Overview

Dataset statistics

Number of variables47
Number of observations187
Missing cells2276
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory73.9 KiB
Average record size in memory404.7 B

Variable types

Categorical20
Text7
DateTime3
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-19953/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신일자 is highly imbalanced (71.2%)Imbalance
발한실여부 is highly imbalanced (59.6%)Imbalance
여성종사자수 is highly imbalanced (77.0%)Imbalance
남성종사자수 is highly imbalanced (77.0%)Imbalance
다중이용업소여부 is highly imbalanced (94.9%)Imbalance
인허가취소일자 has 187 (100.0%) missing valuesMissing
폐업일자 has 38 (20.3%) missing valuesMissing
휴업시작일자 has 187 (100.0%) missing valuesMissing
휴업종료일자 has 187 (100.0%) missing valuesMissing
재개업일자 has 187 (100.0%) missing valuesMissing
전화번호 has 10 (5.3%) missing valuesMissing
도로명주소 has 121 (64.7%) missing valuesMissing
도로명우편번호 has 126 (67.4%) missing valuesMissing
좌표정보(X) has 86 (46.0%) missing valuesMissing
좌표정보(Y) has 86 (46.0%) missing valuesMissing
건물지상층수 has 61 (32.6%) missing valuesMissing
사용시작지상층 has 83 (44.4%) missing valuesMissing
사용끝지상층 has 119 (63.6%) missing valuesMissing
사용끝지하층 has 127 (67.9%) missing valuesMissing
욕실수 has 84 (44.9%) missing valuesMissing
발한실여부 has 13 (7.0%) missing valuesMissing
조건부허가신고사유 has 187 (100.0%) missing valuesMissing
조건부허가시작일자 has 187 (100.0%) missing valuesMissing
조건부허가종료일자 has 187 (100.0%) missing valuesMissing
다중이용업소여부 has 13 (7.0%) 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 78 (41.7%) zerosZeros
사용시작지상층 has 64 (34.2%) zerosZeros
사용끝지상층 has 19 (10.2%) zerosZeros
사용끝지하층 has 17 (9.1%) zerosZeros
욕실수 has 50 (26.7%) zerosZeros

Reproduction

Analysis started2024-04-29 20:03:41.823182
Analysis finished2024-04-29 20:03:42.743253
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3010000
187 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 187
100.0%

Length

2024-04-30T05:03:42.813660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:42.904380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 187
100.0%

관리번호
Text

UNIQUE 

Distinct187
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:03:43.065696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4114
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

Unique187 ?
Unique (%)100.0%

Sample

1st row3010000-202-1954-00245
2nd row3010000-202-1960-00242
3rd row3010000-202-1960-00283
4th row3010000-202-1961-00346
5th row3010000-202-1962-00247
ValueCountFrequency (%)
3010000-202-1954-00245 1
 
0.5%
3010000-202-2002-00010 1
 
0.5%
3010000-202-2003-00012 1
 
0.5%
3010000-202-2002-00001 1
 
0.5%
3010000-202-2002-00002 1
 
0.5%
3010000-202-2002-00004 1
 
0.5%
3010000-202-2002-00005 1
 
0.5%
3010000-202-2002-00006 1
 
0.5%
3010000-202-2002-00007 1
 
0.5%
3010000-202-2002-00008 1
 
0.5%
Other values (177) 177
94.7%
2024-04-30T05:03:43.361318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1802
43.8%
2 576
 
14.0%
- 561
 
13.6%
1 390
 
9.5%
3 307
 
7.5%
9 188
 
4.6%
8 82
 
2.0%
7 61
 
1.5%
4 57
 
1.4%
6 49
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3553
86.4%
Dash Punctuation 561
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1802
50.7%
2 576
 
16.2%
1 390
 
11.0%
3 307
 
8.6%
9 188
 
5.3%
8 82
 
2.3%
7 61
 
1.7%
4 57
 
1.6%
6 49
 
1.4%
5 41
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 561
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1802
43.8%
2 576
 
14.0%
- 561
 
13.6%
1 390
 
9.5%
3 307
 
7.5%
9 188
 
4.6%
8 82
 
2.0%
7 61
 
1.5%
4 57
 
1.4%
6 49
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1802
43.8%
2 576
 
14.0%
- 561
 
13.6%
1 390
 
9.5%
3 307
 
7.5%
9 188
 
4.6%
8 82
 
2.0%
7 61
 
1.5%
4 57
 
1.4%
6 49
 
1.2%
Distinct166
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1954-02-05 00:00:00
Maximum2023-11-29 00:00:00
2024-04-30T05:03:43.499800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:03:43.630543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
149 
1
38 

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 (%)
3 149
79.7%
1 38
 
20.3%

Length

2024-04-30T05:03:43.729557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:43.816042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 149
79.7%
1 38
 
20.3%

영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
149 
영업/정상
38 

Length

Max length5
Median length2
Mean length2.6096257
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 149
79.7%
영업/정상 38
 
20.3%

Length

2024-04-30T05:03:43.928322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:44.022603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
79.7%
영업/정상 38
 
20.3%
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2
149 
1
38 

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 (%)
2 149
79.7%
1 38
 
20.3%

Length

2024-04-30T05:03:44.122377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:44.231484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 149
79.7%
1 38
 
20.3%
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
149 
영업
38 

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 149
79.7%
영업 38
 
20.3%

Length

2024-04-30T05:03:44.358955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:44.461960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
79.7%
영업 38
 
20.3%

폐업일자
Date

MISSING 

Distinct124
Distinct (%)83.2%
Missing38
Missing (%)20.3%
Memory size1.6 KiB
Minimum1993-05-03 00:00:00
Maximum2023-05-12 00:00:00
2024-04-30T05:03:44.574470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:03:44.690106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB

전화번호
Text

MISSING 

Distinct171
Distinct (%)96.6%
Missing10
Missing (%)5.3%
Memory size1.6 KiB
2024-04-30T05:03:44.900754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8022599
Min length2

