Overview

Dataset statistics

Number of variables47
Number of observations90
Missing cells819
Missing cells (%)19.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.7 KiB
Average record size in memory406.5 B

Variable types

Categorical23
Text7
DateTime3
Unsupported7
Numeric5
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-19961/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (58.8%)Imbalance
위생업태명 is highly imbalanced (55.2%)Imbalance
발한실여부 is highly imbalanced (58.6%)Imbalance
여성종사자수 is highly imbalanced (84.6%)Imbalance
남성종사자수 is highly imbalanced (84.6%)Imbalance
인허가취소일자 has 90 (100.0%) missing valuesMissing
폐업일자 has 18 (20.0%) missing valuesMissing
휴업시작일자 has 90 (100.0%) missing valuesMissing
휴업종료일자 has 90 (100.0%) missing valuesMissing
재개업일자 has 90 (100.0%) missing valuesMissing
전화번호 has 2 (2.2%) missing valuesMissing
도로명주소 has 64 (71.1%) missing valuesMissing
도로명우편번호 has 64 (71.1%) missing valuesMissing
좌표정보(X) has 4 (4.4%) missing valuesMissing
좌표정보(Y) has 4 (4.4%) missing valuesMissing
건물지상층수 has 21 (23.3%) missing valuesMissing
발한실여부 has 6 (6.7%) missing valuesMissing
조건부허가신고사유 has 90 (100.0%) missing valuesMissing
조건부허가시작일자 has 90 (100.0%) missing valuesMissing
조건부허가종료일자 has 90 (100.0%) missing valuesMissing
다중이용업소여부 has 6 (6.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 39 (43.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:50:55.898731
Analysis finished2024-05-11 06:50:56.853442
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
3090000
90 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 90
100.0%

Length

2024-05-11T15:50:56.956907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:57.120273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 90
100.0%

관리번호
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-05-11T15:50:57.402811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1980
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

Unique90 ?
Unique (%)100.0%

Sample

1st row3090000-202-1968-00096
2nd row3090000-202-1971-00061
3rd row3090000-202-1972-00068
4th row3090000-202-1972-00097
5th row3090000-202-1973-00055
ValueCountFrequency (%)
3090000-202-1968-00096 1
 
1.1%
3090000-202-1999-00114 1
 
1.1%
3090000-202-1998-00109 1
 
1.1%
3090000-202-1998-00108 1
 
1.1%
3090000-202-1998-00107 1
 
1.1%
3090000-202-1998-00106 1
 
1.1%
3090000-202-1997-00106 1
 
1.1%
3090000-202-1997-00105 1
 
1.1%
3090000-202-1997-00104 1
 
1.1%
3090000-202-1997-00103 1
 
1.1%
Other values (80) 80
88.9%
2024-05-11T15:50:57.966879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 880
44.4%
- 270
 
13.6%
2 223
 
11.3%
9 214
 
10.8%
1 121
 
6.1%
3 118
 
6.0%
8 52
 
2.6%
7 33
 
1.7%
6 27
 
1.4%
5 22
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1710
86.4%
Dash Punctuation 270
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 880
51.5%
2 223
 
13.0%
9 214
 
12.5%
1 121
 
7.1%
3 118
 
6.9%
8 52
 
3.0%
7 33
 
1.9%
6 27
 
1.6%
5 22
 
1.3%
4 20
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1980
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 880
44.4%
- 270
 
13.6%
2 223
 
11.3%
9 214
 
10.8%
1 121
 
6.1%
3 118
 
6.0%
8 52
 
2.6%
7 33
 
1.7%
6 27
 
1.4%
5 22
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 880
44.4%
- 270
 
13.6%
2 223
 
11.3%
9 214
 
10.8%
1 121
 
6.1%
3 118
 
6.0%
8 52
 
2.6%
7 33
 
1.7%
6 27
 
1.4%
5 22
 
1.1%

인허가일자
Date

Distinct87
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum1968-12-06 00:00:00
Maximum2008-02-26 00:00:00
2024-05-11T15:50:58.260758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:58.524359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
3
72 
1
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 72
80.0%
1 18
 
20.0%

Length

2024-05-11T15:50:58.756925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:58.941298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 72
80.0%
1 18
 
20.0%

영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
폐업
72 
영업/정상
18 

Length

Max length5
Median length2
Mean length2.6
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 72
80.0%
영업/정상 18
 
20.0%

Length

2024-05-11T15:50:59.141971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:59.407937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 72
80.0%
영업/정상 18
 
20.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
2
72 
1
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 72
80.0%
1 18
 
20.0%

Length

2024-05-11T15:50:59.577058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:59.744541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 72
80.0%
1 18
 
20.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
폐업
72 
영업
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 72
80.0%
영업 18
 
20.0%

Length

2024-05-11T15:50:59.944531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:00.510370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 72
80.0%
영업 18
 
20.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)90.3%
Missing18
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean20045505
Minimum19931230
Maximum20230127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-05-11T15:51:00.764194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19931230
5-th percentile19965957
Q120001027
median20030857
Q320070393
95-th percentile20195200
Maximum20230127
Range298897
Interquartile range (IQR)69366

Descriptive statistics

Standard deviation66409.526
Coefficient of variation (CV)0.0033129384
Kurtosis1.0433522
Mean20045505
Median Absolute Deviation (MAD)30252
Skewness1.1022313
Sum1.4432764 × 109
Variance4.4102251 × 109
MonotonicityNot monotonic
2024-05-11T15:51:01.017192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20001027 3
 
