Overview

Dataset statistics

Number of variables47
Number of observations156
Missing cells1694
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.7 KiB
Average record size in memory404.8 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
Numeric8
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-19289/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.4%)Imbalance
여성종사자수 is highly imbalanced (71.4%)Imbalance
다중이용업소여부 is highly imbalanced (93.4%)Imbalance
인허가취소일자 has 156 (100.0%) missing valuesMissing
폐업일자 has 50 (32.1%) missing valuesMissing
휴업시작일자 has 156 (100.0%) missing valuesMissing
휴업종료일자 has 156 (100.0%) missing valuesMissing
재개업일자 has 156 (100.0%) missing valuesMissing
전화번호 has 30 (19.2%) missing valuesMissing
도로명주소 has 47 (30.1%) missing valuesMissing
도로명우편번호 has 48 (30.8%) missing valuesMissing
좌표정보(X) has 5 (3.2%) missing valuesMissing
좌표정보(Y) has 5 (3.2%) missing valuesMissing
건물지상층수 has 38 (24.4%) missing valuesMissing
건물지하층수 has 48 (30.8%) missing valuesMissing
사용시작지상층 has 58 (37.2%) missing valuesMissing
사용끝지상층 has 74 (47.4%) missing valuesMissing
발한실여부 has 35 (22.4%) missing valuesMissing
조건부허가신고사유 has 156 (100.0%) missing valuesMissing
조건부허가시작일자 has 156 (100.0%) missing valuesMissing
조건부허가종료일자 has 156 (100.0%) missing valuesMissing
남성종사자수 has 136 (87.2%) missing valuesMissing
다중이용업소여부 has 28 (17.9%) 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 58 (37.2%) zerosZeros
건물지하층수 has 62 (39.7%) zerosZeros
사용시작지상층 has 14 (9.0%) zerosZeros
사용끝지상층 has 8 (5.1%) zerosZeros
남성종사자수 has 11 (7.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:00:37.854466
Analysis finished2024-05-11 06:00:38.863710
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3120000
156 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 156
100.0%

Length

2024-05-11T15:00:38.953522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:39.084475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 156
100.0%

관리번호
Text

UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:00:39.320920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3432
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

Unique156 ?
Unique (%)100.0%

Sample

1st row3120000-206-1992-00001
2nd row3120000-206-1993-00906
3rd row3120000-206-1994-00907
4th row3120000-206-1994-02183
5th row3120000-206-1994-02184
ValueCountFrequency (%)
3120000-206-1992-00001 1
 
0.6%
3120000-206-2014-00001 1
 
0.6%
3120000-206-2014-00010 1
 
0.6%
3120000-206-2012-00007 1
 
0.6%
3120000-206-2013-00001 1
 
0.6%
3120000-206-2013-00002 1
 
0.6%
3120000-206-2013-00003 1
 
0.6%
3120000-206-2013-00004 1
 
0.6%
3120000-206-2013-00005 1
 
0.6%
3120000-206-2014-00003 1
 
0.6%
Other values (146) 146
93.6%
2024-05-11T15:00:39.869480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1566
45.6%
2 516
 
15.0%
- 468
 
13.6%
1 298
 
8.7%
3 194
 
5.7%
6 188
 
5.5%
9 71
 
2.1%
4 43
 
1.3%
8 34
 
1.0%
7 29
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2964
86.4%
Dash Punctuation 468
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1566
52.8%
2 516
 
17.4%
1 298
 
10.1%
3 194
 
6.5%
6 188
 
6.3%
9 71
 
2.4%
4 43
 
1.5%
8 34
 
1.1%
7 29
 
1.0%
5 25
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 468
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1566
45.6%
2 516
 
15.0%
- 468
 
13.6%
1 298
 
8.7%
3 194
 
5.7%
6 188
 
5.5%
9 71
 
2.1%
4 43
 
1.3%
8 34
 
1.0%
7 29
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1566
45.6%
2 516
 
15.0%
- 468
 
13.6%
1 298
 
8.7%
3 194
 
5.7%
6 188
 
5.5%
9 71
 
2.1%
4 43
 
1.3%
8 34
 
1.0%
7 29
 
0.8%
Distinct149
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1992-12-10 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:00:40.118908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:00:40.361742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
106 
1
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 106
67.9%
1 50
32.1%

Length

2024-05-11T15:00:40.548274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:40.682274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 106
67.9%
1 50
32.1%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
106 
영업/정상
50 

Length

Max length5
Median length2
Mean length2.9615385
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 106
67.9%
영업/정상 50
32.1%

Length

2024-05-11T15:00:40.860024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:41.041809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 106
67.9%
영업/정상 50
32.1%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
106 
1
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 106
67.9%
1 50
32.1%

Length

2024-05-11T15:00:41.193367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:41.323321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 106
67.9%
1 50
32.1%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
106 
영업
50 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 106
67.9%
영업 50
32.1%

Length

2024-05-11T15:00:41.494894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:41.677450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 106
67.9%
영업 50
32.1%

폐업일자
Date

MISSING 

Distinct91
Distinct (%)85.8%
Missing50
Missing (%)32.1%
Memory size1.3 KiB
Minimum1996-10-10 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T15:00:41.889200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:00:42.108505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct122
Distinct (%)96.8%
Missing30
Missing (%)19.2%
Memory size1.3 KiB
2024-05-11T15:00:42.576537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6190476
Min length6

Characters and Unicode

Total characters1212
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

Unique118 ?
Unique (%)93.7%

Sample

1st row02 3644987
2nd row02 3227138
3rd row02 3078161
4th row02 7237091
5th row02 3655484
ValueCountFrequency (%)
02 75
35.5%
3241027 2
 
