Overview

Dataset statistics

Number of variables47
Number of observations203
Missing cells2220
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory80.2 KiB
Average record size in memory404.7 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
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-19284/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용끝지하층 is highly imbalanced (56.6%)Imbalance
건물소유구분명 is highly imbalanced (71.7%)Imbalance
여성종사자수 is highly imbalanced (56.6%)Imbalance
인허가취소일자 has 203 (100.0%) missing valuesMissing
폐업일자 has 69 (34.0%) missing valuesMissing
휴업시작일자 has 203 (100.0%) missing valuesMissing
휴업종료일자 has 203 (100.0%) missing valuesMissing
재개업일자 has 203 (100.0%) missing valuesMissing
전화번호 has 62 (30.5%) missing valuesMissing
도로명주소 has 67 (33.0%) missing valuesMissing
도로명우편번호 has 69 (34.0%) missing valuesMissing
좌표정보(X) has 8 (3.9%) missing valuesMissing
좌표정보(Y) has 8 (3.9%) missing valuesMissing
건물지상층수 has 61 (30.0%) missing valuesMissing
사용시작지상층 has 83 (40.9%) missing valuesMissing
사용끝지상층 has 128 (63.1%) missing valuesMissing
발한실여부 has 40 (19.7%) missing valuesMissing
조건부허가신고사유 has 203 (100.0%) missing valuesMissing
조건부허가시작일자 has 203 (100.0%) missing valuesMissing
조건부허가종료일자 has 203 (100.0%) missing valuesMissing
남성종사자수 has 164 (80.8%) missing valuesMissing
다중이용업소여부 has 38 (18.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 83 (40.9%) zerosZeros
사용시작지상층 has 27 (13.3%) zerosZeros
사용끝지상층 has 9 (4.4%) zerosZeros
남성종사자수 has 27 (13.3%) zerosZeros

Reproduction

Analysis started2024-05-11 04:08:02.576804
Analysis finished2024-05-11 04:08:04.150323
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3070000
203 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 203
100.0%

Length

2024-05-11T04:08:04.337287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:04.687363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 203
100.0%

관리번호
Text

UNIQUE 

Distinct203
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:08:05.239402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4466
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

Unique203 ?
Unique (%)100.0%

Sample

1st row3070000-206-1991-02869
2nd row3070000-206-1993-02860
3rd row3070000-206-1993-02861
4th row3070000-206-1993-02866
5th row3070000-206-1993-02867
ValueCountFrequency (%)
3070000-206-1991-02869 1
 
0.5%
3070000-206-2015-00003 1
 
0.5%
3070000-206-2016-00010 1
 
0.5%
3070000-206-2014-00001 1
 
0.5%
3070000-206-2014-00002 1
 
0.5%
3070000-206-2014-00003 1
 
0.5%
3070000-206-2014-00004 1
 
0.5%
3070000-206-2014-00005 1
 
0.5%
3070000-206-2014-00006 1
 
0.5%
3070000-206-2014-00007 1
 
0.5%
Other values (193) 193
95.1%
2024-05-11T04:08:06.303013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2205
49.4%
- 609
 
13.6%
2 476
 
10.7%
3 268
 
6.0%
6 252
 
5.6%
7 238
 
5.3%
1 186
 
4.2%
9 91
 
2.0%
8 52
 
1.2%
5 47
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3857
86.4%
Dash Punctuation 609
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2205
57.2%
2 476
 
12.3%
3 268
 
6.9%
6 252
 
6.5%
7 238
 
6.2%
1 186
 
4.8%
9 91
 
2.4%
8 52
 
1.3%
5 47
 
1.2%
4 42
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 609
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2205
49.4%
- 609
 
13.6%
2 476
 
10.7%
3 268
 
6.0%
6 252
 
5.6%
7 238
 
5.3%
1 186
 
4.2%
9 91
 
2.0%
8 52
 
1.2%
5 47
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2205
49.4%
- 609
 
13.6%
2 476
 
10.7%
3 268
 
6.0%
6 252
 
5.6%
7 238
 
5.3%
1 186
 
4.2%
9 91
 
2.0%
8 52
 
1.2%
5 47
 
1.1%

인허가일자
Date

Distinct193
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1991-05-08 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T04:08:06.938995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:08:07.443257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
134 
1
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 134
66.0%
1 69
34.0%

Length

2024-05-11T04:08:07.968296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:08.333213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 134
66.0%
1 69
34.0%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
134 
영업/정상
69 

Length

Max length5
Median length2
Mean length3.0197044
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 134
66.0%
영업/정상 69
34.0%

Length

2024-05-11T04:08:08.845634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:09.238353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 134
66.0%
영업/정상 69
34.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
134 
1
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 134
66.0%
1 69
34.0%

Length

2024-05-11T04:08:09.685573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:10.049266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 134
66.0%
1 69
34.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
134 
영업
69 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 134
66.0%
영업 69
34.0%

Length

2024-05-11T04:08:10.501041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:11.296131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 134
66.0%
영업 69
34.0%

폐업일자
Date

MISSING 

Distinct120
Distinct (%)89.6%
Missing69
Missing (%)34.0%
Memory size1.7 KiB
Minimum1995-12-09 00:00:00
Maximum2024-04-03 00:00:00
2024-05-11T04:08:11.673424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:08:12.271722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

