Overview

Dataset statistics

Number of variables47
Number of observations155
Missing cells1107
Missing cells (%)15.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.1 KiB
Average record size in memory403.9 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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-19956/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
데이터갱신일자 is highly imbalanced (64.1%)Imbalance
업태구분명 is highly imbalanced (67.2%)Imbalance
위생업태명 is highly imbalanced (60.0%)Imbalance
건물지하층수 is highly imbalanced (50.8%)Imbalance
사용끝지상층 is highly imbalanced (67.5%)Imbalance
사용끝지하층 is highly imbalanced (59.2%)Imbalance
욕실수 is highly imbalanced (51.6%)Imbalance
발한실여부 is highly imbalanced (72.0%)Imbalance
조건부허가시작일자 is highly imbalanced (94.4%)Imbalance
조건부허가종료일자 is highly imbalanced (94.4%)Imbalance
건물소유구분명 is highly imbalanced (86.2%)Imbalance
여성종사자수 is highly imbalanced (76.4%)Imbalance
남성종사자수 is highly imbalanced (76.4%)Imbalance
다중이용업소여부 is highly imbalanced (94.0%)Imbalance
인허가취소일자 has 155 (100.0%) missing valuesMissing
폐업일자 has 24 (15.5%) missing valuesMissing
휴업시작일자 has 155 (100.0%) missing valuesMissing
휴업종료일자 has 155 (100.0%) missing valuesMissing
재개업일자 has 155 (100.0%) missing valuesMissing
도로명주소 has 108 (69.7%) missing valuesMissing
도로명우편번호 has 109 (70.3%) missing valuesMissing
좌표정보(X) has 14 (9.0%) missing valuesMissing
좌표정보(Y) has 14 (9.0%) missing valuesMissing
건물지상층수 has 41 (26.5%) missing valuesMissing
발한실여부 has 11 (7.1%) missing valuesMissing
조건부허가신고사유 has 154 (99.4%) missing valuesMissing
다중이용업소여부 has 11 (7.1%) 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 103 (66.5%) zerosZeros

Reproduction

Analysis started2024-05-18 01:09:34.925203
Analysis finished2024-05-18 01:09:36.063208
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3040000
155 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 155
100.0%

Length

2024-05-18T10:09:36.254437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:36.563555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 155
100.0%

관리번호
Text

UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-18T10:09:37.003094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3410
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

Unique155 ?
Unique (%)100.0%

Sample

1st row3040000-202-1970-00022
2nd row3040000-202-1970-00031
3rd row3040000-202-1970-00037
4th row3040000-202-1970-00064
5th row3040000-202-1970-00093
ValueCountFrequency (%)
3040000-202-1970-00022 1
 
0.6%
3040000-202-1993-00026 1
 
0.6%
3040000-202-1995-00029 1
 
0.6%
3040000-202-1991-00117 1
 
0.6%
3040000-202-1991-00118 1
 
0.6%
3040000-202-1992-00092 1
 
0.6%
3040000-202-1992-00094 1
 
0.6%
3040000-202-1992-00096 1
 
0.6%
3040000-202-1993-00021 1
 
0.6%
3040000-202-1993-00099 1
 
0.6%
Other values (145) 145
93.5%
2024-05-18T10:09:37.757951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1488
43.6%
- 465
 
13.6%
2 397
 
11.6%
1 222
 
6.5%
3 216
 
6.3%
4 192
 
5.6%
9 190
 
5.6%
8 119
 
3.5%
7 53
 
1.6%
5 35
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2945
86.4%
Dash Punctuation 465
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1488
50.5%
2 397
 
13.5%
1 222
 
7.5%
3 216
 
7.3%
4 192
 
6.5%
9 190
 
6.5%
8 119
 
4.0%
7 53
 
1.8%
5 35
 
1.2%
6 33
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 465
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3410
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1488
43.6%
- 465
 
13.6%
2 397
 
11.6%
1 222
 
6.5%
3 216
 
6.3%
4 192
 
5.6%
9 190
 
5.6%
8 119
 
3.5%
7 53
 
1.6%
5 35
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3410
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1488
43.6%
- 465
 
13.6%
2 397
 
11.6%
1 222
 
6.5%
3 216
 
6.3%
4 192
 
5.6%
9 190
 
5.6%
8 119
 
3.5%
7 53
 
1.6%
5 35
 
1.0%

인허가일자
Date

Distinct135
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1970-01-09 00:00:00
Maximum2022-07-19 00:00:00
2024-05-18T10:09:38.165293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:09:38.591846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
131 
1
24 

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 (%)
3 131
84.5%
1 24
 
15.5%

Length

2024-05-18T10:09:38.979089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:39.166774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 131
84.5%
1 24
 
15.5%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
131 
영업/정상
24 

Length

Max length5
Median length2
Mean length2.4645161
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 131
84.5%
영업/정상 24
 
15.5%

Length

2024-05-18T10:09:39.484154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:39.712292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 131
84.5%
영업/정상 24
 
15.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
131 
1
24 

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 (%)
2 131
84.5%
1 24
 
15.5%

Length

2024-05-18T10:09:40.109047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:40.428465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 131
84.5%
1 24
 
15.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
131 
영업
24 

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 131
84.5%
영업 24
 
15.5%

Length

2024-05-18T10:09:40.681148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:41.181804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 131
84.5%
영업 24
 
15.5%

폐업일자
Date

MISSING 

Distinct103
Distinct (%)78.6%
Missing24
Missing (%)15.5%
Memory size1.3 KiB
Minimum1989-03-09 00:00:00
Maximum2023-08-17 00:00:00
2024-05-18T10:09:41.529843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:09:42.010041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

Distinct140
Distinct (%)90.9%
Missing1
Missing (%)0.6%
Memory size1.3 KiB
2024-05-18T10:09:42.645859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.214286
Min length6

Characters and Unicode

Total characters1573
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

Unique132 ?
Unique (%)85.7%

Sample

1st row02 4974289
2nd row02 4663943
3rd row02 4661720
4th row02 444 1080
5th row02 4656512
ValueCountFrequency (%)
02 113
37.3%
0211111111 6
 
