Overview

Dataset statistics

Number of variables47
Number of observations286
Missing cells3357
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.0 KiB
Average record size in memory404.5 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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-19279/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.0%)Imbalance
위생업태명 is highly imbalanced (64.4%)Imbalance
사용시작지하층 is highly imbalanced (58.0%)Imbalance
사용끝지하층 is highly imbalanced (75.1%)Imbalance
건물소유구분명 is highly imbalanced (59.8%)Imbalance
여성종사자수 is highly imbalanced (73.6%)Imbalance
다중이용업소여부 is highly imbalanced (96.3%)Imbalance
인허가취소일자 has 286 (100.0%) missing valuesMissing
폐업일자 has 72 (25.2%) missing valuesMissing
휴업시작일자 has 286 (100.0%) missing valuesMissing
휴업종료일자 has 286 (100.0%) missing valuesMissing
재개업일자 has 286 (100.0%) missing valuesMissing
전화번호 has 57 (19.9%) missing valuesMissing
소재지우편번호 has 3 (1.0%) missing valuesMissing
지번주소 has 3 (1.0%) missing valuesMissing
도로명주소 has 129 (45.1%) missing valuesMissing
도로명우편번호 has 129 (45.1%) missing valuesMissing
좌표정보(X) has 9 (3.1%) missing valuesMissing
좌표정보(Y) has 9 (3.1%) missing valuesMissing
건물지상층수 has 124 (43.4%) missing valuesMissing
건물지하층수 has 132 (46.2%) missing valuesMissing
사용시작지상층 has 154 (53.8%) missing valuesMissing
사용끝지상층 has 217 (75.9%) missing valuesMissing
발한실여부 has 39 (13.6%) missing valuesMissing
조건부허가신고사유 has 286 (100.0%) missing valuesMissing
조건부허가시작일자 has 286 (100.0%) missing valuesMissing
조건부허가종료일자 has 286 (100.0%) missing valuesMissing
남성종사자수 has 246 (86.0%) missing valuesMissing
다중이용업소여부 has 32 (11.2%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 103 (36.0%) zerosZeros
건물지하층수 has 130 (45.5%) zerosZeros
사용시작지상층 has 51 (17.8%) zerosZeros
사용끝지상층 has 11 (3.8%) zerosZeros
남성종사자수 has 26 (9.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:25:05.721734
Analysis finished2024-05-11 05:25:06.683182
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3020000
286 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 286
100.0%

Length

2024-05-11T14:25:06.779402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:06.896141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 286
100.0%

관리번호
Text

UNIQUE 

Distinct286
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T14:25:07.094204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6292
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

Unique286 ?
Unique (%)100.0%

Sample

1st row3020000-206-1987-01718
2nd row3020000-206-1987-01720
3rd row3020000-206-1989-01721
4th row3020000-206-1989-01722
5th row3020000-206-1991-01719
ValueCountFrequency (%)
3020000-206-1987-01718 1
 
0.3%
3020000-206-2010-00015 1
 
0.3%
3020000-206-2011-00005 1
 
0.3%
3020000-206-2011-00004 1
 
0.3%
3020000-206-2011-00003 1
 
0.3%
3020000-206-2011-00002 1
 
0.3%
3020000-206-2011-00001 1
 
0.3%
3020000-206-2011-00009 1
 
0.3%
3020000-206-2010-00014 1
 
0.3%
3020000-206-2011-00007 1
 
0.3%
Other values (276) 276
96.5%
2024-05-11T14:25:07.493173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3007
47.8%
2 896
 
14.2%
- 858
 
13.6%
3 364
 
5.8%
6 352
 
5.6%
1 344
 
5.5%
9 156
 
2.5%
7 125
 
2.0%
5 79
 
1.3%
4 61
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5434
86.4%
Dash Punctuation 858
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3007
55.3%
2 896
 
16.5%
3 364
 
6.7%
6 352
 
6.5%
1 344
 
6.3%
9 156
 
2.9%
7 125
 
2.3%
5 79
 
1.5%
4 61
 
1.1%
8 50
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 858
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3007
47.8%
2 896
 
14.2%
- 858
 
13.6%
3 364
 
5.8%
6 352
 
5.6%
1 344
 
5.5%
9 156
 
2.5%
7 125
 
2.0%
5 79
 
1.3%
4 61
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3007
47.8%
2 896
 
14.2%
- 858
 
13.6%
3 364
 
5.8%
6 352
 
5.6%
1 344
 
5.5%
9 156
 
2.5%
7 125
 
2.0%
5 79
 
1.3%
4 61
 
1.0%
Distinct274
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1987-07-04 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T14:25:07.892897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:25:08.079428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3
214 
1
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 214
74.8%
1 72
 
25.2%

Length

2024-05-11T14:25:08.265213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:08.456961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 214
74.8%
1 72
 
25.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
214 
영업/정상
72 

Length

Max length5
Median length2
Mean length2.7552448
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 214
74.8%
영업/정상 72
 
25.2%

Length

2024-05-11T14:25:08.640680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:08.766705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 214
74.8%
영업/정상 72
 
25.2%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2
214 
1
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 214
74.8%
1 72
 
25.2%

Length

2024-05-11T14:25:08.906139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:09.020209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 214
74.8%
1 72
 
25.2%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
214 
영업
72 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 214
74.8%
영업 72
 
25.2%

Length

2024-05-11T14:25:09.189562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:09.331895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 214
74.8%
영업 72
 
25.2%

폐업일자
Date

MISSING 

Distinct173
Distinct (%)80.8%
Missing72
Missing (%)25.2%
Memory size2.4 KiB
Minimum1995-03-20 00:00:00
Maximum2024-03-26 00:00:00
2024-05-11T14:25:09.485665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:25:09.667261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