전화번호
Text

MISSING 

Distinct135
Distinct (%)95.7%
Missing62
Missing (%)30.5%
Memory size1.7 KiB
2024-05-11T04:08:13.233529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.624113
Min length2

Characters and Unicode

Total characters1498
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

Unique129 ?
Unique (%)91.5%

Sample

1st row0209640508
2nd row0207450268
3rd row02 7637721
4th row02 9120921
5th row0209135954
ValueCountFrequency (%)
02 103
34.8%
941 4
 
1.4%
070 4
 
1.4%
915 4
 
1.4%
927 3
 
1.0%
587 2
 
0.7%
6324 2
 
0.7%
929 2
 
0.7%
0171 2
 
0.7%
9279538 2
 
0.7%
Other values (160) 168
56.8%
2024-05-11T04:08:14.691653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 264
17.6%
0 249
16.6%
209
14.0%
9 162
10.8%
1 113
7.5%
7 102
 
6.8%
3 93
 
6.2%
5 82
 
5.5%
4 82
 
5.5%
6 74
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1289
86.0%
Space Separator 209
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 264
20.5%
0 249
19.3%
9 162
12.6%
1 113
8.8%
7 102
 
7.9%
3 93
 
7.2%
5 82
 
6.4%
4 82
 
6.4%
6 74
 
5.7%
8 68
 
5.3%
Space Separator
ValueCountFrequency (%)
209
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 264
17.6%
0 249
16.6%
209
14.0%
9 162
10.8%
1 113
7.5%
7 102
 
6.8%
3 93
 
6.2%
5 82
 
5.5%
4 82
 
5.5%
6 74
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 264
17.6%
0 249
16.6%
209
14.0%
9 162
10.8%
1 113
7.5%
7 102
 
6.8%
3 93
 
6.2%
5 82
 
5.5%
4 82
 
5.5%
6 74
 
4.9%

소재지면적
Text

Distinct142
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:08:15.691293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9852217
Min length3

Characters and Unicode

Total characters1012
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

Unique120 ?
Unique (%)59.1%

Sample

1st row50.00
2nd row56.10
3rd row70.35
4th row99.70
5th row114.35
ValueCountFrequency (%)
00 19
 
9.4%
10.00 8
 
3.9%
33.00 7
 
3.4%
23.00 4
 
2.0%
66.00 4
 
2.0%
20.00 3
 
1.5%
14.00 3
 
1.5%
30.00 3
 
1.5%
35.00 3
 
1.5%
60.00 3
 
1.5%
Other values (132) 146
71.9%
2024-05-11T04:08:17.013920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 263
26.0%
. 203
20.1%
1 94
 
9.3%
2 77
 
7.6%
3 68
 
6.7%
6 67
 
6.6%
5 60
 
5.9%
4 58
 
5.7%
8 46
 
4.5%
7 37
 
3.7%
Other values (2) 39
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 807
79.7%
Other Punctuation 205
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 263
32.6%
1 94
 
11.6%
2 77
 
9.5%
3 68
 
8.4%
6 67
 
8.3%
5 60
 
7.4%
4 58
 
7.2%
8 46
 
5.7%
7 37
 
4.6%
9 37
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 203
99.0%
, 2
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 263
26.0%
. 203
20.1%
1 94
 
9.3%
2 77
 
7.6%
3 68
 
6.7%
6 67
 
6.6%
5 60
 
5.9%
4 58
 
5.7%
8 46
 
4.5%
7 37
 
3.7%
Other values (2) 39
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 263
26.0%
. 203
20.1%
1 94
 
9.3%
2 77
 
7.6%
3 68
 
6.7%
6 67
 
6.6%
5 60
 
5.9%
4 58
 
5.7%
8 46
 
4.5%
7 37
 
3.7%
Other values (2) 39
 
3.9%

소재지우편번호
Text

Distinct97
Distinct (%)48.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2024-05-11T04:08:17.839024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1039604
Min length6

Characters and Unicode

Total characters1233
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

Unique52 ?
Unique (%)25.7%

Sample

1st row136120
2nd row136031
3rd row136044
4th row136827
5th row136858
ValueCountFrequency (%)
136053 7
 
3.5%
136874 7
 
3.5%
136858 6
 
3.0%
136045 6
 
3.0%
136060 6
 
3.0%
136054 5
 
2.5%
136873 5
 
2.5%
136828 5
 
2.5%
136035 5
 
2.5%
136130 4
 
2.0%
Other values (87) 146
72.3%
2024-05-11T04:08:19.902706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 265
21.5%
1 253
20.5%
6 236
19.1%
8 144
11.7%
0 109
8.8%
5 64
 
5.2%
4 55
 
4.5%
7 45
 
3.6%
2 32
 
2.6%
- 21
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1212
98.3%
Dash Punctuation 21
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 265
21.9%
1 253
20.9%
6 236
19.5%
8 144
11.9%
0 109
9.0%
5 64
 
5.3%
4 55
 
4.5%
7 45
 
3.7%
2 32
 
2.6%
9 9
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 265
21.5%
1 253
20.5%
6 236
19.1%
8 144
11.7%
0 109
8.8%
5 64
 
5.2%
4 55
 
4.5%
7 45
 
3.6%
2 32
 
2.6%
- 21
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 265
21.5%
1 253
20.5%
6 236
19.1%
8 144
11.7%
0 109
8.8%
5 64
 
5.2%
4 55
 
4.5%
7 45
 
3.6%
2 32
 
2.6%
- 21
 
1.7%

지번주소
Text

Distinct196
Distinct (%)97.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2024-05-11T04:08:21.201418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length25.252475
Min length16

