Overview

Dataset statistics

Number of variables47
Number of observations287
Missing cells2867
Missing cells (%)21.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.4 KiB
Average record size in memory404.5 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric7
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-19296/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
여성종사자수 is highly imbalanced (71.0%)Imbalance
남성종사자수 is highly imbalanced (70.8%)Imbalance
인허가취소일자 has 287 (100.0%) missing valuesMissing
폐업일자 has 65 (22.6%) missing valuesMissing
휴업시작일자 has 287 (100.0%) missing valuesMissing
휴업종료일자 has 287 (100.0%) missing valuesMissing
재개업일자 has 287 (100.0%) missing valuesMissing
전화번호 has 60 (20.9%) missing valuesMissing
도로명주소 has 125 (43.6%) missing valuesMissing
도로명우편번호 has 128 (44.6%) missing valuesMissing
좌표정보(X) has 6 (2.1%) missing valuesMissing
좌표정보(Y) has 6 (2.1%) missing valuesMissing
건물지상층수 has 71 (24.7%) missing valuesMissing
건물지하층수 has 75 (26.1%) missing valuesMissing
사용시작지상층 has 107 (37.3%) missing valuesMissing
사용끝지상층 has 121 (42.2%) missing valuesMissing
발한실여부 has 49 (17.1%) missing valuesMissing
조건부허가신고사유 has 287 (100.0%) missing valuesMissing
조건부허가시작일자 has 287 (100.0%) missing valuesMissing
조건부허가종료일자 has 287 (100.0%) missing valuesMissing
다중이용업소여부 has 43 (15.0%) 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 128 (44.6%) zerosZeros
건물지하층수 has 145 (50.5%) zerosZeros
사용시작지상층 has 67 (23.3%) zerosZeros
사용끝지상층 has 81 (28.2%) zerosZeros

Reproduction

Analysis started2024-05-11 03:01:28.808064
Analysis finished2024-05-11 03:01:30.655316
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3190000
287 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 287
100.0%

Length

2024-05-11T03:01:31.074240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:31.541414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 287
100.0%

관리번호
Text

UNIQUE 

Distinct287
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:01:32.186407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6314
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

Unique287 ?
Unique (%)100.0%

Sample

1st row3190000-206-1987-01922
2nd row3190000-206-1988-01923
3rd row3190000-206-1989-01924
4th row3190000-206-1990-01927
5th row3190000-206-1991-01928
ValueCountFrequency (%)
3190000-206-1987-01922 1
 
0.3%
3190000-206-2012-00003 1
 
0.3%
3190000-206-2011-00005 1
 
0.3%
3190000-206-2011-00004 1
 
0.3%
3190000-206-2011-00003 1
 
0.3%
3190000-206-2011-00002 1
 
0.3%
3190000-206-2011-00001 1
 
0.3%
3190000-206-2010-00015 1
 
0.3%
3190000-206-2010-00013 1
 
0.3%
3190000-206-2010-00005 1
 
0.3%
Other values (277) 277
96.5%
2024-05-11T03:01:33.520743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2736
43.3%
- 861
 
13.6%
2 624
 
9.9%
1 612
 
9.7%
9 497
 
7.9%
3 369
 
5.8%
6 357
 
5.7%
4 79
 
1.3%
5 69
 
1.1%
7 62
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5453
86.4%
Dash Punctuation 861
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2736
50.2%
2 624
 
11.4%
1 612
 
11.2%
9 497
 
9.1%
3 369
 
6.8%
6 357
 
6.5%
4 79
 
1.4%
5 69
 
1.3%
7 62
 
1.1%
8 48
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 861
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2736
43.3%
- 861
 
13.6%
2 624
 
9.9%
1 612
 
9.7%
9 497
 
7.9%
3 369
 
5.8%
6 357
 
5.7%
4 79
 
1.3%
5 69
 
1.1%
7 62
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2736
43.3%
- 861
 
13.6%
2 624
 
9.9%
1 612
 
9.7%
9 497
 
7.9%
3 369
 
5.8%
6 357
 
5.7%
4 79
 
1.3%
5 69
 
1.1%
7 62
 
1.0%
Distinct279
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1987-11-23 00:00:00
Maximum2023-10-20 00:00:00
2024-05-11T03:01:34.098694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:01:34.565633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3
222 
1
65 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 222
77.4%
1 65
 
22.6%

Length

2024-05-11T03:01:34.964480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:35.261561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 222
77.4%
1 65
 
22.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
222 
영업/정상
65 

Length

Max length5
Median length2
Mean length2.6794425
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 222
77.4%
영업/정상 65
 
22.6%

Length

2024-05-11T03:01:35.695608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:36.152816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 222
77.4%
영업/정상 65
 
22.6%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2
222 
1
65 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 222
77.4%
1 65
 
22.6%

Length

2024-05-11T03:01:36.678512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:37.224064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 222
77.4%
1 65
 
22.6%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
222 
영업
65 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 222
77.4%
영업 65
 
22.6%

Length

2024-05-11T03:01:37.649672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:38.003014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 222
77.4%
영업 65
 
22.6%

폐업일자
Date

MISSING 

Distinct198
Distinct (%)89.2%
Missing65
Missing (%)22.6%
Memory size2.4 KiB
Minimum1993-12-18 00:00:00
Maximum2024-02-28 00:00:00
2024-05-11T03:01:38.548175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:01:39.193085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB

전화번호
Text

MISSING 

Distinct207
Distinct (%)91.2%
Missing60
Missing (%)20.9%
Memory size2.4 KiB
2024-05-11T03:01:40.041380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.14978
Min length6

