Overview

Dataset statistics

Number of variables47
Number of observations404
Missing cells4335
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory159.1 KiB
Average record size in memory403.3 B

Variable types

Categorical19
Text8
DateTime4
Unsupported6
Numeric8
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-19974/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
건물소유구분명 is highly imbalanced (50.5%)Imbalance
남성종사자수 is highly imbalanced (66.2%)Imbalance
다중이용업소여부 is highly imbalanced (95.2%)Imbalance
인허가취소일자 has 404 (100.0%) missing valuesMissing
폐업일자 has 72 (17.8%) missing valuesMissing
휴업시작일자 has 404 (100.0%) missing valuesMissing
휴업종료일자 has 404 (100.0%) missing valuesMissing
재개업일자 has 404 (100.0%) missing valuesMissing
전화번호 has 61 (15.1%) missing valuesMissing
도로명주소 has 206 (51.0%) missing valuesMissing
도로명우편번호 has 212 (52.5%) missing valuesMissing
좌표정보(X) has 6 (1.5%) missing valuesMissing
좌표정보(Y) has 6 (1.5%) missing valuesMissing
건물지상층수 has 118 (29.2%) missing valuesMissing
건물지하층수 has 120 (29.7%) missing valuesMissing
사용시작지상층 has 198 (49.0%) missing valuesMissing
사용끝지상층 has 338 (83.7%) missing valuesMissing
욕실수 has 105 (26.0%) missing valuesMissing
발한실여부 has 33 (8.2%) missing valuesMissing
조건부허가신고사유 has 403 (99.8%) missing valuesMissing
조건부허가시작일자 has 404 (100.0%) missing valuesMissing
조건부허가종료일자 has 404 (100.0%) missing valuesMissing
다중이용업소여부 has 33 (8.2%) 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
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 233 (57.7%) zerosZeros
건물지하층수 has 243 (60.1%) zerosZeros
사용시작지상층 has 172 (42.6%) zerosZeros
사용끝지상층 has 39 (9.7%) zerosZeros
욕실수 has 164 (40.6%) zerosZeros

Reproduction

Analysis started2024-04-29 20:04:29.829507
Analysis finished2024-04-29 20:04:30.812189
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
3220000
404 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 404
100.0%

Length

2024-04-30T05:04:30.871650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:30.946953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 404
100.0%

관리번호
Text

UNIQUE 

Distinct404
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-30T05:04:31.094697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8888
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

Unique404 ?
Unique (%)100.0%

Sample

1st row3220000-202-1973-00299
2nd row3220000-202-1973-00300
3rd row3220000-202-1974-00301
4th row3220000-202-1975-00298
5th row3220000-202-1977-00293
ValueCountFrequency (%)
3220000-202-1973-00299 1
 
0.2%
3220000-202-2005-00005 1
 
0.2%
3220000-202-2006-00006 1
 
0.2%
3220000-202-2006-00005 1
 
0.2%
3220000-202-2006-00004 1
 
0.2%
3220000-202-2006-00003 1
 
0.2%
3220000-202-2006-00002 1
 
0.2%
3220000-202-2006-00001 1
 
0.2%
3220000-202-2005-00010 1
 
0.2%
3220000-202-2005-00009 1
 
0.2%
Other values (394) 394
97.5%
2024-04-30T05:04:31.370713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3610
40.6%
2 2057
23.1%
- 1212
 
13.6%
3 605
 
6.8%
1 462
 
5.2%
9 369
 
4.2%
8 187
 
2.1%
7 106
 
1.2%
4 106
 
1.2%
5 87
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7676
86.4%
Dash Punctuation 1212
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3610
47.0%
2 2057
26.8%
3 605
 
7.9%
1 462
 
6.0%
9 369
 
4.8%
8 187
 
2.4%
7 106
 
1.4%
4 106
 
1.4%
5 87
 
1.1%
6 87
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3610
40.6%
2 2057
23.1%
- 1212
 
13.6%
3 605
 
6.8%
1 462
 
5.2%
9 369
 
4.2%
8 187
 
2.1%
7 106
 
1.2%
4 106
 
1.2%
5 87
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3610
40.6%
2 2057
23.1%
- 1212
 
13.6%
3 605
 
6.8%
1 462
 
5.2%
9 369
 
4.2%
8 187
 
2.1%
7 106
 
1.2%
4 106
 
1.2%
5 87
 
1.0%
Distinct387
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum1973-10-18 00:00:00
Maximum2023-07-13 00:00:00
2024-04-30T05:04:31.500842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:04:31.632873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
3
332 
1
72 

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 (%)
3 332
82.2%
1 72
 
17.8%

Length

2024-04-30T05:04:31.737408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:31.828522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 332
82.2%
1 72
 
17.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
폐업
332 
영업/정상
72 

Length

Max length5
Median length2
Mean length2.5346535
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 332
82.2%
영업/정상 72
 
17.8%

Length

2024-04-30T05:04:31.924176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:32.020152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 332
82.2%
영업/정상 72
 
17.8%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2
332 
1
72 

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 (%)
2 332
82.2%
1 72
 
17.8%

Length

2024-04-30T05:04:32.120815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:32.215454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 332
82.2%
1 72
 
17.8%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
폐업
332 
영업
72 

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 332
82.2%
영업 72
 
17.8%

Length

2024-04-30T05:04:32.303592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:32.397109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 332
82.2%
영업 72
 
17.8%

폐업일자
Date

MISSING 

Distinct287
Distinct (%)86.4%
Missing72
Missing (%)17.8%
Memory size3.3 KiB
Minimum1991-12-31 00:00:00
Maximum2024-04-11 00:00:00
2024-04-30T05:04:32.515090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:04:32.637378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB

전화번호
Text

MISSING 

Distinct320
Distinct (%)93.3%
Missing61
Missing (%)15.1%
Memory size3.3 KiB
2024-04-30T05:04:32.883484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.125364
Min length2