전화번호
Text

MISSING 

Distinct217
Distinct (%)94.8%
Missing57
Missing (%)19.9%
Memory size2.4 KiB
2024-05-11T14:25:10.079960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.9956332
Min length7

Characters and Unicode

Total characters2289
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

Unique206 ?
Unique (%)90.0%

Sample

1st row02 7171365
2nd row02 7941674
3rd row02 7555161
4th row02 7024784
5th row0207144676
ValueCountFrequency (%)
02 148
34.3%
797 4
 
0.9%
5050 3
 
0.7%
702 3
 
0.7%
749 3
 
0.7%
7555161 3
 
0.7%
32729977 3
 
0.7%
793 3
 
0.7%
7969124 3
 
0.7%
794 2
 
0.5%
Other values (246) 257
59.5%
2024-05-11T14:25:10.691471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 361
15.8%
2 322
14.1%
7 314
13.7%
264
11.5%
9 197
8.6%
1 173
7.6%
3 163
7.1%
5 136
 
5.9%
4 132
 
5.8%
8 117
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2025
88.5%
Space Separator 264
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 361
17.8%
2 322
15.9%
7 314
15.5%
9 197
9.7%
1 173
8.5%
3 163
8.0%
5 136
 
6.7%
4 132
 
6.5%
8 117
 
5.8%
6 110
 
5.4%
Space Separator
ValueCountFrequency (%)
264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2289
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 361
15.8%
2 322
14.1%
7 314
13.7%
264
11.5%
9 197
8.6%
1 173
7.6%
3 163
7.1%
5 136
 
5.9%
4 132
 
5.8%
8 117
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 361
15.8%
2 322
14.1%
7 314
13.7%
264
11.5%
9 197
8.6%
1 173
7.6%
3 163
7.1%
5 136
 
5.9%
4 132
 
5.8%
8 117
 
5.1%
Distinct196
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T14:25:11.188897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9545455
Min length3

Characters and Unicode

Total characters1417
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

Unique172 ?
Unique (%)60.1%

Sample

1st row80.88
2nd row108.08
3rd row.00
4th row67.93
5th row49.50
ValueCountFrequency (%)
00 39
 
13.6%
30.00 7
 
2.4%
66.00 7
 
2.4%
33.00 7
 
2.4%
49.50 6
 
2.1%
82.50 5
 
1.7%
20.00 4
 
1.4%
12.00 3
 
1.0%
19.80 3
 
1.0%
99.00 3
 
1.0%
Other values (186) 202
70.6%
2024-05-11T14:25:11.947937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 359
25.3%
. 286
20.2%
2 102
 
7.2%
1 102
 
7.2%
3 95
 
6.7%
8 92
 
6.5%
4 84
 
5.9%
9 83
 
5.9%
5 77
 
5.4%
6 74
 
5.2%
Other values (2) 63
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1126
79.5%
Other Punctuation 291
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 359
31.9%
2 102
 
9.1%
1 102
 
9.1%
3 95
 
8.4%
8 92
 
8.2%
4 84
 
7.5%
9 83
 
7.4%
5 77
 
6.8%
6 74
 
6.6%
7 58
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 286
98.3%
, 5
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1417
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 359
25.3%
. 286
20.2%
2 102
 
7.2%
1 102
 
7.2%
3 95
 
6.7%
8 92
 
6.5%
4 84
 
5.9%
9 83
 
5.9%
5 77
 
5.4%
6 74
 
5.2%
Other values (2) 63
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 359
25.3%
. 286
20.2%
2 102
 
7.2%
1 102
 
7.2%
3 95
 
6.7%
8 92
 
6.5%
4 84
 
5.9%
9 83
 
5.9%
5 77
 
5.4%
6 74
 
5.2%
Other values (2) 63
 
4.4%

소재지우편번호
Text

MISSING 

Distinct97
Distinct (%)34.3%
Missing3
Missing (%)1.0%
Memory size2.4 KiB
2024-05-11T14:25:12.407321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0812721
Min length6

Characters and Unicode

Total characters1721
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

Unique42 ?
Unique (%)14.8%

Sample

1st row140090
2nd row140889
3rd row140901
4th row140806
5th row140807
ValueCountFrequency (%)
140871 14
 
4.9%
140846 13
 
4.6%
140011 12
 
4.2%
140872 11
 
3.9%
140889 10
 
3.5%
140880 9
 
3.2%
140848 9
 
3.2%
140827 8
 
2.8%
140893 8
 
2.8%
140847 7
 
2.5%
Other values (87) 182
64.3%
2024-05-11T14:25:13.087126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 389
22.6%
1 371
21.6%
4 330
19.2%
8 270
15.7%
7 92
 
5.3%
9 69
 
4.0%
2 64
 
3.7%
6 47
 
2.7%
3 33
 
1.9%
5 33
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1698
98.7%
Dash Punctuation 23
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 389
22.9%
1 371
21.8%
4 330
19.4%
8 270
15.9%
7 92
 
5.4%
9 69
 
4.1%
2 64
 
3.8%
6 47
 
2.8%
3 33
 
1.9%
5 33
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1721
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 389
22.6%
1 371
21.6%
4 330
19.2%
8 270
15.7%
7 92
 
5.3%
9 69
 
4.0%
2 64
 
3.7%
6 47
 
2.7%
3 33
 
1.9%
5 33
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1721
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 389
22.6%
1 371
21.6%
4 330
19.2%
8 270
15.7%
7 92
 
5.3%
9 69
 
4.0%
2 64
 
3.7%
6 47
 
2.7%
3 33
 
1.9%
5 33
 
1.9%

지번주소
Text

MISSING 

Distinct259
Distinct (%)91.5%
Missing3
Missing (%)1.0%
Memory size2.4 KiB
2024-05-11T14:25:13.554664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length25.533569
Min length17

