Overview

Dataset statistics

Number of variables47
Number of observations470
Missing cells4120
Missing cells (%)18.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory185.6 KiB
Average record size in memory404.3 B

Variable types

Categorical23
Text7
DateTime4
Unsupported7
Numeric4
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-17961/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (72.6%)Imbalance
위생업태명 is highly imbalanced (66.2%)Imbalance
여성종사자수 is highly imbalanced (53.1%)Imbalance
남성종사자수 is highly imbalanced (53.1%)Imbalance
회수건조수 is highly imbalanced (54.2%)Imbalance
인허가취소일자 has 470 (100.0%) missing valuesMissing
폐업일자 has 111 (23.6%) missing valuesMissing
휴업시작일자 has 470 (100.0%) missing valuesMissing
휴업종료일자 has 470 (100.0%) missing valuesMissing
재개업일자 has 470 (100.0%) missing valuesMissing
전화번호 has 40 (8.5%) missing valuesMissing
도로명주소 has 220 (46.8%) missing valuesMissing
도로명우편번호 has 223 (47.4%) missing valuesMissing
좌표정보(X) has 11 (2.3%) missing valuesMissing
좌표정보(Y) has 11 (2.3%) missing valuesMissing
건물지상층수 has 160 (34.0%) missing valuesMissing
발한실여부 has 33 (7.0%) missing valuesMissing
조건부허가신고사유 has 470 (100.0%) missing valuesMissing
조건부허가시작일자 has 470 (100.0%) missing valuesMissing
조건부허가종료일자 has 470 (100.0%) missing valuesMissing
다중이용업소여부 has 21 (4.5%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 159 (33.8%) zerosZeros

Reproduction

Analysis started2024-05-11 08:03:14.044044
Analysis finished2024-05-11 08:03:14.871749
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3090000
470 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 470
100.0%

Length

2024-05-11T17:03:14.945412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:15.065008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 470
100.0%

관리번호
Text

UNIQUE 

Distinct470
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T17:03:15.289912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10340
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

Unique470 ?
Unique (%)100.0%

Sample

1st row3090000-205-1987-01195
2nd row3090000-205-1987-01198
3rd row3090000-205-1987-01199
4th row3090000-205-1987-01202
5th row3090000-205-1987-01204
ValueCountFrequency (%)
3090000-205-1987-01195 1
 
0.2%
3090000-205-2003-00027 1
 
0.2%
3090000-205-2004-00003 1
 
0.2%
3090000-205-2004-00002 1
 
0.2%
3090000-205-2004-00001 1
 
0.2%
3090000-205-2003-00036 1
 
0.2%
3090000-205-2003-00035 1
 
0.2%
3090000-205-2003-00034 1
 
0.2%
3090000-205-2003-00033 1
 
0.2%
3090000-205-2003-00032 1
 
0.2%
Other values (460) 460
97.9%
2024-05-11T17:03:15.674866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4268
41.3%
- 1410
 
13.6%
9 1022
 
9.9%
2 928
 
9.0%
1 754
 
7.3%
3 731
 
7.1%
5 618
 
6.0%
4 190
 
1.8%
8 162
 
1.6%
7 154
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8930
86.4%
Dash Punctuation 1410
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4268
47.8%
9 1022
 
11.4%
2 928
 
10.4%
1 754
 
8.4%
3 731
 
8.2%
5 618
 
6.9%
4 190
 
2.1%
8 162
 
1.8%
7 154
 
1.7%
6 103
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1410
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4268
41.3%
- 1410
 
13.6%
9 1022
 
9.9%
2 928
 
9.0%
1 754
 
7.3%
3 731
 
7.1%
5 618
 
6.0%
4 190
 
1.8%
8 162
 
1.6%
7 154
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4268
41.3%
- 1410
 
13.6%
9 1022
 
9.9%
2 928
 
9.0%
1 754
 
7.3%
3 731
 
7.1%
5 618
 
6.0%
4 190
 
1.8%
8 162
 
1.6%
7 154
 
1.5%
Distinct395
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1987-06-05 00:00:00
Maximum2022-05-20 00:00:00
2024-05-11T17:03:15.868011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:16.039927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
359 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 359
76.4%
1 111
 
23.6%

Length

2024-05-11T17:03:16.205072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:16.315218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 359
76.4%
1 111
 
23.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
359 
영업/정상
111 

Length

Max length5
Median length2
Mean length2.7085106
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업/정상
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 359
76.4%
영업/정상 111
 
23.6%

Length

2024-05-11T17:03:16.428026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:16.540884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 359
76.4%
영업/정상 111
 
23.6%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
359 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 359
76.4%
1 111
 
23.6%

Length

2024-05-11T17:03:16.637434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:16.742471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 359
76.4%
1 111
 
23.6%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
359 
영업
111 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 359
76.4%
영업 111
 
23.6%

Length

2024-05-11T17:03:16.844613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:16.938305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 359
76.4%
영업 111
 
23.6%

폐업일자
Date

MISSING 

Distinct308
Distinct (%)85.8%
Missing111
Missing (%)23.6%
Memory size3.8 KiB
Minimum1993-02-15 00:00:00
Maximum2023-10-25 00:00:00
2024-05-11T17:03:17.051496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:17.194943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

전화번호
Text

MISSING 

Distinct400
Distinct (%)93.0%
Missing40
Missing (%)8.5%
Memory size3.8 KiB
2024-05-11T17:03:17.452363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6488372
Min length2

Characters and Unicode

Total characters4149
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)88.6%

Sample

1st row02 9542280
2nd row0200000000
3rd row0209541590
4th row9064271
5th row0209945468
ValueCountFrequency (%)
02 187
28.2%
0200000000 9
 
