Overview

Dataset statistics

Number of variables47
Number of observations241
Missing cells2552
Missing cells (%)22.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory95.2 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
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-19288/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (96.1%)Imbalance
위생업태명 is highly imbalanced (57.3%)Imbalance
사용끝지하층 is highly imbalanced (53.8%)Imbalance
여성종사자수 is highly imbalanced (59.3%)Imbalance
인허가취소일자 has 241 (100.0%) missing valuesMissing
폐업일자 has 86 (35.7%) missing valuesMissing
휴업시작일자 has 241 (100.0%) missing valuesMissing
휴업종료일자 has 241 (100.0%) missing valuesMissing
재개업일자 has 241 (100.0%) missing valuesMissing
전화번호 has 59 (24.5%) missing valuesMissing
도로명주소 has 58 (24.1%) missing valuesMissing
도로명우편번호 has 61 (25.3%) missing valuesMissing
좌표정보(X) has 8 (3.3%) missing valuesMissing
좌표정보(Y) has 8 (3.3%) missing valuesMissing
건물지상층수 has 70 (29.0%) missing valuesMissing
사용시작지상층 has 110 (45.6%) missing valuesMissing
사용끝지상층 has 141 (58.5%) missing valuesMissing
발한실여부 has 44 (18.3%) missing valuesMissing
조건부허가신고사유 has 241 (100.0%) missing valuesMissing
조건부허가시작일자 has 241 (100.0%) missing valuesMissing
조건부허가종료일자 has 241 (100.0%) missing valuesMissing
남성종사자수 has 180 (74.7%) missing valuesMissing
다중이용업소여부 has 39 (16.2%) 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 106 (44.0%) zerosZeros
사용시작지상층 has 38 (15.8%) zerosZeros
사용끝지상층 has 19 (7.9%) zerosZeros
남성종사자수 has 26 (10.8%) zerosZeros

Reproduction

Analysis started2024-05-11 08:57:51.346386
Analysis finished2024-05-11 08:57:51.996636
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3110000
241 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 241
100.0%

Length

2024-05-11T17:57:52.045954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:52.113255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 241
100.0%

관리번호
Text

UNIQUE 

Distinct241
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T17:57:52.247595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5302
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

Unique241 ?
Unique (%)100.0%

Sample

1st row3110000-206-1987-02124
2nd row3110000-206-1987-02125
3rd row3110000-206-1992-02124
4th row3110000-206-1993-02140
5th row3110000-206-1995-02125
ValueCountFrequency (%)
3110000-206-1987-02124 1
 
0.4%
3110000-206-2010-00009 1
 
0.4%
3110000-206-2016-00005 1
 
0.4%
3110000-206-2014-00008 1
 
0.4%
3110000-206-2014-00009 1
 
0.4%
3110000-206-2014-00010 1
 
0.4%
3110000-206-2015-00001 1
 
0.4%
3110000-206-2015-00002 1
 
0.4%
3110000-206-2015-00003 1
 
0.4%
3110000-206-2015-00004 1
 
0.4%
Other values (231) 231
95.9%
2024-05-11T17:57:52.520081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2391
45.1%
- 723
 
13.6%
1 715
 
13.5%
2 594
 
11.2%
3 309
 
5.8%
6 290
 
5.5%
9 77
 
1.5%
4 67
 
1.3%
7 60
 
1.1%
5 44
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4579
86.4%
Dash Punctuation 723
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2391
52.2%
1 715
 
15.6%
2 594
 
13.0%
3 309
 
6.7%
6 290
 
6.3%
9 77
 
1.7%
4 67
 
1.5%
7 60
 
1.3%
5 44
 
1.0%
8 32
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 723
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2391
45.1%
- 723
 
13.6%
1 715
 
13.5%
2 594
 
11.2%
3 309
 
5.8%
6 290
 
5.5%
9 77
 
1.5%
4 67
 
1.3%
7 60
 
1.1%
5 44
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2391
45.1%
- 723
 
13.6%
1 715
 
13.5%
2 594
 
11.2%
3 309
 
5.8%
6 290
 
5.5%
9 77
 
1.5%
4 67
 
1.3%
7 60
 
1.1%
5 44
 
0.8%
Distinct226
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1987-06-01 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T17:57:52.659794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:57:52.770524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
155 
1
86 

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 (%)
3 155
64.3%
1 86
35.7%

Length

2024-05-11T17:57:52.866917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:52.948698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 155
64.3%
1 86
35.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
155 
영업/정상
86 

Length

Max length5
Median length2
Mean length3.0705394
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 155
64.3%
영업/정상 86
35.7%

Length

2024-05-11T17:57:53.032292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:53.134025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 155
64.3%
영업/정상 86
35.7%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2
155 
1
86 

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 (%)
2 155
64.3%
1 86
35.7%

Length

2024-05-11T17:57:53.222781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:53.307563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 155
64.3%
1 86
35.7%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
155 
영업
86 

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 155
64.3%
영업 86
35.7%

Length

2024-05-11T17:57:53.397890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:53.472603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 155
64.3%
영업 86
35.7%

폐업일자
Date

MISSING 

Distinct119
Distinct (%)76.8%
Missing86
Missing (%)35.7%
Memory size2.0 KiB
Minimum1998-09-04 00:00:00
Maximum2024-04-18 00:00:00
2024-05-11T17:57:53.576909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:57:53.700286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct174
Distinct (%)95.6%
Missing59
Missing (%)24.5%
Memory size2.0 KiB
2024-05-11T17:57:53.961580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.274725
Min length7