0.9%
3337074 2
 
0.9%
3137226 2
 
0.9%
60845130 2
 
0.9%
3252470 2
 
0.9%
430 1
 
0.5%
054 1
 
0.5%
8912 1
 
0.5%
323 1
 
0.5%
Other values (122) 122
57.8%
2024-05-11T15:00:43.202916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 206
17.0%
2 195
16.1%
3 179
14.8%
1 102
8.4%
97
8.0%
7 95
7.8%
6 92
7.6%
4 67
 
5.5%
8 60
 
5.0%
9 60
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1115
92.0%
Space Separator 97
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 206
18.5%
2 195
17.5%
3 179
16.1%
1 102
9.1%
7 95
8.5%
6 92
8.3%
4 67
 
6.0%
8 60
 
5.4%
9 60
 
5.4%
5 59
 
5.3%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 206
17.0%
2 195
16.1%
3 179
14.8%
1 102
8.4%
97
8.0%
7 95
7.8%
6 92
7.6%
4 67
 
5.5%
8 60
 
5.0%
9 60
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 206
17.0%
2 195
16.1%
3 179
14.8%
1 102
8.4%
97
8.0%
7 95
7.8%
6 92
7.6%
4 67
 
5.5%
8 60
 
5.0%
9 60
 
5.0%
Distinct113
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:00:43.663217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1666667
Min length3

Characters and Unicode

Total characters806
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

Unique93 ?
Unique (%)59.6%

Sample

1st row165.10
2nd row2,825.42
3rd row41.60
4th row72.30
5th row61.22
ValueCountFrequency (%)
33.00 10
 
6.4%
00 5
 
3.2%
10.00 4
 
2.6%
20.00 4
 
2.6%
99.00 4
 
2.6%
13.00 4
 
2.6%
35.00 3
 
1.9%
165.00 3
 
1.9%
30.00 3
 
1.9%
66.00 3
 
1.9%
Other values (103) 113
72.4%
2024-05-11T15:00:44.364854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 189
23.4%
. 156
19.4%
3 74
 
9.2%
1 74
 
9.2%
2 64
 
7.9%
6 49
 
6.1%
4 46
 
5.7%
5 45
 
5.6%
9 44
 
5.5%
7 32
 
4.0%
Other values (2) 33
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 646
80.1%
Other Punctuation 160
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 189
29.3%
3 74
 
11.5%
1 74
 
11.5%
2 64
 
9.9%
6 49
 
7.6%
4 46
 
7.1%
5 45
 
7.0%
9 44
 
6.8%
7 32
 
5.0%
8 29
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 156
97.5%
, 4
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 806
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 189
23.4%
. 156
19.4%
3 74
 
9.2%
1 74
 
9.2%
2 64
 
7.9%
6 49
 
6.1%
4 46
 
5.7%
5 45
 
5.6%
9 44
 
5.5%
7 32
 
4.0%
Other values (2) 33
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 806
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 189
23.4%
. 156
19.4%
3 74
 
9.2%
1 74
 
9.2%
2 64
 
7.9%
6 49
 
6.1%
4 46
 
5.7%
5 45
 
5.6%
9 44
 
5.5%
7 32
 
4.0%
Other values (2) 33
 
4.1%
Distinct65
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:00:44.703857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1025641
Min length6

Characters and Unicode

Total characters952
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 (%)20.5%

Sample

1st row120012
2nd row120824
3rd row120817
4th row120858
5th row120012
ValueCountFrequency (%)
120012 12
 
7.7%
120827 12
 
7.7%
120817 8
 
5.1%
120814 7
 
4.5%
120013 6
 
3.8%
120837 5
 
3.2%
120805 4
 
2.6%
120806 4
 
2.6%
120859 4
 
2.6%
120857 4
 
2.6%
Other values (55) 90
57.7%
2024-05-11T15:00:45.225709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 233
24.5%
1 219
23.0%
2 204
21.4%
8 116
12.2%
7 44
 
4.6%
3 36
 
3.8%
4 26
 
2.7%
5 25
 
2.6%
6 25
 
2.6%
- 16
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
98.3%
Dash Punctuation 16
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 233
24.9%
1 219
23.4%
2 204
21.8%
8 116
12.4%
7 44
 
4.7%
3 36
 
3.8%
4 26
 
2.8%
5 25
 
2.7%
6 25
 
2.7%
9 8
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 233
24.5%
1 219
23.0%
2 204
21.4%
8 116
12.2%
7 44
 
4.6%
3 36
 
3.8%
4 26
 
2.7%
5 25
 
2.6%
6 25
 
2.6%
- 16
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 233
24.5%
1 219
23.0%
2 204
21.4%
8 116
12.2%
7 44
 
4.6%
3 36
 
3.8%
4 26
 
2.7%
5 25
 
2.6%
6 25
 
2.6%
- 16
 
1.7%
Distinct146
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:00:45.642475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length26.570513
Min length17

Characters and Unicode

Total characters4145
Distinct characters134
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

Unique136 ?
Unique (%)87.2%

Sample

1st row서울특별시 서대문구 충정로2가 191 (14층)
2nd row서울특별시 서대문구 연희동 92-18 3층 300호
3rd row서울특별시 서대문구 북가좌동 392-26 (2층)
4th row서울특별시 서대문구 홍제동 307-12
5th row서울특별시 서대문구 충정로2가 191 유원골든타워빌딩1409
ValueCountFrequency (%)
서울특별시 156
20.2%
서대문구 156
20.2%
북가좌동 31
 
4.0%
연희동 29
 
3.8%
홍제동 17
 
2.2%
2층 16
 
2.1%
충정로2가 16
 
2.1%
충정로3가 13
 
1.7%
1층 12
 
1.6%
남가좌동 11
 
1.4%
Other values (216) 316
40.9%
2024-05-11T15:00:46.195425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
735
17.7%
314
 
