Overview

Dataset statistics

Number of variables47
Number of observations250
Missing cells2364
Missing cells (%)20.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory98.8 KiB
Average record size in memory404.5 B

Variable types

Categorical19
Text7
DateTime4
Unsupported5
Numeric10
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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-17443/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 is highly imbalanced (58.0%)Imbalance
조건부허가시작일자 is highly imbalanced (96.2%)Imbalance
조건부허가종료일자 is highly imbalanced (96.2%)Imbalance
여성종사자수 is highly imbalanced (84.7%)Imbalance
남성종사자수 is highly imbalanced (84.7%)Imbalance
다중이용업소여부 is highly imbalanced (95.2%)Imbalance
인허가취소일자 has 250 (100.0%) missing valuesMissing
폐업일자 has 113 (45.2%) missing valuesMissing
휴업시작일자 has 250 (100.0%) missing valuesMissing
휴업종료일자 has 250 (100.0%) missing valuesMissing
재개업일자 has 250 (100.0%) missing valuesMissing
전화번호 has 11 (4.4%) missing valuesMissing
도로명주소 has 92 (36.8%) missing valuesMissing
도로명우편번호 has 97 (38.8%) missing valuesMissing
좌표정보(X) has 12 (4.8%) missing valuesMissing
좌표정보(Y) has 12 (4.8%) missing valuesMissing
건물지상층수 has 69 (27.6%) missing valuesMissing
사용시작지상층 has 72 (28.8%) missing valuesMissing
사용끝지상층 has 103 (41.2%) missing valuesMissing
한실수 has 72 (28.8%) missing valuesMissing
양실수 has 104 (41.6%) missing valuesMissing
욕실수 has 110 (44.0%) missing valuesMissing
발한실여부 has 62 (24.8%) missing valuesMissing
좌석수 has 120 (48.0%) missing valuesMissing
조건부허가신고사유 has 250 (100.0%) missing valuesMissing
다중이용업소여부 has 62 (24.8%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 36 (14.4%) zerosZeros
사용시작지상층 has 35 (14.0%) zerosZeros
한실수 has 24 (9.6%) zerosZeros
양실수 has 61 (24.4%) zerosZeros
욕실수 has 78 (31.2%) zerosZeros
좌석수 has 89 (35.6%) zerosZeros

Reproduction

Analysis started2024-04-06 11:04:09.551942
Analysis finished2024-04-06 11:04:10.870253
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3160000
250 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 250
100.0%

Length

2024-04-06T20:04:11.094701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:11.244521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 250
100.0%

관리번호
Text

UNIQUE 

Distinct250
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-06T20:04:11.552961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5500
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

Unique250 ?
Unique (%)100.0%

Sample

1st row3160000-201-1966-00150
2nd row3160000-201-1967-00092
3rd row3160000-201-1968-00095
4th row3160000-201-1968-00099
5th row3160000-201-1968-00218
ValueCountFrequency (%)
3160000-201-1966-00150 1
 
0.4%
3160000-201-1983-00217 1
 
0.4%
3160000-201-1983-00047 1
 
0.4%
3160000-201-1986-00057 1
 
0.4%
3160000-201-1983-00048 1
 
0.4%
3160000-201-1983-00074 1
 
0.4%
3160000-201-1983-00202 1
 
0.4%
3160000-201-1983-00203 1
 
0.4%
3160000-201-1983-00204 1
 
0.4%
3160000-201-1983-00206 1
 
0.4%
Other values (240) 240
96.0%
2024-04-06T20:04:12.250099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1980
36.0%
1 929
16.9%
- 750
 
13.6%
2 388
 
7.1%
3 349
 
6.3%
6 325
 
5.9%
9 305
 
5.5%
7 167
 
3.0%
8 162
 
2.9%
4 76
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4750
86.4%
Dash Punctuation 750
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1980
41.7%
1 929
19.6%
2 388
 
8.2%
3 349
 
7.3%
6 325
 
6.8%
9 305
 
6.4%
7 167
 
3.5%
8 162
 
3.4%
4 76
 
1.6%
5 69
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 750
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1980
36.0%
1 929
16.9%
- 750
 
13.6%
2 388
 
7.1%
3 349
 
6.3%
6 325
 
5.9%
9 305
 
5.5%
7 167
 
3.0%
8 162
 
2.9%
4 76
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1980
36.0%
1 929
16.9%
- 750
 
13.6%
2 388
 
7.1%
3 349
 
6.3%
6 325
 
5.9%
9 305
 
5.5%
7 167
 
3.0%
8 162
 
2.9%
4 76
 
1.4%
Distinct244
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1966-11-22 00:00:00
Maximum2018-08-30 00:00:00
2024-04-06T20:04:12.620019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:12.906045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3
137 
1
113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 137
54.8%
1 113
45.2%

Length

2024-04-06T20:04:13.142223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:13.307172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 137
54.8%
1 113
45.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
137 
영업/정상
113 

Length

Max length5
Median length2
Mean length3.356
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 137
54.8%
영업/정상 113
45.2%

Length

2024-04-06T20:04:13.488424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:13.698220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 137
54.8%
영업/정상 113
45.2%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2
137 
1
113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 137
54.8%
1 113
45.2%

Length

2024-04-06T20:04:13.919977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:14.102467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 137
54.8%
1 113
45.2%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
137 
영업
113 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 137
54.8%
영업 113
45.2%

Length

2024-04-06T20:04:14.261889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:14.410266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 137
54.8%
영업 113
45.2%

폐업일자
Date

MISSING 

Distinct128
Distinct (%)93.4%
Missing113
Missing (%)45.2%
Memory size2.1 KiB
Minimum1994-11-18 00:00:00
Maximum2024-02-27 00:00:00
2024-04-06T20:04:14.610851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:14.857545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct235
Distinct (%)98.3%
Missing11
Missing (%)4.4%
Memory size2.1 KiB
2024-04-06T20:04:15.257331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.125523
Min length6