Characters and Unicode

Total characters7226
Distinct characters190
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)84.8%

Sample

1st row서울특별시 용산구 신계동 43-22
2nd row서울특별시 용산구 한남동 224-0 A동3층
3rd row서울특별시 용산구 후암동 244-5
4th row서울특별시 용산구 갈월동 71-14
5th row서울특별시 용산구 갈월동 89-9 세종빌딩 702호
ValueCountFrequency (%)
서울특별시 282
20.1%
용산구 282
20.1%
한강로2가 42
 
3.0%
한강로3가 40
 
2.9%
한남동 33
 
2.4%
2층 18
 
1.3%
원효로1가 17
 
1.2%
3층 15
 
1.1%
서계동 15
 
1.1%
원효로3가 14
 
1.0%
Other values (406) 642
45.9%
2024-05-11T14:25:14.225089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1344
18.6%
1 320
 
4.4%
304
 
4.2%
300
 
4.2%
297
 
4.1%
287
 
4.0%
284
 
3.9%
283
 
3.9%
282
 
3.9%
282
 
3.9%
Other values (180) 3243
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4037
55.9%
Decimal Number 1558
 
21.6%
Space Separator 1344
 
18.6%
Dash Punctuation 247
 
3.4%
Uppercase Letter 15
 
0.2%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 7
 
0.1%
Lowercase Letter 3
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
304
 
7.5%
300
 
7.4%
297
 
7.4%
287
 
7.1%
284
 
7.0%
283
 
7.0%
282
 
7.0%
282
 
7.0%
164
 
4.1%
163
 
4.0%
Other values (153) 1391
34.5%
Decimal Number
ValueCountFrequency (%)
1 320
20.5%
2 256
16.4%
3 213
13.7%
4 159
10.2%
0 141
9.1%
5 104
 
6.7%
6 104
 
6.7%
7 98
 
6.3%
9 88
 
5.6%
8 75
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
53.3%
D 2
 
13.3%
T 1
 
6.7%
A 1
 
6.7%
K 1
 
6.7%
E 1
 
6.7%
L 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 3
42.9%
/ 2
28.6%
. 2
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
1344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 247
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4037
55.9%
Common 3170
43.9%
Latin 19
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
304
 
7.5%
300
 
7.4%
297
 
7.4%
287
 
7.1%
284
 
7.0%
283
 
7.0%
282
 
7.0%
282
 
7.0%
164
 
4.1%
163
 
4.0%
Other values (153) 1391
34.5%
Common
ValueCountFrequency (%)
1344
42.4%
1 320
 
10.1%
2 256
 
8.1%
- 247
 
7.8%
3 213
 
6.7%
4 159
 
5.0%
0 141
 
4.4%
5 104
 
3.3%
6 104
 
3.3%
7 98
 
3.1%
Other values (7) 184
 
5.8%
Latin
ValueCountFrequency (%)
B 8
42.1%
e 2
 
10.5%
D 2
 
10.5%
1
 
5.3%
T 1
 
5.3%
A 1
 
5.3%
K 1
 
5.3%
a 1
 
5.3%
E 1
 
5.3%
L 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4037
55.9%
ASCII 3188
44.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1344
42.2%
1 320
 
10.0%
2 256
 
8.0%
- 247
 
7.7%
3 213
 
6.7%
4 159
 
5.0%
0 141
 
4.4%
5 104
 
3.3%
6 104
 
3.3%
7 98
 
3.1%
Other values (16) 202
 
6.3%
Hangul
ValueCountFrequency (%)
304
 
7.5%
300
 
7.4%
297
 
7.4%
287
 
7.1%
284
 
7.0%
283
 
7.0%
282
 
7.0%
282
 
7.0%
164
 
4.1%
163
 
4.0%
Other values (153) 1391
34.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct151
Distinct (%)96.2%
Missing129
Missing (%)45.1%
Memory size2.4 KiB
2024-05-11T14:25:14.645939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length33.828025
Min length19

Characters and Unicode

Total characters5311
Distinct characters182
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)92.4%

Sample

1st row서울특별시 용산구 독서당로14길 9 (한남동)
2nd row서울특별시 용산구 한강대로 283 (갈월동,세종빌딩 702호)
3rd row서울특별시 용산구 백범로90다길 3 (문배동,1층)
4th row서울특별시 용산구 청파로 349 (서계동,태호빌딩5층 (502호))
5th row서울특별시 용산구 원효로41길 58-1, 4층 (원효로2가)
ValueCountFrequency (%)
서울특별시 156
 
15.5%
용산구 156
 
15.5%
3층 19
 
1.9%
한강로2가 19
 
1.9%
한강대로 18
 
1.8%
2층 18
 
1.8%
원효로 14
 
1.4%
한강로3가 14
 
1.4%
1층 12
 
1.2%
청파로 11
 
1.1%
Other values (333) 568
56.5%
2024-05-11T14:25:15.329108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
849
 
16.0%
232
 
4.4%
1 218
 
4.1%
2 183
 
3.4%
171
 
3.2%
167
 
3.1%
167
 
3.1%
161
 
3.0%
, 160
 
3.0%
) 158
 
3.0%
Other values (172) 2845
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2993
56.4%
Decimal Number 943
 
17.8%
Space Separator 849
 
16.0%
Other Punctuation 161
 
3.0%
Close Punctuation 158
 
3.0%
Open Punctuation 158
 
3.0%
Dash Punctuation 34
 
0.6%
Uppercase Letter 12
 
0.2%
Lowercase Letter 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
232
 
7.8%
171
 
5.7%
167
 
5.6%
167
 
5.6%
161
 
5.4%
156
 
5.2%
156
 
5.2%
156
 
5.2%
156
 
5.2%
109
 
3.6%
Other values (149) 1362
45.5%
Decimal Number
ValueCountFrequency (%)
1 218
23.1%
2 183
19.4%
3 126
13.4%
0 101
10.7%
4 81
 