Characters and Unicode

Total characters1870
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)91.2%

Sample

1st row02 3846761
2nd row02 7184221
3rd row0203820382
4th row0203080308
5th row0203856516
ValueCountFrequency (%)
02 127
37.0%
358 3
 
0.9%
031 3
 
0.9%
3062322 2
 
0.6%
3826544 2
 
0.6%
5981057 2
 
0.6%
3851799 2
 
0.6%
5568156 2
 
0.6%
3750770 2
 
0.6%
070 2
 
0.6%
Other values (190) 196
57.1%
2024-05-11T17:57:54.316360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 299
16.0%
2 277
14.8%
3 217
11.6%
197
10.5%
5 154
8.2%
8 141
7.5%
1 138
7.4%
7 133
7.1%
4 113
 
6.0%
6 107
 
5.7%
Other values (2) 94
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1672
89.4%
Space Separator 197
 
10.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 299
17.9%
2 277
16.6%
3 217
13.0%
5 154
9.2%
8 141
8.4%
1 138
8.3%
7 133
8.0%
4 113
 
6.8%
6 107
 
6.4%
9 93
 
5.6%
Space Separator
ValueCountFrequency (%)
197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1870
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 299
16.0%
2 277
14.8%
3 217
11.6%
197
10.5%
5 154
8.2%
8 141
7.5%
1 138
7.4%
7 133
7.1%
4 113
 
6.0%
6 107
 
5.7%
Other values (2) 94
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1870
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 299
16.0%
2 277
14.8%
3 217
11.6%
197
10.5%
5 154
8.2%
8 141
7.5%
1 138
7.4%
7 133
7.1%
4 113
 
6.0%
6 107
 
5.7%
Other values (2) 94
 
5.0%
Distinct165
Distinct (%)68.8%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2024-05-11T17:57:54.660959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9375
Min length3

Characters and Unicode

Total characters1185
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

Unique137 ?
Unique (%)57.1%

Sample

1st row67.21
2nd row97.29
3rd row318.48
4th row695.37
5th row596.25
ValueCountFrequency (%)
00 19
 
7.9%
33.00 10
 
4.2%
20.00 7
 
2.9%
60.00 6
 
2.5%
30.00 6
 
2.5%
13.00 4
 
1.7%
10.00 4
 
1.7%
24.00 4
 
1.7%
45.00 4
 
1.7%
66.00 3
 
1.2%
Other values (155) 173
72.1%
2024-05-11T17:57:55.093877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 309
26.1%
. 240
20.3%
3 100
 
8.4%
2 94
 
7.9%
1 80
 
6.8%
6 79
 
6.7%
5 76
 
6.4%
9 63
 
5.3%
4 62
 
5.2%
8 43
 
3.6%
Other values (2) 39
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 943
79.6%
Other Punctuation 242
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 309
32.8%
3 100
 
10.6%
2 94
 
10.0%
1 80
 
8.5%
6 79
 
8.4%
5 76
 
8.1%
9 63
 
6.7%
4 62
 
6.6%
8 43
 
4.6%
7 37
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 240
99.2%
, 2
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1185
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 309
26.1%
. 240
20.3%
3 100
 
8.4%
2 94
 
7.9%
1 80
 
6.8%
6 79
 
6.7%
5 76
 
6.4%
9 63
 
5.3%
4 62
 
5.2%
8 43
 
3.6%
Other values (2) 39
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 309
26.1%
. 240
20.3%
3 100
 
8.4%
2 94
 
7.9%
1 80
 
6.8%
6 79
 
6.7%
5 76
 
6.4%
9 63
 
5.3%
4 62
 
5.2%
8 43
 
3.6%
Other values (2) 39
 
3.3%
Distinct106
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T17:57:55.566799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1120332
Min length6

Characters and Unicode

Total characters1473
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

Unique56 ?
Unique (%)23.2%

Sample

1st row122899
2nd row122-941
3rd row122808
4th row122875
5th row122050
ValueCountFrequency (%)
122834 11
 
4.6%
122810 10
 
4.1%
122933 8
 
3.3%
122842 7
 
2.9%
122860 7
 
2.9%
122951 7
 
2.9%
122895 7
 
2.9%
122900 6
 
2.5%
122882 6
 
2.5%
122935 6
 
2.5%
Other values (96) 166
68.9%
2024-05-11T17:57:55.931038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 522
35.4%
1 301
20.4%
8 177
 
12.0%
9 124
 
8.4%
0 93
 
6.3%
3 73
 
5.0%
4 49
 
3.3%
5 41
 
2.8%
7 40
 
2.7%
- 27
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1446
98.2%
Dash Punctuation 27
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 522
36.1%
1 301
20.8%
8 177
 
12.2%
9 124
 
8.6%
0 93
 
6.4%
3 73
 
5.0%
4 49
 
3.4%
5 41
 
2.8%
7 40
 
2.8%
6 26
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 522
35.4%
1 301
20.4%
8 177
 
12.0%
9 124
 
8.4%
0 93
 
6.3%
3 73
 
5.0%
4 49
 
3.3%
5 41
 
2.8%
7 40
 
2.7%
- 27
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 522
35.4%
1 301
20.4%
8 177
 
12.0%
9 124
 
8.4%
0 93
 
6.3%
3 73
 
5.0%
4 49
 
3.3%
5 41
 
2.8%
7 40
 
2.7%
- 27
 
1.8%
Distinct234
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T17:57:56.188784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length24.688797
Min length17

Characters and Unicode

Total characters5950
Distinct characters152
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