Characters and Unicode

Total characters2420
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

Unique231 ?
Unique (%)96.7%

Sample

1st row02 8597969
2nd row0208544386
3rd row0208551752
4th row0208550760
5th row0208678961
ValueCountFrequency (%)
02 108
30.3%
0226138884 2
 
0.6%
6833444 2
 
0.6%
8579918 2
 
0.6%
8649608 2
 
0.6%
858 2
 
0.6%
861 2
 
0.6%
0208632594 1
 
0.3%
8375502 1
 
0.3%
8635585 1
 
0.3%
Other values (234) 234
65.5%
2024-04-06T20:04:15.911374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 441
18.2%
2 430
17.8%
8 284
11.7%
6 240
9.9%
5 200
8.3%
1 158
 
6.5%
3 157
 
6.5%
136
 
5.6%
9 128
 
5.3%
4 126
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2284
94.4%
Space Separator 136
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 441
19.3%
2 430
18.8%
8 284
12.4%
6 240
10.5%
5 200
8.8%
1 158
 
6.9%
3 157
 
6.9%
9 128
 
5.6%
4 126
 
5.5%
7 120
 
5.3%
Space Separator
ValueCountFrequency (%)
136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 441
18.2%
2 430
17.8%
8 284
11.7%
6 240
9.9%
5 200
8.3%
1 158
 
6.5%
3 157
 
6.5%
136
 
5.6%
9 128
 
5.3%
4 126
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 441
18.2%
2 430
17.8%
8 284
11.7%
6 240
9.9%
5 200
8.3%
1 158
 
6.5%
3 157
 
6.5%
136
 
5.6%
9 128
 
5.3%
4 126
 
5.2%
Distinct207
Distinct (%)83.1%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-04-06T20:04:16.512363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length5.4176707
Min length3

Characters and Unicode

Total characters1349
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

Unique203 ?
Unique (%)81.5%

Sample

1st row92.00
2nd row97.59
3rd row56.00
4th row47.93
5th row.00
ValueCountFrequency (%)
00 40
 
16.1%
486.93 2
 
0.8%
55.54 2
 
0.8%
139.44 2
 
0.8%
754.11 1
 
0.4%
215.44 1
 
0.4%
92.00 1
 
0.4%
123.16 1
 
0.4%
68.80 1
 
0.4%
153.91 1
 
0.4%
Other values (197) 197
79.1%
2024-04-06T20:04:17.467037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 249
18.5%
0 202
15.0%
1 136
10.1%
8 114
8.5%
9 99
 
7.3%
4 99
 
7.3%
2 96
 
7.1%
5 94
 
7.0%
6 92
 
6.8%
7 83
 
6.2%
Other values (2) 85
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1086
80.5%
Other Punctuation 263
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202
18.6%
1 136
12.5%
8 114
10.5%
9 99
9.1%
4 99
9.1%
2 96
8.8%
5 94
8.7%
6 92
8.5%
7 83
7.6%
3 71
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 249
94.7%
, 14
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 249
18.5%
0 202
15.0%
1 136
10.1%
8 114
8.5%
9 99
 
7.3%
4 99
 
7.3%
2 96
 
7.1%
5 94
 
7.0%
6 92
 
6.8%
7 83
 
6.2%
Other values (2) 85
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 249
18.5%
0 202
15.0%
1 136
10.1%
8 114
8.5%
9 99
 
7.3%
4 99
 
7.3%
2 96
 
7.1%
5 94
 
7.0%
6 92
 
6.8%
7 83
 
6.2%
Other values (2) 85
 
6.3%
Distinct54
Distinct (%)21.7%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-04-06T20:04:17.920176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1084337
Min length6

Characters and Unicode

Total characters1521
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

Unique20 ?
Unique (%)8.0%

Sample

1st row152800
2nd row152872
3rd row152875
4th row152871
5th row152875
ValueCountFrequency (%)
152894 31
 
12.4%
152801 24
 
9.6%
152880 21
 
8.4%
152871 12
 
4.8%
152870 12
 
4.8%
152838 11
 
4.4%
152800 10
 
4.0%
152875 9
 
3.6%
152872 9
 
3.6%
152858 7
 
2.8%
Other values (44) 103
41.4%
2024-04-06T20:04:18.740786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 311
20.4%
1 303
19.9%
5 287
18.9%
2 282
18.5%
0 107
 
7.0%
7 61
 
4.0%
4 50
 
3.3%
9 48
 
3.2%
- 27
 
1.8%
3 25
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1494
98.2%
Dash Punctuation 27
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 311
20.8%
1 303
20.3%
5 287
19.2%
2 282
18.9%
0 107
 
7.2%
7 61
 
4.1%
4 50
 
3.3%
9 48
 
3.2%
3 25
 
1.7%
6 20
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1521
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 311
20.4%
1 303
19.9%
5 287
18.9%
2 282
18.5%
0 107
 
7.0%
7 61
 
4.0%
4 50
 
3.3%
9 48
 
3.2%
- 27
 
1.8%
3 25
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1521
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 311
20.4%
1 303
19.9%
5 287
18.9%
2 282
18.5%
0 107
 
7.0%
7 61
 
4.0%
4 50
 
3.3%
9 48
 
3.2%
- 27
 
1.8%
3 25
 
1.6%
Distinct244
Distinct (%)98.0%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-04-06T20:04:19.297626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.967871
Min length18

Characters and Unicode

Total characters5470
Distinct characters68
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

Unique240 ?
Unique (%)96.4%

Sample

1st row서울특별시 구로구 가리봉동 25-63
2nd row서울특별시 구로구 구로동 733-35
3rd row서울특별시 구로구 구로동 801-34
4th row서울특별시 구로구 구로동 730-29
5th row서울특별시 구로구 구로동 798-58번지
ValueCountFrequency (%)
서울특별시 249
24.6%
구로구 249
24.6%
구로동 122
12.0%
오류동 46
 
4.5%
가리봉동 43
 
4.2%
개봉동 15
 
1.5%
고척동 13
 
1.3%
신도림동 9
 
0.9%
55-6번지 3
 
0.3%
1125-8번지 2
 
0.2%
Other values (259) 262
25.9%
2024-04-06T20:04:20.077570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
952
17.4%
620
 
