Overview

Dataset statistics

Number of variables47
Number of observations125
Missing cells1159
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.6 KiB
Average record size in memory406.1 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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-19964/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (61.5%)Imbalance
위생업태명 is highly imbalanced (58.0%)Imbalance
발한실여부 is highly imbalanced (74.9%)Imbalance
건물소유구분명 is highly imbalanced (76.2%)Imbalance
여성종사자수 is highly imbalanced (79.6%)Imbalance
남성종사자수 is highly imbalanced (79.6%)Imbalance
인허가취소일자 has 125 (100.0%) missing valuesMissing
폐업일자 has 23 (18.4%) missing valuesMissing
휴업시작일자 has 125 (100.0%) missing valuesMissing
휴업종료일자 has 125 (100.0%) missing valuesMissing
재개업일자 has 125 (100.0%) missing valuesMissing
전화번호 has 3 (2.4%) missing valuesMissing
도로명주소 has 79 (63.2%) missing valuesMissing
도로명우편번호 has 81 (64.8%) missing valuesMissing
좌표정보(X) has 18 (14.4%) missing valuesMissing
좌표정보(Y) has 18 (14.4%) missing valuesMissing
건물지상층수 has 50 (40.0%) missing valuesMissing
발한실여부 has 6 (4.8%) missing valuesMissing
조건부허가신고사유 has 125 (100.0%) missing valuesMissing
조건부허가시작일자 has 125 (100.0%) missing valuesMissing
조건부허가종료일자 has 125 (100.0%) missing valuesMissing
다중이용업소여부 has 6 (4.8%) 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 66 (52.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:15:40.756037
Analysis finished2024-05-11 06:15:41.914082
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3120000
125 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3120000 125
100.0%

Length

2024-05-11T15:15:42.066495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:42.237010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 125
100.0%

관리번호
Text

UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:15:42.555210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2750
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

Unique125 ?
Unique (%)100.0%

Sample

1st row3120000-202-1962-01251
2nd row3120000-202-1963-00129
3rd row3120000-202-1963-01260
4th row3120000-202-1964-01252
5th row3120000-202-1965-01262
ValueCountFrequency (%)
3120000-202-1962-01251 1
 
0.8%
3120000-202-1988-00108 1
 
0.8%
3120000-202-1999-00952 1
 
0.8%
3120000-202-1998-01402 1
 
0.8%
3120000-202-1998-01400 1
 
0.8%
3120000-202-1998-01399 1
 
0.8%
3120000-202-1998-01263 1
 
0.8%
3120000-202-1998-01261 1
 
0.8%
3120000-202-1998-01037 1
 
0.8%
3120000-202-1998-01024 1
 
0.8%
Other values (115) 115
92.0%
2024-05-11T15:15:43.102756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 956
34.8%
2 490
17.8%
1 384
14.0%
- 375
 
13.6%
3 169
 
6.1%
9 145
 
5.3%
8 64
 
2.3%
4 55
 
2.0%
7 49
 
1.8%
6 35
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2375
86.4%
Dash Punctuation 375
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 956
40.3%
2 490
20.6%
1 384
16.2%
3 169
 
7.1%
9 145
 
6.1%
8 64
 
2.7%
4 55
 
2.3%
7 49
 
2.1%
6 35
 
1.5%
5 28
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 375
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2750
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 956
34.8%
2 490
17.8%
1 384
14.0%
- 375
 
13.6%
3 169
 
6.1%
9 145
 
5.3%
8 64
 
2.3%
4 55
 
2.0%
7 49
 
1.8%
6 35
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 956
34.8%
2 490
17.8%
1 384
14.0%
- 375
 
13.6%
3 169
 
6.1%
9 145
 
5.3%
8 64
 
2.3%
4 55
 
2.0%
7 49
 
1.8%
6 35
 
1.3%

인허가일자
Date

Distinct118
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1962-05-14 00:00:00
Maximum2021-02-22 00:00:00
2024-05-11T15:15:43.358146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:43.622609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
102 
1
23 

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 (%)
3 102
81.6%
1 23
 
18.4%

Length

2024-05-11T15:15:43.940624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:44.103870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 102
81.6%
1 23
 
18.4%

영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
102 
영업/정상
23 

Length

Max length5
Median length2
Mean length2.552
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 102
81.6%
영업/정상 23
 
18.4%

Length

2024-05-11T15:15:44.305289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:44.494875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 102
81.6%
영업/정상 23
 
18.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2
102 
1
23 

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 (%)
2 102
81.6%
1 23
 
18.4%

Length

2024-05-11T15:15:44.683928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:44.867029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 102
81.6%
1 23
 
18.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
102 
영업
23 

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 102
81.6%
영업 23
 
18.4%

Length

2024-05-11T15:15:45.043957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:45.222962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 102
81.6%
영업 23
 
18.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct90
Distinct (%)88.2%
Missing23
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean20062508
Minimum19930727
Maximum20211202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:15:45.426364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930727
5-th percentile19961020
Q120010956
median20050261
Q320120853
95-th percentile20200894
Maximum20211202
Range280475
Interquartile range (IQR)109897.25

Descriptive statistics

Standard deviation71994.494
Coefficient of variation (CV)0.0035885091
Kurtosis-0.7635153
Mean20062508
Median Absolute Deviation (MAD)50615
Skewness0.34452895
Sum2.0463758 × 109
Variance5.1832071 × 109
MonotonicityNot monotonic
2024-05-11T15:15:45.710277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20011110 5
 