Unique229 ?
Unique (%)95.0%

Sample

1st row서울특별시 은평구 역촌동 41-52
2nd row서울특별시 은평구 증산동 223-28 디엠씨 자이2단지(DMC 자이2단지)
3rd row서울특별시 은평구 갈현동 394-15 3층
4th row서울특별시 은평구 수색동 317-1
5th row서울특별시 은평구 갈현동 산 418-18
ValueCountFrequency (%)
서울특별시 241
20.0%
은평구 240
20.0%
응암동 48
 
4.0%
역촌동 33
 
2.7%
갈현동 30
 
2.5%
대조동 26
 
2.2%
녹번동 26
 
2.2%
2층 23
 
1.9%
불광동 21
 
1.7%
증산동 18
 
1.5%
Other values (321) 496
41.3%
2024-05-11T17:57:56.533708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1139
19.1%
1 278
 
4.7%
250
 
4.2%
248
 
4.2%
245
 
4.1%
243
 
4.1%
243
 
4.1%
241
 
4.1%
241
 
4.1%
241
 
4.1%
Other values (142) 2581
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3238
54.4%
Decimal Number 1265
 
21.3%
Space Separator 1139
 
19.1%
Dash Punctuation 222
 
3.7%
Close Punctuation 33
 
0.6%
Open Punctuation 33
 
0.6%
Uppercase Letter 12
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
250
 
7.7%
248
 
7.7%
245
 
7.6%
243
 
7.5%
243
 
7.5%
241
 
7.4%
241
 
7.4%
241
 
7.4%
241
 
7.4%
106
 
3.3%
Other values (121) 939
29.0%
Decimal Number
ValueCountFrequency (%)
1 278
22.0%
2 236
18.7%
3 131
10.4%
4 122
9.6%
0 109
 
8.6%
8 93
 
7.4%
5 93
 
7.4%
7 78
 
6.2%
6 70
 
5.5%
9 55
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
M 3
25.0%
S 2
16.7%
D 2
16.7%
C 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
/ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3238
54.4%
Common 2700
45.4%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
250
 
7.7%
248
 
7.7%
245
 
7.6%
243
 
7.5%
243
 
7.5%
241
 
7.4%
241
 
7.4%
241
 
7.4%
241
 
7.4%
106
 
3.3%
Other values (121) 939
29.0%
Common
ValueCountFrequency (%)
1139
42.2%
1 278
 
10.3%
2 236
 
8.7%
- 222
 
8.2%
3 131
 
4.9%
4 122
 
4.5%
0 109
 
4.0%
8 93
 
3.4%
5 93
 
3.4%
7 78
 
2.9%
Other values (6) 199
 
7.4%
Latin
ValueCountFrequency (%)
B 4
33.3%
M 3
25.0%
S 2
16.7%
D 2
16.7%
C 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3238
54.4%
ASCII 2712
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1139
42.0%
1 278
 
10.3%
2 236
 
8.7%
- 222
 
8.2%
3 131
 
4.8%
4 122
 
4.5%
0 109
 
4.0%
8 93
 
3.4%
5 93
 
3.4%
7 78
 
2.9%
Other values (11) 211
 
7.8%
Hangul
ValueCountFrequency (%)
250
 
7.7%
248
 
7.7%
245
 
7.6%
243
 
7.5%
243
 
7.5%
241
 
7.4%
241
 
7.4%
241
 
7.4%
241
 
7.4%
106
 
3.3%
Other values (121) 939
29.0%

도로명주소
Text

MISSING 

Distinct181
Distinct (%)98.9%
Missing58
Missing (%)24.1%
Memory size2.0 KiB
2024-05-11T17:57:56.776241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length31.863388
Min length22

Characters and Unicode

Total characters5831
Distinct characters151
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

Unique179 ?
Unique (%)97.8%

Sample

1st row서울특별시 은평구 진흥로 51, 2층 (역촌동)
2nd row서울특별시 은평구 수색로 217-1, 405호 (증산동, 디엠씨 자이2단지(DMC 자이2단지))
3rd row서울특별시 은평구 통일로 896-1 (불광동)
4th row서울특별시 은평구 갈현로33길 3 (갈현동)
5th row서울특별시 은평구 연서로26길 18 (대조동)
ValueCountFrequency (%)
서울특별시 183
 
15.8%
은평구 182
 
15.7%
1층 26
 
2.2%
응암동 26
 
2.2%
역촌동 25
 
2.2%
2층 21
 
1.8%
불광동 18
 
1.6%
신사동 18
 
1.6%
통일로 17
 
1.5%
은평로 17
 
1.5%
Other values (340) 624
53.9%
2024-05-11T17:57:57.153210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
974
 
16.7%
1 253
 
4.3%
231
 
4.0%
217
 
3.7%
215
 
3.7%
) 201
 
3.4%
( 201
 
3.4%
, 199
 
3.4%
196
 
3.4%
190
 
3.3%
Other values (141) 2954
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3257
55.9%
Space Separator 974
 
16.7%
Decimal Number 941
 
16.1%
Close Punctuation 201
 
3.4%
Open Punctuation 201
 
3.4%
Other Punctuation 199
 
3.4%
Dash Punctuation 48
 
0.8%
Uppercase Letter 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
231
 
7.1%
217
 
6.7%
215
 
6.6%
196
 
6.0%
190
 
5.8%
183
 
5.6%
183
 
5.6%
183
 
5.6%
183
 
5.6%
180
 
5.5%
Other values (120) 1296
39.8%
Decimal Number
ValueCountFrequency (%)
1 253
26.9%
2 155
16.5%
3 126
13.4%
0 87
 