7.6%
1 178
 
4.3%
166
 
4.0%
159
 
3.8%
158
 
3.8%
157
 
3.8%
156
 
3.8%
156
 
3.8%
156
 
3.8%
Other values (124) 1810
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2330
56.2%
Decimal Number 860
 
20.7%
Space Separator 735
 
17.7%
Dash Punctuation 128
 
3.1%
Close Punctuation 36
 
0.9%
Open Punctuation 36
 
0.9%
Uppercase Letter 12
 
0.3%
Other Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
314
13.5%
166
 
7.1%
159
 
6.8%
158
 
6.8%
157
 
6.7%
156
 
6.7%
156
 
6.7%
156
 
6.7%
133
 
5.7%
75
 
3.2%
Other values (100) 700
30.0%
Decimal Number
ValueCountFrequency (%)
1 178
20.7%
3 148
17.2%
2 140
16.3%
0 72
8.4%
4 57
 
6.6%
9 57
 
6.6%
7 57
 
6.6%
8 57
 
6.6%
6 48
 
5.6%
5 46
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
K 3
25.0%
B 3
25.0%
H 1
 
8.3%
A 1
 
8.3%
D 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 4
50.0%
. 2
25.0%
? 1
 
12.5%
/ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
735
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2330
56.2%
Common 1803
43.5%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
314
13.5%
166
 
7.1%
159
 
6.8%
158
 
6.8%
157
 
6.7%
156
 
6.7%
156
 
6.7%
156
 
6.7%
133
 
5.7%
75
 
3.2%
Other values (100) 700
30.0%
Common
ValueCountFrequency (%)
735
40.8%
1 178
 
9.9%
3 148
 
8.2%
2 140
 
7.8%
- 128
 
7.1%
0 72
 
4.0%
4 57
 
3.2%
9 57
 
3.2%
7 57
 
3.2%
8 57
 
3.2%
Other values (8) 174
 
9.7%
Latin
ValueCountFrequency (%)
S 3
25.0%
K 3
25.0%
B 3
25.0%
H 1
 
8.3%
A 1
 
8.3%
D 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2330
56.2%
ASCII 1815
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
735
40.5%
1 178
 
9.8%
3 148
 
8.2%
2 140
 
7.7%
- 128
 
7.1%
0 72
 
4.0%
4 57
 
3.1%
9 57
 
3.1%
7 57
 
3.1%
8 57
 
3.1%
Other values (14) 186
 
10.2%
Hangul
ValueCountFrequency (%)
314
13.5%
166
 
7.1%
159
 
6.8%
158
 
6.8%
157
 
6.7%
156
 
6.7%
156
 
6.7%
156
 
6.7%
133
 
5.7%
75
 
3.2%
Other values (100) 700
30.0%

도로명주소
Text

MISSING 

Distinct105
Distinct (%)96.3%
Missing47
Missing (%)30.1%
Memory size1.3 KiB
2024-05-11T15:00:46.534019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length34.266055
Min length24

Characters and Unicode

Total characters3735
Distinct characters154
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

Unique101 ?
Unique (%)92.7%

Sample

1st row서울특별시 서대문구 충정로 53, 유원골든타워빌딩 1409호 (충정로2가)
2nd row서울특별시 서대문구 홍제천로 184 (연희동,(1층))
3rd row서울특별시 서대문구 통일로 137-6, 1층 (냉천동)
4th row서울특별시 서대문구 간호대로 11-32 (홍제동)
5th row서울특별시 서대문구 홍제천로 186 (연희동)
ValueCountFrequency (%)
서울특별시 109
 
15.5%
서대문구 109
 
15.5%
연희동 20
 
2.8%
2층 19
 
2.7%
1층 18
 
2.6%
북가좌동 17
 
2.4%
홍제동 11
 
1.6%
연희로 10
 
1.4%
충정로 8
 
1.1%
충정로2가 8
 
1.1%
Other values (238) 375
53.3%
2024-05-11T15:00:47.038865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
596
 
16.0%
226
 
6.1%
1 129
 
3.5%
127
 
3.4%
) 127
 
3.4%
( 127
 
3.4%
, 123
 
3.3%
121
 
3.2%
116
 
3.1%
2 114
 
3.1%
Other values (144) 1929
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2180
58.4%
Space Separator 596
 
16.0%
Decimal Number 549
 
14.7%
Close Punctuation 127
 
3.4%
Open Punctuation 127
 
3.4%
Other Punctuation 124
 
3.3%
Dash Punctuation 22
 
0.6%
Uppercase Letter 10
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
226
 
10.4%
127
 
5.8%
121
 
5.6%
116
 
5.3%
111
 
5.1%
110
 
5.0%
110
 
5.0%
109
 
5.0%
109
 
5.0%
99
 
4.5%
Other values (122) 942
43.2%
Decimal Number
ValueCountFrequency (%)
1 129
23.5%
2 114
20.8%
3 69
12.6%
0 50
 
9.1%
5 45
 
8.2%
7 41
 
7.5%
4 34
 
6.2%
6 27
 
4.9%
8 22
 
4.0%
9 18
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
20.0%
S 2
20.0%
K 2
20.0%
B 2
20.0%
D 1
10.0%
C 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 123
99.2%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
596
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2180
58.4%
Common 1545
41.4%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
226
 
