Overview

Dataset statistics

Number of variables47
Number of observations476
Missing cells5610
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory187.9 KiB
Average record size in memory404.3 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
Numeric8
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-19292/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (97.8%)Imbalance
사용시작지하층 is highly imbalanced (53.6%)Imbalance
사용끝지하층 is highly imbalanced (55.2%)Imbalance
여성종사자수 is highly imbalanced (63.0%)Imbalance
인허가취소일자 has 476 (100.0%) missing valuesMissing
폐업일자 has 201 (42.2%) missing valuesMissing
휴업시작일자 has 476 (100.0%) missing valuesMissing
휴업종료일자 has 476 (100.0%) missing valuesMissing
재개업일자 has 476 (100.0%) missing valuesMissing
전화번호 has 87 (18.3%) missing valuesMissing
도로명주소 has 89 (18.7%) missing valuesMissing
도로명우편번호 has 91 (19.1%) missing valuesMissing
좌표정보(X) has 50 (10.5%) missing valuesMissing
좌표정보(Y) has 50 (10.5%) missing valuesMissing
건물지상층수 has 211 (44.3%) missing valuesMissing
건물지하층수 has 236 (49.6%) missing valuesMissing
사용시작지상층 has 258 (54.2%) missing valuesMissing
사용끝지상층 has 344 (72.3%) missing valuesMissing
발한실여부 has 156 (32.8%) missing valuesMissing
조건부허가신고사유 has 476 (100.0%) missing valuesMissing
조건부허가시작일자 has 476 (100.0%) missing valuesMissing
조건부허가종료일자 has 476 (100.0%) missing valuesMissing
남성종사자수 has 357 (75.0%) missing valuesMissing
다중이용업소여부 has 146 (30.7%) 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 133 (27.9%) zerosZeros
건물지하층수 has 168 (35.3%) zerosZeros
사용시작지상층 has 28 (5.9%) zerosZeros
사용끝지상층 has 37 (7.8%) zerosZeros
남성종사자수 has 79 (16.6%) zerosZeros

Reproduction

Analysis started2024-05-11 05:40:37.026990
Analysis finished2024-05-11 05:40:38.380833
Duration1.35 second
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
3150000
476 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 476
100.0%

Length

2024-05-11T14:40:38.477226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:38.620428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 476
100.0%

관리번호
Text

UNIQUE 

Distinct476
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T14:40:38.831330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10472
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

Unique476 ?
Unique (%)100.0%

Sample

1st row3150000-206-1993-00001
2nd row3150000-206-1995-00001
3rd row3150000-206-1995-00002
4th row3150000-206-1996-00001
5th row3150000-206-1998-01688
ValueCountFrequency (%)
3150000-206-1993-00001 1
 
0.2%
3150000-206-2017-00003 1
 
0.2%
3150000-206-2017-00015 1
 
0.2%
3150000-206-2017-00014 1
 
0.2%
3150000-206-2017-00013 1
 
0.2%
3150000-206-2017-00012 1
 
0.2%
3150000-206-2017-00011 1
 
0.2%
3150000-206-2017-00010 1
 
0.2%
3150000-206-2017-00009 1
 
0.2%
3150000-206-2017-00008 1
 
0.2%
Other values (466) 466
97.9%
2024-05-11T14:40:39.236157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4738
45.2%
- 1428
 
13.6%
2 1196
 
11.4%
1 1014
 
9.7%
3 600
 
5.7%
6 571
 
5.5%
5 558
 
5.3%
9 113
 
1.1%
7 87
 
0.8%
4 85
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9044
86.4%
Dash Punctuation 1428
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4738
52.4%
2 1196
 
13.2%
1 1014
 
11.2%
3 600
 
6.6%
6 571
 
6.3%
5 558
 
6.2%
9 113
 
1.2%
7 87
 
1.0%
4 85
 
0.9%
8 82
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1428
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10472
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4738
45.2%
- 1428
 
13.6%
2 1196
 
11.4%
1 1014
 
9.7%
3 600
 
5.7%
6 571
 
5.5%
5 558
 
5.3%
9 113
 
1.1%
7 87
 
0.8%
4 85
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4738
45.2%
- 1428
 
13.6%
2 1196
 
11.4%
1 1014
 
9.7%
3 600
 
5.7%
6 571
 
5.5%
5 558
 
5.3%
9 113
 
1.1%
7 87
 
0.8%
4 85
 
0.8%
Distinct444
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1993-12-08 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T14:40:39.458170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:39.647411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
275 
1
201 

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 (%)
3 275
57.8%
1 201
42.2%

Length

2024-05-11T14:40:39.799321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:39.943038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 275
57.8%
1 201
42.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
275 
영업/정상
201 

Length

Max length5
Median length2
Mean length3.2668067
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 275
57.8%
영업/정상 201
42.2%

Length

2024-05-11T14:40:40.057943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:40.205988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 275
57.8%
영업/정상 201
42.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
275 
1
201 

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 (%)
2 275
57.8%
1 201
42.2%

Length

2024-05-11T14:40:40.361662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:40.525985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 275
57.8%
1 201
42.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
275 
영업
201 

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 275
57.8%
영업 201
42.2%

Length

2024-05-11T14:40:40.677237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:40.835517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 275
57.8%
영업 201
42.2%

폐업일자
Date

MISSING 

Distinct250
Distinct (%)90.9%
Missing201
Missing (%)42.2%
Memory size3.8 KiB
Minimum2001-08-02 00:00:00
Maximum2024-04-19 00:00:00
2024-05-11T14:40:41.004191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:41.207461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB

전화번호
Text

MISSING 

Distinct372
Distinct (%)95.6%
Missing87
Missing (%)18.3%
Memory size3.8 KiB
2024-05-11T14:40:41.511106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.239075
Min length2

Characters and Unicode

Total characters3983
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

Unique355 ?
Unique (%)91.3%

Sample

1st row02 6950777
2nd row02 36648804
3rd row0226624857
4th row0236640088
5th row02 6535121
ValueCountFrequency (%)
02 76
 