Characters and Unicode

Total characters3473
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

Unique302 ?
Unique (%)88.0%

Sample

1st row02 5473904
2nd row02 5463858
3rd row02 5676817
4th row02 5681188
5th row02 5684485
ValueCountFrequency (%)
02 249
39.5%
00000 5
 
0.8%
542 4
 
0.6%
547 4
 
0.6%
4590573 4
 
0.6%
5557575 3
 
0.5%
5570111 3
 
0.5%
5406399 2
 
0.3%
552 2
 
0.3%
5523457 2
 
0.3%
Other values (332) 353
55.9%
2024-04-30T05:04:33.232377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 631
18.2%
5 541
15.6%
2 510
14.7%
351
10.1%
4 298
8.6%
1 265
7.6%
6 223
 
6.4%
3 199
 
5.7%
7 188
 
5.4%
8 138
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3122
89.9%
Space Separator 351
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 631
20.2%
5 541
17.3%
2 510
16.3%
4 298
9.5%
1 265
8.5%
6 223
 
7.1%
3 199
 
6.4%
7 188
 
6.0%
8 138
 
4.4%
9 129
 
4.1%
Space Separator
ValueCountFrequency (%)
351
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 631
18.2%
5 541
15.6%
2 510
14.7%
351
10.1%
4 298
8.6%
1 265
7.6%
6 223
 
6.4%
3 199
 
5.7%
7 188
 
5.4%
8 138
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 631
18.2%
5 541
15.6%
2 510
14.7%
351
10.1%
4 298
8.6%
1 265
7.6%
6 223
 
6.4%
3 199
 
5.7%
7 188
 
5.4%
8 138
 
4.0%
Distinct377
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-30T05:04:33.531191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.1262376
Min length3

Characters and Unicode

Total characters2475
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

Unique361 ?
Unique (%)89.4%

Sample

1st row428.01
2nd row.00
3rd row107.40
4th row240.70
5th row172.18
ValueCountFrequency (%)
00 9
 
2.2%
328.06 4
 
1.0%
261.42 3
 
0.7%
103.18 3
 
0.7%
453.44 2
 
0.5%
277.65 2
 
0.5%
328.99 2
 
0.5%
227.19 2
 
0.5%
168.00 2
 
0.5%
280.00 2
 
0.5%
Other values (367) 373
92.3%
2024-04-30T05:04:33.986531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 404
16.3%
0 379
15.3%
2 243
9.8%
1 240
9.7%
3 189
7.6%
5 176
7.1%
6 172
6.9%
9 161
 
6.5%
7 159
 
6.4%
4 158
 
6.4%
Other values (2) 194
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2031
82.1%
Other Punctuation 444
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 379
18.7%
2 243
12.0%
1 240
11.8%
3 189
9.3%
5 176
8.7%
6 172
8.5%
9 161
7.9%
7 159
7.8%
4 158
7.8%
8 154
7.6%
Other Punctuation
ValueCountFrequency (%)
. 404
91.0%
, 40
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2475
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 404
16.3%
0 379
15.3%
2 243
9.8%
1 240
9.7%
3 189
7.6%
5 176
7.1%
6 172
6.9%
9 161
 
6.5%
7 159
 
6.4%
4 158
 
6.4%
Other values (2) 194
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 404
16.3%
0 379
15.3%
2 243
9.8%
1 240
9.7%
3 189
7.6%
5 176
7.1%
6 172
6.9%
9 161
 
6.5%
7 159
 
6.4%
4 158
 
6.4%
Other values (2) 194
7.8%
Distinct145
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-30T05:04:34.305944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.049505
Min length6

Characters and Unicode

Total characters2444
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

Unique54 ?
Unique (%)13.4%

Sample

1st row135822
2nd row135948
3rd row135509
4th row135928
5th row135270
ValueCountFrequency (%)
135545 14
 
3.5%
135892 12
 
3.0%
135819 10
 
2.5%
135928 9
 
2.2%
135907 8
 
2.0%
135812 7
 
1.7%
135920 7
 
1.7%
135824 7
 
1.7%
135948 7
 
1.7%
135843 6
 
1.5%
Other values (135) 317
78.5%
2024-04-30T05:04:34.715276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 511
20.9%
1 507
20.7%
3 483
19.8%
8 288
11.8%
9 214
8.8%
2 115
 
4.7%
0 102
 
4.2%
4 84
 
3.4%
7 74
 
3.0%
6 46
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2424
99.2%
Dash Punctuation 20
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 511
21.1%
1 507
20.9%
3 483
19.9%
8 288
11.9%
9 214
8.8%
2 115
 
4.7%
0 102
 
4.2%
4 84
 
3.5%
7 74
 
3.1%
6 46
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 511
20.9%
1 507
20.7%
3 483
19.8%
8 288
11.8%
9 214
8.8%
2 115
 
4.7%
0 102
 
4.2%
4 84
 
3.4%
7 74
 
3.0%
6 46
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 511
20.9%
1 507
20.7%
3 483
19.8%
8 288
11.8%
9 214
8.8%
2 115
 
4.7%
0 102
 
4.2%
4 84
 
3.4%
7 74
 
3.0%
6 46
 
1.9%
Distinct369
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-30T05:04:34.963438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length25.131188
Min length18

Characters and Unicode

Total characters10153
Distinct characters187
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

Unique339 ?
Unique (%)83.9%

Sample

1st row서울특별시 강남구 논현동 122-8번지
2nd row서울특별시 강남구 청담동 3-21번지
3rd row서울특별시 강남구 삼성동 115-28번지
4th row서울특별시 강남구 역삼동 779-5번지
5th row서울특별시 강남구 도곡동 527-0번지
ValueCountFrequency (%)
서울특별시 404
21.5%
강남구 404
21.5%
논현동 94
 
5.0%
역삼동 86
 
4.6%
지하1층 56
 
3.0%
삼성동 51
 
2.7%
신사동 49
 
2.6%
대치동 48
 
2.6%
청담동 27
 
1.4%
지하2층 20
 
1.1%
Other values (470) 640
34.1%
2024-04-30T05:04:35.338321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1844
18.2%
472
 
