Overview

Dataset statistics

Number of variables4
Number of observations43
Missing cells3
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory35.1 B

Variable types

Text3
DateTime1

Dataset

Description인천광역시 중구 소재 세탁업에 관한 정보입니다.파일명 인천광역시 중구 세탁업소현황내용 업소명, 소재지, 소재지전화번호 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038685&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
소재지전화 has 3 (7.0%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-01-28 07:06:24.160913
Analysis finished2024-01-28 07:06:24.495500
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-01-28T16:06:24.626824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length5.744186
Min length3

Characters and Unicode

Total characters247
Distinct characters91
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)95.3%

Sample

1st row현대세탁
2nd row미화세탁소
3rd row인해세탁소
4th row경미사 세탁소
5th row일경명품세탁
ValueCountFrequency (%)
세탁소 3
 
5.6%
현대세탁 2
 
3.7%
그린세탁 1
 
1.9%
크린랜드 1
 
1.9%
중앙사 1
 
1.9%
베스트웨스턴 1
 
1.9%
프리미어 1
 
1.9%
인천공항호텔 1
 
1.9%
엄마손 1
 
1.9%
운동화 1
 
1.9%
Other values (41) 41
75.9%
2024-01-28T16:06:24.924159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 30
 
12.1%
탁 30
 
12.1%
11
 
4.5%
소 10
 
4.0%
크 7
 
2.8%
린 6
 
2.4%
리 5
 
2.0%
미 5
 
2.0%
대 5
 
2.0%
사 4
 
1.6%
Other values (81) 134
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 230
93.1%
Space Separator 11
 
4.5%
Open Punctuation 2
 
0.8%
Close Punctuation 2
 
0.8%
Letter Number 1
 
0.4%
Uppercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 30
 
13.0%
탁 30
 
13.0%
소 10
 
4.3%
크 7
 
3.0%
린 6
 
2.6%
리 5
 
2.2%
미 5
 
2.2%
대 5
 
2.2%
사 4
 
1.7%
천 4
 
1.7%
Other values (76) 124
53.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 230
93.1%
Common 15
 
6.1%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 30
 
13.0%
탁 30
 
13.0%
소 10
 
4.3%
크 7
 
3.0%
린 6
 
2.6%
리 5
 
2.2%
미 5
 
2.2%
대 5
 
2.2%
사 4
 
1.7%
천 4
 
1.7%
Other values (76) 124
53.9%
Common
ValueCountFrequency (%)
11
73.3%
( 2
 
13.3%
) 2
 
13.3%
Latin
ValueCountFrequency (%)
Ⅱ 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 230
93.1%
ASCII 16
 
6.5%
Number Forms 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 30
 
13.0%
탁 30
 
13.0%
소 10
 
4.3%
크 7
 
3.0%
린 6
 
2.6%
리 5
 
2.2%
미 5
 
2.2%
대 5
 
2.2%
사 4
 
1.7%
천 4
 
1.7%
Other values (76) 124
53.9%
ASCII
ValueCountFrequency (%)
11
68.8%
( 2
 
12.5%
) 2
 
12.5%
D 1
 
6.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-01-28T16:06:25.128610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length38
Mean length32.767442
Min length21

Characters and Unicode

Total characters1409
Distinct characters132
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

Unique43 ?
Unique (%)100.0%

Sample

1st row인천광역시 중구 차이나타운로 53-2 (선린동)
2nd row인천광역시 중구 도원로 55 (도원동)
3rd row인천광역시 중구 연안부두로33번길 36, 2층 (항동7가)
4th row인천광역시 중구 우현로72번길 32, 1층 (용동)
5th row인천광역시 중구 연안부두로33번길 36 (항동7가)
ValueCountFrequency (%)
인천광역시 43
 