Characters and Unicode

Total characters5101
Distinct characters157
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

Unique190 ?
Unique (%)94.1%

Sample

1st row서울특별시 성북구 상월곡동 24-194 웅진빌딩
2nd row서울특별시 성북구 동소문동1가 51-0
3rd row서울특별시 성북구 삼선동4가 9-7
4th row서울특별시 성북구 장위동 62-12
5th row서울특별시 성북구 종암동 8-260
ValueCountFrequency (%)
서울특별시 202
20.4%
성북구 201
20.3%
장위동 33
 
3.3%
하월곡동 25
 
2.5%
정릉동 20
 
2.0%
종암동 16
 
1.6%
1층 14
 
1.4%
길음동 11
 
1.1%
돈암동 11
 
1.1%
석관동 11
 
1.1%
Other values (320) 448
45.2%
2024-05-11T04:08:23.148560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
931
18.3%
동 260
 
5.1%
1 252
 
4.9%
성 216
 
4.2%
북 211
 
4.1%
2 207
 
4.1%
서 204
 
4.0%
시 204
 
4.0%
구 203
 
4.0%
특 202
 
4.0%
Other values (147) 2211
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2835
55.6%
Decimal Number 1121
 
22.0%
Space Separator 931
 
18.3%
Dash Punctuation 161
 
3.2%
Close Punctuation 20
 
0.4%
Open Punctuation 20
 
0.4%
Other Punctuation 8
 
0.2%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 260
 
9.2%
성 216
 
7.6%
북 211
 
7.4%
서 204
 
7.2%
시 204
 
7.2%
구 203
 
7.2%
특 202
 
7.1%
별 202
 
7.1%
울 202
 
7.1%
가 80
 
2.8%
Other values (128) 851
30.0%
Decimal Number
ValueCountFrequency (%)
1 252
22.5%
2 207
18.5%
0 105
9.4%
3 102
9.1%
4 98
 
8.7%
6 86
 
7.7%
5 77
 
6.9%
9 69
 
6.2%
7 63
 
5.6%
8 62
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
T 1
20.0%
P 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
931
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2835
55.6%
Common 2261
44.3%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 260
 
9.2%
성 216
 
7.6%
북 211
 
7.4%
서 204
 
7.2%
시 204
 
7.2%
구 203
 
7.2%
특 202
 
7.1%
별 202
 
7.1%
울 202
 
7.1%
가 80
 
2.8%
Other values (128) 851
30.0%
Common
ValueCountFrequency (%)
931
41.2%
1 252
 
11.1%
2 207
 
9.2%
- 161
 
7.1%
0 105
 
4.6%
3 102
 
4.5%
4 98
 
4.3%
6 86
 
3.8%
5 77
 
3.4%
9 69
 
3.1%
Other values (5) 173
 
7.7%
Latin
ValueCountFrequency (%)
B 2
40.0%
T 1
20.0%
P 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2835
55.6%
ASCII 2266
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
931
41.1%
1 252
 
11.1%
2 207
 
9.1%
- 161
 
7.1%
0 105
 
4.6%
3 102
 
4.5%
4 98
 
4.3%
6 86
 
3.8%
5 77
 
3.4%
9 69
 
3.0%
Other values (9) 178
 
7.9%
Hangul
ValueCountFrequency (%)
동 260
 
9.2%
성 216
 
7.6%
북 211
 
7.4%
서 204
 
7.2%
시 204
 
7.2%
구 203
 
7.2%
특 202
 
7.1%
별 202
 
7.1%
울 202
 
7.1%
가 80
 
2.8%
Other values (128) 851
30.0%

도로명주소
Text

MISSING 

Distinct134
Distinct (%)98.5%
Missing67
Missing (%)33.0%
Memory size1.7 KiB
2024-05-11T04:08:23.998671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length33.411765
Min length22

Characters and Unicode

Total characters4544
Distinct characters164
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

Unique132 ?
Unique (%)97.1%

Sample

1st row서울특별시 성북구 화랑로18가길 21, 웅진빌딩 3층 301호 (상월곡동)
2nd row서울특별시 성북구 화랑로35길 56 (장위동)
3rd row서울특별시 성북구 돌곶이로 97 (장위동)
4th row서울특별시 성북구 화랑로13길 32, 202호 (하월곡동, 명성빌딩)
5th row서울특별시 성북구 화랑로14길 5 (하월곡동)
ValueCountFrequency (%)
서울특별시 136
 
15.7%
성북구 135
 
15.6%
1층 24
 
2.8%
장위동 22
 
2.5%
3층 15
 
1.7%
하월곡동 14
 
1.6%
2층 14
 
1.6%
정릉동 12
 
1.4%
동소문로 10
 
1.2%
종암동 9
 
1.0%
Other values (316) 475
54.8%
2024-05-11T04:08:25.432203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
730
 
16.1%
동 207
 
4.6%
1 186
 
4.1%
성 155
 
3.4%
북 154
 
3.4%
( 144
 
3.2%
) 144
 
3.2%
2 141
 
3.1%
서 138
 
3.0%
시 138
 
3.0%
Other values (154) 2407
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2597
57.2%
Decimal Number 773
 