Characters and Unicode

Total characters2304
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

Unique193 ?
Unique (%)85.0%

Sample

1st row02 8231311
2nd row0208241291
3rd row02 8134076
4th row0208480133
5th row02 8227579
ValueCountFrequency (%)
02 156
37.1%
0226029285 6
 
1.4%
0 4
 
1.0%
825 3
 
0.7%
070 3
 
0.7%
599 3
 
0.7%
8364381 2
 
0.5%
8264870 2
 
0.5%
828 2
 
0.5%
823 2
 
0.5%
Other values (224) 238
56.5%
2024-05-11T03:01:41.588478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 409
17.8%
0 352
15.3%
260
11.3%
8 234
10.2%
1 182
7.9%
5 166
7.2%
3 165
7.2%
7 146
 
6.3%
4 143
 
6.2%
9 128
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2044
88.7%
Space Separator 260
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 409
20.0%
0 352
17.2%
8 234
11.4%
1 182
8.9%
5 166
8.1%
3 165
8.1%
7 146
 
7.1%
4 143
 
7.0%
9 128
 
6.3%
6 119
 
5.8%
Space Separator
ValueCountFrequency (%)
260
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 409
17.8%
0 352
15.3%
260
11.3%
8 234
10.2%
1 182
7.9%
5 166
7.2%
3 165
7.2%
7 146
 
6.3%
4 143
 
6.2%
9 128
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 409
17.8%
0 352
15.3%
260
11.3%
8 234
10.2%
1 182
7.9%
5 166
7.2%
3 165
7.2%
7 146
 
6.3%
4 143
 
6.2%
9 128
 
5.6%
Distinct205
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:01:42.524659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.7630662
Min length3

Characters and Unicode

Total characters1367
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

Unique187 ?
Unique (%)65.2%

Sample

1st row0.00
2nd row.00
3rd row.00
4th row.00
5th row.00
ValueCountFrequency (%)
00 51
 
17.8%
33.00 7
 
2.4%
30.00 4
 
1.4%
49.50 4
 
1.4%
60.00 4
 
1.4%
66.00 3
 
1.0%
26.40 3
 
1.0%
23.00 3
 
1.0%
16.00 3
 
1.0%
27.11 2
 
0.7%
Other values (195) 203
70.7%
2024-05-11T03:01:43.910140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 336
24.6%
. 287
21.0%
1 99
 
7.2%
6 98
 
7.2%
2 89
 
6.5%
3 88
 
6.4%
4 85
 
6.2%
5 75
 
5.5%
8 74
 
5.4%
9 66
 
4.8%
Other values (2) 70
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1076
78.7%
Other Punctuation 291
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 336
31.2%
1 99
 
9.2%
6 98
 
9.1%
2 89
 
8.3%
3 88
 
8.2%
4 85
 
7.9%
5 75
 
7.0%
8 74
 
6.9%
9 66
 
6.1%
7 66
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 287
98.6%
, 4
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1367
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 336
24.6%
. 287
21.0%
1 99
 
7.2%
6 98
 
7.2%
2 89
 
6.5%
3 88
 
6.4%
4 85
 
6.2%
5 75
 
5.5%
8 74
 
5.4%
9 66
 
4.8%
Other values (2) 70
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 336
24.6%
. 287
21.0%
1 99
 
7.2%
6 98
 
7.2%
2 89
 
6.5%
3 88
 
6.4%
4 85
 
6.2%
5 75
 
5.5%
8 74
 
5.4%
9 66
 
4.8%
Other values (2) 70
 
5.1%
Distinct77
Distinct (%)26.9%
Missing1
Missing (%)0.3%
Memory size2.4 KiB
2024-05-11T03:01:44.747203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0594406
Min length6

Characters and Unicode

Total characters1733
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

Unique29 ?
Unique (%)10.1%

Sample

1st row156-808
2nd row156030
3rd row156810
4th row156854
5th row156848
ValueCountFrequency (%)
156811 20
 
7.0%
156848 13
 
4.5%
156827 12
 
4.2%
156030 10
 
3.5%
156832 10
 
3.5%
156815 8
 
2.8%
156817 8
 
2.8%
156800 8
 
2.8%
156819 8
 
2.8%
156824 7
 
2.4%
Other values (67) 182
63.6%
2024-05-11T03:01:45.965653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 384
22.2%
5 338
19.5%
6 311
17.9%
8 290
16.7%
0 113
 
6.5%
3 76
 
4.4%
7 62
 
3.6%
2 55
 
3.2%
4 52
 
3.0%
9 35
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1716
99.0%
Dash Punctuation 17
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 384
22.4%
5 338
19.7%
6 311
18.1%
8 290
16.9%
0 113
 
6.6%
3 76
 
4.4%
7 62
 
3.6%
2 55
 
3.2%
4 52
 
3.0%
9 35
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1733
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 384
22.2%
5 338
19.5%
6 311
17.9%
8 290
16.7%
0 113
 
6.5%
3 76
 
4.4%
7 62
 
3.6%
2 55
 
3.2%
4 52
 
3.0%
9 35
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 384
22.2%
5 338
19.5%
6 311
17.9%
8 290
16.7%
0 113
 
6.5%
3 76
 
4.4%
7 62
 
3.6%
2 55
 
3.2%
4 52
 
3.0%
9 35
 
2.0%
Distinct264
Distinct (%)92.3%
Missing1
Missing (%)0.3%
Memory size2.4 KiB
2024-05-11T03:01:46.534799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length24.129371
Min length17

Characters and Unicode

Total characters6901
Distinct characters161
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)87.4%

