Overview

Dataset statistics

Number of variables47
Number of observations664
Missing cells6459
Missing cells (%)20.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory262.1 KiB
Average record size in memory404.2 B

Variable types

Categorical22
Text7
DateTime4
Unsupported7
Numeric5
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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-17956/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (83.7%)Imbalance
위생업태명 is highly imbalanced (73.4%)Imbalance
사용끝지상층 is highly imbalanced (57.2%)Imbalance
사용끝지하층 is highly imbalanced (80.6%)Imbalance
건물소유구분명 is highly imbalanced (81.4%)Imbalance
여성종사자수 is highly imbalanced (71.1%)Imbalance
남성종사자수 is highly imbalanced (75.1%)Imbalance
회수건조수 is highly imbalanced (66.1%)Imbalance
인허가취소일자 has 664 (100.0%) missing valuesMissing
폐업일자 has 162 (24.4%) missing valuesMissing
휴업시작일자 has 664 (100.0%) missing valuesMissing
휴업종료일자 has 664 (100.0%) missing valuesMissing
재개업일자 has 664 (100.0%) missing valuesMissing
전화번호 has 62 (9.3%) missing valuesMissing
도로명주소 has 280 (42.2%) missing valuesMissing
도로명우편번호 has 287 (43.2%) missing valuesMissing
좌표정보(X) has 16 (2.4%) missing valuesMissing
좌표정보(Y) has 16 (2.4%) missing valuesMissing
건물지상층수 has 356 (53.6%) missing valuesMissing
발한실여부 has 44 (6.6%) missing valuesMissing
조건부허가신고사유 has 664 (100.0%) missing valuesMissing
조건부허가시작일자 has 664 (100.0%) missing valuesMissing
조건부허가종료일자 has 664 (100.0%) missing valuesMissing
세탁기수 has 548 (82.5%) missing valuesMissing
다중이용업소여부 has 40 (6.0%) 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 203 (30.6%) zerosZeros
세탁기수 has 40 (6.0%) zerosZeros

Reproduction

Analysis started2024-05-11 05:36:56.130246
Analysis finished2024-05-11 05:36:57.375257
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3040000
664 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 664
100.0%

Length

2024-05-11T14:36:57.461664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:57.622703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 664
100.0%

관리번호
Text

UNIQUE 

Distinct664
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T14:36:57.910970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters14608
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

Unique664 ?
Unique (%)100.0%

Sample

1st row3040000-205-1987-01502
2nd row3040000-205-1987-01512
3rd row3040000-205-1987-01514
4th row3040000-205-1987-01515
5th row3040000-205-1987-01516
ValueCountFrequency (%)
3040000-205-1987-01502 1
 
0.2%
3040000-205-2003-00011 1
 
0.2%
3040000-205-2003-00013 1
 
0.2%
3040000-205-2003-00014 1
 
0.2%
3040000-205-2003-00015 1
 
0.2%
3040000-205-2003-00016 1
 
0.2%
3040000-205-2003-00017 1
 
0.2%
3040000-205-2003-00018 1
 
0.2%
3040000-205-2003-00019 1
 
0.2%
3040000-205-2003-00020 1
 
0.2%
Other values (654) 654
98.5%
2024-05-11T14:36:58.383242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5839
40.0%
- 1992
 
13.6%
2 1109
 
7.6%
1 1097
 
7.5%
5 928
 
6.4%
3 889
 
6.1%
4 835
 
5.7%
9 767
 
5.3%
8 505
 
3.5%
7 376
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12616
86.4%
Dash Punctuation 1992
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5839
46.3%
2 1109
 
8.8%
1 1097
 
8.7%
5 928
 
7.4%
3 889
 
7.0%
4 835
 
6.6%
9 767
 
6.1%
8 505
 
4.0%
7 376
 
3.0%
6 271
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 1992
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14608
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5839
40.0%
- 1992
 
13.6%
2 1109
 
7.6%
1 1097
 
7.5%
5 928
 
6.4%
3 889
 
6.1%
4 835
 
5.7%
9 767
 
5.3%
8 505
 
3.5%
7 376
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14608
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5839
40.0%
- 1992
 
13.6%
2 1109
 
7.6%
1 1097
 
7.5%
5 928
 
6.4%
3 889
 
6.1%
4 835
 
5.7%
9 767
 
5.3%
8 505
 
3.5%
7 376
 
2.6%
Distinct407
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1987-01-12 00:00:00
Maximum2024-03-05 00:00:00
2024-05-11T14:36:58.613866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:58.856046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3
502 
1
162 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 502
75.6%
1 162
 
24.4%

Length

2024-05-11T14:36:59.119647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:59.332188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 502
75.6%
1 162
 
24.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
502 
영업/정상
162 

Length

Max length5
Median length2
Mean length2.7319277
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 502
75.6%
영업/정상 162
 
24.4%

Length

2024-05-11T14:36:59.539950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:59.769650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 502
75.6%
영업/정상 162
 
24.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2
502 
1
162 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 502
75.6%
1 162
 
24.4%

Length

2024-05-11T14:36:59.976126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:00.196833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 502
75.6%
1 162
 
24.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
502 
영업
162 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 502
75.6%
영업 162
 
24.4%

Length

2024-05-11T14:37:00.409625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:00.573410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 502
75.6%
영업 162
 