10.4%
127
 
5.8%
121
 
5.6%
116
 
5.3%
111
 
5.1%
110
 
5.0%
110
 
5.0%
109
 
5.0%
109
 
5.0%
99
 
4.5%
Other values (122) 942
43.2%
Common
ValueCountFrequency (%)
596
38.6%
1 129
 
8.3%
) 127
 
8.2%
( 127
 
8.2%
, 123
 
8.0%
2 114
 
7.4%
3 69
 
4.5%
0 50
 
3.2%
5 45
 
2.9%
7 41
 
2.7%
Other values (6) 124
 
8.0%
Latin
ValueCountFrequency (%)
A 2
20.0%
S 2
20.0%
K 2
20.0%
B 2
20.0%
D 1
10.0%
C 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2180
58.4%
ASCII 1555
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
596
38.3%
1 129
 
8.3%
) 127
 
8.2%
( 127
 
8.2%
, 123
 
7.9%
2 114
 
7.3%
3 69
 
4.4%
0 50
 
3.2%
5 45
 
2.9%
7 41
 
2.6%
Other values (12) 134
 
8.6%
Hangul
ValueCountFrequency (%)
226
 
10.4%
127
 
5.8%
121
 
5.6%
116
 
5.3%
111
 
5.1%
110
 
5.0%
110
 
5.0%
109
 
5.0%
109
 
5.0%
99
 
4.5%
Other values (122) 942
43.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct60
Distinct (%)55.6%
Missing48
Missing (%)30.8%
Infinite0
Infinite (%)0.0%
Mean3706.7685
Minimum3615
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:47.281652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3615
5-th percentile3622
Q13678.75
median3714
Q33737
95-th percentile3782.6
Maximum3789
Range174
Interquartile range (IQR)58.25

Descriptive statistics

Standard deviation43.97187
Coefficient of variation (CV)0.011862589
Kurtosis-0.47772238
Mean3706.7685
Median Absolute Deviation (MAD)27
Skewness-0.30867006
Sum400331
Variance1933.5254
MonotonicityNot monotonic
2024-05-11T15:00:47.750157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3736 6
 
3.8%
3715 5
 
3.2%
3714 4
 
2.6%
3741 4
 
2.6%
3660 4
 
2.6%
3622 3
 
1.9%
3695 3
 
1.9%
3789 3
 
1.9%
3737 3
 
1.9%
3683 3
 
1.9%
Other values (50) 70
44.9%
(Missing) 48
30.8%
ValueCountFrequency (%)
3615 2
1.3%
3619 2
1.3%
3622 3
1.9%
3624 1
 
0.6%
3632 1
 
0.6%
3636 1
 
0.6%
3638 1
 
0.6%
3642 1
 
0.6%
3646 1
 
0.6%
3654 2
1.3%
ValueCountFrequency (%)
3789 3
1.9%
3785 2
1.3%
3784 1
 
0.6%
3780 1
 
0.6%
3767 1
 
0.6%
3765 1
 
0.6%
3762 1
 
0.6%
3757 1
 
0.6%
3752 2
1.3%
3751 1
 
0.6%
Distinct153
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:00:48.080415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.9038462
Min length2

Characters and Unicode

Total characters1233
Distinct characters239
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)96.2%

Sample

1st row유건개발(주)
2nd row용현실업(주)
3rd row환경종합개발
4th row주-삼원관리산업
5th row유건개발(주)
ValueCountFrequency (%)
주식회사 9
 
5.1%
유건개발(주 2
 
1.1%
협동조합 2
 
1.1%
주)신세계에프씨 2
 
1.1%
환경종합개발 2
 
1.1%
크린대장 1
 
0.6%
모두죤서비스개발업 1
 
0.6%
주)아이언클레드 1
 
0.6%
청우환경 1
 
0.6%
주)휴먼종합관리 1
 
0.6%
Other values (155) 155
87.6%
2024-05-11T15:00:48.652166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
8.4%
( 91
 
7.4%
) 91
 
7.4%
32
 
2.6%
27
 
2.2%
26
 
2.1%
24
 
1.9%
21
 
1.7%
20
 
1.6%
20
 
1.6%
Other values (229) 778
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1001
81.2%
Open Punctuation 91
 
7.4%
Close Punctuation 91
 
7.4%
Space Separator 21
 
1.7%
Uppercase Letter 13
 
1.1%
Lowercase Letter 7
 
0.6%
Decimal Number 6
 
0.5%
Other Punctuation 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
103
 
10.3%
32
 
3.2%
27
 
2.7%
26
 
2.6%
24
 
2.4%
20
 
2.0%
20
 
2.0%
19
 
1.9%
18
 
1.8%
17
 
1.7%
Other values (204) 695
69.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
23.1%
K 1
 
7.7%
F 1
 
7.7%
N 1
 
7.7%
B 1
 
7.7%
M 1
 
7.7%
S 1
 
7.7%
A 1
 
7.7%
H 1
 
7.7%
E 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
c 2
28.6%
e 2
28.6%
n 1
14.3%
r 1
14.3%
i 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
5 1
 
16.7%
2 1
 
16.7%
9 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1001
81.2%
Common 212
 
17.2%
Latin 20
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
103
 
10.3%
32
 
3.2%
27
 
2.7%
26
 
2.6%
24
 
2.4%
20
 
2.0%
20
 
2.0%
19
 
1.9%
18
 
1.8%
17
 
1.7%
Other values (204) 695
69.4%
Latin
ValueCountFrequency (%)
C 3
15.0%
c 2
 
10.0%
e 2
 
10.0%
K 1
 
5.0%
F 1
 
5.0%
N 1
 
5.0%
B 1
 
5.0%
M 1
 
5.0%
S 1
 
5.0%
A 1
 
5.0%
Other values (6) 6
30.0%
Common
ValueCountFrequency (%)
( 91
42.9%
) 91
42.9%
21
 