2.0%
444 3
 
1.0%
4531734 3
 
1.0%
4530123 3
 
1.0%
02453 2
 
0.7%
452 2
 
0.7%
02452 2
 
0.7%
446 2
 
0.7%
800 2
 
0.7%
Other values (160) 165
54.5%
2024-05-18T10:09:44.082797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 243
15.4%
2 242
15.4%
4 230
14.6%
171
10.9%
1 139
8.8%
5 132
8.4%
6 124
7.9%
3 98
6.2%
8 81
 
5.1%
7 58
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1402
89.1%
Space Separator 171
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 243
17.3%
2 242
17.3%
4 230
16.4%
1 139
9.9%
5 132
9.4%
6 124
8.8%
3 98
7.0%
8 81
 
5.8%
7 58
 
4.1%
9 55
 
3.9%
Space Separator
ValueCountFrequency (%)
171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1573
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 243
15.4%
2 242
15.4%
4 230
14.6%
171
10.9%
1 139
8.8%
5 132
8.4%
6 124
7.9%
3 98
6.2%
8 81
 
5.1%
7 58
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 243
15.4%
2 242
15.4%
4 230
14.6%
171
10.9%
1 139
8.8%
5 132
8.4%
6 124
7.9%
3 98
6.2%
8 81
 
5.1%
7 58
 
3.7%

소재지면적
Text

Distinct126
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-18T10:09:45.151440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.6
Min length3

Characters and Unicode

Total characters868
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

Unique120 ?
Unique (%)77.4%

Sample

1st row126.30
2nd row211.06
3rd row504.88
4th row342.59
5th row151.40
ValueCountFrequency (%)
00 25
 
16.1%
330.00 2
 
1.3%
218.57 2
 
1.3%
1,320.00 2
 
1.3%
912.54 2
 
1.3%
257.34 2
 
1.3%
331.38 1
 
0.6%
126.30 1
 
0.6%
285.81 1
 
0.6%
405.23 1
 
0.6%
Other values (116) 116
74.8%
2024-05-18T10:09:46.729411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 155
17.9%
0 154
17.7%
2 94
10.8%
3 71
8.2%
1 67
7.7%
5 63
7.3%
6 61
 
7.0%
4 59
 
6.8%
9 51
 
5.9%
8 47
 
5.4%
Other values (2) 46
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 706
81.3%
Other Punctuation 162
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154
21.8%
2 94
13.3%
3 71
10.1%
1 67
9.5%
5 63
8.9%
6 61
 
8.6%
4 59
 
8.4%
9 51
 
7.2%
8 47
 
6.7%
7 39
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 155
95.7%
, 7
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 868
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 155
17.9%
0 154
17.7%
2 94
10.8%
3 71
8.2%
1 67
7.7%
5 63
7.3%
6 61
 
7.0%
4 59
 
6.8%
9 51
 
5.9%
8 47
 
5.4%
Other values (2) 46
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 155
17.9%
0 154
17.7%
2 94
10.8%
3 71
8.2%
1 67
7.7%
5 63
7.3%
6 61
 
7.0%
4 59
 
6.8%
9 51
 
5.9%
8 47
 
5.4%
Other values (2) 46
 
5.3%

소재지우편번호
Text

Distinct68
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-18T10:09:47.941369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0258065
Min length6

Characters and Unicode

Total characters934
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

Unique27 ?
Unique (%)17.4%

Sample

1st row143902
2nd row143846
3rd row143840
4th row143960
5th row143916
ValueCountFrequency (%)
143873 5
 
3.2%
143916 5
 
3.2%
143831 5
 
3.2%
143814 5
 
3.2%
143845 5
 
3.2%
143888 5
 
3.2%
143841 5
 
3.2%
143821 4
 
2.6%
143875 4
 
2.6%
143840 4
 
2.6%
Other values (58) 108
69.7%
2024-05-18T10:09:50.158482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 202
21.6%
4 191
20.4%
3 181
19.4%
8 141
15.1%
9 49
 
5.2%
0 42
 
4.5%
2 41
 
4.4%
7 28
 
3.0%
5 28
 
3.0%
6 27
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 930
99.6%
Dash Punctuation 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 202
21.7%
4 191
20.5%
3 181
19.5%
8 141
15.2%
9 49
 
5.3%
0 42
 
4.5%
2 41
 
4.4%
7 28
 
3.0%
5 28
 
3.0%
6 27
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 202
21.6%
4 191
20.4%
3 181
19.4%
8 141
15.1%
9 49
 
5.2%
0 42
 
4.5%
2 41
 
4.4%
7 28
 
3.0%
5 28
 
3.0%
6 27
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 202
21.6%
4 191
20.4%
3 181
19.4%
8 141
15.1%
9 49
 
5.2%
0 42
 
4.5%
2 41
 
4.4%
7 28
 
3.0%
5 28
 
3.0%
6 27
 
2.9%

지번주소
Text

Distinct131
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-18T10:09:50.890561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length22.645161
Min length18

Characters and Unicode

Total characters3510
Distinct characters80
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

Unique108 ?
Unique (%)69.7%

Sample

1st row서울특별시 광진구 중곡동 196-11번지
2nd row서울특별시 광진구 자양동 236-89번지
3rd row서울특별시 광진구 군자동 346-22번지
4th row서울특별시 광진구 구의동 226-2번지
5th row서울특별시 광진구 화양동 33-34번지
ValueCountFrequency (%)
서울특별시 155
24.1%
광진구 155
24.1%
자양동 50
 
7.8%
중곡동 33
 
5.1%
구의동 29
 
4.5%
광장동 15
 
2.3%
화양동 13
 
2.0%
군자동 11
 
1.7%
능동 4
 
0.6%
466-8번지 3
 
0.5%
Other values (145) 175
27.2%
2024-05-18T10:09:51.702097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
632
18.0%
구 186
 
