Overview

Dataset statistics

Number of variables47
Number of observations158
Missing cells1145
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.3 KiB
Average record size in memory403.8 B

Variable types

Categorical26
Text8
DateTime3
Unsupported4
Numeric4
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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-19955/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (50.7%)Imbalance
영업상태명 is highly imbalanced (50.7%)Imbalance
상세영업상태코드 is highly imbalanced (50.7%)Imbalance
상세영업상태명 is highly imbalanced (50.7%)Imbalance
데이터갱신구분 is highly imbalanced (50.7%)Imbalance
데이터갱신일자 is highly imbalanced (77.4%)Imbalance
업태구분명 is highly imbalanced (76.6%)Imbalance
위생업태명 is highly imbalanced (74.1%)Imbalance
사용끝지상층 is highly imbalanced (71.8%)Imbalance
사용끝지하층 is highly imbalanced (61.5%)Imbalance
발한실여부 is highly imbalanced (60.5%)Imbalance
조건부허가시작일자 is highly imbalanced (94.5%)Imbalance
조건부허가종료일자 is highly imbalanced (94.5%)Imbalance
건물소유구분명 is highly imbalanced (72.4%)Imbalance
여성종사자수 is highly imbalanced (73.8%)Imbalance
남성종사자수 is highly imbalanced (73.8%)Imbalance
인허가취소일자 has 158 (100.0%) missing valuesMissing
폐업일자 has 17 (10.8%) missing valuesMissing
휴업시작일자 has 158 (100.0%) missing valuesMissing
휴업종료일자 has 158 (100.0%) missing valuesMissing
재개업일자 has 158 (100.0%) missing valuesMissing
전화번호 has 6 (3.8%) missing valuesMissing
도로명주소 has 119 (75.3%) missing valuesMissing
도로명우편번호 has 120 (75.9%) missing valuesMissing
좌표정보(X) has 18 (11.4%) missing valuesMissing
좌표정보(Y) has 18 (11.4%) missing valuesMissing
건물지상층수 has 50 (31.6%) missing valuesMissing
발한실여부 has 4 (2.5%) missing valuesMissing
조건부허가신고사유 has 157 (99.4%) missing valuesMissing
다중이용업소여부 has 4 (2.5%) 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
건물지상층수 has 96 (60.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:59:48.985235
Analysis finished2024-05-11 05:59:50.285850
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3030000
158 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 158
100.0%

Length

2024-05-11T05:59:50.487973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:51.079846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 158
100.0%

관리번호
Text

UNIQUE 

Distinct158
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T05:59:51.494111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3476
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

Unique158 ?
Unique (%)100.0%

Sample

1st row3030000-202-1960-00248
2nd row3030000-202-1960-00255
3rd row3030000-202-1960-00273
4th row3030000-202-1960-00276
5th row3030000-202-1965-00263
ValueCountFrequency (%)
3030000-202-1960-00248 1
 
0.6%
3030000-202-2001-00337 1
 
0.6%
3030000-202-2001-00339 1
 
0.6%
3030000-202-2000-00337 1
 
0.6%
3030000-202-2001-00332 1
 
0.6%
3030000-202-2001-00333 1
 
0.6%
3030000-202-2001-00334 1
 
0.6%
3030000-202-2001-00335 1
 
0.6%
3030000-202-2001-00336 1
 
0.6%
3030000-202-2000-00335 1
 
0.6%
Other values (148) 148
93.7%
2024-05-11T05:59:52.356167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1498
43.1%
2 494
 
14.2%
- 474
 
13.6%
3 431
 
12.4%
1 169
 
4.9%
9 144
 
4.1%
8 72
 
2.1%
4 52
 
1.5%
7 52
 
1.5%
6 47
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3002
86.4%
Dash Punctuation 474
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1498
49.9%
2 494
 
16.5%
3 431
 
14.4%
1 169
 
5.6%
9 144
 
4.8%
8 72
 
2.4%
4 52
 
1.7%
7 52
 
1.7%
6 47
 
1.6%
5 43
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1498
43.1%
2 494
 
14.2%
- 474
 
13.6%
3 431
 
12.4%
1 169
 
4.9%
9 144
 
4.1%
8 72
 
2.1%
4 52
 
1.5%
7 52
 
1.5%
6 47
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1498
43.1%
2 494
 
14.2%
- 474
 
13.6%
3 431
 
12.4%
1 169
 
4.9%
9 144
 
4.1%
8 72
 
2.1%
4 52
 
1.5%
7 52
 
1.5%
6 47
 
1.4%

인허가일자
Date

Distinct142
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1960-11-30 00:00:00
Maximum2022-07-07 00:00:00
2024-05-11T05:59:52.957548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:59:53.336678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing158
Missing (%)100.0%
Memory size1.5 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
141 
1
17 

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 (%)
3 141
89.2%
1 17
 
10.8%

Length

2024-05-11T05:59:53.601750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:53.791834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 141
89.2%
1 17
 
10.8%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
141 
영업/정상
17 

Length

Max length5
Median length2
Mean length2.3227848
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 141
89.2%
영업/정상 17
 
10.8%

Length

2024-05-11T05:59:54.245830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:54.584426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 141
89.2%
영업/정상 17
 
10.8%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
141 
1
17 

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 (%)
2 141
89.2%
1 17
 
10.8%

Length

2024-05-11T05:59:54.923270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:55.248799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 141
89.2%
1 17
 
10.8%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
141 
영업
17 

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 141
89.2%
영업 17
 
10.8%

Length

2024-05-11T05:59:55.597136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:55.914208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 141
89.2%
영업 17
 
10.8%

폐업일자
Date

MISSING 

Distinct124
Distinct (%)87.9%
Missing17
Missing (%)10.8%
Memory size1.4 KiB
Minimum1994-10-01 00:00:00
Maximum2024-03-06 00:00:00
2024-05-11T05:59:56.169867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:59:56.622542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing158
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing158
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing158
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct133
Distinct (%)87.5%
Missing6
Missing (%)3.8%
Memory size1.4 KiB
2024-05-11T05:59:57.131920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6118421
Min length2

