Overview

Dataset statistics

Number of variables47
Number of observations301
Missing cells3287
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.9 KiB
Average record size in memory404.4 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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-19280/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (96.8%)Imbalance
위생업태명 is highly imbalanced (53.0%)Imbalance
사용끝지하층 is highly imbalanced (50.2%)Imbalance
여성종사자수 is highly imbalanced (56.6%)Imbalance
다중이용업소여부 is highly imbalanced (96.1%)Imbalance
인허가취소일자 has 301 (100.0%) missing valuesMissing
폐업일자 has 97 (32.2%) missing valuesMissing
휴업시작일자 has 301 (100.0%) missing valuesMissing
휴업종료일자 has 301 (100.0%) missing valuesMissing
재개업일자 has 301 (100.0%) missing valuesMissing
전화번호 has 111 (36.9%) missing valuesMissing
도로명주소 has 91 (30.2%) missing valuesMissing
도로명우편번호 has 96 (31.9%) missing valuesMissing
좌표정보(X) has 5 (1.7%) missing valuesMissing
좌표정보(Y) has 5 (1.7%) missing valuesMissing
건물지상층수 has 99 (32.9%) missing valuesMissing
사용시작지상층 has 143 (47.5%) missing valuesMissing
사용끝지상층 has 171 (56.8%) missing valuesMissing
발한실여부 has 70 (23.3%) missing valuesMissing
조건부허가신고사유 has 301 (100.0%) missing valuesMissing
조건부허가시작일자 has 301 (100.0%) missing valuesMissing
조건부허가종료일자 has 301 (100.0%) missing valuesMissing
남성종사자수 has 232 (77.1%) missing valuesMissing
다중이용업소여부 has 59 (19.6%) 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 125 (41.5%) zerosZeros
사용시작지상층 has 41 (13.6%) zerosZeros
사용끝지상층 has 27 (9.0%) zerosZeros
남성종사자수 has 60 (19.9%) zerosZeros

Reproduction

Analysis started2024-05-11 05:54:37.005557
Analysis finished2024-05-11 05:54:37.969680
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
3030000
301 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 301
100.0%

Length

2024-05-11T14:54:38.035271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:38.444159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 301
100.0%

관리번호
Text

UNIQUE 

Distinct301
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:38.684836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6622
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

Unique301 ?
Unique (%)100.0%

Sample

1st row3030000-206-1991-01871
2nd row3030000-206-1992-01875
3rd row3030000-206-1993-01876
4th row3030000-206-1993-01877
5th row3030000-206-1993-01878
ValueCountFrequency (%)
3030000-206-1991-01871 1
 
0.3%
3030000-206-2013-00009 1
 
0.3%
3030000-206-2014-00010 1
 
0.3%
3030000-206-2014-00009 1
 
0.3%
3030000-206-2014-00008 1
 
0.3%
3030000-206-2014-00007 1
 
0.3%
3030000-206-2014-00006 1
 
0.3%
3030000-206-2014-00005 1
 
0.3%
3030000-206-2014-00004 1
 
0.3%
3030000-206-2014-00003 1
 
0.3%
Other values (291) 291
96.7%
2024-05-11T14:54:39.191061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3213
48.5%
- 903
 
13.6%
3 671
 
10.1%
2 667
 
10.1%
6 370
 
5.6%
1 344
 
5.2%
9 148
 
2.2%
8 105
 
1.6%
4 75
 
1.1%
7 69
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5719
86.4%
Dash Punctuation 903
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3213
56.2%
3 671
 
11.7%
2 667
 
11.7%
6 370
 
6.5%
1 344
 
6.0%
9 148
 
2.6%
8 105
 
1.8%
4 75
 
1.3%
7 69
 
1.2%
5 57
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 903
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6622
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3213
48.5%
- 903
 
13.6%
3 671
 
10.1%
2 667
 
10.1%
6 370
 
5.6%
1 344
 
5.2%
9 148
 
2.2%
8 105
 
1.6%
4 75
 
1.1%
7 69
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3213
48.5%
- 903
 
13.6%
3 671
 
10.1%
2 667
 
10.1%
6 370
 
5.6%
1 344
 
5.2%
9 148
 
2.2%
8 105
 
1.6%
4 75
 
1.1%
7 69
 
1.0%
Distinct281
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum1991-01-21 00:00:00
Maximum2024-03-07 00:00:00
2024-05-11T14:54:39.399346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:39.604170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
3
204 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 204
67.8%
1 97
32.2%

Length

2024-05-11T14:54:39.808947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:39.982958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 204
67.8%
1 97
32.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
폐업
204 
영업/정상
97 

Length

Max length5
Median length2
Mean length2.9667774
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 204
67.8%
영업/정상 97
32.2%

Length

2024-05-11T14:54:40.165098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:40.330596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 204
67.8%
영업/정상 97
32.2%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2
204 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 204
67.8%
1 97
32.2%

Length

2024-05-11T14:54:40.502011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:40.708538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 204
67.8%
1 97
32.2%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
폐업
204 
영업
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 204
67.8%
영업 97
32.2%

Length

2024-05-11T14:54:40.902999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:41.344337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 204
67.8%
영업 97
32.2%

폐업일자
Date

MISSING 

Distinct180
Distinct (%)88.2%
Missing97
Missing (%)32.2%
Memory size2.5 KiB
Minimum1997-12-15 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T14:54:41.567632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:41.885473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB

전화번호
Text

MISSING 

Distinct180
Distinct (%)94.7%
Missing111
Missing (%)36.9%
Memory size2.5 KiB
2024-05-11T14:54:42.420308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.505263
Min length2