9.9%
1 3
 
1.4%
& 2
 
0.9%
5 1
 
0.5%
2 1
 
0.5%
- 1
 
0.5%
9 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1001
81.2%
ASCII 232
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
103
 
10.3%
32
 
3.2%
27
 
2.7%
26
 
2.6%
24
 
2.4%
20
 
2.0%
20
 
2.0%
19
 
1.9%
18
 
1.8%
17
 
1.7%
Other values (204) 695
69.4%
ASCII
ValueCountFrequency (%)
( 91
39.2%
) 91
39.2%
21
 
9.1%
1 3
 
1.3%
C 3
 
1.3%
c 2
 
0.9%
& 2
 
0.9%
e 2
 
0.9%
K 1
 
0.4%
F 1
 
0.4%
Other values (15) 15
 
6.5%
Distinct150
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1999-04-14 00:00:00
Maximum2024-05-07 14:38:45
2024-05-11T15:00:48.874081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:00:49.103805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
105 
U
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 105
67.3%
U 51
32.7%

Length

2024-05-11T15:00:49.389607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:49.591607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 105
67.3%
u 51
32.7%
Distinct61
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:00:49.779135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:00:50.026593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건물위생관리업
155 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0192308
Min length7

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 155
99.4%
건물위생관리업 기타 1
 
0.6%

Length

2024-05-11T15:00:50.235042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:50.400133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 156
99.4%
기타 1
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)74.2%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean194549.13
Minimum191543.28
Maximum196947.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:50.587448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191543.28
5-th percentile191618.07
Q1193281.6
median194266.29
Q3196549.34
95-th percentile196877.15
Maximum196947.25
Range5403.9697
Interquartile range (IQR)3267.7392

Descriptive statistics

Standard deviation1771.5649
Coefficient of variation (CV)0.0091060029
Kurtosis-1.2184673
Mean194549.13
Median Absolute Deviation (MAD)1592.3317
Skewness-0.14486217
Sum29376918
Variance3138442.2
MonotonicityNot monotonic
2024-05-11T15:00:50.874405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196801.661639204 7
 
4.5%
191543.28 4
 
2.6%
196626.844541919 4
 
2.6%
193860.58211819 4
 
2.6%
194265.067639805 3
 
1.9%
191557.35422121 3
 
1.9%
193803.424181589 3
 
1.9%
193423.550017619 2
 
1.3%
194914.495658636 2
 
1.3%
193281.599002951 2
 
1.3%
Other values (102) 117
75.0%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
191543.28 4
2.6%
191557.35422121 3
1.9%
191618.069041323 2
1.3%
191748.016275475 1
 
0.6%
191778.716247587 1
 
0.6%
191836.275479334 1
 
0.6%
191882.842211607 1
 
0.6%
191900.345924872 1
 
0.6%
191957.888065159 1
 
0.6%
192015.923301889 1
 
0.6%
ValueCountFrequency (%)
196947.249719346 1
 
0.6%
196945.454641052 2
 
1.3%
196934.602353655 2
 
1.3%
196892.09236853 2
 
1.3%
196884.166631688 1
 
0.6%
196870.135119188 2
 
1.3%
196855.670746664 2
 
1.3%
196824.072701729 2
 
1.3%
196806.237792473 1
 
0.6%
196801.661639204 7
4.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)74.2%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean452276.81
Minimum450433.69
Maximum454822.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:51.103994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450433.69
5-th percentile450721.15
Q1451281.61
median452324.39
Q3453028.35
95-th percentile454342.97
Maximum454822.28
Range4388.5847
Interquartile range (IQR)1746.7439

Descriptive statistics

Standard deviation1112.0561
Coefficient of variation (CV)0.0024587953
Kurtosis-0.73314162
Mean452276.81
Median Absolute Deviation (MAD)879.11898
Skewness0.28955763
Sum68293799
Variance1236668.8
MonotonicityNot monotonic
2024-05-11T15:00:51.341953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451267.809661546 7
 
4.5%
452508.37 4
 
2.6%
450926.293397092 4
 
2.6%
451975.128845845 4
 
2.6%
450433.691021245 3
 
1.9%
452756.894731199 3
 
1.9%
452723.457356207 3
 
1.9%
452263.136505739 2
 
1.3%
454564.34581261 2
 
1.3%
452698.533288013 2
 
1.3%
Other values (102) 117
75.0%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
450433.691021245 3
1.9%
450503.286604315 1
 
0.6%
450557.288919467 1
 
0.6%
450573.690449065 1
 
0.6%
450637.010875398 1
 
0.6%
450697.986159124 1
 
0.6%
450744.320812298 1
 
0.6%
450752.193815189 1
 
0.6%
450799.041380329 1
 
0.6%
450803.516428064 1
 
0.6%
ValueCountFrequency (%)
454822.275734675 2
1.3%
454635.157093313 1
0.6%
454572.36758883 2
1.3%
454564.34581261 2
1.3%
454365.176561147 1
0.6%
454320.765225854 1
0.6%
454118.828065507 1
0.6%
454101.858995196 1
0.6%
454078.028449131 1
0.6%
453882.809421941 1
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건물위생관리업
128 
<NA>
28 

Length

Max length7
Median length7
Mean length6.4615385
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 128
82.1%
<NA> 28
 
17.9%

Length

2024-05-11T15:00:51.541531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:51.706740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 128
82.1%
na 28
 
17.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)12.7%
Missing38
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean3.2372881
Minimum0
Maximum18
Zeros58
Zeros (%)37.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:51.879841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile17.15
Maximum18
Range18
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.064841
Coefficient of variation (CV)1.5645321
Kurtosis2.9407258
Mean3.2372881
Median Absolute Deviation (MAD)1
Skewness1.9723219
Sum382
Variance25.652615
MonotonicityNot monotonic
2024-05-11T15:00:52.065649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 58
37.2%
3 15
 