5.3%
광 171
 
4.9%
시 156
 
4.4%
동 156
 
4.4%
서 155
 
4.4%
특 155
 
4.4%
별 155
 
4.4%
진 155
 
4.4%
울 155
 
4.4%
Other values (70) 1434
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2058
58.6%
Decimal Number 666
 
19.0%
Space Separator 632
 
18.0%
Dash Punctuation 145
 
4.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Math Symbol 2
 
0.1%
Other Punctuation 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 186
 
9.0%
광 171
 
8.3%
시 156
 
7.6%
동 156
 
7.6%
서 155
 
7.5%
특 155
 
7.5%
별 155
 
7.5%
진 155
 
7.5%
울 155
 
7.5%
지 145
 
7.0%
Other values (53) 469
22.8%
Decimal Number
ValueCountFrequency (%)
1 132
19.8%
4 88
13.2%
2 86
12.9%
6 69
10.4%
3 67
10.1%
5 60
9.0%
8 50
 
7.5%
9 41
 
6.2%
0 38
 
5.7%
7 35
 
5.3%
Space Separator
ValueCountFrequency (%)
632
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
58.6%
Common 1451
41.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 186
 
9.0%
광 171
 
8.3%
시 156
 
7.6%
동 156
 
7.6%
서 155
 
7.5%
특 155
 
7.5%
별 155
 
7.5%
진 155
 
7.5%
울 155
 
7.5%
지 145
 
7.0%
Other values (53) 469
22.8%
Common
ValueCountFrequency (%)
632
43.6%
- 145
 
10.0%
1 132
 
9.1%
4 88
 
6.1%
2 86
 
5.9%
6 69
 
4.8%
3 67
 
4.6%
5 60
 
4.1%
8 50
 
3.4%
9 41
 
2.8%
Other values (6) 81
 
5.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
58.6%
ASCII 1452
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
632
43.5%
- 145
 
10.0%
1 132
 
9.1%
4 88
 
6.1%
2 86
 
5.9%
6 69
 
4.8%
3 67
 
4.6%
5 60
 
4.1%
8 50
 
3.4%
9 41
 
2.8%
Other values (7) 82
 
5.6%
Hangul
ValueCountFrequency (%)
구 186
 
9.0%
광 171
 
8.3%
시 156
 
7.6%
동 156
 
7.6%
서 155
 
7.5%
특 155
 
7.5%
별 155
 
7.5%
진 155
 
7.5%
울 155
 
7.5%
지 145
 
7.0%
Other values (53) 469
22.8%

도로명주소
Text

MISSING 

Distinct45
Distinct (%)95.7%
Missing108
Missing (%)69.7%
Memory size1.3 KiB
2024-05-18T10:09:52.365533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length28.829787
Min length23

Characters and Unicode

Total characters1355
Distinct characters102
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

Unique43 ?
Unique (%)91.5%

Sample

1st row서울특별시 광진구 구의로 65-1 (구의동)
2nd row서울특별시 광진구 긴고랑로 41 (중곡동)
3rd row서울특별시 광진구 능동로37길 6 (중곡동)
4th row서울특별시 광진구 용마산로7길 68 (중곡동)
5th row서울특별시 광진구 자양로 234 (구의동)
ValueCountFrequency (%)
서울특별시 47
 
17.7%
광진구 47
 
17.7%
구의동 11
 
4.1%
중곡동 10
 
3.8%
자양동 10
 
3.8%
광장동 7
 
2.6%
자양로 6
 
2.3%
뚝섬로 4
 
1.5%
177 3
 
1.1%
워커힐로 3
 
1.1%
Other values (95) 118
44.4%
2024-05-18T10:09:53.465721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
16.2%
구 65
 
4.8%
광 60
 
4.4%
동 53
 
3.9%
( 48
 
3.5%
시 48
 
3.5%
) 48
 
3.5%
서 47
 
3.5%
특 47
 
3.5%
별 47
 
3.5%
Other values (92) 673
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 822
60.7%
Space Separator 219
 
16.2%
Decimal Number 186
 
13.7%
Open Punctuation 48
 
3.5%
Close Punctuation 48
 
3.5%
Other Punctuation 20
 
1.5%
Dash Punctuation 5
 
0.4%
Uppercase Letter 4
 
0.3%
Math Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 65
 
7.9%
광 60
 
7.3%
동 53
 
6.4%
시 48
 
5.8%
서 47
 
5.7%
특 47
 
5.7%
별 47
 
5.7%
진 47
 
5.7%
울 47
 
5.7%
로 47
 
5.7%
Other values (74) 314
38.2%
Decimal Number
ValueCountFrequency (%)
1 39
21.0%
3 25
13.4%
7 22
11.8%
2 21
11.3%
5 18
9.7%
6 16
8.6%
4 16
8.6%
0 13
 
7.0%
8 10
 
5.4%
9 6
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%
Space Separator
ValueCountFrequency (%)
219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 822
60.7%
Common 529
39.0%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 65
 
7.9%
광 60
 
7.3%
동 53
 
6.4%
시 48
 
5.8%
서 47
 
5.7%
특 47
 
5.7%
별 47
 
5.7%
진 47
 
5.7%
울 47
 
5.7%
로 47
 
5.7%
Other values (74) 314
38.2%
Common
ValueCountFrequency (%)
219
41.4%
( 48
 
9.1%
) 48
 
9.1%
1 39
 
7.4%
3 25
 
4.7%
7 22
 
4.2%
2 21
 
4.0%
, 20
 
3.8%
5 18
 
3.4%
6 16
 
3.0%
Other values (6) 53
 
10.0%
Latin
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 822
60.7%
ASCII 533
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
41.1%
( 48
 
9.0%
) 48
 
9.0%
1 39
 
7.3%
3 25
 
4.7%
7 22
 
4.1%
2 21
 
3.9%
, 20
 
3.8%
5 18
 
3.4%
6 16
 
3.0%
Other values (8) 57
 
10.7%
Hangul
ValueCountFrequency (%)
구 65
 
7.9%
광 60
 
7.3%
동 53
 
6.4%
시 48
 
5.8%
서 47
 
5.7%
특 47
 
5.7%
별 47
 
5.7%
진 47
 
5.7%
울 47
 
5.7%
로 47
 
5.7%
Other values (74) 314
38.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)78.3%
Missing109
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean5018.0652
Minimum4901
Maximum5119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-18T10:09:53.872977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4901
5-th percentile4910.25
Q14963
median5012.5
Q35087
95-th percentile5117
Maximum5119
Range218
Interquartile range (IQR)124