11.3%
371
 
6.8%
- 250
 
4.6%
250
 
4.6%
249
 
4.6%
249
 
4.6%
249
 
4.6%
249
 
4.6%
249
 
4.6%
Other values (58) 1782
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3124
57.1%
Decimal Number 1140
 
20.8%
Space Separator 952
 
17.4%
Dash Punctuation 250
 
4.6%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
620
19.8%
371
11.9%
250
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
147
 
4.7%
145
 
4.6%
Other values (43) 346
11.1%
Decimal Number
ValueCountFrequency (%)
1 206
18.1%
3 157
13.8%
2 145
12.7%
5 135
11.8%
7 126
11.1%
4 118
10.4%
0 72
 
6.3%
8 63
 
5.5%
6 61
 
5.4%
9 57
 
5.0%
Space Separator
ValueCountFrequency (%)
952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3124
57.1%
Common 2346
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
620
19.8%
371
11.9%
250
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
147
 
4.7%
145
 
4.6%
Other values (43) 346
11.1%
Common
ValueCountFrequency (%)
952
40.6%
- 250
 
10.7%
1 206
 
8.8%
3 157
 
6.7%
2 145
 
6.2%
5 135
 
5.8%
7 126
 
5.4%
4 118
 
5.0%
0 72
 
3.1%
8 63
 
2.7%
Other values (5) 122
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3124
57.1%
ASCII 2346
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
952
40.6%
- 250
 
10.7%
1 206
 
8.8%
3 157
 
6.7%
2 145
 
6.2%
5 135
 
5.8%
7 126
 
5.4%
4 118
 
5.0%
0 72
 
3.1%
8 63
 
2.7%
Other values (5) 122
 
5.2%
Hangul
ValueCountFrequency (%)
620
19.8%
371
11.9%
250
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
249
8.0%
147
 
4.7%
145
 
4.6%
Other values (43) 346
11.1%

도로명주소
Text

MISSING 

Distinct156
Distinct (%)98.7%
Missing92
Missing (%)36.8%
Memory size2.1 KiB
2024-04-06T20:04:20.737155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length26.753165
Min length21

Characters and Unicode

Total characters4227
Distinct characters87
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

Unique154 ?
Unique (%)97.5%

Sample

1st row서울특별시 구로구 구로동로5길 6 (가리봉동)
2nd row서울특별시 구로구 구로동로22길 5-14 (구로동)
3rd row서울특별시 구로구 도림로 8-1 (구로동)
4th row서울특별시 구로구 구로동로26길 55-8 (구로동)
5th row서울특별시 구로구 경인로15길 8-6 (오류동)
ValueCountFrequency (%)
서울특별시 158
19.7%
구로구 158
19.7%
구로동 78
 
9.7%
가리봉동 37
 
4.6%
오류동 25
 
3.1%
경인로22길 12
 
1.5%
구로동로25길 11
 
1.4%
구로동로 11
 
1.4%
경인로 9
 
1.1%
구로동로26길 7
 
0.9%
Other values (186) 298
37.1%
2024-04-06T20:04:21.613098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
646
15.3%
449
 
10.6%
444
 
10.5%
211
 
5.0%
161
 
3.8%
( 160
 
3.8%
) 160
 
3.8%
160
 
3.8%
2 159
 
3.8%
158
 
3.7%
Other values (77) 1519
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2553
60.4%
Space Separator 646
 
15.3%
Decimal Number 634
 
15.0%
Open Punctuation 160
 
3.8%
Close Punctuation 160
 
3.8%
Dash Punctuation 60
 
1.4%
Other Punctuation 14
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
449
17.6%
444
17.4%
211
8.3%
161
 
6.3%
160
 
6.3%
158
 
6.2%
158
 
6.2%
158
 
6.2%
126
 
4.9%
49
 
1.9%
Other values (62) 479
18.8%
Decimal Number
ValueCountFrequency (%)
2 159
25.1%
1 116
18.3%
3 60
 
9.5%
5 57
 
9.0%
0 53
 
8.4%
6 50
 
7.9%
8 39
 
6.2%
7 35
 
5.5%
9 33
 
5.2%
4 32
 
5.0%
Space Separator
ValueCountFrequency (%)
646
100.0%
Open Punctuation
ValueCountFrequency (%)
( 160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2553
60.4%
Common 1674
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
449
17.6%
444
17.4%
211
8.3%
161
 
6.3%
160
 
6.3%
158
 
6.2%
158
 
6.2%
158
 
6.2%
126
 
4.9%
49
 
1.9%
Other values (62) 479
18.8%
Common
ValueCountFrequency (%)
646
38.6%
( 160
 
9.6%
) 160
 
9.6%
2 159
 
9.5%
1 116
 
6.9%
- 60
 
3.6%
3 60
 
3.6%
5 57
 
3.4%
0 53
 
3.2%
6 50
 
3.0%
Other values (5) 153
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2553
60.4%
ASCII 1674
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
646
38.6%
( 160
 
9.6%
) 160
 
9.6%
2 159
 
9.5%
1 116
 
6.9%
- 60
 
3.6%
3 60
 
3.6%
5 57
 
3.4%
0 53
 
3.2%
6 50
 
3.0%
Other values (5) 153
 
9.1%
Hangul
ValueCountFrequency (%)
449
17.6%
444
17.4%
211
8.3%
161
 
6.3%
160
 
6.3%
158
 
6.2%
158
 
6.2%
158
 
6.2%
126
 
4.9%
49
 
1.9%
Other values (62) 479
18.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)29.4%
Missing97
Missing (%)38.8%
Infinite0
Infinite (%)0.0%
Mean8319.5098
Minimum8209
Maximum8395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:21.893975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8209
5-th percentile8271
Q18281
median8311
Q38374
95-th percentile8393.8
Maximum8395
Range186
Interquartile range (IQR)93

Descriptive statistics

Standard deviation46.992037
Coefficient of variation (CV)0.0056484142
Kurtosis-0.7492745
Mean8319.5098
Median Absolute Deviation (MAD)33
Skewness0.25429187
Sum1272885
Variance2208.2515
MonotonicityNot monotonic
2024-04-06T20:04:22.232604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
8271 25
 