Characters and Unicode

Total characters1735
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

Unique167 ?
Unique (%)94.4%

Sample

1st row0222661393
2nd row02 7556700
3rd row02 7559888
4th row0222386506
5th row0207557811
ValueCountFrequency (%)
02 74
28.4%
00000 4
 
1.5%
752 2
 
0.8%
777 2
 
0.8%
3188011 2
 
0.8%
3173306 2
 
0.8%
22685561 2
 
0.8%
22663186 2
 
0.8%
3123244 1
 
0.4%
7506 1
 
0.4%
Other values (169) 169
64.8%
2024-04-30T05:03:45.232967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 412
23.7%
0 305
17.6%
7 170
9.8%
3 159
 
9.2%
115
 
6.6%
5 112
 
6.5%
6 111
 
6.4%
8 110
 
6.3%
1 103
 
5.9%
4 72
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1620
93.4%
Space Separator 115
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 412
25.4%
0 305
18.8%
7 170
10.5%
3 159
 
9.8%
5 112
 
6.9%
6 111
 
6.9%
8 110
 
6.8%
1 103
 
6.4%
4 72
 
4.4%
9 66
 
4.1%
Space Separator
ValueCountFrequency (%)
115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1735
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 412
23.7%
0 305
17.6%
7 170
9.8%
3 159
 
9.2%
115
 
6.6%
5 112
 
6.5%
6 111
 
6.4%
8 110
 
6.3%
1 103
 
5.9%
4 72
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1735
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 412
23.7%
0 305
17.6%
7 170
9.8%
3 159
 
9.2%
115
 
6.6%
5 112
 
6.5%
6 111
 
6.4%
8 110
 
6.3%
1 103
 
5.9%
4 72
 
4.1%
Distinct128
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:03:45.501225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.2299465
Min length3

Characters and Unicode

Total characters978
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

Unique123 ?
Unique (%)65.8%

Sample

1st row.00
2nd row.00
3rd row.00
4th row.00
5th row752.91
ValueCountFrequency (%)
00 56
29.9%
190.48 2
 
1.1%
738.02 2
 
1.1%
265.10 2
 
1.1%
363.00 2
 
1.1%
521.00 1
 
0.5%
246.55 1
 
0.5%
225.97 1
 
0.5%
182.34 1
 
0.5%
660.49 1
 
0.5%
Other values (118) 118
63.1%
2024-04-30T05:03:45.869764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 232
23.7%
. 187
19.1%
2 70
 
7.2%
4 69
 
7.1%
1 65
 
6.6%
6 62
 
6.3%
3 61
 
6.2%
7 57
 
5.8%
8 56
 
5.7%
5 55
 
5.6%
Other values (2) 64
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 776
79.3%
Other Punctuation 202
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 232
29.9%
2 70
 
9.0%
4 69
 
8.9%
1 65
 
8.4%
6 62
 
8.0%
3 61
 
7.9%
7 57
 
7.3%
8 56
 
7.2%
5 55
 
7.1%
9 49
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 187
92.6%
, 15
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Common 978
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 232
23.7%
. 187
19.1%
2 70
 
7.2%
4 69
 
7.1%
1 65
 
6.6%
6 62
 
6.3%
3 61
 
6.2%
7 57
 
5.8%
8 56
 
5.7%
5 55
 
5.6%
Other values (2) 64
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 232
23.7%
. 187
19.1%
2 70
 
7.2%
4 69
 
7.1%
1 65
 
6.6%
6 62
 
6.3%
3 61
 
6.2%
7 57
 
5.8%
8 56
 
5.7%
5 55
 
5.6%
Other values (2) 64
 
6.5%
Distinct91
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:03:46.111230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0534759
Min length6

Characters and Unicode

Total characters1132
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

Unique55 ?
Unique (%)29.4%

Sample

1st row100014
2nd row100051
3rd row100080
4th row100450
5th row100022
ValueCountFrequency (%)
100450 23
 
12.3%
100440 7
 
3.7%
100101 7
 
3.7%
100400 7
 
3.7%
100042 5
 
2.7%
100860 5
 
2.7%
100861 5
 
2.7%
100330 4
 
2.1%
100195 4
 
2.1%
100012 4
 
2.1%
Other values (81) 116
62.0%
2024-04-30T05:03:46.453598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 523
46.2%
1 263
23.2%
8 69
 
6.1%
4 66
 
5.8%
2 48
 
4.2%
5 47
 
4.2%
3 34
 
3.0%
6 29
 
2.6%
9 27
 
2.4%
7 16
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1122
99.1%
Dash Punctuation 10
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 523
46.6%
1 263
23.4%
8 69
 
6.1%
4 66
 
5.9%
2 48
 
4.3%
5 47
 
4.2%
3 34
 
3.0%
6 29
 
2.6%
9 27
 
2.4%
7 16
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1132
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 523
46.2%
1 263
23.2%
8 69
 
6.1%
4 66
 
5.8%
2 48
 
4.2%
5 47
 
4.2%
3 34
 
3.0%
6 29
 
2.6%
9 27
 
2.4%
7 16
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 523
46.2%
1 263
23.2%
8 69
 
6.1%
4 66
 
5.8%
2 48
 
4.2%
5 47
 
4.2%
3 34
 
3.0%
6 29
 
2.6%
9 27
 
2.4%
7 16
 
1.4%
Distinct173
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:03:46.687726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length23.754011
Min length15

Characters and Unicode

Total characters4442
Distinct characters150
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)85.0%

Sample

1st row서울특별시 중구 충무로4가 154-1번지
2nd row서울특별시 중구 회현동1가 196-4번지
3rd row서울특별시 중구 북창동 95-0번지
4th row서울특별시 중구 신당동 294-45번지
5th row서울특별시 중구 명동2가 4-2번지
ValueCountFrequency (%)
서울특별시 187
22.3%
중구 187
22.3%
신당동 38
 