9.6%
4 11
 
7.1%
5 8
 
5.1%
2 8
 
5.1%
18 6
 
3.8%
17 2
 
1.3%
15 2
 
1.3%
1 2
 
1.3%
11 1
 
0.6%
Other values (5) 5
 
3.2%
(Missing) 38
24.4%
ValueCountFrequency (%)
0 58
37.2%
1 2
 
1.3%
2 8
 
5.1%
3 15
 
9.6%
4 11
 
7.1%
5 8
 
5.1%
6 1
 
0.6%
8 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%
ValueCountFrequency (%)
18 6
3.8%
17 2
 
1.3%
16 1
 
0.6%
15 2
 
1.3%
12 1
 
0.6%
11 1
 
0.6%
10 1
 
0.6%
8 1
 
0.6%
6 1
 
0.6%
5 8
5.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)7.4%
Missing48
Missing (%)30.8%
Infinite0
Infinite (%)0.0%
Mean1.0185185
Minimum0
Maximum7
Zeros62
Zeros (%)39.7%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:52.224755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6.65
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8943175
Coefficient of variation (CV)1.8598754
Kurtosis4.3268852
Mean1.0185185
Median Absolute Deviation (MAD)0
Skewness2.3178571
Sum110
Variance3.5884389
MonotonicityNot monotonic
2024-05-11T15:00:52.380895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 62
39.7%
1 31
19.9%
7 6
 
3.8%
2 2
 
1.3%
4 2
 
1.3%
5 2
 
1.3%
6 2
 
1.3%
3 1
 
0.6%
(Missing) 48
30.8%
ValueCountFrequency (%)
0 62
39.7%
1 31
19.9%
2 2
 
1.3%
3 1
 
0.6%
4 2
 
1.3%
5 2
 
1.3%
6 2
 
1.3%
7 6
 
3.8%
ValueCountFrequency (%)
7 6
 
3.8%
6 2
 
1.3%
5 2
 
1.3%
4 2
 
1.3%
3 1
 
0.6%
2 2
 
1.3%
1 31
19.9%
0 62
39.7%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)13.3%
Missing58
Missing (%)37.2%
Infinite0
Infinite (%)0.0%
Mean2.8265306
Minimum0
Maximum14
Zeros14
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:52.569205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33.75
95-th percentile10.3
Maximum14
Range14
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation3.1460186
Coefficient of variation (CV)1.1130319
Kurtosis4.7854777
Mean2.8265306
Median Absolute Deviation (MAD)1
Skewness2.1567352
Sum277
Variance9.8974332
MonotonicityNot monotonic
2024-05-11T15:00:52.762381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 26
16.7%
2 22
 
14.1%
0 14
 
9.0%
3 11
 
7.1%
4 10
 
6.4%
14 3
 
1.9%
7 3
 
1.9%
6 3
 
1.9%
5 2
 
1.3%
8 1
 
0.6%
Other values (3) 3
 
1.9%
(Missing) 58
37.2%
ValueCountFrequency (%)
0 14
9.0%
1 26
16.7%
2 22
14.1%
3 11
7.1%
4 10
 
6.4%
5 2
 
1.3%
6 3
 
1.9%
7 3
 
1.9%
8 1
 
0.6%
10 1
 
0.6%
ValueCountFrequency (%)
14 3
 
1.9%
13 1
 
0.6%
12 1
 
0.6%
10 1
 
0.6%
8 1
 
0.6%
7 3
 
1.9%
6 3
 
1.9%
5 2
 
1.3%
4 10
6.4%
3 11
7.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)17.1%
Missing74
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean10.52439
Minimum0
Maximum614
Zeros8
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:52.919103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile12.95
Maximum614
Range614
Interquartile range (IQR)3

Descriptive statistics

Standard deviation67.54591
Coefficient of variation (CV)6.4180355
Kurtosis81.595451
Mean10.52439
Median Absolute Deviation (MAD)1
Skewness9.0225095
Sum863
Variance4562.45
MonotonicityNot monotonic
2024-05-11T15:00:53.114794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 22
 
14.1%
2 20
 
12.8%
3 9
 
5.8%
0 8
 
5.1%
4 8
 
5.1%
14 3
 
1.9%
7 3
 
1.9%
6 2
 
1.3%
5 2
 
1.3%
8 1
 
0.6%
Other values (4) 4
 
2.6%
(Missing) 74
47.4%
ValueCountFrequency (%)
0 8
 
5.1%
1 22
14.1%
2 20
12.8%
3 9
5.8%
4 8
 
5.1%
5 2
 
1.3%
6 2
 
1.3%
7 3
 
1.9%
8 1
 
0.6%
10 1
 
0.6%
ValueCountFrequency (%)
614 1
 
0.6%
14 3
 
1.9%
13 1
 
0.6%
12 1
 
0.6%
10 1
 
0.6%
8 1
 
0.6%
7 3
 
1.9%
6 2
 
1.3%
5 2
 
1.3%
4 8
5.1%
Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
106 
0
32 
1
16 
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.0384615
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
67.9%
0 32
 
20.5%
1 16
 
10.3%
5 1
 
0.6%
2 1
 
0.6%

Length

2024-05-11T15:00:53.342920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:53.513186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
67.9%
0 32
 
20.5%
1 16
 
10.3%
5 1
 
0.6%
2 1
 
0.6%
Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
117 
0
23 
1
15 
2
 
1

Length

Max length4
Median length4
Mean length3.25
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 117
75.0%
0 23
 
14.7%
1 15
 
9.6%
2 1
 
0.6%

Length

2024-05-11T15:00:53.703960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:53.858815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
75.0%
0 23
 
