSING 

Distinct377
Distinct (%)99.7%
Missing61
Missing (%)13.9%
Memory size3.6 KiB
2023-12-13T02:42:35.063058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters4536
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

Unique376 ?
Unique (%)99.5%

Sample

1st row064-752-5892
2nd row064-724-6582
3rd row064-756-7863
4th row064-752-5364
5th row064-752-6483
ValueCountFrequency (%)
064-722-2957 2
 
0.5%
064-726-4010 1
 
0.3%
064-751-0095 1
 
0.3%
064-742-0082 1
 
0.3%
064-724-7011 1
 
0.3%
064-742-0313 1
 
0.3%
064-747-2535 1
 
0.3%
064-712-3527 1
 
0.3%
064-758-3911 1
 
0.3%
064-702-8284 1
 
0.3%
Other values (367) 367
97.1%
2023-12-13T02:42:35.435494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 756
16.7%
4 628
13.8%
0 574
12.7%
7 573
12.6%
6 566
12.5%
2 310
6.8%
3 279
 
6.2%
5 258
 
5.7%
1 226
 
5.0%
8 215
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3780
83.3%
Dash Punctuation 756
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 628
16.6%
0 574
15.2%
7 573
15.2%
6 566
15.0%
2 310
8.2%
3 279
7.4%
5 258
6.8%
1 226
 
6.0%
8 215
 
5.7%
9 151
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4536
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 756
16.7%
4 628
13.8%
0 574
12.7%
7 573
12.6%
6 566
12.5%
2 310
6.8%
3 279
 
6.2%
5 258
 
5.7%
1 226
 
5.0%
8 215
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4536
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 756
16.7%
4 628
13.8%
0 574
12.7%
7 573
12.6%
6 566
12.5%
2 310
6.8%
3 279
 
6.2%
5 258
 
5.7%
1 226
 
5.0%
8 215
 
4.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T02:42:35.574803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:35.664656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-13T02:42:33.448782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:42:33.525451image/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.
2023-12-13T02:42:33.602109image/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

업소명소재지전화번호데이터기준일자
0단성사제주특별자치도 제주시 신산로7길 4064-752-58922022-12-31
1미미제주특별자치도 제주시 삼성로5길 11064-724-65822022-12-31
2현대제주특별자치도 제주시 동문로 37064-756-78632022-12-31
3서울제주특별자치도 제주시 신산로 11064-752-53642022-12-31
4인화사제주특별자치도 제주시 고마로11길 54064-752-64832022-12-31
5보라세탁전문점제주특별자치도 제주시 만덕로3길 19064-755-89102022-12-31
6제남기계제주특별자치도 제주시 동문로 71064-757-64032022-12-31
7신영사제주특별자치도 제주시 동광로1길 28-1064-753-48702022-12-31
8하나사제주특별자치도 제주시 서사로19길 2064-753-01242022-12-31
9경신제주특별자치도 제주시 일주서로 7768064-742-70822022-12-31
업소명소재지전화번호데이터기준일자
429제광산업제주특별자치도 서귀포시 토평공단로155번길 35064-733-99512022-12-31
4304470세탁소제주특별자치도 서귀포시 중산간동로 8043064-732-44702022-12-31
431호경세탁소제주특별자치도 서귀포시 표선면 중산간동로 5270<NA>2022-12-31
432코인워시셀프빨래방남원점제주특별자치도 서귀포시 남원읍 남원체육관로 342<NA>2022-12-31
433태산둘리세탁소제주특별자치도 서귀포시 대청로 11<NA>2022-12-31
434체인지빨래방제주특별자치도 서귀포시 일주동로 8729<NA>2022-12-31
435정성산업제주특별자치도 서귀포시 성산읍 중산간동로 3235064-782-00522022-12-31
436크린에이드 중문지사제주특별자치도 서귀포시 중문관광로301번길 3064-748-66122022-12-31
437영어마을세탁소제주특별자치도 서귀포시 대정읍 글로벌에듀로 370064-792-19622022-12-31
438더런드리 서귀포 표선점제주특별자치도 서귀포시 표선면 표선동서로 230<NA>2022-12-31