10.0%
8309 11
 
4.4%
8388 9
 
3.6%
8312 8
 
3.2%
8296 8
 
3.2%
8311 8
 
3.2%
8322 8
 
3.2%
8395 8
 
3.2%
8387 7
 
2.8%
8310 5
 
2.0%
Other values (35) 56
22.4%
(Missing) 97
38.8%
ValueCountFrequency (%)
8209 1
 
0.4%
8213 1
 
0.4%
8223 1
 
0.4%
8224 1
 
0.4%
8231 1
 
0.4%
8241 1
 
0.4%
8267 1
 
0.4%
8271 25
10.0%
8277 3
 
1.2%
8278 1
 
0.4%
ValueCountFrequency (%)
8395 8
3.2%
8393 1
 
0.4%
8392 2
 
0.8%
8391 4
1.6%
8388 9
3.6%
8387 7
2.8%
8386 3
 
1.2%
8385 1
 
0.4%
8379 1
 
0.4%
8374 4
1.6%
Distinct227
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-06T20:04:22.734280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length3.308
Min length1

Characters and Unicode

Total characters827
Distinct characters218
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

Unique206 ?
Unique (%)82.4%

Sample

1st row대동장
2nd row원선여인숙
3rd row상하
4th row충남
5th row수양
ValueCountFrequency (%)
모텔 7
 
2.6%
호텔 6
 
2.2%
한일 4
 
1.5%
서울 3
 
1.1%
우진 2
 
0.7%
구로 2
 
0.7%
신도 2
 
0.7%
세븐 2
 
0.7%
현대 2
 
0.7%
흥부 2
 
0.7%
Other values (226) 241
88.3%
2024-04-06T20:04:23.787118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
 
5.9%
40
 
4.8%
29
 
3.5%
23
 
2.8%
19
 
2.3%
19
 
2.3%
19
 
2.3%
17
 
2.1%
15
 
1.8%
14
 
1.7%
Other values (208) 583
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 763
92.3%
Space Separator 23
 
2.8%
Uppercase Letter 23
 
2.8%
Open Punctuation 6
 
0.7%
Close Punctuation 6
 
0.7%
Decimal Number 3
 
0.4%
Lowercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
49
 
6.4%
40
 
5.2%
29
 
3.8%
19
 
2.5%
19
 
2.5%
19
 
2.5%
17
 
2.2%
15
 
2.0%
14
 
1.8%
12
 
1.6%
Other values (189) 530
69.5%
Uppercase Letter
ValueCountFrequency (%)
E 4
17.4%
R 4
17.4%
N 3
13.0%
V 2
8.7%
Z 2
8.7%
O 2
8.7%
B 2
8.7%
M 1
 
4.3%
J 1
 
4.3%
T 1
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
t 1
33.3%
o 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
5 1
33.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 763
92.3%
Common 38
 
4.6%
Latin 26
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
49
 
6.4%
40
 
5.2%
29
 
3.8%
19
 
2.5%
19
 
2.5%
19
 
2.5%
17
 
2.2%
15
 
2.0%
14
 
1.8%
12
 
1.6%
Other values (189) 530
69.5%
Latin
ValueCountFrequency (%)
E 4
15.4%
R 4
15.4%
N 3
11.5%
V 2
7.7%
Z 2
7.7%
O 2
7.7%
B 2
7.7%
M 1
 
3.8%
e 1
 
3.8%
t 1
 
3.8%
Other values (4) 4
15.4%
Common
ValueCountFrequency (%)
23
60.5%
( 6
 
15.8%
) 6
 
15.8%
2 2
 
5.3%
5 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 763
92.3%
ASCII 64
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
49
 
6.4%
40
 
5.2%
29
 
3.8%
19
 
2.5%
19
 
2.5%
19
 
2.5%
17
 
2.2%
15
 
2.0%
14
 
1.8%
12
 
1.6%
Other values (189) 530
69.5%
ASCII
ValueCountFrequency (%)
23
35.9%
( 6
 
9.4%
) 6
 
9.4%
E 4
 
6.2%
R 4
 
6.2%
N 3
 
4.7%
V 2
 
3.1%
Z 2
 
3.1%
O 2
 
3.1%
B 2
 
3.1%
Other values (9) 10
15.6%
Distinct200
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2000-07-12 00:00:00
Maximum2024-03-21 10:20:03
2024-04-06T20:04:24.119323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:24.365703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
U
125 
I
125 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 125
50.0%
I 125
50.0%

Length

2024-04-06T20:04:24.616464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:24.767100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 125
50.0%
i 125
50.0%
Distinct68
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T20:04:24.925853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:25.549434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
여인숙업
137 
여관업
103 
관광호텔
 
6
숙박업(생활)
 
3
일반호텔
 
1

Length

Max length7
Median length4
Mean length3.624
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
여인숙업 137
54.8%
여관업 103
41.2%
관광호텔 6
 
2.4%
숙박업(생활) 3
 
1.2%
일반호텔 1
 
0.4%

Length

2024-04-06T20:04:25.780267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:26.069060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여인숙업 137
54.8%
여관업 103
41.2%
관광호텔 6
 
2.4%
숙박업(생활 3
 
1.2%
일반호텔 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)95.8%
Missing12
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean189075.34
Minimum185550.19
Maximum191178.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:26.312704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185550.19
5-th percentile186081.46
Q1187521.72
median189769.25
Q3190191.21
95-th percentile190999.22
Maximum191178.3
Range5628.1086
Interquartile range (IQR)2669.4926

Descriptive statistics

Standard deviation1659.3015
Coefficient of variation (CV)0.0087758748
Kurtosis-0.76682411
Mean189075.34
Median Absolute Deviation (MAD)529.54206
Skewness-0.86612827
Sum44999932
Variance2753281.6
MonotonicityNot monotonic
2024-04-06T20:04:26.536743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186192.868434835 3
 