Characters and Unicode

Total characters1996
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

Unique173 ?
Unique (%)91.1%

Sample

1st row0222483451
2nd row02 2151642
3rd row02 4634533
4th row02 4617077
5th row02 2996251
ValueCountFrequency (%)
02 101
30.3%
465 3
 
0.9%
070 3
 
0.9%
3535 3
 
0.9%
517 2
 
0.6%
499 2
 
0.6%
031 2
 
0.6%
727 2
 
0.6%
467 2
 
0.6%
545 2
 
0.6%
Other values (205) 211
63.4%
2024-05-11T14:54:43.167603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 397
19.9%
0 373
18.7%
201
10.1%
4 170
8.5%
5 147
 
7.4%
9 139
 
7.0%
3 126
 
6.3%
6 125
 
6.3%
1 112
 
5.6%
7 109
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1795
89.9%
Space Separator 201
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 397
22.1%
0 373
20.8%
4 170
9.5%
5 147
 
8.2%
9 139
 
7.7%
3 126
 
7.0%
6 125
 
7.0%
1 112
 
6.2%
7 109
 
6.1%
8 97
 
5.4%
Space Separator
ValueCountFrequency (%)
201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 397
19.9%
0 373
18.7%
201
10.1%
4 170
8.5%
5 147
 
7.4%
9 139
 
7.0%
3 126
 
6.3%
6 125
 
6.3%
1 112
 
5.6%
7 109
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 397
19.9%
0 373
18.7%
201
10.1%
4 170
8.5%
5 147
 
7.4%
9 139
 
7.0%
3 126
 
6.3%
6 125
 
6.3%
1 112
 
5.6%
7 109
 
5.5%
Distinct219
Distinct (%)73.0%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-05-11T14:54:43.841899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9933333
Min length3

Characters and Unicode

Total characters1498
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

Unique183 ?
Unique (%)61.0%

Sample

1st row668.80
2nd row.00
3rd row.00
4th row64.00
5th row.00
ValueCountFrequency (%)
00 18
 
6.0%
33.00 10
 
3.3%
6.00 5
 
1.7%
40.00 5
 
1.7%
66.00 4
 
1.3%
49.50 4
 
1.3%
30.00 4
 
1.3%
3.30 4
 
1.3%
37.10 3
 
1.0%
6.60 3
 
1.0%
Other values (209) 240
80.0%
2024-05-11T14:54:44.796999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 358
23.9%
. 300
20.0%
3 126
 
8.4%
4 112
 
7.5%
1 112
 
7.5%
2 101
 
6.7%
6 94
 
6.3%
5 88
 
5.9%
7 75
 
5.0%
8 69
 
4.6%
Other values (2) 63
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1195
79.8%
Other Punctuation 303
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 358
30.0%
3 126
 
10.5%
4 112
 
9.4%
1 112
 
9.4%
2 101
 
8.5%
6 94
 
7.9%
5 88
 
7.4%
7 75
 
6.3%
8 69
 
5.8%
9 60
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 300
99.0%
, 3
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 358
23.9%
. 300
20.0%
3 126
 
8.4%
4 112
 
7.5%
1 112
 
7.5%
2 101
 
6.7%
6 94
 
6.3%
5 88
 
5.9%
7 75
 
5.0%
8 69
 
4.6%
Other values (2) 63
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 358
23.9%
. 300
20.0%
3 126
 
8.4%
4 112
 
7.5%
1 112
 
7.5%
2 101
 
6.7%
6 94
 
6.3%
5 88
 
5.9%
7 75
 
5.0%
8 69
 
4.6%
Other values (2) 63
 
4.2%
Distinct80
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:45.240264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1262458
Min length6

Characters and Unicode

Total characters1844
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

Unique32 ?
Unique (%)10.6%

Sample

1st row133851
2nd row133850
3rd row133822
4th row133832
5th row133840
ValueCountFrequency (%)
133850 25
 
8.3%
133832 17
 
5.6%
133834 15
 
5.0%
133835 14
 
4.7%
133847 12
 
4.0%
133851 10
 
3.3%
133882 10
 
3.3%
133833 9
 
3.0%
133823 9
 
3.0%
133815 9
 
3.0%
Other values (70) 171
56.8%
2024-05-11T14:54:45.888115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 717
38.9%
1 355
19.3%
8 309
16.8%
2 105
 
5.7%
5 88
 
4.8%
4 76
 
4.1%
0 70
 
3.8%
7 38
 
2.1%
- 38
 
2.1%
9 28
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1806
97.9%
Dash Punctuation 38
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 717
39.7%
1 355
19.7%
8 309
17.1%
2 105
 
5.8%
5 88
 
4.9%
4 76
 
4.2%
0 70
 
3.9%
7 38
 
2.1%
9 28
 
1.6%
6 20
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 717
38.9%
1 355
19.3%
8 309
16.8%
2 105
 
5.7%
5 88
 
4.8%
4 76
 
4.1%
0 70
 
3.8%
7 38
 
2.1%
- 38
 
2.1%
9 28
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 717
38.9%
1 355
19.3%
8 309
16.8%
2 105
 
5.7%
5 88
 
4.8%
4 76
 
4.1%
0 70
 
3.8%
7 38
 
2.1%
- 38
 
2.1%
9 28
 
1.5%
Distinct265
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:46.297173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length26.156146
Min length17

Characters and Unicode

Total characters7873
Distinct characters211
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique237 ?
Unique (%)78.7%

Sample

1st row서울특별시 성동구 용답동 236-7
2nd row서울특별시 성동구 용답동 229-13
3rd row서울특별시 성동구 성수동1가 13-1
4th row서울특별시 성동구 성수동2가 277-50
5th row서울특별시 성동구 옥수동 365-6
ValueCountFrequency (%)
서울특별시 300
20.4%
성동구 300
20.4%
성수동2가 92
 