4.5%
충무로2가 14
 
1.7%
태평로1가 9
 
1.1%
지하1층 9
 
1.1%
황학동 8
 
1.0%
남대문로5가 8
 
1.0%
쌍림동 7
 
0.8%
명동2가 6
 
0.7%
Other values (254) 365
43.6%
2024-04-30T05:03:47.018172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
825
18.6%
215
 
4.8%
1 205
 
4.6%
193
 
4.3%
189
 
4.3%
188
 
4.2%
187
 
4.2%
187
 
4.2%
187
 
4.2%
187
 
4.2%
Other values (140) 1879
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2571
57.9%
Decimal Number 853
 
19.2%
Space Separator 825
 
18.6%
Dash Punctuation 159
 
3.6%
Uppercase Letter 11
 
0.2%
Other Punctuation 9
 
0.2%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
215
 
8.4%
193
 
7.5%
189
 
7.4%
188
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
166
 
6.5%
128
 
5.0%
Other values (114) 744
28.9%
Decimal Number
ValueCountFrequency (%)
1 205
24.0%
2 170
19.9%
3 98
11.5%
0 73
 
8.6%
4 62
 
7.3%
5 61
 
7.2%
9 50
 
5.9%
7 50
 
5.9%
6 47
 
5.5%
8 37
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
J 2
 
18.2%
D 2
 
18.2%
T 1
 
9.1%
L 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
w 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
. 1
 
11.1%
/ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2571
57.9%
Common 1856
41.8%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
215
 
8.4%
193
 
7.5%
189
 
7.4%
188
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
166
 
6.5%
128
 
5.0%
Other values (114) 744
28.9%
Common
ValueCountFrequency (%)
825
44.5%
1 205
 
11.0%
2 170
 
9.2%
- 159
 
8.6%
3 98
 
5.3%
0 73
 
3.9%
4 62
 
3.3%
5 61
 
3.3%
9 50
 
2.7%
7 50
 
2.7%
Other values (7) 103
 
5.5%
Latin
ValueCountFrequency (%)
B 5
33.3%
J 2
 
13.3%
D 2
 
13.3%
r 1
 
6.7%
e 1
 
6.7%
w 1
 
6.7%
o 1
 
6.7%
T 1
 
6.7%
L 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2571
57.9%
ASCII 1871
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
825
44.1%
1 205
 
11.0%
2 170
 
9.1%
- 159
 
8.5%
3 98
 
5.2%
0 73
 
3.9%
4 62
 
3.3%
5 61
 
3.3%
9 50
 
2.7%
7 50
 
2.7%
Other values (16) 118
 
6.3%
Hangul
ValueCountFrequency (%)
215
 
8.4%
193
 
7.5%
189
 
7.4%
188
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
187
 
7.3%
166
 
6.5%
128
 
5.0%
Other values (114) 744
28.9%

도로명주소
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing121
Missing (%)64.7%
Memory size1.6 KiB
2024-04-30T05:03:47.266819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length38
Mean length30.212121
Min length20

Characters and Unicode

Total characters1994
Distinct characters145
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st row서울특별시 중구 충무로5길 3 (초동)
2nd row서울특별시 중구 퇴계로88길 55 (신당동)
3rd row서울특별시 중구 만리재로31길 5 (만리동2가)
4th row서울특별시 중구 퇴계로20길 2 (남산동2가)
5th row서울특별시 중구 퇴계로87길 30 (황학동)
ValueCountFrequency (%)
서울특별시 66
 
17.1%
중구 66
 
17.1%
지하1층 8
 
2.1%
신당동 7
 
1.8%
2층 5
 
1.3%
태평로1가 5
 
1.3%
퇴계로 5
 
1.3%
27 5
 
1.3%
충무로2가 5
 
1.3%
세종대로 5
 
1.3%
Other values (165) 208
54.0%
2024-04-30T05:03:47.634759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319
 
16.0%
83
 
4.2%
2 74
 
3.7%
1 73
 
3.7%
) 69
 
3.5%
( 69
 
3.5%
69
 
3.5%
69
 
3.5%
67
 
3.4%
67
 
3.4%
Other values (135) 1035
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1160
58.2%
Space Separator 319
 
16.0%
Decimal Number 311
 
15.6%
Close Punctuation 69
 
3.5%
Open Punctuation 69
 
3.5%
Other Punctuation 47
 
2.4%
Dash Punctuation 7
 
0.4%
Uppercase Letter 7
 
0.4%
Lowercase Letter 4
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
83
 
7.2%
69
 
5.9%
69
 
5.9%
67
 
5.8%
67
 
5.8%
67
 
5.8%
66
 
5.7%
66
 
5.7%
54
 
4.7%
45
 
3.9%
Other values (109) 507
43.7%
Decimal Number
ValueCountFrequency (%)
2 74
23.8%
1 73
23.5%
3 34
10.9%
5 24
 
7.7%
0 23
 
7.4%
8 23
 
7.4%
6 23
 
7.4%
4 16
 
5.1%
7 11
 
3.5%
9 10
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
57.1%
L 1
 
14.3%
T 1
 
14.3%
D 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
w 1
25.0%
e 1
25.0%
r 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 45
95.7%
. 1
 
2.1%
/ 1
 
2.1%
Space Separator
ValueCountFrequency (%)
319
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1160
58.2%
Common 823
41.3%
Latin 11
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
83
 
7.2%
69
 
5.9%
69
 
5.9%
67
 
5.8%
67
 
5.8%
67
 
5.8%
66
 
5.7%
66
 
5.7%
54
 
4.7%
45
 
3.9%
Other values (109) 507
43.7%
Common
ValueCountFrequency (%)
319
38.8%
2 74
 
9.0%
1 73
 
8.9%
) 69
 
8.4%
( 69
 
8.4%
, 45
 
5.5%
3 34
 
4.1%
5 24
 
2.9%
0 23
 
2.8%
8 23
 
2.8%
Other values (8) 70
 
8.5%
Latin
ValueCountFrequency (%)
B 4
36.4%
L 1
 
9.1%
T 1
 
9.1%
o 1
 
9.1%
w 1
 
9.1%
e 1
 
9.1%
r 1
 
9.1%
D 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1160
58.2%
ASCII 834
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319
38.2%
2 74
 