Descriptive statistics

Standard deviation72.358798
Coefficient of variation (CV)0.014419661
Kurtosis-1.381183
Mean5018.0652
Median Absolute Deviation (MAD)60
Skewness0.020778531
Sum230831
Variance5235.7957
MonotonicityNot monotonic
2024-05-18T10:09:54.317918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
4963 3
 
1.9%
4949 2
 
1.3%
4969 2
 
1.3%
4974 2
 
1.3%
5117 2
 
1.3%
5115 2
 
1.3%
5112 2
 
1.3%
5102 2
 
1.3%
5065 2
 
1.3%
5051 1
 
0.6%
Other values (26) 26
 
16.8%
(Missing) 109
70.3%
ValueCountFrequency (%)
4901 1
0.6%
4903 1
0.6%
4910 1
0.6%
4911 1
0.6%
4919 1
0.6%
4922 1
0.6%
4936 1
0.6%
4947 1
0.6%
4949 2
1.3%
4956 1
0.6%
ValueCountFrequency (%)
5119 1
0.6%
5118 1
0.6%
5117 2
1.3%
5116 1
0.6%
5115 2
1.3%
5112 2
1.3%
5102 2
1.3%
5090 1
0.6%
5078 1
0.6%
5068 1
0.6%

사업장명
Text

Distinct146
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-18T10:09:55.065146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length4.8709677
Min length2

Characters and Unicode

Total characters755
Distinct characters173
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

Unique137 ?
Unique (%)88.4%

Sample

1st row도원탕
2nd row성춘탕
3rd row장안탕
4th row은호탕
5th row화연탕
ValueCountFrequency (%)
천일탕 2
 
1.2%
청수탕 2
 
1.2%
대천 2
 
1.2%
서호탕 2
 
1.2%
대원탕 2
 
1.2%
현대탕 2
 
1.2%
우정탕 2
 
1.2%
동천탕 2
 
1.2%
조영목욕탕 2
 
1.2%
노다지 1
 
0.6%
Other values (148) 148
88.6%
2024-05-18T10:09:56.186585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 97
 
12.8%
대 39
 
5.2%
우 27
 
3.6%
사 26
 
3.4%
나 25
 
3.3%
목 23
 
3.0%
욕 23
 
3.0%
동 19
 
2.5%
중 19
 
2.5%
천 16
 
2.1%
Other values (163) 441
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
93.9%
Space Separator 12
 
1.6%
Lowercase Letter 8
 
1.1%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Decimal Number 7
 
0.9%
Uppercase Letter 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 97
 
13.7%
대 39
 
5.5%
우 27
 
3.8%
사 26
 
3.7%
나 25
 
3.5%
목 23
 
3.2%
욕 23
 
3.2%
동 19
 
2.7%
중 19
 
2.7%
천 16
 
2.3%
Other values (145) 395
55.7%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
c 1
12.5%
i 1
12.5%
a 1
12.5%
l 1
12.5%
e 1
12.5%
h 1
12.5%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
2 2
28.6%
0 2
28.6%
5 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
T 1
20.0%
M 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 709
93.9%
Common 33
 
4.4%
Latin 13
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 97
 
13.7%
대 39
 
5.5%
우 27
 
3.8%
사 26
 
3.7%
나 25
 
3.5%
목 23
 
3.2%
욕 23
 
3.2%
동 19
 
2.7%
중 19
 
2.7%
천 16
 
2.3%
Other values (145) 395
55.7%
Latin
ValueCountFrequency (%)
C 2
15.4%
s 2
15.4%
T 1
7.7%
c 1
7.7%
i 1
7.7%
a 1
7.7%
l 1
7.7%
e 1
7.7%
h 1
7.7%
M 1
7.7%
Common
ValueCountFrequency (%)
12
36.4%
( 7
21.2%
) 7
21.2%
4 2
 
6.1%
2 2
 
6.1%
0 2
 
6.1%
5 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 709
93.9%
ASCII 46
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 97
 
13.7%
대 39
 
5.5%
우 27
 
3.8%
사 26
 
3.7%
나 25
 
3.5%
목 23
 
3.2%
욕 23
 
3.2%
동 19
 
2.7%
중 19
 
2.7%
천 16
 
2.3%
Other values (145) 395
55.7%
ASCII
ValueCountFrequency (%)
12
26.1%
( 7
15.2%
) 7
15.2%
4 2
 
4.3%
2 2
 
4.3%
C 2
 
4.3%
0 2
 
4.3%
s 2
 
4.3%
T 1
 
2.2%
5 1
 
2.2%
Other values (8) 8
17.4%

최종수정일자
Date

Distinct81
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1999-01-22 00:00:00
Maximum2023-08-17 13:56:04
2024-05-18T10:09:56.646558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:09:57.222008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
123 
U
32 

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 123
79.4%
U 32
 
20.6%

Length

2024-05-18T10:09:57.820573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:58.210833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 123
79.4%
u 32
 
20.6%

데이터갱신일자
Categorical

IMBALANCE 

Distinct31
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2018-08-31 23:59:59.0
122 
2019-04-11 02:40:00.0
 
3
2021-12-03 22:03:00.0
 
2
2021-11-02 00:09:00.0
 
1
2021-05-15 02:40:00.0
 
1
Other values (26)
26 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique28 ?
Unique (%)18.1%

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 23:59:59.0 122
78.7%
2019-04-11 02:40:00.0 3
 