8.6%
8 53
 
5.6%
5 49
 
5.2%
6 46
 
4.9%
7 46
 
4.9%
9 40
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 8
66.7%
E 1
 
8.3%
L 1
 
8.3%
K 1
 
8.3%
T 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 160
99.4%
. 1
 
0.6%
Space Separator
ValueCountFrequency (%)
849
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2993
56.4%
Common 2303
43.4%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
232
 
7.8%
171
 
5.7%
167
 
5.6%
167
 
5.6%
161
 
5.4%
156
 
5.2%
156
 
5.2%
156
 
5.2%
156
 
5.2%
109
 
3.6%
Other values (149) 1362
45.5%
Common
ValueCountFrequency (%)
849
36.9%
1 218
 
9.5%
2 183
 
7.9%
, 160
 
6.9%
) 158
 
6.9%
( 158
 
6.9%
3 126
 
5.5%
0 101
 
4.4%
4 81
 
3.5%
8 53
 
2.3%
Other values (6) 216
 
9.4%
Latin
ValueCountFrequency (%)
B 8
53.3%
e 2
 
13.3%
1
 
6.7%
E 1
 
6.7%
L 1
 
6.7%
K 1
 
6.7%
T 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2993
56.4%
ASCII 2317
43.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
849
36.6%
1 218
 
9.4%
2 183
 
7.9%
, 160
 
6.9%
) 158
 
6.8%
( 158
 
6.8%
3 126
 
5.4%
0 101
 
4.4%
4 81
 
3.5%
8 53
 
2.3%
Other values (12) 230
 
9.9%
Hangul
ValueCountFrequency (%)
232
 
7.8%
171
 
5.7%
167
 
5.6%
167
 
5.6%
161
 
5.4%
156
 
5.2%
156
 
5.2%
156
 
5.2%
156
 
5.2%
109
 
3.6%
Other values (149) 1362
45.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)36.3%
Missing129
Missing (%)45.1%
Infinite0
Infinite (%)0.0%
Mean4415.5096
Minimum4300
Maximum12927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:15.591760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4303
Q14337
median4366
Q34382
95-th percentile4410
Maximum12927
Range8627
Interquartile range (IQR)45

Descriptive statistics

Standard deviation684.35667
Coefficient of variation (CV)0.15498928
Kurtosis156.33565
Mean4415.5096
Median Absolute Deviation (MAD)17
Skewness12.490402
Sum693235
Variance468344.05
MonotonicityNot monotonic
2024-05-11T14:25:15.831636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4382 12
 
4.2%
4352 8
 
2.8%
4363 8
 
2.8%
4376 8
 
2.8%
4365 6
 
2.1%
4373 6
 
2.1%
4386 6
 
2.1%
4300 5
 
1.7%
4370 5
 
1.7%
4410 5
 
1.7%
Other values (47) 88
30.8%
(Missing) 129
45.1%
ValueCountFrequency (%)
4300 5
1.7%
4301 2
 
0.7%
4303 4
1.4%
4304 2
 
0.7%
4315 3
1.0%
4316 5
1.7%
4317 1
 
0.3%
4321 1
 
0.3%
4322 2
 
0.7%
4323 2
 
0.7%
ValueCountFrequency (%)
12927 1
 
0.3%
4428 2
 
0.7%
4419 1
 
0.3%
4412 1
 
0.3%
4410 5
1.7%
4409 3
1.0%
4407 1
 
0.3%
4406 3
1.0%
4405 1
 
0.3%
4402 1
 
0.3%
Distinct278
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T14:25:16.250264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.1748252
Min length2

Characters and Unicode

Total characters2338
Distinct characters292
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)94.8%

Sample

1st row삼환흥업(주)
2nd row(주)동방디에스시스템
3rd row삼신용역
4th row성화개발(주)
5th row태광진흥(주)
ValueCountFrequency (%)
주식회사 14
 
4.4%
정심유통(주 3
 
1.0%
3
 
1.0%
주)정성디앤엠 2
 
0.6%
케이비에스진흥개발(주 2
 
0.6%
삼신용역(주 2
 
0.6%
주)흥업 2
 
0.6%
사람들 2
 
0.6%
주)경남시스템 2
 
0.6%
주)휴먼에스엔피 2
 
0.6%
Other values (281) 281
89.2%
2024-05-11T14:25:16.836071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
9.2%
( 202
 
8.6%
) 202
 
8.6%
98
 
4.2%
64
 
2.7%
57
 
2.4%
39
 
1.7%
36
 
1.5%
30
 
1.3%
29
 
1.2%
Other values (282) 1366
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1884
80.6%
Open Punctuation 202
 
8.6%
Close Punctuation 202
 
8.6%
Space Separator 29
 
1.2%
Uppercase Letter 13
 
0.6%
Other Punctuation 4
 
0.2%
Lowercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
215
 
11.4%
98
 
5.2%
64
 
3.4%
57
 
3.0%
39
 
2.1%
36
 
1.9%
30
 
1.6%
29
 
1.5%
28
 
1.5%
27
 
1.4%
Other values (269) 1261
66.9%
Uppercase Letter
ValueCountFrequency (%)
M 4
30.8%
S 3
23.1%
C 3
23.1%
B 2
15.4%
F 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
m 1
25.0%
r 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
. 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 202
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1884
80.6%
Common 437
 
18.7%
Latin 17
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
215
 
11.4%
98
 
5.2%
64
 
3.4%
57
 
3.0%
39
 
2.1%
36
 
1.9%
30
 
1.6%
29
 
1.5%
28
 
1.5%
27
 
1.4%
Other values (269) 1261
66.9%
Latin
ValueCountFrequency (%)
M 4
23.5%
S 3
17.6%
C 3
17.6%
B 2
11.8%
o 2
11.8%
m 1
 