8.9%
1 73
 
8.8%
) 69
 
8.3%
( 69
 
8.3%
, 45
 
5.4%
3 34
 
4.1%
5 24
 
2.9%
0 23
 
2.8%
8 23
 
2.8%
Other values (16) 81
 
9.7%
Hangul
ValueCountFrequency (%)
83
 
7.2%
69
 
5.9%
69
 
5.9%
67
 
5.8%
67
 
5.8%
67
 
5.8%
66
 
5.7%
66
 
5.7%
54
 
4.7%
45
 
3.9%
Other values (109) 507
43.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)68.9%
Missing126
Missing (%)67.4%
Infinite0
Infinite (%)0.0%
Mean4556.7049
Minimum4505
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:47.771431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4505
5-th percentile4516
Q14527
median4546
Q34584
95-th percentile4618
Maximum4637
Range132
Interquartile range (IQR)57

Descriptive statistics

Standard deviation35.684424
Coefficient of variation (CV)0.0078311905
Kurtosis-0.6970367
Mean4556.7049
Median Absolute Deviation (MAD)22
Skewness0.67844189
Sum277959
Variance1273.3781
MonotonicityNot monotonic
2024-04-30T05:03:47.900068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
4537 5
 
2.7%
4526 4
 
2.1%
4605 3
 
1.6%
4520 3
 
1.6%
4536 2
 
1.1%
4519 2
 
1.1%
4527 2
 
1.1%
4550 2
 
1.1%
4546 2
 
1.1%
4549 2
 
1.1%
Other values (32) 34
 
18.2%
(Missing) 126
67.4%
ValueCountFrequency (%)
4505 1
 
0.5%
4507 1
 
0.5%
4511 1
 
0.5%
4516 1
 
0.5%
4519 2
1.1%
4520 3
1.6%
4522 2
1.1%
4526 4
2.1%
4527 2
1.1%
4533 1
 
0.5%
ValueCountFrequency (%)
4637 1
 
0.5%
4631 1
 
0.5%
4627 1
 
0.5%
4618 1
 
0.5%
4615 2
1.1%
4614 1
 
0.5%
4610 1
 
0.5%
4605 3
1.6%
4598 1
 
0.5%
4595 1
 
0.5%
Distinct177
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:03:48.130919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length17
Mean length5.7860963
Min length2

Characters and Unicode

Total characters1082
Distinct characters224
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

Unique167 ?
Unique (%)89.3%

Sample

1st row중앙탕
2nd row회현탕
3rd row북창탕
4th row문화탕
5th row동해탕
ValueCountFrequency (%)
사우나 3
 
1.4%
은천탕 2
 
0.9%
sauna 2
 
0.9%
주식회사 2
 
0.9%
앰배서더 2
 
0.9%
서울 2
 
0.9%
호텔 2
 
0.9%
대왕탕 2
 
0.9%
황금사우나 2
 
0.9%
중앙탕 2
 
0.9%
Other values (187) 194
90.2%
2024-04-30T05:03:48.475530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
7.3%
46
 
4.3%
45
 
4.2%
43
 
4.0%
30
 
2.8%
29
 
2.7%
28
 
2.6%
24
 
2.2%
24
 
2.2%
) 21
 
1.9%
Other values (214) 713
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 971
89.7%
Space Separator 28
 
2.6%
Lowercase Letter 25
 
2.3%
Close Punctuation 21
 
1.9%
Open Punctuation 21
 
1.9%
Uppercase Letter 14
 
1.3%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
79
 
8.1%
46
 
4.7%
45
 
4.6%
43
 
4.4%
30
 
3.1%
29
 
3.0%
24
 
2.5%
24
 
2.5%
21
 
2.2%
21
 
2.2%
Other values (192) 609
62.7%
Lowercase Letter
ValueCountFrequency (%)
a 8
32.0%
n 5
20.0%
e 4
16.0%
u 3
 
12.0%
i 1
 
4.0%
s 1
 
4.0%
h 1
 
4.0%
r 1
 
4.0%
y 1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
T 2
14.3%
A 2
14.3%
L 2
14.3%
C 2
14.3%
P 1
 
7.1%
K 1
 
7.1%
B 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 971
89.7%
Common 72
 
6.7%
Latin 39
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
79
 
8.1%
46
 
4.7%
45
 
4.6%
43
 
4.4%
30
 
3.1%
29
 
3.0%
24
 
2.5%
24
 
2.5%
21
 
2.2%
21
 
2.2%
Other values (192) 609
62.7%
Latin
ValueCountFrequency (%)
a 8
20.5%
n 5
12.8%
e 4
10.3%
S 3
 
7.7%
u 3
 
7.7%
T 2
 
5.1%
A 2
 
5.1%
L 2
 
5.1%
C 2
 
5.1%
i 1
 
2.6%
Other values (7) 7
17.9%
Common
ValueCountFrequency (%)
28
38.9%
) 21
29.2%
( 21
29.2%
1 1
 
1.4%
2 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 971
89.7%
ASCII 111
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
79
 
8.1%
46
 
4.7%
45
 
4.6%
43
 
4.4%
30
 
3.1%
29
 
3.0%
24
 
2.5%
24
 
2.5%
21
 
2.2%
21
 
2.2%
Other values (192) 609
62.7%
ASCII
ValueCountFrequency (%)
28
25.2%
) 21
18.9%
( 21
18.9%
a 8
 
7.2%
n 5
 
4.5%
e 4
 
3.6%
S 3
 
2.7%
u 3
 
2.7%
T 2
 
1.8%
A 2
 
1.8%
Other values (12) 14
12.6%
Distinct122
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1999-03-30 00:00:00
Maximum2023-12-27 16:08:44
2024-04-30T05:03:48.613272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:03:48.912297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
I
162 
U
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 162
86.6%
U 25
 
13.4%

Length

2024-04-30T05:03:49.049140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:49.147010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 162
86.6%
u 25
 