24.4%

폐업일자
Date

MISSING 

Distinct366
Distinct (%)72.9%
Missing162
Missing (%)24.4%
Memory size5.3 KiB
Minimum1988-02-16 00:00:00
Maximum2023-12-26 00:00:00
2024-05-11T14:37:00.740308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:37:00.989166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

전화번호
Text

MISSING 

Distinct531
Distinct (%)88.2%
Missing62
Missing (%)9.3%
Memory size5.3 KiB
2024-05-11T14:37:01.347653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.142857
Min length6

Characters and Unicode

Total characters6106
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

Unique479 ?
Unique (%)79.6%

Sample

1st row02 4662468
2nd row02 4448620
3rd row02 4448250
4th row02 4460680
5th row02 4476143
ValueCountFrequency (%)
02 562
45.7%
0 16
 
1.3%
454 8
 
0.7%
447 7
 
0.6%
467 6
 
0.5%
456 5
 
0.4%
453 5
 
0.4%
457 5
 
0.4%
444 4
 
0.3%
458 4
 
0.3%
Other values (545) 608
49.4%
2024-05-11T14:37:02.019090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1005
16.5%
2 940
15.4%
0 862
14.1%
741
12.1%
6 508
8.3%
5 481
7.9%
7 354
 
5.8%
3 338
 
5.5%
8 315
 
5.2%
9 288
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5365
87.9%
Space Separator 741
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1005
18.7%
2 940
17.5%
0 862
16.1%
6 508
9.5%
5 481
9.0%
7 354
 
6.6%
3 338
 
6.3%
8 315
 
5.9%
9 288
 
5.4%
1 274
 
5.1%
Space Separator
ValueCountFrequency (%)
741
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6106
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1005
16.5%
2 940
15.4%
0 862
14.1%
741
12.1%
6 508
8.3%
5 481
7.9%
7 354
 
5.8%
3 338
 
5.5%
8 315
 
5.2%
9 288
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1005
16.5%
2 940
15.4%
0 862
14.1%
741
12.1%
6 508
8.3%
5 481
7.9%
7 354
 
5.8%
3 338
 
5.5%
8 315
 
5.2%
9 288
 
4.7%
Distinct307
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T14:37:02.671545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.5316265
Min length3

Characters and Unicode

Total characters3009
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

Unique244 ?
Unique (%)36.7%

Sample

1st row23.40
2nd row14.40
3rd row20.40
4th row11.70
5th row11.00
ValueCountFrequency (%)
00 176
26.5%
33.00 19
 
2.9%
24.00 13
 
2.0%
26.40 12
 
1.8%
20.00 12
 
1.8%
25.00 11
 
1.7%
30.00 9
 
1.4%
23.10 9
 
1.4%
19.80 8
 
1.2%
29.70 6
 
0.9%
Other values (297) 389
58.6%
2024-05-11T14:37:03.818500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 895
29.7%
. 664
22.1%
2 273
 
9.1%
1 232
 
7.7%
3 212
 
7.0%
4 165
 
5.5%
5 154
 
5.1%
8 117
 
3.9%
6 108
 
3.6%
7 96
 
3.2%
Other values (2) 93
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2344
77.9%
Other Punctuation 665
 
22.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 895
38.2%
2 273
 
11.6%
1 232
 
9.9%
3 212
 
9.0%
4 165
 
7.0%
5 154
 
6.6%
8 117
 
5.0%
6 108
 
4.6%
7 96
 
4.1%
9 92
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 664
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 895
29.7%
. 664
22.1%
2 273
 
9.1%
1 232
 
7.7%
3 212
 
7.0%
4 165
 
5.5%
5 154
 
5.1%
8 117
 
3.9%
6 108
 
3.6%
7 96
 
3.2%
Other values (2) 93
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 895
29.7%
. 664
22.1%
2 273
 
9.1%
1 232
 
7.7%
3 212
 
7.0%
4 165
 
5.5%
5 154
 
5.1%
8 117
 
3.9%
6 108
 
3.6%
7 96
 
3.2%
Other values (2) 93
 
3.1%
Distinct118
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T14:37:04.319317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0331325
Min length6

Characters and Unicode

Total characters4006
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

Unique35 ?
Unique (%)5.3%

Sample

1st row143840
2nd row143806
3rd row143835
4th row143817
5th row143816
ValueCountFrequency (%)
143865 20
 
3.0%
143888 18
 
2.7%
143887 18
 
2.7%
143842 15
 
2.3%
143914 15
 
2.3%
143915 15
 
2.3%
143866 15
 
2.3%
143837 15
 
2.3%
143916 15
 
2.3%
143822 14
 
2.1%
Other values (108) 504
75.9%
2024-05-11T14:37:04.934008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 827
20.6%
4 799
19.9%
3 787
19.6%
8 635
15.9%
9 233
 
5.8%
2 160
 
4.0%
6 153
 
3.8%
0 135
 
3.4%
7 132
 
3.3%
5 123
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3984
99.5%
Dash Punctuation 22
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 827
20.8%
4 799
20.1%
3 787
19.8%
8 635
15.9%
9 233
 
5.8%
2 160
 
4.0%
6 153
 
3.8%
0 135
 
3.4%
7 132
 
3.3%
5 123
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 827
20.6%
4 799
19.9%
3 787
19.6%
8 635
15.9%
9 233
 