4.6%
1 422
 
4.2%
410
 
4.0%
410
 
4.0%
409
 
4.0%
409
 
4.0%
407
 
4.0%
405
 
4.0%
404
 
4.0%
Other values (177) 4561
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5954
58.6%
Decimal Number 1898
 
18.7%
Space Separator 1844
 
18.2%
Dash Punctuation 364
 
3.6%
Other Punctuation 51
 
0.5%
Uppercase Letter 13
 
0.1%
Math Symbol 11
 
0.1%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
472
 
7.9%
410
 
6.9%
410
 
6.9%
409
 
6.9%
409
 
6.9%
407
 
6.8%
405
 
6.8%
404
 
6.8%
404
 
6.8%
404
 
6.8%
Other values (153) 1820
30.6%
Decimal Number
ValueCountFrequency (%)
1 422
22.2%
2 249
13.1%
6 178
9.4%
5 177
9.3%
7 158
 
8.3%
3 156
 
8.2%
0 150
 
7.9%
4 143
 
7.5%
9 136
 
7.2%
8 129
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
B 7
53.8%
T 1
 
7.7%
L 1
 
7.7%
G 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%
K 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 49
96.1%
. 2
 
3.9%
Space Separator
ValueCountFrequency (%)
1844
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5954
58.6%
Common 4186
41.2%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
472
 
7.9%
410
 
6.9%
410
 
6.9%
409
 
6.9%
409
 
6.9%
407
 
6.8%
405
 
6.8%
404
 
6.8%
404
 
6.8%
404
 
6.8%
Other values (153) 1820
30.6%
Common
ValueCountFrequency (%)
1844
44.1%
1 422
 
10.1%
- 364
 
8.7%
2 249
 
5.9%
6 178
 
4.3%
5 177
 
4.2%
7 158
 
3.8%
3 156
 
3.7%
0 150
 
3.6%
4 143
 
3.4%
Other values (7) 345
 
8.2%
Latin
ValueCountFrequency (%)
B 7
53.8%
T 1
 
7.7%
L 1
 
7.7%
G 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%
K 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5954
58.6%
ASCII 4199
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1844
43.9%
1 422
 
10.1%
- 364
 
8.7%
2 249
 
5.9%
6 178
 
4.2%
5 177
 
4.2%
7 158
 
3.8%
3 156
 
3.7%
0 150
 
3.6%
4 143
 
3.4%
Other values (14) 358
 
8.5%
Hangul
ValueCountFrequency (%)
472
 
7.9%
410
 
6.9%
410
 
6.9%
409
 
6.9%
409
 
6.9%
407
 
6.8%
405
 
6.8%
404
 
6.8%
404
 
6.8%
404
 
6.8%
Other values (153) 1820
30.6%

도로명주소
Text

MISSING 

Distinct187
Distinct (%)94.4%
Missing206
Missing (%)51.0%
Memory size3.3 KiB
2024-04-30T05:04:35.563833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length44
Mean length31.944444
Min length23

Characters and Unicode

Total characters6325
Distinct characters181
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

Unique179 ?
Unique (%)90.4%

Sample

1st row서울특별시 강남구 압구정로29길 71 (압구정동,,B상가)
2nd row서울특별시 강남구 봉은사로 150 (역삼동)
3rd row서울특별시 강남구 압구정로 216 (신사동,코끼리 상가 지하1층)
4th row서울특별시 강남구 개포로 310 (개포동)
5th row서울특별시 강남구 도곡로 510 (대치동,,3)
ValueCountFrequency (%)
서울특별시 198
 
16.9%
강남구 198
 
16.9%
지하1층 49
 
4.2%
논현동 40
 
3.4%
역삼동 29
 
2.5%
봉은사로 23
 
2.0%
지하2층 22
 
1.9%
대치동 16
 
1.4%
언주로 15
 
1.3%
논현로 12
 
1.0%
Other values (351) 569
48.6%
2024-04-30T05:04:35.907442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
973
 
15.4%
1 264
 
4.2%
220
 
3.5%
219
 
3.5%
213
 
3.4%
207
 
3.3%
, 205
 
3.2%
( 202
 
3.2%
) 202
 
3.2%
201
 
3.2%
Other values (171) 3419
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3775
59.7%
Space Separator 973
 
15.4%
Decimal Number 935
 
14.8%
Other Punctuation 207
 
3.3%
Open Punctuation 202
 
3.2%
Close Punctuation 202
 
3.2%
Uppercase Letter 15
 
0.2%
Math Symbol 10
 
0.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
220
 
5.8%
219
 
5.8%
213
 
5.6%
207
 
5.5%
201
 
5.3%
200
 
5.3%
199
 
5.3%
198
 
5.2%
198
 
5.2%
198
 
5.2%
Other values (147) 1722
45.6%
Decimal Number
ValueCountFrequency (%)
1 264
28.2%
2 155
16.6%
3 110
11.8%
4 75
 
8.0%
5 73
 
7.8%
0 72
 
7.7%
6 55
 
5.9%
7 50
 
5.3%
8 46
 
4.9%
9 35
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 9
60.0%
G 1
 
6.7%
T 1
 
6.7%
L 1
 
6.7%
K 1
 
6.7%
S 1
 
6.7%
A 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 205
99.0%
. 2
 
1.0%
Space Separator
ValueCountFrequency (%)
973
100.0%
Open Punctuation
ValueCountFrequency (%)
( 202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 202
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3775
59.7%
Common 2535
40.1%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
220
 
5.8%
219
 
5.8%
213
 
5.6%
207
 
5.5%
201
 
5.3%
200
 
5.3%
199
 
5.3%
198
 
5.2%
198
 
5.2%
198
 
5.2%
Other values (147) 1722
45.6%
Common
ValueCountFrequency (%)
973
38.4%
1 264
 