1.4%
956 5
 
0.8%
990 4
 
0.6%
955 4
 
0.6%
9965728 4
 
0.6%
902 3
 
0.5%
9542800 3
 
0.5%
02954 3
 
0.5%
9552578 3
 
0.5%
Other values (400) 438
66.1%
2024-05-11T17:03:17.869413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 854
20.6%
9 722
17.4%
2 622
15.0%
4 295
 
7.1%
5 289
 
7.0%
3 287
 
6.9%
278
 
6.7%
6 225
 
5.4%
7 206
 
5.0%
8 195
 
4.7%
Other values (2) 176
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3870
93.3%
Space Separator 278
 
6.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 854
22.1%
9 722
18.7%
2 622
16.1%
4 295
 
7.6%
5 289
 
7.5%
3 287
 
7.4%
6 225
 
5.8%
7 206
 
5.3%
8 195
 
5.0%
1 175
 
4.5%
Space Separator
ValueCountFrequency (%)
278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 854
20.6%
9 722
17.4%
2 622
15.0%
4 295
 
7.1%
5 289
 
7.0%
3 287
 
6.9%
278
 
6.7%
6 225
 
5.4%
7 206
 
5.0%
8 195
 
4.7%
Other values (2) 176
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 854
20.6%
9 722
17.4%
2 622
15.0%
4 295
 
7.1%
5 289
 
7.0%
3 287
 
6.9%
278
 
6.7%
6 225
 
5.4%
7 206
 
5.0%
8 195
 
4.7%
Other values (2) 176
 
4.2%
Distinct264
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T17:03:18.226767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8638298
Min length3

Characters and Unicode

Total characters2286
Distinct characters12
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

Unique209 ?
Unique (%)44.5%

Sample

1st row16.50
2nd row14.66
3rd row10.56
4th row19.49
5th row17.80
ValueCountFrequency (%)
00 44
 
9.4%
33.00 23
 
4.9%
26.40 20
 
4.3%
23.10 14
 
3.0%
30.00 12
 
2.6%
24.00 9
 
1.9%
19.80 8
 
1.7%
36.00 6
 
1.3%
18.00 6
 
1.3%
28.00 6
 
1.3%
Other values (254) 322
68.5%
2024-05-11T17:03:18.714463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 542
23.7%
. 470
20.6%
2 249
10.9%
1 196
 
8.6%
3 185
 
8.1%
6 128
 
5.6%
4 125
 
5.5%
8 109
 
4.8%
9 98
 
4.3%
5 98
 
4.3%
Other values (2) 86
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1815
79.4%
Other Punctuation 471
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 542
29.9%
2 249
13.7%
1 196
 
10.8%
3 185
 
10.2%
6 128
 
7.1%
4 125
 
6.9%
8 109
 
6.0%
9 98
 
5.4%
5 98
 
5.4%
7 85
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 470
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 542
23.7%
. 470
20.6%
2 249
10.9%
1 196
 
8.6%
3 185
 
8.1%
6 128
 
5.6%
4 125
 
5.5%
8 109
 
4.8%
9 98
 
4.3%
5 98
 
4.3%
Other values (2) 86
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 542
23.7%
. 470
20.6%
2 249
10.9%
1 196
 
8.6%
3 185
 
8.1%
6 128
 
5.6%
4 125
 
5.5%
8 109
 
4.8%
9 98
 
4.3%
5 98
 
4.3%
Other values (2) 86
 
3.8%
Distinct121
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T17:03:19.058611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0212766
Min length6

Characters and Unicode

Total characters2830
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

Unique38 ?
Unique (%)8.1%

Sample

1st row132819
2nd row132816
3rd row132814
4th row132875
5th row132815
ValueCountFrequency (%)
132040 24
 
5.1%
132916 12
 
2.6%
132854 12
 
2.6%
132850 12
 
2.6%
132924 10
 
2.1%
132821 10
 
2.1%
132858 10
 
2.1%
132918 9
 
1.9%
132844 9
 
1.9%
132861 9
 
1.9%
Other values (111) 353
75.1%
2024-05-11T17:03:19.613742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 597
21.1%
2 591
20.9%
3 527
18.6%
8 392
13.9%
9 172
 
6.1%
0 153
 
5.4%
4 122
 
4.3%
5 100
 
3.5%
6 98
 
3.5%
7 68
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2820
99.6%
Dash Punctuation 10
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 597
21.2%
2 591
21.0%
3 527
18.7%
8 392
13.9%
9 172
 
6.1%
0 153
 
5.4%
4 122
 
4.3%
5 100
 
3.5%
6 98
 
3.5%
7 68
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2830
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 597
21.1%
2 591
20.9%
3 527
18.6%
8 392
13.9%
9 172
 
6.1%
0 153
 
5.4%
4 122
 
4.3%
5 100
 
3.5%
6 98
 
3.5%
7 68
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 597
21.1%
2 591
20.9%
3 527
18.6%
8 392
13.9%
9 172
 
6.1%
0 153
 
5.4%
4 122
 
4.3%
5 100
 
3.5%
6 98
 
3.5%
7 68
 
2.4%
Distinct444
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T17:03:19.950706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length26.185106
Min length18

Characters and Unicode

Total characters12307
Distinct characters141
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

Unique422 ?
Unique (%)89.8%

Sample

1st row서울특별시 도봉구 도봉동 600-3번지
2nd row서울특별시 도봉구 도봉동 589-7번지
3rd row서울특별시 도봉구 도봉동 566-5번지
4th row서울특별시 도봉구 쌍문동 286-68번지 (28/5)
5th row서울특별시 도봉구 도봉동 574-34번지
ValueCountFrequency (%)
서울특별시 470
20.5%
도봉구 470
20.5%
창동 138
 