3.3%
20021031 3
 
3.3%
20030226 3
 
3.3%
19980623 2
 
2.2%
20211230 1
 
1.1%
20070906 1
 
1.1%
20110209 1
 
1.1%
20020508 1
 
1.1%
20230127 1
 
1.1%
20030813 1
 
1.1%
Other values (55) 55
61.1%
(Missing) 18
 
20.0%
ValueCountFrequency (%)
19931230 1
1.1%
19940331 1
1.1%
19960223 1
1.1%
19960514 1
1.1%
19970410 1
1.1%
19970728 1
1.1%
19970825 1
1.1%
19970911 1
1.1%
19971013 1
1.1%
19980623 2
2.2%
ValueCountFrequency (%)
20230127 1
1.1%
20211230 1
1.1%
20210511 1
1.1%
20200921 1
1.1%
20190520 1
1.1%
20181030 1
1.1%
20180404 1
1.1%
20170202 1
1.1%
20110905 1
1.1%
20110209 1
1.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

전화번호
Text

MISSING 

Distinct84
Distinct (%)95.5%
Missing2
Missing (%)2.2%
Memory size852.0 B
2024-05-11T15:51:01.437804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.2727273
Min length2

Characters and Unicode

Total characters816
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

Unique81 ?
Unique (%)92.0%

Sample

1st row02 9920979
2nd row0209918893
3rd row02
4th row0209923314
5th row02 9967289
ValueCountFrequency (%)
02 40
30.1%
9559234 2
 
1.5%
9566973 2
 
1.5%
9569944 2
 
1.5%
9038443 2
 
1.5%
9912135 2
 
1.5%
9920979 1
 
0.8%
9554847 1
 
0.8%
6699 1
 
0.8%
992 1
 
0.8%
Other values (79) 79
59.4%
2024-05-11T15:51:02.102004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 171
21.0%
9 156
19.1%
2 111
13.6%
3 61
 
7.5%
4 60
 
7.4%
49
 
6.0%
6 44
 
5.4%
5 43
 
5.3%
8 42
 
5.1%
1 41
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 767
94.0%
Space Separator 49
 
6.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171
22.3%
9 156
20.3%
2 111
14.5%
3 61
 
8.0%
4 60
 
7.8%
6 44
 
5.7%
5 43
 
5.6%
8 42
 
5.5%
1 41
 
5.3%
7 38
 
5.0%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 816
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171
21.0%
9 156
19.1%
2 111
13.6%
3 61
 
7.5%
4 60
 
7.4%
49
 
6.0%
6 44
 
5.4%
5 43
 
5.3%
8 42
 
5.1%
1 41
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171
21.0%
9 156
19.1%
2 111
13.6%
3 61
 
7.5%
4 60
 
7.4%
49
 
6.0%
6 44
 
5.4%
5 43
 
5.3%
8 42
 
5.1%
1 41
 
5.0%

소재지면적
Text

Distinct85
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-05-11T15:51:02.652665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0444444
Min length3

Characters and Unicode

Total characters544
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

Unique81 ?
Unique (%)90.0%

Sample

1st row121.85
2nd row154.88
3rd row144.90
4th row163.20
5th row214.35
ValueCountFrequency (%)
00 3
 
3.3%
390.00 2
 
2.2%
305.56 2
 
2.2%
575.90 2
 
2.2%
515.08 1
 
1.1%
749.39 1
 
1.1%
546.20 1
 
1.1%
300.23 1
 
1.1%
214.30 1
 
1.1%
580.01 1
 
1.1%
Other values (75) 75
83.3%
2024-05-11T15:51:03.338560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 90
16.5%
0 83
15.3%
2 54
9.9%
3 45
8.3%
4 45
8.3%
8 45
8.3%
5 40
7.4%
1 39
7.2%
6 37
6.8%
7 32
 
5.9%
Other values (2) 34
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 448
82.4%
Other Punctuation 96
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83
18.5%
2 54
12.1%
3 45
10.0%
4 45
10.0%
8 45
10.0%
5 40
8.9%
1 39
8.7%
6 37
8.3%
7 32
 
7.1%
9 28
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 90
93.8%
, 6
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 90
16.5%
0 83
15.3%
2 54
9.9%
3 45
8.3%
4 45
8.3%
8 45
8.3%
5 40
7.4%
1 39
7.2%
6 37
6.8%
7 32
 
5.9%
Other values (2) 34
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 90
16.5%
0 83
15.3%
2 54
9.9%
3 45
8.3%
4 45
8.3%
8 45
8.3%
5 40
7.4%
1 39
7.2%
6 37
6.8%
7 32
 
5.9%
Other values (2) 34
 
6.2%

소재지우편번호
Text

Distinct57
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-05-11T15:51:03.765390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0444444
Min length6

Characters and Unicode

Total characters544
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

Unique34 ?
Unique (%)37.8%

Sample

1st row132822
2nd row132866
3rd row132918
4th row132821
5th row132863
ValueCountFrequency (%)
132864 4
 