9.2%
7 63
 
6.7%
4 59
 
6.3%
6 54
 
5.7%
8 51
 
5.4%
5 50
 
5.3%
9 43
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
40.0%
M 2
20.0%
D 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%
S 1
 
10.0%
Space Separator
ValueCountFrequency (%)
974
100.0%
Close Punctuation
ValueCountFrequency (%)
) 201
100.0%
Open Punctuation
ValueCountFrequency (%)
( 201
100.0%
Other Punctuation
ValueCountFrequency (%)
, 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3257
55.9%
Common 2564
44.0%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
231
 
7.1%
217
 
6.7%
215
 
6.6%
196
 
6.0%
190
 
5.8%
183
 
5.6%
183
 
5.6%
183
 
5.6%
183
 
5.6%
180
 
5.5%
Other values (120) 1296
39.8%
Common
ValueCountFrequency (%)
974
38.0%
1 253
 
9.9%
) 201
 
7.8%
( 201
 
7.8%
, 199
 
7.8%
2 155
 
6.0%
3 126
 
4.9%
0 87
 
3.4%
7 63
 
2.5%
4 59
 
2.3%
Other values (5) 246
 
9.6%
Latin
ValueCountFrequency (%)
B 4
40.0%
M 2
20.0%
D 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%
S 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3257
55.9%
ASCII 2574
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
974
37.8%
1 253
 
9.8%
) 201
 
7.8%
( 201
 
7.8%
, 199
 
7.7%
2 155
 
6.0%
3 126
 
4.9%
0 87
 
3.4%
7 63
 
2.4%
4 59
 
2.3%
Other values (11) 256
 
9.9%
Hangul
ValueCountFrequency (%)
231
 
7.1%
217
 
6.7%
215
 
6.6%
196
 
6.0%
190
 
5.8%
183
 
5.6%
183
 
5.6%
183
 
5.6%
183
 
5.6%
180
 
5.5%
Other values (120) 1296
39.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct103
Distinct (%)57.2%
Missing61
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean3433.9944
Minimum3304
Maximum6727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:57:57.270740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3304
5-th percentile3320.95
Q13381.5
median3417.5
Q33459
95-th percentile3498
Maximum6727
Range3423
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation253.02442
Coefficient of variation (CV)0.073682245
Kurtosis162.69542
Mean3433.9944
Median Absolute Deviation (MAD)41.5
Skewness12.439517
Sum618119
Variance64021.358
MonotonicityNot monotonic
2024-05-11T17:57:57.385217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3453 9
 
3.7%
3450 5
 
2.1%
3345 5
 
2.1%
3385 4
 
1.7%
3470 4
 
1.7%
3459 4
 
1.7%
3458 4
 
1.7%
3368 3
 
1.2%
3430 3
 
1.2%
3500 3
 
1.2%
Other values (93) 136
56.4%
(Missing) 61
25.3%
ValueCountFrequency (%)
3304 1
0.4%
3307 2
0.8%
3311 1
0.4%
3314 2
0.8%
3315 2
0.8%
3320 1
0.4%
3321 2
0.8%
3322 1
0.4%
3325 1
0.4%
3328 1
0.4%
ValueCountFrequency (%)
6727 1
 
0.4%
3505 2
0.8%
3504 1
 
0.4%
3501 1
 
0.4%
3500 3
1.2%
3498 2
0.8%
3497 3
1.2%
3495 1
 
0.4%
3494 1
 
0.4%
3493 2
0.8%
Distinct236
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T17:57:57.611140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length7.8713693
Min length2

Characters and Unicode

Total characters1897
Distinct characters290
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)95.9%

Sample

1st row진광시스템(주)
2nd row(주)보경실업
3rd row한영정수산업사
4th row한양환경개발
5th row기형상사
ValueCountFrequency (%)
주식회사 26
 
9.0%
주)해담솔 2
 
0.7%
j&j크린공영 2
 
0.7%
제이피앤아이 2
 
0.7%
협동조합 2
 
0.7%
그린환경 2
 
0.7%
태림주택종합관리(주 2
 
0.7%
주)한빛티엠에스 2
 
0.7%
밝은세상 1
 
0.3%
광동 1
 
0.3%
Other values (248) 248
85.5%
2024-05-11T17:57:57.980083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
7.1%
) 106
 
5.6%
( 102
 
5.4%
54
 
2.8%
51
 
2.7%
49
 
2.6%
39
 
2.1%
35
 
1.8%
35
 
1.8%
33
 
1.7%
Other values (280) 1259
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1589
83.8%
Close Punctuation 106
 
5.6%
Open Punctuation 102
 
5.4%
Space Separator 49
 
2.6%
Uppercase Letter 31
 
1.6%
Lowercase Letter 10
 
0.5%
Other Punctuation 7
 
0.4%
Decimal Number 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
134
 
8.4%
54
 
3.4%
51
 
3.2%
39
 
2.5%
35
 
2.2%
35
 
2.2%
33
 
2.1%
30
 
1.9%
30
 
1.9%
27
 
1.7%
Other values (251) 1121
70.5%
Uppercase Letter
ValueCountFrequency (%)
C 5
16.1%
S 5
16.1%
J 4
12.9%
O 3
9.7%
T 2
 
6.5%
E 2
 
6.5%
N 2
 
6.5%
H 1
 
3.2%
I 1
 
3.2%
D 1
 
3.2%
Other values (5) 5
16.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
30.0%
a 3
30.0%
n 1
 
10.0%
e 1
 
10.0%
l 1
 
10.0%
o 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
& 3
42.9%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1588
83.7%
Common 267
 