4.0%
19990904 2
 
1.6%
20090511 2
 
1.6%
20030723 2
 
1.6%
20071008 2
 
1.6%
20041122 2
 
1.6%
20050321 2
 
1.6%
20140613 2
 
1.6%
20091231 2
 
1.6%
20201005 1
 
0.8%
Other values (80) 80
64.0%
(Missing) 23
 
18.4%
ValueCountFrequency (%)
19930727 1
0.8%
19941104 1
0.8%
19950111 1
0.8%
19960520 1
0.8%
19960614 1
0.8%
19961019 1
0.8%
19961031 1
0.8%
19970220 1
0.8%
19970417 1
0.8%
19970613 1
0.8%
ValueCountFrequency (%)
20211202 1
0.8%
20211119 1
0.8%
20201104 1
0.8%
20201102 1
0.8%
20201005 1
0.8%
20200903 1
0.8%
20200724 1
0.8%
20191105 1
0.8%
20180110 1
0.8%
20161129 1
0.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

전화번호
Text

MISSING 

Distinct118
Distinct (%)96.7%
Missing3
Missing (%)2.4%
Memory size1.1 KiB
2024-05-11T15:15:46.262874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.032787
Min length7

Characters and Unicode

Total characters1224
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

Unique114 ?
Unique (%)93.4%

Sample

1st row02 7381407
2nd row02 7469518
3rd row0203621123
4th row0203921724
5th row0203727167
ValueCountFrequency (%)
02 64
33.9%
7300277 2
 
1.1%
3721989 2
 
1.1%
308 2
 
1.1%
8777 2
 
1.1%
3127031 2
 
1.1%
3126611 1
 
0.5%
0203320222 1
 
0.5%
3649222 1
 
0.5%
3720700 1
 
0.5%
Other values (111) 111
58.7%
2024-05-11T15:15:46.926032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 252
20.6%
2 236
19.3%
3 199
16.3%
7 100
 
8.2%
1 78
 
6.4%
69
 
5.6%
5 63
 
5.1%
6 61
 
5.0%
9 60
 
4.9%
4 60
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1155
94.4%
Space Separator 69
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 252
21.8%
2 236
20.4%
3 199
17.2%
7 100
 
8.7%
1 78
 
6.8%
5 63
 
5.5%
6 61
 
5.3%
9 60
 
5.2%
4 60
 
5.2%
8 46
 
4.0%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 252
20.6%
2 236
19.3%
3 199
16.3%
7 100
 
8.2%
1 78
 
6.4%
69
 
5.6%
5 63
 
5.1%
6 61
 
5.0%
9 60
 
4.9%
4 60
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 252
20.6%
2 236
19.3%
3 199
16.3%
7 100
 
8.2%
1 78
 
6.4%
69
 
5.6%
5 63
 
5.1%
6 61
 
5.0%
9 60
 
4.9%
4 60
 
4.9%

소재지면적
Text

Distinct123
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:15:47.520686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.096
Min length3

Characters and Unicode

Total characters762
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

Unique121 ?
Unique (%)96.8%

Sample

1st row106.38
2nd row185.03
3rd row128.90
4th row153.25
5th row179.57
ValueCountFrequency (%)
258.52 2
 
1.6%
117.36 2
 
1.6%
1,339.99 1
 
0.8%
222.85 1
 
0.8%
215.86 1
 
0.8%
412.81 1
 
0.8%
641.37 1
 
0.8%
205.44 1
 
0.8%
160.27 1
 
0.8%
2,307.00 1
 
0.8%
Other values (113) 113
90.4%
2024-05-11T15:15:48.383162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 125
16.4%
2 89
11.7%
1 82
10.8%
3 74
9.7%
6 68
8.9%
0 67
8.8%
5 59
7.7%
4 54
7.1%
7 50
 
6.6%
9 46
 
6.0%
Other values (2) 48
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 629
82.5%
Other Punctuation 133
 
17.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 89
14.1%
1 82
13.0%
3 74
11.8%
6 68
10.8%
0 67
10.7%
5 59
9.4%
4 54
8.6%
7 50
7.9%
9 46
7.3%
8 40
6.4%
Other Punctuation
ValueCountFrequency (%)
. 125
94.0%
, 8
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 125
16.4%
2 89
11.7%
1 82
10.8%
3 74
9.7%
6 68
8.9%
0 67
8.8%
5 59
7.7%
4 54
7.1%
7 50
 
6.6%
9 46
 
6.0%
Other values (2) 48
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 125
16.4%
2 89
11.7%
1 82
10.8%
3 74
9.7%
6 68
8.9%
0 67
8.8%
5 59
7.7%
4 54
7.1%
7 50
 
6.6%
9 46
 
6.0%
Other values (2) 48
 
6.3%

소재지우편번호
Text

Distinct62
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:15:48.925880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.016
Min length6

Characters and Unicode

Total characters752
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

Unique26 ?
Unique (%)20.8%

Sample

1st row120857
2nd row120856
3rd row120819
4th row120865
5th row120060
ValueCountFrequency (%)
120827 6
 
4.8%
120821 5
 
4.0%
120857 5
 
4.0%
120805 5
 
4.0%
120833 4
 
3.2%
120820 3
 
2.4%
120809 3
 
2.4%
120802 3
 
2.4%
120815 3
 
2.4%
120836 3
 
2.4%
Other values (52) 85
68.0%
2024-05-11T15:15:49.606990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 193
25.7%
1 166
22.1%
2 153
20.3%
8 105
14.0%
5 36
 