15.4%
031 5
 
1.0%
070 4
 
0.8%
0269591855 2
 
0.4%
0267372728 2
 
0.4%
0226592814 2
 
0.4%
0226660872 2
 
0.4%
0236650891 2
 
0.4%
07074435900 2
 
0.4%
0226580052 2
 
0.4%
Other values (382) 394
79.9%
2024-05-11T14:40:42.018378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 768
19.3%
0 684
17.2%
6 601
15.1%
3 326
8.2%
5 288
 
7.2%
8 254
 
6.4%
1 250
 
6.3%
7 239
 
6.0%
4 227
 
5.7%
9 199
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3836
96.3%
Space Separator 147
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 768
20.0%
0 684
17.8%
6 601
15.7%
3 326
8.5%
5 288
 
7.5%
8 254
 
6.6%
1 250
 
6.5%
7 239
 
6.2%
4 227
 
5.9%
9 199
 
5.2%
Space Separator
ValueCountFrequency (%)
147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3983
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 768
19.3%
0 684
17.2%
6 601
15.1%
3 326
8.2%
5 288
 
7.2%
8 254
 
6.4%
1 250
 
6.3%
7 239
 
6.0%
4 227
 
5.7%
9 199
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 768
19.3%
0 684
17.2%
6 601
15.1%
3 326
8.2%
5 288
 
7.2%
8 254
 
6.4%
1 250
 
6.3%
7 239
 
6.0%
4 227
 
5.7%
9 199
 
5.0%
Distinct351
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T14:40:42.725907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0861345
Min length3

Characters and Unicode

Total characters2421
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

Unique299 ?
Unique (%)62.8%

Sample

1st row89.38
2nd row82.80
3rd row32.20
4th row80.45
5th row96.22
ValueCountFrequency (%)
33.00 13
 
2.7%
66.00 13
 
2.7%
3.30 10
 
2.1%
00 8
 
1.7%
30.00 7
 
1.5%
25.00 6
 
1.3%
99.00 6
 
1.3%
24.00 5
 
1.1%
23.10 5
 
1.1%
40.00 4
 
0.8%
Other values (341) 399
83.8%
2024-05-11T14:40:43.527535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 479
19.8%
. 476
19.7%
3 222
9.2%
2 193
8.0%
6 187
 
7.7%
1 182
 
7.5%
4 175
 
7.2%
5 153
 
6.3%
8 140
 
5.8%
9 121
 
5.0%
Other values (2) 93
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1943
80.3%
Other Punctuation 478
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 479
24.7%
3 222
11.4%
2 193
9.9%
6 187
 
9.6%
1 182
 
9.4%
4 175
 
9.0%
5 153
 
7.9%
8 140
 
7.2%
9 121
 
6.2%
7 91
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 476
99.6%
, 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 2421
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 479
19.8%
. 476
19.7%
3 222
9.2%
2 193
8.0%
6 187
 
7.7%
1 182
 
7.5%
4 175
 
7.2%
5 153
 
6.3%
8 140
 
5.8%
9 121
 
5.0%
Other values (2) 93
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 479
19.8%
. 476
19.7%
3 222
9.2%
2 193
8.0%
6 187
 
7.7%
1 182
 
7.5%
4 175
 
7.2%
5 153
 
6.3%
8 140
 
5.8%
9 121
 
5.0%
Other values (2) 93
 
3.8%
Distinct120
Distinct (%)25.3%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-05-11T14:40:43.898020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1894737
Min length6

Characters and Unicode

Total characters2940
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

Unique57 ?
Unique (%)12.0%

Sample

1st row157872
2nd row157846
3rd row157-210
4th row157280
5th row157836
ValueCountFrequency (%)
157210 78
 
16.4%
157930 40
 
8.4%
157-210 34
 
7.2%
157853 22
 
4.6%
157812 11
 
2.3%
157840 11
 
2.3%
157851 10
 
2.1%
157850 9
 
1.9%
157847 8
 
1.7%
157925 8
 
1.7%
Other values (110) 244
51.4%
2024-05-11T14:40:44.446861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 670
22.8%
5 558
19.0%
7 531
18.1%
8 292
9.9%
0 249
 
8.5%
2 196
 
6.7%
9 121
 
4.1%
3 111
 
3.8%
- 90
 
3.1%
4 66
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2850
96.9%
Dash Punctuation 90
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 670
23.5%
5 558
19.6%
7 531
18.6%
8 292
10.2%
0 249
 
8.7%
2 196
 
6.9%
9 121
 
4.2%
3 111
 
3.9%
4 66
 
2.3%
6 56
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 670
22.8%
5 558
19.0%
7 531
18.1%
8 292
9.9%
0 249
 
8.5%
2 196
 
6.7%
9 121
 
4.1%
3 111
 
3.8%
- 90
 
3.1%
4 66
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 670
22.8%
5 558
19.0%
7 531
18.1%
8 292
9.9%
0 249
 
8.5%
2 196
 
6.7%
9 121
 
4.1%
3 111
 
3.8%
- 90
 
3.1%
4 66
 
2.2%
Distinct453
Distinct (%)95.4%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-05-11T14:40:44.757754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length38
Mean length27.842105
Min length17

Characters and Unicode

Total characters13225
Distinct characters248
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)91.6%

Sample

1st row서울특별시 강서구 화곡동 105-72
2nd row서울특별시 강서구 방화동 247-109
3rd row서울특별시 강서구 마곡동 757-3 마곡나루역보타닉비즈타워
4th row서울특별시 강서구 내발산동 656 게이트웨이 2층
5th row서울특별시 강서구 등촌동 512-7
ValueCountFrequency (%)
서울특별시 475
18.3%
강서구 475
18.3%
마곡동 112
 