Characters and Unicode

Total characters1461
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

Unique119 ?
Unique (%)78.3%

Sample

1st row02 2320702
2nd row02
3rd row0200000000
4th row02 2930377
5th row02 2923860
ValueCountFrequency (%)
02 61
29.6%
0222319821 2
 
1.0%
0222822422 2
 
1.0%
4995852 2
 
1.0%
0222983802 2
 
1.0%
4672458 2
 
1.0%
0222472962 2
 
1.0%
4653365 2
 
1.0%
0200000000 2
 
1.0%
0222983305 2
 
1.0%
Other values (123) 127
61.7%
2024-05-11T05:59:57.982734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 413
28.3%
0 273
18.7%
4 120
 
8.2%
9 117
 
8.0%
6 103
 
7.0%
3 92
 
6.3%
5 82
 
5.6%
1 69
 
4.7%
7 67
 
4.6%
8 65
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1401
95.9%
Space Separator 60
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 413
29.5%
0 273
19.5%
4 120
 
8.6%
9 117
 
8.4%
6 103
 
7.4%
3 92
 
6.6%
5 82
 
5.9%
1 69
 
4.9%
7 67
 
4.8%
8 65
 
4.6%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 413
28.3%
0 273
18.7%
4 120
 
8.2%
9 117
 
8.0%
6 103
 
7.0%
3 92
 
6.3%
5 82
 
5.6%
1 69
 
4.7%
7 67
 
4.6%
8 65
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 413
28.3%
0 273
18.7%
4 120
 
8.2%
9 117
 
8.0%
6 103
 
7.0%
3 92
 
6.3%
5 82
 
5.6%
1 69
 
4.7%
7 67
 
4.6%
8 65
 
4.4%

소재지면적
Text

Distinct124
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T05:59:58.555381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0316456
Min length3

Characters and Unicode

Total characters953
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

Unique103 ?
Unique (%)65.2%

Sample

1st row143.35
2nd row169.15
3rd row197.09
4th row93.17
5th row192.44
ValueCountFrequency (%)
00 7
 
4.4%
199.70 4
 
2.5%
700.00 3
 
1.9%
540.00 3
 
1.9%
569.87 3
 
1.9%
211.20 3
 
1.9%
218.94 3
 
1.9%
379.82 3
 
1.9%
655.88 2
 
1.3%
476.02 2
 
1.3%
Other values (114) 125
79.1%
2024-05-11T05:59:59.427453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 158
16.6%
0 154
16.2%
1 107
11.2%
2 88
9.2%
9 70
7.3%
7 66
6.9%
8 66
6.9%
6 64
6.7%
5 60
 
6.3%
3 58
 
6.1%
Other values (2) 62
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 781
82.0%
Other Punctuation 172
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154
19.7%
1 107
13.7%
2 88
11.3%
9 70
9.0%
7 66
8.5%
8 66
8.5%
6 64
8.2%
5 60
 
7.7%
3 58
 
7.4%
4 48
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 158
91.9%
, 14
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Common 953
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 158
16.6%
0 154
16.2%
1 107
11.2%
2 88
9.2%
9 70
7.3%
7 66
6.9%
8 66
6.9%
6 64
6.7%
5 60
 
6.3%
3 58
 
6.1%
Other values (2) 62
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 158
16.6%
0 154
16.2%
1 107
11.2%
2 88
9.2%
9 70
7.3%
7 66
6.9%
8 66
6.9%
6 64
6.7%
5 60
 
6.3%
3 58
 
6.1%
Other values (2) 62
 
6.5%

소재지우편번호
Text

Distinct63
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T05:59:59.911398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0253165
Min length6

Characters and Unicode

Total characters952
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

Unique22 ?
Unique (%)13.9%

Sample

1st row133801
2nd row133805
3rd row133882
4th row133881
5th row133867
ValueCountFrequency (%)
133851 7
 
4.4%
133850 6
 
3.8%
133812 6
 
3.8%
133882 5
 
3.2%
133809 5
 
3.2%
133858 5
 
3.2%
133804 5
 
3.2%
133815 5
 
3.2%
133868 5
 
3.2%
133808 4
 
2.5%
Other values (53) 105
66.5%
2024-05-11T06:00:00.765267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 339
35.6%
1 198
20.8%
8 174
18.3%
0 52
 
5.5%
2 44
 
4.6%
5 42
 
4.4%
6 32
 
3.4%
4 28
 
2.9%
7 23
 
2.4%
9 16
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 948
99.6%
Dash Punctuation 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 339
35.8%
1 198
20.9%
8 174
18.4%
0 52
 
5.5%
2 44
 
4.6%
5 42
 
4.4%
6 32
 
3.4%
4 28
 
3.0%
7 23
 
2.4%
9 16
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 339
35.6%
1 198
20.8%
8 174
18.3%
0 52
 
5.5%
2 44
 
4.6%
5 42
 
4.4%
6 32
 
3.4%
4 28
 
2.9%
7 23
 
2.4%
9 16
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 339
35.6%
1 198
20.8%
8 174
18.3%
0 52
 
5.5%
2 44
 
4.6%
5 42
 
4.4%
6 32
 
3.4%
4 28
 
2.9%
7 23
 
2.4%
9 16
 
1.7%

지번주소
Text

Distinct130
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T06:00:01.299482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length24.689873
Min length19

Characters and Unicode

Total characters3901
Distinct characters106
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

Unique109 ?
Unique (%)69.0%

Sample

1st row서울특별시 성동구 금호동1가 531-0번지
2nd row서울특별시 성동구 금호동3가 420-0번지
3rd row서울특별시 성동구 도선동 285-1번지
4th row서울특별시 성동구 홍익동 420-0번지
5th row서울특별시 성동구 행당동 292-54번지
ValueCountFrequency (%)
서울특별시 158
23.6%
성동구 158
23.6%
행당동 20
 