14.7%
1 15
 
9.6%
2 1
 
0.6%

한실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
81 
<NA>
75 

Length

Max length4
Median length1
Mean length2.4423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 81
51.9%
<NA> 75
48.1%

Length

2024-05-11T15:00:54.036743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:54.191911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 81
51.9%
na 75
48.1%

양실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
81 
<NA>
75 

Length

Max length4
Median length1
Mean length2.4423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 81
51.9%
<NA> 75
48.1%

Length

2024-05-11T15:00:54.339643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:54.509438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 81
51.9%
na 75
48.1%

욕실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
81 
<NA>
75 

Length

Max length4
Median length1
Mean length2.4423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 81
51.9%
<NA> 75
48.1%

Length

2024-05-11T15:00:54.671315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:54.804714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 81
51.9%
na 75
48.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing35
Missing (%)22.4%
Memory size444.0 B
False
121 
(Missing)
35 
ValueCountFrequency (%)
False 121
77.6%
(Missing) 35
 
22.4%
2024-05-11T15:00:54.932178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
81 
<NA>
75 

Length

Max length4
Median length1
Mean length2.4423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 81
51.9%
<NA> 75
48.1%

Length

2024-05-11T15:00:55.065024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:55.248919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 81
51.9%
na 75
48.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB
Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
임대
78 
<NA>
74 
자가
 
4

Length

Max length4
Median length2
Mean length2.9487179
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 78
50.0%
<NA> 74
47.4%
자가 4
 
2.6%

Length

2024-05-11T15:00:55.487029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:55.659041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 78
50.0%
na 74
47.4%
자가 4
 
2.6%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
84 
0
72 

Length

Max length4
Median length4
Mean length2.6153846
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> 84
53.8%
0 72
46.2%

Length

2024-05-11T15:00:55.825027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:55.974867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
53.8%
0 72
46.2%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
137 
0
15 
1
 
2
5
 
1
11
 
1

Length

Max length4
Median length4
Mean length3.6410256
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 137
87.8%
0 15
 
9.6%
1 2
 
1.3%
5 1
 
0.6%
11 1
 
0.6%

Length

2024-05-11T15:00:56.147248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:56.343229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
87.8%
0 15
 
9.6%
1 2
 
1.3%
5 1
 
0.6%
11 1
 
0.6%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)30.0%
Missing136
Missing (%)87.2%
Infinite0
Infinite (%)0.0%
Mean1.7
Minimum0
Maximum17
Zeros11
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:00:56.500894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4.65
Maximum17
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.8127211
Coefficient of variation (CV)2.2427771
Kurtosis15.236639
Mean1.7
Median Absolute Deviation (MAD)0
Skewness3.7383903
Sum34
Variance14.536842
MonotonicityNot monotonic
2024-05-11T15:00:56.674900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 11
 
7.1%
1 3
 
1.9%
2 2
 
1.3%
3 2
 
1.3%
17 1
 
0.6%
4 1
 
0.6%
(Missing) 136
87.2%
ValueCountFrequency (%)
0 11
7.1%
1 3
 
1.9%
2 2
 
1.3%
3 2
 
1.3%
4 1
 
0.6%
17 1
 
0.6%
ValueCountFrequency (%)
17 1
 
0.6%
4 1
 
0.6%
3 2
 
1.3%
2 2
 
1.3%
1 3
 
1.9%
0 11
7.1%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
98 
0
58 

Length

Max length4
Median length4
Mean length2.8846154
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> 98
62.8%
0 58
37.2%

Length

2024-05-11T15:00:56.890310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:57.056918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
62.8%
0 58
37.2%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
102 
0
54 

Length

Max length4
Median length4
Mean length2.9615385
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> 102
65.4%
0 54
34.6%

Length

2024-05-11T15:00:57.224784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:57.412345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
65.4%
0 54
34.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.6%
Missing28
Missing (%)17.9%
Memory size444.0 B
False
127 
True
 