5.8%
2 160
 
4.0%
6 153
 
3.8%
0 135
 
3.4%
7 132
 
3.3%
5 123
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 827
20.6%
4 799
19.9%
3 787
19.6%
8 635
15.9%
9 233
 
5.8%
2 160
 
4.0%
6 153
 
3.8%
0 135
 
3.4%
7 132
 
3.3%
5 123
 
3.1%
Distinct620
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T14:37:05.424067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length22.923193
Min length16

Characters and Unicode

Total characters15221
Distinct characters99
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

Unique583 ?
Unique (%)87.8%

Sample

1st row서울특별시 광진구 군자동 371-4번지
2nd row서울특별시 광진구 광장동 272-4번지
3rd row서울특별시 광진구 구의동 636-5번지
4th row서울특별시 광진구 구의동 33-12번지
5th row서울특별시 광진구 구의동 30-15번지
ValueCountFrequency (%)
서울특별시 664
23.4%
광진구 664
23.4%
자양동 210
 
7.4%
중곡동 159
 
5.6%
구의동 127
 
4.5%
1층 65
 
2.3%
화양동 61
 
2.2%
군자동 57
 
2.0%
광장동 32
 
1.1%
능동 18
 
0.6%
Other values (676) 779
27.5%
2024-05-11T14:37:06.264416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2781
18.3%
791
 
5.2%
701
 
4.6%
676
 
4.4%
665
 
4.4%
665
 
4.4%
664
 
4.4%
664
 
4.4%
664
 
4.4%
664
 
4.4%
Other values (89) 6286
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8675
57.0%
Decimal Number 3057
 
20.1%
Space Separator 2781
 
18.3%
Dash Punctuation 633
 
4.2%
Open Punctuation 30
 
0.2%
Close Punctuation 30
 
0.2%
Uppercase Letter 11
 
0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
791
 
9.1%
701
 
8.1%
676
 
7.8%
665
 
7.7%
665
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
501
 
5.8%
Other values (68) 2020
23.3%
Decimal Number
ValueCountFrequency (%)
1 578
18.9%
2 479
15.7%
3 334
10.9%
4 326
10.7%
5 299
9.8%
6 286
9.4%
0 221
 
7.2%
7 206
 
6.7%
8 165
 
5.4%
9 163
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 6
54.5%
F 2
 
18.2%
P 1
 
9.1%
T 1
 
9.1%
B 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2781
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 633
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8675
57.0%
Common 6535
42.9%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
791
 
9.1%
701
 
8.1%
676
 
7.8%
665
 
7.7%
665
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
501
 
5.8%
Other values (68) 2020
23.3%
Common
ValueCountFrequency (%)
2781
42.6%
- 633
 
9.7%
1 578
 
8.8%
2 479
 
7.3%
3 334
 
5.1%
4 326
 
5.0%
5 299
 
4.6%
6 286
 
4.4%
0 221
 
3.4%
7 206
 
3.2%
Other values (6) 392
 
6.0%
Latin
ValueCountFrequency (%)
A 6
54.5%
F 2
 
18.2%
P 1
 
9.1%
T 1
 
9.1%
B 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8675
57.0%
ASCII 6546
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2781
42.5%
- 633
 
9.7%
1 578
 
8.8%
2 479
 
7.3%
3 334
 
5.1%
4 326
 
5.0%
5 299
 
4.6%
6 286
 
4.4%
0 221
 
3.4%
7 206
 
3.1%
Other values (11) 403
 
6.2%
Hangul
ValueCountFrequency (%)
791
 
9.1%
701
 
8.1%
676
 
7.8%
665
 
7.7%
665
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
664
 
7.7%
501
 
5.8%
Other values (68) 2020
23.3%

도로명주소
Text

MISSING 

Distinct368
Distinct (%)95.8%
Missing280
Missing (%)42.2%
Memory size5.3 KiB
2024-05-11T14:37:06.721430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length28.127604
Min length22

Characters and Unicode

Total characters10801
Distinct characters124
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

Unique353 ?
Unique (%)91.9%

Sample

1st row서울특별시 광진구 광나루로17길 14-5 (군자동)
2nd row서울특별시 광진구 자양로32길 84 (구의동)
3rd row서울특별시 광진구 광나루로40길 34, 1층 (구의동)
4th row서울특별시 광진구 구의로 67 (구의동)
5th row서울특별시 광진구 자양로18길 67 (구의동)
ValueCountFrequency (%)
서울특별시 384
18.2%
광진구 384
18.2%
자양동 100
 
4.7%
중곡동 92
 
4.4%
1층 77
 
3.6%
구의동 71
 
3.4%
군자동 29
 
1.4%
화양동 28
 
1.3%
광장동 16
 
0.8%
군자로 13
 
0.6%
Other values (439) 918
43.5%
2024-05-11T14:37:07.497285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1728
 
16.0%
493
 
4.6%
478
 
4.4%
433
 
4.0%
1 420
 
3.9%
( 409
 
3.8%
) 409
 
3.8%
388
 
3.6%
387
 
3.6%
385
 
3.6%
Other values (114) 5271
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6349
58.8%
Space Separator 1728
 