3.0%
용답동 20
 
3.0%
성수동1가 19
 
2.8%
성수동2가 16
 
2.4%
마장동 16
 
2.4%
하왕십리동 14
 
2.1%
금호동4가 9
 
1.3%
옥수동 8
 
1.2%
Other values (163) 232
34.6%
2024-05-11T06:00:01.997093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
664
17.0%
동 318
 
8.2%
성 196
 
5.0%
시 161
 
4.1%
서 160
 
4.1%
울 160
 
4.1%
특 159
 
4.1%
별 159
 
4.1%
구 158
 
4.1%
지 158
 
4.1%
Other values (96) 1608
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2281
58.5%
Decimal Number 787
 
20.2%
Space Separator 664
 
17.0%
Dash Punctuation 143
 
3.7%
Other Punctuation 16
 
0.4%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Math Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 318
13.9%
성 196
 
8.6%
시 161
 
7.1%
서 160
 
7.0%
울 160
 
7.0%
특 159
 
7.0%
별 159
 
7.0%
구 158
 
6.9%
지 158
 
6.9%
번 144
 
6.3%
Other values (77) 508
22.3%
Decimal Number
ValueCountFrequency (%)
1 158
20.1%
2 132
16.8%
6 81
10.3%
3 76
9.7%
5 72
9.1%
0 63
 
8.0%
8 63
 
8.0%
4 57
 
7.2%
9 48
 
6.1%
7 37
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 14
87.5%
: 2
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2281
58.5%
Common 1618
41.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 318
13.9%
성 196
 
8.6%
시 161
 
7.1%
서 160
 
7.0%
울 160
 
7.0%
특 159
 
7.0%
별 159
 
7.0%
구 158
 
6.9%
지 158
 
6.9%
번 144
 
6.3%
Other values (77) 508
22.3%
Common
ValueCountFrequency (%)
664
41.0%
1 158
 
9.8%
- 143
 
8.8%
2 132
 
8.2%
6 81
 
5.0%
3 76
 
4.7%
5 72
 
4.4%
0 63
 
3.9%
8 63
 
3.9%
4 57
 
3.5%
Other values (7) 109
 
6.7%
Latin
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2281
58.5%
ASCII 1620
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
664
41.0%
1 158
 
9.8%
- 143
 
8.8%
2 132
 
8.1%
6 81
 
5.0%
3 76
 
4.7%
5 72
 
4.4%
0 63
 
3.9%
8 63
 
3.9%
4 57
 
3.5%
Other values (9) 111
 
6.9%
Hangul
ValueCountFrequency (%)
동 318
13.9%
성 196
 
8.6%
시 161
 
7.1%
서 160
 
7.0%
울 160
 
7.0%
특 159
 
7.0%
별 159
 
7.0%
구 158
 
6.9%
지 158
 
6.9%
번 144
 
6.3%
Other values (77) 508
22.3%

도로명주소
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing119
Missing (%)75.3%
Memory size1.4 KiB
2024-05-11T06:00:02.506551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length37
Mean length31.487179
Min length23

Characters and Unicode

Total characters1228
Distinct characters104
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

Unique39 ?
Unique (%)100.0%

Sample

1st row서울특별시 성동구 장터길 21 (금호동3가)
2nd row서울특별시 성동구 성덕정19길 11 (성수동2가)
3rd row서울특별시 성동구 독서당로 280-5, 616호 (금호동4가)
4th row서울특별시 성동구 성덕정길 63-39 (성수동1가)
5th row서울특별시 성동구 무학봉길 57 (하왕십리동)
ValueCountFrequency (%)
서울특별시 39
 
17.6%
성동구 39
 
17.6%
독서당로 7
 
3.2%
하왕십리동 6
 
2.7%
지하1층 6
 
2.7%
성수동1가 4
 
1.8%
왕십리로 4
 
1.8%
성수동2가 4
 
1.8%
행당동 3
 
1.4%
금호동4가 3
 
1.4%
Other values (94) 107
48.2%
2024-05-11T06:00:03.488491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
183
 
14.9%
동 82
 
6.7%
성 55
 
4.5%
서 48
 
3.9%
1 48
 
3.9%
) 42
 
3.4%
( 42
 
3.4%
시 41
 
3.3%
울 41
 
3.3%
특 39
 
3.2%
Other values (94) 607
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 759
61.8%
Space Separator 183
 
14.9%
Decimal Number 172
 
14.0%
Close Punctuation 42
 
3.4%
Open Punctuation 42
 
3.4%
Other Punctuation 25
 
2.0%
Dash Punctuation 3
 
0.2%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 82
 
10.8%
성 55
 
7.2%
서 48
 
6.3%
시 41
 
5.4%
울 41
 
5.4%
특 39
 
5.1%
구 39
 
5.1%
별 39
 
5.1%
로 29
 
3.8%
길 20
 
2.6%
Other values (77) 326
43.0%
Decimal Number
ValueCountFrequency (%)
1 48
27.9%
3 21
12.2%
2 20
11.6%
6 18
 
10.5%
8 15
 
8.7%
5 12
 
7.0%
4 12
 
7.0%
0 12
 
7.0%
7 10
 
5.8%
9 4
 
2.3%
Space Separator
ValueCountFrequency (%)
183
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 759
61.8%
Common 468
38.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 82
 
10.8%
성 55
 
7.2%
서 48
 
6.3%
시 41
 
5.4%
울 41
 
5.4%
특 39
 
5.1%
구 39
 
5.1%
별 39
 
5.1%
로 29
 
3.8%
길 20
 
2.6%
Other values (77) 326
43.0%
Common
ValueCountFrequency (%)
183
39.1%
1 48
 
10.3%
) 42
 
9.0%
( 42
 
9.0%
, 25
 
5.3%
3 21
 
4.5%
2 20
 
4.3%
6 18
 
3.8%
8 15
 
3.2%
5 12
 
2.6%
Other values (6) 42
 
9.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 759
61.8%
ASCII 469
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
183
39.0%
1 48
 