4.4%
132839 4
 
4.4%
132801 3
 
3.3%
132890 3
 
3.3%
132918 3
 
3.3%
132861 3
 
3.3%
132922 3
 
3.3%
132920 3
 
3.3%
132827 2
 
2.2%
132848 2
 
2.2%
Other values (47) 60
66.7%
2024-05-11T15:51:04.379900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 116
21.3%
2 112
20.6%
3 105
19.3%
8 77
14.2%
9 42
 
7.7%
0 28
 
5.1%
6 19
 
3.5%
4 17
 
3.1%
7 13
 
2.4%
5 11
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 540
99.3%
Dash Punctuation 4
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 116
21.5%
2 112
20.7%
3 105
19.4%
8 77
14.3%
9 42
 
7.8%
0 28
 
5.2%
6 19
 
3.5%
4 17
 
3.1%
7 13
 
2.4%
5 11
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 116
21.3%
2 112
20.6%
3 105
19.3%
8 77
14.2%
9 42
 
7.7%
0 28
 
5.1%
6 19
 
3.5%
4 17
 
3.1%
7 13
 
2.4%
5 11
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 116
21.3%
2 112
20.6%
3 105
19.3%
8 77
14.2%
9 42
 
7.7%
0 28
 
5.1%
6 19
 
3.5%
4 17
 
3.1%
7 13
 
2.4%
5 11
 
2.0%

지번주소
Text

Distinct80
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-05-11T15:51:04.940035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length23.322222
Min length17

Characters and Unicode

Total characters2099
Distinct characters63
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)81.1%

Sample

1st row서울특별시 도봉구 도봉동 633-13번지
2nd row서울특별시 도봉구 쌍문동 120-8번지
3rd row서울특별시 도봉구 창동 582-24번지
4th row서울특별시 도봉구 도봉동 624-83번지
5th row서울특별시 도봉구 쌍문동 85-6번지
ValueCountFrequency (%)
서울특별시 90
23.1%
도봉구 90
23.1%
창동 28
 
7.2%
쌍문동 26
 
6.7%
방학동 20
 
5.1%
도봉동 16
 
4.1%
지하1층 5
 
1.3%
619-7번지 4
 
1.0%
89-150번지 3
 
0.8%
703-14번지 2
 
0.5%
Other values (97) 106
27.2%
2024-05-11T15:51:05.696887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
383
18.2%
도 106
 
5.1%
봉 106
 
5.1%
동 96
 
4.6%
서 90
 
4.3%
구 90
 
4.3%
울 90
 
4.3%
시 90
 
4.3%
별 90
 
4.3%
특 90
 
4.3%
Other values (53) 868
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1208
57.6%
Decimal Number 415
 
19.8%
Space Separator 383
 
18.2%
Dash Punctuation 83
 
4.0%
Other Punctuation 4
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 106
 
8.8%
봉 106
 
8.8%
동 96
 
7.9%
서 90
 
7.5%
구 90
 
7.5%
울 90
 
7.5%
시 90
 
7.5%
별 90
 
7.5%
특 90
 
7.5%
지 85
 
7.0%
Other values (37) 275
22.8%
Decimal Number
ValueCountFrequency (%)
1 69
16.6%
2 57
13.7%
6 55
13.3%
3 51
12.3%
5 39
9.4%
8 37
8.9%
0 32
7.7%
7 26
 
6.3%
9 26
 
6.3%
4 23
 
5.5%
Space Separator
ValueCountFrequency (%)
383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1208
57.6%
Common 889
42.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 106
 
8.8%
봉 106
 
8.8%
동 96
 
7.9%
서 90
 
7.5%
구 90
 
7.5%
울 90
 
7.5%
시 90
 
7.5%
별 90
 
7.5%
특 90
 
7.5%
지 85
 
7.0%
Other values (37) 275
22.8%
Common
ValueCountFrequency (%)
383
43.1%
- 83
 
9.3%
1 69
 
7.8%
2 57
 
6.4%
6 55
 
6.2%
3 51
 
5.7%
5 39
 
4.4%
8 37
 
4.2%
0 32
 
3.6%
7 26
 
2.9%
Other values (5) 57
 
6.4%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1208
57.6%
ASCII 891
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
383
43.0%
- 83
 
9.3%
1 69
 
7.7%
2 57
 
6.4%
6 55
 
6.2%
3 51
 
5.7%
5 39
 
4.4%
8 37
 
4.2%
0 32
 
3.6%
7 26
 
2.9%
Other values (6) 59
 
6.6%
Hangul
ValueCountFrequency (%)
도 106
 
8.8%
봉 106
 
8.8%
동 96
 
7.9%
서 90
 
7.5%
구 90
 
7.5%
울 90
 
7.5%
시 90
 
7.5%
별 90
 
7.5%
특 90
 
7.5%
지 85
 
7.0%
Other values (37) 275
22.8%

도로명주소
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing64
Missing (%)71.1%
Memory size852.0 B
2024-05-11T15:51:06.082559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length39
Mean length28.153846
Min length22

Characters and Unicode

Total characters732
Distinct characters65
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row서울특별시 도봉구 도봉로113가길 5 (쌍문동)
2nd row서울특별시 도봉구 우이천로12길 41 (창동)
3rd row서울특별시 도봉구 우이천로34길 44 (쌍문동)
4th row서울특별시 도봉구 덕릉로59길 20 (창동)
5th row서울특별시 도봉구 도봉로169나길 14 (도봉동)
ValueCountFrequency (%)
서울특별시 26
18.1%
도봉구 26
18.1%
창동 8
 