10.4%
, 205
 
8.1%
( 202
 
8.0%
) 202
 
8.0%
2 155
 
6.1%
3 110
 
4.3%
4 75
 
3.0%
5 73
 
2.9%
0 72
 
2.8%
Other values (7) 204
 
8.0%
Latin
ValueCountFrequency (%)
B 9
60.0%
G 1
 
6.7%
T 1
 
6.7%
L 1
 
6.7%
K 1
 
6.7%
S 1
 
6.7%
A 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3775
59.7%
ASCII 2550
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
973
38.2%
1 264
 
10.4%
, 205
 
8.0%
( 202
 
7.9%
) 202
 
7.9%
2 155
 
6.1%
3 110
 
4.3%
4 75
 
2.9%
5 73
 
2.9%
0 72
 
2.8%
Other values (14) 219
 
8.6%
Hangul
ValueCountFrequency (%)
220
 
5.8%
219
 
5.8%
213
 
5.6%
207
 
5.5%
201
 
5.3%
200
 
5.3%
199
 
5.3%
198
 
5.2%
198
 
5.2%
198
 
5.2%
Other values (147) 1722
45.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)62.5%
Missing212
Missing (%)52.5%
Infinite0
Infinite (%)0.0%
Mean6156.0938
Minimum6002
Maximum6377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:36.028365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6002
5-th percentile6026
Q16070.5
median6133.5
Q36232.25
95-th percentile6333.25
Maximum6377
Range375
Interquartile range (IQR)161.75

Descriptive statistics

Standard deviation97.311943
Coefficient of variation (CV)0.015807417
Kurtosis-0.96852222
Mean6156.0938
Median Absolute Deviation (MAD)77
Skewness0.36853755
Sum1181970
Variance9469.6142
MonotonicityNot monotonic
2024-04-30T05:04:36.162613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6226 6
 
1.5%
6199 5
 
1.2%
6120 5
 
1.2%
6071 4
 
1.0%
6038 4
 
1.0%
6122 4
 
1.0%
6114 4
 
1.0%
6124 4
 
1.0%
6062 4
 
1.0%
6054 3
 
0.7%
Other values (110) 149
36.9%
(Missing) 212
52.5%
ValueCountFrequency (%)
6002 1
0.2%
6005 1
0.2%
6014 1
0.2%
6017 2
0.5%
6018 1
0.2%
6022 1
0.2%
6023 1
0.2%
6025 1
0.2%
6026 2
0.5%
6027 1
0.2%
ValueCountFrequency (%)
6377 1
 
0.2%
6366 1
 
0.2%
6349 1
 
0.2%
6343 1
 
0.2%
6341 1
 
0.2%
6339 1
 
0.2%
6337 1
 
0.2%
6336 3
0.7%
6331 1
 
0.2%
6329 1
 
0.2%
Distinct365
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-30T05:04:36.386882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length5.6757426
Min length1

Characters and Unicode

Total characters2293
Distinct characters310
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)82.9%

Sample

1st row영동상가탕
2nd row다미향탕
3rd row삼성탕
4th row삼보탕
5th row충무탕
ValueCountFrequency (%)
사우나 15
 
3.3%
강남탕 4
 
0.9%
수양 4
 
0.9%
스타사우나 3
 
0.7%
강남사우나 3
 
0.7%
스파 3
 
0.7%
한증막 3
 
0.7%
서울 3
 
0.7%
낙원탕 3
 
0.7%
광일탕 3
 
0.7%
Other values (383) 416
90.4%
2024-04-30T05:04:36.693384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
5.2%
119
 
5.2%
115
 
5.0%
112
 
4.9%
81
 
3.5%
57
 
2.5%
48
 
2.1%
47
 
2.0%
41
 
1.8%
38
 
1.7%
Other values (300) 1515
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2153
93.9%
Space Separator 57
 
2.5%
Close Punctuation 22
 
1.0%
Open Punctuation 22
 
1.0%
Uppercase Letter 18
 
0.8%
Decimal Number 12
 
0.5%
Lowercase Letter 8
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
120
 
5.6%
119
 
5.5%
115
 
5.3%
112
 
5.2%
81
 
3.8%
48
 
2.2%
47
 
2.2%
41
 
1.9%
38
 
1.8%
35
 
1.6%
Other values (272) 1397
64.9%
Uppercase Letter
ValueCountFrequency (%)
M 3
16.7%
A 3
16.7%
C 3
16.7%
S 2
11.1%
Y 1
 
5.6%
K 1
 
5.6%
Z 1
 
5.6%
E 1
 
5.6%
T 1
 
5.6%
F 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
p 1
12.5%
m 1
12.5%
n 1
12.5%
e 1
12.5%
d 1
12.5%
a 1
12.5%
r 1
12.5%
o 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 4
33.3%
4 4
33.3%
5 2
16.7%
3 1
 
8.3%
6 1
 
8.3%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2153
93.9%
Common 114
 
5.0%
Latin 26
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
120
 
5.6%
119
 
5.5%
115
 
5.3%
112
 
5.2%
81
 
3.8%
48
 
2.2%
47
 
2.2%
41
 
1.9%
38
 
1.8%
35
 
1.6%
Other values (272) 1397
64.9%
Latin
ValueCountFrequency (%)
M 3
 
11.5%
A 3
 
11.5%
C 3
 
11.5%
S 2
 
7.7%
Y 1
 
3.8%
K 1
 
3.8%
p 1
 
3.8%
Z 1
 
3.8%
E 1
 
3.8%
T 1
 
3.8%
Other values (9) 9
34.6%
Common
ValueCountFrequency (%)
57
50.0%
) 22
 
19.3%
( 22
 
19.3%
2 4
 
3.5%
4 4
 
3.5%
5 2
 
1.8%
3 1
 
0.9%
6 1
 
0.9%
? 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2153
93.9%
ASCII 140
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
120
 