16.0%
Decimal Number 1691
 
15.7%
Open Punctuation 409
 
3.8%
Close Punctuation 409
 
3.8%
Other Punctuation 178
 
1.6%
Dash Punctuation 35
 
0.3%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
493
 
7.8%
478
 
7.5%
433
 
6.8%
388
 
6.1%
387
 
6.1%
385
 
6.1%
384
 
6.0%
384
 
6.0%
384
 
6.0%
384
 
6.0%
Other values (98) 2249
35.4%
Decimal Number
ValueCountFrequency (%)
1 420
24.8%
2 211
12.5%
3 207
12.2%
5 157
 
9.3%
4 151
 
8.9%
0 137
 
8.1%
6 134
 
7.9%
8 101
 
6.0%
7 100
 
5.9%
9 73
 
4.3%
Space Separator
ValueCountFrequency (%)
1728
100.0%
Open Punctuation
ValueCountFrequency (%)
( 409
100.0%
Close Punctuation
ValueCountFrequency (%)
) 409
100.0%
Other Punctuation
ValueCountFrequency (%)
, 178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6349
58.8%
Common 4450
41.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
493
 
7.8%
478
 
7.5%
433
 
6.8%
388
 
6.1%
387
 
6.1%
385
 
6.1%
384
 
6.0%
384
 
6.0%
384
 
6.0%
384
 
6.0%
Other values (98) 2249
35.4%
Common
ValueCountFrequency (%)
1728
38.8%
1 420
 
9.4%
( 409
 
9.2%
) 409
 
9.2%
2 211
 
4.7%
3 207
 
4.7%
, 178
 
4.0%
5 157
 
3.5%
4 151
 
3.4%
0 137
 
3.1%
Other values (5) 443
 
10.0%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6349
58.8%
ASCII 4452
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1728
38.8%
1 420
 
9.4%
( 409
 
9.2%
) 409
 
9.2%
2 211
 
4.7%
3 207
 
4.6%
, 178
 
4.0%
5 157
 
3.5%
4 151
 
3.4%
0 137
 
3.1%
Other values (6) 445
 
10.0%
Hangul
ValueCountFrequency (%)
493
 
7.8%
478
 
7.5%
433
 
6.8%
388
 
6.1%
387
 
6.1%
385
 
6.1%
384
 
6.0%
384
 
6.0%
384
 
6.0%
384
 
6.0%
Other values (98) 2249
35.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct161
Distinct (%)42.7%
Missing287
Missing (%)43.2%
Infinite0
Infinite (%)0.0%
Mean5007.626
Minimum4901
Maximum5119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-11T14:37:07.787951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4901
5-th percentile4906.8
Q14949
median5008
Q35062
95-th percentile5105
Maximum5119
Range218
Interquartile range (IQR)113

Descriptive statistics

Standard deviation64.464535
Coefficient of variation (CV)0.012873273
Kurtosis-1.1694118
Mean5007.626
Median Absolute Deviation (MAD)57
Skewness-0.017500036
Sum1887875
Variance4155.6762
MonotonicityNot monotonic
2024-05-11T14:37:08.046631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5015 7
 
1.1%
4945 6
 
0.9%
5066 6
 
0.9%
5099 6
 
0.9%
4986 6
 
0.9%
4903 6
 
0.9%
5098 6
 
0.9%
5041 6
 
0.9%
4974 5
 
0.8%
5101 5
 
0.8%
Other values (151) 318
47.9%
(Missing) 287
43.2%
ValueCountFrequency (%)
4901 1
 
0.2%
4902 5
0.8%
4903 6
0.9%
4904 3
0.5%
4905 3
0.5%
4906 1
 
0.2%
4907 2
 
0.3%
4908 4
0.6%
4909 1
 
0.2%
4910 1
 
0.2%
ValueCountFrequency (%)
5119 2
0.3%
5118 1
 
0.2%
5117 1
 
0.2%
5116 4
0.6%
5115 2
0.3%
5112 3
0.5%
5108 2
0.3%
5106 3
0.5%
5105 3
0.5%
5103 1
 
0.2%
Distinct469
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T14:37:08.588815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length4.4563253
Min length1

Characters and Unicode

Total characters2959
Distinct characters278
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)56.6%

Sample

1st row수도사
2nd row백영사
3rd row대성사
4th row명문사
5th row보들세탁
ValueCountFrequency (%)
현대세탁소 16
 
2.3%
현대사 16
 
2.3%
세탁소 12
 
1.7%
백양사 10
 
1.4%
그린세탁소 8
 
1.1%
백양세탁소 8
 
1.1%
중앙사 6
 
0.9%
제일사 6
 
0.9%
백조사 6
 
0.9%
빨래방 6
 
0.9%
Other values (471) 609
86.6%
2024-05-11T14:37:09.342238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
9.1%
248
 
8.4%
246
 
8.3%
162
 
5.5%
87
 
2.9%
73
 
2.5%
67
 
2.3%
67
 
2.3%
65
 
2.2%
64
 
2.2%
Other values (268) 1610
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2862
96.7%
Space Separator 40
 
1.4%
Uppercase Letter 15
 
0.5%
Decimal Number 14
 
0.5%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%
Lowercase Letter 8
 
0.3%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
270
 
9.4%
248
 
8.7%
246
 
8.6%
162
 
5.7%
87
 
3.0%
73
 
2.6%
67
 
2.3%
67
 
2.3%
65
 
2.3%
64
 
2.2%
Other values (245) 1513
52.9%
Uppercase Letter
ValueCountFrequency (%)
F 3
20.0%
C 3
20.0%
S 2
13.3%
L 1
 