6.0%
방학동 131
 
5.7%
쌍문동 126
 
5.5%
도봉동 75
 
3.3%
지상1층 33
 
1.4%
상가동 31
 
1.4%
1층 17
 
0.7%
103호 10
 
0.4%
Other values (618) 791
34.5%
2024-05-11T17:03:20.482286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2214
 
18.0%
565
 
4.6%
549
 
4.5%
548
 
4.5%
1 479
 
3.9%
479
 
3.9%
474
 
3.9%
473
 
3.8%
471
 
3.8%
470
 
3.8%
Other values (131) 5585
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7070
57.4%
Decimal Number 2534
 
20.6%
Space Separator 2214
 
18.0%
Dash Punctuation 402
 
3.3%
Uppercase Letter 50
 
0.4%
Other Punctuation 22
 
0.2%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
565
 
8.0%
549
 
7.8%
548
 
7.8%
479
 
6.8%
474
 
6.7%
473
 
6.7%
471
 
6.7%
470
 
6.6%
470
 
6.6%
464
 
6.6%
Other values (101) 2107
29.8%
Decimal Number
ValueCountFrequency (%)
1 479
18.9%
2 325
12.8%
6 307
12.1%
0 305
12.0%
3 253
10.0%
5 237
9.4%
7 180
 
7.1%
4 177
 
7.0%
8 170
 
6.7%
9 101
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 21
42.0%
P 9
18.0%
T 8
 
16.0%
B 5
 
10.0%
S 2
 
4.0%
R 2
 
4.0%
I 1
 
2.0%
K 1
 
2.0%
E 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
@ 16
72.7%
, 2
 
9.1%
/ 2
 
9.1%
. 2
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
s 1
33.3%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
2214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 402
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7070
57.4%
Common 5184
42.1%
Latin 53
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
565
 
8.0%
549
 
7.8%
548
 
7.8%
479
 
6.8%
474
 
6.7%
473
 
6.7%
471
 
6.7%
470
 
6.6%
470
 
6.6%
464
 
6.6%
Other values (101) 2107
29.8%
Common
ValueCountFrequency (%)
2214
42.7%
1 479
 
9.2%
- 402
 
7.8%
2 325
 
6.3%
6 307
 
5.9%
0 305
 
5.9%
3 253
 
4.9%
5 237
 
4.6%
7 180
 
3.5%
4 177
 
3.4%
Other values (8) 305
 
5.9%
Latin
ValueCountFrequency (%)
A 21
39.6%
P 9
17.0%
T 8
 
15.1%
B 5
 
9.4%
S 2
 
3.8%
R 2
 
3.8%
I 1
 
1.9%
K 1
 
1.9%
E 1
 
1.9%
e 1
 
1.9%
Other values (2) 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7070
57.4%
ASCII 5237
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2214
42.3%
1 479
 
9.1%
- 402
 
7.7%
2 325
 
6.2%
6 307
 
5.9%
0 305
 
5.8%
3 253
 
4.8%
5 237
 
4.5%
7 180
 
3.4%
4 177
 
3.4%
Other values (20) 358
 
6.8%
Hangul
ValueCountFrequency (%)
565
 
8.0%
549
 
7.8%
548
 
7.8%
479
 
6.8%
474
 
6.7%
473
 
6.7%
471
 
6.7%
470
 
6.6%
470
 
6.6%
464
 
6.6%
Other values (101) 2107
29.8%

도로명주소
Text

MISSING 

Distinct249
Distinct (%)99.6%
Missing220
Missing (%)46.8%
Memory size3.8 KiB
2024-05-11T17:03:20.877943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length32.648
Min length22

Characters and Unicode

Total characters8162
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

Unique248 ?
Unique (%)99.2%

Sample

1st row서울특별시 도봉구 도봉로165길 9 (도봉동)
2nd row서울특별시 도봉구 도봉로181길 25 (도봉동)
3rd row서울특별시 도봉구 우이천로36길 8 (쌍문동,(28/5))
4th row서울특별시 도봉구 도봉로154가길 26 (도봉동)
5th row서울특별시 도봉구 우이천로48길 4 (쌍문동)
ValueCountFrequency (%)
서울특별시 250
 
16.1%
도봉구 250
 
16.1%
창동 66
 
4.2%
쌍문동 59
 
3.8%
방학동 58
 
3.7%
지상1층 41
 
2.6%
상가동 38
 
2.4%
도봉동 32
 
2.1%
1층 21
 
1.3%
해등로 20
 
1.3%
Other values (413) 721
46.3%
2024-05-11T17:03:21.410283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1306
 
16.0%
1 380
 
4.7%
379
 
4.6%
370
 
4.5%
332
 
4.1%
268
 
3.3%
255
 
3.1%
) 254
 
3.1%
( 254
 
3.1%
253
 
3.1%
Other values (138) 4111
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4686
57.4%
Decimal Number 1394
 
17.1%
Space Separator 1306
 
16.0%
Close Punctuation 254
 
3.1%
Open Punctuation 254
 
3.1%
Other Punctuation 212
 
2.6%
Dash Punctuation 29
 
0.4%
Uppercase Letter 24
 
0.3%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
379
 
8.1%
370
 
7.9%
332
 
7.1%
268
 
5.7%
255
 
5.4%
253
 
5.4%
251
 
5.4%
250
 
5.3%
250
 
5.3%
250
 
5.3%
Other values (108) 1828
39.0%
Decimal Number
ValueCountFrequency (%)
1 380
27.3%
2 195
14.0%
0 154
11.0%
3 129
 