Sample

1st row서울특별시 동작구 대방동 339-1 솔표빌딩 3층
2nd row서울특별시 동작구 상도동 60-1
3rd row서울특별시 동작구 대방동 385-4 선린빌딩 305호
4th row서울특별시 동작구 신대방동 690-20
5th row서울특별시 동작구 신대방동 361-59
ValueCountFrequency (%)
서울특별시 286
21.3%
동작구 286
21.3%
사당동 91
 
6.8%
상도동 49
 
3.7%
신대방동 49
 
3.7%
대방동 44
 
3.3%
노량진동 30
 
2.2%
3층 16
 
1.2%
1층 13
 
1.0%
흑석동 10
 
0.7%
Other values (339) 466
34.8%
2024-05-11T03:01:47.945529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1287
18.6%
586
 
8.5%
1 293
 
4.2%
290
 
4.2%
289
 
4.2%
288
 
4.2%
288
 
4.2%
288
 
4.2%
286
 
4.1%
286
 
4.1%
Other values (151) 2720
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3773
54.7%
Decimal Number 1505
 
21.8%
Space Separator 1287
 
18.6%
Dash Punctuation 264
 
3.8%
Open Punctuation 28
 
0.4%
Close Punctuation 28
 
0.4%
Uppercase Letter 8
 
0.1%
Other Punctuation 4
 
0.1%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
586
15.5%
290
 
7.7%
289
 
7.7%
288
 
7.6%
288
 
7.6%
288
 
7.6%
286
 
7.6%
286
 
7.6%
105
 
2.8%
95
 
2.5%
Other values (127) 972
25.8%
Decimal Number
ValueCountFrequency (%)
1 293
19.5%
2 234
15.5%
3 230
15.3%
0 141
9.4%
4 139
9.2%
6 122
8.1%
9 104
 
6.9%
7 90
 
6.0%
5 83
 
5.5%
8 69
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
A 3
37.5%
T 1
 
12.5%
K 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
w 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
1287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3773
54.7%
Common 3116
45.2%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
586
15.5%
290
 
7.7%
289
 
7.7%
288
 
7.6%
288
 
7.6%
288
 
7.6%
286
 
7.6%
286
 
7.6%
105
 
2.8%
95
 
2.5%
Other values (127) 972
25.8%
Common
ValueCountFrequency (%)
1287
41.3%
1 293
 
9.4%
- 264
 
8.5%
2 234
 
7.5%
3 230
 
7.4%
0 141
 
4.5%
4 139
 
4.5%
6 122
 
3.9%
9 104
 
3.3%
7 90
 
2.9%
Other values (6) 212
 
6.8%
Latin
ValueCountFrequency (%)
B 3
25.0%
A 3
25.0%
r 1
 
8.3%
e 1
 
8.3%
w 1
 
8.3%
o 1
 
8.3%
T 1
 
8.3%
K 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3773
54.7%
ASCII 3128
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1287
41.1%
1 293
 
9.4%
- 264
 
8.4%
2 234
 
7.5%
3 230
 
7.4%
0 141
 
4.5%
4 139
 
4.4%
6 122
 
3.9%
9 104
 
3.3%
7 90
 
2.9%
Other values (14) 224
 
7.2%
Hangul
ValueCountFrequency (%)
586
15.5%
290
 
7.7%
289
 
7.7%
288
 
7.6%
288
 
7.6%
288
 
7.6%
286
 
7.6%
286
 
7.6%
105
 
2.8%
95
 
2.5%
Other values (127) 972
25.8%

도로명주소
Text

MISSING 

Distinct155
Distinct (%)95.7%
Missing125
Missing (%)43.6%
Memory size2.4 KiB
2024-05-11T03:01:48.592246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length32.740741
Min length22

Characters and Unicode

Total characters5304
Distinct characters169
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)92.6%

Sample

1st row서울특별시 동작구 노량진로 26 (대방동,솔표빌딩 3층)
2nd row서울특별시 동작구 대림로 34 (신대방동)
3rd row서울특별시 동작구 동작대로29가길 30 (사당동, 2층)
4th row서울특별시 동작구 서달로14가길 20, 2층 (흑석동)
5th row서울특별시 동작구 사당로23길 46 (사당동)
ValueCountFrequency (%)
서울특별시 162
 
15.9%
동작구 162
 
15.9%
사당동 42
 
4.1%
신대방동 28
 
2.7%
대방동 23
 
2.3%
상도동 23
 
2.3%
1층 21
 
2.1%
2층 18
 
1.8%
노량진동 17
 
1.7%
3층 14
 
1.4%
Other values (291) 511
50.0%
2024-05-11T03:01:49.906445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
859
 
16.2%
362
 
6.8%
1 191
 
3.6%
) 178
 
3.4%
( 178
 
3.4%
174
 
3.3%
167
 
3.1%
165
 
3.1%
163
 
3.1%
162
 
3.1%
Other values (159) 2705
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3088
58.2%
Space Separator 859
 
16.2%
Decimal Number 809
 
15.3%
Close Punctuation 178
 
3.4%
Open Punctuation 178
 
3.4%
Other Punctuation 155
 
2.9%
Dash Punctuation 20
 
0.4%
Uppercase Letter 11
 
0.2%
Lowercase Letter 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
362
 
11.7%
174
 
5.6%
167
 
5.4%
165
 
5.3%
163
 
5.3%
162
 
5.2%
162
 
5.2%
162
 
5.2%
153
 
5.0%
117
 
3.8%
Other values (134) 1301
42.1%
Decimal Number
ValueCountFrequency (%)
1 191
23.6%
2 159
19.7%
3 89
11.0%
0 87
10.8%
4 77
9.5%
5 53
 