5.6%
119
 
5.5%
115
 
5.3%
112
 
5.2%
81
 
3.8%
48
 
2.2%
47
 
2.2%
41
 
1.9%
38
 
1.8%
35
 
1.6%
Other values (272) 1397
64.9%
ASCII
ValueCountFrequency (%)
57
40.7%
) 22
 
15.7%
( 22
 
15.7%
2 4
 
2.9%
4 4
 
2.9%
M 3
 
2.1%
A 3
 
2.1%
C 3
 
2.1%
5 2
 
1.4%
S 2
 
1.4%
Other values (18) 18
 
12.9%
Distinct305
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum1999-02-02 00:00:00
Maximum2024-04-11 14:09:12
2024-04-30T05:04:36.826694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:04:37.149051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
I
304 
U
100 

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 304
75.2%
U 100
 
24.8%

Length

2024-04-30T05:04:37.269198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:37.347629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 304
75.2%
u 100
 
24.8%
Distinct92
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:03:00
2024-04-30T05:04:37.446060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:04:37.568155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
공동탕업
285 
목욕장업 기타
56 
한증막업
44 
공동탕업+찜질시설서비스영업
 
11
찜질시설서비스영업
 
8

Length

Max length14
Median length4
Mean length4.7871287
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 285
70.5%
목욕장업 기타 56
 
13.9%
한증막업 44
 
10.9%
공동탕업+찜질시설서비스영업 11
 
2.7%
찜질시설서비스영업 8
 
2.0%

Length

2024-04-30T05:04:37.689319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:37.783143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 285
62.0%
목욕장업 56
 
12.2%
기타 56
 
12.2%
한증막업 44
 
9.6%
공동탕업+찜질시설서비스영업 11
 
2.4%
찜질시설서비스영업 8
 
1.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct273
Distinct (%)68.6%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean203711.43
Minimum201621.77
Maximum209260.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:37.899918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201621.77
5-th percentile201955.79
Q1202657.99
median203479.29
Q3204620.65
95-th percentile205946.61
Maximum209260.8
Range7639.0328
Interquartile range (IQR)1962.66

Descriptive statistics

Standard deviation1366.4617
Coefficient of variation (CV)0.0067078303
Kurtosis1.2530285
Mean203711.43
Median Absolute Deviation (MAD)967.97689
Skewness0.98014198
Sum81077147
Variance1867217.5
MonotonicityNot monotonic
2024-04-30T05:04:38.021899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203848.249311066 5
 
1.2%
202378.390574465 5
 
1.2%
203901.878812978 5
 
1.2%
204324.263443033 4
 
1.0%
202962.441804948 4
 
1.0%
202422.404397085 4
 
1.0%
202220.14 4
 
1.0%
202708.424437436 4
 
1.0%
207563.895 4
 
1.0%
203034.658805791 4
 
1.0%
Other values (263) 355
87.9%
(Missing) 6
 
1.5%
ValueCountFrequency (%)
201621.76711437 2
0.5%
201658.416590861 1
 
0.2%
201733.702293954 1
 
0.2%
201749.456413619 1
 
0.2%
201782.10122745 2
0.5%
201794.159357626 1
 
0.2%
201812.63828808 2
0.5%
201823.394492126 1
 
0.2%
201828.756638827 2
0.5%
201881.31429345 3
0.7%
ValueCountFrequency (%)
209260.799930773 1
 
0.2%
209016.60879649 1
 
0.2%
208937.760652081 1
 
0.2%
207914.471699463 1
 
0.2%
207563.895 4
1.0%
207231.166556636 2
0.5%
207139.307975369 1
 
0.2%
206970.919291372 2
0.5%
206857.136167987 1
 
0.2%
206794.144841917 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct273
Distinct (%)68.6%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean445060.74
Minimum439882.12
Maximum447864.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:38.148994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439882.12
5-th percentile442738.66
Q1444115.3
median445029.82
Q3446141.27
95-th percentile447020.66
Maximum447864.76
Range7982.6454
Interquartile range (IQR)2025.9662

Descriptive statistics

Standard deviation1346.2763
Coefficient of variation (CV)0.0030249271
Kurtosis-0.16876537
Mean445060.74
Median Absolute Deviation (MAD)1059.8824
Skewness-0.34457022
Sum1.7713417 × 108
Variance1812459.8
MonotonicityNot monotonic
2024-04-30T05:04:38.265804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443834.310545284 5
 
1.2%
446705.197148871 5
 
1.2%
446783.967552696 5
 
1.2%
445580.187539001 4
 
1.0%
447371.866295615 4
 
1.0%
444877.223579374 4
 
1.0%
444805.625 4
 
1.0%
445478.950854571 4
 
1.0%
443559.94 4
 
1.0%
446445.535888377 4
 
1.0%
Other values (263) 355
87.9%
(Missing) 6
 
1.5%
ValueCountFrequency (%)
439882.118303183 1
0.2%
440934.812128081 1
0.2%
441761.986429568 2
0.5%
441815.822474066 2
0.5%
442307.749979092 1
0.2%
442329.621421183 1
0.2%
442405.135283439 1
0.2%
442495.244980358 2
0.5%
442546.552791506 2
0.5%
442550.634567769 1
0.2%
ValueCountFrequency (%)
447864.763737276 1
 
0.2%
447748.161018109 1
 
0.2%
447649.978394541 2
0.5%
447371.866295615 4
1.0%
447334.651098516 1
 
0.2%
447313.362226154 1
 
0.2%
447247.654297357 1
 
0.2%
447231.954885143 1
 
0.2%
447187.183943078 1
 
0.2%
447092.815391301 1
 
0.2%

위생업태명
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
공동탕업
267 
목욕장업 기타
47 
한증막업
42 
<NA>
33 
찜질시설서비스영업
 
8

Length

Max length14
Median length4
Mean length4.6212871
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 267
66.1%
목욕장업 기타 47
 
11.6%
한증막업 42
 
10.4%
<NA> 33
 
8.2%
찜질시설서비스영업 8
 
2.0%
공동탕업+찜질시설서비스영업 7
 
1.7%

Length

2024-04-30T05:04:38.389603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:38.500412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 267
59.2%
목욕장업 47
 