9.3%
6 114
 
8.2%
4 110
 
7.9%
5 105
 
7.5%
9 78
 
5.6%
8 67
 
4.8%
7 62
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 8
33.3%
B 4
16.7%
P 3
 
12.5%
T 2
 
8.3%
R 2
 
8.3%
S 2
 
8.3%
I 1
 
4.2%
K 1
 
4.2%
E 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 202
95.3%
@ 7
 
3.3%
/ 2
 
0.9%
. 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
s 1
33.3%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
1306
100.0%
Close Punctuation
ValueCountFrequency (%)
) 254
100.0%
Open Punctuation
ValueCountFrequency (%)
( 254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4686
57.4%
Common 3449
42.3%
Latin 27
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
379
 
8.1%
370
 
7.9%
332
 
7.1%
268
 
5.7%
255
 
5.4%
253
 
5.4%
251
 
5.4%
250
 
5.3%
250
 
5.3%
250
 
5.3%
Other values (108) 1828
39.0%
Common
ValueCountFrequency (%)
1306
37.9%
1 380
 
11.0%
) 254
 
7.4%
( 254
 
7.4%
, 202
 
5.9%
2 195
 
5.7%
0 154
 
4.5%
3 129
 
3.7%
6 114
 
3.3%
4 110
 
3.2%
Other values (8) 351
 
10.2%
Latin
ValueCountFrequency (%)
A 8
29.6%
B 4
14.8%
P 3
 
11.1%
T 2
 
7.4%
R 2
 
7.4%
S 2
 
7.4%
I 1
 
3.7%
K 1
 
3.7%
E 1
 
3.7%
e 1
 
3.7%
Other values (2) 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4686
57.4%
ASCII 3476
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1306
37.6%
1 380
 
10.9%
) 254
 
7.3%
( 254
 
7.3%
, 202
 
5.8%
2 195
 
5.6%
0 154
 
4.4%
3 129
 
3.7%
6 114
 
3.3%
4 110
 
3.2%
Other values (20) 378
 
10.9%
Hangul
ValueCountFrequency (%)
379
 
8.1%
370
 
7.9%
332
 
7.1%
268
 
5.7%
255
 
5.4%
253
 
5.4%
251
 
5.4%
250
 
5.3%
250
 
5.3%
250
 
5.3%
Other values (108) 1828
39.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)51.4%
Missing223
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean1394.3927
Minimum1302
Maximum1489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T17:03:21.577178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1302
5-th percentile1306.3
Q11350
median1392
Q31447
95-th percentile1478
Maximum1489
Range187
Interquartile range (IQR)97

Descriptive statistics

Standard deviation55.840616
Coefficient of variation (CV)0.040046549
Kurtosis-1.2352435
Mean1394.3927
Median Absolute Deviation (MAD)50
Skewness0.006962218
Sum344415
Variance3118.1744
MonotonicityNot monotonic
2024-05-11T17:03:21.789717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1314 6
 
1.3%
1306 6
 
1.3%
1462 4
 
0.9%
1417 4
 
0.9%
1392 4
 
0.9%
1357 4
 
0.9%
1363 4
 
0.9%
1478 3
 
0.6%
1332 3
 
0.6%
1308 3
 
0.6%
Other values (117) 206
43.8%
(Missing) 223
47.4%
ValueCountFrequency (%)
1302 1
 
0.2%
1303 1
 
0.2%
1304 2
 
0.4%
1305 3
0.6%
1306 6
1.3%
1307 2
 
0.4%
1308 3
0.6%
1310 1
 
0.2%
1314 6
1.3%
1315 1
 
0.2%
ValueCountFrequency (%)
1489 2
0.4%
1488 2
0.4%
1487 3
0.6%
1484 2
0.4%
1481 3
0.6%
1478 3
0.6%
1475 2
0.4%
1474 2
0.4%
1473 2
0.4%
1472 1
 
0.2%
Distinct354
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T17:03:22.132889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length4.7765957
Min length2

Characters and Unicode

Total characters2245
Distinct characters255
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

Unique287 ?
Unique (%)61.1%

Sample

1st row백설사
2nd row동궁사
3rd row미미사
4th row영광세탁소
5th row백광사
ValueCountFrequency (%)
백양사 9
 
1.8%
현대세탁 8
 
1.6%
한양세탁소 6
 
1.2%
삼익세탁소 6
 
1.2%
세탁소 6
 
1.2%
대성사 5
 
1.0%
백양 5
 
1.0%
빨래방 5
 
1.0%
세탁 4
 
0.8%
크린토피아 4
 
0.8%
Other values (359) 454
88.7%
2024-05-11T17:03:22.676157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
 
10.0%
224
 
10.0%
142
 
6.3%
141
 
6.3%
59
 
2.6%
52
 
2.3%
49
 
2.2%
45
 
2.0%
42
 
1.9%
41
 
1.8%
Other values (245) 1225
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2162
96.3%
Space Separator 42
 
1.9%
Lowercase Letter 11
 
0.5%
Decimal Number 10
 
0.4%
Uppercase Letter 7
 
0.3%
Open Punctuation 5
 
0.2%
Close Punctuation 5
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
225
 
10.4%
224
 
10.4%
142
 
6.6%
141
 
6.5%
59
 
2.7%
52
 
2.4%
49
 
2.3%
45
 
2.1%
41
 
1.9%
39
 
1.8%
Other values (225) 1145
53.0%
Lowercase Letter
ValueCountFrequency (%)
o 3
27.3%
r 2
18.2%
m 1
 