1
(Missing)
28 
ValueCountFrequency (%)
False 127
81.4%
True 1
 
0.6%
(Missing) 28
 
17.9%
2024-05-11T15:00:57.574518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031200003120000-206-1992-0000119921210<NA>3폐업2폐업20040210<NA><NA><NA>02 3644987165.10120012서울특별시 서대문구 충정로2가 191 (14층)<NA><NA>유건개발(주)2014-01-14 09:59:51I2018-08-31 23:59:59.0건물위생관리업196801.661639451267.809662건물위생관리업1871414<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131200003120000-206-1993-0090619931218<NA>3폐업2폐업19961011<NA><NA><NA>02 32271382,825.42120824서울특별시 서대문구 연희동 92-18 3층 300호<NA><NA>용현실업(주)2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업193860.582118451975.128846건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231200003120000-206-1994-0090719940407<NA>3폐업2폐업20040210<NA><NA><NA>02 307816141.60120817서울특별시 서대문구 북가좌동 392-26 (2층)<NA><NA>환경종합개발2014-01-14 10:00:17I2018-08-31 23:59:59.0건물위생관리업191618.069041452417.992626건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331200003120000-206-1994-0218319940414<NA>3폐업2폐업20000313<NA><NA><NA>02 723709172.30120858서울특별시 서대문구 홍제동 307-12<NA><NA>주-삼원관리산업2000-04-14 00:00:00I2018-08-31 23:59:59.0건물위생관리업194850.291513453882.809422건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431200003120000-206-1994-0218419921210<NA>1영업/정상1영업<NA><NA><NA><NA>02 365548461.22120012서울특별시 서대문구 충정로2가 191 유원골든타워빌딩1409서울특별시 서대문구 충정로 53, 유원골든타워빌딩 1409호 (충정로2가)3736유건개발(주)2019-07-25 11:10:15U2019-07-27 02:40:00.0건물위생관리업196801.661639451267.809662건물위생관리업1871414<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
531200003120000-206-1994-0218519940407<NA>3폐업2폐업20181113<NA><NA><NA>02 307816239.67120827서울특별시 서대문구 연희동 170-112 (1층)서울특별시 서대문구 홍제천로 184 (연희동,(1층))3660환경종합개발2018-11-13 13:21:55U2018-11-15 02:36:21.0건물위생관리업194048.734323452910.282115건물위생관리업4122<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
631200003120000-206-1994-0218619941226<NA>1영업/정상1영업<NA><NA><NA><NA>02 725066835.28120050서울특별시 서대문구 냉천동 173서울특별시 서대문구 통일로 137-6, 1층 (냉천동)3735(주)창성기업2013-09-16 16:59:56I2018-08-31 23:59:59.0건물위생관리업196855.670747451592.649579건물위생관리업4<NA><NA>3<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731200003120000-206-1995-0218419950622<NA>3폐업2폐업19961010<NA><NA><NA>02 061.18120814서울특별시 서대문구 북가좌동 308-6<NA><NA>광산종합관리주식회사2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업192015.923302453035.413734건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831200003120000-206-1995-0218619951027<NA>1영업/정상1영업<NA><NA><NA><NA>02 3911112132.00120863서울특별시 서대문구 홍제동 278-9서울특별시 서대문구 간호대로 11-32 (홍제동)3619(주)포콤방범시스템2021-10-06 14:34:04U2021-10-08 02:40:00.0건물위생관리업195333.442347454822.275735건물위생관리업5<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931200003120000-206-1996-0090819960320<NA>3폐업2폐업19961023<NA><NA><NA>02 336755155.86120824서울특별시 서대문구 연희동 92-18<NA><NA>현대종합관리2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업193860.582118451975.128846건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14631200003120000-206-2022-000042022-11-28<NA>3폐업2폐업2023-12-05<NA><NA><NA>1599763034.00120-848서울특별시 서대문구 홍은동 402-26 필하우스서울특별시 서대문구 증가로10길 96-7, 201A호 (홍은동, 필하우스)3662그린F5서대문본부2023-12-05 13:26:27U2022-11-02 00:07:00.0건물위생관리업193468.958475453132.328457<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14731200003120000-206-2022-0000520221208<NA>1영업/정상1영업<NA><NA><NA><NA>02 303 07317.00120812서울특별시 서대문구 북가좌동 294-16서울특별시 서대문구 응암로 90, 1층 (북가좌동)3682한강C&B2022-12-08 15:18:10I2021-11-01 23:00:00.0건물위생관리업192185.182189453165.457955<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14831200003120000-206-2022-0000620221209<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30120827서울특별시 서대문구 연희동 717-29 한인트윈빌서울특별시 서대문구 홍연길 77, 202호 C-46호 (연희동, 한인트윈빌)3695아트소마2022-12-09 14:32:52I2021-11-01 23:01:00.0건물위생관리업193803.424182452723.457356<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14931200003120000-206-2022-0000720221219<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.28120715서울특별시 서대문구 충정로3가 139 동아일보사건물서울특별시 서대문구 충정로 29, 동아일보사건물 17층 (충정로3가)3737(주)동아엠텍2023-01-17 11:54:55I2022-11-30 23:09:00.0건물위생관리업196694.508583451070.35971<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15031200003120000-206-2023-000012023-01-17<NA>3폐업2폐업2023-09-21<NA><NA><NA>02 322093788.15120-861서울특별시 서대문구 홍제동 361-197서울특별시 서대문구 홍제내길 20, 2층 (홍제동)3642주식회사 동우코퍼레이션2023-09-21 15:12:02U2022-12-08 22:03:00.0건물위생관리업194355.240639453475.988355<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15131200003120000-206-2023-000022023-02-01<NA>3폐업2폐업2024-01-17<NA><NA><NA><NA>28.25120-829서울특별시 서대문구 연희동 140-12 연희동 다세대주택 1호서울특별시 서대문구 연희로28길 51-8, 1층 1호 (연희동, 연희동 다세대주택)3720(주) 유토산업개발2024-01-17 15:54:00U2023-11-30 23:09:00.0건물위생관리업194471.031235452559.763601<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15231200003120000-206-2023-000032023-02-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>223.00120-823서울특별시 서대문구 연희동 69서울특별시 서대문구 연희로26다길 54, 지하1층,지상2층 (연희동)3720(주)에이치씨알시스템2023-02-09 16:17:14I2022-12-01 23:01:00.0건물위생관리업194430.963061452482.828312<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15331200003120000-206-2023-000042023-07-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.79120-863서울특별시 서대문구 홍제동 282-26서울특별시 서대문구 세검정로4길 28, 지1층 전체호 (홍제동)3622크린대장 서대문점2023-07-17 11:27:00I2022-12-06 23:09:00.0건물위생관리업195475.349958454635.157093<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15431200003120000-206-2023-000052023-11-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.00120-706서울특별시 서대문구 창천동 30-33 현대백화점신촌점서울특별시 서대문구 신촌로 83, 현대백화점신촌점 지5층 일부호 (창천동)3789태영씨에치엠2023-11-28 15:43:03I2022-10-31 21:00:00.0건물위생관리업194265.06764450433.691021<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15531200003120000-206-2024-000012024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00120-817서울특별시 서대문구 북가좌동 392-35서울특별시 서대문구 수색로 139, 207-5호 (북가좌동)3715청소1192024-05-07 14:38:45I2023-12-05 00:09:00.0건물위생관리업191543.28452508.37<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>