6.2%
용답동 57
 
3.9%
성수동1가 44
 
3.0%
도선동 21
 
1.4%
하왕십리동 17
 
1.2%
옥수동 17
 
1.2%
마장동 17
 
1.2%
234 11
 
0.7%
Other values (391) 596
40.5%
2024-05-11T14:54:47.087545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1406
17.9%
632
 
8.0%
458
 
5.8%
2 383
 
4.9%
1 329
 
4.2%
307
 
3.9%
307
 
3.9%
306
 
3.9%
300
 
3.8%
300
 
3.8%
Other values (201) 3145
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4425
56.2%
Decimal Number 1697
 
21.6%
Space Separator 1406
 
17.9%
Dash Punctuation 251
 
3.2%
Uppercase Letter 47
 
0.6%
Close Punctuation 16
 
0.2%
Open Punctuation 16
 
0.2%
Lowercase Letter 8
 
0.1%
Other Punctuation 6
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
632
14.3%
458
 
10.4%
307
 
6.9%
307
 
6.9%
306
 
6.9%
300
 
6.8%
300
 
6.8%
300
 
6.8%
164
 
3.7%
159
 
3.6%
Other values (166) 1192
26.9%
Uppercase Letter
ValueCountFrequency (%)
A 11
23.4%
T 7
14.9%
B 5
10.6%
E 4
 
8.5%
P 3
 
6.4%
D 3
 
6.4%
C 2
 
4.3%
K 2
 
4.3%
N 2
 
4.3%
R 2
 
4.3%
Other values (4) 6
12.8%
Decimal Number
ValueCountFrequency (%)
2 383
22.6%
1 329
19.4%
3 170
10.0%
0 147
 
8.7%
7 137
 
8.1%
6 126
 
7.4%
5 111
 
6.5%
8 103
 
6.1%
4 101
 
6.0%
9 90
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
w 2
25.0%
e 2
25.0%
r 2
25.0%
o 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
/ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1406
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 251
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4425
56.2%
Common 3392
43.1%
Latin 56
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
632
14.3%
458
 
10.4%
307
 
6.9%
307
 
6.9%
306
 
6.9%
300
 
6.8%
300
 
6.8%
300
 
6.8%
164
 
3.7%
159
 
3.6%
Other values (166) 1192
26.9%
Latin
ValueCountFrequency (%)
A 11
19.6%
T 7
12.5%
B 5
 
8.9%
E 4
 
7.1%
P 3
 
5.4%
D 3
 
5.4%
C 2
 
3.6%
w 2
 
3.6%
e 2
 
3.6%
r 2
 
3.6%
Other values (9) 15
26.8%
Common
ValueCountFrequency (%)
1406
41.5%
2 383
 
11.3%
1 329
 
9.7%
- 251
 
7.4%
3 170
 
5.0%
0 147
 
4.3%
7 137
 
4.0%
6 126
 
3.7%
5 111
 
3.3%
8 103
 
3.0%
Other values (6) 229
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4425
56.2%
ASCII 3447
43.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1406
40.8%
2 383
 
11.1%
1 329
 
9.5%
- 251
 
7.3%
3 170
 
4.9%
0 147
 
4.3%
7 137
 
4.0%
6 126
 
3.7%
5 111
 
3.2%
8 103
 
3.0%
Other values (24) 284
 
8.2%
Hangul
ValueCountFrequency (%)
632
14.3%
458
 
10.4%
307
 
6.9%
307
 
6.9%
306
 
6.9%
300
 
6.8%
300
 
6.8%
300
 
6.8%
164
 
3.7%
159
 
3.6%
Other values (166) 1192
26.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct204
Distinct (%)97.1%
Missing91
Missing (%)30.2%
Memory size2.5 KiB
2024-05-11T14:54:47.521879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length48
Mean length37.257143
Min length23

Characters and Unicode

Total characters7824
Distinct characters203
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)94.3%

Sample

1st row서울특별시 성동구 청계천로 468, 신일금속빌딩 4층 (하왕십리동)
2nd row서울특별시 성동구 고산자로 269 (도선동,신한넥스텔 713호)
3rd row서울특별시 성동구 서울숲길 51 (성수동1가)
4th row서울특별시 성동구 마장로 305 (마장동,지상3층)
5th row서울특별시 성동구 고산자로8길 12, 1층 (행당동)
ValueCountFrequency (%)
서울특별시 209
 
14.2%
성동구 209
 
14.2%
성수동2가 64
 
4.3%
용답동 34
 
2.3%
성수동1가 28
 
1.9%
2층 26
 
1.8%
자동차시장1길 23
 
1.6%
3층 21
 
1.4%
1층 19
 
1.3%
도선동 15
 
1.0%
Other values (455) 824
56.0%
2024-05-11T14:54:48.261545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1262
 
16.1%
480
 
6.1%
1 402
 
5.1%
357
 
4.6%
, 254
 
3.2%
2 251
 
3.2%
238
 
3.0%
223
 
2.9%
) 218
 
2.8%
( 218
 
2.8%
Other values (193) 3921
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4330
55.3%
Decimal Number 1441
 
18.4%
Space Separator 1262
 
16.1%
Other Punctuation 255
 
3.3%
Close Punctuation 218
 
2.8%
Open Punctuation 218
 
2.8%
Dash Punctuation 54
 
0.7%
Uppercase Letter 37
 
0.5%
Lowercase Letter 8
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
480
 
11.1%
357
 
8.2%
238
 
5.5%
223
 
5.2%
217
 
5.0%
209
 
4.8%
209
 
4.8%
209
 
4.8%
165
 
3.8%
158
 
3.6%
Other values (163) 1865
43.1%
Decimal Number
ValueCountFrequency (%)
1 402
27.9%
2 251
17.4%
3 149
 