10.4%
기타 47
 
10.4%
한증막업 42
 
9.3%
na 33
 
7.3%
찜질시설서비스영업 8
 
1.8%
공동탕업+찜질시설서비스영업 7
 
1.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)6.3%
Missing118
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.3706294
Minimum0
Maximum26
Zeros233
Zeros (%)57.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:38.620148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.75
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.673859
Coefficient of variation (CV)2.6804175
Kurtosis15.593083
Mean1.3706294
Median Absolute Deviation (MAD)0
Skewness3.6522955
Sum392
Variance13.49724
MonotonicityNot monotonic
2024-04-30T05:04:38.730070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 233
57.7%
5 13
 
3.2%
6 10
 
2.5%
4 6
 
1.5%
3 3
 
0.7%
2 2
 
0.5%
1 2
 
0.5%
13 2
 
0.5%
8 2
 
0.5%
18 2
 
0.5%
Other values (8) 11
 
2.7%
(Missing) 118
29.2%
ValueCountFrequency (%)
0 233
57.7%
1 2
 
0.5%
2 2
 
0.5%
3 3
 
0.7%
4 6
 
1.5%
5 13
 
3.2%
6 10
 
2.5%
7 2
 
0.5%
8 2
 
0.5%
9 1
 
0.2%
ValueCountFrequency (%)
26 1
0.2%
22 1
0.2%
20 1
0.2%
18 2
0.5%
14 2
0.5%
13 2
0.5%
11 1
0.2%
10 2
0.5%
9 1
0.2%
8 2
0.5%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.8%
Missing120
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean0.3556338
Minimum0
Maximum7
Zeros243
Zeros (%)60.1%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:38.822144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0881322
Coefficient of variation (CV)3.0596986
Kurtosis16.42584
Mean0.3556338
Median Absolute Deviation (MAD)0
Skewness3.8799836
Sum101
Variance1.1840318
MonotonicityNot monotonic
2024-04-30T05:04:38.923491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 243
60.1%
1 16
 
4.0%
2 11
 
2.7%
4 5
 
1.2%
3 4
 
1.0%
6 2
 
0.5%
7 2
 
0.5%
5 1
 
0.2%
(Missing) 120
29.7%
ValueCountFrequency (%)
0 243
60.1%
1 16
 
4.0%
2 11
 
2.7%
3 4
 
1.0%
4 5
 
1.2%
5 1
 
0.2%
6 2
 
0.5%
7 2
 
0.5%
ValueCountFrequency (%)
7 2
 
0.5%
6 2
 
0.5%
5 1
 
0.2%
4 5
 
1.2%
3 4
 
1.0%
2 11
 
2.7%
1 16
 
4.0%
0 243
60.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.4%
Missing198
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean0.41262136
Minimum0
Maximum6
Zeros172
Zeros (%)42.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:39.027775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.095283
Coefficient of variation (CV)2.6544505
Kurtosis10.243288
Mean0.41262136
Median Absolute Deviation (MAD)0
Skewness3.126974
Sum85
Variance1.1996448
MonotonicityNot monotonic
2024-04-30T05:04:39.112679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 172
42.6%
2 14
 
3.5%
1 8
 
2.0%
3 6
 
1.5%
5 3
 
0.7%
6 2
 
0.5%
4 1
 
0.2%
(Missing) 198
49.0%
ValueCountFrequency (%)
0 172
42.6%
1 8
 
2.0%
2 14
 
3.5%
3 6
 
1.5%
4 1
 
0.2%
5 3
 
0.7%
6 2
 
0.5%
ValueCountFrequency (%)
6 2
 
0.5%
5 3
 
0.7%
4 1
 
0.2%
3 6
 
1.5%
2 14
 
3.5%
1 8
 
2.0%
0 172
42.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.6%
Missing338
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean1.4090909
Minimum0
Maximum7
Zeros39
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:39.199025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.9452291
Coefficient of variation (CV)1.3804851
Kurtosis0.64949971
Mean1.4090909
Median Absolute Deviation (MAD)0
Skewness1.208407
Sum93
Variance3.7839161
MonotonicityNot monotonic
2024-04-30T05:04:39.289166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 39
 
9.7%
3 12
 
3.0%
2 7
 
1.7%
5 3
 
0.7%
4 2
 
0.5%
7 2
 
0.5%
6 1
 
0.2%
(Missing) 338
83.7%
ValueCountFrequency (%)
0 39
9.7%
2 7
 
1.7%
3 12
 
3.0%
4 2
 
0.5%
5 3
 
0.7%
6 1
 
0.2%
7 2
 
0.5%
ValueCountFrequency (%)
7 2
 
0.5%
6 1
 
0.2%
5 3
 
0.7%
4 2
 
0.5%
3 12
 
3.0%
2 7
 
1.7%
0 39
9.7%
Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
175 
0
165 
1
46 
2
 
16
3
 
2

Length

Max length4
Median length1
Mean length2.299505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 175
43.3%
0 165
40.8%
1 46
 
11.4%
2 16
 
4.0%
3 2
 
0.5%

Length

2024-04-30T05:04:39.411655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:39.519948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 175
43.3%
0 165
40.8%
1 46
 
11.4%
2 16
 
4.0%
3 2
 
0.5%
Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
311 
1
41 
0
 
27
2
 
21
3
 
4

Length

Max length4
Median length4
Mean length3.3094059
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> 311
77.0%
1 41
 
10.1%
0 27
 
6.7%
2 21
 
5.2%
3 4
 
1.0%

Length

2024-04-30T05:04:39.641032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:39.745626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 311
77.0%
1 41
 
10.1%
0 27
 
6.7%
2 21
 
5.2%
3 4
 
1.0%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
258 
<NA>
146 

Length

Max length4
Median length1
Mean length2.0841584
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 258
63.9%
<NA> 146
36.1%

Length

2024-04-30T05:04:39.865004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:39.965561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 258
63.9%
na 146
36.1%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
258 
<NA>
146 

Length

Max length4
Median length1
Mean length2.0841584
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 258
63.9%
<NA> 146
36.1%