1.2%
186211.713224521 2
 
0.8%
190298.79584467 2
 
0.8%
186194.414532272 2
 
0.8%
190326.678121622 2
 
0.8%
189723.465336734 2
 
0.8%
191171.973158694 2
 
0.8%
186081.463781645 2
 
0.8%
186391.769129848 2
 
0.8%
189495.315331697 1
 
0.4%
Other values (218) 218
87.2%
(Missing) 12
 
4.8%
ValueCountFrequency (%)
185550.189291341 1
0.4%
185765.052827235 1
0.4%
185788.729049335 1
0.4%
185889.96050866 1
0.4%
185892.732951693 1
0.4%
185898.983303029 1
0.4%
185900.76304245 1
0.4%
185904.966553826 1
0.4%
185915.942839289 1
0.4%
185928.587749649 1
0.4%
ValueCountFrequency (%)
191178.297851366 1
0.4%
191171.973158694 2
0.8%
191151.374492515 1
0.4%
191132.368435152 1
0.4%
191121.109753612 1
0.4%
191112.844250184 1
0.4%
191112.035664451 1
0.4%
191098.98881955 1
0.4%
191053.08026408 1
0.4%
191030.319950169 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)95.8%
Missing12
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean443224.19
Minimum441924.61
Maximum445527.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:26.789814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441924.61
5-th percentile442003.47
Q1442420.81
median443173.06
Q3443803.33
95-th percentile444534.96
Maximum445527.83
Range3603.2156
Interquartile range (IQR)1382.5175

Descriptive statistics

Standard deviation852.92017
Coefficient of variation (CV)0.0019243538
Kurtosis-0.79961232
Mean443224.19
Median Absolute Deviation (MAD)647.79374
Skewness0.22091476
Sum1.0548736 × 108
Variance727472.82
MonotonicityNot monotonic
2024-04-06T20:04:27.035737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443764.341182161 3
 
1.2%
443744.926320387 2
 
0.8%
442152.778031612 2
 
0.8%
443742.167882891 2
 
0.8%
444439.374712808 2
 
0.8%
443171.443308097 2
 
0.8%
442343.517380858 2
 
0.8%
443677.477878516 2
 
0.8%
443886.316589264 2
 
0.8%
443972.600931418 1
 
0.4%
Other values (218) 218
87.2%
(Missing) 12
 
4.8%
ValueCountFrequency (%)
441924.609619553 1
0.4%
441929.798809285 1
0.4%
441938.438406374 1
0.4%
441947.454339126 1
0.4%
441951.694531956 1
0.4%
441956.100568837 1
0.4%
441957.227369102 1
0.4%
441970.427503288 1
0.4%
441980.107377152 1
0.4%
441982.850684756 1
0.4%
ValueCountFrequency (%)
445527.825251583 1
0.4%
445336.847944801 1
0.4%
445158.699507853 1
0.4%
445157.626366229 1
0.4%
444939.837035174 1
0.4%
444933.961164397 1
0.4%
444888.137537357 1
0.4%
444842.380229228 1
0.4%
444626.783638857 1
0.4%
444546.415192668 1
0.4%

위생업태명
Categorical

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
여인숙업
100 
여관업
85 
<NA>
62 
일반호텔
 
1
관광호텔
 
1

Length

Max length7
Median length4
Mean length3.672
Min length3

Unique

Unique3 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
여인숙업 100
40.0%
여관업 85
34.0%
<NA> 62
24.8%
일반호텔 1
 
0.4%
관광호텔 1
 
0.4%
숙박업(생활) 1
 
0.4%

Length

2024-04-06T20:04:27.316718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:27.513448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여인숙업 100
40.0%
여관업 85
34.0%
na 62
24.8%
일반호텔 1
 
0.4%
관광호텔 1
 
0.4%
숙박업(생활 1
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.1%
Missing69
Missing (%)27.6%
Infinite0
Infinite (%)0.0%
Mean2.6187845
Minimum0
Maximum15
Zeros36
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:27.678068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1662771
Coefficient of variation (CV)0.82720706
Kurtosis5.427414
Mean2.6187845
Median Absolute Deviation (MAD)1
Skewness1.5257629
Sum474
Variance4.6927563
MonotonicityNot monotonic
2024-04-06T20:04:27.854244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 57
22.8%
0 36
14.4%
3 27
 
10.8%
4 22
 
8.8%
5 16
 
6.4%
1 10
 
4.0%
6 4
 
1.6%
8 4
 
1.6%
7 3
 
1.2%
9 1
 
0.4%
(Missing) 69
27.6%
ValueCountFrequency (%)
0 36
14.4%
1 10
 
4.0%
2 57
22.8%
3 27
10.8%
4 22
 
8.8%
5 16
 
6.4%
6 4
 
1.6%
7 3
 
1.2%
8 4
 
1.6%
9 1
 
0.4%
ValueCountFrequency (%)
15 1
 
0.4%
9 1
 
0.4%
8 4
 
1.6%
7 3
 
1.2%
6 4
 
1.6%
5 16
 
6.4%
4 22
 
8.8%
3 27
10.8%
2 57
22.8%
1 10
 
4.0%
Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
1
107 
<NA>
84 
0
58 
2
 
1

Length

Max length4
Median length1
Mean length2.008
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 107
42.8%
<NA> 84
33.6%
0 58
23.2%
2 1
 
0.4%

Length

2024-04-06T20:04:28.054997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:28.190141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 107
42.8%
na 84
33.6%
0 58
23.2%
2 1
 
0.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.4%
Missing72
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean1.2134831
Minimum0
Maximum15
Zeros35
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:28.318192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3016453
Coefficient of variation (CV)1.0726521
Kurtosis70.93722
Mean1.2134831
Median Absolute Deviation (MAD)0
Skewness6.8250484
Sum216
Variance1.6942805
MonotonicityNot monotonic
2024-04-06T20:04:28.511173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 91
36.4%
2 44
17.6%
0 35
 