14.1%
Latin 41
 
2.2%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
134
 
8.4%
54
 
3.4%
51
 
3.2%
39
 
2.5%
35
 
2.2%
35
 
2.2%
33
 
2.1%
30
 
1.9%
30
 
1.9%
27
 
1.7%
Other values (250) 1120
70.5%
Latin
ValueCountFrequency (%)
C 5
12.2%
S 5
12.2%
J 4
 
9.8%
c 3
 
7.3%
O 3
 
7.3%
a 3
 
7.3%
T 2
 
4.9%
E 2
 
4.9%
N 2
 
4.9%
H 1
 
2.4%
Other values (11) 11
26.8%
Common
ValueCountFrequency (%)
) 106
39.7%
( 102
38.2%
49
18.4%
. 4
 
1.5%
& 3
 
1.1%
1 1
 
0.4%
2 1
 
0.4%
- 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1588
83.7%
ASCII 308
 
16.2%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
134
 
8.4%
54
 
3.4%
51
 
3.2%
39
 
2.5%
35
 
2.2%
35
 
2.2%
33
 
2.1%
30
 
1.9%
30
 
1.9%
27
 
1.7%
Other values (250) 1120
70.5%
ASCII
ValueCountFrequency (%)
) 106
34.4%
( 102
33.1%
49
15.9%
C 5
 
1.6%
S 5
 
1.6%
J 4
 
1.3%
. 4
 
1.3%
& 3
 
1.0%
c 3
 
1.0%
O 3
 
1.0%
Other values (19) 24
 
7.8%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct222
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1999-10-05 00:00:00
Maximum2024-04-25 14:08:26
2024-05-11T17:57:58.108037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:57:58.225273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
I
180 
U
61 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 180
74.7%
U 61
 
25.3%

Length

2024-05-11T17:57:58.341178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:58.418393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 180
74.7%
u 61
 
25.3%
Distinct92
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-05-11T17:57:58.515115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:57:58.625027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
건물위생관리업
240 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0124481
Min length7

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 240
99.6%
건물위생관리업 기타 1
 
0.4%

Length

2024-05-11T17:57:58.752624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:58.845280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 241
99.6%
기타 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)82.0%
Missing8
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean192748.19
Minimum190028.98
Maximum202336.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:57:58.961730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190028.98
5-th percentile191503.74
Q1192347.32
median192729.67
Q3193156.56
95-th percentile193941.27
Maximum202336.84
Range12307.857
Interquartile range (IQR)809.24518

Descriptive statistics

Standard deviation1010.8206
Coefficient of variation (CV)0.0052442548
Kurtosis34.650822
Mean192748.19
Median Absolute Deviation (MAD)417.56941
Skewness3.4778272
Sum44910329
Variance1021758.4
MonotonicityNot monotonic
2024-05-11T17:57:59.096507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192600.451566859 9
 
3.7%
192917.802185102 5
 
2.1%
193156.561270858 5
 
2.1%
192783.308940152 3
 
1.2%
193519.842696237 2
 
0.8%
192008.407936712 2
 
0.8%
192467.624181515 2
 
0.8%
192563.874496397 2
 
0.8%
192085.158902114 2
 
0.8%
192680.746837163 2
 
0.8%
Other values (181) 199
82.6%
(Missing) 8
 
3.3%
ValueCountFrequency (%)
190028.982761489 1
0.4%
190083.674433147 2
0.8%
190508.444272436 1
0.4%
190532.78702044 1
0.4%
190667.735544513 1
0.4%
190913.630942746 1
0.4%
191058.008397579 1
0.4%
191117.479985364 2
0.8%
191459.014199221 1
0.4%
191460.615806283 1
0.4%
ValueCountFrequency (%)
202336.840042177 1
0.4%
195358.535748819 2
0.8%
194367.970247735 1
0.4%
194279.733222003 1
0.4%
194260.483039208 1
0.4%
194157.526710123 2
0.8%
194149.311652603 1
0.4%
194101.134591972 1
0.4%
194032.3439259 1
0.4%
193974.930174692 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)82.0%
Missing8
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean455773.87
Minimum442859.79
Maximum461455.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:57:59.233342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442859.79
5-th percentile453530.56
Q1454814.1
median455760.02
Q3456814.3
95-th percentile458031.33
Maximum461455.88
Range18596.083
Interquartile range (IQR)2000.1947

Descriptive statistics

Standard deviation1718.9715
Coefficient of variation (CV)0.0037715447
Kurtosis13.323982
Mean455773.87
Median Absolute Deviation (MAD)1013.6947
Skewness-1.4562537
Sum1.0619531 × 108
Variance2954863
MonotonicityNot monotonic
2024-05-11T17:57:59.376186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455197.91922534 9
 
3.7%
453966.944976326 5
 
2.1%
457559.907742276 5
 
2.1%
458021.403650943 3
 
1.2%
456728.319721599 2
 
0.8%
455031.178100729 2
 
0.8%
455618.001373317 2
 
0.8%
456570.084566278 2
 
0.8%
455071.308631398 2
 
0.8%
454110.082534622 2
 
0.8%
Other values (181) 199
82.6%
(Missing) 8
 
3.3%
ValueCountFrequency (%)
442859.79398989 1
0.4%
452946.246733537 1
0.4%
453196.900861084 2
0.8%
453201.795288361 1
0.4%
453237.627360387 1
0.4%
453244.229758597 2
0.8%
453245.327026837 1
0.4%
453356.681279568 1
0.4%
453516.699551356 1
0.4%
453519.463895899 1
0.4%
ValueCountFrequency (%)
461455.876513588 2
0.8%
460763.547867283 1
0.4%
459156.947874 1
0.4%
458291.029836776 1
0.4%
458261.247322256 1
0.4%
458256.056907266 1
0.4%
458182.795406051 1
0.4%
458118.947090882 1
0.4%
458051.808468089 2
0.8%
458046.211064805 1
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
건물위생관리업
201 
<NA>
39 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.526971
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 201
83.4%
<NA> 39
 