17.0%
Space Separator 730
 
16.1%
Open Punctuation 144
 
3.2%
Close Punctuation 144
 
3.2%
Other Punctuation 133
 
2.9%
Dash Punctuation 20
 
0.4%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 207
 
8.0%
성 155
 
6.0%
북 154
 
5.9%
서 138
 
5.3%
시 138
 
5.3%
구 137
 
5.3%
특 136
 
5.2%
별 136
 
5.2%
울 136
 
5.2%
로 136
 
5.2%
Other values (138) 1124
43.3%
Decimal Number
ValueCountFrequency (%)
1 186
24.1%
2 141
18.2%
3 109
14.1%
0 70
 
9.1%
6 61
 
7.9%
4 60
 
7.8%
8 44
 
5.7%
5 44
 
5.7%
7 31
 
4.0%
9 27
 
3.5%
Space Separator
ValueCountFrequency (%)
730
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Other Punctuation
ValueCountFrequency (%)
, 133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2597
57.2%
Common 1944
42.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 207
 
8.0%
성 155
 
6.0%
북 154
 
5.9%
서 138
 
5.3%
시 138
 
5.3%
구 137
 
5.3%
특 136
 
5.2%
별 136
 
5.2%
울 136
 
5.2%
로 136
 
5.2%
Other values (138) 1124
43.3%
Common
ValueCountFrequency (%)
730
37.6%
1 186
 
9.6%
( 144
 
7.4%
) 144
 
7.4%
2 141
 
7.3%
, 133
 
6.8%
3 109
 
5.6%
0 70
 
3.6%
6 61
 
3.1%
4 60
 
3.1%
Other values (5) 166
 
8.5%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2597
57.2%
ASCII 1947
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
730
37.5%
1 186
 
9.6%
( 144
 
7.4%
) 144
 
7.4%
2 141
 
7.2%
, 133
 
6.8%
3 109
 
5.6%
0 70
 
3.6%
6 61
 
3.1%
4 60
 
3.1%
Other values (6) 169
 
8.7%
Hangul
ValueCountFrequency (%)
동 207
 
8.0%
성 155
 
6.0%
북 154
 
5.9%
서 138
 
5.3%
시 138
 
5.3%
구 137
 
5.3%
특 136
 
5.2%
별 136
 
5.2%
울 136
 
5.2%
로 136
 
5.2%
Other values (138) 1124
43.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)52.2%
Missing69
Missing (%)34.0%
Infinite0
Infinite (%)0.0%
Mean2799.2612
Minimum2709
Maximum3368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:25.915635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2709
5-th percentile2718.65
Q12748.75
median2796.5
Q32835
95-th percentile2873
Maximum3368
Range659
Interquartile range (IQR)86.25

Descriptive statistics

Standard deviation71.068952
Coefficient of variation (CV)0.025388468
Kurtosis29.679225
Mean2799.2612
Median Absolute Deviation (MAD)43.5
Skewness3.8156031
Sum375101
Variance5050.7959
MonotonicityNot monotonic
2024-05-11T04:08:26.560622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2832 5
 
2.5%
2872 5
 
2.5%
2739 4
 
2.0%
2771 4
 
2.0%
2873 4
 
2.0%
2840 4
 
2.0%
2797 4
 
2.0%
2709 4
 
2.0%
2833 3
 
1.5%
2776 3
 
1.5%
Other values (60) 94
46.3%
(Missing) 69
34.0%
ValueCountFrequency (%)
2709 4
2.0%
2711 1
 
0.5%
2718 2
1.0%
2719 2
1.0%
2725 3
1.5%
2726 1
 
0.5%
2732 2
1.0%
2733 2
1.0%
2734 3
1.5%
2735 2
1.0%
ValueCountFrequency (%)
3368 1
 
0.5%
2880 3
1.5%
2873 4
2.0%
2872 5
2.5%
2868 1
 
0.5%
2866 1
 
0.5%
2865 1
 
0.5%
2863 1
 
0.5%
2862 2
 
1.0%
2859 1
 
0.5%

사업장명
Text

Distinct197
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T04:08:27.352342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length7.4827586
Min length2

Characters and Unicode

Total characters1519
Distinct characters264
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)94.1%

Sample

1st row(주)국제안전시스템
2nd row(주)선진프라자
3rd row(주)일운설비
4th row두산종합관리(주)
5th row일성설비(주)
ValueCountFrequency (%)
주식회사 21
 
9.0%
태림주택종합관리(주 2
 
0.9%
일성설비(주 2
 
0.9%
에벤에셀상사 2
 
0.9%
드림사 2
 
0.9%
주)유케이개발 2
 
0.9%
주)선진비엠 2
 
0.9%
주)태경티엠에스 1
 
0.4%
향기나는 1
 
0.4%
청소 1
 
0.4%
Other values (197) 197
84.5%
2024-05-11T04:08:28.824667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 130
 
8.6%
) 107
 
7.0%
( 106
 
7.0%
스 50
 
3.3%
에 37
 
2.4%
이 35
 
2.3%
리 33
 
2.2%
사 32
 
2.1%
30
 
2.0%
회 27
 
1.8%
Other values (254) 932
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1262
83.1%
Close Punctuation 107
 