13.4%

데이터갱신일자
Categorical

IMBALANCE 

Distinct30
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2018-08-31 23:59:59.0
157 
2022-12-01 23:09:00.0
 
2
2021-11-24 02:40:00.0
 
1
2019-10-26 02:40:00.0
 
1
2021-06-09 02:40:00.0
 
1
Other values (25)
25 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique28 ?
Unique (%)15.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 157
84.0%
2022-12-01 23:09:00.0 2
 
1.1%
2021-11-24 02:40:00.0 1
 
0.5%
2019-10-26 02:40:00.0 1
 
0.5%
2021-06-09 02:40:00.0 1
 
0.5%
2022-11-01 23:00:00.0 1
 
0.5%
2022-12-01 23:06:00.0 1
 
0.5%
2021-05-13 02:40:00.0 1
 
0.5%
2022-03-24 02:40:00.0 1
 
0.5%
2018-10-19 02:37:47.0 1
 
0.5%
Other values (20) 20
 
10.7%

Length

2024-04-30T05:03:49.234398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 158
42.2%
2018-08-31 157
42.0%
02:40:00.0 12
 
3.2%
2022-12-01 3
 
0.8%
2022-11-01 2
 
0.5%
23:07:00.0 2
 
0.5%
23:09:00.0 2
 
0.5%
2019-12-20 1
 
0.3%
00:23:32.0 1
 
0.3%
22:09:00.0 1
 
0.3%
Other values (35) 35
 
9.4%

업태구분명
Categorical

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
공동탕업
140 
목욕장업 기타
22 
한증막업
19 
공동탕업+찜질시설서비스영업
 
6

Length

Max length14
Median length4
Mean length4.6737968
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 140
74.9%
목욕장업 기타 22
 
11.8%
한증막업 19
 
10.2%
공동탕업+찜질시설서비스영업 6
 
3.2%

Length

2024-04-30T05:03:49.337319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:49.434453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 140
67.0%
목욕장업 22
 
10.5%
기타 22
 
10.5%
한증막업 19
 
9.1%
공동탕업+찜질시설서비스영업 6
 
2.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)83.2%
Missing86
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean199416.63
Minimum196948.93
Maximum201856.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:49.546010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196948.93
5-th percentile197462.2
Q1198259.65
median199261.52
Q3200613.51
95-th percentile201637.86
Maximum201856.23
Range4907.296
Interquartile range (IQR)2353.8567

Descriptive statistics

Standard deviation1343.0507
Coefficient of variation (CV)0.0067348982
Kurtosis-1.1174201
Mean199416.63
Median Absolute Deviation (MAD)1195.6713
Skewness0.14046122
Sum20141079
Variance1803785.1
MonotonicityNot monotonic
2024-04-30T05:03:49.665115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198737.553769773 4
 
2.1%
200613.510297669 3
 
1.6%
200419.832186515 3
 
1.6%
199550.506270874 2
 
1.1%
197986.895692742 2
 
1.1%
200090.428459125 2
 
1.1%
199023.967503662 2
 
1.1%
200750.455125653 2
 
1.1%
197963.789217064 2
 
1.1%
196948.933328771 2
 
1.1%
Other values (74) 77
41.2%
(Missing) 86
46.0%
ValueCountFrequency (%)
196948.933328771 2
1.1%
197156.145532304 1
0.5%
197258.590020479 1
0.5%
197424.712852952 1
0.5%
197462.198757043 1
0.5%
197620.676444642 1
0.5%
197692.601616889 1
0.5%
197762.501510022 1
0.5%
197799.544196134 1
0.5%
197799.810120099 1
0.5%
ValueCountFrequency (%)
201856.229350031 1
0.5%
201853.827140376 1
0.5%
201823.908977364 1
0.5%
201801.667760135 1
0.5%
201681.923662932 1
0.5%
201637.855135326 1
0.5%
201580.145904355 1
0.5%
201442.039019479 1
0.5%
201362.695573425 1
0.5%
201313.243777435 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)83.2%
Missing86
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean451142.03
Minimum449638.82
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:49.783580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449638.82
5-th percentile450093.36
Q1450944.45
median451162.5
Q3451610.95
95-th percentile451817.52
Maximum452076.82
Range2437.9944
Interquartile range (IQR)666.50477

Descriptive statistics

Standard deviation545.18288
Coefficient of variation (CV)0.0012084507
Kurtosis0.78474208
Mean451142.03
Median Absolute Deviation (MAD)334.63622
Skewness-0.93239413
Sum45565345
Variance297224.37
MonotonicityNot monotonic
2024-04-30T05:03:49.890715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451081.894647871 4
 
2.1%
451817.515366883 3
 
1.6%
451197.291107237 3
 
1.6%
451392.219693582 2
 
1.1%
451089.662576161 2
 
1.1%
451647.218394571 2
 
1.1%
451105.474557896 2
 
1.1%
449638.824308081 2
 
1.1%
451793.816975812 2
 
1.1%
450906.177832843 2
 
1.1%
Other values (74) 77
41.2%
(Missing) 86
46.0%
ValueCountFrequency (%)
449638.824308081 2
1.1%
449646.639622415 1
0.5%
449777.515840267 1
0.5%
449809.744684888 1
0.5%
450093.361161044 1
0.5%
450100.127638921 2
1.1%
450154.733137123 1
0.5%
450337.580626313 1
0.5%
450361.506112161 1
0.5%
450497.460903907 1
0.5%
ValueCountFrequency (%)
452076.818664092 1
 
0.5%
451945.75542127 1
 
0.5%
451867.372461174 1
 
0.5%
451817.515366883 3
1.6%
451816.806629958 1
 
0.5%
451793.816975812 2
1.1%
451779.880897566 2
1.1%
451777.955529093 1
 
0.5%
451775.169253151 1
 
0.5%
451745.025547093 1
 
0.5%

위생업태명
Categorical

Distinct5
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
공동탕업
134 
한증막업
18 
목욕장업 기타
16 
<NA>
 