4.8%
3 28
 
3.7%
7 21
 
2.8%
4 18
 
2.4%
6 17
 
2.3%
9 13
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
99.7%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 193
25.7%
1 166
22.1%
2 153
20.4%
8 105
14.0%
5 36
 
4.8%
3 28
 
3.7%
7 21
 
2.8%
4 18
 
2.4%
6 17
 
2.3%
9 13
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 193
25.7%
1 166
22.1%
2 153
20.3%
8 105
14.0%
5 36
 
4.8%
3 28
 
3.7%
7 21
 
2.8%
4 18
 
2.4%
6 17
 
2.3%
9 13
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 193
25.7%
1 166
22.1%
2 153
20.3%
8 105
14.0%
5 36
 
4.8%
3 28
 
3.7%
7 21
 
2.8%
4 18
 
2.4%
6 17
 
2.3%
9 13
 
1.7%

지번주소
Text

Distinct118
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:15:50.175480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length24.392
Min length18

Characters and Unicode

Total characters3049
Distinct characters81
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

Unique111 ?
Unique (%)88.8%

Sample

1st row서울특별시 서대문구 홍제동 266-21번지
2nd row서울특별시 서대문구 홍제동 174-18번지
3rd row서울특별시 서대문구 북아현동 147-1번지
4th row서울특별시 서대문구 북아현동 1-149번지
5th row서울특별시 서대문구 옥천동 3-0번지
ValueCountFrequency (%)
서울특별시 125
24.0%
서대문구 125
24.0%
홍제동 23
 
4.4%
남가좌동 19
 
3.7%
북가좌동 15
 
2.9%
북아현동 14
 
2.7%
연희동 14
 
2.7%
홍은동 11
 
2.1%
창천동 10
 
1.9%
대현동 3
 
0.6%
Other values (144) 161
31.0%
2024-05-11T15:15:51.017931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
514
16.9%
서 250
 
8.2%
1 140
 
4.6%
대 130
 
4.3%
특 125
 
4.1%
별 125
 
4.1%
시 125
 
4.1%
문 125
 
4.1%
구 125
 
4.1%
울 125
 
4.1%
Other values (71) 1265
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1829
60.0%
Decimal Number 570
 
18.7%
Space Separator 514
 
16.9%
Dash Punctuation 114
 
3.7%
Other Punctuation 12
 
0.4%
Uppercase Letter 4
 
0.1%
Open Punctuation 3
 
0.1%
Close Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 250
13.7%
대 130
 
7.1%
특 125
 
6.8%
별 125
 
6.8%
시 125
 
6.8%
문 125
 
6.8%
구 125
 
6.8%
울 125
 
6.8%
동 123
 
6.7%
지 114
 
6.2%
Other values (52) 462
25.3%
Decimal Number
ValueCountFrequency (%)
1 140
24.6%
2 76
13.3%
3 70
12.3%
4 52
 
9.1%
0 51
 
8.9%
5 46
 
8.1%
7 42
 
7.4%
6 38
 
6.7%
9 32
 
5.6%
8 23
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
K 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
514
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1829
60.0%
Common 1216
39.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 250
13.7%
대 130
 
7.1%
특 125
 
6.8%
별 125
 
6.8%
시 125
 
6.8%
문 125
 
6.8%
구 125
 
6.8%
울 125
 
6.8%
동 123
 
6.7%
지 114
 
6.2%
Other values (52) 462
25.3%
Common
ValueCountFrequency (%)
514
42.3%
1 140
 
11.5%
- 114
 
9.4%
2 76
 
6.2%
3 70
 
5.8%
4 52
 
4.3%
0 51
 
4.2%
5 46
 
3.8%
7 42
 
3.5%
6 38
 
3.1%
Other values (6) 73
 
6.0%
Latin
ValueCountFrequency (%)
B 2
50.0%
K 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1829
60.0%
ASCII 1220
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
514
42.1%
1 140
 
11.5%
- 114
 
9.3%
2 76
 
6.2%
3 70
 
5.7%
4 52
 
4.3%
0 51
 
4.2%
5 46
 
3.8%
7 42
 
3.4%
6 38
 
3.1%
Other values (9) 77
 
6.3%
Hangul
ValueCountFrequency (%)
서 250
13.7%
대 130
 
7.1%
특 125
 
6.8%
별 125
 
6.8%
시 125
 
6.8%
문 125
 
6.8%
구 125
 
6.8%
울 125
 
6.8%
동 123
 
6.7%
지 114
 
6.2%
Other values (52) 462
25.3%

도로명주소
Text

MISSING 

Distinct43
Distinct (%)93.5%
Missing79
Missing (%)63.2%
Memory size1.1 KiB
2024-05-11T15:15:51.489666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length29.717391
Min length23

Characters and Unicode

Total characters1367
Distinct characters107
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

Unique40 ?
Unique (%)87.0%

Sample

1st row서울특별시 서대문구 북아현로14길 27 (북아현동)
2nd row서울특별시 서대문구 통일로39길 22-43 (홍제동)
3rd row서울특별시 서대문구 통일로32길 6 (홍제동)
4th row서울특별시 서대문구 독립문로 1 (영천동)
5th row서울특별시 서대문구 세무서길 103 (홍제동)
ValueCountFrequency (%)
서울특별시 46
 
18.3%
서대문구 46
 
18.3%
홍제동 13
 
5.2%
남가좌동 8
 
3.2%
창천동 4
 
1.6%
연희동 4
 
1.6%
통일로32길 3
 
1.2%
모래내로 3
 
1.2%
6 3
 
1.2%
35 3
 
1.2%
Other values (101) 118
47.0%
2024-05-11T15:15:52.205506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
205
 