10.2%
) 42
 
9.0%
( 42
 
9.0%
, 25
 
5.3%
3 21
 
4.5%
2 20
 
4.3%
6 18
 
3.8%
8 15
 
3.2%
5 12
 
2.6%
Other values (7) 43
 
9.2%
Hangul
ValueCountFrequency (%)
동 82
 
10.8%
성 55
 
7.2%
서 48
 
6.3%
시 41
 
5.4%
울 41
 
5.4%
특 39
 
5.1%
구 39
 
5.1%
별 39
 
5.1%
로 29
 
3.8%
길 20
 
2.6%
Other values (77) 326
43.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)81.6%
Missing120
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean4746.8684
Minimum4701
Maximum4808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T06:00:03.742598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4701
5-th percentile4701
Q14716.5
median4740.5
Q34775
95-th percentile4805.15
Maximum4808
Range107
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation34.559132
Coefficient of variation (CV)0.0072804065
Kurtosis-1.1212787
Mean4746.8684
Median Absolute Deviation (MAD)30.5
Skewness0.36755731
Sum180381
Variance1194.3336
MonotonicityNot monotonic
2024-05-11T06:00:04.084002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4710 3
 
1.9%
4701 3
 
1.9%
4737 2
 
1.3%
4775 2
 
1.3%
4750 2
 
1.3%
4768 1
 
0.6%
4745 1
 
0.6%
4736 1
 
0.6%
4799 1
 
0.6%
4734 1
 
0.6%
Other values (21) 21
 
13.3%
(Missing) 120
75.9%
ValueCountFrequency (%)
4701 3
1.9%
4704 1
 
0.6%
4708 1
 
0.6%
4709 1
 
0.6%
4710 3
1.9%
4716 1
 
0.6%
4718 1
 
0.6%
4720 1
 
0.6%
4724 1
 
0.6%
4728 1
 
0.6%
ValueCountFrequency (%)
4808 1
0.6%
4806 1
0.6%
4805 1
0.6%
4800 1
0.6%
4799 1
0.6%
4797 1
0.6%
4791 1
0.6%
4782 1
0.6%
4776 1
0.6%
4775 2
1.3%

사업장명
Text

Distinct135
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T06:00:04.555854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length4.835443
Min length2

Characters and Unicode

Total characters764
Distinct characters162
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)74.1%

Sample

1st row금호탕
2nd row옥천목욕탕
3rd row무학탕
4th row시온탕
5th row은하수탕
ValueCountFrequency (%)
유성탕 5
 
3.0%
온천탕 3
 
1.8%
남광탕 3
 
1.8%
목욕탕 3
 
1.8%
금강탕 2
 
1.2%
삼오탕 2
 
1.2%
성동한증원 2
 
1.2%
옥수탕 2
 
1.2%
대성탕 2
 
1.2%
성수대중탕 2
 
1.2%
Other values (130) 139
84.2%
2024-05-11T06:00:05.457130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 114
 
14.9%
대 34
 
4.5%
욕 27
 
3.5%
목 27
 
3.5%
우 26
 
3.4%
성 25
 
3.3%
사 25
 
3.3%
수 23
 
3.0%
중 22
 
2.9%
나 22
 
2.9%
Other values (152) 419
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 741
97.0%
Decimal Number 8
 
1.0%
Space Separator 7
 
0.9%
Close Punctuation 3
 
0.4%
Other Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 114
 
15.4%
대 34
 
4.6%
욕 27
 
3.6%
목 27
 
3.6%
우 26
 
3.5%
성 25
 
3.4%
사 25
 
3.4%
수 23
 
3.1%
중 22
 
3.0%
나 22
 
3.0%
Other values (140) 396
53.4%
Decimal Number
ValueCountFrequency (%)
2 2
25.0%
3 1
12.5%
6 1
12.5%
1 1
12.5%
8 1
12.5%
9 1
12.5%
4 1
12.5%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 741
97.0%
Common 22
 
2.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 114
 
15.4%
대 34
 
4.6%
욕 27
 
3.6%
목 27
 
3.6%
우 26
 
3.5%
성 25
 
3.4%
사 25
 
3.4%
수 23
 
3.1%
중 22
 
3.0%
나 22
 
3.0%
Other values (140) 396
53.4%
Common
ValueCountFrequency (%)
7
31.8%
) 3
13.6%
. 2
 
9.1%
( 2
 
9.1%
2 2
 
9.1%
3 1
 
4.5%
6 1
 
4.5%
1 1
 
4.5%
8 1
 
4.5%
9 1
 
4.5%
Latin
ValueCountFrequency (%)
H 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 741
97.0%
ASCII 23
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 114
 
15.4%
대 34
 
4.6%
욕 27
 
3.6%
목 27
 
3.6%
우 26
 
3.5%
성 25
 
3.4%
사 25
 
3.4%
수 23
 
3.1%
중 22
 
3.0%
나 22
 
3.0%
Other values (140) 396
53.4%
ASCII
ValueCountFrequency (%)
7
30.4%
) 3
13.0%
. 2
 
8.7%
( 2
 
8.7%
2 2
 
8.7%
H 1
 
4.3%
3 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%
8 1
 
4.3%
Other values (2) 2
 
8.7%

최종수정일자
Date

Distinct104
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1999-02-02 00:00:00
Maximum2024-03-06 13:52:59
2024-05-11T06:00:05.852274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:00:06.207001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
141 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 141
89.2%
U 17
 
10.8%

Length

2024-05-11T06:00:06.631593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:06.911262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 141
89.2%
u 17
 
10.8%

데이터갱신일자
Categorical

IMBALANCE 

Distinct16
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2018-08-31 23:59:59.0
141 
2020-03-18 02:40:00.0
 
3
2021-09-04 02:40:00.0
 
1
2023-12-01 00:07:00.0
 
1
2022-12-01 23:07:00.0
 
1
Other values (11)
 
11

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique14 ?
Unique (%)8.9%

Sample

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

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 141
89.2%
2020-03-18 02:40:00.0 3
 