14.0%
3 6
 
2.4%
4 1
 
0.4%
15 1
 
0.4%
(Missing) 72
28.8%
ValueCountFrequency (%)
0 35
 
14.0%
1 91
36.4%
2 44
17.6%
3 6
 
2.4%
4 1
 
0.4%
15 1
 
0.4%
ValueCountFrequency (%)
15 1
 
0.4%
4 1
 
0.4%
3 6
 
2.4%
2 44
17.6%
1 91
36.4%
0 35
 
14.0%

사용끝지상층
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)8.2%
Missing103
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean3.170068
Minimum0
Maximum21
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:28.685417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile7
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4700234
Coefficient of variation (CV)0.77917048
Kurtosis20.977219
Mean3.170068
Median Absolute Deviation (MAD)1
Skewness3.6419161
Sum466
Variance6.1010157
MonotonicityNot monotonic
2024-04-06T20:04:28.838521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 55
22.0%
3 24
 
9.6%
4 20
 
8.0%
1 19
 
7.6%
5 14
 
5.6%
7 4
 
1.6%
6 3
 
1.2%
8 3
 
1.2%
0 2
 
0.8%
21 1
 
0.4%
Other values (2) 2
 
0.8%
(Missing) 103
41.2%
ValueCountFrequency (%)
0 2
 
0.8%
1 19
 
7.6%
2 55
22.0%
3 24
9.6%
4 20
 
8.0%
5 14
 
5.6%
6 3
 
1.2%
7 4
 
1.6%
8 3
 
1.2%
9 1
 
0.4%
ValueCountFrequency (%)
21 1
 
0.4%
15 1
 
0.4%
9 1
 
0.4%
8 3
 
1.2%
7 4
 
1.6%
6 3
 
1.2%
5 14
 
5.6%
4 20
 
8.0%
3 24
9.6%
2 55
22.0%
Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
126 
0
87 
1
36 
8
 
1

Length

Max length4
Median length4
Mean length2.512
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 126
50.4%
0 87
34.8%
1 36
 
14.4%
8 1
 
0.4%

Length

2024-04-06T20:04:29.042652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:29.185341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 126
50.4%
0 87
34.8%
1 36
 
14.4%
8 1
 
0.4%
Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
159 
0
53 
1
37 
42
 
1

Length

Max length4
Median length4
Mean length2.912
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
63.6%
0 53
 
21.2%
1 37
 
14.8%
42 1
 
0.4%

Length

2024-04-06T20:04:29.337991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:29.468924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 159
63.6%
0 53
 
21.2%
1 37
 
14.8%
42 1
 
0.4%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)10.1%
Missing72
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean8.2359551
Minimum0
Maximum57
Zeros24
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:29.565813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.25
median9
Q311
95-th percentile15
Maximum57
Range57
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation5.6967083
Coefficient of variation (CV)0.69168764
Kurtosis29.274069
Mean8.2359551
Median Absolute Deviation (MAD)3
Skewness3.332236
Sum1466
Variance32.452485
MonotonicityNot monotonic
2024-04-06T20:04:29.674497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9 26
 
10.4%
0 24
 
9.6%
10 22
 
8.8%
7 15
 
6.0%
11 13
 
5.2%
8 12
 
4.8%
12 12
 
4.8%
6 9
 
3.6%
13 9
 
3.6%
4 8
 
3.2%
Other values (8) 28
 
11.2%
(Missing) 72
28.8%
ValueCountFrequency (%)
0 24
9.6%
1 1
 
0.4%
3 5
 
2.0%
4 8
 
3.2%
5 7
 
2.8%
6 9
 
3.6%
7 15
6.0%
8 12
4.8%
9 26
10.4%
10 22
8.8%
ValueCountFrequency (%)
57 1
 
0.4%
19 1
 
0.4%
16 4
 
1.6%
15 4
 
1.6%
14 5
 
2.0%
13 9
 
3.6%
12 12
4.8%
11 13
5.2%
10 22
8.8%
9 26
10.4%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)24.0%
Missing104
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean12.123288
Minimum0
Maximum269
Zeros61
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:29.803387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.5
Q316
95-th percentile36
Maximum269
Range269
Interquartile range (IQR)16

Descriptive statistics

Standard deviation24.716012
Coefficient of variation (CV)2.0387219
Kurtosis81.023059
Mean12.123288
Median Absolute Deviation (MAD)6.5
Skewness7.9517456
Sum1770
Variance610.88125
MonotonicityNot monotonic
2024-04-06T20:04:29.983471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 61
24.4%
10 7
 
2.8%
14 6
 
2.4%
11 5
 
2.0%
36 4
 
1.6%
6 4
 
1.6%
15 4
 
1.6%
18 4
 
1.6%
23 4
 
1.6%
4 3
 
1.2%
Other values (25) 44
17.6%
(Missing) 104
41.6%
ValueCountFrequency (%)
0 61
24.4%
2 1
 
0.4%
3 1
 
0.4%
4 3
 
1.2%
5 3
 
1.2%
6 4
 
1.6%
7 3
 
1.2%
8 1
 
0.4%
9 2
 
0.8%
10 7
 
2.8%
ValueCountFrequency (%)
269 1
 
0.4%
54 1
 
0.4%
49 1
 
0.4%
47 1
 
0.4%
37 2
0.8%
36 4
1.6%
35 2
0.8%
33 2
0.8%
32 2
0.8%
29 1
 
0.4%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)22.1%
Missing110
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean9.6642857
Minimum0
Maximum49
Zeros78
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:30.141894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319
95-th percentile33.05
Maximum49
Range49
Interquartile range (IQR)19

Descriptive statistics

Standard deviation12.648889
Coefficient of variation (CV)1.3088282
Kurtosis0.017935019
Mean9.6642857
Median Absolute Deviation (MAD)0
Skewness1.0185064
Sum1353
Variance159.9944
MonotonicityNot monotonic
2024-04-06T20:04:30.283585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 78
31.2%
12 4
 
1.6%
22 4
 
1.6%
19 4
 
1.6%
20 4
 
1.6%
14 3
 
1.2%
21 3
 
1.2%
18 3
 
1.2%
15 3
 
1.2%
17 3
 
1.2%
Other values (21) 31
 
12.4%
(Missing) 110
44.0%
ValueCountFrequency (%)
0 78
31.2%
1 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%
10 2
 