6.7%
A 1
 
6.7%
N 1
 
6.7%
E 1
 
6.7%
V 1
 
6.7%
I 1
 
6.7%
P 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
c 2
25.0%
e 2
25.0%
n 1
12.5%
a 1
12.5%
l 1
12.5%
i 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 8
57.1%
4 6
42.9%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2860
96.7%
Common 74
 
2.5%
Latin 23
 
0.8%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
270
 
9.4%
248
 
8.7%
246
 
8.6%
162
 
5.7%
87
 
3.0%
73
 
2.6%
67
 
2.3%
67
 
2.3%
65
 
2.3%
64
 
2.2%
Other values (243) 1511
52.8%
Latin
ValueCountFrequency (%)
F 3
13.0%
C 3
13.0%
S 2
 
8.7%
c 2
 
8.7%
e 2
 
8.7%
L 1
 
4.3%
A 1
 
4.3%
n 1
 
4.3%
a 1
 
4.3%
l 1
 
4.3%
Other values (6) 6
26.1%
Common
ValueCountFrequency (%)
40
54.1%
( 9
 
12.2%
) 9
 
12.2%
2 8
 
10.8%
4 6
 
8.1%
- 1
 
1.4%
. 1
 
1.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2860
96.7%
ASCII 97
 
3.3%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
270
 
9.4%
248
 
8.7%
246
 
8.6%
162
 
5.7%
87
 
3.0%
73
 
2.6%
67
 
2.3%
67
 
2.3%
65
 
2.3%
64
 
2.2%
Other values (243) 1511
52.8%
ASCII
ValueCountFrequency (%)
40
41.2%
( 9
 
9.3%
) 9
 
9.3%
2 8
 
8.2%
4 6
 
6.2%
F 3
 
3.1%
C 3
 
3.1%
S 2
 
2.1%
c 2
 
2.1%
e 2
 
2.1%
Other values (13) 13
 
13.4%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct437
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1999-02-03 00:00:00
Maximum2024-03-05 16:20:36
2024-05-11T14:37:09.611854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:37:09.890600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
I
451 
U
213 

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 451
67.9%
U 213
32.1%

Length

2024-05-11T14:37:10.149024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:10.369475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 451
67.9%
u 213
32.1%
Distinct127
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:07:00
2024-05-11T14:37:10.548254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:37:10.797853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
일반세탁업
633 
빨래방업
 
18
운동화전문세탁업
 
12
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length5.0286145
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 633
95.3%
빨래방업 18
 
2.7%
운동화전문세탁업 12
 
1.8%
세탁업 기타 1
 
0.2%

Length

2024-05-11T14:37:11.131179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:11.348220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 633
95.2%
빨래방업 18
 
2.7%
운동화전문세탁업 12
 
1.8%
세탁업 1
 
0.2%
기타 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct535
Distinct (%)82.6%
Missing16
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean207107.85
Minimum205275.89
Maximum209551.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-11T14:37:11.587268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205275.89
5-th percentile205743.27
Q1206422.43
median207125.91
Q3207769.1
95-th percentile208558.29
Maximum209551.05
Range4275.1617
Interquartile range (IQR)1346.6737

Descriptive statistics

Standard deviation887.24428
Coefficient of variation (CV)0.0042839722
Kurtosis-0.29884666
Mean207107.85
Median Absolute Deviation (MAD)669.1414
Skewness0.23578825
Sum1.3420589 × 108
Variance787202.42
MonotonicityNot monotonic
2024-05-11T14:37:11.827699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208644.819209521 5
 
0.8%
209551.051963422 4
 
0.6%
207150.073653666 4
 
0.6%
207306.382464524 4
 
0.6%
208020.871131573 4
 
0.6%
205766.923712371 4
 
0.6%
208558.286631653 4
 
0.6%
208072.562115189 4
 
0.6%
206509.370227697 3
 
0.5%
207331.534670858 3
 
0.5%
Other values (525) 609
91.7%
(Missing) 16
 
2.4%
ValueCountFrequency (%)
205275.890261202 1
0.2%
205339.579978572 1
0.2%
205346.565381464 1
0.2%
205366.118854171 1
0.2%
205383.614414329 1
0.2%
205474.021736376 2
0.3%
205475.031292954 2
0.3%
205496.064969509 1
0.2%
205498.511213927 1
0.2%
205505.528803012 1
0.2%
ValueCountFrequency (%)
209551.051963422 4
0.6%
209523.395129627 2
0.3%
209433.056005011 1
 
0.2%
209416.956231521 1
 
0.2%
209410.516401176 1
 
0.2%
209390.460834219 1
 
0.2%
209345.941766315 1
 
0.2%
209237.010976216 1
 
0.2%
209175.614022905 1
 
0.2%
209138.04726487 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct535
Distinct (%)82.6%
Missing16
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean449355.44
Minimum447331.9
Maximum452124.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-11T14:37:12.075833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447331.9
5-th percentile447619.59
Q1448321.01
median449169.6
Q3450397.74
95-th percentile451573.11
Maximum452124.25
Range4792.3463
Interquartile range (IQR)2076.7322

Descriptive statistics

Standard deviation1255.6989
Coefficient of variation (CV)0.0027944446
Kurtosis-0.96225468
Mean449355.44
Median Absolute Deviation (MAD)1058.6651
Skewness0.3257293
Sum2.9118233 × 108
Variance1576779.7
MonotonicityNot monotonic
2024-05-11T14:37:12.336058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448711.725750126 5
 