6.6%
6 42
 
5.2%
7 39
 
4.8%
8 37
 
4.6%
9 35
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
w 1
20.0%
r 1
20.0%
a 1
20.0%
o 1
20.0%
e 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
A 4
36.4%
K 1
 
9.1%
T 1
 
9.1%
Space Separator
ValueCountFrequency (%)
859
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Other Punctuation
ValueCountFrequency (%)
, 155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3088
58.2%
Common 2200
41.5%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
362
 
11.7%
174
 
5.6%
167
 
5.4%
165
 
5.3%
163
 
5.3%
162
 
5.2%
162
 
5.2%
162
 
5.2%
153
 
5.0%
117
 
3.8%
Other values (134) 1301
42.1%
Common
ValueCountFrequency (%)
859
39.0%
1 191
 
8.7%
) 178
 
8.1%
( 178
 
8.1%
2 159
 
7.2%
, 155
 
7.0%
3 89
 
4.0%
0 87
 
4.0%
4 77
 
3.5%
5 53
 
2.4%
Other values (6) 174
 
7.9%
Latin
ValueCountFrequency (%)
B 5
31.2%
A 4
25.0%
w 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
K 1
 
6.2%
T 1
 
6.2%
o 1
 
6.2%
e 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3088
58.2%
ASCII 2216
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
859
38.8%
1 191
 
8.6%
) 178
 
8.0%
( 178
 
8.0%
2 159
 
7.2%
, 155
 
7.0%
3 89
 
4.0%
0 87
 
3.9%
4 77
 
3.5%
5 53
 
2.4%
Other values (15) 190
 
8.6%
Hangul
ValueCountFrequency (%)
362
 
11.7%
174
 
5.6%
167
 
5.4%
165
 
5.3%
163
 
5.3%
162
 
5.2%
162
 
5.2%
162
 
5.2%
153
 
5.0%
117
 
3.8%
Other values (134) 1301
42.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)44.7%
Missing128
Missing (%)44.6%
Infinite0
Infinite (%)0.0%
Mean6999.2075
Minimum6900
Maximum7073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:01:50.502385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6900
5-th percentile6912
Q16949.5
median7012
Q37054
95-th percentile7070.1
Maximum7073
Range173
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation53.338669
Coefficient of variation (CV)0.0076206726
Kurtosis-1.2935909
Mean6999.2075
Median Absolute Deviation (MAD)44
Skewness-0.29066291
Sum1112874
Variance2845.0136
MonotonicityNot monotonic
2024-05-11T03:01:51.043409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7055 10
 
3.5%
7056 9
 
3.1%
7071 7
 
2.4%
7005 6
 
2.1%
7030 4
 
1.4%
7013 4
 
1.4%
6900 4
 
1.4%
6954 4
 
1.4%
6938 4
 
1.4%
7023 4
 
1.4%
Other values (61) 103
35.9%
(Missing) 128
44.6%
ValueCountFrequency (%)
6900 4
1.4%
6902 1
 
0.3%
6904 2
0.7%
6912 2
0.7%
6915 1
 
0.3%
6919 1
 
0.3%
6922 1
 
0.3%
6924 2
0.7%
6927 1
 
0.3%
6928 2
0.7%
ValueCountFrequency (%)
7073 1
 
0.3%
7071 7
2.4%
7070 3
1.0%
7069 3
1.0%
7067 2
 
0.7%
7065 1
 
0.3%
7063 1
 
0.3%
7062 1
 
0.3%
7059 1
 
0.3%
7057 1
 
0.3%
Distinct273
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:01:51.836314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.6898955
Min length2

Characters and Unicode

Total characters2207
Distinct characters288
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

Unique263 ?
Unique (%)91.6%

Sample

1st row주식회사 순일기업
2nd row대종개발(주)
3rd row보건기업(주)
4th row오에스개발주식회사
5th row(주)신라한영위생
ValueCountFrequency (%)
주식회사 25
 
7.5%
주)부건안전개발 6
 
1.8%
주)와이즈비젼 2
 
0.6%
나사산업안전(주 2
 
0.6%
주)솔리엔 2
 
0.6%
보건산업공사 2
 
0.6%
삼우안전관리(주 2
 
0.6%
주)하진개발 2
 
0.6%
파워크린 2
 
0.6%
운천개발환경(주 2
 
0.6%
Other values (284) 285
85.8%
2024-05-11T03:01:53.214245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
198
 
9.0%
( 166
 
7.5%
) 166
 
7.5%
76
 
3.4%
52
 
2.4%
50
 
2.3%
45
 
2.0%
45
 
2.0%
35
 
1.6%
33
 
1.5%
Other values (278) 1341
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1807
81.9%
Open Punctuation 166
 
7.5%
Close Punctuation 166
 
7.5%
Space Separator 45
 
2.0%
Uppercase Letter 15
 
0.7%
Other Punctuation 4
 
0.2%
Lowercase Letter 3
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
198
 
11.0%
76
 
4.2%
52
 
2.9%
50
 
2.8%
45
 
2.5%
35
 
1.9%
33
 
1.8%
31
 
1.7%
31
 
1.7%
29
 
1.6%
Other values (261) 1227
67.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
33.3%
S 3
20.0%
N 2
 
13.3%
L 1
 
6.7%
K 1
 
6.7%
M 1
 
6.7%
A 1
 
6.7%
T 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
p 1
33.3%
r 1
33.3%
o 1
33.3%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1807
81.9%
Common 382
 