5.6%
쌍문동 6
 
4.2%
시루봉로 4
 
2.8%
도봉동 4
 
2.8%
방학동 4
 
2.8%
상가동 3
 
2.1%
지하1층 2
 
1.4%
도당로 2
 
1.4%
Other values (58) 59
41.0%
2024-05-11T15:51:06.717983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
16.1%
봉 40
 
5.5%
도 39
 
5.3%
동 31
 
4.2%
시 31
 
4.2%
) 27
 
3.7%
( 27
 
3.7%
서 26
 
3.6%
특 26
 
3.6%
별 26
 
3.6%
Other values (55) 341
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 438
59.8%
Space Separator 118
 
16.1%
Decimal Number 103
 
14.1%
Close Punctuation 27
 
3.7%
Open Punctuation 27
 
3.7%
Other Punctuation 14
 
1.9%
Dash Punctuation 3
 
0.4%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 40
 
9.1%
도 39
 
8.9%
동 31
 
7.1%
시 31
 
7.1%
서 26
 
5.9%
특 26
 
5.9%
별 26
 
5.9%
구 26
 
5.9%
울 26
 
5.9%
로 25
 
5.7%
Other values (39) 142
32.4%
Decimal Number
ValueCountFrequency (%)
1 22
21.4%
4 12
11.7%
2 11
10.7%
6 10
9.7%
3 10
9.7%
5 9
8.7%
7 8
 
7.8%
8 8
 
7.8%
0 7
 
6.8%
9 6
 
5.8%
Space Separator
ValueCountFrequency (%)
118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 438
59.8%
Common 292
39.9%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 40
 
9.1%
도 39
 
8.9%
동 31
 
7.1%
시 31
 
7.1%
서 26
 
5.9%
특 26
 
5.9%
별 26
 
5.9%
구 26
 
5.9%
울 26
 
5.9%
로 25
 
5.7%
Other values (39) 142
32.4%
Common
ValueCountFrequency (%)
118
40.4%
) 27
 
9.2%
( 27
 
9.2%
1 22
 
7.5%
, 14
 
4.8%
4 12
 
4.1%
2 11
 
3.8%
6 10
 
3.4%
3 10
 
3.4%
5 9
 
3.1%
Other values (5) 32
 
11.0%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 438
59.8%
ASCII 294
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
40.1%
) 27
 
9.2%
( 27
 
9.2%
1 22
 
7.5%
, 14
 
4.8%
4 12
 
4.1%
2 11
 
3.7%
6 10
 
3.4%
3 10
 
3.4%
5 9
 
3.1%
Other values (6) 34
 
11.6%
Hangul
ValueCountFrequency (%)
봉 40
 
9.1%
도 39
 
8.9%
동 31
 
7.1%
시 31
 
7.1%
서 26
 
5.9%
특 26
 
5.9%
별 26
 
5.9%
구 26
 
5.9%
울 26
 
5.9%
로 25
 
5.7%
Other values (39) 142
32.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)100.0%
Missing64
Missing (%)71.1%
Infinite0
Infinite (%)0.0%
Mean1395.9615
Minimum1301
Maximum1489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-05-11T15:51:06.996222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1301
5-th percentile1307
Q11355.5
median1397
Q31440.75
95-th percentile1474.5
Maximum1489
Range188
Interquartile range (IQR)85.25

Descriptive statistics

Standard deviation59.079256
Coefficient of variation (CV)0.04232155
Kurtosis-1.210394
Mean1395.9615
Median Absolute Deviation (MAD)44
Skewness-0.14706607
Sum36295
Variance3490.3585
MonotonicityNot monotonic
2024-05-11T15:51:07.219275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1301 1
 
1.1%
1434 1
 
1.1%
1385 1
 
1.1%
1489 1
 
1.1%
1357 1
 
1.1%
1389 1
 
1.1%
1331 1
 
1.1%
1455 1
 
1.1%
1432 1
 
1.1%
1416 1
 
1.1%
Other values (16) 16
 
17.8%
(Missing) 64
71.1%
ValueCountFrequency (%)
1301 1
1.1%
1306 1
1.1%
1310 1
1.1%
1314 1
1.1%
1322 1
1.1%
1331 1
1.1%
1355 1
1.1%
1357 1
1.1%
1359 1
1.1%
1379 1
1.1%
ValueCountFrequency (%)
1489 1
1.1%
1476 1
1.1%
1470 1
1.1%
1469 1
1.1%
1467 1
1.1%
1455 1
1.1%
1443 1
1.1%
1434 1
1.1%
1432 1
1.1%
1429 1
1.1%

사업장명
Text

Distinct83
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-05-11T15:51:07.672562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length4.8666667
Min length2

Characters and Unicode

Total characters438
Distinct characters129
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)85.6%

Sample

1st row남문탕
2nd row유림탕
3rd row은호탕
4th row진양탕
5th row북일탕
ValueCountFrequency (%)
사우나 5
 
5.0%
은하탕 3
 
3.0%
옥 3
 
3.0%
쌍용탕 2
 
2.0%
대원 2
 
2.0%
두승대중목욕탕 2
 
2.0%
올림픽 2
 
2.0%
로얄목욕탕 2
 
2.0%
도봉산싱싱사우나 1
 
1.0%
동성 1
 
1.0%
Other values (78) 78
77.2%
2024-05-11T15:51:08.374617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 61
 