1.9%
2021-09-04 02:40:00.0 1
 
0.6%
2023-12-01 00:07:00.0 1
 
0.6%
2022-12-01 23:07:00.0 1
 
0.6%
2020-07-31 02:40:00.0 1
 
0.6%
2023-12-03 00:08:00.0 1
 
0.6%
2021-12-16 02:40:00.0 1
 
0.6%
2021-10-27 02:40:00.0 1
 
0.6%
2021-10-15 02:40:00.0 1
 
0.6%
Other values (6) 6
 
3.8%

Length

2024-05-11T06:00:07.109776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 141
44.6%
23:59:59.0 141
44.6%
02:40:00.0 13
 
4.1%
2020-03-18 3
 
0.9%
2021-10-27 1
 
0.3%
2022-12-04 1
 
0.3%
2020-11-27 1
 
0.3%
2021-06-26 1
 
0.3%
2021-11-20 1
 
0.3%
2020-09-12 1
 
0.3%
Other values (12) 12
 
3.8%

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
공동탕업
147 
한증막업
 
5
목욕장업 기타
 
4
공동탕업+찜질시설서비스영업
 
2

Length

Max length14
Median length4
Mean length4.2025316
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 147
93.0%
한증막업 5
 
3.2%
목욕장업 기타 4
 
2.5%
공동탕업+찜질시설서비스영업 2
 
1.3%

Length

2024-05-11T06:00:07.365924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:07.577579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 147
90.7%
한증막업 5
 
3.1%
목욕장업 4
 
2.5%
기타 4
 
2.5%
공동탕업+찜질시설서비스영업 2
 
1.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)71.4%
Missing18
Missing (%)11.4%
Infinite0
Infinite (%)0.0%
Mean203516.33
Minimum200967.54
Maximum206209.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T06:00:07.815441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200967.54
5-th percentile201668.79
Q1202375.41
median203350.73
Q3204615.31
95-th percentile205784.87
Maximum206209.28
Range5241.7438
Interquartile range (IQR)2239.9054

Descriptive statistics

Standard deviation1318.1247
Coefficient of variation (CV)0.0064767516
Kurtosis-0.86258888
Mean203516.33
Median Absolute Deviation (MAD)990.72334
Skewness0.23370301
Sum28492287
Variance1737452.8
MonotonicityNot monotonic
2024-05-11T06:00:08.237628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203946.402057096 4
 
2.5%
202202.550291784 4
 
2.5%
206033.909589487 4
 
2.5%
203910.819069149 3
 
1.9%
204120.878013768 3
 
1.9%
202954.660600194 3
 
1.9%
203970.690429198 3
 
1.9%
202371.997992402 3
 
1.9%
205784.868811814 3
 
1.9%
204934.319835624 3
 
1.9%
Other values (90) 107
67.7%
(Missing) 18
 
11.4%
ValueCountFrequency (%)
200967.537033206 1
0.6%
200992.431390651 1
0.6%
201070.376244 1
0.6%
201176.434918 1
0.6%
201462.251313062 1
0.6%
201540.816056093 1
0.6%
201649.612936525 1
0.6%
201669.803556903 2
1.3%
201742.272982354 1
0.6%
201766.681912935 1
0.6%
ValueCountFrequency (%)
206209.280864162 1
 
0.6%
206033.909589487 4
2.5%
205921.703469803 1
 
0.6%
205784.868811814 3
1.9%
205753.250469411 2
1.3%
205722.425433401 1
 
0.6%
205701.564885453 1
 
0.6%
205658.359614296 1
 
0.6%
205543.417245819 1
 
0.6%
205349.235501036 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)71.4%
Missing18
Missing (%)11.4%
Infinite0
Infinite (%)0.0%
Mean450345.29
Minimum448258.52
Maximum452041.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T06:00:08.503986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448258.52
5-th percentile448481.46
Q1449490.99
median450658.82
Q3451238.61
95-th percentile451921.93
Maximum452041.56
Range3783.0433
Interquartile range (IQR)1747.6226

Descriptive statistics

Standard deviation1062.0486
Coefficient of variation (CV)0.0023582985
Kurtosis-1.1722392
Mean450345.29
Median Absolute Deviation (MAD)948.02285
Skewness-0.23094944
Sum63048341
Variance1127947.3
MonotonicityNot monotonic
2024-05-11T06:00:08.822300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449240.375683662 4
 
2.5%
449620.09101942 4
 
2.5%
450882.776032621 4
 
2.5%
448979.260262165 3
 
1.9%
449576.874617144 3
 
1.9%
451925.163200505 3
 
1.9%
451606.839801414 3
 
1.9%
451423.409695956 3
 
1.9%
450883.524006222 3
 
1.9%
451032.958798449 3
 
1.9%
Other values (90) 107
67.7%
(Missing) 18
 
11.4%
ValueCountFrequency (%)
448258.515774754 1
0.6%
448266.234571726 1
0.6%
448361.103638303 2
1.3%
448371.9861317 1
0.6%
448399.948660115 1
0.6%
448458.156755337 1
0.6%
448482.688533222 1
0.6%
448496.064438128 1
0.6%
448709.190492902 1
0.6%
448735.491625585 1
0.6%
ValueCountFrequency (%)
452041.559037331 1
 
0.6%
452014.305822436 2
1.3%
451970.379979961 1
 
0.6%
451925.163200505 3
1.9%
451921.755683909 1
 
0.6%
451908.86237999 1
 
0.6%
451687.890552805 2
1.3%
451681.921847476 2
1.3%
451627.794307125 1
 
0.6%
451606.839801414 3
1.9%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
공동탕업
144 
한증막업
 
5
<NA>
 
4
목욕장업 기타
 
3
공동탕업+찜질시설서비스영업
 
2

Length

Max length14
Median length4
Mean length4.1835443
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 144
91.1%
한증막업 5
 