15.0%
서 96
 
7.0%
대 50
 
3.7%
문 49
 
3.6%
울 47
 
3.4%
동 47
 
3.4%
( 47
 
3.4%
시 47
 
3.4%
별 46
 
3.4%
구 46
 
3.4%
Other values (97) 687
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 845
61.8%
Space Separator 205
 
15.0%
Decimal Number 180
 
13.2%
Open Punctuation 47
 
3.4%
Close Punctuation 46
 
3.4%
Other Punctuation 26
 
1.9%
Dash Punctuation 11
 
0.8%
Uppercase Letter 5
 
0.4%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 96
 
11.4%
대 50
 
5.9%
문 49
 
5.8%
울 47
 
5.6%
동 47
 
5.6%
시 47
 
5.6%
별 46
 
5.4%
구 46
 
5.4%
특 46
 
5.4%
로 39
 
4.6%
Other values (78) 332
39.3%
Decimal Number
ValueCountFrequency (%)
1 39
21.7%
2 30
16.7%
3 27
15.0%
4 25
13.9%
5 15
 
8.3%
6 13
 
7.2%
7 13
 
7.2%
0 9
 
5.0%
8 5
 
2.8%
9 4
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
S 1
 
20.0%
K 1
 
20.0%
Space Separator
ValueCountFrequency (%)
205
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 845
61.8%
Common 517
37.8%
Latin 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 96
 
11.4%
대 50
 
5.9%
문 49
 
5.8%
울 47
 
5.6%
동 47
 
5.6%
시 47
 
5.6%
별 46
 
5.4%
구 46
 
5.4%
특 46
 
5.4%
로 39
 
4.6%
Other values (78) 332
39.3%
Common
ValueCountFrequency (%)
205
39.7%
( 47
 
9.1%
) 46
 
8.9%
1 39
 
7.5%
2 30
 
5.8%
3 27
 
5.2%
, 26
 
5.0%
4 25
 
4.8%
5 15
 
2.9%
6 13
 
2.5%
Other values (6) 44
 
8.5%
Latin
ValueCountFrequency (%)
B 3
60.0%
S 1
 
20.0%
K 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 845
61.8%
ASCII 522
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
205
39.3%
( 47
 
9.0%
) 46
 
8.8%
1 39
 
7.5%
2 30
 
5.7%
3 27
 
5.2%
, 26
 
5.0%
4 25
 
4.8%
5 15
 
2.9%
6 13
 
2.5%
Other values (9) 49
 
9.4%
Hangul
ValueCountFrequency (%)
서 96
 
11.4%
대 50
 
5.9%
문 49
 
5.8%
울 47
 
5.6%
동 47
 
5.6%
시 47
 
5.6%
별 46
 
5.4%
구 46
 
5.4%
특 46
 
5.4%
로 39
 
4.6%
Other values (78) 332
39.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)79.5%
Missing81
Missing (%)64.8%
Infinite0
Infinite (%)0.0%
Mean3696.6136
Minimum3606
Maximum3791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:15:52.458793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3606
5-th percentile3622.3
Q13633
median3709
Q33736.5
95-th percentile3784.85
Maximum3791
Range185
Interquartile range (IQR)103.5

Descriptive statistics

Standard deviation57.546024
Coefficient of variation (CV)0.015567227
Kurtosis-1.3108228
Mean3696.6136
Median Absolute Deviation (MAD)58
Skewness0.020214831
Sum162651
Variance3311.5449
MonotonicityNot monotonic
2024-05-11T15:15:52.763065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3628 4
 
3.2%
3633 3
 
2.4%
3646 2
 
1.6%
3721 2
 
1.6%
3712 2
 
1.6%
3709 2
 
1.6%
3777 1
 
0.8%
3787 1
 
0.8%
3632 1
 
0.8%
3756 1
 
0.8%
Other values (25) 25
 
20.0%
(Missing) 81
64.8%
ValueCountFrequency (%)
3606 1
 
0.8%
3612 1
 
0.8%
3622 1
 
0.8%
3624 1
 
0.8%
3628 4
3.2%
3632 1
 
0.8%
3633 3
2.4%
3637 1
 
0.8%
3646 2
1.6%
3650 1
 
0.8%
ValueCountFrequency (%)
3791 1
0.8%
3787 1
0.8%
3785 1
0.8%
3784 1
0.8%
3780 1
0.8%
3777 1
0.8%
3766 1
0.8%
3756 1
0.8%
3753 1
0.8%
3749 1
0.8%

사업장명
Text

Distinct118
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:15:53.224013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length4.432
Min length2

Characters and Unicode

Total characters554
Distinct characters162
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)89.6%

Sample

1st row대흥탕
2nd row청온탕
3rd row복수탕
4th row능수탕
5th row옥천탕
ValueCountFrequency (%)
안산탕 3
 
2.3%
송천탕 2
 
1.6%
수성탕 2
 
1.6%
현대탕 2
 
1.6%
홍은탕 2
 
1.6%
제일목욕탕 2
 
1.6%
황실탕 1
 
0.8%
제일대중사우나 1
 
0.8%
연가탕 1
 
0.8%
오성24시사우나 1
 
0.8%
Other values (112) 112
86.8%
2024-05-11T15:15:53.884573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 80
 