13.9%
우 20
 
4.6%
사 19
 
4.3%
나 19
 
4.3%
목 19
 
4.3%
욕 19
 
4.3%
대 17
 
3.9%
중 11
 
2.5%
11
 
2.5%
천 9
 
2.1%
Other values (119) 233
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
96.1%
Space Separator 11
 
2.5%
Decimal Number 2
 
0.5%
Other Punctuation 2
 
0.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 61
 
14.5%
우 20
 
4.8%
사 19
 
4.5%
나 19
 
4.5%
목 19
 
4.5%
욕 19
 
4.5%
대 17
 
4.0%
중 11
 
2.6%
천 9
 
2.1%
성 9
 
2.1%
Other values (112) 218
51.8%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
96.1%
Common 17
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 61
 
14.5%
우 20
 
4.8%
사 19
 
4.5%
나 19
 
4.5%
목 19
 
4.5%
욕 19
 
4.5%
대 17
 
4.0%
중 11
 
2.6%
천 9
 
2.1%
성 9
 
2.1%
Other values (112) 218
51.8%
Common
ValueCountFrequency (%)
11
64.7%
4 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%
. 1
 
5.9%
( 1
 
5.9%
) 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
96.1%
ASCII 17
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 61
 
14.5%
우 20
 
4.8%
사 19
 
4.5%
나 19
 
4.5%
목 19
 
4.5%
욕 19
 
4.5%
대 17
 
4.0%
중 11
 
2.6%
천 9
 
2.1%
성 9
 
2.1%
Other values (112) 218
51.8%
ASCII
ValueCountFrequency (%)
11
64.7%
4 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%
. 1
 
5.9%
( 1
 
5.9%
) 1
 
5.9%

최종수정일자
Date

Distinct66
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum1999-08-31 00:00:00
Maximum2024-04-16 09:48:17
2024-05-11T15:51:08.636301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:08.918139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
I
66 
U
24 

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 66
73.3%
U 24
 
26.7%

Length

2024-05-11T15:51:09.129761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:09.359058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 66
73.3%
u 24
 
26.7%

데이터갱신일자
Date

Distinct18
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-05-11T15:51:09.528472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:09.749012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
공동탕업
77 
공동탕업+찜질시설서비스영업
12 
목욕장업 기타
 
1

Length

Max length14
Median length4
Mean length5.3666667
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 77
85.6%
공동탕업+찜질시설서비스영업 12
 
13.3%
목욕장업 기타 1
 
1.1%

Length

2024-05-11T15:51:10.045110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:10.249196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 77
84.6%
공동탕업+찜질시설서비스영업 12
 
13.2%
목욕장업 1
 
1.1%
기타 1
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)80.2%
Missing4
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean203237.23
Minimum201167.09
Maximum204719.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-05-11T15:51:10.461846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201167.09
5-th percentile202136
Q1202845.29
median203200.87
Q3203719.64
95-th percentile204386.77
Maximum204719.28
Range3552.1908
Interquartile range (IQR)874.3446

Descriptive statistics

Standard deviation741.12121
Coefficient of variation (CV)0.003646582
Kurtosis0.97703197
Mean203237.23
Median Absolute Deviation (MAD)450.33801
Skewness-0.56686303
Sum17478402
Variance549260.65
MonotonicityNot monotonic
2024-05-11T15:51:10.740721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202845.291963923 4
 
4.4%
204111.39312246 3
 
3.3%
202689.091766098 2
 
2.2%
202514.254595328 2
 
2.2%
203163.4892727 2
 
2.2%
203220.921406024 2
 
2.2%
202960.38831722 2
 
2.2%
204719.277363253 2
 
2.2%
203651.208011649 2
 
2.2%
204391.615 2
 
2.2%
Other values (59) 63
70.0%
(Missing) 4
 
4.4%
ValueCountFrequency (%)
201167.086526829 1
1.1%
201177.743198866 2
2.2%
201290.398748685 1
1.1%
202104.930009838 1
1.1%
202229.214835264 1
1.1%
202407.917419757 1
1.1%
202416.159454124 1
1.1%
202514.254595328 2
2.2%
202531.829312848 1
1.1%
202616.381133222 1
1.1%
ValueCountFrequency (%)
204719.277363253 2
2.2%
204414.113861369 1
 
1.1%
204391.615 2
2.2%
204372.245062863 1
 
1.1%
204290.372418121 1
 
1.1%
204135.386163501 1
 
1.1%
204120.313491171 1
 
1.1%
204111.39312246 3
3.3%
204083.769271308 1
 
1.1%
204047.061280934 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)80.2%
Missing4
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean461771.1
Minimum459351.63
Maximum465094.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-05-11T15:51:11.034001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum459351.63
5-th percentile459745.13
Q1460687.65
median461650.23
Q3462724.81
95-th percentile464174.85
Maximum465094.19
Range5742.5564
Interquartile range (IQR)2037.1596

Descriptive statistics

Standard deviation1393.9464
Coefficient of variation (CV)0.0030186957
Kurtosis-0.60592264
Mean461771.1
Median Absolute Deviation (MAD)1059.6052
Skewness0.30646883
Sum39712314
Variance1943086.6
MonotonicityNot monotonic
2024-05-11T15:51:11.300661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462724.806678955 4
 