4.3%
화곡동 99
 
3.8%
방화동 94
 
3.6%
등촌동 82
 
3.2%
2층 28
 
1.1%
공항동 27
 
1.0%
3층 26
 
1.0%
1층 24
 
0.9%
Other values (733) 1152
44.4%
2024-05-11T14:40:45.215518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2341
 
17.7%
960
 
7.3%
523
 
4.0%
1 513
 
3.9%
483
 
3.7%
479
 
3.6%
477
 
3.6%
476
 
3.6%
475
 
3.6%
475
 
3.6%
Other values (238) 6023
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7372
55.7%
Decimal Number 2941
 
22.2%
Space Separator 2341
 
17.7%
Dash Punctuation 414
 
3.1%
Close Punctuation 41
 
0.3%
Open Punctuation 41
 
0.3%
Uppercase Letter 39
 
0.3%
Letter Number 20
 
0.2%
Other Punctuation 9
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
960
 
13.0%
523
 
7.1%
483
 
6.6%
479
 
6.5%
477
 
6.5%
476
 
6.5%
475
 
6.4%
475
 
6.4%
243
 
3.3%
225
 
3.1%
Other values (203) 2556
34.7%
Uppercase Letter
ValueCountFrequency (%)
B 10
25.6%
A 7
17.9%
W 5
12.8%
M 4
 
10.3%
P 2
 
5.1%
I 2
 
5.1%
O 2
 
5.1%
V 2
 
5.1%
C 1
 
2.6%
T 1
 
2.6%
Other values (3) 3
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 513
17.4%
0 344
11.7%
2 334
11.4%
7 323
11.0%
6 272
9.2%
4 260
8.8%
5 237
8.1%
3 233
7.9%
8 221
7.5%
9 204
 
6.9%
Letter Number
ValueCountFrequency (%)
13
65.0%
5
 
25.0%
1
 
5.0%
1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Space Separator
ValueCountFrequency (%)
2341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 414
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7372
55.7%
Common 5793
43.8%
Latin 60
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
960
 
13.0%
523
 
7.1%
483
 
6.6%
479
 
6.5%
477
 
6.5%
476
 
6.5%
475
 
6.4%
475
 
6.4%
243
 
3.3%
225
 
3.1%
Other values (203) 2556
34.7%
Latin
ValueCountFrequency (%)
13
21.7%
B 10
16.7%
A 7
11.7%
W 5
 
8.3%
5
 
8.3%
M 4
 
6.7%
P 2
 
3.3%
I 2
 
3.3%
O 2
 
3.3%
V 2
 
3.3%
Other values (8) 8
13.3%
Common
ValueCountFrequency (%)
2341
40.4%
1 513
 
8.9%
- 414
 
7.1%
0 344
 
5.9%
2 334
 
5.8%
7 323
 
5.6%
6 272
 
4.7%
4 260
 
4.5%
5 237
 
4.1%
3 233
 
4.0%
Other values (7) 522
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7372
55.7%
ASCII 5833
44.1%
Number Forms 20
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2341
40.1%
1 513
 
8.8%
- 414
 
7.1%
0 344
 
5.9%
2 334
 
5.7%
7 323
 
5.5%
6 272
 
4.7%
4 260
 
4.5%
5 237
 
4.1%
3 233
 
4.0%
Other values (21) 562
 
9.6%
Hangul
ValueCountFrequency (%)
960
 
13.0%
523
 
7.1%
483
 
6.6%
479
 
6.5%
477
 
6.5%
476
 
6.5%
475
 
6.4%
475
 
6.4%
243
 
3.3%
225
 
3.1%
Other values (203) 2556
34.7%
Number Forms
ValueCountFrequency (%)
13
65.0%
5
 
25.0%
1
 
5.0%
1
 
5.0%

도로명주소
Text

MISSING 

Distinct377
Distinct (%)97.4%
Missing89
Missing (%)18.7%
Memory size3.8 KiB
2024-05-11T14:40:45.503725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length46
Mean length37.155039
Min length22

Characters and Unicode

Total characters14379
Distinct characters263
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique367 ?
Unique (%)94.8%

Sample

1st row서울특별시 강서구 초원로 83 (방화동)
2nd row서울특별시 강서구 마곡중앙5로1길 20, 마곡나루역보타닉비즈타워 1118호 (마곡동)
3rd row서울특별시 강서구 공항대로 375, 3층 (등촌동)
4th row서울특별시 강서구 양천로 716 (염창동,신한빌딩 301호)
5th row서울특별시 강서구 하늘길 210 (공항동, 화물청사 202-3)
ValueCountFrequency (%)
서울특별시 387
 
14.3%
강서구 387
 
14.3%
마곡동 109
 
4.0%
화곡동 64
 
2.4%
공항대로 61
 
2.2%
등촌동 58
 
2.1%
방화동 55
 
2.0%
1층 35
 
1.3%
2층 34
 
1.3%
강서로 32
 
1.2%
Other values (760) 1493
55.0%
2024-05-11T14:40:46.012023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2328
 
16.2%
844
 
5.9%
1 527
 
3.7%
473
 
3.3%
, 457
 
3.2%
445
 
3.1%
) 407
 
2.8%
( 407
 
2.8%
392
 
2.7%
389
 
2.7%
Other values (253) 7710
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8129
56.5%
Decimal Number 2512
 
17.5%
Space Separator 2328
 
16.2%
Other Punctuation 457
 
3.2%
Close Punctuation 407
 
2.8%
Open Punctuation 407
 
2.8%
Dash Punctuation 65
 
0.5%
Uppercase Letter 44
 
0.3%
Letter Number 20
 
0.1%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
844
 
10.4%
473
 
5.8%
445
 
5.5%
392
 
4.8%
389
 
4.8%
388
 
4.8%
388
 
4.8%
387
 
4.8%
387
 
4.8%
315
 
3.9%
Other values (219) 3721
45.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
27.3%
A 9
20.5%
M 5
11.4%
W 5
11.4%
O 2
 