16.2%
건물위생관리업 기타 1
 
0.4%

Length

2024-05-11T17:57:59.523740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:57:59.610374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 202
83.5%
na 39
 
16.1%
기타 1
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.4%
Missing70
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean1.6432749
Minimum0
Maximum15
Zeros106
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:57:59.693503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6404542
Coefficient of variation (CV)1.6068245
Kurtosis6.8931434
Mean1.6432749
Median Absolute Deviation (MAD)0
Skewness2.2163748
Sum281
Variance6.9719986
MonotonicityNot monotonic
2024-05-11T17:57:59.796547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 106
44.0%
5 17
 
7.1%
4 14
 
5.8%
3 14
 
5.8%
2 9
 
3.7%
1 3
 
1.2%
6 2
 
0.8%
9 2
 
0.8%
15 2
 
0.8%
10 1
 
0.4%
(Missing) 70
29.0%
ValueCountFrequency (%)
0 106
44.0%
1 3
 
1.2%
2 9
 
3.7%
3 14
 
5.8%
4 14
 
5.8%
5 17
 
7.1%
6 2
 
0.8%
7 1
 
0.4%
9 2
 
0.8%
10 1
 
0.4%
ValueCountFrequency (%)
15 2
 
0.8%
10 1
 
0.4%
9 2
 
0.8%
7 1
 
0.4%
6 2
 
0.8%
5 17
7.1%
4 14
5.8%
3 14
5.8%
2 9
3.7%
1 3
 
1.2%
Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
116 
<NA>
75 
1
44 
5
 
3
2
 
2

Length

Max length4
Median length1
Mean length1.93361
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 116
48.1%
<NA> 75
31.1%
1 44
 
18.3%
5 3
 
1.2%
2 2
 
0.8%
4 1
 
0.4%

Length

2024-05-11T17:57:59.927678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:00.031351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 116
48.1%
na 75
31.1%
1 44
 
18.3%
5 3
 
1.2%
2 2
 
0.8%
4 1
 
0.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)7.6%
Missing110
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean2.0152672
Minimum0
Maximum14
Zeros38
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:58:00.122136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile5.5
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2971043
Coefficient of variation (CV)1.139851
Kurtosis7.2335759
Mean2.0152672
Median Absolute Deviation (MAD)1
Skewness2.177361
Sum264
Variance5.2766882
MonotonicityNot monotonic
2024-05-11T17:58:00.225959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 38
 
15.8%
2 33
 
13.7%
1 26
 
10.8%
5 12
 
5.0%
3 8
 
3.3%
4 7
 
2.9%
6 3
 
1.2%
8 2
 
0.8%
14 1
 
0.4%
12 1
 
0.4%
(Missing) 110
45.6%
ValueCountFrequency (%)
0 38
15.8%
1 26
10.8%
2 33
13.7%
3 8
 
3.3%
4 7
 
2.9%
5 12
 
5.0%
6 3
 
1.2%
8 2
 
0.8%
12 1
 
0.4%
14 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
12 1
 
0.4%
8 2
 
0.8%
6 3
 
1.2%
5 12
 
5.0%
4 7
 
2.9%
3 8
 
3.3%
2 33
13.7%
1 26
10.8%
0 38
15.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)10.0%
Missing141
Missing (%)58.5%
Infinite0
Infinite (%)0.0%
Mean2.34
Minimum0
Maximum14
Zeros19
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:58:00.339157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3665173
Coefficient of variation (CV)1.0113322
Kurtosis7.1886655
Mean2.34
Median Absolute Deviation (MAD)1
Skewness2.1546376
Sum234
Variance5.600404
MonotonicityNot monotonic
2024-05-11T17:58:00.439606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 27
 
11.2%
1 23
 
9.5%
0 19
 
7.9%
5 12
 
5.0%
3 7
 
2.9%
4 6
 
2.5%
6 3
 
1.2%
8 1
 
0.4%
14 1
 
0.4%
12 1
 
0.4%
(Missing) 141
58.5%
ValueCountFrequency (%)
0 19
7.9%
1 23
9.5%
2 27
11.2%
3 7
 
2.9%
4 6
 
2.5%
5 12
5.0%
6 3
 
1.2%
8 1
 
0.4%
12 1
 
0.4%
14 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
12 1
 
0.4%
8 1
 
0.4%
6 3
 
1.2%
5 12
5.0%
4 6
 
2.5%
3 7
 
2.9%
2 27
11.2%
1 23
9.5%
0 19
7.9%
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
164 
0
66 
1
 
11

Length

Max length4
Median length4
Mean length3.0414938
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 164
68.0%
0 66
27.4%
1 11
 
4.6%

Length

2024-05-11T17:58:00.563516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:00.670615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 164
68.0%
0 66
27.4%
1 11
 
4.6%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
190 
0
40 
1
 
10
5
 
1

Length

Max length4
Median length4
Mean length3.3651452
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 190
78.8%
0 40
 
16.6%
1 10
 
4.1%
5 1
 
0.4%

Length

2024-05-11T17:58:00.769595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:00.878723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 190
78.8%
0 40
 