3.2%
<NA> 4
 
2.5%
목욕장업 기타 3
 
1.9%
공동탕업+찜질시설서비스영업 2
 
1.3%

Length

2024-05-11T06:00:09.090076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:09.300802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 144
89.4%
한증막업 5
 
3.1%
na 4
 
2.5%
목욕장업 3
 
1.9%
기타 3
 
1.9%
공동탕업+찜질시설서비스영업 2
 
1.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)10.2%
Missing50
Missing (%)31.6%
Infinite0
Infinite (%)0.0%
Mean1.1296296
Minimum0
Maximum25
Zeros96
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T06:00:09.511929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8.65
Maximum25
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.7568445
Coefficient of variation (CV)3.3257312
Kurtosis19.259933
Mean1.1296296
Median Absolute Deviation (MAD)0
Skewness4.1218664
Sum122
Variance14.11388
MonotonicityNot monotonic
2024-05-11T06:00:09.739166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 96
60.8%
5 2
 
1.3%
7 2
 
1.3%
10 1
 
0.6%
8 1
 
0.6%
13 1
 
0.6%
18 1
 
0.6%
11 1
 
0.6%
4 1
 
0.6%
9 1
 
0.6%
(Missing) 50
31.6%
ValueCountFrequency (%)
0 96
60.8%
4 1
 
0.6%
5 2
 
1.3%
7 2
 
1.3%
8 1
 
0.6%
9 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%
13 1
 
0.6%
18 1
 
0.6%
ValueCountFrequency (%)
25 1
0.6%
18 1
0.6%
13 1
0.6%
11 1
0.6%
10 1
0.6%
9 1
0.6%
8 1
0.6%
7 2
1.3%
5 2
1.3%
4 1
0.6%

건물지하층수
Categorical

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
96 
<NA>
50 
3
 
4
2
 
4
4
 
2

Length

Max length4
Median length1
Mean length1.9493671
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 96
60.8%
<NA> 50
31.6%
3 4
 
2.5%
2 4
 
2.5%
4 2
 
1.3%
1 2
 
1.3%

Length

2024-05-11T06:00:10.431241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:10.758436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
60.8%
na 50
31.6%
3 4
 
2.5%
2 4
 
2.5%
4 2
 
1.3%
1 2
 
1.3%

사용시작지상층
Categorical

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
97 
<NA>
56 
4
 
3
1
 
2

Length

Max length4
Median length1
Mean length2.0632911
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 97
61.4%
<NA> 56
35.4%
4 3
 
1.9%
1 2
 
1.3%

Length

2024-05-11T06:00:11.162950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:11.526725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 97
61.4%
na 56
35.4%
4 3
 
1.9%
1 2
 
1.3%

사용끝지상층
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
136 
0
18 
4
 
1
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.5822785
Min length1

Unique

Unique4 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 136
86.1%
0 18
 
11.4%
4 1
 
0.6%
1 1
 
0.6%
2 1
 
0.6%
5 1
 
0.6%

Length

2024-05-11T06:00:11.919028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:12.279940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
86.1%
0 18
 
11.4%
4 1
 
0.6%
1 1
 
0.6%
2 1
 
0.6%
5 1
 
0.6%

사용시작지하층
Categorical

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
90 
<NA>
51 
1
14 
2
 
3

Length

Max length4
Median length1
Mean length1.9683544
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 90
57.0%
<NA> 51
32.3%
1 14
 
8.9%
2 3
 
1.9%

Length

2024-05-11T06:00:12.604679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:12.820539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 90
57.0%
na 51
32.3%
1 14
 
8.9%
2 3
 
1.9%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
133 
0
 
10
1
 
10
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.5253165
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 133
84.2%
0 10
 
6.3%
1 10
 
6.3%
2 4
 
2.5%
3 1
 
0.6%

Length

2024-05-11T06:00:13.067636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:13.337940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 133
84.2%
0 10
 
6.3%
1 10
 
6.3%
2 4
 
2.5%
3 1
 
0.6%

한실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
104 
<NA>
54 

Length

Max length4
Median length1
Mean length2.0253165
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
65.8%
<NA> 54
34.2%

Length

2024-05-11T06:00:13.598967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:13.805839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
65.8%
na 54
34.2%

양실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
104 
<NA>
54 

Length

Max length4
Median length1
Mean length2.0253165
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
65.8%
<NA> 54
34.2%

Length

2024-05-11T06:00:14.014988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:14.422615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
65.8%
na 54
34.2%

욕실수
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
94 
<NA>
46 
2
13 
6
 
3
4
 
2

Length

Max length4
Median length1
Mean length1.8734177
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 94
59.5%
<NA> 46
29.1%
2 13
 
8.2%
6 3
 
1.9%
4 2
 
1.3%

Length

2024-05-11T06:00:14.810065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:15.178741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 94
59.5%
na 46
29.1%
2 13
 
8.2%
6 3
 
1.9%
4 2
 
1.3%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.3%
Missing4
Missing (%)2.5%
Memory size448.0 B
False
142 
True
 
12
(Missing)
 
4
ValueCountFrequency (%)
False 142
89.9%
True 12
 
7.6%
(Missing) 4
 
2.5%
2024-05-11T06:00:15.514172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
104 
<NA>
54 

Length

Max length4
Median length1
Mean length2.0253165
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
65.8%
<NA> 54
34.2%

Length

2024-05-11T06:00:15.864917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:16.165645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
65.8%
na 54
34.2%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing157
Missing (%)99.4%
Memory size1.4 KiB
2024-05-11T06:00:16.537042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length69
Mean length69
Min length69

Characters and Unicode

Total characters69
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row이 영업신고의 효력은 건축물 임시사용승인기간 2012.4.30까지이며 건축물 사용승인 연장 또는 준공 완료시 재신청 해야 함
ValueCountFrequency (%)
건축물 2
13.3%
이 1
 