4.4%
464174.850719823 3
 
3.3%
460933.143726765 2
 
2.2%
461495.802497168 2
 
2.2%
460267.764490406 2
 
2.2%
459746.924430501 2
 
2.2%
459745.131171423 2
 
2.2%
460365.605858665 2
 
2.2%
462576.540812657 2
 
2.2%
461208.365 2
 
2.2%
Other values (59) 63
70.0%
(Missing) 4
 
4.4%
ValueCountFrequency (%)
459351.632781587 1
1.1%
459579.006433072 1
1.1%
459584.582698404 1
1.1%
459727.261479337 1
1.1%
459745.131171423 2
2.2%
459746.924430501 2
2.2%
459820.472338941 1
1.1%
459824.7352776 1
1.1%
459877.64952715 1
1.1%
460224.197874758 1
1.1%
ValueCountFrequency (%)
465094.18915856 1
 
1.1%
464731.761130542 1
 
1.1%
464404.895005692 1
 
1.1%
464385.587785162 1
 
1.1%
464174.850719823 3
3.3%
464069.834711115 1
 
1.1%
463765.987531795 1
 
1.1%
463763.240794805 1
 
1.1%
463510.022238309 1
 
1.1%
463494.086004902 1
 
1.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
공동탕업
74 
공동탕업+찜질시설서비스영업
9 
<NA>
 
6
목욕장업 기타
 
1

Length

Max length14
Median length4
Mean length5.0333333
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 74
82.2%
공동탕업+찜질시설서비스영업 9
 
10.0%
<NA> 6
 
6.7%
목욕장업 기타 1
 
1.1%

Length

2024-05-11T15:51:11.648993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:11.858869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 74
81.3%
공동탕업+찜질시설서비스영업 9
 
9.9%
na 6
 
6.6%
목욕장업 1
 
1.1%
기타 1
 
1.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.1%
Missing21
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean1.5942029
Minimum0
Maximum7
Zeros39
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-05-11T15:51:12.118263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.009674
Coefficient of variation (CV)1.2606137
Kurtosis-0.61806865
Mean1.5942029
Median Absolute Deviation (MAD)0
Skewness0.8153097
Sum110
Variance4.0387894
MonotonicityNot monotonic
2024-05-11T15:51:12.296702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 39
43.3%
4 12
 
13.3%
3 7
 
7.8%
2 6
 
6.7%
6 2
 
2.2%
5 2
 
2.2%
7 1
 
1.1%
(Missing) 21
23.3%
ValueCountFrequency (%)
0 39
43.3%
2 6
 
6.7%
3 7
 
7.8%
4 12
 
13.3%
5 2
 
2.2%
6 2
 
2.2%
7 1
 
1.1%
ValueCountFrequency (%)
7 1
 
1.1%
6 2
 
2.2%
5 2
 
2.2%
4 12
 
13.3%
3 7
 
7.8%
2 6
 
6.7%
0 39
43.3%

건물지하층수
Categorical

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
41 
1
24 
<NA>
22 
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.7333333
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 41
45.6%
1 24
26.7%
<NA> 22
24.4%
2 2
 
2.2%
3 1
 
1.1%

Length

2024-05-11T15:51:12.548726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:12.774921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
45.6%
1 24
26.7%
na 22
24.4%
2 2
 
2.2%
3 1
 
1.1%

사용시작지상층
Categorical

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
42 
<NA>
21 
1
17 
2
9 
3
 
1

Length

Max length4
Median length1
Mean length1.7
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42
46.7%
<NA> 21
23.3%
1 17
18.9%
2 9
 
10.0%
3 1
 
1.1%

Length

2024-05-11T15:51:12.985263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:13.181365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
46.7%
na 21
23.3%
1 17
18.9%
2 9
 
10.0%
3 1
 
1.1%

사용끝지상층
Categorical

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
53 
3
10 
0
10 
2
9 
1
 
5

Length

Max length4
Median length4
Mean length2.7666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 53
58.9%
3 10
 
11.1%
0 10
 
11.1%
2 9
 
10.0%
1 5
 
5.6%
4 3
 
3.3%

Length

2024-05-11T15:51:13.370552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:13.558642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
58.9%
3 10
 
11.1%
0 10
 
11.1%
2 9
 
10.0%
1 5
 
5.6%
4 3
 
3.3%

사용시작지하층
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
41 
<NA>
27 
1
22 

Length

Max length4
Median length1
Mean length1.9
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 41
45.6%
<NA> 27
30.0%
1 22
24.4%

Length

2024-05-11T15:51:13.778379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:13.970809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
45.6%
na 27
30.0%
1 22
24.4%

사용끝지하층
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
59 
1
20 
0
9 
2
 
2

Length

Max length4
Median length4
Mean length2.9666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
65.6%
1 20
 
22.2%
0 9
 
10.0%
2 2
 
2.2%

Length

2024-05-11T15:51:14.139603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:14.352246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
65.6%
1 20
 
22.2%
0 9
 
10.0%
2 2
 
2.2%

한실수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
54 
<NA>
36 

Length

Max length4
Median length1
Mean length2.2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 54
60.0%
<NA> 36
40.0%

Length

2024-05-11T15:51:14.546873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:14.723946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
60.0%
na 36
40.0%