4.5%
P 2
 
4.5%
V 2
 
4.5%
I 2
 
4.5%
T 1
 
2.3%
E 1
 
2.3%
Other values (3) 3
 
6.8%
Decimal Number
ValueCountFrequency (%)
1 527
21.0%
2 369
14.7%
0 311
12.4%
3 237
9.4%
5 236
9.4%
4 229
9.1%
6 207
 
8.2%
8 162
 
6.4%
7 132
 
5.3%
9 102
 
4.1%
Letter Number
ValueCountFrequency (%)
13
65.0%
5
 
25.0%
1
 
5.0%
1
 
5.0%
Space Separator
ValueCountFrequency (%)
2328
100.0%
Other Punctuation
ValueCountFrequency (%)
, 457
100.0%
Close Punctuation
ValueCountFrequency (%)
) 407
100.0%
Open Punctuation
ValueCountFrequency (%)
( 407
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8129
56.5%
Common 6185
43.0%
Latin 65
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
844
 
10.4%
473
 
5.8%
445
 
5.5%
392
 
4.8%
389
 
4.8%
388
 
4.8%
388
 
4.8%
387
 
4.8%
387
 
4.8%
315
 
3.9%
Other values (219) 3721
45.8%
Latin
ValueCountFrequency (%)
13
20.0%
B 12
18.5%
A 9
13.8%
5
 
7.7%
M 5
 
7.7%
W 5
 
7.7%
O 2
 
3.1%
P 2
 
3.1%
V 2
 
3.1%
I 2
 
3.1%
Other values (8) 8
12.3%
Common
ValueCountFrequency (%)
2328
37.6%
1 527
 
8.5%
, 457
 
7.4%
) 407
 
6.6%
( 407
 
6.6%
2 369
 
6.0%
0 311
 
5.0%
3 237
 
3.8%
5 236
 
3.8%
4 229
 
3.7%
Other values (6) 677
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8129
56.5%
ASCII 6230
43.3%
Number Forms 20
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2328
37.4%
1 527
 
8.5%
, 457
 
7.3%
) 407
 
6.5%
( 407
 
6.5%
2 369
 
5.9%
0 311
 
5.0%
3 237
 
3.8%
5 236
 
3.8%
4 229
 
3.7%
Other values (20) 722
 
11.6%
Hangul
ValueCountFrequency (%)
844
 
10.4%
473
 
5.8%
445
 
5.5%
392
 
4.8%
389
 
4.8%
388
 
4.8%
388
 
4.8%
387
 
4.8%
387
 
4.8%
315
 
3.9%
Other values (219) 3721
45.8%
Number Forms
ValueCountFrequency (%)
13
65.0%
5
 
25.0%
1
 
5.0%
1
 
5.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct136
Distinct (%)35.3%
Missing91
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean7663.8468
Minimum7503
Maximum7807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:46.174071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7503
5-th percentile7512
Q17587
median7638
Q37788
95-th percentile7806
Maximum7807
Range304
Interquartile range (IQR)201

Descriptive statistics

Standard deviation100.93407
Coefficient of variation (CV)0.013170158
Kurtosis-1.3834206
Mean7663.8468
Median Absolute Deviation (MAD)80
Skewness0.15202385
Sum2950581
Variance10187.687
MonotonicityNot monotonic
2024-05-11T14:40:46.340258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7788 26
 
5.5%
7803 21
 
4.4%
7802 14
 
2.9%
7806 12
 
2.5%
7631 10
 
2.1%
7807 9
 
1.9%
7591 9
 
1.9%
7604 8
 
1.7%
7587 8
 
1.7%
7620 8
 
1.7%
Other values (126) 260
54.6%
(Missing) 91
 
19.1%
ValueCountFrequency (%)
7503 3
0.6%
7504 2
 
0.4%
7505 2
 
0.4%
7509 3
0.6%
7510 5
1.1%
7511 4
0.8%
7512 2
 
0.4%
7517 1
 
0.2%
7518 1
 
0.2%
7519 2
 
0.4%
ValueCountFrequency (%)
7807 9
 
1.9%
7806 12
2.5%
7805 3
 
0.6%
7803 21
4.4%
7802 14
2.9%
7801 4
 
0.8%
7798 4
 
0.8%
7792 2
 
0.4%
7789 2
 
0.4%
7788 26
5.5%
Distinct466
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T14:40:46.586365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.1953782
Min length3

Characters and Unicode

Total characters3901
Distinct characters360
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

Unique456 ?
Unique (%)95.8%

Sample

1st row(주)중앙에코텍
2nd row대아환경(주)
3rd row(주)에이치에스에스공영
4th row문창기업(주)
5th row경인기공
ValueCountFrequency (%)
주식회사 77
 
13.0%
4
 
0.7%
크린 3
 
0.5%
수씨엔에스 2
 
0.3%
주)송원이앤씨 2
 
0.3%
지오크린 2
 
0.3%
토탈크린 2
 
0.3%
사단법인 2
 
0.3%
토우코리아 2
 
0.3%
클린 2
 
0.3%
Other values (488) 495
83.5%
2024-05-11T14:40:46.991013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
349
 
8.9%
( 261
 
6.7%
) 261
 
6.7%
138
 
3.5%
127
 
3.3%
117
 
3.0%
114
 
2.9%
113
 
2.9%
99
 
2.5%
89
 
2.3%
Other values (350) 2233
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3200
82.0%
Open Punctuation 261
 
6.7%
Close Punctuation 261
 
6.7%
Space Separator 117
 
3.0%
Uppercase Letter 39
 
1.0%
Decimal Number 12
 
0.3%
Other Punctuation 7
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
349
 
10.9%
138
 
4.3%
127
 
4.0%
114
 
3.6%
113
 
3.5%
99
 
3.1%
89
 
2.8%
59
 
1.8%
52
 
1.6%
52
 
1.6%
Other values (322) 2008
62.7%
Uppercase Letter
ValueCountFrequency (%)
K 5
12.8%
C 5
12.8%
N 4
10.3%
S 4
10.3%
D 3
7.7%
B 3
7.7%
E 2
 