9.1%
s 1
 
9.1%
i 1
 
9.1%
d 1
 
9.1%
l 1
 
9.1%
w 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
M 2
28.6%
O 2
28.6%
K 2
28.6%
Y 1
14.3%
Decimal Number
ValueCountFrequency (%)
4 4
40.0%
1 4
40.0%
2 2
20.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2162
96.3%
Common 65
 
2.9%
Latin 18
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
225
 
10.4%
224
 
10.4%
142
 
6.6%
141
 
6.5%
59
 
2.7%
52
 
2.4%
49
 
2.3%
45
 
2.1%
41
 
1.9%
39
 
1.8%
Other values (225) 1145
53.0%
Latin
ValueCountFrequency (%)
o 3
16.7%
M 2
11.1%
r 2
11.1%
O 2
11.1%
K 2
11.1%
m 1
 
5.6%
s 1
 
5.6%
i 1
 
5.6%
d 1
 
5.6%
l 1
 
5.6%
Other values (2) 2
11.1%
Common
ValueCountFrequency (%)
42
64.6%
( 5
 
7.7%
) 5
 
7.7%
4 4
 
6.2%
1 4
 
6.2%
. 2
 
3.1%
2 2
 
3.1%
, 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2162
96.3%
ASCII 83
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
225
 
10.4%
224
 
10.4%
142
 
6.6%
141
 
6.5%
59
 
2.7%
52
 
2.4%
49
 
2.3%
45
 
2.1%
41
 
1.9%
39
 
1.8%
Other values (225) 1145
53.0%
ASCII
ValueCountFrequency (%)
42
50.6%
( 5
 
6.0%
) 5
 
6.0%
4 4
 
4.8%
1 4
 
4.8%
o 3
 
3.6%
. 2
 
2.4%
M 2
 
2.4%
r 2
 
2.4%
2 2
 
2.4%
Other values (10) 12
 
14.5%
Distinct342
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1999-03-22 00:00:00
Maximum2023-12-05 15:09:49
2024-05-11T17:03:22.826021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:22.964289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
372 
U
98 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 372
79.1%
U 98
 
20.9%

Length

2024-05-11T17:03:23.125748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:23.229076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 372
79.1%
u 98
 
20.9%
Distinct82
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2022-12-04 22:05:00
2024-05-11T17:03:23.351287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:03:23.498855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
일반세탁업
429 
빨래방업
 
23
운동화전문세탁업
 
12
세탁업 기타
 
6

Length

Max length8
Median length5
Mean length5.0404255
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반세탁업
2nd row일반세탁업
3rd row일반세탁업
4th row일반세탁업
5th row일반세탁업

Common Values

ValueCountFrequency (%)
일반세탁업 429
91.3%
빨래방업 23
 
4.9%
운동화전문세탁업 12
 
2.6%
세탁업 기타 6
 
1.3%

Length

2024-05-11T17:03:23.674441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:23.850540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 429
90.1%
빨래방업 23
 
4.8%
운동화전문세탁업 12
 
2.5%
세탁업 6
 
1.3%
기타 6
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct351
Distinct (%)76.5%
Missing11
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean203261.9
Minimum201275.31
Maximum204623.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T17:03:23.997360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201275.31
5-th percentile202115.62
Q1202831.27
median203315.57
Q3203753.16
95-th percentile204212
Maximum204623.02
Range3347.71
Interquartile range (IQR)921.8868

Descriptive statistics

Standard deviation661.52011
Coefficient of variation (CV)0.0032545209
Kurtosis0.06783473
Mean203261.9
Median Absolute Deviation (MAD)451.89814
Skewness-0.50923879
Sum93297213
Variance437608.85
MonotonicityNot monotonic
2024-05-11T17:03:24.193112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204192.915094501 6
 
1.3%
202237.410410982 6
 
1.3%
204169.847670316 5
 
1.1%
204031.968329866 4
 
0.9%
203034.367076332 4
 
0.9%
202480.863291217 4
 
0.9%
204214.210632572 3
 
0.6%
203569.924230066 3
 
0.6%
204178.603486457 3
 
0.6%
204623.018873403 3
 
0.6%
Other values (341) 418
88.9%
(Missing) 11
 
2.3%
ValueCountFrequency (%)
201275.308860073 2
0.4%
201290.465392239 2
0.4%
201297.754230366 1
0.2%
201347.360601868 1
0.2%
201402.961915116 1
0.2%
201501.945534806 1
0.2%
201546.846516404 1
0.2%
201849.092876972 1
0.2%
201872.541247361 1
0.2%
201916.386863619 1
0.2%
ValueCountFrequency (%)
204623.018873403 3
0.6%
204468.657003222 2
0.4%
204414.113861369 2
0.4%
204388.488423515 1
 
0.2%
204372.245062863 1
 
0.2%
204367.28957808 2
0.4%
204304.582300411 1
 
0.2%
204256.35494754 1
 
0.2%
204256.34452567 1
 
0.2%
204255.071269421 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct351
Distinct (%)76.5%
Missing11
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean461817.92
Minimum458954.55
Maximum464977.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T17:03:24.678866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum458954.55
5-th percentile459594.41
Q1460786.69
median461737.66
Q3462745.91
95-th percentile464370.6
Maximum464977.79
Range6023.2416
Interquartile range (IQR)1959.224

Descriptive statistics

Standard deviation1384.6596
Coefficient of variation (CV)0.0029982803
Kurtosis-0.45193681
Mean461817.92
Median Absolute Deviation (MAD)965.54951
Skewness0.18622446
Sum2.1197443 × 108
Variance1917282.1
MonotonicityNot monotonic
2024-05-11T17:03:24.836375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461653.03000502 6
 