7.0%
Open Punctuation 106
 
7.0%
Space Separator 30
 
2.0%
Uppercase Letter 7
 
0.5%
Decimal Number 6
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 130
 
10.3%
스 50
 
4.0%
에 37
 
2.9%
이 35
 
2.8%
리 33
 
2.6%
사 32
 
2.5%
회 27
 
2.1%
식 23
 
1.8%
린 22
 
1.7%
성 21
 
1.7%
Other values (239) 852
67.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
M 1
14.3%
C 1
14.3%
Y 1
14.3%
B 1
14.3%
A 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
9 1
16.7%
3 1
16.7%
1 1
16.7%
4 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Other Punctuation
ValueCountFrequency (%)
＆ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1262
83.1%
Common 250
 
16.5%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 130
 
10.3%
스 50
 
4.0%
에 37
 
2.9%
이 35
 
2.8%
리 33
 
2.6%
사 32
 
2.5%
회 27
 
2.1%
식 23
 
1.8%
린 22
 
1.7%
성 21
 
1.7%
Other values (239) 852
67.5%
Common
ValueCountFrequency (%)
) 107
42.8%
( 106
42.4%
30
 
12.0%
2 2
 
0.8%
＆ 1
 
0.4%
9 1
 
0.4%
3 1
 
0.4%
1 1
 
0.4%
4 1
 
0.4%
Latin
ValueCountFrequency (%)
S 2
28.6%
M 1
14.3%
C 1
14.3%
Y 1
14.3%
B 1
14.3%
A 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1262
83.1%
ASCII 256
 
16.9%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 130
 
10.3%
스 50
 
4.0%
에 37
 
2.9%
이 35
 
2.8%
리 33
 
2.6%
사 32
 
2.5%
회 27
 
2.1%
식 23
 
1.8%
린 22
 
1.7%
성 21
 
1.7%
Other values (239) 852
67.5%
ASCII
ValueCountFrequency (%)
) 107
41.8%
( 106
41.4%
30
 
11.7%
2 2
 
0.8%
S 2
 
0.8%
M 1
 
0.4%
C 1
 
0.4%
Y 1
 
0.4%
B 1
 
0.4%
A 1
 
0.4%
Other values (4) 4
 
1.6%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Date

Distinct184
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1999-10-05 00:00:00
Maximum2024-05-09 11:09:15
2024-05-11T04:08:29.453602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:08:29.877871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
157 
U
46 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 157
77.3%
U 46
 
22.7%

Length

2024-05-11T04:08:30.296679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:30.644269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 157
77.3%
u 46
 
22.7%

데이터갱신일자
Date

Distinct74
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T04:08:30.975854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:08:31.404903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
건물위생관리업
203 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 203
100.0%

Length

2024-05-11T04:08:31.894328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:32.177906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 203
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct164
Distinct (%)84.1%
Missing8
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean202416.69
Minimum193910.05
Maximum205719.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:32.541521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum193910.05
5-th percentile200522.26
Q1201330.38
median201989.27
Q3203544.69
95-th percentile205148.78
Maximum205719.83
Range11809.777
Interquartile range (IQR)2214.3086

Descriptive statistics

Standard deviation1603.9391
Coefficient of variation (CV)0.0079239468
Kurtosis2.8773819
Mean202416.69
Median Absolute Deviation (MAD)1028.4729
Skewness-0.2946864
Sum39471255
Variance2572620.7
MonotonicityNot monotonic
2024-05-11T04:08:33.001909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201215.878160704 4
 
2.0%
201459.631351667 3
 
1.5%
201770.292339503 3
 
1.5%
201803.62404929 3
 
1.5%
200854.984440466 3
 
1.5%
200608.656831329 3
 
1.5%
201724.901024486 3
 
1.5%
200841.726990037 3
 
1.5%
202010.412505798 2
 
1.0%
202736.984230664 2
 
1.0%
Other values (154) 166
81.8%
(Missing) 8
 
3.9%
ValueCountFrequency (%)
193910.050646347 1
0.5%
199755.023298919 1
0.5%
199861.559742765 1
0.5%
200013.105915953 1
0.5%
200233.152026351 1
0.5%
200246.071325337 2
1.0%
200398.987830949 1
0.5%
200422.723883879 1
0.5%
200436.045840447 1
0.5%
200559.212829633 1
0.5%
ValueCountFrequency (%)
205719.827630349 1
0.5%
205628.44785241 1
0.5%
205602.660143248 1
0.5%
205583.773471307 1
0.5%
205571.992125441 1
0.5%
205543.663020561 1
0.5%
205520.10656798 1
0.5%
205320.583627529 1
0.5%
205290.961125822 1
0.5%
205232.638999928 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct164
Distinct (%)84.1%
Missing8
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean455332.82
Minimum452935.22
Maximum457647.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:33.440019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452935.22
5-th percentile453260.69
Q1454446.18
median455417.93
Q3456300.76
95-th percentile457095.51
Maximum457647.49
Range4712.2674
Interquartile range (IQR)1854.5741

Descriptive statistics

Standard deviation1169.8943
Coefficient of variation (CV)0.0025693169
Kurtosis-0.9100388
Mean455332.82
Median Absolute Deviation (MAD)935.47543
Skewness-0.090190866
Sum88789901
Variance1368652.7
MonotonicityNot monotonic
2024-05-11T04:08:33.931375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454367.577780192 4
 