13
공동탕업+찜질시설서비스영업
 
6

Length

Max length14
Median length4
Mean length4.5775401
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 134
71.7%
한증막업 18
 
9.6%
목욕장업 기타 16
 
8.6%
<NA> 13
 
7.0%
공동탕업+찜질시설서비스영업 6
 
3.2%

Length

2024-04-30T05:03:50.009272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:50.104042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 134
66.0%
한증막업 18
 
8.9%
목욕장업 16
 
7.9%
기타 16
 
7.9%
na 13
 
6.4%
공동탕업+찜질시설서비스영업 6
 
3.0%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)15.1%
Missing61
Missing (%)32.6%
Infinite0
Infinite (%)0.0%
Mean2.8095238
Minimum0
Maximum35
Zeros78
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:50.196571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile13.75
Maximum35
Range35
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.4460471
Coefficient of variation (CV)1.9384235
Kurtosis10.56626
Mean2.8095238
Median Absolute Deviation (MAD)0
Skewness2.8596088
Sum354
Variance29.659429
MonotonicityNot monotonic
2024-04-30T05:03:50.299800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 78
41.7%
2 10
 
5.3%
10 6
 
3.2%
3 6
 
3.2%
6 4
 
2.1%
1 3
 
1.6%
5 3
 
1.6%
4 3
 
1.6%
12 2
 
1.1%
13 2
 
1.1%
Other values (9) 9
 
4.8%
(Missing) 61
32.6%
ValueCountFrequency (%)
0 78
41.7%
1 3
 
1.6%
2 10
 
5.3%
3 6
 
3.2%
4 3
 
1.6%
5 3
 
1.6%
6 4
 
2.1%
7 1
 
0.5%
8 1
 
0.5%
10 6
 
3.2%
ValueCountFrequency (%)
35 1
 
0.5%
22 1
 
0.5%
18 1
 
0.5%
17 1
 
0.5%
16 1
 
0.5%
15 1
 
0.5%
14 1
 
0.5%
13 2
 
1.1%
12 2
 
1.1%
10 6
3.2%
Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
84 
<NA>
72 
1
18 
2
10 
3
 
2

Length

Max length4
Median length1
Mean length2.1550802
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 84
44.9%
<NA> 72
38.5%
1 18
 
9.6%
2 10
 
5.3%
3 2
 
1.1%
8 1
 
0.5%

Length

2024-04-30T05:03:50.405956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:50.502231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 84
44.9%
na 72
38.5%
1 18
 
9.6%
2 10
 
5.3%
3 2
 
1.1%
8 1
 
0.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)12.5%
Missing83
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean1.5769231
Minimum0
Maximum16
Zeros64
Zeros (%)34.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:50.605158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.25
95-th percentile11.7
Maximum16
Range16
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation3.4407391
Coefficient of variation (CV)2.1819321
Kurtosis7.798205
Mean1.5769231
Median Absolute Deviation (MAD)0
Skewness2.8927935
Sum164
Variance11.838686
MonotonicityNot monotonic
2024-04-30T05:03:50.694699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 64
34.2%
1 14
 
7.5%
2 10
 
5.3%
3 5
 
2.7%
12 2
 
1.1%
4 2
 
1.1%
14 1
 
0.5%
13 1
 
0.5%
8 1
 
0.5%
15 1
 
0.5%
Other values (3) 3
 
1.6%
(Missing) 83
44.4%
ValueCountFrequency (%)
0 64
34.2%
1 14
 
7.5%
2 10
 
5.3%
3 5
 
2.7%
4 2
 
1.1%
7 1
 
0.5%
8 1
 
0.5%
10 1
 
0.5%
12 2
 
1.1%
13 1
 
0.5%
ValueCountFrequency (%)
16 1
 
0.5%
15 1
 
0.5%
14 1
 
0.5%
13 1
 
0.5%
12 2
 
1.1%
10 1
 
0.5%
8 1
 
0.5%
7 1
 
0.5%
4 2
 
1.1%
3 5
2.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)22.1%
Missing119
Missing (%)63.6%
Infinite0
Infinite (%)0.0%
Mean2.9264706
Minimum0
Maximum17
Zeros19
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:50.794358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile12.65
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.8606943
Coefficient of variation (CV)1.3192322
Kurtosis4.6242629
Mean2.9264706
Median Absolute Deviation (MAD)1.5
Skewness2.191681
Sum199
Variance14.90496
MonotonicityNot monotonic
2024-04-30T05:03:50.891029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 19
 
10.2%
2 14
 
7.5%
3 11
 
5.9%
1 9
 
4.8%
4 4
 
2.1%
5 2
 
1.1%
14 1
 
0.5%
13 1
 
0.5%
8 1
 
0.5%
12 1
 
0.5%
Other values (5) 5
 
2.7%
(Missing) 119
63.6%
ValueCountFrequency (%)
0 19
10.2%
1 9
4.8%
2 14
7.5%
3 11
5.9%
4 4
 
2.1%
5 2
 
1.1%
6 1
 
0.5%
7 1
 
0.5%
8 1
 
0.5%
10 1
 
0.5%
ValueCountFrequency (%)
17 1
0.5%
16 1
0.5%
14 1
0.5%
13 1
0.5%
12 1
0.5%
10 1
0.5%
8 1
0.5%
7 1
0.5%
6 1
0.5%
5 2
1.1%
Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
86 
0
61 
1
30 
2
 
8
4
 
1

Length

Max length4
Median length1
Mean length2.3796791
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 86
46.0%
0 61
32.6%
1 30
 
16.0%
2 8
 
4.3%
4 1
 
0.5%
8 1
 
0.5%

Length

2024-04-30T05:03:51.009219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:51.099359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 86
46.0%
0 61
32.6%
1 30
 
16.0%
2 8
 
4.3%
4 1
 
0.5%
8 1
 
0.5%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)10.0%
Missing127
Missing (%)67.9%
Infinite0
Infinite (%)0.0%
Mean1.1333333
Minimum0
Maximum8
Zeros17
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:51.190700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile2.05
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2414681
Coefficient of variation (CV)1.095413
Kurtosis15.311855
Mean1.1333333
Median Absolute Deviation (MAD)1
Skewness3.0925616
Sum68
Variance1.5412429
MonotonicityNot monotonic
2024-04-30T05:03:51.286088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 27
 