1.3%
461736.71535014 6
 
1.3%
464814.717432497 5
 
1.1%
461333.59735433 4
 
0.9%
461652.607571422 4
 
0.9%
461781.424512879 4
 
0.9%
460746.553675666 3
 
0.6%
461317.249801704 3
 
0.6%
462521.720396049 3
 
0.6%
460378.90288955 3
 
0.6%
Other values (341) 418
88.9%
(Missing) 11
 
2.3%
ValueCountFrequency (%)
458954.54912126 2
0.4%
459025.006247749 1
0.2%
459045.546289341 1
0.2%
459076.349555381 1
0.2%
459086.49336668 1
0.2%
459088.76279645 2
0.4%
459117.54081963 1
0.2%
459176.67168066 1
0.2%
459219.034904213 1
0.2%
459306.956666314 1
0.2%
ValueCountFrequency (%)
464977.790753524 2
 
0.4%
464926.884466418 1
 
0.2%
464905.033086911 1
 
0.2%
464820.298057488 1
 
0.2%
464814.717432497 5
1.1%
464807.990354563 1
 
0.2%
464788.847055332 1
 
0.2%
464768.43323261 1
 
0.2%
464721.115684815 1
 
0.2%
464715.959316893 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
일반세탁업
410 
빨래방업
 
22
<NA>
 
21
운동화전문세탁업
 
12
세탁업 기타
 
5

Length

Max length8
Median length5
Mean length4.9957447
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반세탁업
2nd row일반세탁업
3rd row일반세탁업
4th row일반세탁업
5th row일반세탁업

Common Values

ValueCountFrequency (%)
일반세탁업 410
87.2%
빨래방업 22
 
4.7%
<NA> 21
 
4.5%
운동화전문세탁업 12
 
2.6%
세탁업 기타 5
 
1.1%

Length

2024-05-11T17:03:25.001071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:25.156480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 410
86.3%
빨래방업 22
 
4.6%
na 21
 
4.4%
운동화전문세탁업 12
 
2.5%
세탁업 5
 
1.1%
기타 5
 
1.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.9%
Missing160
Missing (%)34.0%
Infinite0
Infinite (%)0.0%
Mean1.3387097
Minimum0
Maximum11
Zeros159
Zeros (%)33.8%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T17:03:25.266643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6735478
Coefficient of variation (CV)1.25012
Kurtosis2.9910078
Mean1.3387097
Median Absolute Deviation (MAD)0
Skewness1.350629
Sum415
Variance2.8007621
MonotonicityNot monotonic
2024-05-11T17:03:25.428757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 159
33.8%
2 47
 
10.0%
3 46
 
9.8%
4 26
 
5.5%
1 23
 
4.9%
5 5
 
1.1%
7 2
 
0.4%
6 1
 
0.2%
11 1
 
0.2%
(Missing) 160
34.0%
ValueCountFrequency (%)
0 159
33.8%
1 23
 
4.9%
2 47
 
10.0%
3 46
 
9.8%
4 26
 
5.5%
5 5
 
1.1%
6 1
 
0.2%
7 2
 
0.4%
11 1
 
0.2%
ValueCountFrequency (%)
11 1
 
0.2%
7 2
 
0.4%
6 1
 
0.2%
5 5
 
1.1%
4 26
 
5.5%
3 46
 
9.8%
2 47
 
10.0%
1 23
 
4.9%
0 159
33.8%
Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
206 
0
192 
1
67 
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length2.3148936
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 206
43.8%
0 192
40.9%
1 67
 
14.3%
2 3
 
0.6%
3 2
 
0.4%

Length

2024-05-11T17:03:25.595723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:25.736045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 206
43.8%
0 192
40.9%
1 67
 
14.3%
2 3
 
0.6%
3 2
 
0.4%
Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
1
239 
<NA>
140 
2
47 
0
35 
3
 
8

Length

Max length4
Median length1
Mean length1.893617
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 239
50.9%
<NA> 140
29.8%
2 47
 
10.0%
0 35
 
7.4%
3 8
 
1.7%
4 1
 
0.2%

Length

2024-05-11T17:03:25.893236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:26.070015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 239
50.9%
na 140
29.8%
2 47
 
10.0%
0 35
 
7.4%
3 8
 
1.7%
4 1
 
0.2%
Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
1
230 
<NA>
163 
2
47 
0
 
22
3
 
7

Length

Max length4
Median length1
Mean length2.0404255
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 230
48.9%
<NA> 163
34.7%
2 47
 
10.0%
0 22
 
4.7%
3 7
 
1.5%
4 1
 
0.2%

Length

2024-05-11T17:03:26.224161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:26.349331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 230
48.9%
na 163
34.7%
2 47
 
10.0%
0 22
 
4.7%
3 7
 
1.5%
4 1
 
0.2%
Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
303 
0
156 
1
 
10
2
 
1

Length

Max length4
Median length4
Mean length2.9340426
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 303
64.5%
0 156
33.2%
1 10
 
2.1%
2 1
 
0.2%

Length

2024-05-11T17:03:26.494372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:26.612008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 303
64.5%
0 156
33.2%
1 10
 
2.1%
2 1
 
0.2%
Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
319 
0
140 
1
 
10
2
 
1

Length

Max length4
Median length4
Mean length3.0361702
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 319
67.9%
0 140
29.8%
1 10
 
2.1%
2 1
 
0.2%

Length

2024-05-11T17:03:26.740668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:26.858424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
67.9%
0 140
29.8%
1 10
 