14.4%
우 25
 
4.5%
나 21
 
3.8%
사 21
 
3.8%
목 16
 
2.9%
욕 16
 
2.9%
대 16
 
2.9%
수 15
 
2.7%
성 11
 
2.0%
은 9
 
1.6%
Other values (152) 324
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
96.9%
Decimal Number 9
 
1.6%
Space Separator 4
 
0.7%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 80
 
14.9%
우 25
 
4.7%
나 21
 
3.9%
사 21
 
3.9%
목 16
 
3.0%
욕 16
 
3.0%
대 16
 
3.0%
수 15
 
2.8%
성 11
 
2.0%
은 9
 
1.7%
Other values (144) 307
57.2%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
4 3
33.3%
1 1
 
11.1%
5 1
 
11.1%
3 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
96.9%
Common 17
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 80
 
14.9%
우 25
 
4.7%
나 21
 
3.9%
사 21
 
3.9%
목 16
 
3.0%
욕 16
 
3.0%
대 16
 
3.0%
수 15
 
2.8%
성 11
 
2.0%
은 9
 
1.7%
Other values (144) 307
57.2%
Common
ValueCountFrequency (%)
4
23.5%
2 3
17.6%
4 3
17.6%
) 2
11.8%
( 2
11.8%
1 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
96.9%
ASCII 17
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 80
 
14.9%
우 25
 
4.7%
나 21
 
3.9%
사 21
 
3.9%
목 16
 
3.0%
욕 16
 
3.0%
대 16
 
3.0%
수 15
 
2.8%
성 11
 
2.0%
은 9
 
1.7%
Other values (144) 307
57.2%
ASCII
ValueCountFrequency (%)
4
23.5%
2 3
17.6%
4 3
17.6%
) 2
11.8%
( 2
11.8%
1 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

최종수정일자
Date

Distinct89
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1999-04-09 00:00:00
Maximum2024-01-05 14:31:31
2024-05-11T15:15:54.542152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:54.827739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
I
106 
U
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 106
84.8%
U 19
 
15.2%

Length

2024-05-11T15:15:55.079400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:55.294507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 106
84.8%
u 19
 
15.2%

데이터갱신일자
Date

Distinct21
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-01 00:07:00
2024-05-11T15:15:55.496356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:55.717304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공동탕업
106 
공동탕업+찜질시설서비스영업
14 
목욕장업 기타
 
4
찜질시설서비스영업
 
1

Length

Max length14
Median length4
Mean length5.256
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 106
84.8%
공동탕업+찜질시설서비스영업 14
 
11.2%
목욕장업 기타 4
 
3.2%
찜질시설서비스영업 1
 
0.8%

Length

2024-05-11T15:15:55.971118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:56.176486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 106
82.2%
공동탕업+찜질시설서비스영업 14
 
10.9%
목욕장업 4
 
3.1%
기타 4
 
3.1%
찜질시설서비스영업 1
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct96
Distinct (%)89.7%
Missing18
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean194382.18
Minimum191552.61
Maximum197075.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:15:56.523673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191552.61
5-th percentile192039.7
Q1193224.65
median194466.42
Q3195441.22
95-th percentile196490.8
Maximum197075.88
Range5523.2657
Interquartile range (IQR)2216.5735

Descriptive statistics

Standard deviation1437.7282
Coefficient of variation (CV)0.0073963992
Kurtosis-0.96184594
Mean194382.18
Median Absolute Deviation (MAD)974.80447
Skewness-0.19391222
Sum20798893
Variance2067062.4
MonotonicityNot monotonic
2024-05-11T15:15:56.792345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195441.224667242 3
 
2.4%
196395.729633115 2
 
1.6%
192214.50843343 2
 
1.6%
191552.612967645 2
 
1.6%
194871.776999811 2
 
1.6%
195133.483709943 2
 
1.6%
193762.64108662 2
 
1.6%
195055.550568823 2
 
1.6%
194466.420198929 2
 
1.6%
191836.275479334 2
 
1.6%
Other values (86) 86
68.8%
(Missing) 18
 
14.4%
ValueCountFrequency (%)
191552.612967645 2
1.6%
191836.275479334 2
1.6%
192000.945942229 1
0.8%
192008.587379083 1
0.8%
192112.287100613 1
0.8%
192214.50843343 2
1.6%
192220.269674735 1
0.8%
192333.122015203 1
0.8%
192358.298872317 1
0.8%
192364.592285441 1
0.8%
ValueCountFrequency (%)
197075.878707576 1
0.8%
196945.454641052 1
0.8%
196820.124190281 1
0.8%
196631.136806992 1
0.8%
196517.174899788 1
0.8%
196495.065321462 1
0.8%
196480.858573948 1
0.8%
196395.729633115 2
1.6%
196345.578316587 1
0.8%
196328.539699705 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct96
Distinct (%)89.7%
Missing18
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean452482.15
Minimum450450.02
Maximum455378.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:15:57.097864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450450.02
5-th percentile450556.99
Q1451291.99
median452481.35
Q3453602.5
95-th percentile454538.15
Maximum455378.25
Range4928.2271
Interquartile range (IQR)2310.5164

Descriptive statistics

Standard deviation1334.7744
Coefficient of variation (CV)0.0029498942
Kurtosis-1.0497153
Mean452482.15
Median Absolute Deviation (MAD)1121.1536
Skewness0.1047495
Sum48415590
Variance1781622.8
MonotonicityNot monotonic
2024-05-11T15:15:57.392197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453602.502032778 3
 