17.3%
Latin 18
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
198
 
11.0%
76
 
4.2%
52
 
2.9%
50
 
2.8%
45
 
2.5%
35
 
1.9%
33
 
1.8%
31
 
1.7%
31
 
1.7%
29
 
1.6%
Other values (261) 1227
67.9%
Latin
ValueCountFrequency (%)
C 5
27.8%
S 3
16.7%
N 2
 
11.1%
L 1
 
5.6%
K 1
 
5.6%
M 1
 
5.6%
p 1
 
5.6%
r 1
 
5.6%
o 1
 
5.6%
A 1
 
5.6%
Common
ValueCountFrequency (%)
( 166
43.5%
) 166
43.5%
45
 
11.8%
& 3
 
0.8%
4 1
 
0.3%
. 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1807
81.9%
ASCII 400
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
198
 
11.0%
76
 
4.2%
52
 
2.9%
50
 
2.8%
45
 
2.5%
35
 
1.9%
33
 
1.8%
31
 
1.7%
31
 
1.7%
29
 
1.6%
Other values (261) 1227
67.9%
ASCII
ValueCountFrequency (%)
( 166
41.5%
) 166
41.5%
45
 
11.2%
C 5
 
1.2%
S 3
 
0.8%
& 3
 
0.8%
N 2
 
0.5%
L 1
 
0.2%
K 1
 
0.2%
M 1
 
0.2%
Other values (7) 7
 
1.8%
Distinct242
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1999-06-02 00:00:00
Maximum2024-03-26 14:47:17
2024-05-11T03:01:53.798871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:01:54.287405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
I
195 
U
92 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 195
67.9%
U 92
32.1%

Length

2024-05-11T03:01:54.865049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:55.293808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 195
67.9%
u 92
32.1%
Distinct82
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:01:00
2024-05-11T03:01:55.773012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:01:56.643637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
건물위생관리업
287 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 287
100.0%

Length

2024-05-11T03:01:57.148572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:57.403194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 287
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct215
Distinct (%)76.5%
Missing6
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean195202.39
Minimum191585.3
Maximum198336.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:01:57.769391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191585.3
5-th percentile192013.39
Q1193435.22
median194571.15
Q3197458.43
95-th percentile198238
Maximum198336.37
Range6751.069
Interquartile range (IQR)4023.2094

Descriptive statistics

Standard deviation2023.935
Coefficient of variation (CV)0.010368393
Kurtosis-1.345439
Mean195202.39
Median Absolute Deviation (MAD)1414.1134
Skewness0.18824305
Sum54851870
Variance4096312.7
MonotonicityNot monotonic
2024-05-11T03:01:58.213980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197545.985381694 8
 
2.8%
193322.874700908 7
 
2.4%
194146.150470591 6
 
2.1%
193300.832515956 5
 
1.7%
192917.968628959 5
 
1.7%
193639.332709567 5
 
1.7%
196739.152428297 4
 
1.4%
197212.097911311 3
 
1.0%
191902.683054282 3
 
1.0%
197769.222153741 3
 
1.0%
Other values (205) 232
80.8%
(Missing) 6
 
2.1%
ValueCountFrequency (%)
191585.298671366 1
 
0.3%
191726.918169614 1
 
0.3%
191773.113359066 2
0.7%
191787.677056618 1
 
0.3%
191803.524952767 1
 
0.3%
191856.280274493 1
 
0.3%
191902.683054282 3
1.0%
191932.053918973 1
 
0.3%
191964.072033492 1
 
0.3%
191988.034222325 2
0.7%
ValueCountFrequency (%)
198336.367676399 1
0.3%
198328.849512449 1
0.3%
198323.315884585 1
0.3%
198322.130585912 1
0.3%
198315.315293216 1
0.3%
198308.285936457 1
0.3%
198297.499577352 1
0.3%
198284.751826686 1
0.3%
198274.488080944 1
0.3%
198264.305057987 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct215
Distinct (%)76.5%
Missing6
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean443776.36
Minimum441566.95
Maximum445901.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:01:58.645399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441566.95
5-th percentile441774.23
Q1442685.89
median444040.84
Q3444625.09
95-th percentile445632.68
Maximum445901.41
Range4334.4598
Interquartile range (IQR)1939.2028

Descriptive statistics

Standard deviation1197.2513
Coefficient of variation (CV)0.0026978708
Kurtosis-1.1008655
Mean443776.36
Median Absolute Deviation (MAD)1051.8011
Skewness-0.063029136
Sum1.2470116 × 108
Variance1433410.7
MonotonicityNot monotonic
2024-05-11T03:01:59.077161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442685.886949892 8
 
2.8%
444058.673239527 7
 
2.4%
444548.437469433 6
 
2.1%
443302.417672701 5
 
1.7%
444095.390554081 5
 
1.7%
445637.87823237 5
 
1.7%
445284.174739618 4
 
1.4%
441679.709963705 3
 
1.0%
443289.49398995 3
 
1.0%
442294.595260336 3
 
1.0%
Other values (205) 232
80.8%
(Missing) 6
 
2.1%
ValueCountFrequency (%)
441566.953618972 1
 
0.3%
441588.861462309 2
0.7%
441605.468222373 2
0.7%
441622.478200576 1
 
0.3%
441636.913732911 1
 
0.3%
441639.261005501 1
 
0.3%
441671.438697802 1
 
0.3%
441679.709963705 3
1.0%
441722.703838414 2
0.7%
441774.231346897 1
 
0.3%
ValueCountFrequency (%)
445901.413432497 2
 
0.7%
445823.500892497 2
 
0.7%
445820.883711428 1
 
0.3%
445790.549860682 1
 
0.3%
445651.858121299 1
 
0.3%
445649.406187751 1
 
0.3%
445638.69807136 1
 
0.3%
445637.87823237 5
1.7%
445632.68426838 1
 
0.3%
445623.080168564 1
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
건물위생관리업
244 
<NA>
43 