15.8%
중구 43
 
15.8%
1층 14
 
5.1%
운서동 10
 
3.7%
중산동 5
 
1.8%
34 4
 
1.5%
102호 4
 
1.5%
공항로424번길 3
 
1.1%
신흥동1가 3
 
1.1%
도원동 3
 
1.1%
Other values (121) 140
51.5%
2024-01-28T16:06:25.427701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
 
16.3%
1 61
 
4.3%
동 53
 
3.8%
중 52
 
3.7%
인 47
 
3.3%
시 47
 
3.3%
, 44
 
3.1%
역 43
 
3.1%
구 43
 
3.1%
천 43
 
3.1%
Other values (122) 747
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 801
56.8%
Decimal Number 238
 
16.9%
Space Separator 229
 
16.3%
Other Punctuation 44
 
3.1%
Close Punctuation 43
 
3.1%
Open Punctuation 43
 
3.1%
Dash Punctuation 7
 
0.5%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
6.6%
중 52
 
6.5%
인 47
 
5.9%
시 47
 
5.9%
역 43
 
5.4%
구 43
 
5.4%
천 43
 
5.4%
광 43
 
5.4%
로 41
 
5.1%
길 21
 
2.6%
Other values (103) 368
45.9%
Decimal Number
ValueCountFrequency (%)
1 61
25.6%
2 39
16.4%
4 27
11.3%
3 26
10.9%
0 19
 
8.0%
6 18
 
7.6%
5 16
 
6.7%
8 14
 
5.9%
7 9
 
3.8%
9 9
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
B 1
25.0%
I 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
229
100.0%
Other Punctuation
ValueCountFrequency (%)
, 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 801
56.8%
Common 604
42.9%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
6.6%
중 52
 
6.5%
인 47
 
5.9%
시 47
 
5.9%
역 43
 
5.4%
구 43
 
5.4%
천 43
 
5.4%
광 43
 
5.4%
로 41
 
5.1%
길 21
 
2.6%
Other values (103) 368
45.9%
Common
ValueCountFrequency (%)
229
37.9%
1 61
 
10.1%
, 44
 
7.3%
) 43
 
7.1%
( 43
 
7.1%
2 39
 
6.5%
4 27
 
4.5%
3 26
 
4.3%
0 19
 
3.1%
6 18
 
3.0%
Other values (5) 55
 
9.1%
Latin
ValueCountFrequency (%)
C 1
25.0%
B 1
25.0%
I 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 801
56.8%
ASCII 608
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
37.7%
1 61
 
10.0%
, 44
 
7.2%
) 43
 
7.1%
( 43
 
7.1%
2 39
 
6.4%
4 27
 
4.4%
3 26
 
4.3%
0 19
 
3.1%
6 18
 
3.0%
Other values (9) 59
 
9.7%
Hangul
ValueCountFrequency (%)
동 53
 
6.6%
중 52
 
6.5%
인 47
 
5.9%
시 47
 
5.9%
역 43
 
5.4%
구 43
 
5.4%
천 43
 
5.4%
광 43
 
5.4%
로 41
 
5.1%
길 21
 
2.6%
Other values (103) 368
45.9%

소재지전화
Text

MISSING 

Distinct40
Distinct (%)100.0%
Missing3
Missing (%)7.0%
Memory size476.0 B
2024-01-28T16:06:25.635194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters480
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

Unique40 ?
Unique (%)100.0%

Sample

1st row032-772-5821
2nd row032-884-1416
3rd row032-882-4366
4th row032-772-7401
5th row032-887-4627
ValueCountFrequency (%)
032-762-4410 1
 
2.5%
032-884-0762 1
 
2.5%
032-746-9978 1
 
2.5%
032-762-2727 1
 
2.5%
032-752-3484 1
 
2.5%
032-761-1992 1
 
2.5%
032-743-1000 1
 
2.5%
032-766-4500 1
 
2.5%
032-752-9991 1
 
2.5%
032-746-0083 1
 
2.5%
Other values (30) 30
75.0%
2024-01-28T16:06:25.994339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 80
16.7%
2 72
15.0%
0 64
13.3%
3 58
12.1%
7 50
10.4%
6 31
 