10.3%
0 146
 
10.1%
4 107
 
7.4%
5 102
 
7.1%
7 81
 
5.6%
8 78
 
5.4%
6 65
 
4.5%
9 60
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 11
29.7%
A 7
18.9%
C 6
16.2%
T 4
 
10.8%
D 3
 
8.1%
I 2
 
5.4%
K 2
 
5.4%
V 1
 
2.7%
S 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
w 2
25.0%
r 2
25.0%
e 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 254
99.6%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1262
100.0%
Close Punctuation
ValueCountFrequency (%)
) 218
100.0%
Open Punctuation
ValueCountFrequency (%)
( 218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4330
55.3%
Common 3448
44.1%
Latin 46
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
480
 
11.1%
357
 
8.2%
238
 
5.5%
223
 
5.2%
217
 
5.0%
209
 
4.8%
209
 
4.8%
209
 
4.8%
165
 
3.8%
158
 
3.6%
Other values (163) 1865
43.1%
Common
ValueCountFrequency (%)
1262
36.6%
1 402
 
11.7%
, 254
 
7.4%
2 251
 
7.3%
) 218
 
6.3%
( 218
 
6.3%
3 149
 
4.3%
0 146
 
4.2%
4 107
 
3.1%
5 102
 
3.0%
Other values (6) 339
 
9.8%
Latin
ValueCountFrequency (%)
B 11
23.9%
A 7
15.2%
C 6
13.0%
T 4
 
8.7%
D 3
 
6.5%
I 2
 
4.3%
o 2
 
4.3%
K 2
 
4.3%
w 2
 
4.3%
r 2
 
4.3%
Other values (4) 5
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4330
55.3%
ASCII 3493
44.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1262
36.1%
1 402
 
11.5%
, 254
 
7.3%
2 251
 
7.2%
) 218
 
6.2%
( 218
 
6.2%
3 149
 
4.3%
0 146
 
4.2%
4 107
 
3.1%
5 102
 
2.9%
Other values (19) 384
 
11.0%
Hangul
ValueCountFrequency (%)
480
 
11.1%
357
 
8.2%
238
 
5.5%
223
 
5.2%
217
 
5.0%
209
 
4.8%
209
 
4.8%
209
 
4.8%
165
 
3.8%
158
 
3.6%
Other values (163) 1865
43.1%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct67
Distinct (%)32.7%
Missing96
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean4810.2341
Minimum4700
Maximum12927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:48.518117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4707.2
Q14737
median4786
Q34797
95-th percentile4808
Maximum12927
Range8227
Interquartile range (IQR)60

Descriptive statistics

Standard deviation570.77995
Coefficient of variation (CV)0.11865949
Kurtosis203.39888
Mean4810.2341
Median Absolute Deviation (MAD)20
Skewness14.234091
Sum986098
Variance325789.75
MonotonicityNot monotonic
2024-05-11T14:54:48.741873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4808 31
 
10.3%
4709 12
 
4.0%
4793 11
 
3.7%
4797 10
 
3.3%
4794 8
 
2.7%
4735 7
 
2.3%
4782 6
 
2.0%
4790 6
 
2.0%
4789 5
 
1.7%
4779 5
 
1.7%
Other values (57) 104
34.6%
(Missing) 96
31.9%
ValueCountFrequency (%)
4700 1
 
0.3%
4701 1
 
0.3%
4702 3
 
1.0%
4704 2
 
0.7%
4705 1
 
0.3%
4707 3
 
1.0%
4708 1
 
0.3%
4709 12
4.0%
4710 3
 
1.0%
4711 1
 
0.3%
ValueCountFrequency (%)
12927 1
 
0.3%
4808 31
10.3%
4807 1
 
0.3%
4806 1
 
0.3%
4805 3
 
1.0%
4803 1
 
0.3%
4800 2
 
0.7%
4799 4
 
1.3%
4798 3
 
1.0%
4797 10
 
3.3%
Distinct290
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:49.114444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length7.8637874
Min length2

Characters and Unicode

Total characters2367
Distinct characters294
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

Unique279 ?
Unique (%)92.7%

Sample

1st row산마루실업
2nd row중앙용역
3rd row(주)동양수관리
4th row현대환경청소산업
5th row(주)진영토스템
ValueCountFrequency (%)
주식회사 33
 
9.6%
주식회사지에프엔에스 2
 
0.6%
주)나라환경산업 2
 
0.6%
깨끗한세상 2
 
0.6%
주)에코캠크린 2
 
0.6%
주성산업 2
 
0.6%
포스원산업 2
 
0.6%
2
 
0.6%
승주개발용역(주 2
 
0.6%
중앙용역 2
 
0.6%
Other values (289) 293
85.2%
2024-05-11T14:54:49.746285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
9.0%
( 169
 
7.1%
) 169
 
7.1%
100
 
4.2%
66
 
2.8%
65
 
2.7%
55
 
2.3%
53
 
2.2%
46
 
1.9%
44
 
1.9%
Other values (284) 1388
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1954
82.6%
Open Punctuation 169
 
7.1%
Close Punctuation 169
 
7.1%
Space Separator 44
 
1.9%
Uppercase Letter 19
 
0.8%
Lowercase Letter 10
 
0.4%
Decimal Number 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
212
 
10.8%
100
 
5.1%
66
 
3.4%
65
 
3.3%
55
 
2.8%
53
 
2.7%
46
 
2.4%
41
 
2.1%
32
 
1.6%
32
 
1.6%
Other values (258) 1252
64.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
21.1%
P 2
10.5%
C 2
10.5%
O 2
10.5%
H 2
10.5%
B 1
 