Length

Max length7
Median length7
Mean length6.5505226
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 244
85.0%
<NA> 43
 
15.0%

Length

2024-05-11T03:01:59.498198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:01:59.826117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 244
85.0%
na 43
 
15.0%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.6%
Missing71
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean1.9305556
Minimum0
Maximum27
Zeros128
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:02:00.067182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile6
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.5633524
Coefficient of variation (CV)1.8457653
Kurtosis24.348774
Mean1.9305556
Median Absolute Deviation (MAD)0
Skewness4.1426568
Sum417
Variance12.697481
MonotonicityNot monotonic
2024-05-11T03:02:00.559197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 128
44.6%
4 26
 
9.1%
5 19
 
6.6%
3 14
 
4.9%
2 8
 
2.8%
6 8
 
2.8%
1 7
 
2.4%
27 2
 
0.7%
10 1
 
0.3%
8 1
 
0.3%
Other values (2) 2
 
0.7%
(Missing) 71
24.7%
ValueCountFrequency (%)
0 128
44.6%
1 7
 
2.4%
2 8
 
2.8%
3 14
 
4.9%
4 26
 
9.1%
5 19
 
6.6%
6 8
 
2.8%
8 1
 
0.3%
10 1
 
0.3%
13 1
 
0.3%
ValueCountFrequency (%)
27 2
 
0.7%
20 1
 
0.3%
13 1
 
0.3%
10 1
 
0.3%
8 1
 
0.3%
6 8
 
2.8%
5 19
6.6%
4 26
9.1%
3 14
4.9%
2 8
 
2.8%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.8%
Missing75
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean0.41981132
Minimum0
Maximum6
Zeros145
Zeros (%)50.5%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:02:00.883945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.84773686
Coefficient of variation (CV)2.0193283
Kurtosis17.3339
Mean0.41981132
Median Absolute Deviation (MAD)0
Skewness3.6465747
Sum89
Variance0.71865778
MonotonicityNot monotonic
2024-05-11T03:02:01.215284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 145
50.5%
1 60
20.9%
3 3
 
1.0%
5 2
 
0.7%
4 1
 
0.3%
6 1
 
0.3%
(Missing) 75
26.1%
ValueCountFrequency (%)
0 145
50.5%
1 60
20.9%
3 3
 
1.0%
4 1
 
0.3%
5 2
 
0.7%
6 1
 
0.3%
ValueCountFrequency (%)
6 1
 
0.3%
5 2
 
0.7%
4 1
 
0.3%
3 3
 
1.0%
1 60
20.9%
0 145
50.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)6.7%
Missing107
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean2.0722222
Minimum0
Maximum24
Zeros67
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:02:01.524898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6.05
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9559722
Coefficient of variation (CV)1.4264745
Kurtosis20.962661
Mean2.0722222
Median Absolute Deviation (MAD)1
Skewness3.6938394
Sum373
Variance8.7377716
MonotonicityNot monotonic
2024-05-11T03:02:01.904276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 67
23.3%
2 28
 
9.8%
1 26
 
9.1%
3 25
 
8.7%
4 15
 
5.2%
5 7
 
2.4%
6 3
 
1.0%
7 3
 
1.0%
11 2
 
0.7%
9 2
 
0.7%
Other values (2) 2
 
0.7%
(Missing) 107
37.3%
ValueCountFrequency (%)
0 67
23.3%
1 26
 
9.1%
2 28
9.8%
3 25
 
8.7%
4 15
 
5.2%
5 7
 
2.4%
6 3
 
1.0%
7 3
 
1.0%
9 2
 
0.7%
11 2
 
0.7%
ValueCountFrequency (%)
24 1
 
0.3%
18 1
 
0.3%
11 2
 
0.7%
9 2
 
0.7%
7 3
 
1.0%
6 3
 
1.0%
5 7
 
2.4%
4 15
5.2%
3 25
8.7%
2 28
9.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.6%
Missing121
Missing (%)42.2%
Infinite0
Infinite (%)0.0%
Mean1.6144578
Minimum0
Maximum18
Zeros81
Zeros (%)28.2%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:02:02.244316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4187717
Coefficient of variation (CV)1.4981944
Kurtosis13.496878
Mean1.6144578
Median Absolute Deviation (MAD)1
Skewness2.8819664
Sum268
Variance5.8504564
MonotonicityNot monotonic
2024-05-11T03:02:02.626157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 81
28.2%
1 21
 
7.3%
2 20
 
7.0%
3 17
 
5.9%
4 12
 
4.2%
5 7
 
2.4%
6 2
 
0.7%
7 2
 
0.7%
9 2
 
0.7%
11 1
 
0.3%
(Missing) 121
42.2%
ValueCountFrequency (%)
0 81
28.2%
1 21
 
7.3%
2 20
 
7.0%
3 17
 
5.9%
4 12
 
4.2%
5 7
 
2.4%
6 2
 
0.7%
7 2
 
0.7%
9 2
 
0.7%
11 1
 
0.3%
ValueCountFrequency (%)
18 1
 
0.3%
11 1
 
0.3%
9 2
 
0.7%
7 2
 
0.7%
6 2
 
0.7%
5 7
 
2.4%
4 12
4.2%
3 17
5.9%
2 20
7.0%
1 21
7.3%
Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
192 
0
82 
1
 
12
3
 
1

Length

Max length4
Median length4
Mean length3.0069686
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 192
66.9%
0 82
28.6%
1 12
 