1.9%
2021-12-03 22:03:00.0 2
 
1.3%
2021-11-02 00:09:00.0 1
 
0.6%
2021-05-15 02:40:00.0 1
 
0.6%
2019-10-02 02:40:00.0 1
 
0.6%
2022-12-05 00:07:00.0 1
 
0.6%
2021-10-31 00:07:00.0 1
 
0.6%
2018-11-15 02:36:27.0 1
 
0.6%
2019-03-31 02:40:00.0 1
 
0.6%
Other values (21) 21
 
13.5%

Length

2024-05-18T10:09:58.620605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 122
39.4%
23:59:59.0 122
39.4%
02:40:00.0 21
 
6.8%
00:07:00.0 3
 
1.0%
2019-04-11 3
 
1.0%
2022-12-03 2
 
0.6%
2021-12-07 2
 
0.6%
22:03:00.0 2
 
0.6%
2021-12-03 2
 
0.6%
00:09:00.0 1
 
0.3%
Other values (30) 30
 
9.7%

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동탕업
137 
공동탕업+찜질시설서비스영업
 
11
목욕장업 기타
 
6
한증막업
 
1

Length

Max length14
Median length4
Mean length4.8258065
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 137
88.4%
공동탕업+찜질시설서비스영업 11
 
7.1%
목욕장업 기타 6
 
3.9%
한증막업 1
 
0.6%

Length

2024-05-18T10:09:59.141088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:09:59.596329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 137
85.1%
공동탕업+찜질시설서비스영업 11
 
6.8%
목욕장업 6
 
3.7%
기타 6
 
3.7%
한증막업 1
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)76.6%
Missing14
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean207217.58
Minimum205310.29
Maximum209775.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-18T10:10:00.235102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205310.29
5-th percentile205732.47
Q1206324.45
median207299.66
Q3207850.47
95-th percentile209375.07
Maximum209775.27
Range4464.9821
Interquartile range (IQR)1526.0268

Descriptive statistics

Standard deviation1031.465
Coefficient of variation (CV)0.0049776903
Kurtosis-0.15838714
Mean207217.58
Median Absolute Deviation (MAD)731.42197
Skewness0.41100865
Sum29217679
Variance1063920
MonotonicityNot monotonic
2024-05-18T10:10:00.782995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208644.819209521 5
 
3.2%
206324.446092607 3
 
1.9%
207368.624495222 3
 
1.9%
205983.644347859 3
 
1.9%
207850.472864274 2
 
1.3%
207030.250867409 2
 
1.3%
207572.70864703 2
 
1.3%
205310.285709458 2
 
1.3%
206678.650243653 2
 
1.3%
207299.658338386 2
 
1.3%
Other values (98) 115
74.2%
(Missing) 14
 
9.0%
ValueCountFrequency (%)
205310.285709458 2
1.3%
205470.823903755 1
0.6%
205606.03952062 2
1.3%
205711.907068319 1
0.6%
205725.117770632 1
0.6%
205732.471502236 1
0.6%
205761.443344855 1
0.6%
205819.55963304 1
0.6%
205828.733665313 1
0.6%
205963.789092452 1
0.6%
ValueCountFrequency (%)
209775.267831522 1
 
0.6%
209766.973555533 2
 
1.3%
209637.078215509 2
 
1.3%
209602.113978282 1
 
0.6%
209506.54940258 1
 
0.6%
209375.068351656 1
 
0.6%
208644.819209521 5
3.2%
208558.286631653 1
 
0.6%
208403.746065593 1
 
0.6%
208394.416382167 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)76.6%
Missing14
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean449293.82
Minimum447577.18
Maximum452100.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-18T10:10:01.238899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447577.18
5-th percentile447709.28
Q1448227.22
median449017.18
Q3450273.92
95-th percentile451550.42
Maximum452100.9
Range4523.7251
Interquartile range (IQR)2046.6992

Descriptive statistics

Standard deviation1248.4536
Coefficient of variation (CV)0.0027787019
Kurtosis-0.8273786
Mean449293.82
Median Absolute Deviation (MAD)1020.6435
Skewness0.49183257
Sum63350429
Variance1558636.4
MonotonicityNot monotonic
2024-05-18T10:10:01.759423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448711.725750126 5
 
3.2%
447831.329438269 3
 
1.9%
447632.296040333 3
 
1.9%
448466.849833572 3
 
1.9%
450253.602991313 2
 
1.3%
450781.379549387 2
 
1.3%
448680.326713005 2
 
1.3%
448183.850317743 2
 
1.3%
450573.359771289 2
 
1.3%
451267.124132505 2
 
1.3%
Other values (98) 115
74.2%
(Missing) 14
 
9.0%
ValueCountFrequency (%)
447577.178294961 1
 
0.6%
447632.296040333 3
1.9%
447665.572094253 1
 
0.6%
447700.642403113 1
 
0.6%
447704.663602133 1
 
0.6%
447709.275315842 2
1.3%
447746.321126737 1
 
0.6%
447754.123727158 1
 
0.6%
447754.934754273 1
 
0.6%
447773.388572371 1
 
0.6%
ValueCountFrequency (%)
452100.903431521 1
0.6%
452070.118445356 1
0.6%
452012.470712384 1
0.6%
451935.251493803 1
0.6%
451864.561543605 1
0.6%
451840.405435241 2
1.3%
451550.424992111 1
0.6%
451461.155352247 1
0.6%
451435.772826853 1
0.6%
451267.124132505 2
1.3%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동탕업
129 
<NA>
 
11
공동탕업+찜질시설서비스영업
 
10
목욕장업 기타
 
4
한증막업
 
1

Length

Max length14
Median length4
Mean length4.7225806
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 129
83.2%
<NA> 11
 
7.1%
공동탕업+찜질시설서비스영업 10
 
6.5%
목욕장업 기타 4
 
2.6%
한증막업 1
 
0.6%

Length

2024-05-18T10:10:02.370692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:02.821399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 129
81.1%
na 11
 