5.3%
T 1
 
5.3%
E 1
 
5.3%
A 1
 
5.3%
N 1
 
5.3%
Other values (2) 2
10.5%
Lowercase Letter
ValueCountFrequency (%)
a 2
20.0%
e 1
10.0%
n 1
10.0%
i 1
10.0%
m 1
10.0%
t 1
10.0%
s 1
10.0%
l 1
10.0%
g 1
10.0%
Open Punctuation
ValueCountFrequency (%)
( 169
100.0%
Close Punctuation
ValueCountFrequency (%)
) 169
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1954
82.6%
Common 384
 
16.2%
Latin 29
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
212
 
10.8%
100
 
5.1%
66
 
3.4%
65
 
3.3%
55
 
2.8%
53
 
2.7%
46
 
2.4%
41
 
2.1%
32
 
1.6%
32
 
1.6%
Other values (258) 1252
64.1%
Latin
ValueCountFrequency (%)
S 4
 
13.8%
P 2
 
6.9%
C 2
 
6.9%
O 2
 
6.9%
a 2
 
6.9%
H 2
 
6.9%
e 1
 
3.4%
n 1
 
3.4%
i 1
 
3.4%
m 1
 
3.4%
Other values (11) 11
37.9%
Common
ValueCountFrequency (%)
( 169
44.0%
) 169
44.0%
44
 
11.5%
1 1
 
0.3%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1954
82.6%
ASCII 413
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
212
 
10.8%
100
 
5.1%
66
 
3.4%
65
 
3.3%
55
 
2.8%
53
 
2.7%
46
 
2.4%
41
 
2.1%
32
 
1.6%
32
 
1.6%
Other values (258) 1252
64.1%
ASCII
ValueCountFrequency (%)
( 169
40.9%
) 169
40.9%
44
 
10.7%
S 4
 
1.0%
P 2
 
0.5%
C 2
 
0.5%
O 2
 
0.5%
a 2
 
0.5%
H 2
 
0.5%
e 1
 
0.2%
Other values (16) 16
 
3.9%
Distinct269
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum1999-07-15 00:00:00
Maximum2024-05-08 14:04:09
2024-05-11T14:54:50.001766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:50.240791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
I
208 
U
93 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 208
69.1%
U 93
30.9%

Length

2024-05-11T14:54:50.493075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:50.661761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 208
69.1%
u 93
30.9%
Distinct118
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T14:54:50.851409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:51.128378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
건물위생관리업
300 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0099668
Min length7

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 300
99.7%
건물위생관리업 기타 1
 
0.3%

Length

2024-05-11T14:54:51.361796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:51.536291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 301
99.7%
기타 1
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct200
Distinct (%)67.6%
Missing5
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean204196.63
Minimum200951.21
Maximum218366.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:51.736257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200951.21
5-th percentile201375.15
Q1203089.86
median204480.35
Q3205079.3
95-th percentile205851.99
Maximum218366.2
Range17414.996
Interquartile range (IQR)1989.4404

Descriptive statistics

Standard deviation1552.8126
Coefficient of variation (CV)0.0076044969
Kurtosis22.348496
Mean204196.63
Median Absolute Deviation (MAD)754.50297
Skewness2.1308963
Sum60442202
Variance2411227.1
MonotonicityNot monotonic
2024-05-11T14:54:51.967529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205784.868811814 11
 
3.7%
205039.907145725 9
 
3.0%
203089.863865288 8
 
2.7%
204966.098616157 5
 
1.7%
201258.52524431 5
 
1.7%
205260.827743854 4
 
1.3%
205198.708251778 4
 
1.3%
204489.124604852 4
 
1.3%
200951.206580662 4
 
1.3%
204934.166661444 3
 
1.0%
Other values (190) 239
79.4%
(Missing) 5
 
1.7%
ValueCountFrequency (%)
200951.206580662 4
1.3%
201084.709621627 2
 
0.7%
201222.07429303 1
 
0.3%
201258.52524431 5
1.7%
201286.413820482 1
 
0.3%
201299.635998002 1
 
0.3%
201356.590509 1
 
0.3%
201381.341820138 1
 
0.3%
201396.118230344 1
 
0.3%
201669.803556903 1
 
0.3%
ValueCountFrequency (%)
218366.202136734 1
 
0.3%
206347.265568329 1
 
0.3%
206193.500564601 1
 
0.3%
206033.909589487 3
1.0%
206019.74086692 1
 
0.3%
205998.740564647 1
 
0.3%
205996.36323681 1
 
0.3%
205993.649689478 1
 
0.3%
205979.911432555 1
 
0.3%
205948.345792507 2
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct200
Distinct (%)67.6%
Missing5
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean450088.69
Minimum448169.31
Maximum452076.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:52.242218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448169.31
5-th percentile448518.65
Q1449173.61
median449760.42
Q3451033.57
95-th percentile451684.71
Maximum452076.36
Range3907.0532
Interquartile range (IQR)1859.962

Descriptive statistics

Standard deviation1068.2269
Coefficient of variation (CV)0.0023733699
Kurtosis-1.3827057
Mean450088.69
Median Absolute Deviation (MAD)996.78214
Skewness0.1351448
Sum1.3322625 × 108
Variance1141108.8
MonotonicityNot monotonic
2024-05-11T14:54:52.498853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450883.524006222 11
 