0.8%
12 4
 
1.6%
13 1
 
0.4%
14 3
 
1.2%
15 3
 
1.2%
16 2
 
0.8%
ValueCountFrequency (%)
49 1
0.4%
47 1
0.4%
43 1
0.4%
36 2
0.8%
34 2
0.8%
33 2
0.8%
32 2
0.8%
31 1
0.4%
30 2
0.8%
29 2
0.8%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.1%
Missing62
Missing (%)24.8%
Memory size632.0 B
True
172 
False
 
16
(Missing)
62 
ValueCountFrequency (%)
True 172
68.8%
False 16
 
6.4%
(Missing) 62
 
24.8%
2024-04-06T20:04:30.432512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)16.2%
Missing120
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean11.715385
Minimum0
Maximum84
Zeros89
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-06T20:04:30.551627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q322
95-th percentile55.7
Maximum84
Range84
Interquartile range (IQR)22

Descriptive statistics

Standard deviation20.069351
Coefficient of variation (CV)1.7130765
Kurtosis2.2726514
Mean11.715385
Median Absolute Deviation (MAD)0
Skewness1.7240622
Sum1523
Variance402.77883
MonotonicityNot monotonic
2024-04-06T20:04:30.664502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 89
35.6%
72 4
 
1.6%
30 4
 
1.6%
40 4
 
1.6%
20 3
 
1.2%
26 3
 
1.2%
28 3
 
1.2%
38 3
 
1.2%
16 2
 
0.8%
46 2
 
0.8%
Other values (11) 13
 
5.2%
(Missing) 120
48.0%
ValueCountFrequency (%)
0 89
35.6%
12 1
 
0.4%
14 1
 
0.4%
16 2
 
0.8%
20 3
 
1.2%
22 2
 
0.8%
23 1
 
0.4%
26 3
 
1.2%
28 3
 
1.2%
30 4
 
1.6%
ValueCountFrequency (%)
84 1
 
0.4%
72 4
1.6%
64 1
 
0.4%
62 1
 
0.4%
48 1
 
0.4%
46 2
0.8%
44 1
 
0.4%
40 4
1.6%
38 3
1.2%
34 2
0.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
249 
20190530
 
1

Length

Max length8
Median length4
Mean length4.016
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
99.6%
20190530 1
 
0.4%

Length

2024-04-06T20:04:30.794095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:30.929986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
99.6%
20190530 1
 
0.4%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
249 
20210316
 
1

Length

Max length8
Median length4
Mean length4.016
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
99.6%
20210316 1
 
0.4%

Length

2024-04-06T20:04:31.144194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:31.341407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
99.6%
20210316 1
 
0.4%
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
128 
자가
61 
임대
61 

Length

Max length4
Median length4
Mean length3.024
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
51.2%
자가 61
24.4%
임대 61
24.4%

Length

2024-04-06T20:04:31.557703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:31.759589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
51.2%
자가 61
24.4%
임대 61
24.4%

세탁기수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
169 
0
81 

Length

Max length4
Median length4
Mean length3.028
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 169
67.6%
0 81
32.4%

Length

2024-04-06T20:04:31.942785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:32.121873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 169
67.6%
0 81
32.4%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
241 
0
 
8
1
 
1

Length

Max length4
Median length4
Mean length3.892
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 241
96.4%
0 8
 
3.2%
1 1
 
0.4%

Length

2024-04-06T20:04:32.304255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:32.468711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
96.4%
0 8
 
3.2%
1 1
 
0.4%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
241 
0
 
8
1
 
1

Length

Max length4
Median length4
Mean length3.892
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 241
96.4%
0 8
 
3.2%
1 1
 
0.4%

Length

2024-04-06T20:04:32.638350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:32.800972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
96.4%
0 8
 
3.2%
1 1
 
0.4%

회수건조수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
171 
0
79 

Length

Max length4
Median length4
Mean length3.052
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 171
68.4%
0 79
31.6%

Length

2024-04-06T20:04:33.015973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:33.213062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 171
68.4%
0 79
31.6%

침대수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
171 
0
79 

Length

Max length4
Median length4
Mean length3.052
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 171
68.4%
0 79
31.6%

Length

2024-04-06T20:04:33.395669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:33.572459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 171
68.4%
0 79
31.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.1%
Missing62
Missing (%)24.8%
Memory size632.0 B
False
187 
True
 