0.8%
449715.700452182 4
 
0.6%
451988.229220642 4
 
0.6%
447374.008518853 4
 
0.6%
448578.828510777 4
 
0.6%
448521.355284197 4
 
0.6%
448353.905156369 4
 
0.6%
447904.856376524 4
 
0.6%
450371.529121582 3
 
0.5%
449052.586544458 3
 
0.5%
Other values (525) 609
91.7%
(Missing) 16
 
2.4%
ValueCountFrequency (%)
447331.904249819 2
0.3%
447374.008518853 4
0.6%
447375.994047199 1
 
0.2%
447434.777242906 2
0.3%
447452.653781347 1
 
0.2%
447456.019020609 1
 
0.2%
447456.62489213 1
 
0.2%
447464.440447288 1
 
0.2%
447472.327838321 1
 
0.2%
447473.715631334 2
0.3%
ValueCountFrequency (%)
452124.250520928 1
0.2%
452093.521893286 1
0.2%
452081.627702376 1
0.2%
452044.630941699 1
0.2%
452040.483594359 1
0.2%
452036.093818641 1
0.2%
452022.249976971 1
0.2%
452011.489289509 1
0.2%
452010.46831334 1
0.2%
451999.598596272 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
일반세탁업
597 
<NA>
 
40
빨래방업
 
16
운동화전문세탁업
 
10
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.9623494
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 597
89.9%
<NA> 40
 
6.0%
빨래방업 16
 
2.4%
운동화전문세탁업 10
 
1.5%
세탁업 기타 1
 
0.2%

Length

2024-05-11T14:37:12.570858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:12.770702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 597
89.8%
na 40
 
6.0%
빨래방업 16
 
2.4%
운동화전문세탁업 10
 
1.5%
세탁업 1
 
0.2%
기타 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.3%
Missing356
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean1.0357143
Minimum0
Maximum12
Zeros203
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-11T14:37:12.944327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6743
Coefficient of variation (CV)1.6165655
Kurtosis5.0234533
Mean1.0357143
Median Absolute Deviation (MAD)0
Skewness1.7915992
Sum319
Variance2.8032806
MonotonicityNot monotonic
2024-05-11T14:37:13.148247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 203
30.6%
4 38
 
5.7%
3 29
 
4.4%
1 18
 
2.7%
2 15
 
2.3%
5 4
 
0.6%
12 1
 
0.2%
(Missing) 356
53.6%
ValueCountFrequency (%)
0 203
30.6%
1 18
 
2.7%
2 15
 
2.3%
3 29
 
4.4%
4 38
 
5.7%
5 4
 
0.6%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
5 4
 
0.6%
4 38
 
5.7%
3 29
 
4.4%
2 15
 
2.3%
1 18
 
2.7%
0 203
30.6%
Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
400 
0
230 
1
 
33
2
 
1

Length

Max length4
Median length4
Mean length2.8072289
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 400
60.2%
0 230
34.6%
1 33
 
5.0%
2 1
 
0.2%

Length

2024-05-11T14:37:13.435083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:13.593197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 400
60.2%
0 230
34.6%
1 33
 
5.0%
2 1
 
0.2%
Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
378 
0
149 
1
128 
2
 
8
3
 
1

Length

Max length4
Median length4
Mean length2.7078313
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 378
56.9%
0 149
 
22.4%
1 128
 
19.3%
2 8
 
1.2%
3 1
 
0.2%

Length

2024-05-11T14:37:13.783531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:13.992018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 378
56.9%
0 149
 
22.4%
1 128
 
19.3%
2 8
 
1.2%
3 1
 
0.2%

사용끝지상층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
541 
1
98 
0
 
19
2
 
6

Length

Max length4
Median length4
Mean length3.4442771
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> 541
81.5%
1 98
 
14.8%
0 19
 
2.9%
2 6
 
0.9%

Length

2024-05-11T14:37:14.224014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:14.406357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 541
81.5%
1 98
 
14.8%
0 19
 
2.9%
2 6
 
0.9%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
499 
0
163 
1
 
2

Length

Max length4
Median length4
Mean length3.2545181
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 499
75.2%
0 163
 
24.5%
1 2
 
0.3%

Length

2024-05-11T14:37:14.607174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:14.777397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 499
75.2%
0 163
 
24.5%
1 2
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
630 
0
 
32
1
 
2

Length

Max length4
Median length4
Mean length3.8463855
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> 630
94.9%
0 32
 
4.8%
1 2
 
0.3%

Length

2024-05-11T14:37:14.953433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:15.160283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 630
94.9%
0 32
 
4.8%
1 2
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
418 
0
246 

Length

Max length4
Median length4
Mean length2.8885542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 418
63.0%
0 246
37.0%

Length

2024-05-11T14:37:15.365692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:15.568377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 418
63.0%
0 246
37.0%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
418 
0
246 

Length

Max length4
Median length4
Mean length2.8885542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 418
63.0%
0 246
37.0%

Length

2024-05-11T14:37:15.778112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:15.944278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 418
63.0%
0 246
37.0%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
418 
0
246 

Length

Max length4
Median length4
Mean length2.8885542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 418
63.0%
0 246
37.0%