5.1%
O 2
 
5.1%
P 2
 
5.1%
G 2
 
5.1%
Other values (6) 7
17.9%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 2
 
16.7%
9 2
 
16.7%
0 1
 
8.3%
6 1
 
8.3%
4 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
& 2
 
28.6%
Open Punctuation
ValueCountFrequency (%)
( 261
100.0%
Close Punctuation
ValueCountFrequency (%)
) 261
100.0%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3200
82.0%
Common 662
 
17.0%
Latin 39
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
349
 
10.9%
138
 
4.3%
127
 
4.0%
114
 
3.6%
113
 
3.5%
99
 
3.1%
89
 
2.8%
59
 
1.8%
52
 
1.6%
52
 
1.6%
Other values (322) 2008
62.7%
Latin
ValueCountFrequency (%)
K 5
12.8%
C 5
12.8%
N 4
10.3%
S 4
10.3%
D 3
7.7%
B 3
7.7%
E 2
 
5.1%
O 2
 
5.1%
P 2
 
5.1%
G 2
 
5.1%
Other values (6) 7
17.9%
Common
ValueCountFrequency (%)
( 261
39.4%
) 261
39.4%
117
17.7%
1 5
 
0.8%
. 5
 
0.8%
- 4
 
0.6%
& 2
 
0.3%
2 2
 
0.3%
9 2
 
0.3%
0 1
 
0.2%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3200
82.0%
ASCII 701
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
349
 
10.9%
138
 
4.3%
127
 
4.0%
114
 
3.6%
113
 
3.5%
99
 
3.1%
89
 
2.8%
59
 
1.8%
52
 
1.6%
52
 
1.6%
Other values (322) 2008
62.7%
ASCII
ValueCountFrequency (%)
( 261
37.2%
) 261
37.2%
117
16.7%
K 5
 
0.7%
C 5
 
0.7%
1 5
 
0.7%
. 5
 
0.7%
N 4
 
0.6%
S 4
 
0.6%
- 4
 
0.6%
Other values (18) 30
 
4.3%
Distinct452
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2001-08-06 00:00:00
Maximum2024-05-03 16:51:32
2024-05-11T14:40:47.151245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:47.358984image/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
274 
U
202 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 274
57.6%
U 202
42.4%

Length

2024-05-11T14:40:47.515584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:47.674728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 274
57.6%
u 202
42.4%
Distinct214
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T14:40:47.789841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:47.956262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
건물위생관리업
475 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0063025
Min length7

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 475
99.8%
건물위생관리업 기타 1
 
0.2%

Length

2024-05-11T14:40:48.087621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:48.175349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 476
99.8%
기타 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct321
Distinct (%)75.4%
Missing50
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean185344.3
Minimum182141.21
Maximum189102.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:48.286412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile182914.77
Q1183585.77
median185600.72
Q3186476.32
95-th percentile187917.44
Maximum189102.28
Range6961.0721
Interquartile range (IQR)2890.5453

Descriptive statistics

Standard deviation1681.478
Coefficient of variation (CV)0.0090721857
Kurtosis-0.93944208
Mean185344.3
Median Absolute Deviation (MAD)1261.3434
Skewness0.053035056
Sum78956674
Variance2827368.1
MonotonicityNot monotonic
2024-05-11T14:40:48.445003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186378.231818091 7
 
1.5%
187052.323132425 5
 
1.1%
185642.667278438 5
 
1.1%
187999.32555627 4
 
0.8%
184655.264279055 4
 
0.8%
185660.0 4
 
0.8%
184498.0 4
 
0.8%
182914.770762913 4
 
0.8%
183382.861571856 4
 
0.8%
183315.556652953 4
 
0.8%
Other values (311) 381
80.0%
(Missing) 50
 
10.5%
ValueCountFrequency (%)
182141.205465089 1
 
0.2%
182154.410343287 1
 
0.2%
182157.843375714 1
 
0.2%
182243.855587728 1
 
0.2%
182297.683890108 1
 
0.2%
182456.194080179 1
 
0.2%
182478.394935408 1
 
0.2%
182742.537963411 2
0.4%
182801.931637762 3
0.6%
182853.820302804 1
 
0.2%
ValueCountFrequency (%)
189102.277524848 1
0.2%
189058.62791549 1
0.2%
188998.678607376 1
0.2%
188991.037609055 1
0.2%
188954.187154407 1
0.2%
188953.293071222 1
0.2%
188944.612624413 1
0.2%
188918.130854419 1
0.2%
188883.085593065 1
0.2%
188843.428976776 2
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct321
Distinct (%)75.4%
Missing50
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean450662.72
Minimum447353.95
Maximum453520.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:48.876670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447353.95
5-th percentile447974.55
Q1449946.32
median450839.76
Q3451649.07
95-th percentile452713.51
Maximum453520.89
Range6166.9403
Interquartile range (IQR)1702.7482

Descriptive statistics

Standard deviation1339.0775
Coefficient of variation (CV)0.002971352
Kurtosis-0.12874568
Mean450662.72
Median Absolute Deviation (MAD)848.42954
Skewness-0.55561797
Sum1.9198232 × 108
Variance1793128.7
MonotonicityNot monotonic
2024-05-11T14:40:49.058402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450937.877207072 7
 
1.5%
450291.97922408 5
 
1.1%
450883.006755308 5
 
1.1%
449920.361168751 4
 
0.8%
451864.298152252 4
 
0.8%
450884.0 4
 
0.8%
451786.0 4
 
0.8%
451105.609040835 4
 
0.8%
452713.505241493 4
 
0.8%
452204.165533971 4
 
0.8%
Other values (311) 381
80.0%
(Missing) 50
 
10.5%
ValueCountFrequency (%)
447353.94960188 1
0.2%
447419.255013569 1
0.2%
447473.079874062 1
0.2%
447473.568819772 1
0.2%
447497.183033891 1
0.2%
447514.56416265 1
0.2%
447533.777125216 1
0.2%
447545.877972964 1
0.2%
447549.922621908 1
0.2%
447588.385038404 1
0.2%
ValueCountFrequency (%)
453520.889900319 1
 