16.6%
1 10
 
4.1%
5 1
 
0.4%

한실수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
146 
<NA>
95 

Length

Max length4
Median length1
Mean length2.1825726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 146
60.6%
<NA> 95
39.4%

Length

2024-05-11T17:58:00.992320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:01.094892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
60.6%
na 95
39.4%

양실수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
146 
<NA>
95 

Length

Max length4
Median length1
Mean length2.1825726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 146
60.6%
<NA> 95
39.4%

Length

2024-05-11T17:58:01.193911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:01.286461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
60.6%
na 95
39.4%

욕실수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
146 
<NA>
95 

Length

Max length4
Median length1
Mean length2.1825726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 146
60.6%
<NA> 95
39.4%

Length

2024-05-11T17:58:01.370143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:01.454584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
60.6%
na 95
39.4%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing44
Missing (%)18.3%
Memory size614.0 B
False
197 
(Missing)
44 
ValueCountFrequency (%)
False 197
81.7%
(Missing) 44
 
18.3%
2024-05-11T17:58:01.525997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
146 
<NA>
95 

Length

Max length4
Median length1
Mean length2.1825726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 146
60.6%
<NA> 95
39.4%

Length

2024-05-11T17:58:01.613595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:01.703783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
60.6%
na 95
39.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
156 
임대
80 
자가
 
5

Length

Max length4
Median length4
Mean length3.2946058
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> 156
64.7%
임대 80
33.2%
자가 5
 
2.1%

Length

2024-05-11T17:58:01.793622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:02.178030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 156
64.7%
임대 80
33.2%
자가 5
 
2.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
121 
0
120 

Length

Max length4
Median length4
Mean length2.5062241
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> 121
50.2%
0 120
49.8%

Length

2024-05-11T17:58:02.275735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:02.381160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
50.2%
0 120
49.8%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
183 
0
44 
1
 
11
15
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.2821577
Min length1

Unique

Unique3 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 183
75.9%
0 44
 
18.3%
1 11
 
4.6%
15 1
 
0.4%
3 1
 
0.4%
2 1
 
0.4%

Length

2024-05-11T17:58:02.476983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:02.578832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 183
75.9%
0 44
 
18.3%
1 11
 
4.6%
15 1
 
0.4%
3 1
 
0.4%
2 1
 
0.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)19.7%
Missing180
Missing (%)74.7%
Infinite0
Infinite (%)0.0%
Mean2.6721311
Minimum0
Maximum50
Zeros26
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T17:58:02.665019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile11
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.9730943
Coefficient of variation (CV)2.6095629
Kurtosis36.322652
Mean2.6721311
Median Absolute Deviation (MAD)1
Skewness5.5845914
Sum163
Variance48.624044
MonotonicityNot monotonic
2024-05-11T17:58:02.761402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 26
 
10.8%
1 16
 
6.6%
2 6
 
2.5%
3 3
 
1.2%
4 3
 
1.2%
50 1
 
0.4%
10 1
 
0.4%
6 1
 
0.4%
12 1
 
0.4%
16 1
 
0.4%
Other values (2) 2
 
0.8%
(Missing) 180
74.7%
ValueCountFrequency (%)
0 26
10.8%
1 16
6.6%
2 6
 
2.5%
3 3
 
1.2%
4 3
 
1.2%
6 1
 
0.4%
9 1
 
0.4%
10 1
 
0.4%
11 1
 
0.4%
12 1
 
0.4%
ValueCountFrequency (%)
50 1
 
0.4%
16 1
 
0.4%
12 1
 
0.4%
11 1
 
0.4%
10 1
 
0.4%
9 1
 
0.4%
6 1
 
0.4%
4 3
1.2%
3 3
1.2%
2 6
2.5%

회수건조수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
130 
0
111 

Length

Max length4
Median length4
Mean length2.6182573
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> 130
53.9%
0 111
46.1%

Length

2024-05-11T17:58:02.883144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:02.968703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
53.9%
0 111
46.1%

침대수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
136 
0
105 

Length

Max length4
Median length4
Mean length2.6929461
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> 136
56.4%
0 105
43.6%

Length

2024-05-11T17:58:03.082379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:58:03.207494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
56.4%
0 105
43.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing39
Missing (%)16.2%
Memory size614.0 B
False
202 
(Missing)
39 
ValueCountFrequency (%)
False 202
83.8%
(Missing) 39
 