Length

2024-04-30T05:04:40.069532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:40.154931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 258
63.9%
na 146
36.1%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)4.0%
Missing105
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean1.3411371
Minimum0
Maximum16
Zeros164
Zeros (%)40.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-30T05:04:40.230624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.277114
Coefficient of variation (CV)1.697898
Kurtosis8.9026426
Mean1.3411371
Median Absolute Deviation (MAD)0
Skewness2.6410775
Sum401
Variance5.1852484
MonotonicityNot monotonic
2024-04-30T05:04:40.329393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 164
40.6%
1 44
 
10.9%
2 42
 
10.4%
3 12
 
3.0%
4 10
 
2.5%
6 8
 
2.0%
5 6
 
1.5%
8 5
 
1.2%
7 3
 
0.7%
11 2
 
0.5%
Other values (2) 3
 
0.7%
(Missing) 105
26.0%
ValueCountFrequency (%)
0 164
40.6%
1 44
 
10.9%
2 42
 
10.4%
3 12
 
3.0%
4 10
 
2.5%
5 6
 
1.5%
6 8
 
2.0%
7 3
 
0.7%
8 5
 
1.2%
10 2
 
0.5%
ValueCountFrequency (%)
16 1
 
0.2%
11 2
 
0.5%
10 2
 
0.5%
8 5
 
1.2%
7 3
 
0.7%
6 8
 
2.0%
5 6
 
1.5%
4 10
 
2.5%
3 12
 
3.0%
2 42
10.4%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.5%
Missing33
Missing (%)8.2%
Memory size940.0 B
False
312 
True
59 
(Missing)
33 
ValueCountFrequency (%)
False 312
77.2%
True 59
 
14.6%
(Missing) 33
 
8.2%
2024-04-30T05:04:40.418707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
258 
<NA>
145 
6
 
1

Length

Max length4
Median length1
Mean length2.0767327
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 258
63.9%
<NA> 145
35.9%
6 1
 
0.2%

Length

2024-04-30T05:04:40.512103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:40.597009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 258
63.9%
na 145
35.9%
6 1
 
0.2%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing403
Missing (%)99.8%
Memory size3.3 KiB
2024-04-30T05:04:40.725538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row지위승계신청보류
ValueCountFrequency (%)
지위승계신청보류 1
100.0%
2024-04-30T05:04:40.952156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing404
Missing (%)100.0%
Memory size3.7 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
338 
임대
47 
자가
 
19

Length

Max length4
Median length4
Mean length3.6732673
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> 338
83.7%
임대 47
 
11.6%
자가 19
 
4.7%

Length

2024-04-30T05:04:41.077625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:41.182584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 338
83.7%
임대 47
 
11.6%
자가 19
 
4.7%

세탁기수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
284 
0
120 

Length

Max length4
Median length4
Mean length3.1089109
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> 284
70.3%
0 120
29.7%

Length

2024-04-30T05:04:41.274330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:41.358443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 284
70.3%
0 120
29.7%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
357 
0
47 

Length

Max length4
Median length4
Mean length3.6509901
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> 357
88.4%
0 47
 
11.6%

Length

2024-04-30T05:04:41.457176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:41.544487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 357
88.4%
0 47
 
11.6%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
357 
0
46 
1
 
1

Length

Max length4
Median length4
Mean length3.6509901
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 357
88.4%
0 46
 
11.4%
1 1
 
0.2%

Length

2024-04-30T05:04:41.646522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:41.736061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 357
88.4%
0 46
 
11.4%
1 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
302 
0
102 

Length

Max length4
Median length4
Mean length3.2425743
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> 302
74.8%
0 102
 
25.2%

Length

2024-04-30T05:04:41.827061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:41.926218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 302
74.8%
0 102
 
25.2%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
302 
0
102 

Length

Max length4
Median length4
Mean length3.2425743
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> 302
74.8%
0 102
 
25.2%

Length

2024-04-30T05:04:42.027939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:42.328701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 302
74.8%
0 102
 
25.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing33
Missing (%)8.2%
Memory size940.0 B
False
369 
True
 
2
(Missing)
 