2.4%
450722.953691199 2
 
1.6%
452192.485035958 2
 
1.6%
452591.427943603 2
 
1.6%
454233.675366061 2
 
1.6%
451997.349100221 2
 
1.6%
451445.274814853 2
 
1.6%
454355.62123459 2
 
1.6%
450555.963250898 2
 
1.6%
452295.332828958 2
 
1.6%
Other values (86) 86
68.8%
(Missing) 18
 
14.4%
ValueCountFrequency (%)
450450.019449555 1
0.8%
450450.682916715 1
0.8%
450504.59151374 1
0.8%
450512.155519127 1
0.8%
450555.963250898 2
1.6%
450559.384864063 1
0.8%
450596.325543619 1
0.8%
450597.757522205 1
0.8%
450651.820958883 1
0.8%
450660.447504718 1
0.8%
ValueCountFrequency (%)
455378.246569486 1
0.8%
455201.994071747 1
0.8%
454959.600760468 1
0.8%
454786.019433577 1
0.8%
454649.074711917 1
0.8%
454566.233259377 1
0.8%
454472.630937817 1
0.8%
454455.929009429 1
0.8%
454369.670464217 1
0.8%
454355.62123459 2
1.6%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공동탕업
102 
공동탕업+찜질시설서비스영업
13 
<NA>
 
6
목욕장업 기타
 
3
찜질시설서비스영업
 
1

Length

Max length14
Median length4
Mean length5.152
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 102
81.6%
공동탕업+찜질시설서비스영업 13
 
10.4%
<NA> 6
 
4.8%
목욕장업 기타 3
 
2.4%
찜질시설서비스영업 1
 
0.8%

Length

2024-05-11T15:15:57.846468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:58.062596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 102
79.7%
공동탕업+찜질시설서비스영업 13
 
10.2%
na 6
 
4.7%
목욕장업 3
 
2.3%
기타 3
 
2.3%
찜질시설서비스영업 1
 
0.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)10.7%
Missing50
Missing (%)40.0%
Infinite0
Infinite (%)0.0%
Mean0.78666667
Minimum0
Maximum16
Zeros66
Zeros (%)52.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:15:58.297391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6726509
Coefficient of variation (CV)3.3974376
Kurtosis19.395297
Mean0.78666667
Median Absolute Deviation (MAD)0
Skewness4.2318482
Sum59
Variance7.1430631
MonotonicityNot monotonic
2024-05-11T15:15:58.562182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 66
52.8%
5 3
 
2.4%
7 1
 
0.8%
16 1
 
0.8%
4 1
 
0.8%
3 1
 
0.8%
13 1
 
0.8%
1 1
 
0.8%
(Missing) 50
40.0%
ValueCountFrequency (%)
0 66
52.8%
1 1
 
0.8%
3 1
 
0.8%
4 1
 
0.8%
5 3
 
2.4%
7 1
 
0.8%
13 1
 
0.8%
16 1
 
0.8%
ValueCountFrequency (%)
16 1
 
0.8%
13 1
 
0.8%
7 1
 
0.8%
5 3
 
2.4%
4 1
 
0.8%
3 1
 
0.8%
1 1
 
0.8%
0 66
52.8%

건물지하층수
Categorical

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
67 
<NA>
50 
1
 
4
3
 
2
5
 
1

Length

Max length4
Median length1
Mean length2.2
Min length1

Unique

Unique2 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 67
53.6%
<NA> 50
40.0%
1 4
 
3.2%
3 2
 
1.6%
5 1
 
0.8%
2 1
 
0.8%

Length

2024-05-11T15:15:58.828645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:59.066094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
53.6%
na 50
40.0%
1 4
 
3.2%
3 2
 
1.6%
5 1
 
0.8%
2 1
 
0.8%

사용시작지상층
Categorical

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
49 
<NA>
49 
1
21 
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length2.176
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 49
39.2%
<NA> 49
39.2%
1 21
16.8%
2 3
 
2.4%
3 2
 
1.6%
4 1
 
0.8%

Length

2024-05-11T15:15:59.306823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:59.531385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 49
39.2%
na 49
39.2%
1 21
16.8%
2 3
 
2.4%
3 2
 
1.6%
4 1
 
0.8%

사용끝지상층
Categorical

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
88 
1
12 
0
11 
2
 
6
3
 
5

Length

Max length4
Median length4
Mean length3.112
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 88
70.4%
1 12
 
9.6%
0 11
 
8.8%
2 6
 
4.8%
3 5
 
4.0%
4 3
 
2.4%

Length

2024-05-11T15:15:59.751085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:59.993520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
70.4%
1 12
 
9.6%
0 11
 
8.8%
2 6
 
4.8%
3 5
 
4.0%
4 3
 
2.4%

사용시작지하층
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
58 
<NA>
50 
1
16 
2
 
1

Length

Max length4
Median length1
Mean length2.2
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 58
46.4%
<NA> 50
40.0%
1 16
 
12.8%
2 1
 
0.8%

Length

2024-05-11T15:16:00.268659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:00.488279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 58
46.4%
na 50
40.0%
1 16
 
12.8%
2 1
 
0.8%

사용끝지하층
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
89 
0
19 
1
11 
2
 
6

Length

Max length4
Median length4
Mean length3.136
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
71.2%
0 19
 
15.2%
1 11
 
8.8%
2 6
 
4.8%

Length

2024-05-11T15:16:00.744987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:00.974706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
71.2%
0 19
 
15.2%
1 11
 
8.8%
2 6
 
4.8%

한실수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
75 
<NA>
50 

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 75
60.0%
<NA> 50
40.0%

Length

2024-05-11T15:16:01.191873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:01.432006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 75
60.0%
na 50
40.0%