4.2%
3 1
 
0.3%

Length

2024-05-11T03:02:03.316714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:03.861025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 192
66.9%
0 82
28.6%
1 12
 
4.2%
3 1
 
0.3%
Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
192 
0
84 
1
 
10
4
 
1

Length

Max length4
Median length4
Mean length3.0069686
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 192
66.9%
0 84
29.3%
1 10
 
3.5%
4 1
 
0.3%

Length

2024-05-11T03:02:04.460790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:04.825995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 192
66.9%
0 84
29.3%
1 10
 
3.5%
4 1
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
163 
<NA>
124 

Length

Max length4
Median length1
Mean length2.2961672
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 163
56.8%
<NA> 124
43.2%

Length

2024-05-11T03:02:05.333861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:05.719861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 163
56.8%
na 124
43.2%

양실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
163 
<NA>
124 

Length

Max length4
Median length1
Mean length2.2961672
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 163
56.8%
<NA> 124
43.2%

Length

2024-05-11T03:02:06.115629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:06.531476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 163
56.8%
na 124
43.2%

욕실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
163 
<NA>
124 

Length

Max length4
Median length1
Mean length2.2961672
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 163
56.8%
<NA> 124
43.2%

Length

2024-05-11T03:02:06.892171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:07.246989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 163
56.8%
na 124
43.2%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing49
Missing (%)17.1%
Memory size706.0 B
False
238 
(Missing)
49 
ValueCountFrequency (%)
False 238
82.9%
(Missing) 49
 
17.1%
2024-05-11T03:02:07.647345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
163 
<NA>
122 
8
 
1
3
 
1

Length

Max length4
Median length1
Mean length2.2752613
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 163
56.8%
<NA> 122
42.5%
8 1
 
0.3%
3 1
 
0.3%

Length

2024-05-11T03:02:08.307652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:08.813999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 163
56.8%
na 122
42.5%
8 1
 
0.3%
3 1
 
0.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing287
Missing (%)100.0%
Memory size2.7 KiB
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
199 
임대
87 
자가
 
1

Length

Max length4
Median length4
Mean length3.3867596
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
69.3%
임대 87
30.3%
자가 1
 
0.3%

Length

2024-05-11T03:02:09.520317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:09.866598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 199
69.3%
임대 87
30.3%
자가 1
 
0.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
170 
0
117 

Length

Max length4
Median length4
Mean length2.7770035
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> 170
59.2%
0 117
40.8%

Length

2024-05-11T03:02:10.440523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:10.939477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 170
59.2%
0 117
40.8%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
250 
0
30 
1
 
5
7
 
1
8
 
1

Length

Max length4
Median length4
Mean length3.6132404
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 250
87.1%
0 30
 
10.5%
1 5
 
1.7%
7 1
 
0.3%
8 1
 
0.3%

Length

2024-05-11T03:02:11.476085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:12.016981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 250
87.1%
0 30
 
10.5%
1 5
 
1.7%
7 1
 
0.3%
8 1
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
249 
0
25 
1
 
8
2
 
3
6
 
1

Length

Max length4
Median length4
Mean length3.6027875
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
86.8%
0 25
 
8.7%
1 8
 
2.8%
2 3
 
1.0%
6 1
 
0.3%
3 1
 
0.3%

Length

2024-05-11T03:02:12.565572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:13.023473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
86.8%
0 25
 
8.7%
1 8
 
2.8%
2 3
 
1.0%
6 1
 
0.3%
3 1
 
0.3%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
187 
0
100 

Length

Max length4
Median length4
Mean length2.9547038
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> 187
65.2%
0 100
34.8%

Length

2024-05-11T03:02:13.476736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:13.861920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 187
65.2%
0 100
34.8%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
194 
0
93 

Length

Max length4
Median length4
Mean length3.0278746
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> 194
67.6%
0 93
32.4%

Length

2024-05-11T03:02:14.365011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:02:14.740805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
67.6%
0 93
32.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing43
Missing (%)15.0%
Memory size706.0 B
False
244 
(Missing)
43 
ValueCountFrequency (%)
False 244
85.0%
(Missing) 43
 