0.2%
453468.096258454 1
 
0.2%
453178.305694113 3
0.6%
453171.703673371 1
 
0.2%
453082.089785426 1
 
0.2%
453071.208897794 1
 
0.2%
452956.60414556 1
 
0.2%
452922.98039021 1
 
0.2%
452906.521290095 2
0.4%
452867.511201654 3
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
건물위생관리업
330 
<NA>
146 

Length

Max length7
Median length7
Mean length6.0798319
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 330
69.3%
<NA> 146
30.7%

Length

2024-05-11T14:40:49.239774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:49.338218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 330
69.3%
na 146
30.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)6.8%
Missing211
Missing (%)44.3%
Infinite0
Infinite (%)0.0%
Mean2.5886792
Minimum0
Maximum30
Zeros133
Zeros (%)27.9%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:49.429068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile10
Maximum30
Range30
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.7900218
Coefficient of variation (CV)1.4640755
Kurtosis11.182353
Mean2.5886792
Median Absolute Deviation (MAD)0
Skewness2.5830787
Sum686
Variance14.364265
MonotonicityNot monotonic
2024-05-11T14:40:49.571612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 133
27.9%
3 32
 
6.7%
4 27
 
5.7%
5 16
 
3.4%
2 14
 
2.9%
7 9
 
1.9%
10 8
 
1.7%
1 6
 
1.3%
6 6
 
1.3%
12 3
 
0.6%
Other values (8) 11
 
2.3%
(Missing) 211
44.3%
ValueCountFrequency (%)
0 133
27.9%
1 6
 
1.3%
2 14
 
2.9%
3 32
 
6.7%
4 27
 
5.7%
5 16
 
3.4%
6 6
 
1.3%
7 9
 
1.9%
8 2
 
0.4%
9 1
 
0.2%
ValueCountFrequency (%)
30 1
 
0.2%
16 1
 
0.2%
15 2
 
0.4%
14 2
 
0.4%
13 1
 
0.2%
12 3
 
0.6%
11 1
 
0.2%
10 8
1.7%
9 1
 
0.2%
8 2
 
0.4%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.9%
Missing236
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.45
Minimum0
Maximum6
Zeros168
Zeros (%)35.3%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:49.691500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9315484
Coefficient of variation (CV)2.0701076
Kurtosis12.70023
Mean0.45
Median Absolute Deviation (MAD)0
Skewness3.247194
Sum108
Variance0.86778243
MonotonicityNot monotonic
2024-05-11T14:40:49.819344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 168
35.3%
1 57
 
12.0%
2 5
 
1.1%
3 4
 
0.8%
5 3
 
0.6%
4 2
 
0.4%
6 1
 
0.2%
(Missing) 236
49.6%
ValueCountFrequency (%)
0 168
35.3%
1 57
 
12.0%
2 5
 
1.1%
3 4
 
0.8%
4 2
 
0.4%
5 3
 
0.6%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 3
 
0.6%
4 2
 
0.4%
3 4
 
0.8%
2 5
 
1.1%
1 57
 
12.0%
0 168
35.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)6.4%
Missing258
Missing (%)54.2%
Infinite0
Infinite (%)0.0%
Mean2.9724771
Minimum0
Maximum15
Zeros28
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:49.983403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile9
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.8590828
Coefficient of variation (CV)0.96185191
Kurtosis2.453258
Mean2.9724771
Median Absolute Deviation (MAD)1
Skewness1.5563081
Sum648
Variance8.1743542
MonotonicityNot monotonic
2024-05-11T14:40:50.095450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 54
 
11.3%
2 45
 
9.5%
0 28
 
5.9%
3 26
 
5.5%
4 18
 
3.8%
6 12
 
2.5%
5 10
 
2.1%
8 6
 
1.3%
9 6
 
1.3%
7 5
 
1.1%
Other values (4) 8
 
1.7%
(Missing) 258
54.2%
ValueCountFrequency (%)
0 28
5.9%
1 54
11.3%
2 45
9.5%
3 26
5.5%
4 18
 
3.8%
5 10
 
2.1%
6 12
 
2.5%
7 5
 
1.1%
8 6
 
1.3%
9 6
 
1.3%
ValueCountFrequency (%)
15 1
 
0.2%
13 2
 
0.4%
11 4
 
0.8%
10 1
 
0.2%
9 6
 
1.3%
8 6
 
1.3%
7 5
 
1.1%
6 12
2.5%
5 10
2.1%
4 18
3.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)19.7%
Missing344
Missing (%)72.3%
Infinite0
Infinite (%)0.0%
Mean28.962121
Minimum0
Maximum614
Zeros37
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:50.245016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile209.7
Maximum614
Range614
Interquartile range (IQR)5

Descriptive statistics

Standard deviation94.829007
Coefficient of variation (CV)3.2742425
Kurtosis18.045001
Mean28.962121
Median Absolute Deviation (MAD)2
Skewness4.1231954
Sum3823
Variance8992.5405
MonotonicityNot monotonic
2024-05-11T14:40:50.423671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 37
 
7.8%
1 21
 
4.4%
2 19
 
4.0%
3 10
 
2.1%
4 8
 
1.7%
5 7
 
1.5%
6 5
 
1.1%
8 4
 
0.8%
9 3
 
0.6%
7 2
 
0.4%
Other values (16) 16
 
3.4%
(Missing) 344
72.3%
ValueCountFrequency (%)
0 37
7.8%
1 21
4.4%
2 19
4.0%
3 10
 