양실수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
75 
<NA>
50 

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 75
60.0%
<NA> 50
40.0%

Length

2024-05-11T15:16:01.666644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:01.859752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 75
60.0%
na 50
40.0%

욕실수
Categorical

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
68 
<NA>
47 
2
7 
1
 
1
11
 
1

Length

Max length4
Median length1
Mean length2.136
Min length1

Unique

Unique3 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
54.4%
<NA> 47
37.6%
2 7
 
5.6%
1 1
 
0.8%
11 1
 
0.8%
5 1
 
0.8%

Length

2024-05-11T15:16:02.066017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:02.348579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
54.4%
na 47
37.6%
2 7
 
5.6%
1 1
 
0.8%
11 1
 
0.8%
5 1
 
0.8%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.7%
Missing6
Missing (%)4.8%
Memory size382.0 B
False
114 
True
 
5
(Missing)
 
6
ValueCountFrequency (%)
False 114
91.2%
True 5
 
4.0%
(Missing) 6
 
4.8%
2024-05-11T15:16:02.558614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
75 
<NA>
50 

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 75
60.0%
<NA> 50
40.0%

Length

2024-05-11T15:16:02.780291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:02.968750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 75
60.0%
na 50
40.0%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
117 
임대
 
7
자가
 
1

Length

Max length4
Median length4
Mean length3.872
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 117
93.6%
임대 7
 
5.6%
자가 1
 
0.8%

Length

2024-05-11T15:16:03.168494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:03.388182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
93.6%
임대 7
 
5.6%
자가 1
 
0.8%

세탁기수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
89 
0
36 

Length

Max length4
Median length4
Mean length3.136
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
71.2%
0 36
28.8%

Length

2024-05-11T15:16:03.571807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:03.738668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
71.2%
0 36
28.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
121 
0
 
4

Length

Max length4
Median length4
Mean length3.904
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> 121
96.8%
0 4
 
3.2%

Length

2024-05-11T15:16:03.926320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:04.119781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
96.8%
0 4
 
3.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
121 
0
 
4

Length

Max length4
Median length4
Mean length3.904
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> 121
96.8%
0 4
 
3.2%

Length

2024-05-11T15:16:04.295724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:04.591896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
96.8%
0 4
 
3.2%

회수건조수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
93 
0
32 

Length

Max length4
Median length4
Mean length3.232
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 93
74.4%
0 32
 
25.6%

Length

2024-05-11T15:16:04.883054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:05.080472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 93
74.4%
0 32
 
25.6%

침대수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
93 
0
32 

Length

Max length4
Median length4
Mean length3.232
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 93
74.4%
0 32
 
25.6%

Length

2024-05-11T15:16:05.288589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:16:05.528807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 93
74.4%
0 32
 
25.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing6
Missing (%)4.8%
Memory size382.0 B
False
119 
(Missing)
 