Length

2024-05-11T14:37:16.137230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:16.338551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 418
63.0%
0 246
37.0%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing44
Missing (%)6.6%
Memory size1.4 KiB
False
620 
(Missing)
 
44
ValueCountFrequency (%)
False 620
93.4%
(Missing) 44
 
6.6%
2024-05-11T14:37:16.579828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
418 
0
246 

Length

Max length4
Median length4
Mean length2.8885542
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 418
63.0%
0 246
37.0%

Length

2024-05-11T14:37:16.756267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:16.935193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 418
63.0%
0 246
37.0%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing664
Missing (%)100.0%
Memory size6.0 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
632 
임대
 
30
자가
 
2

Length

Max length4
Median length4
Mean length3.9036145
Min length2

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> 632
95.2%
임대 30
 
4.5%
자가 2
 
0.3%

Length

2024-05-11T14:37:17.478104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:17.683806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 632
95.2%
임대 30
 
4.5%
자가 2
 
0.3%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)6.0%
Missing548
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean1.3189655
Minimum0
Maximum8
Zeros40
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-11T14:37:17.847608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4240123
Coefficient of variation (CV)1.0796433
Kurtosis3.3783424
Mean1.3189655
Median Absolute Deviation (MAD)1
Skewness1.4955919
Sum153
Variance2.0278111
MonotonicityNot monotonic
2024-05-11T14:37:18.127130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 40
 
6.0%
1 36
 
5.4%
2 18
 
2.7%
3 13
 
2.0%
4 6
 
0.9%
5 2
 
0.3%
8 1
 
0.2%
(Missing) 548
82.5%
ValueCountFrequency (%)
0 40
6.0%
1 36
5.4%
2 18
2.7%
3 13
 
2.0%
4 6
 
0.9%
5 2
 
0.3%
8 1
 
0.2%
ValueCountFrequency (%)
8 1
 
0.2%
5 2
 
0.3%
4 6
 
0.9%
3 13
 
2.0%
2 18
2.7%
1 36
5.4%
0 40
6.0%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
609 
0
 
48
1
 
7

Length

Max length4
Median length4
Mean length3.751506
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> 609
91.7%
0 48
 
7.2%
1 7
 
1.1%

Length

2024-05-11T14:37:18.377295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:18.577385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 609
91.7%
0 48
 
7.2%
1 7
 
1.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
609 
0
 
36
1
 
18
3
 
1

Length

Max length4
Median length4
Mean length3.751506
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> 609
91.7%
0 36
 
5.4%
1 18
 
2.7%
3 1
 
0.2%

Length

2024-05-11T14:37:18.771743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:18.962998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 609
91.7%
0 36
 
5.4%
1 18
 
2.7%
3 1
 
0.2%

회수건조수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
556 
0
62 
1
 
35
3
 
7
2
 
3

Length

Max length4
Median length4
Mean length3.5120482
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> 556
83.7%
0 62
 
9.3%
1 35
 
5.3%
3 7
 
1.1%
2 3
 
0.5%
4 1
 
0.2%

Length

2024-05-11T14:37:19.157539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:19.334288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 556
83.7%
0 62
 
9.3%
1 35
 
5.3%
3 7
 
1.1%
2 3
 
0.5%
4 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
560 
0
104 

Length

Max length4
Median length4
Mean length3.5301205
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> 560
84.3%
0 104
 
15.7%

Length

2024-05-11T14:37:19.590849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:19.824422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 560
84.3%
0 104
 
15.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing40
Missing (%)6.0%
Memory size1.4 KiB
False
624 
(Missing)
 