2.1%
4 8
 
1.7%
5 7
 
1.5%
6 5
 
1.1%
7 2
 
0.4%
8 4
 
0.8%
9 3
 
0.6%
ValueCountFrequency (%)
614 1
0.2%
508 1
0.2%
403 1
0.2%
334 1
0.2%
307 1
0.2%
302 1
0.2%
213 1
0.2%
207 1
0.2%
203 1
0.2%
202 1
0.2%

사용시작지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
374 
0
79 
1
 
22
4
 
1

Length

Max length4
Median length4
Mean length3.3571429
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 374
78.6%
0 79
 
16.6%
1 22
 
4.6%
4 1
 
0.2%

Length

2024-05-11T14:40:50.577479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:50.759081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 374
78.6%
0 79
 
16.6%
1 22
 
4.6%
4 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
396 
0
75 
1
 
5

Length

Max length4
Median length4
Mean length3.4957983
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> 396
83.2%
0 75
 
15.8%
1 5
 
1.1%

Length

2024-05-11T14:40:50.899121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:51.027425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 396
83.2%
0 75
 
15.8%
1 5
 
1.1%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
244 
0
232 

Length

Max length4
Median length4
Mean length2.5378151
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 244
51.3%
0 232
48.7%

Length

2024-05-11T14:40:51.157464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:51.299400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 244
51.3%
0 232
48.7%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
244 
0
232 

Length

Max length4
Median length4
Mean length2.5378151
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 244
51.3%
0 232
48.7%

Length

2024-05-11T14:40:51.445878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:51.565385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 244
51.3%
0 232
48.7%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
244 
0
232 

Length

Max length4
Median length4
Mean length2.5378151
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 244
51.3%
0 232
48.7%

Length

2024-05-11T14:40:51.696581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:51.851603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 244
51.3%
0 232
48.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing156
Missing (%)32.8%
Memory size1.1 KiB
False
320 
(Missing)
156 
ValueCountFrequency (%)
False 320
67.2%
(Missing) 156
32.8%
2024-05-11T14:40:51.975508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
244 
0
232 

Length

Max length4
Median length4
Mean length2.5378151
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 244
51.3%
0 232
48.7%

Length

2024-05-11T14:40:52.166731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:52.306509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 244
51.3%
0 232
48.7%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing476
Missing (%)100.0%
Memory size4.3 KiB
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
301 
임대
167 
자가
 
8

Length

Max length4
Median length4
Mean length3.2647059
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> 301
63.2%
임대 167
35.1%
자가 8
 
1.7%

Length

2024-05-11T14:40:52.473886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:52.656614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 301
63.2%
임대 167
35.1%
자가 8
 
1.7%

세탁기수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
250 
0
226 

Length

Max length4
Median length4
Mean length2.5756303
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> 250
52.5%
0 226
47.5%

Length

2024-05-11T14:40:52.804349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:52.938290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 250
52.5%
0 226
47.5%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
357 
0
108 
1
 
7
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.2521008
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 357
75.0%
0 108
 
22.7%
1 7
 
1.5%
2 2
 
0.4%
3 1
 
0.2%
25 1
 
0.2%

Length

2024-05-11T14:40:53.131191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:53.323272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 357
75.0%
0 108
 
22.7%
1 7
 
1.5%
2 2
 
0.4%
3 1
 
0.2%
25 1
 
0.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)8.4%
Missing357
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean4.1428571
Minimum0
Maximum400
Zeros79
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T14:40:53.475461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4.1
Maximum400
Range400
Interquartile range (IQR)1

Descriptive statistics

Standard deviation36.653736
Coefficient of variation (CV)8.8474535
Kurtosis118.2287
Mean4.1428571
Median Absolute Deviation (MAD)0
Skewness10.856967
Sum493
Variance1343.4964
MonotonicityNot monotonic
2024-05-11T14:40:53.647466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 79
 
16.6%
1 26
 
5.5%
3 5
 
1.1%
2 2
 
0.4%
5 2
 
0.4%
400 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
(Missing) 357
75.0%
ValueCountFrequency (%)
0 79
16.6%
1 26
 
5.5%
2 2
 
0.4%
3 5
 
1.1%
4 1
 
0.2%
5 2
 
0.4%
6 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
400 1
 
0.2%
ValueCountFrequency (%)
400 1
 
0.2%
15 1
 
0.2%
13 1
 
0.2%
6 1
 
0.2%
5 2
 
0.4%
4 1
 
0.2%
3 5
 
1.1%
2 2
 
0.4%
1 26
 
5.5%
0 79
16.6%

회수건조수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
273 
0
203 

Length

Max length4
Median length4
Mean length2.7205882
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> 273
57.4%
0 203
42.6%

Length

2024-05-11T14:40:53.829903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:53.964036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 273
57.4%
0 203
42.6%

침대수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
278 
0
198 

Length

Max length4
Median length4
Mean length2.7521008
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> 278
58.4%
0 198
41.6%