6
ValueCountFrequency (%)
False 119
95.2%
(Missing) 6
 
4.8%
2024-05-11T15:16:05.685996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031200003120000-202-1962-0125119620514<NA>3폐업2폐업19970220<NA><NA><NA>02 7381407106.38120857서울특별시 서대문구 홍제동 266-21번지<NA><NA>대흥탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업195209.276137454369.670464공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131200003120000-202-1963-0012919630620<NA>3폐업2폐업19981113<NA><NA><NA>02 7469518185.03120856서울특별시 서대문구 홍제동 174-18번지<NA><NA>청온탕2002-10-22 00:00:00I2018-08-31 23:59:59.0공동탕업195140.615102453964.86414공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231200003120000-202-1963-0126019630625<NA>3폐업2폐업20000928<NA><NA><NA>0203621123128.90120819서울특별시 서대문구 북아현동 147-1번지<NA><NA>복수탕2000-09-28 00:00:00I2018-08-31 23:59:59.0공동탕업196034.099631450786.760333공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331200003120000-202-1964-0125219641214<NA>3폐업2폐업20191105<NA><NA><NA><NA>153.25120865서울특별시 서대문구 북아현동 1-149번지서울특별시 서대문구 북아현로14길 27 (북아현동)3749능수탕2019-11-05 09:38:23U2019-11-07 02:40:00.0공동탕업196131.37705451207.356577공동탕업001100000N0<NA><NA><NA><NA>0<NA><NA>00N
431200003120000-202-1965-0126219651008<NA>3폐업2폐업19941104<NA><NA><NA>0203921724179.57120060서울특별시 서대문구 옥천동 3-0번지<NA><NA>옥천탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업196631.136807451902.950417공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531200003120000-202-1968-0009619680831<NA>3폐업2폐업20091231<NA><NA><NA>0203727167166.21120801서울특별시 서대문구 남가좌동 76-32번지<NA><NA>명지탕2003-04-09 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
631200003120000-202-1969-0012219691223<NA>3폐업2폐업20100824<NA><NA><NA>02 3621621147.44120821서울특별시 서대문구 북아현동 158-1번지<NA><NA>원일2006-05-08 00:00:00I2018-08-31 23:59:59.0공동탕업195854.931381450651.820959공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731200003120000-202-1969-0012319690211<NA>3폐업2폐업20131220<NA><NA><NA>000203955762137.33120859서울특별시 서대문구 홍제동 332-12번지서울특별시 서대문구 통일로39길 22-43 (홍제동)3637수향목욕장2013-11-27 16:05:32I2018-08-31 23:59:59.0공동탕업194830.233641454071.145606공동탕업001200000N0<NA><NA><NA><NA>0<NA><NA>00N
831200003120000-202-1969-0012419690726<NA>3폐업2폐업20111103<NA><NA><NA>0203658748226.81120821서울특별시 서대문구 북아현동 159-20번지<NA><NA>현대대중목욕탕2003-05-01 00:00:00I2018-08-31 23:59:59.0공동탕업195828.112832450675.687041공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931200003120000-202-1970-0000119700113<NA>3폐업2폐업20011110<NA><NA><NA>02 7373481196.71120855서울특별시 서대문구 홍제동 147-2번지<NA><NA>대륙탕2001-11-12 00:00:00I2018-08-31 23:59:59.0공동탕업195241.347675453729.459095공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
11531200003120000-202-2010-0000120101011<NA>1영업/정상1영업<NA><NA><NA><NA>02 3122521296.69120030서울특별시 서대문구 합동 116 (SK 리쳄블 B101-1,2,3,4서울특별시 서대문구 서소문로 45 (합동,(SK 리쳄블 B101-1,2,3,4)3741미소사우나2022-10-14 11:13:46U2021-10-30 23:06:00.0공동탕업196945.454641451003.162676<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11631200003120000-202-2012-0000120120529<NA>3폐업2폐업20140916<NA><NA><NA><NA>109.92120150서울특별시 서대문구 봉원동 51번지서울특별시 서대문구 봉원사길 75-7 (봉원동)3721온 찜질방2014-05-19 10:27:17I2018-08-31 23:59:59.0찜질시설서비스영업195133.48371451997.3491찜질시설서비스영업101100005Y0<NA><NA><NA>임대0<NA><NA>00N
11731200003120000-202-2013-0000120130902<NA>3폐업2폐업20140731<NA><NA><NA>02 7300277117.36120854서울특별시 서대문구 홍제동 104-20번지서울특별시 서대문구 통일로32길 6 (홍제동)3633안산탕2014-03-19 17:04:55I2018-08-31 23:59:59.0목욕장업 기타195441.224667453602.502033목욕장업 기타0011<NA><NA>002N0<NA><NA><NA><NA>0<NA><NA>00N
11831200003120000-202-2013-0000220131128<NA>1영업/정상1영업<NA><NA><NA><NA>02 3958822343.15120857서울특별시 서대문구 홍제동 266-105서울특별시 서대문구 세무서5길 35 (홍제동)3628유진사우나2022-11-10 15:27:10U2021-10-31 23:02:00.0목욕장업 기타195055.550569454355.621235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11931200003120000-202-2014-0000120140904<NA>1영업/정상1영업<NA><NA><NA><NA>02 7300277231.40120854서울특별시 서대문구 홍제동 104-20서울특별시 서대문구 통일로32길 6, 1층 (홍제동)3633안산탕2020-09-09 13:56:09U2020-09-11 02:40:00.0공동탕업195441.224667453602.502033공동탕업511100002N0<NA><NA><NA>임대0<NA><NA>00N
12031200003120000-202-2015-000012015-02-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 54719001376.30120-836서울특별시 서대문구 창천동 374서울특별시 서대문구 신촌로 1, 지4~5층 (창천동, 쓰리알유시티아파트)3785홍대24시불가마사우나2023-12-22 17:15:55U2022-11-01 22:04:00.0공동탕업+찜질시설서비스영업193526.467942450742.78735<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12131200003120000-202-2016-0000120161229<NA>1영업/정상1영업<NA><NA><NA><NA>02379 6399295.29120857서울특별시 서대문구 홍제동 299-2 효신빌딩 3층서울특별시 서대문구 통일로 472, 효신빌딩 3층 (홍제동)3628스타칼리2022-01-11 09:52:30U2022-01-13 02:40:00.0공동탕업+찜질시설서비스영업194871.777454233.675366공동탕업+찜질시설서비스영업513000000N0<NA><NA><NA><NA>00000N
12231200003120000-202-2018-0000120180329<NA>3폐업2폐업20200903<NA><NA><NA>02 308 8777504.30120120서울특별시 서대문구 남가좌동 379 지하1,지하2층 래미안남가좌2차아파트서울특별시 서대문구 수색로6길 43, 지하1층,지하2층 (남가좌동, 래미안남가좌2차아파트)3709래미안 휘트니스센터2020-09-03 17:00:08U2020-09-05 02:40:00.0공동탕업192214.508433452192.485036공동탕업000012000N0<NA><NA><NA>임대00000N
12331200003120000-202-2021-0000120210107<NA>1영업/정상1영업<NA><NA><NA><NA><NA>222.85120809서울특별시 서대문구 대현동 104-15 월호텔 지하1,2층서울특별시 서대문구 연세로2길 101-10, 월호텔 지하1,2층 (대현동)3780호텔월 사우나2021-01-07 14:51:21I2021-01-09 00:23:05.0공동탕업194848.133274450596.325544공동탕업<NA><NA><NA><NA>12<NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
12431200003120000-202-2021-0000220210222<NA>1영업/정상1영업<NA><NA><NA><NA>02 308 8777453.79120120서울특별시 서대문구 남가좌동 379 래미안남가좌2차아파트 지하1,2층서울특별시 서대문구 수색로6길 43, 지하1,2층 (남가좌동, 래미안남가좌2차아파트)3791래미안휘트니스센터(주)2021-02-22 10:37:13I2021-02-24 00:23:01.0공동탕업192214.508433452192.485036공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N