2.1%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
241 
0
229 

Length

Max length4
Median length4
Mean length2.5382979
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 241
51.3%
0 229
48.7%

Length

2024-05-11T17:03:26.998408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:27.131836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
51.3%
0 229
48.7%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
241 
0
229 

Length

Max length4
Median length4
Mean length2.5382979
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 241
51.3%
0 229
48.7%

Length

2024-05-11T17:03:27.273595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:27.406071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
51.3%
0 229
48.7%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
241 
0
229 

Length

Max length4
Median length4
Mean length2.5382979
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 241
51.3%
0 229
48.7%

Length

2024-05-11T17:03:27.547734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:27.672234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
51.3%
0 229
48.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing33
Missing (%)7.0%
Memory size1.0 KiB
False
437 
(Missing)
 
33
ValueCountFrequency (%)
False 437
93.0%
(Missing) 33
 
7.0%
2024-05-11T17:03:27.790192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
239 
0
229 
3
 
2

Length

Max length4
Median length4
Mean length2.5255319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 239
50.9%
0 229
48.7%
3 2
 
0.4%

Length

2024-05-11T17:03:27.912092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:28.039075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
50.9%
0 229
48.7%
3 2
 
0.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
291 
임대
160 
자가
 
19

Length

Max length4
Median length4
Mean length3.2382979
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row임대
4th row임대
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 291
61.9%
임대 160
34.0%
자가 19
 
4.0%

Length

2024-05-11T17:03:28.178810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:28.313760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 291
61.9%
임대 160
34.0%
자가 19
 
4.0%

세탁기수
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
251 
0
133 
1
37 
2
29 
3
 
19

Length

Max length4
Median length4
Mean length2.6021277
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 251
53.4%
0 133
28.3%
1 37
 
7.9%
2 29
 
6.2%
3 19
 
4.0%
4 1
 
0.2%

Length

2024-05-11T17:03:28.443608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:28.580709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 251
53.4%
0 133
28.3%
1 37
 
7.9%
2 29
 
6.2%
3 19
 
4.0%
4 1
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
423 
0
47 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 423
90.0%
0 47
 
10.0%

Length

2024-05-11T17:03:28.727371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:28.853301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 423
90.0%
0 47
 
10.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
423 
0
47 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 423
90.0%
0 47
 
10.0%

Length

2024-05-11T17:03:28.983497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.115444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 423
90.0%
0 47
 
10.0%

회수건조수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
370 
0
79 
1
 
20
7
 
1

Length

Max length4
Median length4
Mean length3.3617021
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 370
78.7%
0 79
 
16.8%
1 20
 
4.3%
7 1
 
0.2%

Length

2024-05-11T17:03:29.246699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.376156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
78.7%
0 79
 
16.8%
1 20
 
4.3%
7 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
371 
0
99 

Length

Max length4
Median length4
Mean length3.3680851
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 371
78.9%
0 99
 
21.1%

Length

2024-05-11T17:03:29.508793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:03:29.619742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
78.9%
0 99
 
21.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing21
Missing (%)4.5%
Memory size1.0 KiB
False
449 
(Missing)
 