2.0%
454725.925956661 3
 
1.5%
453882.081063818 3
 
1.5%
454867.240191258 3
 
1.5%
454453.100879544 3
 
1.5%
454200.586664535 3
 
1.5%
453036.352333829 3
 
1.5%
454721.505180141 3
 
1.5%
456069.874150175 2
 
1.0%
455985.603272447 2
 
1.0%
Other values (154) 166
81.8%
(Missing) 8
 
3.9%
ValueCountFrequency (%)
452935.221547454 1
 
0.5%
452962.144125456 1
 
0.5%
453036.352333829 3
1.5%
453093.907933997 1
 
0.5%
453149.907328352 1
 
0.5%
453156.226397094 1
 
0.5%
453212.394700124 1
 
0.5%
453231.65984039 1
 
0.5%
453273.131287687 1
 
0.5%
453454.226068463 1
 
0.5%
ValueCountFrequency (%)
457647.48893155 1
0.5%
457579.902139067 1
0.5%
457522.977816057 1
0.5%
457377.671933134 1
0.5%
457373.722542473 1
0.5%
457368.697634387 1
0.5%
457346.819159596 1
0.5%
457338.238601213 1
0.5%
457105.96633226 2
1.0%
457091.02577769 1
0.5%

위생업태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
건물위생관리업
165 
<NA>
38 

Length

Max length7
Median length7
Mean length6.4384236
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 165
81.3%
<NA> 38
 
18.7%

Length

2024-05-11T04:08:34.448850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:34.808344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 165
81.3%
na 38
 
18.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)6.3%
Missing61
Missing (%)30.0%
Infinite0
Infinite (%)0.0%
Mean1.4366197
Minimum0
Maximum9
Zeros83
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:35.100477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.081546
Coefficient of variation (CV)1.4489193
Kurtosis1.2575877
Mean1.4366197
Median Absolute Deviation (MAD)0
Skewness1.3686345
Sum204
Variance4.3328339
MonotonicityNot monotonic
2024-05-11T04:08:35.416672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 83
40.9%
5 13
 
6.4%
4 12
 
5.9%
3 10
 
4.9%
2 10
 
4.9%
1 10
 
4.9%
9 2
 
1.0%
7 1
 
0.5%
6 1
 
0.5%
(Missing) 61
30.0%
ValueCountFrequency (%)
0 83
40.9%
1 10
 
4.9%
2 10
 
4.9%
3 10
 
4.9%
4 12
 
5.9%
5 13
 
6.4%
6 1
 
0.5%
7 1
 
0.5%
9 2
 
1.0%
ValueCountFrequency (%)
9 2
 
1.0%
7 1
 
0.5%
6 1
 
0.5%
5 13
 
6.4%
4 12
 
5.9%
3 10
 
4.9%
2 10
 
4.9%
1 10
 
4.9%
0 83
40.9%

건물지하층수
Categorical

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
97 
<NA>
69 
1
35 
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length2.0197044
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 97
47.8%
<NA> 69
34.0%
1 35
 
17.2%
3 1
 
0.5%
2 1
 
0.5%

Length

2024-05-11T04:08:35.795848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:36.084667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 97
47.8%
na 69
34.0%
1 35
 
17.2%
3 1
 
0.5%
2 1
 
0.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)7.5%
Missing83
Missing (%)40.9%
Infinite0
Infinite (%)0.0%
Mean1.8583333
Minimum0
Maximum8
Zeros27
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:36.410996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.701684
Coefficient of variation (CV)0.91570437
Kurtosis1.1466226
Mean1.8583333
Median Absolute Deviation (MAD)1
Skewness1.1199758
Sum223
Variance2.8957283
MonotonicityNot monotonic
2024-05-11T04:08:36.782985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 34
16.7%
0 27
 
13.3%
2 26
 
12.8%
4 12
 
5.9%
3 12
 
5.9%
5 4
 
2.0%
6 3
 
1.5%
7 1
 
0.5%
8 1
 
0.5%
(Missing) 83
40.9%
ValueCountFrequency (%)
0 27
13.3%
1 34
16.7%
2 26
12.8%
3 12
 
5.9%
4 12
 
5.9%
5 4
 
2.0%
6 3
 
1.5%
7 1
 
0.5%
8 1
 
0.5%
ValueCountFrequency (%)
8 1
 
0.5%
7 1
 
0.5%
6 3
 
1.5%
5 4
 
2.0%
4 12
 
5.9%
3 12
 
5.9%
2 26
12.8%
1 34
16.7%
0 27
13.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)10.7%
Missing128
Missing (%)63.1%
Infinite0
Infinite (%)0.0%
Mean2.0666667
Minimum0
Maximum8
Zeros9
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:37.160826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6135686
Coefficient of variation (CV)0.780759
Kurtosis1.7413452
Mean2.0666667
Median Absolute Deviation (MAD)1
Skewness1.1978042
Sum155
Variance2.6036036
MonotonicityNot monotonic
2024-05-11T04:08:37.520896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 23
 
11.3%
2 22
 
10.8%
0 9
 
4.4%
4 8
 
3.9%
3 7
 
3.4%
5 3
 
1.5%
6 2
 
1.0%
8 1
 
0.5%
(Missing) 128
63.1%
ValueCountFrequency (%)
0 9
 
4.4%
1 23
11.3%
2 22
10.8%
3 7
 
3.4%
4 8
 
3.9%
5 3
 
1.5%
6 2
 
1.0%
8 1
 
0.5%
ValueCountFrequency (%)
8 1
 
0.5%
6 2
 
1.0%
5 3
 
1.5%
4 8
 
3.9%
3 7
 
3.4%
2 22
10.8%
1 23
11.3%
0 9
 
4.4%

사용시작지하층
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
151 
0
38 
1
 
14

Length

Max length4
Median length4
Mean length3.2315271
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
74.4%
0 38
 