1
(Missing)
62 
ValueCountFrequency (%)
False 187
74.8%
True 1
 
0.4%
(Missing) 62
 
24.8%
2024-04-06T20:04:33.708287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031600003160000-201-1966-0015019661122<NA>1영업/정상1영업<NA><NA><NA><NA>02 859796992.00152800서울특별시 구로구 가리봉동 25-63서울특별시 구로구 구로동로5길 6 (가리봉동)8321대동장2022-07-20 10:48:17U2021-12-06 22:03:00.0여인숙업189820.180619442529.193769<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131600003160000-201-1967-0009219670831<NA>1영업/정상1영업<NA><NA><NA><NA>020854438697.59152872서울특별시 구로구 구로동 733-35서울특별시 구로구 구로동로22길 5-14 (구로동)8311원선여인숙2020-12-17 11:32:48U2020-12-19 02:40:00.0여인숙업189774.162625443070.250973여인숙업1011001000Y0<NA><NA><NA>자가0<NA><NA>00N
231600003160000-201-1968-0009519680729<NA>1영업/정상1영업<NA><NA><NA><NA>020855175256.00152875서울특별시 구로구 구로동 801-34서울특별시 구로구 도림로 8-1 (구로동)8374상하2022-07-12 10:47:27U2021-12-06 23:04:00.0여인숙업189925.985866442579.676677<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331600003160000-201-1968-0009919681228<NA>1영업/정상1영업<NA><NA><NA><NA>020855076047.93152871서울특별시 구로구 구로동 730-29서울특별시 구로구 구로동로26길 55-8 (구로동)8311충남2022-07-12 10:37:41U2021-12-06 23:04:00.0여인숙업189986.432015443125.781588<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431600003160000-201-1968-0021819680229<NA>3폐업2폐업19970710<NA><NA><NA>0208678961.00152875서울특별시 구로구 구로동 798-58번지<NA><NA>수양2003-02-11 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>900Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531600003160000-201-1969-0009319691029<NA>3폐업2폐업20110620<NA><NA><NA>02 8560993142.31152870서울특별시 구로구 구로동 704-60번지<NA><NA>한일2010-06-30 11:09:10I2018-08-31 23:59:59.0여인숙업189564.953294443240.185156여인숙업2<NA>11<NA><NA>15<NA><NA>Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
631600003160000-201-1969-0009419691227<NA>3폐업2폐업20160324<NA><NA><NA>0226869566138.84152889서울특별시 구로구 오류동 6-114번지서울특별시 구로구 경인로15길 8-6 (오류동)<NA>나나2009-04-29 15:04:18I2018-08-31 23:59:59.0여인숙업185788.729049443644.444603여인숙업2<NA>22<NA><NA>16<NA><NA>Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
731600003160000-201-1969-0010119691101<NA>3폐업2폐업20060823<NA><NA><NA>022619895089.26152824서울특별시 구로구 고척동 52-43번지<NA><NA>송죽2005-06-09 00:00:00I2018-08-31 23:59:59.0여인숙업187970.738868444439.903608여인숙업1<NA>11<NA><NA>7<NA><NA>Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
831600003160000-201-1969-0010219691209<NA>3폐업2폐업20140507<NA><NA><NA>02 861 1050165.00152871서울특별시 구로구 구로동 722-54번지서울특별시 구로구 구로동로19길 3 (구로동)<NA>대성장2012-06-15 15:18:10I2018-08-31 23:59:59.0여인숙업189684.781579442968.063518여인숙업2<NA>12<NA><NA>8<NA><NA>Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
931600003160000-201-1969-0016819691001<NA>1영업/정상1영업<NA><NA><NA><NA>0208665079189.42152854서울특별시 구로구 구로동 414-30서울특별시 구로구 구로동로35길 13 (구로동)8286삼화2022-03-28 13:26:05U2021-12-02 21:00:00.0여인숙업189569.973156443496.775934<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
24031600003160000-201-2010-000012010-11-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 6905952218500.83152-880서울특별시 구로구 구로동 1128-1서울특별시 구로구 디지털로32길 72 (구로동)8393포포인츠 바이 쉐라톤 서울 구로2023-03-31 17:52:45U2022-12-04 00:02:00.0관광호텔190990.955753442338.842381<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24131600003160000-201-2011-000012011-08-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>486.93152-894서울특별시 구로구 오류동 52-4서울특별시 구로구 경인로20나길 6 (오류동)8271아공스테이2023-06-14 16:14:38U2022-12-05 23:06:00.0여관업186081.463782443677.477879<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24231600003160000-201-2011-0000320110823<NA>3폐업2폐업20211101<NA><NA><NA>02 2211200047,468.04152888서울특별시 구로구 신도림동 692서울특별시 구로구 경인로 662 (신도림동)8209쉐라톤서울 디큐브시티호텔2021-11-01 11:16:16U2021-11-03 02:40:00.0관광호텔190107.045415445157.626366관광호텔000084202690N0<NA><NA><NA><NA>00000N
24331600003160000-201-2014-000012014-07-10<NA>1영업/정상1영업<NA><NA><NA><NA>026210100599337912.00<NA><NA>서울특별시 구로구 디지털로 300 (구로동, (주)호텔롯데 롯데시티호텔 구로)8379롯데시티호텔 구로2023-09-08 10:47:28U2022-12-08 23:00:00.0관광호텔190779.824681442527.527967<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24431600003160000-201-2014-000022014-12-05<NA>1영업/정상1영업<NA><NA><NA><NA>022683900021131.68152-892서울특별시 구로구 오류동 31-277 호텔 베르누이서울특별시 구로구 경인로 229 (오류동, 호텔 베르누이)8267호텔 베르누이2023-03-31 17:43:27U2022-12-04 00:02:00.0관광호텔186313.367967443926.763932<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24531600003160000-201-2018-000012018-08-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>976.00152-801서울특별시 구로구 가리봉동 135-25서울특별시 구로구 남부순환로105길 32 (가리봉동)8395구로제이에스호스텔2023-03-31 17:58:32U2022-12-04 00:02:00.0관광호텔190289.173315441929.798809<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24631600003160000-201-2018-000022018-08-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>732.50152-801서울특별시 구로구 가리봉동 131-18 아단아서울특별시 구로구 디지털로19길 6-8, 아단아 (가리봉동)8388아단아2023-03-31 17:57:48U2022-12-04 00:02:00.0관광호텔190241.658927442019.000152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24731600003160000-214-2013-000012013-11-04<NA>1영업/정상1영업<NA><NA><NA><NA>070452050123076.67152-894서울특별시 구로구 오류동 55-42 코업시티호텔 스테이코서울특별시 구로구 경인로20가길 19 (오류동, 코업시티호텔 스테이코)8271한강골드호텔2024-02-26 15:12:23U2023-12-01 22:08:00.0숙박업(생활)186211.713225443744.92632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24831600003160000-214-2017-0000120170309<NA>3폐업2폐업20210824<NA><NA><NA><NA>1,567.00152894서울특별시 구로구 오류동 63-1 영흥빌딩서울특별시 구로구 경인로20가길 69 (오류동, 영흥빌딩)8271썬스카이 호텔2021-08-24 11:27:04U2021-08-26 02:40:00.0숙박업(생활)186459.871744443814.15667숙박업(생활)1511515115700N0<NA><NA><NA>자가01100Y
24931600003160000-214-2018-000012018-06-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>683.20152-801서울특별시 구로구 가리봉동 135-30 바모스하우스서울특별시 구로구 남부순환로105다길 12, 바모스하우스 (가리봉동)8395바모스하우스2023-03-31 17:51:48U2022-12-04 00:02:00.0숙박업(생활)190311.667218441947.454339<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>