3.7%
449216.223655036 9
 
3.0%
451271.366165685 8
 
2.7%
449159.452779834 5
 
1.7%
448763.634282312 5
 
1.7%
448399.948660115 4
 
1.3%
451031.626755333 4
 
1.3%
449490.007760201 4
 
1.3%
449000.920061846 4
 
1.3%
449083.056771443 3
 
1.0%
Other values (190) 239
79.4%
(Missing) 5
 
1.7%
ValueCountFrequency (%)
448169.308636228 2
0.7%
448238.821371375 1
 
0.3%
448303.982643822 1
 
0.3%
448313.428616502 1
 
0.3%
448395.08837964 1
 
0.3%
448399.948660115 4
1.3%
448475.825571531 1
 
0.3%
448488.088528314 1
 
0.3%
448498.435494754 1
 
0.3%
448509.720346432 1
 
0.3%
ValueCountFrequency (%)
452076.36180744 1
0.3%
452051.354497514 1
0.3%
452019.558572479 1
0.3%
452006.304255755 1
0.3%
451997.220136633 2
0.7%
451979.217307863 1
0.3%
451949.23629208 1
0.3%
451945.90847576 1
0.3%
451934.193821509 1
0.3%
451832.124598785 1
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
건물위생관리업
241 
<NA>
59 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.4219269
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 241
80.1%
<NA> 59
 
19.6%
건물위생관리업 기타 1
 
0.3%

Length

2024-05-11T14:54:52.742496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:52.921488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 242
80.1%
na 59
 
19.5%
기타 1
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)6.4%
Missing99
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean2.2029703
Minimum0
Maximum22
Zeros125
Zeros (%)41.5%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:53.477863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile9
Maximum22
Range22
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.7367865
Coefficient of variation (CV)1.6962491
Kurtosis8.2944474
Mean2.2029703
Median Absolute Deviation (MAD)0
Skewness2.5236904
Sum445
Variance13.963573
MonotonicityNot monotonic
2024-05-11T14:54:53.702319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 125
41.5%
4 18
 
6.0%
3 16
 
5.3%
5 13
 
4.3%
8 7
 
2.3%
10 5
 
1.7%
2 4
 
1.3%
19 3
 
1.0%
9 3
 
1.0%
7 3
 
1.0%
Other values (3) 5
 
1.7%
(Missing) 99
32.9%
ValueCountFrequency (%)
0 125
41.5%
1 1
 
0.3%
2 4
 
1.3%
3 16
 
5.3%
4 18
 
6.0%
5 13
 
4.3%
6 3
 
1.0%
7 3
 
1.0%
8 7
 
2.3%
9 3
 
1.0%
ValueCountFrequency (%)
22 1
 
0.3%
19 3
 
1.0%
10 5
 
1.7%
9 3
 
1.0%
8 7
 
2.3%
7 3
 
1.0%
6 3
 
1.0%
5 13
4.3%
4 18
6.0%
3 16
5.3%
Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
131 
<NA>
106 
1
49 
4
 
5
3
 
5

Length

Max length4
Median length1
Mean length2.0564784
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 131
43.5%
<NA> 106
35.2%
1 49
 
16.3%
4 5
 
1.7%
3 5
 
1.7%
2 5
 
1.7%

Length

2024-05-11T14:54:53.968721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:54.203423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 131
43.5%
na 106
35.2%
1 49
 
16.3%
4 5
 
1.7%
3 5
 
1.7%
2 5
 
1.7%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)8.9%
Missing143
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean2.8101266
Minimum0
Maximum17
Zeros41
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:54.418994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile8
Maximum17
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0393427
Coefficient of variation (CV)1.0815679
Kurtosis5.7750182
Mean2.8101266
Median Absolute Deviation (MAD)2
Skewness1.9960612
Sum444
Variance9.2376038
MonotonicityNot monotonic
2024-05-11T14:54:54.617455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 41
 
13.6%
4 23
 
7.6%
2 23
 
7.6%
3 22
 
7.3%
1 21
 
7.0%
5 8
 
2.7%
8 5
 
1.7%
6 5
 
1.7%
7 3
 
1.0%
17 2
 
0.7%
Other values (4) 5
 
1.7%
(Missing) 143
47.5%
ValueCountFrequency (%)
0 41
13.6%
1 21
7.0%
2 23
7.6%
3 22
7.3%
4 23
7.6%
5 8
 
2.7%
6 5
 
1.7%
7 3
 
1.0%
8 5
 
1.7%
9 1
 
0.3%
ValueCountFrequency (%)
17 2
 
0.7%
13 1
 
0.3%
12 1
 
0.3%
10 2
 
0.7%
9 1
 
0.3%
8 5
 
1.7%
7 3
 
1.0%
6 5
 
1.7%
5 8
 
2.7%
4 23
7.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)9.2%
Missing171
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean2.8692308
Minimum0
Maximum17
Zeros27
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:54.862043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile8
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9396737
Coefficient of variation (CV)1.0245512
Kurtosis7.6477888
Mean2.8692308
Median Absolute Deviation (MAD)2
Skewness2.23532
Sum373
Variance8.6416816
MonotonicityNot monotonic
2024-05-11T14:54:55.084391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 27
 
9.0%
2 22
 
7.3%
3 20
 
6.6%
4 20
 
6.6%
1 19
 
6.3%
5 7
 
2.3%
8 5
 
1.7%
6 3
 
1.0%
7 3
 
1.0%
17 2
 
0.7%
Other values (2) 2
 
0.7%
(Missing) 171
56.8%
ValueCountFrequency (%)
0 27
9.0%
1 19
6.3%
2 22
7.3%
3 20
6.6%
4 20
6.6%
5 7
 
2.3%
6 3
 
1.0%
7 3
 
1.0%
8 5
 
1.7%
9 1
 
0.3%
ValueCountFrequency (%)
17 2
 
0.7%
13 1
 
0.3%
9 1
 
0.3%
8 5
 
1.7%
7 3
 
1.0%
6 3
 
1.0%
5 7
 
2.3%
4 20
6.6%
3 20
6.6%
2 22
7.3%
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
220 
0
76 
1
 