양실수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
54 
<NA>
36 

Length

Max length4
Median length1
Mean length2.2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 54
60.0%
<NA> 36
40.0%

Length

2024-05-11T15:51:14.914467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:15.084399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
60.0%
na 36
40.0%

욕실수
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
48 
<NA>
29 
2
12 
1
 
1

Length

Max length4
Median length1
Mean length1.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 48
53.3%
<NA> 29
32.2%
2 12
 
13.3%
1 1
 
1.1%

Length

2024-05-11T15:51:15.260504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:15.421416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 48
53.3%
na 29
32.2%
2 12
 
13.3%
1 1
 
1.1%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)2.4%
Missing6
Missing (%)6.7%
Memory size312.0 B
False
77 
True
 
7
(Missing)
 
6
ValueCountFrequency (%)
False 77
85.6%
True 7
 
7.8%
(Missing) 6
 
6.7%
2024-05-11T15:51:15.893111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
0
54 
<NA>
36 

Length

Max length4
Median length1
Mean length2.2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 54
60.0%
<NA> 36
40.0%

Length

2024-05-11T15:51:16.055883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:16.260825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
60.0%
na 36
40.0%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

건물소유구분명
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
55 
자가
21 
임대
14 

Length

Max length4
Median length4
Mean length3.2222222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 55
61.1%
자가 21
 
23.3%
임대 14
 
15.6%

Length

2024-05-11T15:51:16.468782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:16.683953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
61.1%
자가 21
 
23.3%
임대 14
 
15.6%

세탁기수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
68 
0
22 

Length

Max length4
Median length4
Mean length3.2666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 68
75.6%
0 22
 
24.4%

Length

2024-05-11T15:51:16.896673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:17.075235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
75.6%
0 22
 
24.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
88 
0
 
2

Length

Max length4
Median length4
Mean length3.9333333
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> 88
97.8%
0 2
 
2.2%

Length

2024-05-11T15:51:17.262123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:17.451177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
97.8%
0 2
 
2.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
88 
0
 
2

Length

Max length4
Median length4
Mean length3.9333333
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> 88
97.8%
0 2
 
2.2%

Length

2024-05-11T15:51:17.687948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:17.892267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
97.8%
0 2
 
2.2%

회수건조수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
70 
0
20 

Length

Max length4
Median length4
Mean length3.3333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
77.8%
0 20
 
22.2%

Length

2024-05-11T15:51:18.126899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:18.376232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
77.8%
0 20
 
22.2%

침대수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
70 
0
20 

Length

Max length4
Median length4
Mean length3.3333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
77.8%
0 20
 
22.2%

Length

2024-05-11T15:51:18.618243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:18.810649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
77.8%
0 20
 
22.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.2%
Missing6
Missing (%)6.7%
Memory size312.0 B
False
84 
(Missing)
 