15.0%
2024-05-11T03:02:15.197286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031900003190000-206-1987-019221987-11-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 82313110.00156-808서울특별시 동작구 대방동 339-1 솔표빌딩 3층서울특별시 동작구 노량진로 26 (대방동,솔표빌딩 3층)6938주식회사 순일기업2023-04-13 13:42:51U2022-12-03 23:05:00.0건물위생관리업193639.33271445637.878232<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131900003190000-206-1988-0192319881130<NA>3폐업2폐업20111115<NA><NA><NA>0208241291.00156030서울특별시 동작구 상도동 60-1<NA><NA>대종개발(주)2005-01-04 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
231900003190000-206-1989-0192419890225<NA>3폐업2폐업20030213<NA><NA><NA>02 8134076.00156810서울특별시 동작구 대방동 385-4 선린빌딩 305호<NA><NA>보건기업(주)2003-02-13 00:00:00I2018-08-31 23:59:59.0건물위생관리업193098.896109444721.943187건물위생관리업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331900003190000-206-1990-0192719900829<NA>1영업/정상1영업<NA><NA><NA><NA>0208480133.00156854서울특별시 동작구 신대방동 690-20서울특별시 동작구 대림로 34 (신대방동)7070오에스개발주식회사2022-10-25 13:44:53U2021-10-30 22:07:00.0건물위생관리업191932.053919442799.937388<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431900003190000-206-1991-0192819910808<NA>3폐업2폐업19950327<NA><NA><NA>02 8227579.00156848서울특별시 동작구 신대방동 361-59<NA><NA>(주)신라한영위생2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업193269.829685443948.499895건물위생관리업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531900003190000-206-1992-0192919920128<NA>3폐업2폐업20020321<NA><NA><NA>02 824424270.50156847서울특별시 동작구 신대방동 344-16<NA><NA>대동시설관리(주)2002-03-21 00:00:00I2018-08-31 23:59:59.0건물위생관리업193532.600275443907.905571건물위생관리업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631900003190000-206-1992-0193019920718<NA>3폐업2폐업20100401<NA><NA><NA>02 5250662.00156879서울특별시 동작구 사당동 206-122<NA><NA>다이음(주)2007-07-25 09:24:11I2018-08-31 23:59:59.0건물위생관리업197021.859465442766.971205건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731900003190000-206-1992-0193119921109<NA>3폐업2폐업20050214<NA><NA><NA>02 8143878.00156856서울특별시 동작구 흑석동 1-3 원불교서울회관 201호<NA><NA>홍익에이디넷(주)2004-12-07 00:00:00I2018-08-31 23:59:59.0건물위생관리업196739.152428445284.17474건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831900003190000-206-1993-0192519930313<NA>3폐업2폐업19950417<NA><NA><NA>02 8214844.00156848서울특별시 동작구 신대방동 362-23<NA><NA>한조청수산업2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업193263.623858444030.62372건물위생관리업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931900003190000-206-1993-0192619930313<NA>3폐업2폐업19940608<NA><NA><NA>0208254204.00156856서울특별시 동작구 흑석동 1-3<NA><NA>청녹환경2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업196739.152428445284.17474건물위생관리업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
27731900003190000-206-2022-0000320220831<NA>1영업/정상1영업<NA><NA><NA><NA>02 846966849.00156736서울특별시 동작구 신대방동 395-73 캐릭터 그린빌서울특별시 동작구 보라매로5가길 7, 505호 (신대방동, 캐릭터 그린빌)7071에스앤관리2022-09-04 12:46:53U2021-12-09 00:06:00.0건물위생관리업193300.832516443302.417673<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27831900003190000-206-2022-000042022-09-14<NA>1영업/정상1영업<NA><NA><NA><NA>023477906932.40156-840서울특별시 동작구 상도동 197-2서울특별시 동작구 성대로37길 73, 1층 (상도동)6961에스오산업 주식회사2023-11-15 13:46:47U2022-10-31 23:07:00.0건물위생관리업194415.385302444379.606365<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27931900003190000-206-2022-000052022-11-18<NA>3폐업2폐업2024-02-28<NA><NA><NA>02 8270927136.36156-832서울특별시 동작구 상도동 360-6 송정빌딩서울특별시 동작구 상도로15길 103, 송정빌딩 2층 (상도동)6949해가온건설(주)2024-02-28 13:01:44U2023-12-03 00:01:00.0건물위생관리업194302.669553444709.829804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28031900003190000-206-2022-0000620221124<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.80156825서울특별시 동작구 사당동 1027-5서울특별시 동작구 동작대로9가길 28, 3층 (사당동)7015주식회사 지디관리2022-11-24 11:54:22I2021-10-31 22:06:00.0건물위생관리업198013.083713441943.397056<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28131900003190000-206-2022-0000720221222<NA>1영업/정상1영업<NA><NA><NA><NA><NA>92.00156811서울특별시 동작구 대방동 397-16서울특별시 동작구 대방동1길 39, 301동 (대방동)6955전국기초생활 수급자 복지중앙회2022-12-22 15:51:28I2021-11-01 22:04:00.0건물위생관리업193157.038949444233.112601<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28231900003190000-206-2023-000012023-01-31<NA>3폐업2폐업2023-12-22<NA><NA><NA><NA>26.40156-883서울특별시 동작구 사당동 232-17서울특별시 동작구 사당로10길 20, 1층 우측호 (사당동)7009엠케이(MK)랜드2023-12-22 13:38:51U2022-11-01 22:04:00.0건물위생관리업197207.736379442466.190057<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28331900003190000-206-2023-000022023-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00156-090서울특별시 동작구 사당동 1150 사당삼익그린뷰아파트서울특별시 동작구 남부순환로255길 21, 상가동 지101호 (사당동, 사당삼익그린뷰아파트)7021청소코리아2023-04-18 16:20:41I2022-12-03 22:00:00.0건물위생관리업197212.097911441679.709964<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28431900003190000-206-2023-000032023-06-15<NA>1영업/정상1영업<NA><NA><NA><NA>023280770820.69156-805서울특별시 동작구 노량진동 292-1서울특별시 동작구 노량진로6길 82, 2층 (노량진동)6934도깨비소독방역2023-11-17 14:28:47U2022-10-31 23:09:00.0건물위생관리업194348.725325445270.766181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28531900003190000-206-2023-000042023-07-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>75.00156-810서울특별시 동작구 대방동 389-23 시저스타운서울특별시 동작구 여의대방로 182-1, 시저스타운 3층 (대방동)6945(주)정든종합관리2023-07-10 15:08:01I2022-12-06 23:03:00.0건물위생관리업193026.63188444552.339772<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28631900003190000-206-2023-000052023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.28156-030서울특별시 동작구 상도동 535 상도2차두산위브트레지움아파트서울특별시 동작구 상도로30길 40, 제2종근린생활시설동 2층 214호 (상도동, 상도2차두산위브트레지움아파트)6964한빛기술2023-12-20 08:41:04U2022-11-01 22:03:00.0건물위생관리업194870.384384444631.112679<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>