6.9%
공동탕업+찜질시설서비스영업 10
 
6.3%
목욕장업 4
 
2.5%
기타 4
 
2.5%
한증막업 1
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)6.1%
Missing41
Missing (%)26.5%
Infinite0
Infinite (%)0.0%
Mean0.70175439
Minimum0
Maximum20
Zeros103
Zeros (%)66.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-18T10:10:03.323636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.7
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6371405
Coefficient of variation (CV)3.7579253
Kurtosis28.864663
Mean0.70175439
Median Absolute Deviation (MAD)0
Skewness4.968489
Sum80
Variance6.9545102
MonotonicityNot monotonic
2024-05-18T10:10:03.815513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 103
66.5%
4 3
 
1.9%
11 2
 
1.3%
7 2
 
1.3%
3 2
 
1.3%
6 1
 
0.6%
20 1
 
0.6%
(Missing) 41
 
26.5%
ValueCountFrequency (%)
0 103
66.5%
3 2
 
1.3%
4 3
 
1.9%
6 1
 
0.6%
7 2
 
1.3%
11 2
 
1.3%
20 1
 
0.6%
ValueCountFrequency (%)
20 1
 
0.6%
11 2
 
1.3%
7 2
 
1.3%
6 1
 
0.6%
4 3
 
1.9%
3 2
 
1.3%
0 103
66.5%

건물지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
103 
<NA>
42 
1
 
5
6
 
2
4
 
2

Length

Max length4
Median length1
Mean length1.8129032
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 103
66.5%
<NA> 42
27.1%
1 5
 
3.2%
6 2
 
1.3%
4 2
 
1.3%
3 1
 
0.6%

Length

2024-05-18T10:10:04.346512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:04.719257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 103
66.5%
na 42
27.1%
1 5
 
3.2%
6 2
 
1.3%
4 2
 
1.3%
3 1
 
0.6%

사용시작지상층
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
103 
<NA>
45 
1
 
6
6
 
1

Length

Max length4
Median length1
Mean length1.8709677
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 103
66.5%
<NA> 45
29.0%
1 6
 
3.9%
6 1
 
0.6%

Length

2024-05-18T10:10:05.299922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:05.751179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 103
66.5%
na 45
29.0%
1 6
 
3.9%
6 1
 
0.6%

사용끝지상층
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
131 
0
17 
2
 
3
1
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.5354839
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 131
84.5%
0 17
 
11.0%
2 3
 
1.9%
1 2
 
1.3%
4 1
 
0.6%
6 1
 
0.6%

Length

2024-05-18T10:10:06.183497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:06.608915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
84.5%
0 17
 
11.0%
2 3
 
1.9%
1 2
 
1.3%
4 1
 
0.6%
6 1
 
0.6%

사용시작지하층
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
97 
<NA>
43 
1
12 
2
 
3

Length

Max length4
Median length1
Mean length1.8322581
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 97
62.6%
<NA> 43
27.7%
1 12
 
7.7%
2 3
 
1.9%

Length

2024-05-18T10:10:07.024231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:07.422768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 97
62.6%
na 43
27.7%
1 12
 
7.7%
2 3
 
1.9%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
129 
0
 
11
1
 
9
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length3.4967742
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> 129
83.2%
0 11
 
7.1%
1 9
 
5.8%
2 4
 
2.6%
3 2
 
1.3%

Length

2024-05-18T10:10:08.022677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:08.422853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
83.2%
0 11
 
7.1%
1 9
 
5.8%
2 4
 
2.6%
3 2
 
1.3%

한실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
110 
<NA>
45 

Length

Max length4
Median length1
Mean length1.8709677
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 110
71.0%
<NA> 45
29.0%

Length

2024-05-18T10:10:08.835446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:09.205250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 110
71.0%
na 45
29.0%

양실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
110 
<NA>
45 

Length

Max length4
Median length1
Mean length1.8709677
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 110
71.0%
<NA> 45
29.0%

Length

2024-05-18T10:10:09.765516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:10.560576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 110
71.0%
na 45
29.0%

욕실수
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
104 
<NA>
40 
2
 
8
3
 
1
4
 
1

Length

Max length4
Median length1
Mean length1.7741935
Min length1

Unique

Unique3 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
67.1%
<NA> 40
 
25.8%
2 8
 
5.2%
3 1
 
0.6%
4 1
 
0.6%
1 1
 
0.6%

Length

2024-05-18T10:10:10.960819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:11.421013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
67.1%
na 40
 
25.8%
2 8
 
5.2%
3 1
 
0.6%
4 1
 
0.6%
1 1
 
0.6%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.4%
Missing11
Missing (%)7.1%
Memory size442.0 B
False
137 
True
 
7
(Missing)
 
11
ValueCountFrequency (%)
False 137
88.4%
True 7
 
4.5%
(Missing) 11
 
7.1%
2024-05-18T10:10:11.845469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
110 
<NA>
45 

Length

Max length4
Median length1
Mean length1.8709677
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 110
71.0%
<NA> 45
29.0%

Length

2024-05-18T10:10:12.370844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:12.840404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 110
71.0%
na 45
29.0%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-05-18T10:10:13.351888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length88
Mean length88
Min length88

Characters and Unicode

Total characters88
Distinct characters43
Distinct categories7 ?
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 row영업신고 수리는 임시사용승인기간(2005.2.28 ~ 2006.2.27)으로 하고 기간해제(사용검사 필)나 기간연장시는 자동으로 해제 또는 연장된것으로 본다.
ValueCountFrequency (%)
영업신고 1
 
7.1%
수리는 1
 
7.1%
임시사용승인기간(2005.2.28 1
 
7.1%
1
 
7.1%
2006.2.27)으로 1
 
7.1%
하고 1
 
7.1%
기간해제(사용검사 1
 
7.1%
필)나 1
 
7.1%
기간연장시는 1
 
7.1%
자동으로 1
 
7.1%
Other values (4) 4
28.6%
2024-05-18T10:10:14.368124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
14.8%
2 6
 
6.8%
. 5
 
5.7%
0 4
 
4.5%
기 3
 
3.4%
간 3
 
3.4%
로 3
 
3.4%
으 3
 
3.4%
는 3
 
3.4%
사 3
 
3.4%
Other values (33) 42
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51
58.0%
Decimal Number 14
 