5.9%
r 1
 
5.9%
F 1
 
5.9%
Common
ValueCountFrequency (%)
( 202
46.2%
) 202
46.2%
29
 
6.6%
& 2
 
0.5%
. 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1884
80.6%
ASCII 454
 
19.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
215
 
11.4%
98
 
5.2%
64
 
3.4%
57
 
3.0%
39
 
2.1%
36
 
1.9%
30
 
1.6%
29
 
1.5%
28
 
1.5%
27
 
1.4%
Other values (269) 1261
66.9%
ASCII
ValueCountFrequency (%)
( 202
44.5%
) 202
44.5%
29
 
6.4%
M 4
 
0.9%
S 3
 
0.7%
C 3
 
0.7%
& 2
 
0.4%
. 2
 
0.4%
B 2
 
0.4%
o 2
 
0.4%
Other values (3) 3
 
0.7%
Distinct244
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1999-05-07 00:00:00
Maximum2024-04-25 16:32:30
2024-05-11T14:25:17.051970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:25:17.274769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
I
214 
U
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 214
74.8%
U 72
 
25.2%

Length

2024-05-11T14:25:17.511638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:17.716940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 214
74.8%
u 72
 
25.2%
Distinct80
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-05-11T14:25:17.887210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:25:18.092871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
건물위생관리업
284 
건물위생관리업 기타
 
2

Length

Max length10
Median length7
Mean length7.020979
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 284
99.3%
건물위생관리업 기타 2
 
0.7%

Length

2024-05-11T14:25:18.295251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:18.479936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 286
99.3%
기타 2
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)72.9%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean197621.01
Minimum195322.6
Maximum218366.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:18.644516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195322.6
5-th percentile195929.51
Q1196761.35
median197179.08
Q3197650.24
95-th percentile200483.77
Maximum218366.2
Range23043.6
Interquartile range (IQR)888.8885

Descriptive statistics

Standard deviation1817.1272
Coefficient of variation (CV)0.0091950103
Kurtosis60.727432
Mean197621.01
Median Absolute Deviation (MAD)456.54255
Skewness5.7363073
Sum54741019
Variance3301951.2
MonotonicityNot monotonic
2024-05-11T14:25:18.849061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195385.722601944 7
 
2.4%
197179.077851578 5
 
1.7%
197137.181447006 4
 
1.4%
197128.016394734 4
 
1.4%
196189.205036161 4
 
1.4%
197083.100438264 4
 
1.4%
199678.685128404 4
 
1.4%
197043.070567006 3
 
1.0%
197515.558871235 3
 
1.0%
200483.772510759 3
 
1.0%
Other values (192) 236
82.5%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
195322.602262906 2
 
0.7%
195385.722601944 7
2.4%
195547.140326252 1
 
0.3%
195626.865584206 1
 
0.3%
195786.784181661 1
 
0.3%
195830.491553112 1
 
0.3%
195886.024469289 1
 
0.3%
195940.379990325 2
 
0.7%
195956.83241222 1
 
0.3%
195986.460643685 1
 
0.3%
ValueCountFrequency (%)
218366.202136734 1
0.3%
200740.35198837 2
0.7%
200697.42588055 2
0.7%
200670.660798804 1
0.3%
200628.554655257 1
0.3%
200597.33115081 2
0.7%
200580.674245336 1
0.3%
200580.663401657 1
0.3%
200550.758573376 1
0.3%
200550.508834553 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)72.9%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean448213.28
Minimum446114.16
Maximum450239.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:19.046057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446114.16
5-th percentile447020.84
Q1447583.74
median448008
Q3448773.78
95-th percentile449927.37
Maximum450239.91
Range4125.75
Interquartile range (IQR)1190.0422

Descriptive statistics

Standard deviation884.29882
Coefficient of variation (CV)0.001972942
Kurtosis-0.35508671
Mean448213.28
Median Absolute Deviation (MAD)502.70835
Skewness0.54872927
Sum1.2415508 × 108
Variance781984.4
MonotonicityNot monotonic
2024-05-11T14:25:19.279542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447982.919183883 7
 
2.4%
447103.868743863 5
 
1.7%
448678.609024275 4
 
1.4%
450187.639791092 4
 
1.4%
447894.643407414 4
 
1.4%
447552.774477998 4
 
1.4%
448086.564575334 4
 
1.4%
447583.735611074 3
 
1.0%
449721.082675464 3
 
1.0%
447564.413544716 3
 
1.0%
Other values (192) 236
82.5%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
446114.155238838 2
0.7%
446465.258260869 1
 
0.3%
446807.367720033 1
 
0.3%
446840.161242814 1
 
0.3%
446873.375211103 1
 
0.3%
446885.776874727 2
0.7%
446918.407128289 1
 
0.3%
446951.304743913 1
 
0.3%
447009.361612995 1
 
0.3%
447010.511469994 3
1.0%
ValueCountFrequency (%)
450239.905239 1
 
0.3%
450221.094117628 1
 
0.3%
450187.639791092 4
1.4%
450126.951675139 1
 
0.3%
450028.532903853 1
 
0.3%
450014.537949042 1
 
0.3%
449995.833612525 1
 
0.3%
449991.611230574 2
0.7%
449948.691583125 1
 
0.3%
449935.220440528 1
 
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
건물위생관리업
252 
<NA>
32 
건물위생관리업 기타
 
2

Length

Max length10
Median length7
Mean length6.6853147
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 252
88.1%
<NA> 32
 
11.2%
건물위생관리업 기타 2
 
0.7%

Length

2024-05-11T14:25:19.487690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:19.660524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 254
88.2%
na 32
 