Length

2024-05-11T14:40:54.143821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:54.314201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 278
58.4%
0 198
41.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing146
Missing (%)30.7%
Memory size1.1 KiB
False
330 
(Missing)
146 
ValueCountFrequency (%)
False 330
69.3%
(Missing) 146
30.7%
2024-05-11T14:40:54.443709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031500003150000-206-1993-0000119931208<NA>3폐업2폐업20011112<NA><NA><NA>02 695077789.38157872서울특별시 강서구 화곡동 105-72<NA><NA>(주)중앙에코텍2002-06-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업186033.023786448859.526341건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131500003150000-206-1995-0000119950512<NA>3폐업2폐업20150226<NA><NA><NA>02 3664880482.80157846서울특별시 강서구 방화동 247-109서울특별시 강서구 초원로 83 (방화동)7606대아환경(주)2014-09-25 13:43:32I2018-08-31 23:59:59.0건물위생관리업183567.474425451733.143807건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231500003150000-206-1995-000021995-04-29<NA>1영업/정상1영업<NA><NA><NA><NA>022662485732.20157-210서울특별시 강서구 마곡동 757-3 마곡나루역보타닉비즈타워서울특별시 강서구 마곡중앙5로1길 20, 마곡나루역보타닉비즈타워 1118호 (마곡동)7788(주)에이치에스에스공영2023-10-13 14:43:03U2022-10-30 23:05:00.0건물위생관리업184622.249503451831.21854<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331500003150000-206-1996-0000119960325<NA>3폐업2폐업20030218<NA><NA><NA>023664008880.45157280서울특별시 강서구 내발산동 656 게이트웨이 2층<NA><NA>문창기업(주)2003-02-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431500003150000-206-1998-0168819980223<NA>3폐업2폐업20010802<NA><NA><NA>02 653512196.22157836서울특별시 강서구 등촌동 512-7<NA><NA>경인기공2001-08-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업187747.587175449268.71092건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531500003150000-206-1998-0168919980223<NA>3폐업2폐업20010802<NA><NA><NA>0256.68157884서울특별시 강서구 화곡동 379-100<NA><NA>준성개발2001-08-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업185603.433204448447.475782건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631500003150000-206-1998-0169019980629<NA>3폐업2폐업20190704<NA><NA><NA>0227017223128.40157930서울특별시 강서구 등촌동 660-7 3층서울특별시 강서구 공항대로 375, 3층 (등촌동)7590미성엠프로주식회사2019-07-04 14:56:38U2019-07-06 02:40:00.0건물위생관리업186645.455747450557.881899건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731500003150000-206-1999-0169019990222<NA>3폐업2폐업20010802<NA><NA><NA>0226021276.00157918서울특별시 강서구 화곡동 1006-13<NA><NA>늘푸른환경2001-08-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업185410.679548449443.817067건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831500003150000-206-1999-0169219990224<NA>3폐업2폐업20010920<NA><NA><NA>023664502261.66157864서울특별시 강서구 염창동 283-11 덕신빌딩 3층<NA><NA>(주)남기개발2002-06-19 00:00:00I2018-08-31 23:59:59.0건물위생관리업189058.627915449482.632252건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931500003150000-206-1999-0169319990623<NA>3폐업2폐업20090806<NA><NA><NA>0236653356100.17157864서울특별시 강서구 염창동 282-19 (3층)<NA><NA>태평산업(주)2003-06-16 00:00:00I2018-08-31 23:59:59.0건물위생관리업188953.293071449482.995275건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
46631500003150000-206-2023-000192023-12-28<NA>1영업/정상1영업<NA><NA><NA><NA>02769 103061.60157-210서울특별시 강서구 마곡동 797-7 퀸즈파크텐서울특별시 강서구 마곡중앙6로 66, 퀸즈파크텐 512호 (마곡동)7803(사)행복일자리운동본부2023-12-28 15:19:19I2022-11-01 21:00:00.0건물위생관리업185292.766644450863.026924<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46731500003150000-206-2023-000202023-12-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.47157-930서울특별시 강서구 등촌동 698-1 세신등촌종합상가서울특별시 강서구 공항대로41길 66, 세신등촌종합상가 지하1층 제비 146호 (등촌동)7587크린테라피2023-12-28 15:53:13I2022-11-01 21:00:00.0건물위생관리업186378.231818450937.877207<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46831500003150000-206-2023-000212023-12-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>132.16157-850서울특별시 강서구 방화동 563-45 문화빌딩서울특별시 강서구 양천로14길 13-5, 문화빌딩 2층 (방화동)7603(주)그레이트 석세스 인터내셔널2023-12-29 17:34:34I2022-11-01 21:01:00.0건물위생관리업183185.596835452269.704362<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46931500003150000-206-2024-000012024-01-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.94157-210서울특별시 강서구 마곡동 800-15 이너매스마곡Ⅱ서울특별시 강서구 마곡중앙2로 35, 이너매스마곡Ⅱ 327호 (마곡동)7806오비스 크린2024-01-11 15:42:34I2023-11-30 23:03:00.0건물위생관리업184971.5227450643.056387<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47031500003150000-206-2024-000022024-02-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00157-893서울특별시 강서구 화곡동 463-27 1층우측호서울특별시 강서구 곰달래로49길 95, 1층 우측호 (화곡동)7744참조은2024-02-22 16:00:09I2023-12-01 22:05:00.0건물위생관리업187154.291363448137.713778<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47131500003150000-206-2024-000032024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.17157-210서울특별시 강서구 마곡동 759-1 두산더랜드타워서울특별시 강서구 마곡서로 152, 두산더랜드타워 오비동 10층 1015호 (마곡동)7788휴비스 주식회사2024-02-27 15:44:29I2023-12-01 22:09:00.0건물위생관리업184526.084368451722.650631<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47231500003150000-206-2024-000042024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>022088298032.37157-210서울특별시 강서구 마곡동 757 두산더랜드파크 제오씨동 513호서울특별시 강서구 마곡중앙로 161-8, 두산더랜드파크 제오씨동 5층 513호 (마곡동)7788다원파트너스 주식회사2024-03-04 14:50:32I2023-12-03 00:06:00.0건물위생관리업184655.264279451864.298152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47331500003150000-206-2024-000052024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA>02608522545.00157-871서울특별시 강서구 화곡동 100-16 대영빌라트 201호서울특별시 강서구 초록마을로6길 52, 2층 201호 (화곡동, 대영빌라트)7722주식회사 대경티엠2024-03-12 15:16:48I2023-12-02 23:04:00.0건물위생관리업186297.149057448750.374241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47431500003150000-206-2024-000062024-03-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>58.02157-210서울특별시 강서구 마곡동 797 에이스타워 마곡 810호서울특별시 강서구 공항대로 237, 에이스타워 마곡 8층 810호 (마곡동)7803강건비엠에스 주식회사2024-03-20 11:42:46I2023-12-02 22:02:00.0건물위생관리업185253.478151450811.037606<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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