6.5%
4 28
 
5.8%
1 28
 
5.8%
8 27
 
5.6%
5 21
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
83.3%
Dash Punctuation 80
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 72
18.0%
0 64
16.0%
3 58
14.5%
7 50
12.5%
6 31
7.8%
4 28
 
7.0%
1 28
 
7.0%
8 27
 
6.8%
5 21
 
5.2%
9 21
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 80
16.7%
2 72
15.0%
0 64
13.3%
3 58
12.1%
7 50
10.4%
6 31
 
6.5%
4 28
 
5.8%
1 28
 
5.8%
8 27
 
5.6%
5 21
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 80
16.7%
2 72
15.0%
0 64
13.3%
3 58
12.1%
7 50
10.4%
6 31
 
6.5%
4 28
 
5.8%
1 28
 
5.8%
8 27
 
5.6%
5 21
 
4.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2023-07-05 00:00:00
Maximum2023-07-05 00:00:00
2024-01-28T16:06:26.127970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:06:26.218632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-01-28T16:06:26.287501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화
업소명1.0001.0001.000
영업소 주소(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2024-01-28T16:06:24.395928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:06:24.468351image/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

업소명영업소 주소(도로명)소재지전화데이터기준일자
0현대세탁인천광역시 중구 차이나타운로 53-2 (선린동)032-772-58212023-07-05
1미화세탁소인천광역시 중구 도원로 55 (도원동)032-884-14162023-07-05
2인해세탁소인천광역시 중구 연안부두로33번길 36, 2층 (항동7가)032-882-43662023-07-05
3경미사 세탁소인천광역시 중구 우현로72번길 32, 1층 (용동)032-772-74012023-07-05
4일경명품세탁인천광역시 중구 연안부두로33번길 36 (항동7가)032-887-46272023-07-05
5문성세탁인천광역시 중구 도원서길 12 (선화동)032-883-62202023-07-05
6장미사인천광역시 중구 제물량로206번길 35-1 (관동1가)032-763-43522023-07-05
7도원빨리셀프크리닝인천광역시 중구 도원로26번길 21 (도원동)032-887-25902023-07-05
8삼보세탁인천광역시 중구 도원서길 49, 114동 102호 (신흥동2가, 삼정베스트빌아파트)032-887-11792023-07-05
9풍림세탁인천광역시 중구 인중로 109 (신흥동1가)032-884-07622023-07-05
업소명영업소 주소(도로명)소재지전화데이터기준일자
33그린세탁인천광역시 중구 영종대로 84, 1층 112호 (운서동)032-747-00412023-07-05
34세탁이야기인천광역시 중구 운중로 44, 1층 (운남동)032-746-84822023-07-05
35백곰세탁인천광역시 중구 제물량로 128-1 (답동, 1층)032-766-73632023-07-05
36비발디 세탁소인천광역시 중구 하늘별빛로 86, 단지내상가동 204호 (중산동)032-751-99092023-07-05
37천일세탁인천광역시 중구 넙디로 34, 1층 (운서동)032-746-10012023-07-05
38전우사인천광역시 중구 축항대로2번길 28 (북성동1가, 인방사)<NA>2023-07-05
39(주)대원크리닝 인천지점인천광역시 중구 영종해안남로321번길 186, 지하1층 (운서동, 파라다이스시티)032-729-27502023-07-05
40해피 빨래방인천광역시 중구 홍예문로68번길 27, 1층 (전동)032-766-19852023-07-05
41베스트 크린인천광역시 중구 공항로424번길 50, IBC 월드게이트 지하 1층 136호 (운서동)032-743-85252023-07-05
42영종 세탁인천광역시 중구 운중로 25 (운남동)032-746-88812023-07-05