15.9%
Space Separator 13
 
14.8%
Other Punctuation 5
 
5.7%
Close Punctuation 2
 
2.3%
Open Punctuation 2
 
2.3%
Math Symbol 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3
 
5.9%
간 3
 
5.9%
로 3
 
5.9%
으 3
 
5.9%
는 3
 
5.9%
사 3
 
5.9%
연 2
 
3.9%
장 2
 
3.9%
제 2
 
3.9%
해 2
 
3.9%
Other values (22) 25
49.0%
Decimal Number
ValueCountFrequency (%)
2 6
42.9%
0 4
28.6%
8 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%
5 1
 
7.1%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51
58.0%
Common 37
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3
 
5.9%
간 3
 
5.9%
로 3
 
5.9%
으 3
 
5.9%
는 3
 
5.9%
사 3
 
5.9%
연 2
 
3.9%
장 2
 
3.9%
제 2
 
3.9%
해 2
 
3.9%
Other values (22) 25
49.0%
Common
ValueCountFrequency (%)
13
35.1%
2 6
16.2%
. 5
 
13.5%
0 4
 
10.8%
) 2
 
5.4%
( 2
 
5.4%
8 1
 
2.7%
7 1
 
2.7%
6 1
 
2.7%
~ 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51
58.0%
ASCII 37
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
35.1%
2 6
16.2%
. 5
 
13.5%
0 4
 
10.8%
) 2
 
5.4%
( 2
 
5.4%
8 1
 
2.7%
7 1
 
2.7%
6 1
 
2.7%
~ 1
 
2.7%
Hangul
ValueCountFrequency (%)
기 3
 
5.9%
간 3
 
5.9%
로 3
 
5.9%
으 3
 
5.9%
는 3
 
5.9%
사 3
 
5.9%
연 2
 
3.9%
장 2
 
3.9%
제 2
 
3.9%
해 2
 
3.9%
Other values (22) 25
49.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
154 
20050304
 
1

Length

Max length8
Median length4
Mean length4.0258065
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> 154
99.4%
20050304 1
 
0.6%

Length

2024-05-18T10:10:14.953380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:15.422184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
99.4%
20050304 1
 
0.6%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
154 
20060227
 
1

Length

Max length8
Median length4
Mean length4.0258065
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> 154
99.4%
20060227 1
 
0.6%

Length

2024-05-18T10:10:15.877045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:16.318794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
99.4%
20060227 1
 
0.6%

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
임대
 
3

Length

Max length4
Median length4
Mean length3.9612903
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> 152
98.1%
임대 3
 
1.9%

Length

2024-05-18T10:10:16.792623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:17.249838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
98.1%
임대 3
 
1.9%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
130 
0
25 

Length

Max length4
Median length4
Mean length3.516129
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> 130
83.9%
0 25
 
16.1%

Length

2024-05-18T10:10:17.616934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:18.036101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
83.9%
0 25
 
16.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
6

Length

Max length4
Median length4
Mean length3.883871
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> 149
96.1%
0 6
 
3.9%

Length

2024-05-18T10:10:18.543786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:18.840540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
96.1%
0 6
 
3.9%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
6

Length

Max length4
Median length4
Mean length3.883871
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> 149
96.1%
0 6
 
3.9%

Length

2024-05-18T10:10:19.130454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:19.383741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
96.1%
0 6
 
3.9%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
131 
0
24 

Length

Max length4
Median length4
Mean length3.5354839
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> 131
84.5%
0 24
 
15.5%

Length

2024-05-18T10:10:19.763532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:20.167164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
84.5%
0 24
 
15.5%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
131 
0
24 

Length

Max length4
Median length4
Mean length3.5354839
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> 131
84.5%
0 24
 
15.5%

Length

2024-05-18T10:10:20.713188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:10:21.294897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
84.5%
0 24
 
15.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.4%
Missing11
Missing (%)7.1%
Memory size442.0 B
False
143 
True
 
1
(Missing)
 