21
ValueCountFrequency (%)
False 449
95.5%
(Missing) 21
 
4.5%
2024-05-11T17:03:29.714856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030900003090000-205-1987-0119519870704<NA>3폐업2폐업20190527<NA><NA><NA>02 954228016.50132819서울특별시 도봉구 도봉동 600-3번지서울특별시 도봉구 도봉로165길 9 (도봉동)1307백설사2019-05-27 16:09:57U2019-05-29 02:40:00.0일반세탁업203841.064216463872.82088일반세탁업001100000N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
130900003090000-205-1987-0119819870715<NA>3폐업2폐업20030711<NA><NA><NA>020000000014.66132816서울특별시 도봉구 도봉동 589-7번지<NA><NA>동궁사2003-05-16 00:00:00I2018-08-31 23:59:59.0일반세탁업203593.652659464139.818411일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230900003090000-205-1987-0119919870715<NA>1영업/정상1영업<NA><NA><NA><NA>020954159010.56132814서울특별시 도봉구 도봉동 566-5번지서울특별시 도봉구 도봉로181길 25 (도봉동)1304미미사2014-01-02 11:51:16I2018-08-31 23:59:59.0일반세탁업203855.291595464621.700291일반세탁업201100000N0<NA><NA><NA>임대0<NA><NA><NA><NA>N
330900003090000-205-1987-0120219870605<NA>3폐업2폐업20160713<NA><NA><NA>906427119.49132875서울특별시 도봉구 쌍문동 286-68번지 (28/5)서울특별시 도봉구 우이천로36길 8 (쌍문동,(28/5))1378영광세탁소2007-06-08 00:00:00I2018-08-31 23:59:59.0일반세탁업201978.773856460854.316013일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
430900003090000-205-1987-0120419870630<NA>3폐업2폐업20030501<NA><NA><NA>020994546817.80132815서울특별시 도봉구 도봉동 574-34번지<NA><NA>백광사2003-05-23 00:00:00I2018-08-31 23:59:59.0일반세탁업203741.36581464699.323138일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530900003090000-205-1987-0120519870625<NA>3폐업2폐업20021129<NA><NA><NA>020905740319.74132821서울특별시 도봉구 도봉동 625-33번지<NA><NA>백합사2003-06-23 00:00:00I2018-08-31 23:59:59.0일반세탁업204017.85546463580.323873일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630900003090000-205-1987-0120619870918<NA>3폐업2폐업20120830<NA><NA><NA>02954 875014.42132821서울특별시 도봉구 도봉동 623-94번지서울특별시 도봉구 도봉로154가길 26 (도봉동)1328웰빙사2007-03-30 00:00:00I2018-08-31 23:59:59.0일반세탁업203947.083435463341.502685일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
730900003090000-205-1987-0120819870625<NA>3폐업2폐업20030226<NA><NA><NA>020904625513.42132821서울특별시 도봉구 도봉동 623-123번지<NA><NA>거북사2003-02-26 00:00:00I2018-08-31 23:59:59.0일반세탁업204015.770775463287.403652일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830900003090000-205-1987-0121019870630<NA>3폐업2폐업20021226<NA><NA><NA>020905854718.51132822서울특별시 도봉구 도봉동 628-1번지<NA><NA>화성사2003-05-26 00:00:00I2018-08-31 23:59:59.0일반세탁업203985.756748464010.932065일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930900003090000-205-1987-0121119870625<NA>3폐업2폐업20050715<NA><NA><NA>023493568815.63132854서울특별시 도봉구 방학동 713-36번지<NA><NA>대흥사세탁소2003-11-18 00:00:00I2018-08-31 23:59:59.0일반세탁업204005.41103462287.033408일반세탁업<NA><NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
46030900003090000-205-2019-0000120190411<NA>1영업/정상1영업<NA><NA><NA><NA>02 997 879633.00132864서울특별시 도봉구 쌍문동 103-61 지상1층서울특별시 도봉구 도봉로109길 35-7, 지상1층 (쌍문동)1448노아2020-10-12 12:00:39U2020-10-14 02:40:00.0일반세탁업202711.666199460480.612615일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>00000N
46130900003090000-205-2019-0000220190517<NA>3폐업2폐업20190829<NA><NA><NA>02 900 370716.50132864서울특별시 도봉구 쌍문동 103-70번지 지상1층서울특별시 도봉구 도봉로 413, 지상1층 (쌍문동)1452바디시크릿2019-08-29 09:27:54U2019-08-31 02:40:00.0빨래방업202665.184974460114.547562빨래방업0011<NA><NA>000N0<NA><NA><NA><NA>00000N
46230900003090000-205-2019-0000320190703<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.36132771서울특별시 도봉구 쌍문동 285-5번지 동익아파트 5동상가동 2층6호서울특별시 도봉구 우이천로32길 65, 동익아파트 5동상가동 2층6호 (쌍문동)1379동익세탁소2019-07-03 10:05:08I2019-07-05 02:21:29.0일반세탁업202115.623338461010.132322일반세탁업0022<NA><NA>000N0<NA><NA><NA><NA>00000N
46330900003090000-205-2020-0000120200416<NA>1영업/정상1영업<NA><NA><NA><NA>02 997307618.60132910서울특별시 도봉구 창동 347-4번지 주공3단지아파트 종합상가 110호서울특별시 도봉구 해등로 48, 주공3단지아파트 종합상가 110호 (창동)1421특급세탁소2020-04-16 11:13:57I2020-04-18 00:23:21.0일반세탁업203794.927271460699.794608일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>10010N
46430900003090000-205-2021-0000120210513<NA>3폐업2폐업20210830<NA><NA><NA><NA>30.00132020서울특별시 도봉구 방학동 734 청구아파트 상가B동 203호서울특별시 도봉구 해등로 268, 청구아파트 상가B동 203호 (방학동)1363청구세탁소2021-08-30 15:30:21U2021-09-01 02:40:00.0일반세탁업202237.410411461736.71535일반세탁업002200000N0<NA><NA><NA><NA>40000N
46530900003090000-205-2021-0000220210622<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.00132819서울특별시 도봉구 도봉동 602-21 1층서울특별시 도봉구 도봉로159길 30, 1층 (도봉동)1308주식회사 월드탑크린2021-06-22 10:40:06I2021-06-24 00:22:53.0일반세탁업203691.505814463568.862076일반세탁업001100000N0<NA><NA><NA><NA>00000N
46630900003090000-205-2021-0000320211005<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.75132925서울특별시 도봉구 창동 667-54서울특별시 도봉구 도봉로110바길 40, 1층 (창동)1456창대세탁2021-10-05 13:58:44I2021-10-07 00:22:47.0일반세탁업203229.807583460643.429541일반세탁업000000000N0<NA><NA><NA><NA>10010N
46730900003090000-205-2021-0000420211012<NA>3폐업2폐업20220824<NA><NA><NA>02 955 1317134.86132913서울특별시 도봉구 창동 443-6서울특별시 도봉구 덕릉로 272, 1층 (창동)1487도봉지역자활센터2022-08-24 11:26:13U2021-12-07 22:06:00.0일반세탁업203553.135407459890.855841<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46830900003090000-205-2022-0000120220120<NA>1영업/정상1영업<NA><NA><NA><NA>02995 212145.21132040서울특별시 도봉구 창동 27-3 주공아파트서울특별시 도봉구 노해로70길 46, 주공아파트 상가동 지하1층 10호 (창동)1417백양2022-01-20 11:58:46I2022-01-22 00:22:40.0일반세탁업204468.657003460879.972975일반세탁업001100000N0<NA><NA><NA><NA>30000N
46930900003090000-205-2022-0000220220520<NA>1영업/정상1영업<NA><NA><NA><NA>1666833146.20132817서울특별시 도봉구 도봉동 594-10 1층서울특별시 도봉구 도봉로169길 53, 1층 (도봉동)1306아이자리2022-05-20 16:38:33I2021-12-04 22:02:00.0세탁업 기타203721.773715464096.867767<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>