33
ValueCountFrequency (%)
False 369
91.3%
True 2
 
0.5%
(Missing) 33
 
8.2%
2024-04-30T05:04:42.401596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032200003220000-202-1973-0029919731119<NA>3폐업2폐업20021017<NA><NA><NA>02 5473904428.01135822서울특별시 강남구 논현동 122-8번지<NA><NA>영동상가탕2002-10-26 00:00:00I2018-08-31 23:59:59.0공동탕업202010.01034445368.131755공동탕업401<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132200003220000-202-1973-0030019731018<NA>3폐업2폐업19960304<NA><NA><NA>02 5463858.00135948서울특별시 강남구 청담동 3-21번지<NA><NA>다미향탕2001-08-03 00:00:00I2018-08-31 23:59:59.0공동탕업203611.536802446736.048729공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232200003220000-202-1974-0030119741021<NA>3폐업2폐업20050502<NA><NA><NA>02 5676817107.40135509서울특별시 강남구 삼성동 115-28번지<NA><NA>삼성탕2001-11-15 00:00:00I2018-08-31 23:59:59.0공동탕업204384.977691445523.738755공동탕업502<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332200003220000-202-1975-0029819751210<NA>3폐업2폐업20061019<NA><NA><NA>02 5681188240.70135928서울특별시 강남구 역삼동 779-5번지<NA><NA>삼보탕2002-11-27 00:00:00I2018-08-31 23:59:59.0공동탕업203942.743843443773.130888공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432200003220000-202-1977-0029319771117<NA>3폐업2폐업20020506<NA><NA><NA>02 5684485172.18135270서울특별시 강남구 도곡동 527-0번지<NA><NA>충무탕2002-06-26 00:00:00I2018-08-31 23:59:59.0공동탕업204400.333433443483.209967공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532200003220000-202-1977-0030219770919<NA>3폐업2폐업19970722<NA><NA><NA>02 5571667208.35135841서울특별시 강남구 대치동 904-12번지<NA><NA>대치탕2002-03-14 00:00:00I2018-08-31 23:59:59.0공동탕업204915.673076444488.265184공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632200003220000-202-1978-0020719780628<NA>1영업/정상1영업<NA><NA><NA><NA>02 5439694247.00135110서울특별시 강남구 압구정동 369-1번지 ,B상가서울특별시 강남구 압구정로29길 71 (압구정동,,B상가)6002이조한증막2003-03-15 00:00:00I2018-08-31 23:59:59.0한증막업202398.594378447864.763737한증막업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732200003220000-202-1978-0020819781204<NA>3폐업2폐업19950731<NA><NA><NA>02 5428240.00135897서울특별시 강남구 신사동 660-6번지<NA><NA>한양한증막2001-08-03 00:00:00I2018-08-31 23:59:59.0한증막업203257.555575447334.651099한증막업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832200003220000-202-1978-0030319781223<NA>3폐업2폐업20020411<NA><NA><NA>0205577740117.39135835서울특별시 강남구 대치동 259-15번지<NA><NA>한양탕2002-04-11 00:00:00I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업502<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932200003220000-202-1979-0020019790328<NA>3폐업2폐업20050915<NA><NA><NA>02 5420112319.08135812서울특별시 강남구 논현동 6-0번지 지상2층,지상3층<NA><NA>영동사우나2004-11-19 00:00:00I2018-08-31 23:59:59.0공동탕업202108.433847446160.61824공동탕업<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
39432200003220000-202-2021-0000320210330<NA>1영업/정상1영업<NA><NA><NA><NA><NA>912.75135896서울특별시 강남구 신사동 638-13 쌍봉빌딩서울특별시 강남구 언주로 874, 쌍봉빌딩 지하1층 (신사동)6017더원사우나2021-03-30 16:45:39I2021-04-01 00:22:58.0공동탕업202962.441805447371.866296공동탕업00<NA><NA><NA><NA>008N0<NA><NA><NA><NA>00000N
39532200003220000-202-2021-000042021-05-06<NA>1영업/정상1영업<NA><NA><NA><NA>02 727 7361310.07135-915서울특별시 강남구 역삼동 676 센터필드서울특별시 강남구 테헤란로 231, 센터필드 26층 (역삼동)6142(주)조선호텔앤리조트 조선팰리스강남 사우나2023-12-07 17:37:12U2022-11-02 00:09:00.0공동탕업203599.062772444556.062267<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39632200003220000-202-2021-0000520210625<NA>1영업/정상1영업<NA><NA><NA><NA><NA>456.74135819서울특별시 강남구 논현동 98-6서울특별시 강남구 언주로148길 6, 지하1층,2층 (논현동)6057케렌시아사우나2021-06-25 16:47:06I2021-06-27 00:23:03.0찜질시설서비스영업203034.658806446445.535888찜질시설서비스영업00<NA><NA>12001N0<NA><NA><NA><NA>00000N
39732200003220000-202-2021-0000620211008<NA>3폐업2폐업20220221<NA><NA><NA><NA>103.18135928서울특별시 강남구 역삼동 774-43서울특별시 강남구 도곡로37길 45, 지하1층 (역삼동)6226수양사우나2022-02-21 14:59:39U2022-02-23 02:40:00.0공동탕업203848.249311443834.310545공동탕업000011001Y0<NA><NA><NA><NA>00000N
39832200003220000-202-2021-0000720211118<NA>1영업/정상1영업<NA><NA><NA><NA><NA>289.00135860서울특별시 강남구 도곡동 949-3 캠코양재타워서울특별시 강남구 강남대로 262, 캠코양재타워 지하3층 (도곡동)6265자마이카 피트니스2021-11-18 16:41:18I2021-11-20 00:22:44.0공동탕업202880.352623442776.692189공동탕업000033003N0<NA><NA><NA><NA>00000N
39932200003220000-202-2021-0000820211209<NA>1영업/정상1영업<NA><NA><NA><NA>02 518 2113363.66135996서울특별시 강남구 논현동 211-21서울특별시 강남구 언주로 641, 지하2층 (논현동)6105펜트힐 사우나2021-12-09 16:00:01I2021-12-11 00:22:54.0공동탕업+찜질시설서비스영업203021.909102445735.022021공동탕업+찜질시설서비스영업000022002N0<NA><NA><NA><NA>00000N
40032200003220000-202-2021-0000920211217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>297.00135555서울특별시 강남구 도곡동 467-24 우성캐릭터199서울특별시 강남구 언주로 118, 지하1층 스포라인호 (도곡동, 우성캐릭터199)6295(주)자마이카 휘트니스2021-12-17 11:33:28I2021-12-19 00:22:42.0공동탕업204518.87998442703.584824공동탕업000011001N0<NA><NA><NA><NA>00000N
40132200003220000-202-2021-0001020211230<NA>1영업/정상1영업<NA><NA><NA><NA><NA>171.18135934서울특별시 강남구 역삼동 825-30 강남 캠퍼스호텔서울특별시 강남구 테헤란로2길 13, 강남 캠퍼스호텔 지하1층 (역삼동)6232리프레쉬2021-12-30 14:53:26I2022-01-01 00:22:41.0찜질시설서비스영업202511.316147443900.589322찜질시설서비스영업000011001N0<NA><NA><NA><NA>00000N
40232200003220000-202-2022-000012022-03-11<NA>3폐업2폐업2023-06-05<NA><NA><NA><NA>103.18135-928서울특별시 강남구 역삼동 774-43서울특별시 강남구 도곡로37길 45, 지하1층 (역삼동)6226수양2023-06-05 13:21:24U2022-12-06 00:08:00.0공동탕업203848.249311443834.310545<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
40332200003220000-202-2023-000012023-07-13<NA>3폐업2폐업2023-12-06<NA><NA><NA><NA>103.18135-928서울특별시 강남구 역삼동 774-43서울특별시 강남구 도곡로37길 45, 지하1층 (역삼동)6226수양2023-12-06 16:34:23U2022-11-02 00:08:00.0공동탕업203848.249311443834.310545<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>