6.7%
영업신고의 1
 
6.7%
효력은 1
 
6.7%
임시사용승인기간 1
 
6.7%
2012.4.30까지이며 1
 
6.7%
사용승인 1
 
6.7%
연장 1
 
6.7%
또는 1
 
6.7%
준공 1
 
6.7%
Other values (4) 4
26.7%
2024-05-11T06:00:17.240605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
20.3%
이 2
 
2.9%
축 2
 
2.9%
. 2
 
2.9%
0 2
 
2.9%
인 2
 
2.9%
승 2
 
2.9%
용 2
 
2.9%
사 2
 
2.9%
시 2
 
2.9%
Other values (33) 37
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
66.7%
Space Separator 14
 
20.3%
Decimal Number 7
 
10.1%
Other Punctuation 2
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2
 
4.3%
축 2
 
4.3%
인 2
 
4.3%
승 2
 
4.3%
용 2
 
4.3%
사 2
 
4.3%
시 2
 
4.3%
물 2
 
4.3%
건 2
 
4.3%
신 2
 
4.3%
Other values (26) 26
56.5%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
2 2
28.6%
3 1
14.3%
4 1
14.3%
1 1
14.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46
66.7%
Common 23
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2
 
4.3%
축 2
 
4.3%
인 2
 
4.3%
승 2
 
4.3%
용 2
 
4.3%
사 2
 
4.3%
시 2
 
4.3%
물 2
 
4.3%
건 2
 
4.3%
신 2
 
4.3%
Other values (26) 26
56.5%
Common
ValueCountFrequency (%)
14
60.9%
. 2
 
8.7%
0 2
 
8.7%
2 2
 
8.7%
3 1
 
4.3%
4 1
 
4.3%
1 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46
66.7%
ASCII 23
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
60.9%
. 2
 
8.7%
0 2
 
8.7%
2 2
 
8.7%
3 1
 
4.3%
4 1
 
4.3%
1 1
 
4.3%
Hangul
ValueCountFrequency (%)
이 2
 
4.3%
축 2
 
4.3%
인 2
 
4.3%
승 2
 
4.3%
용 2
 
4.3%
사 2
 
4.3%
시 2
 
4.3%
물 2
 
4.3%
건 2
 
4.3%
신 2
 
4.3%
Other values (26) 26
56.5%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
157 
20120301
 
1

Length

Max length8
Median length4
Mean length4.0253165
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
99.4%
20120301 1
 
0.6%

Length

2024-05-11T06:00:17.716611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:18.095149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
99.4%
20120301 1
 
0.6%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
157 
20120430
 
1

Length

Max length8
Median length4
Mean length4.0253165
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
99.4%
20120430 1
 
0.6%

Length

2024-05-11T06:00:18.514338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:18.814013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
99.4%
20120430 1
 
0.6%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
146 
임대
 
10
자가
 
2

Length

Max length4
Median length4
Mean length3.8481013
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 146
92.4%
임대 10
 
6.3%
자가 2
 
1.3%

Length

2024-05-11T06:00:19.074243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:19.338591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
92.4%
임대 10
 
6.3%
자가 2
 
1.3%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
134 
0
24 

Length

Max length4
Median length4
Mean length3.5443038
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> 134
84.8%
0 24
 
15.2%

Length

2024-05-11T06:00:19.714062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:20.077687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
84.8%
0 24
 
15.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
151 
0
 
7

Length

Max length4
Median length4
Mean length3.8670886
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> 151
95.6%
0 7
 
4.4%

Length

2024-05-11T06:00:20.552868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:20.867891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
95.6%
0 7
 
4.4%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
151 
0
 
7

Length

Max length4
Median length4
Mean length3.8670886
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> 151
95.6%
0 7
 
4.4%

Length

2024-05-11T06:00:21.228565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:21.598320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
95.6%
0 7
 
4.4%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
137 
0
21 

Length

Max length4
Median length4
Mean length3.6012658
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 137
86.7%
0 21
 
13.3%

Length

2024-05-11T06:00:21.965581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:22.177782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
86.7%
0 21
 
13.3%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
137 
0
21 

Length

Max length4
Median length4
Mean length3.6012658
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 137
86.7%
0 21
 
13.3%

Length

2024-05-11T06:00:22.541202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:00:22.923648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
86.7%
0 21
 
13.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing4
Missing (%)2.5%
Memory size448.0 B
False
154 
(Missing)
 