16.2%
2024-05-11T17:58:03.295544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031100003110000-206-1987-0212419870916<NA>3폐업2폐업20200623<NA><NA><NA>02 384676167.21122899서울특별시 은평구 역촌동 41-52서울특별시 은평구 진흥로 51, 2층 (역촌동)3408진광시스템(주)2020-07-03 11:32:52U2020-07-05 02:40:00.0건물위생관리업192890.62884455496.445463건물위생관리업00220<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131100003110000-206-1987-021251987-06-01<NA>3폐업2폐업2023-03-08<NA><NA><NA>02 718422197.29122-941서울특별시 은평구 증산동 223-28 디엠씨 자이2단지(DMC 자이2단지)서울특별시 은평구 수색로 217-1, 405호 (증산동, 디엠씨 자이2단지(DMC 자이2단지))3504(주)보경실업2023-03-08 10:59:46U2022-12-02 23:00:00.0건물위생관리업191058.008398452946.246734<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231100003110000-206-1992-0212419921230<NA>3폐업2폐업20030624<NA><NA><NA>0203820382318.48122808서울특별시 은평구 갈현동 394-15 3층<NA><NA>한영정수산업사2003-06-24 00:00:00I2018-08-31 23:59:59.0건물위생관리업192792.887634457717.426213건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331100003110000-206-1993-0214019931229<NA>3폐업2폐업20030624<NA><NA><NA>0203080308695.37122875서울특별시 은평구 수색동 317-1<NA><NA>한양환경개발2003-06-24 00:00:00I2018-08-31 23:59:59.0건물위생관리업190083.674433453779.973027건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431100003110000-206-1995-0212519950919<NA>3폐업2폐업19980904<NA><NA><NA>0203856516596.25122050서울특별시 은평구 갈현동 산 418-18<NA><NA>기형상사2001-09-28 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531100003110000-206-1996-0212619960115<NA>3폐업2폐업19990514<NA><NA><NA>02 8391600896.91122100서울특별시 은평구 증산동 산 158-25<NA><NA>영원실업(주)2001-09-28 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631100003110000-206-1996-0212719960924<NA>3폐업2폐업19980923<NA><NA><NA>02 35916742,915.16122020서울특별시 은평구 녹번동 산 86 은평빌딩 200동<NA><NA>(주)동주개발2001-09-28 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731100003110000-206-1997-0212819970502<NA>3폐업2폐업20060412<NA><NA><NA>0231510181551.64122951서울특별시 은평구 응암동 285-31<NA><NA>삼경용역(주)2004-11-16 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
831100003110000-206-1997-0212919970816<NA>3폐업2폐업20121012<NA><NA><NA>02 3892281113.79122814서울특별시 은평구 갈현동 499-20<NA><NA>현대기획2012-10-12 15:36:52I2018-08-31 23:59:59.0건물위생관리업192446.951926457243.131124건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931100003110000-206-1997-0213019971014<NA>3폐업2폐업19991005<NA><NA><NA>02 38621822,076.96122070서울특별시 은평구 역촌동 산 17-1<NA><NA>주)이글메너지먼트1999-10-05 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
23131100003110000-206-2023-000032023-05-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.00122-837서울특별시 은평구 대조동 6-9서울특별시 은평구 통일로 739, 3층 301호 (대조동)3396한국위생관리2023-05-24 16:09:15I2022-12-04 22:06:00.0건물위생관리업193630.612534456543.824997<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23231100003110000-206-2023-000042023-05-31<NA>1영업/정상1영업<NA><NA><NA><NA>02 695260523.30122-959서울특별시 은평구 갈현동 452-28서울특별시 은평구 연서로27길 22, 지층 디-18호 (갈현동)3331(주)제이에스토탈매니지먼트2023-05-31 14:27:45I2022-12-06 00:02:00.0건물위생관리업192625.57754457350.179826<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23331100003110000-206-2023-000062023-08-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 354 540060.72122-200서울특별시 은평구 진관동 277-17서울특별시 은평구 대서문길 36, B동 215, 216호 (진관동)3307스마일클린2023-08-23 15:35:32I2022-12-07 22:05:00.0건물위생관리업195358.535749461455.876514<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23431100003110000-206-2023-000072023-09-06<NA>1영업/정상1영업<NA><NA><NA><NA>0269251780159.00122-947서울특별시 은평구 대조동 84-7서울특별시 은평구 통일로71길 8, 지하1층 (대조동)3391다은보호작업장2023-09-06 15:59:27I2022-12-09 00:08:00.0건물위생관리업193402.553027456847.885474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23531100003110000-206-2023-000082023-11-21<NA>1영업/정상1영업<NA><NA><NA><NA>0269547848204.68122-814서울특별시 은평구 갈현동 511-29 데미안빌 지층 01호서울특별시 은평구 갈현로23길 15, 지층 01호 (갈현동, 데미안빌)3325(주)정윤이앤지2023-11-21 16:10:12I2022-10-31 22:03:00.0건물위생관리업192194.088008457167.7859<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23631100003110000-206-2023-000092023-11-29<NA>3폐업2폐업2024-04-18<NA><NA><NA><NA>0.00122-896서울특별시 은평구 역촌동 25-122서울특별시 은평구 진흥로7길 18, 1층 3호 (역촌동)3403삼성 클린 방역시스템2024-04-24 15:40:44U2023-12-03 22:06:00.0건물위생관리업192836.637992455803.82258<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23731100003110000-206-2024-000012024-02-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.64122-901서울특별시 은평구 역촌동 66-46서울특별시 은평구 연서로3길 12-4, 202호 (역촌동)3418(주)세한에스에이치2024-02-23 10:55:37I2023-12-01 22:06:00.0건물위생관리업192381.950279455587.487033<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23831100003110000-206-2024-000022024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 357111620.00122-838서울특별시 은평구 대조동 48-80 101호서울특별시 은평구 서오릉로 130, 101호 (대조동)3394신성크린환경2024-03-04 17:44:40I2023-12-03 00:06:00.0건물위생관리업192735.08261456497.816448<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23931100003110000-206-2024-000032024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.00122-901서울특별시 은평구 역촌동 64-48 1층 좌측서울특별시 은평구 연서로5길 15, 1층 좌측호 (역촌동)3418오버클린2024-04-01 16:37:04I2023-12-04 00:03:00.0건물위생관리업192312.096976455735.017534<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24031100003110000-206-2024-000042024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.40122-896서울특별시 은평구 역촌동 25-122 1층 3호서울특별시 은평구 진흥로7길 18, 1층 3호 (역촌동)3403우림아이엔씨2024-04-25 14:08:26I2023-12-03 22:07:00.0건물위생관리업192836.637992455803.82258<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>