5

Length

Max length4
Median length4
Mean length3.192691
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 220
73.1%
0 76
 
25.2%
1 5
 
1.7%

Length

2024-05-11T14:54:55.333012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.502177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
73.1%
0 76
 
25.2%
1 5
 
1.7%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
243 
0
53 
1
 
5

Length

Max length4
Median length4
Mean length3.4219269
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> 243
80.7%
0 53
 
17.6%
1 5
 
1.7%

Length

2024-05-11T14:54:55.676990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.839344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 243
80.7%
0 53
 
17.6%
1 5
 
1.7%

한실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
169 
<NA>
132 

Length

Max length4
Median length1
Mean length2.3156146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
56.1%
<NA> 132
43.9%

Length

2024-05-11T14:54:56.023673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.194321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
56.1%
na 132
43.9%

양실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
169 
<NA>
132 

Length

Max length4
Median length1
Mean length2.3156146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
56.1%
<NA> 132
43.9%

Length

2024-05-11T14:54:56.376943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.580076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
56.1%
na 132
43.9%

욕실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
169 
<NA>
132 

Length

Max length4
Median length1
Mean length2.3156146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
56.1%
<NA> 132
43.9%

Length

2024-05-11T14:54:56.808597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.058319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
56.1%
na 132
43.9%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing70
Missing (%)23.3%
Memory size734.0 B
False
231 
(Missing)
70 
ValueCountFrequency (%)
False 231
76.7%
(Missing) 70
 
23.3%
2024-05-11T14:54:57.200870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
169 
<NA>
132 

Length

Max length4
Median length1
Mean length2.3156146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
56.1%
<NA> 132
43.9%

Length

2024-05-11T14:54:57.422499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.626768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
56.1%
na 132
43.9%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing301
Missing (%)100.0%
Memory size2.8 KiB
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
218 
임대
80 
자가
 
3

Length

Max length4
Median length4
Mean length3.448505
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> 218
72.4%
임대 80
 
26.6%
자가 3
 
1.0%

Length

2024-05-11T14:54:57.824348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.013360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 218
72.4%
임대 80
 
26.6%
자가 3
 
1.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
147 

Length

Max length4
Median length4
Mean length2.5348837
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> 154
51.2%
0 147
48.8%

Length

2024-05-11T14:54:58.202525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.379082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
51.2%
0 147
48.8%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
233 
0
63 
1
 
4
2
 
1

Length

Max length4
Median length4
Mean length3.3222591
Min length1

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> 233
77.4%
0 63
 
20.9%
1 4
 
1.3%
2 1
 
0.3%

Length

2024-05-11T14:54:58.663359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.845410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 233
77.4%
0 63
 
20.9%
1 4
 
1.3%
2 1
 
0.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)8.7%
Missing232
Missing (%)77.1%
Infinite0
Infinite (%)0.0%
Mean1.7101449
Minimum0
Maximum101
Zeros60
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T14:54:59.033836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum101
Range101
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.152344
Coefficient of variation (CV)7.1060314
Kurtosis68.444535
Mean1.7101449
Median Absolute Deviation (MAD)0
Skewness8.2579591
Sum118
Variance147.67945
MonotonicityNot monotonic
2024-05-11T14:54:59.250713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 60
 
19.9%
2 4
 
1.3%
1 2
 
0.7%
3 1
 
0.3%
4 1
 
0.3%
101 1
 
0.3%
(Missing) 232
77.1%
ValueCountFrequency (%)
0 60
19.9%
1 2
 
0.7%
2 4
 
1.3%
3 1
 
0.3%
4 1
 
0.3%
101 1
 
0.3%
ValueCountFrequency (%)
101 1
 
0.3%
4 1
 
0.3%
3 1
 
0.3%
2 4
 
1.3%
1 2
 
0.7%
0 60
19.9%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
166 
0
135 

Length

Max length4
Median length4
Mean length2.654485
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> 166
55.1%
0 135
44.9%

Length

2024-05-11T14:54:59.486238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:59.659760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
55.1%
0 135
44.9%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
167 
0
134 

Length

Max length4
Median length4
Mean length2.6644518
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> 167
55.5%
0 134
44.5%

Length

2024-05-11T14:54:59.853515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:00.030411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 167
55.5%
0 134
44.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.8%
Missing59
Missing (%)19.6%
Memory size734.0 B
False
241 
True
 