14.4%
0 17
 
9.1%
2 13
 
7.0%
3 1
 
0.5%
4 1
 
0.5%
8 1
 
0.5%
(Missing) 127
67.9%
ValueCountFrequency (%)
0 17
9.1%
1 27
14.4%
2 13
7.0%
3 1
 
0.5%
4 1
 
0.5%
8 1
 
0.5%
ValueCountFrequency (%)
8 1
 
0.5%
4 1
 
0.5%
3 1
 
0.5%
2 13
7.0%
1 27
14.4%
0 17
9.1%

한실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
96 
<NA>
91 

Length

Max length4
Median length1
Mean length2.459893
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 96
51.3%
<NA> 91
48.7%

Length

2024-04-30T05:03:51.396478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:51.483799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
51.3%
na 91
48.7%

양실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
96 
<NA>
91 

Length

Max length4
Median length1
Mean length2.459893
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 96
51.3%
<NA> 91
48.7%

Length

2024-04-30T05:03:51.585938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:51.700501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
51.3%
na 91
48.7%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)11.7%
Missing84
Missing (%)44.9%
Infinite0
Infinite (%)0.0%
Mean2.1359223
Minimum0
Maximum16
Zeros50
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:03:51.776614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile7.9
Maximum16
Range16
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.9139574
Coefficient of variation (CV)1.3642619
Kurtosis4.6748843
Mean2.1359223
Median Absolute Deviation (MAD)1
Skewness1.8581869
Sum220
Variance8.4911479
MonotonicityNot monotonic
2024-04-30T05:03:51.871437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 50
26.7%
2 12
 
6.4%
5 8
 
4.3%
3 8
 
4.3%
4 7
 
3.7%
1 6
 
3.2%
6 5
 
2.7%
8 3
 
1.6%
7 1
 
0.5%
16 1
 
0.5%
Other values (2) 2
 
1.1%
(Missing) 84
44.9%
ValueCountFrequency (%)
0 50
26.7%
1 6
 
3.2%
2 12
 
6.4%
3 8
 
4.3%
4 7
 
3.7%
5 8
 
4.3%
6 5
 
2.7%
7 1
 
0.5%
8 3
 
1.6%
10 1
 
0.5%
ValueCountFrequency (%)
16 1
 
0.5%
11 1
 
0.5%
10 1
 
0.5%
8 3
 
1.6%
7 1
 
0.5%
6 5
2.7%
5 8
4.3%
4 7
3.7%
3 8
4.3%
2 12
6.4%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.1%
Missing13
Missing (%)7.0%
Memory size506.0 B
False
160 
True
 
14
(Missing)
 
13
ValueCountFrequency (%)
False 160
85.6%
True 14
 
7.5%
(Missing) 13
 
7.0%
2024-04-30T05:03:51.980001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
96 
<NA>
91 

Length

Max length4
Median length1
Mean length2.459893
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 96
51.3%
<NA> 91
48.7%

Length

2024-04-30T05:03:52.085335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:52.170386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
51.3%
na 91
48.7%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing187
Missing (%)100.0%
Memory size1.8 KiB
Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
113 
자가
37 
임대
37 

Length

Max length4
Median length4
Mean length3.2085561
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> 113
60.4%
자가 37
 
19.8%
임대 37
 
19.8%

Length

2024-04-30T05:03:52.267668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:52.373985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
60.4%
자가 37
 
19.8%
임대 37
 
19.8%

세탁기수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
137 
0
50 

Length

Max length4
Median length4
Mean length3.197861
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> 137
73.3%
0 50
 
26.7%

Length

2024-04-30T05:03:52.475206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:52.555522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
73.3%
0 50
 
26.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
180 
0
 
7

Length

Max length4
Median length4
Mean length3.8877005
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> 180
96.3%
0 7
 
3.7%

Length

2024-04-30T05:03:52.646291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:52.735854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 180
96.3%
0 7
 
3.7%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
180 
0
 
7

Length

Max length4
Median length4
Mean length3.8877005
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> 180
96.3%
0 7
 
3.7%

Length

2024-04-30T05:03:52.819072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:52.902292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 180
96.3%
0 7
 
3.7%

회수건조수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
139 
0
48 

Length

Max length4
Median length4
Mean length3.2299465
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> 139
74.3%
0 48
 
25.7%

Length

2024-04-30T05:03:53.005869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:53.103475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 139
74.3%
0 48
 
25.7%

침대수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
140 
0
47 

Length

Max length4
Median length4
Mean length3.2459893
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> 140
74.9%
0 47
 
25.1%

Length

2024-04-30T05:03:53.207564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:53.297181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 140
74.9%
0 47
 
25.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.1%
Missing13
Missing (%)7.0%
Memory size506.0 B
False
173 
True
 
1
(Missing)
 