6
ValueCountFrequency (%)
False 84
93.3%
(Missing) 6
 
6.7%
2024-05-11T15:51:18.992858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030900003090000-202-1968-0009619681206<NA>3폐업2폐업19990910<NA><NA><NA>02 9920979121.85132822서울특별시 도봉구 도봉동 633-13번지<NA><NA>남문탕1999-09-10 00:00:00I2018-08-31 23:59:59.0공동탕업204120.313491463510.022238공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130900003090000-202-1971-0006119711230<NA>1영업/정상1영업<NA><NA><NA><NA>0209918893154.88132866서울특별시 도봉구 쌍문동 120-8번지서울특별시 도봉구 도봉로113가길 5 (쌍문동)1443유림탕2019-11-13 17:42:44U2019-11-15 02:40:00.0공동탕업202775.158407460701.660336공동탕업201100000N0<NA><NA><NA>자가0<NA><NA>00N
230900003090000-202-1972-0006819721007<NA>3폐업2폐업19990831<NA><NA><NA>02144.90132918서울특별시 도봉구 창동 582-24번지<NA><NA>은호탕1999-08-31 00:00:00I2018-08-31 23:59:59.0공동탕업203105.783988459820.472339공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330900003090000-202-1972-0009719721214<NA>3폐업2폐업19970825<NA><NA><NA>0209923314163.20132821서울특별시 도봉구 도봉동 624-83번지<NA><NA>진양탕2002-01-18 00:00:00I2018-08-31 23:59:59.0공동탕업204019.915809463372.616482공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430900003090000-202-1973-0005519731219<NA>3폐업2폐업20020501<NA><NA><NA>02 9967289214.35132863서울특별시 도봉구 쌍문동 85-6번지<NA><NA>북일탕2002-05-01 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
530900003090000-202-1973-0006619730226<NA>3폐업2폐업20001027<NA><NA><NA>02 9928606224.20132920서울특별시 도봉구 창동 621-53번지<NA><NA>서울낙원2003-01-20 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
630900003090000-202-1974-0008419741217<NA>3폐업2폐업20001027<NA><NA><NA>0234917373421.28132845서울특별시 도봉구 방학동 649-29번지<NA><NA>현대온탕2000-10-27 00:00:00I2018-08-31 23:59:59.0공동탕업203588.667124462838.090373공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730900003090000-202-1975-0007219751230<NA>1영업/정상1영업<NA><NA><NA><NA>0209929789207.45132917서울특별시 도봉구 창동 532-1서울특별시 도봉구 우이천로12길 41 (창동)1476송림탕2020-10-15 11:30:25U2020-10-17 02:40:00.0공동탕업203485.37849459351.632782공동탕업311311000N0<NA><NA><NA><NA>0<NA><NA>00N
830900003090000-202-1978-0005919781130<NA>3폐업2폐업20000107<NA><NA><NA>0209032432158.52132884서울특별시 도봉구 쌍문동 381-4번지<NA><NA>쌍문탕2000-01-07 00:00:00I2018-08-31 23:59:59.0공동탕업202229.214835460537.736609공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930900003090000-202-1978-0011119781220<NA>3폐업2폐업19940331<NA><NA><NA>0209922333199.84132010서울특별시 도봉구 도봉동 661-1번지<NA><NA>방학탕2002-01-18 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
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
8030900003090000-202-2003-0000420031211<NA>3폐업2폐업20070222<NA><NA><NA>9902046388.00132890서울특별시 도봉구 쌍문동 509-1번지<NA><NA>올림픽2006-05-16 00:00:00I2018-08-31 23:59:59.0공동탕업201177.743199461734.803519공동탕업51<NA><NA>11<NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
8130900003090000-202-2004-0000120040109<NA>3폐업2폐업20071217<NA><NA><NA><NA>989.80132861서울특별시 도봉구 쌍문동 59-5번지 한양6차상가 지층<NA><NA>한양여성전용 한증막2009-04-21 17:17:38I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업202514.254595461495.802497공동탕업+찜질시설서비스영업43<NA><NA>11001N0<NA><NA><NA>자가0<NA><NA><NA><NA>N
8230900003090000-202-2004-0000220040407<NA>1영업/정상1영업<NA><NA><NA><NA>02 9550206494.00132827서울특별시 도봉구 방학동 263-75 지층서울특별시 도봉구 도당로 36 (방학동,지층)1389수정목욕탕2021-02-09 10:11:38U2021-02-11 02:40:00.0공동탕업+찜질시설서비스영업203024.819705462097.646735공동탕업+찜질시설서비스영업410011002N0<NA><NA><NA>임대0<NA><NA>00N
8330900003090000-202-2004-0000320040903<NA>3폐업2폐업20170202<NA><NA><NA>02 9566973375.00132848서울특별시 도봉구 방학동 668-3번지서울특별시 도봉구 도당로9길 47 (방학동)1357로얄목욕탕2015-12-04 14:20:20I2018-08-31 23:59:59.0목욕장업 기타202748.76714462257.05523목욕장업 기타312111002N0<NA><NA><NA>임대0<NA><NA>00N
8430900003090000-202-2004-0000420041227<NA>3폐업2폐업20181030<NA><NA><NA>02 905 8007804.00132901서울특별시 도봉구 창동 38-3번지서울특별시 도봉구 덕릉로 408 (창동)1489녹천24시사우나2018-10-30 16:14:19U2018-11-01 02:38:03.0공동탕업+찜질시설서비스영업204719.277363460365.605859공동탕업+찜질시설서비스영업420012002N0<NA><NA><NA>자가0<NA><NA>00N
8530900003090000-202-2005-0000120050613<NA>3폐업2폐업20180404<NA><NA><NA>991 1188809.00132858서울특별시 도봉구 쌍문동 20번지 벽상상가동 B101,B201호 지하1,2층서울특별시 도봉구 도당로 7, 상가동 지하1,2층 B101,B201호 (쌍문동, 벽산아파트)1385벽산사우나2018-04-04 15:17:02I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업202998.896552461818.50605공동탕업+찜질시설서비스영업000012002Y0<NA><NA><NA>임대0<NA><NA>00N
8630900003090000-202-2005-0000220050912<NA>3폐업2폐업20060921<NA><NA><NA>9912135261.00132864서울특별시 도봉구 쌍문동 94-56번지 1층<NA><NA>효재목욕탕2005-09-12 00:00:00I2018-08-31 23:59:59.0공동탕업202835.069813460682.97605공동탕업<NA><NA>11<NA><NA><NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
8730900003090000-202-2006-0000120060731<NA>3폐업2폐업20080711<NA><NA><NA>90027802,686.00132920서울특별시 도봉구 창동 623-45번지<NA><NA>도래천스파월드2007-05-10 00:00:00I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업203163.489273460267.76449공동탕업+찜질시설서비스영업<NA><NA>12<NA><NA><NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
8830900003090000-202-2006-0000220060829<NA>3폐업2폐업20091012<NA><NA><NA>9569944390.00132839서울특별시 도봉구 방학동 619-7번지<NA><NA>대원 옥 사우나2008-03-05 16:39:09I2018-08-31 23:59:59.0공동탕업202845.291964462724.806679공동탕업<NA><NA>23<NA><NA><NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
8930900003090000-202-2008-0000120080226<NA>1영업/정상1영업<NA><NA><NA><NA>02 900 6547820.16132861서울특별시 도봉구 쌍문동 59-5 쌍문6차아파트상가 지하1층서울특별시 도봉구 시루봉로 56, 상가동 지하1층 (쌍문동, 쌍문6차아파트)1434선덕 사우나2020-10-15 11:04:39U2020-10-17 02:40:00.0공동탕업+찜질시설서비스영업202514.254595461495.802497공동탕업+찜질시설서비스영업000011002Y0<NA><NA><NA>자가0<NA><NA>00N