1
(Missing)
59 
ValueCountFrequency (%)
False 241
80.1%
True 1
 
0.3%
(Missing) 59
 
19.6%
2024-05-11T14:55:00.185092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030300003030000-206-1991-0187119910121<NA>3폐업2폐업19990208<NA><NA><NA>0222483451668.80133851서울특별시 성동구 용답동 236-7<NA><NA>산마루실업2001-09-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업205993.649689450890.06848건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130300003030000-206-1992-0187519920609<NA>3폐업2폐업19980918<NA><NA><NA>02 2151642.00133850서울특별시 성동구 용답동 229-13<NA><NA>중앙용역2001-09-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업205347.840006451004.91006건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230300003030000-206-1993-0187619930906<NA>3폐업2폐업19990912<NA><NA><NA>02 4634533.00133822서울특별시 성동구 성수동1가 13-1<NA><NA>(주)동양수관리2002-03-21 00:00:00I2018-08-31 23:59:59.0건물위생관리업204135.350981449906.682597건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330300003030000-206-1993-0187719930716<NA>3폐업2폐업20030217<NA><NA><NA>02 461707764.00133832서울특별시 성동구 성수동2가 277-50<NA><NA>현대환경청소산업2003-02-20 00:00:00I2018-08-31 23:59:59.0건물위생관리업205170.446244449170.608973건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430300003030000-206-1993-0187819930903<NA>3폐업2폐업19971215<NA><NA><NA>02 2996251.00133840서울특별시 성동구 옥수동 365-6<NA><NA>(주)진영토스템2001-09-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업201396.11823448897.697384건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530300003030000-206-1994-0187219940601<NA>1영업/정상1영업<NA><NA><NA><NA>0222814174165.00133854서울특별시 성동구 하왕십리동 301-3 신일금속빌딩서울특별시 성동구 청계천로 468, 신일금속빌딩 4층 (하왕십리동)4702유명기업(주)2022-03-21 14:03:18U2022-03-23 02:40:00.0건물위생관리업202478.967119451934.193822건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630300003030000-206-1994-0187419940117<NA>1영업/정상1영업<NA><NA><NA><NA>022291080238.50133714서울특별시 성동구 도선동 14 신한넥스텔 713호서울특별시 성동구 고산자로 269 (도선동,신한넥스텔 713호)4709무량개발2020-09-21 16:52:01U2020-09-23 02:40:00.0건물위생관리업203089.863865451271.366166건물위생관리업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
730300003030000-206-1994-0187919940117<NA>1영업/정상1영업<NA><NA><NA><NA>020466777668.20133825서울특별시 성동구 성수동1가 685-295서울특별시 성동구 서울숲길 51 (성수동1가)4766광명건설(주)2003-02-20 00:00:00I2018-08-31 23:59:59.0건물위생관리업203743.914867449552.506044건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830300003030000-206-1994-0188019940307<NA>3폐업2폐업20030217<NA><NA><NA>02 253003135.10133803서울특별시 성동구 금호동2가 322-1<NA><NA>대한상사2003-02-20 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
930300003030000-206-1994-0188219940422<NA>3폐업2폐업19971215<NA><NA><NA>02 464396263.00133832서울특별시 성동구 성수동2가 280-17<NA><NA>경성흥산(주)2001-09-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업205482.152008449487.568219건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
29130300003030000-206-2022-0001020220118<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00133850서울특별시 성동구 용답동 233-2 원광빌딩서울특별시 성동구 천호대로 418, 3층 301호 (용답동)4808유한회사 경인의보환경산업2022-10-05 17:27:14I2021-10-31 00:07:00.0건물위생관리업205704.46009450970.779835<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29230300003030000-206-2022-000112022-03-14<NA>3폐업2폐업2023-02-02<NA><NA><NA>032 466270233.45133-832서울특별시 성동구 성수동2가 277-17 성수아카데미타워서울특별시 성동구 성수이로 118, 성수아카데미타워 9층 925호 (성수동2가)4797(주)도기야2023-02-02 17:01:38I2022-12-02 00:04:00.0건물위생관리업205039.907146449216.223655<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29330300003030000-206-2023-000012023-02-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.56133-820서울특별시 성동구 성수동1가 197-2서울특별시 성동구 성덕정길 40-1, 1층 C-2, C-3호 (성수동1가)4774(주)미루클린2023-02-13 13:01:01I2022-12-01 23:05:00.0건물위생관리업204178.887703448488.088528<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29430300003030000-206-2023-000022023-06-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>79.27133-850서울특별시 성동구 용답동 234 장안평중고자동차시장서울특별시 성동구 자동차시장1길 70, 장안평중고자동차시장 A호 B동 3층 가7호 (용답동)4808(주)오에이케이오크2023-06-02 15:04:17I2022-12-06 00:04:00.0건물위생관리업205784.868812450883.524006<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29530300003030000-206-2023-000032023-06-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.46133-839서울특별시 성동구 옥수동 250-7 옥수삼성아파트 상가서울특별시 성동구 한림말길 31, 옥수삼성아파트 상가 지1층 비13호 (옥수동)4735클린스쿨서울2023-06-19 10:41:18I2022-12-05 22:01:00.0건물위생관리업201222.074293448765.977811<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29630300003030000-206-2023-000042023-08-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 835 353575.04133-839서울특별시 성동구 옥수동 200-4 삼오빌딩서울특별시 성동구 한림말길 41-21, 삼오빌딩 4층 (옥수동)4735(주)삼오피엠씨2023-08-21 10:14:45I2022-12-07 22:03:00.0건물위생관리업201258.525244448763.634282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29730300003030000-206-2023-000052023-11-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.00133-834서울특별시 성동구 성수동2가 300-1 삼진빌딩서울특별시 성동구 아차산로 113, 삼진빌딩 8층 8151호 (성수동2가)4794(주)진현티엠2023-11-10 11:15:10I2022-10-31 23:02:00.0건물위생관리업204966.098616449159.45278<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29830300003030000-206-2024-000012024-02-19<NA>3폐업2폐업2024-02-29<NA><NA><NA><NA>31.11133-859서울특별시 성동구 하왕십리동 1015-2서울특별시 성동구 무학봉길 44, 1, 2층 (하왕십리동)4714미래환경2024-02-29 11:24:24U2023-12-03 00:02:00.0건물위생관리업202365.559281450900.276131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29930300003030000-206-2024-000022024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.11133-859서울특별시 성동구 하왕십리동 1015-2서울특별시 성동구 무학봉길 44, 1, 2층 (하왕십리동)4714미래환경2024-02-29 11:27:21I2023-12-03 00:02:00.0건물위생관리업202365.559281450900.276131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30030300003030000-206-2024-000032024-03-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30133-924서울특별시 성동구 성수동1가 656-1572서울특별시 성동구 상원1길 25, 4층 4317호 (성수동1가)4779팀블라스팅(Team Blasting)2024-03-07 16:07:11I2023-12-03 00:09:00.0건물위생관리업204167.721292449290.778226<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>