11.1%
기타 2
 
0.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)8.0%
Missing124
Missing (%)43.4%
Infinite0
Infinite (%)0.0%
Mean2.3518519
Minimum0
Maximum28
Zeros103
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:19.837464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile15
Maximum28
Range28
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.908444
Coefficient of variation (CV)2.0870549
Kurtosis12.319326
Mean2.3518519
Median Absolute Deviation (MAD)0
Skewness3.2905645
Sum381
Variance24.092823
MonotonicityNot monotonic
2024-05-11T14:25:20.059472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 103
36.0%
4 13
 
4.5%
5 12
 
4.2%
3 10
 
3.5%
2 5
 
1.7%
15 5
 
1.7%
1 4
 
1.4%
6 3
 
1.0%
16 2
 
0.7%
28 2
 
0.7%
Other values (3) 3
 
1.0%
(Missing) 124
43.4%
ValueCountFrequency (%)
0 103
36.0%
1 4
 
1.4%
2 5
 
1.7%
3 10
 
3.5%
4 13
 
4.5%
5 12
 
4.2%
6 3
 
1.0%
8 1
 
0.3%
10 1
 
0.3%
15 5
 
1.7%
ValueCountFrequency (%)
28 2
 
0.7%
26 1
 
0.3%
16 2
 
0.7%
15 5
 
1.7%
10 1
 
0.3%
8 1
 
0.3%
6 3
 
1.0%
5 12
4.2%
4 13
4.5%
3 10
3.5%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.9%
Missing132
Missing (%)46.2%
Infinite0
Infinite (%)0.0%
Mean0.31168831
Minimum0
Maximum6
Zeros130
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:20.260569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.90401776
Coefficient of variation (CV)2.9003903
Kurtosis15.213397
Mean0.31168831
Median Absolute Deviation (MAD)0
Skewness3.6965081
Sum48
Variance0.81724811
MonotonicityNot monotonic
2024-05-11T14:25:20.430026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 130
45.5%
1 13
 
4.5%
2 4
 
1.4%
3 3
 
1.0%
4 3
 
1.0%
6 1
 
0.3%
(Missing) 132
46.2%
ValueCountFrequency (%)
0 130
45.5%
1 13
 
4.5%
2 4
 
1.4%
3 3
 
1.0%
4 3
 
1.0%
6 1
 
0.3%
ValueCountFrequency (%)
6 1
 
0.3%
4 3
 
1.0%
3 3
 
1.0%
2 4
 
1.4%
1 13
 
4.5%
0 130
45.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)9.1%
Missing154
Missing (%)53.8%
Infinite0
Infinite (%)0.0%
Mean2.1818182
Minimum0
Maximum11
Zeros51
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:20.972649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile7
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4706466
Coefficient of variation (CV)1.1323797
Kurtosis1.4478042
Mean2.1818182
Median Absolute Deviation (MAD)2
Skewness1.292625
Sum288
Variance6.1040944
MonotonicityNot monotonic
2024-05-11T14:25:21.167809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 51
 
17.8%
2 21
 
7.3%
3 21
 
7.3%
1 10
 
3.5%
4 9
 
3.1%
5 6
 
2.1%
6 4
 
1.4%
7 4
 
1.4%
9 2
 
0.7%
8 2
 
0.7%
Other values (2) 2
 
0.7%
(Missing) 154
53.8%
ValueCountFrequency (%)
0 51
17.8%
1 10
 
3.5%
2 21
7.3%
3 21
7.3%
4 9
 
3.1%
5 6
 
2.1%
6 4
 
1.4%
7 4
 
1.4%
8 2
 
0.7%
9 2
 
0.7%
ValueCountFrequency (%)
11 1
 
0.3%
10 1
 
0.3%
9 2
 
0.7%
8 2
 
0.7%
7 4
 
1.4%
6 4
 
1.4%
5 6
 
2.1%
4 9
3.1%
3 21
7.3%
2 21
7.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)17.4%
Missing217
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean3.3188406
Minimum0
Maximum18
Zeros11
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:21.467595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile9
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.0558178
Coefficient of variation (CV)0.92074858
Kurtosis7.22914
Mean3.3188406
Median Absolute Deviation (MAD)1
Skewness2.1306012
Sum229
Variance9.3380222
MonotonicityNot monotonic
2024-05-11T14:25:21.671145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 16
 
5.6%
2 14
 
4.9%
0 11
 
3.8%
4 8
 
2.8%
1 5
 
1.7%
5 4
 
1.4%
6 3
 
1.0%
7 3
 
1.0%
9 2
 
0.7%
18 1
 
0.3%
Other values (2) 2
 
0.7%
(Missing) 217
75.9%
ValueCountFrequency (%)
0 11
3.8%
1 5
 
1.7%
2 14
4.9%
3 16
5.6%
4 8
2.8%
5 4
 
1.4%
6 3
 
1.0%
7 3
 
1.0%
9 2
 
0.7%
10 1
 
0.3%
ValueCountFrequency (%)
18 1
 
0.3%
11 1
 
0.3%
10 1
 
0.3%
9 2
 
0.7%
7 3
 
1.0%
6 3
 
1.0%
5 4
 
1.4%
4 8
2.8%
3 16
5.6%
2 14
4.9%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
217 
0
60 
1
 
5
4
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.2762238
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 217
75.9%
0 60
 
21.0%
1 5
 
1.7%
4 3
 
1.0%
3 1
 
0.3%

Length

2024-05-11T14:25:21.906666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:22.098019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
75.9%
0 60
 
21.0%
1 5
 
1.7%
4 3
 
1.0%
3 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
261 
0
 
21
1
 
2
4
 
2

Length

Max length4
Median length4
Mean length3.7377622
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> 261
91.3%
0 21
 