11
ValueCountFrequency (%)
False 143
92.3%
True 1
 
0.6%
(Missing) 11
 
7.1%
2024-05-18T10:10:21.740757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030400003040000-202-1970-0002219700723<NA>3폐업2폐업20060901<NA><NA><NA>02 4974289126.30143902서울특별시 광진구 중곡동 196-11번지<NA><NA>도원탕2003-10-21 00:00:00I2018-08-31 23:59:59.0공동탕업207343.773689451935.251494공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130400003040000-202-1970-0003119700210<NA>3폐업2폐업20010601<NA><NA><NA>02 4663943211.06143846서울특별시 광진구 자양동 236-89번지<NA><NA>성춘탕2003-03-19 00:00:00I2018-08-31 23:59:59.0공동탕업205470.823904448324.268025공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230400003040000-202-1970-0003719700109<NA>3폐업2폐업20030704<NA><NA><NA>02 4661720504.88143840서울특별시 광진구 군자동 346-22번지<NA><NA>장안탕2002-09-07 00:00:00I2018-08-31 23:59:59.0공동탕업206168.205128449716.021289공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330400003040000-202-1970-0006419700904<NA>3폐업2폐업20150403<NA><NA><NA>02 444 1080342.59143960서울특별시 광진구 구의동 226-2번지서울특별시 광진구 구의로 65-1 (구의동)<NA>은호탕2013-03-15 11:37:28I2018-08-31 23:59:59.0공동탕업207899.235292449066.743743공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430400003040000-202-1970-0009319700902<NA>3폐업2폐업19910502<NA><NA><NA>02 4656512151.40143916서울특별시 광진구 화양동 33-34번지<NA><NA>화연탕2001-11-29 00:00:00I2018-08-31 23:59:59.0공동탕업206015.280336449180.408499공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530400003040000-202-1971-0003919711001<NA>3폐업2폐업20050427<NA><NA><NA>02 4662616132.21143837서울특별시 광진구 군자동 53-11번지<NA><NA>동원탕2002-09-25 00:00:00I2018-08-31 23:59:59.0공동탕업206615.761543450276.646167공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630400003040000-202-1971-0004819710216<NA>3폐업2폐업20020507<NA><NA><NA>02 4526405199.47143894서울특별시 광진구 중곡동 149-10번지<NA><NA>대신탕2002-07-31 00:00:00I2018-08-31 23:59:59.0공동탕업207534.328842450977.481203공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730400003040000-202-1971-0007219710927<NA>3폐업2폐업20060531<NA><NA><NA>0204576531197.79143852서울특별시 광진구 자양동 228-24번지<NA><NA>부광옥사우나2004-06-08 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
830400003040000-202-1972-0004219720128<NA>3폐업2폐업20170608<NA><NA><NA>02 4667383345.09143903서울특별시 광진구 중곡동 241-17번지서울특별시 광진구 긴고랑로 41 (중곡동)4910대화탕2017-06-08 13:40:48I2018-08-31 23:59:59.0공동탕업207080.733578451198.2759공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930400003040000-202-1972-0004419720904<NA>3폐업2폐업20140605<NA><NA><NA>02 4672162214.21143912서울특별시 광진구 중곡동 648-14번지서울특별시 광진구 능동로37길 6 (중곡동)4919라보탕2012-01-04 13:49:21I2018-08-31 23:59:59.0공동탕업206961.612379450659.222623공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14530400003040000-202-2010-0000120100210<NA>3폐업2폐업20140314<NA><NA><NA>02 452 801266.11143873서울특별시 광진구 자양동 662-5번지서울특별시 광진구 자양로5길 36, 지층 (자양동)5102스파목욕장2013-03-15 14:10:32I2018-08-31 23:59:59.0목욕장업 기타207332.900096447665.572094목욕장업 기타41<NA><NA>11000Y0<NA><NA><NA><NA>0<NA><NA>00N
14630400003040000-202-2010-0000220100819<NA>3폐업2폐업20190409<NA><NA><NA>02 498 8876571.42143840서울특별시 광진구 군자동 360-20번지서울특별시 광진구 광나루로 361 (군자동)5003광진사우나2019-04-09 14:14:17U2019-04-11 02:40:00.0공동탕업+찜질시설서비스영업206135.609363449591.55558공동탕업+찜질시설서비스영업2040011002Y0<NA><NA><NA><NA>0<NA><NA>00N
14730400003040000-202-2011-0000120110613<NA>3폐업2폐업20190409<NA><NA><NA>02 3424781266.00143200서울특별시 광진구 구의동 546-4번지 (프라임센터 12층)서울특별시 광진구 광나루로56길 85 (구의동,(프라임센터 12층))5116(주)아이에스휘트니스2019-04-09 14:10:40U2019-04-11 02:40:00.0목욕장업 기타208394.416382448165.28목욕장업 기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
14830400003040000-202-2017-0000120170529<NA>1영업/정상1영업<NA><NA><NA><NA>02 446 0117539.28143831서울특별시 광진구 구의동 596-5번지서울특별시 광진구 뚝섬로 742 (구의동)5115이안목욕탕2020-06-10 14:22:26U2020-06-12 02:40:00.0공동탕업208006.50481447998.92438공동탕업73<NA><NA>23002N0<NA><NA><NA>임대00000N
14930400003040000-202-2018-0000120180122<NA>1영업/정상1영업<NA><NA><NA><NA>02 4524455436.60143758서울특별시 광진구 자양동 227-7 더샵스타시티 지하1층, B100-1호서울특별시 광진구 아차산로 272, 더샵스타시티 지하1층 B100-1호 (자양동)5065주식회사 헬스보이컴퍼니2021-09-28 17:07:10U2021-09-30 02:40:00.0공동탕업206349.675048448396.939704공동탕업000011004N0<NA><NA><NA>임대00000Y
15030400003040000-202-2019-000012019-02-18<NA>3폐업2폐업2023-08-17<NA><NA><NA>02 450 4425257.34143-708서울특별시 광진구 광장동 22-1 워커힐호텔서울특별시 광진구 워커힐로 177, 워커힐호텔-매튜 1층 (광장동)4963매튜사우나2023-08-17 13:56:04U2022-12-07 23:09:00.0공동탕업209775.267832450327.577093<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15130400003040000-202-2019-0000220191219<NA>3폐업2폐업20200702<NA><NA><NA>02 456889833.84143875서울특별시 광진구 자양동 685 편안한요양병원서울특별시 광진구 자양로 38, 편안한요양병원 6층 (자양동)5112프라임스파2020-07-02 11:10:17U2020-07-04 02:40:00.0공동탕업207574.350933447709.275316공동탕업0066<NA><NA>001N0<NA><NA><NA><NA>00000N
15230400003040000-202-2020-0000120201228<NA>1영업/정상1영업<NA><NA><NA><NA>02 446 5300469.00143832서울특별시 광진구 구의동 611 구의현대2단지아파트서울특별시 광진구 광나루로56길 32, 수영장 지하2~3층 (구의동, 구의현대2단지아파트)5118현대프라임스포츠센타2022-04-21 10:22:23U2021-12-03 22:03:00.0공동탕업208403.746066448490.23918<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15330400003040000-202-2020-0000220201228<NA>1영업/정상1영업<NA><NA><NA><NA>02 456 4455220.00143723서울특별시 광진구 구의동 199-18 구의동삼성쉐르빌서울특별시 광진구 구의강변로 106, 지하층 B113호 (구의동, 구의동삼성쉐르빌)5117(주)비터스윗코리아2022-04-21 10:24:26U2021-12-03 22:03:00.0공동탕업208310.37226448631.437595<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15430400003040000-202-2022-0000120220719<NA>1영업/정상1영업<NA><NA><NA><NA><NA>157.00143814서울특별시 광진구 광장동 484 광장현대3단지아파트서울특별시 광진구 아차산로70길 62, 312동 B2층 (광장동, 광장현대3단지아파트)4974(주)비스코 헬스케어2022-07-19 16:24:07I2021-12-06 22:01:00.0목욕장업 기타208644.81921448711.72575<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>