40
ValueCountFrequency (%)
False 624
94.0%
(Missing) 40
 
6.0%
2024-05-11T14:37:19.961061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030400003040000-205-1987-0150219870824<NA>3폐업2폐업20181203<NA><NA><NA>02 466246823.40143840서울특별시 광진구 군자동 371-4번지서울특별시 광진구 광나루로17길 14-5 (군자동)5005수도사2018-12-03 11:39:03U2018-12-05 02:40:00.0일반세탁업206360.503935449574.218837일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130400003040000-205-1987-0151219870630<NA>3폐업2폐업20071112<NA><NA><NA>02 444862014.40143806서울특별시 광진구 광장동 272-4번지<NA><NA>백영사2003-03-10 00:00:00I2018-08-31 23:59:59.0일반세탁업209237.010976449506.881867일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230400003040000-205-1987-0151419870630<NA>3폐업2폐업20020527<NA><NA><NA>02 444825020.40143835서울특별시 광진구 구의동 636-5번지<NA><NA>대성사2002-07-15 00:00:00I2018-08-31 23:59:59.0일반세탁업207287.674444449019.590976일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330400003040000-205-1987-0151519870715<NA>3폐업2폐업20060516<NA><NA><NA>02 446068011.70143817서울특별시 광진구 구의동 33-12번지<NA><NA>명문사2002-04-15 00:00:00I2018-08-31 23:59:59.0일반세탁업208296.153607450005.759785일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430400003040000-205-1987-0151619871012<NA>3폐업2폐업20020527<NA><NA><NA>02 447614311.00143816서울특별시 광진구 구의동 30-15번지<NA><NA>보들세탁2002-07-15 00:00:00I2018-08-31 23:59:59.0일반세탁업208158.784704450097.085496일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530400003040000-205-1987-0152319871012<NA>3폐업2폐업20130701<NA><NA><NA>02 452364220.35143960서울특별시 광진구 구의동 226-45번지서울특별시 광진구 자양로32길 84 (구의동)<NA>삼양사2003-03-05 00:00:00I2018-08-31 23:59:59.0일반세탁업207864.339946449076.704774일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630400003040000-205-1987-0152419870630<NA>3폐업2폐업20020527<NA><NA><NA>02 445418817.90143824서울특별시 광진구 구의동 235-1번지<NA><NA>성모사2002-07-15 00:00:00I2018-08-31 23:59:59.0일반세탁업207575.201559449108.377936일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730400003040000-205-1987-0152619870630<NA>1영업/정상1영업<NA><NA><NA><NA>02 446002720.00143962서울특별시 광진구 구의동 231-9서울특별시 광진구 광나루로40길 34, 1층 (구의동)5032대영사2022-12-27 15:26:55U2021-11-01 22:09:00.0일반세탁업207808.781349449012.433555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830400003040000-205-1987-0152719870630<NA>3폐업2폐업20120604<NA><NA><NA>02 452926521.00143962서울특별시 광진구 구의동 229-5번지서울특별시 광진구 구의로 67 (구의동)5032백조사2003-03-10 00:00:00I2018-08-31 23:59:59.0일반세탁업207914.999129449093.469787일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930400003040000-205-1987-0152819870630<NA>3폐업2폐업20020527<NA><NA><NA>02 452589018.52143824서울특별시 광진구 구의동 240-1번지<NA><NA>명성사2002-07-15 00:00:00I2018-08-31 23:59:59.0일반세탁업207771.012934448808.283726일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
65430400003040000-205-2021-0000420210623<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.00143904서울특별시 광진구 중곡동 253-18서울특별시 광진구 동일로66길 13, 1층 (중곡동)4916광진세탁소2021-06-23 11:45:43I2021-06-25 00:22:54.0일반세탁업206647.107035451048.509692일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>10110N
65530400003040000-205-2021-0000520210804<NA>1영업/정상1영업<NA><NA><NA><NA>02 69 52733833.00143852서울특별시 광진구 자양동 219-7서울특별시 광진구 아차산로 358, 202호 (자양동)5055쿨 트레이딩2021-08-04 16:21:14I2021-08-06 00:22:51.0운동화전문세탁업207211.60264448254.436455운동화전문세탁업002200000N0<NA><NA><NA><NA>00300N
65630400003040000-205-2021-0000620210809<NA>1영업/정상1영업<NA><NA><NA><NA>02 468828437.05143839서울특별시 광진구 군자동 103 세종 힐 라움서울특별시 광진구 군자로 108, 세종 힐 라움 1층 108호 (군자동)5004마마운동화이불빨래방2021-08-19 10:58:29U2021-08-21 02:40:00.0운동화전문세탁업206299.750492450037.825731운동화전문세탁업001100000N0<NA><NA><NA><NA>31140N
65730400003040000-205-2021-000072021-12-13<NA>3폐업2폐업2023-12-26<NA><NA><NA><NA>30.00143-909서울특별시 광진구 중곡동 548서울특별시 광진구 답십리로 392-1, 1층 (중곡동)4903서울광진지역자활센터2023-12-26 16:55:58U2022-11-01 22:08:00.0일반세탁업207362.374898452093.521893<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65830400003040000-205-2022-000012022-04-06<NA>3폐업2폐업2023-06-08<NA><NA><NA><NA>15.74143-899서울특별시 광진구 중곡동 162-5서울특별시 광진구 긴고랑로14길 59, 1층 (중곡동)4915그린세탁소2023-06-08 14:24:15U2022-12-05 23:00:00.0일반세탁업207030.481467450857.595472<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65930400003040000-205-2022-0000220220414<NA>1영업/정상1영업<NA><NA><NA><NA>02 447 848233.00143888서울특별시 광진구 중곡동 80-24서울특별시 광진구 자양로43길 149, 1층 (중곡동)4949마마운동화이불빨래방 중곡점2022-04-14 14:50:49I2021-12-03 23:06:00.0운동화전문세탁업207768.461525450541.99611<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66030400003040000-205-2022-0000320220901<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00143819서울특별시 광진구 구의동 71-26서울특별시 광진구 자양로 254, 109호 (구의동)4975마마운동화이불빨래방2022-09-01 15:21:21I2021-12-09 00:03:00.0운동화전문세탁업207854.732905449614.894892<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66130400003040000-205-2023-000012023-01-03<NA>3폐업2폐업2023-09-08<NA><NA><NA>02 455828435.29143-806서울특별시 광진구 광장동 287-5서울특별시 광진구 광장로 66-1 (광장동)4968마마운동화이불빨래방2023-09-08 14:12:13U2022-12-08 23:00:00.0빨래방업209175.614023449457.650549<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66230400003040000-205-2023-000022023-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.00143-827서울특별시 광진구 구의동 254-45서울특별시 광진구 자양로23길 38, 1층 102호 (구의동)5024미소세탁2023-03-23 11:00:44U2022-12-02 22:05:00.0일반세탁업207271.635263448875.134082<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66330400003040000-205-2024-000012024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>117.25143-839서울특별시 광진구 군자동 125-23서울특별시 광진구 동일로 244-1, 2층 (군자동)5001광진 크린업2024-03-05 16:20:36I2023-12-03 00:07:00.0빨래방업206172.562246450127.30404<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>