18.7%
1 14
 
6.9%

Length

2024-05-11T04:08:37.942396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:38.305194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
74.4%
0 38
 
18.7%
1 14
 
6.9%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
176 
0
18 
1
 
9

Length

Max length4
Median length4
Mean length3.6009852
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
86.7%
0 18
 
8.9%
1 9
 
4.4%

Length

2024-05-11T04:08:38.669642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:39.264378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
86.7%
0 18
 
8.9%
1 9
 
4.4%

한실수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
112 
<NA>
91 

Length

Max length4
Median length1
Mean length2.3448276
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 112
55.2%
<NA> 91
44.8%

Length

2024-05-11T04:08:39.606235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:39.946095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 112
55.2%
na 91
44.8%

양실수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
112 
<NA>
91 

Length

Max length4
Median length1
Mean length2.3448276
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 112
55.2%
<NA> 91
44.8%

Length

2024-05-11T04:08:40.338896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:40.701229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 112
55.2%
na 91
44.8%

욕실수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
112 
<NA>
91 

Length

Max length4
Median length1
Mean length2.3448276
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 112
55.2%
<NA> 91
44.8%

Length

2024-05-11T04:08:41.062653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:41.446412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 112
55.2%
na 91
44.8%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing40
Missing (%)19.7%
Memory size538.0 B
False
163 
(Missing)
40 
ValueCountFrequency (%)
False 163
80.3%
(Missing) 40
 
19.7%
2024-05-11T04:08:41.827810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
112 
<NA>
91 

Length

Max length4
Median length1
Mean length2.3448276
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 112
55.2%
<NA> 91
44.8%

Length

2024-05-11T04:08:42.217647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:42.581640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 112
55.2%
na 91
44.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing203
Missing (%)100.0%
Memory size1.9 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
193 
임대
 
10

Length

Max length4
Median length4
Mean length3.9014778
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> 193
95.1%
임대 10
 
4.9%

Length

2024-05-11T04:08:42.981114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:43.379946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
95.1%
임대 10
 
4.9%

세탁기수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
111 
0
92 

Length

Max length4
Median length4
Mean length2.6403941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 111
54.7%
0 92
45.3%

Length

2024-05-11T04:08:43.826164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:44.178717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 111
54.7%
0 92
45.3%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
164 
0
31 
1
 
7
9
 
1

Length

Max length4
Median length4
Mean length3.4236453
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 164
80.8%
0 31
 
15.3%
1 7
 
3.4%
9 1
 
0.5%

Length

2024-05-11T04:08:44.703819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:45.194569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 164
80.8%
0 31
 
15.3%
1 7
 
3.4%
9 1
 
0.5%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)15.4%
Missing164
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean0.71794872
Minimum0
Maximum7
Zeros27
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T04:08:45.658127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3.2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5034822
Coefficient of variation (CV)2.094136
Kurtosis8.572906
Mean0.71794872
Median Absolute Deviation (MAD)0
Skewness2.8121995
Sum28
Variance2.2604588
MonotonicityNot monotonic
2024-05-11T04:08:46.108444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 27
 
13.3%
1 6
 
3.0%
2 2
 
1.0%
3 2
 
1.0%
5 1
 
0.5%
7 1
 
0.5%
(Missing) 164
80.8%
ValueCountFrequency (%)
0 27
13.3%
1 6
 
3.0%
2 2
 
1.0%
3 2
 
1.0%
5 1
 
0.5%
7 1
 
0.5%
ValueCountFrequency (%)
7 1
 
0.5%
5 1
 
0.5%
3 2
 
1.0%
2 2
 
1.0%
1 6
 
3.0%
0 27
13.3%

회수건조수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
117 
0
86 

Length

Max length4
Median length4
Mean length2.729064
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> 117
57.6%
0 86
42.4%

Length

2024-05-11T04:08:46.583926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:46.915776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
57.6%
0 86
42.4%

침대수
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
120 
0
83 

Length

Max length4
Median length4
Mean length2.773399
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> 120
59.1%
0 83
40.9%

Length

2024-05-11T04:08:47.381014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:47.752741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
59.1%
0 83
40.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing38
Missing (%)18.7%
Memory size538.0 B
False
165 
(Missing)
38 
ValueCountFrequency (%)
False 165
81.3%
(Missing) 38
 