7.3%
1 2
 
0.7%
4 2
 
0.7%

Length

2024-05-11T14:25:22.506996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:22.740686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 261
91.3%
0 21
 
7.3%
1 2
 
0.7%
4 2
 
0.7%

한실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
148 
<NA>
138 

Length

Max length4
Median length1
Mean length2.4475524
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 148
51.7%
<NA> 138
48.3%

Length

2024-05-11T14:25:22.998181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:23.201824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 148
51.7%
na 138
48.3%

양실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
148 
<NA>
138 

Length

Max length4
Median length1
Mean length2.4475524
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 148
51.7%
<NA> 138
48.3%

Length

2024-05-11T14:25:23.386103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:23.574317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 148
51.7%
na 138
48.3%

욕실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
148 
<NA>
138 

Length

Max length4
Median length1
Mean length2.4475524
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 148
51.7%
<NA> 138
48.3%

Length

2024-05-11T14:25:23.784609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:23.954824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 148
51.7%
na 138
48.3%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing39
Missing (%)13.6%
Memory size704.0 B
False
247 
(Missing)
39 
ValueCountFrequency (%)
False 247
86.4%
(Missing) 39
 
13.6%
2024-05-11T14:25:24.091135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
148 
<NA>
138 

Length

Max length4
Median length1
Mean length2.4475524
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 148
51.7%
<NA> 138
48.3%

Length

2024-05-11T14:25:24.277258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:24.453860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 148
51.7%
na 138
48.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing286
Missing (%)100.0%
Memory size2.6 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
246 
임대
37 
자가
 
3

Length

Max length4
Median length4
Mean length3.7202797
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> 246
86.0%
임대 37
 
12.9%
자가 3
 
1.0%

Length

2024-05-11T14:25:24.715572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:24.958031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
86.0%
임대 37
 
12.9%
자가 3
 
1.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
178 
0
108 

Length

Max length4
Median length4
Mean length2.8671329
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> 178
62.2%
0 108
37.8%

Length

2024-05-11T14:25:25.139339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:25.349964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
62.2%
0 108
37.8%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
247 
0
34 
2
 
2
5
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.5909091
Min length1

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 247
86.4%
0 34
 
11.9%
2 2
 
0.7%
5 1
 
0.3%
6 1
 
0.3%
1 1
 
0.3%

Length

2024-05-11T14:25:25.578292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:25.782092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
86.4%
0 34
 
11.9%
2 2
 
0.7%
5 1
 
0.3%
6 1
 
0.3%
1 1
 
0.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)20.0%
Missing246
Missing (%)86.0%
Infinite0
Infinite (%)0.0%
Mean2.25
Minimum0
Maximum26
Zeros26
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-05-11T14:25:25.954004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8.9
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.834249
Coefficient of variation (CV)2.5929996
Kurtosis13.234551
Mean2.25
Median Absolute Deviation (MAD)0
Skewness3.6391382
Sum90
Variance34.038462
MonotonicityNot monotonic
2024-05-11T14:25:26.135386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 26
 
9.1%
2 4
 
1.4%
1 3
 
1.0%
5 2
 
0.7%
26 2
 
0.7%
3 1
 
0.3%
8 1
 
0.3%
6 1
 
0.3%
(Missing) 246
86.0%
ValueCountFrequency (%)
0 26
9.1%
1 3
 
1.0%
2 4
 
1.4%
3 1
 
0.3%
5 2
 
0.7%
6 1
 
0.3%
8 1
 
0.3%
26 2
 
0.7%
ValueCountFrequency (%)
26 2
 
0.7%
8 1
 
0.3%
6 1
 
0.3%
5 2
 
0.7%
3 1
 
0.3%
2 4
 
1.4%
1 3
 
1.0%
0 26
9.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
191 
0
95 

Length

Max length4
Median length4
Mean length3.0034965
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> 191
66.8%
0 95
33.2%

Length

2024-05-11T14:25:26.350585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:26.552361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 191
66.8%
0 95
33.2%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
194 
0
92 

Length

Max length4
Median length4
Mean length3.034965
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 194
67.8%
0 92
32.2%

Length

2024-05-11T14:25:26.753353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:25:26.926623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
67.8%
0 92
32.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.8%
Missing32
Missing (%)11.2%
Memory size704.0 B
False
253 
True
 