4
ValueCountFrequency (%)
False 154
97.5%
(Missing) 4
 
2.5%
2024-05-11T06:00:23.258101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030300003030000-202-1960-0024819601130<NA>3폐업2폐업19970506<NA><NA><NA>02 2320702143.35133801서울특별시 성동구 금호동1가 531-0번지<NA><NA>금호탕2001-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업201797.844579450186.113277공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130300003030000-202-1960-0025519601228<NA>3폐업2폐업19990922<NA><NA><NA>02169.15133805서울특별시 성동구 금호동3가 420-0번지<NA><NA>옥천목욕탕2001-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업201833.804518449573.097223공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230300003030000-202-1960-0027319601228<NA>3폐업2폐업19990923<NA><NA><NA>0200000000197.09133882서울특별시 성동구 도선동 285-1번지<NA><NA>무학탕2002-04-09 00:00:00I2018-08-31 23:59:59.0공동탕업202797.681704451228.899925공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330300003030000-202-1960-0027619601130<NA>3폐업2폐업19970331<NA><NA><NA>02 293037793.17133881서울특별시 성동구 홍익동 420-0번지<NA><NA>시온탕2001-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업202619.72639451627.794307공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430300003030000-202-1965-0026319651111<NA>3폐업2폐업19970702<NA><NA><NA>02 2923860192.44133867서울특별시 성동구 행당동 292-54번지<NA><NA>은하수탕2001-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업202864.796628450901.755492공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530300003030000-202-1966-0024919660927<NA>3폐업2폐업19980212<NA><NA><NA>02 2533278180.08133801서울특별시 성동구 금호동1가 580-0번지<NA><NA>백세탕2001-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업202050.023562450076.427964공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630300003030000-202-1967-0023619670605<NA>3폐업2폐업20210902<NA><NA><NA>0222384094400.91133807서울특별시 성동구 금호동3가 1305-1서울특별시 성동구 장터길 21 (금호동3가)4724서중탕2021-09-02 10:55:42U2021-09-04 02:40:00.0공동탕업201540.816056449583.320152공동탕업000000000N0<NA><NA><NA><NA>00000N
730300003030000-202-1967-0032219671028<NA>1영업/정상1영업<NA><NA><NA><NA>02 4628561149.64133827서울특별시 성동구 성수동2가 331-163번지서울특별시 성동구 성덕정19길 11 (성수동2가)4776성수탕2011-08-16 17:18:52I2018-08-31 23:59:59.0공동탕업204923.683617448371.986132공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N
830300003030000-202-1967-0032319671030<NA>1영업/정상1영업<NA><NA><NA><NA>0222970720119.34133809서울특별시 성동구 금호동4가 615-616번지서울특별시 성동구 독서당로 280-5, 616호 (금호동4가)4737금호한증막2014-04-18 17:59:51I2018-08-31 23:59:59.0한증막업201742.272982449445.591517한증막업<NA><NA><NA><NA><NA><NA><NA><NA>2Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930300003030000-202-1968-0026019680914<NA>3폐업2폐업20030214<NA><NA><NA>0202920305288.96133817서울특별시 성동구 사근동 204-3번지<NA><NA>은천탕2003-02-17 00:00:00I2018-08-31 23:59:59.0공동탕업204129.659784450977.582843공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14830300003030000-202-2008-0000120080211<NA>3폐업2폐업20100601<NA><NA><NA>000222473300597.40133851서울특별시 성동구 용답동 223-5번지<NA><NA>사)한국체육지도자총연합회연수원2008-02-12 09:47:20I2018-08-31 23:59:59.0공동탕업204934.319836451032.958798공동탕업720011004Y0<NA><NA><NA>임대0<NA><NA><NA><NA>N
14930300003030000-202-2009-0000120090603<NA>3폐업2폐업20120430<NA><NA><NA>02 220016004,896.00133866서울특별시 성동구 행당동 168-1번지서울특별시 성동구 왕십리광장로 17 (행당동, 왕십리민자역사 지상4,5층)4750포시즌2012-11-15 13:46:19I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업203292.151899451267.730901공동탕업+찜질시설서비스영업004500006Y0이 영업신고의 효력은 건축물 임시사용승인기간 2012.4.30까지이며 건축물 사용승인 연장 또는 준공 완료시 재신청 해야 함2012030120120430임대0<NA><NA>00N
15030300003030000-202-2010-0000120101025<NA>3폐업2폐업20130902<NA><NA><NA>22813435833.00133050서울특별시 성동구 마장동 439-1번지 마축일축산물시장 지하1층(101,102,103호)서울특별시 성동구 마장로35길 68 (마장동,마축일축산물시장 지하1층(101,102,103호))4752청계참숯가마사우나2012-05-22 08:49:02I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업203576.594692452041.559037공동탕업+찜질시설서비스영업00<NA><NA>11006Y0<NA><NA><NA><NA>0<NA><NA>00N
15130300003030000-202-2013-0000120130408<NA>3폐업2폐업20140203<NA><NA><NA>02 22912456570.00133856서울특별시 성동구 하왕십리동 866-2번지 지하1,2층서울특별시 성동구 왕십리로 386, 지하1,2층 (하왕십리동)4701삼협사우나2013-07-02 15:08:15I2018-08-31 23:59:59.0공동탕업202371.997992451423.409696공동탕업000012000N0<NA><NA><NA><NA>0<NA><NA>00N
15230300003030000-202-2013-0000220130719<NA>3폐업2폐업20170515<NA><NA><NA><NA>1,627.00133866서울특별시 성동구 행당동 168-151번지서울특별시 성동구 왕십리광장로 17, 5층 (행당동)4750포시즌2017-05-15 14:08:42I2018-08-31 23:59:59.0공동탕업203321.56233451001.868688공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
15330300003030000-202-2013-0000320130904<NA>1영업/정상1영업<NA><NA><NA><NA>0222953333379.82133858서울특별시 성동구 하왕십리동 990번지 지하2층서울특별시 성동구 왕십리로31나길 18, 지하2층 (하왕십리동)4710한신옥사우나2020-03-16 11:15:20U2020-03-18 02:40:00.0공동탕업202437.643551451119.695239공동탕업00<NA><NA>2<NA>000N0<NA><NA><NA><NA>0<NA><NA>00N
15430300003030000-202-2014-0000120140430<NA>3폐업2폐업20180111<NA><NA><NA><NA>145.00133070서울특별시 성동구 행당동 376번지서울특별시 성동구 고산자로 177, 지하1층 B01호 (행당동, 서울숲행당푸르지오아파트)4716바디짐2018-01-11 10:48:35I2018-08-31 23:59:59.0목욕장업 기타202799.275304450325.895702목욕장업 기타00<NA><NA>11000N0<NA><NA><NA><NA>0<NA><NA>00N
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15630300003030000-202-2020-0000120200720<NA>1영업/정상1영업<NA><NA><NA><NA>0222865213349.51133851서울특별시 성동구 용답동 223-5 서울시투자기관교육복지통합센터서울특별시 성동구 천호대로78길 15-48, 지하1층 (용답동)4806성동구립용답체육센터 목욕탕2020-11-25 15:57:55U2020-11-27 02:40:00.0공동탕업204934.319836451032.958798공동탕업000000004Y0<NA><NA><NA><NA>00000N
15730300003030000-202-2022-000012022-07-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>132.06133-856서울특별시 성동구 하왕십리동 866-2 삼협빌딩서울특별시 성동구 왕십리로 386, 삼협빌딩 지1층 (하왕십리동)4701해빗2023-03-30 14:50:19U2022-12-04 00:01:00.0목욕장업 기타202371.997992451423.409696<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>