13
ValueCountFrequency (%)
False 173
92.5%
True 1
 
0.5%
(Missing) 13
 
7.0%
2024-04-30T05:03:53.379313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030100003010000-202-1954-0024519540205<NA>3폐업2폐업20010227<NA><NA><NA>0222661393.00100014서울특별시 중구 충무로4가 154-1번지<NA><NA>중앙탕2001-07-05 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130100003010000-202-1960-0024219600411<NA>3폐업2폐업19980212<NA><NA><NA>02 7556700.00100051서울특별시 중구 회현동1가 196-4번지<NA><NA>회현탕2001-10-08 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230100003010000-202-1960-0028319601201<NA>3폐업2폐업20111221<NA><NA><NA>02 7559888.00100080서울특별시 중구 북창동 95-0번지<NA><NA>북창탕2006-11-14 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA>13<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330100003010000-202-1961-0034619611201<NA>3폐업2폐업19990806<NA><NA><NA>0222386506.00100450서울특별시 중구 신당동 294-45번지<NA><NA>문화탕2001-10-08 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430100003010000-202-1962-0024719620221<NA>3폐업2폐업20030226<NA><NA><NA>0207557811752.91100022서울특별시 중구 명동2가 4-2번지<NA><NA>동해탕2003-04-10 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530100003010000-202-1963-0027919630709<NA>3폐업2폐업20000221<NA><NA><NA>02 883585274.54100450서울특별시 중구 신당동 308-5번지<NA><NA>신양2001-10-08 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630100003010000-202-1964-0034419641211<NA>3폐업2폐업20040330<NA><NA><NA>0207536825.00100130서울특별시 중구 순화동 1-98번지<NA><NA>순화2004-04-23 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730100003010000-202-1965-0034119650614<NA>3폐업2폐업20030226<NA><NA><NA>02 2336690.00100450서울특별시 중구 신당동 52-278번지<NA><NA>명진2003-04-10 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830100003010000-202-1968-0033319680619<NA>3폐업2폐업20001016<NA><NA><NA>02 2792882.00100400서울특별시 중구 쌍림동 182-69번지<NA><NA>장충탕2000-10-17 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930100003010000-202-1968-0034219681205<NA>3폐업2폐업20040203<NA><NA><NA>0222346263.00100450서울특별시 중구 신당동 372-31번지<NA><NA>동광탕2004-02-03 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<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
17730100003010000-202-2016-0000120160802<NA>3폐업2폐업20180912<NA><NA><NA>02 749 3322363.00100860서울특별시 중구 충무로2가 11-1번지 지하2층서울특별시 중구 명동8가길 27 (충무로2가, 지하2층)4537이브천지연(남탕)2018-09-12 16:15:49U2018-09-12 23:59:59.0공동탕업+찜질시설서비스영업198737.55377451081.894648공동탕업+찜질시설서비스영업00<NA><NA>22005Y0<NA><NA><NA><NA>00000N
17830100003010000-202-2016-0000220161222<NA>1영업/정상1영업<NA><NA><NA><NA>02 753 9800413.37100210서울특별시 중구 수하동 67번지 미래에셋 센터원빌딩 3층서울특별시 중구 을지로5길 26 (수하동, 미래에셋 센터원빌딩 3층)4539(주)센터원웰니스2016-12-22 17:13:49I2018-08-31 23:59:59.0목욕장업 기타198620.934275451681.958036목욕장업 기타0033<NA><NA>003N0<NA><NA><NA><NA>00000N
17930100003010000-202-2018-0000120181019<NA>1영업/정상1영업<NA><NA><NA><NA><NA>198.00100860서울특별시 중구 충무로2가 11-1 지하2층서울특별시 중구 명동8가길 27, 지하2층 (충무로2가)4537황금사우나 남탕2022-03-16 15:06:43U2022-03-18 02:40:00.0공동탕업198737.55377451081.894648공동탕업0022<NA><NA>001Y0<NA><NA><NA>임대00000Y
18030100003010000-202-2018-0000220181228<NA>1영업/정상1영업<NA><NA><NA><NA>02 777 82001,003.80100768서울특별시 중구 태평로1가 84번지 파이낸스빌딩 지하2층서울특별시 중구 세종대로 136, 파이낸스빌딩 지하2층 (태평로1가)4520시그마 스포츠클럽2020-05-27 16:20:51U2020-05-29 02:40:00.0공동탕업197963.789217451793.816976공동탕업00<NA><NA>22005Y0<NA><NA><NA><NA>00000N
18130100003010000-202-2020-0000120200429<NA>1영업/정상1영업<NA><NA><NA><NA><NA>497.56100800서울특별시 중구 남대문로5가 36-1번지서울특별시 중구 세종대로2나길 23, 지하1층 (남대문로5가)4527남문 대종탕2020-04-29 15:04:30I2020-05-01 00:23:32.0목욕장업 기타197692.601617450709.793991목욕장업 기타00<NA><NA>11006N0<NA><NA><NA><NA>00000N
18230100003010000-202-2020-0000220200513<NA>1영업/정상1영업<NA><NA><NA><NA>026250820040.00100192서울특별시 중구 을지로2가 205번지 신한L Tower서울특별시 중구 삼일대로 358, 신한L Tower 지하1층 (을지로2가)4542(주)스포짐을지2020-05-13 16:42:14I2020-05-15 00:23:19.0목욕장업 기타198877.134151451578.377237목욕장업 기타00<NA><NA>11001N0<NA><NA><NA>임대00000N
18330100003010000-202-2020-0000320201008<NA>1영업/정상1영업<NA><NA><NA><NA><NA>450.00100101서울특별시 중구 태평로1가 61-1 코리아나호텔서울특별시 중구 세종대로 135, 코리아나호텔 4층 (태평로1가)4519(주)피트비엠2020-10-08 11:42:57I2020-10-10 00:23:11.0목욕장업 기타197867.156641451779.880898목욕장업 기타0044<NA><NA>002N0<NA><NA><NA><NA>00000N
18430100003010000-202-2021-000012021-09-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>72.00100-170서울특별시 중구 무교동 19서울특별시 중구 무교로 16, 9,10층 (무교동)4522피트니스온 서울시청점2023-03-13 14:37:20U2022-12-02 23:05:00.0목욕장업 기타198123.904576451671.110699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18530100003010000-202-2023-000012023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>104.34100-824서울특별시 중구 신당동 291-48 동산빌딩서울특별시 중구 다산로36길 11, 동산빌딩 2층 (신당동)4585세신샵 수련2023-10-20 14:29:05I2022-10-30 22:02:00.0목욕장업 기타201362.695573451177.222462<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18630100003010000-202-2023-000022023-11-29<NA>1영업/정상1영업<NA><NA><NA><NA>0269563518311.72100-890서울특별시 중구 신당동 304-733서울특별시 중구 청구로8길 22, 1층,2층 (신당동)4610어르신헬스케어센터2023-11-29 17:07:43I2022-11-02 00:01:00.0공동탕업201144.248792451013.075207<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>