18.7%
2024-05-11T04:08:48.088572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030700003070000-206-1991-0286919910508<NA>1영업/정상1영업<NA><NA><NA><NA>020964050850.00136120서울특별시 성북구 상월곡동 24-194 웅진빌딩서울특별시 성북구 화랑로18가길 21, 웅진빌딩 3층 301호 (상월곡동)2791(주)국제안전시스템2020-11-30 15:41:43U2020-12-02 02:40:00.0건물위생관리업204287.033178455882.236992건물위생관리업000000000N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
130700003070000-206-1993-0286019930111<NA>3폐업2폐업20021202<NA><NA><NA>020745026856.10136031서울특별시 성북구 동소문동1가 51-0<NA><NA>(주)선진프라자2003-06-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업200608.656831454200.586665건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230700003070000-206-1993-0286119930423<NA>3폐업2폐업20030410<NA><NA><NA>02 763772170.35136044서울특별시 성북구 삼선동4가 9-7<NA><NA>(주)일운설비2003-04-10 00:00:00I2018-08-31 23:59:59.0건물위생관리업200867.270359454072.427002건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330700003070000-206-1993-0286619931118<NA>3폐업2폐업20180910<NA><NA><NA>02 912092199.70136827서울특별시 성북구 장위동 62-12서울특별시 성북구 화랑로35길 56 (장위동)2776두산종합관리(주)2018-09-10 16:11:57U2018-09-10 23:59:59.0건물위생관리업204893.970144456797.938626건물위생관리업3122<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430700003070000-206-1993-0286719930326<NA>3폐업2폐업20040130<NA><NA><NA>0209135954114.35136858서울특별시 성북구 종암동 8-260<NA><NA>일성설비(주)2003-02-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업203263.71381454754.431589건물위생관리업2111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530700003070000-206-1994-0285319941111<NA>3폐업2폐업19951209<NA><NA><NA>020945066576.32136874서울특별시 성북구 하월곡동 90-1132<NA><NA>무지게파워환경2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업202935.804436455669.596142건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630700003070000-206-1994-0286819940624<NA>3폐업2폐업19951209<NA><NA><NA>020929502471.18136055서울특별시 성북구 동선동5가 46-0<NA><NA>오성2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업201409.647482454807.434108건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730700003070000-206-1994-0287019940720<NA>3폐업2폐업19951209<NA><NA><NA>020909218894.82136874서울특별시 성북구 하월곡동 90-109<NA><NA>서암건물관리(주)2001-09-27 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
830700003070000-206-1994-0287219941005<NA>3폐업2폐업19961210<NA><NA><NA>02 9636991296.54136817서울특별시 성북구 석관동 125-17<NA><NA>(주)제산시스템2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업205628.447852456577.675679건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930700003070000-206-1995-0286319951109<NA>3폐업2폐업20021202<NA><NA><NA>02 9285437.00136087서울특별시 성북구 보문동7가 120-1<NA><NA>리빙용역2003-06-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업201925.779526452962.144125건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
19330700003070000-206-2022-0000420220610<NA>1영업/정상1영업<NA><NA><NA><NA>02 915 424733.00136801서울특별시 성북구 길음동 1070-19서울특별시 성북구 동소문로 269-13, 2층 203호 (길음동)2732주식회사 마리글로벌2022-06-10 14:45:48I2021-12-05 23:02:00.0건물위생관리업202153.432201455880.68555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19430700003070000-206-2022-0000520220812<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.77136755서울특별시 성북구 돈암동 15-1 돈암동 삼성아파트서울특별시 성북구 동소문로34길 24, B상가동 205호 (돈암동, 돈암동 삼성아파트)2807유니탑2022-08-12 15:39:05I2021-12-07 23:04:00.0건물위생관리업201989.271689455190.095863<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19530700003070000-206-2023-000012023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.18136-819서울특별시 성북구 석관동 261-133서울특별시 성북구 화랑로32길 100, 1층 좌측호 (석관동)2789클리어존2023-03-08 13:13:45I2022-12-02 23:00:00.0건물위생관리업205112.840567456009.558088<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19630700003070000-206-2023-000022023-05-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>58.78136-815서울특별시 성북구 석관동 306-4 유태영치과의원서울특별시 성북구 돌곶이로 36, 유태영치과의원 2층 (석관동)2785(주)위라보2023-05-26 11:07:58I2022-12-04 22:08:00.0건물위생관리업205290.961126456137.81235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19730700003070000-206-2023-000032023-07-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.54136-825서울특별시 성북구 성북동 175-3 창성교회서울특별시 성북구 성북로10길 6, 창성교회 2층 (성북동)2835인트로맨(주)2023-07-25 11:14:01I2022-12-06 22:07:00.0건물위생관리업200246.071325454396.421633<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19830700003070000-206-2023-000042023-08-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.00136-841서울특별시 성북구 정릉동 16-118서울특별시 성북구 정릉로40길 18, 1층 (정릉동)2816윈시스템2023-08-21 14:20:06I2022-12-07 22:03:00.0건물위생관리업201656.305939455445.632894<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19930700003070000-206-2023-000052023-11-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>87.36136-864서울특별시 성북구 종암동 3-327서울특별시 성북구 월곡로5길 38, 1층 (종암동)279739어비스(ABYSS)2023-11-30 11:28:57I2022-11-02 00:02:00.0건물위생관리업203238.406771455128.190836<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20030700003070000-206-2023-000062023-11-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 32966057120.30136-824서울특별시 성북구 성북동 125-9 백강빌딩서울특별시 성북구 성북로 87-1, 백강빌딩 2층 (성북동)2880(주)에스지공영2024-01-22 14:39:20I2023-11-30 22:04:00.0건물위생관리업199861.559743454508.792987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20130700003070000-206-2024-000012024-01-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.30136-863서울특별시 성북구 종암동 124-25 201호서울특별시 성북구 정릉로 446-1, 201호 (종암동)2802주식회사 다다크린2024-01-26 14:54:10I2023-11-30 22:08:00.0건물위생관리업202666.543222455694.581028<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20230700003070000-206-2024-000032024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 26574447115.68136-036서울특별시 성북구 동소문동6가 117-2 보미리즌빌서울특별시 성북구 동소문로 89, 보미리즌빌 6층 (동소문동6가)2830(주)보미엔터프라이즈2024-04-30 16:13:40I2023-12-05 00:02:00.0건물위생관리업201294.859108454483.588644<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>