1
(Missing)
32 
ValueCountFrequency (%)
False 253
88.5%
True 1
 
0.3%
(Missing) 32
 
11.2%
2024-05-11T14:25:27.091411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030200003020000-206-1987-0171819870704<NA>3폐업2폐업19950320<NA><NA><NA>02 717136580.88140090서울특별시 용산구 신계동 43-22<NA><NA>삼환흥업(주)2002-03-20 00:00:00I2018-08-31 23:59:59.0건물위생관리업196517.651484447901.945502건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130200003020000-206-1987-0172019870804<NA>3폐업2폐업20190911<NA><NA><NA>02 7941674108.08140889서울특별시 용산구 한남동 224-0 A동3층서울특별시 용산구 독서당로14길 9 (한남동)4410(주)동방디에스시스템2019-09-11 14:50:55U2019-09-13 02:40:00.0건물위생관리업200597.331151447832.386553건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230200003020000-206-1989-0172119890712<NA>3폐업2폐업20021022<NA><NA><NA>02 7555161.00140901서울특별시 용산구 후암동 244-5<NA><NA>삼신용역2003-03-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업197997.147101449529.230653건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330200003020000-206-1989-0172219890904<NA>3폐업2폐업19980708<NA><NA><NA>02 702478467.93140806서울특별시 용산구 갈월동 71-14<NA><NA>성화개발(주)2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업197410.273484449567.081618건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430200003020000-206-1991-0171919911120<NA>3폐업2폐업20160513<NA><NA><NA>020714467649.50140807서울특별시 용산구 갈월동 89-9 세종빌딩 702호서울특별시 용산구 한강대로 283 (갈월동,세종빌딩 702호)4321태광진흥(주)2016-05-12 16:01:15I2018-08-31 23:59:59.0건물위생관리업197450.832481449012.518444건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530200003020000-206-1991-0172319911031<NA>3폐업2폐업20200117<NA><NA><NA>02 7139813.00140100서울특별시 용산구 문배동 33-11 1층서울특별시 용산구 백범로90다길 3 (문배동,1층)4369동덕흥업(주)2020-01-17 10:37:03U2020-01-19 02:40:00.0건물위생관리업197298.387322448258.15566건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630200003020000-206-1992-0172419920128<NA>3폐업2폐업20080226<NA><NA><NA>02 749000299.00140011서울특별시 용산구 한강로1가 255-0 한길빌딩 3층<NA><NA>오형실업(주)2006-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업197520.431624448177.289086건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730200003020000-206-1992-0172519920916<NA>3폐업2폐업19960502<NA><NA><NA>02 7046416.00140090서울특별시 용산구 신계동 39-8<NA><NA>대신전기(주)2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업196579.066054447976.51988건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830200003020000-206-1992-0172619921212<NA>3폐업2폐업20050307<NA><NA><NA>02 7068065.00140869서울특별시 용산구 청파동1가 154-32 범양빌딩 202,203호<NA><NA>(주)유진엔지니어링1999-05-07 00:00:00I2018-08-31 23:59:59.0건물위생관리업197300.851983449590.701465건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930200003020000-206-1993-0172719930129<NA>3폐업2폐업19970418<NA><NA><NA>02 7192300.00140846서울특별시 용산구 원효로1가 47-24<NA><NA>동진엔지니어링2001-09-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업197137.181447448678.609024건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
27630200003020000-206-2021-0000220211112<NA>3폐업2폐업20221011<NA><NA><NA>026925307151.84140012서울특별시 용산구 한강로2가 422 래미안용산 더 센트럴서울특별시 용산구 한강대로 95, B동 18층 1825호 (한강로2가, 래미안용산 더 센트럴)4378제이피테크코리아2022-10-11 11:43:30U2021-10-30 23:03:00.0건물위생관리업197011.0447404.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27730200003020000-206-2021-0000320211125<NA>1영업/정상1영업<NA><NA><NA><NA>027973151,158.27140026서울특별시 용산구 용산동6가 69-167 신동아쇼핑서울특별시 용산구 이촌로 352, 신동아쇼핑 5층 (용산동6가)4428신동아건설(주)2021-11-25 14:47:54I2021-11-27 00:22:44.0건물위생관리업198622.89265446114.155239건물위생관리업535500000N0<NA><NA><NA>자가00000N
27830200003020000-206-2022-0000120220128<NA>1영업/정상1영업<NA><NA><NA><NA>02 790806553.80140889서울특별시 용산구 한남동 113-2 디케이밸리뷰 101동 202호서울특별시 용산구 독서당로 27, 디케이밸리뷰 101동 202호 (한남동)4410부성건설산업(주)2022-01-28 14:12:16I2022-01-30 00:22:49.0건물위생관리업200580.674245447632.608372건물위생관리업002200000N0<NA><NA><NA><NA>00000N
27930200003020000-206-2022-000022022-08-22<NA>1영업/정상1영업<NA><NA><NA><NA>02 586000234.75140-858서울특별시 용산구 이태원동 127-13 이화빌딩 5층서울특별시 용산구 보광로60길 3, 이화빌딩 5층 (이태원동)4406올이즈웰2023-08-29 13:43:50U2022-12-07 21:01:00.0건물위생관리업199432.697924447981.941091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28030200003020000-206-2022-0000320221201<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.00140909서울특별시 용산구 이촌동 203-44서울특별시 용산구 이촌로22길 14, 1층 일부호 (이촌동)4374(주)이은종합환경2022-12-01 14:43:39I2021-11-02 00:03:00.0건물위생관리업196022.593397447026.733326<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28130200003020000-206-2022-0000420221229<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.00140848서울특별시 용산구 원효로3가 51-37 e-테크벨리오피스텔서울특별시 용산구 원효로 128, e-테크벨리오피스텔 6층 611호 (원효로3가)4366클린비젼2022-12-29 10:51:56I2021-11-01 21:01:00.0건물위생관리업196189.205036447894.643407<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28230200003020000-206-2023-000012023-06-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 794 317720.50140-160서울특별시 용산구 남영동 50-1서울특별시 용산구 한강대로80길 21-7, 1층 101호 (남영동)4352(주)웰빙이앤지2023-06-07 15:02:53I2022-12-06 00:09:00.0건물위생관리업197621.641524448967.231392<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28330200003020000-206-2023-000022023-08-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 3142450044.03140-827서울특별시 용산구 서계동 96-16서울특별시 용산구 청파로77가길 9, 지하1층 비01호 (서계동)4303주식회사 씨티컴퍼니2023-08-08 15:53:57I2022-12-07 23:00:00.0건물위생관리업197111.922283449895.108414<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28430200003020000-206-2024-000012024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 711 300247.99140-735서울특별시 용산구 한강로2가 2-37 용산토투밸리서울특별시 용산구 새창로 217, 용산토투밸리 11층 1105호 (한강로2가)4376(사)한국장애인녹색재단 녹색클린2024-03-12 15:50:18I2023-12-02 23:04:00.0건물위생관리업197083.100438447552.774478<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28530200003020000-206-2024-000022024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60140-846서울특별시 용산구 원효로1가 28-20서울특별시 용산구 원효로 229-2, 1층 (원효로1가)4316합동크린2024-04-25 15:21:37I2023-12-03 22:07:00.0건물위생관리업197012.370864448499.653262<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>