Overview

Dataset statistics

Number of variables47
Number of observations157
Missing cells1701
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.1 KiB
Average record size in memory404.8 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric9
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-17444/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
건물소유구분명 is highly imbalanced (56.9%)Imbalance
여성종사자수 is highly imbalanced (83.8%)Imbalance
남성종사자수 is highly imbalanced (86.2%)Imbalance
다중이용업소여부 is highly imbalanced (88.3%)Imbalance
인허가취소일자 has 157 (100.0%) missing valuesMissing
폐업일자 has 69 (43.9%) missing valuesMissing
휴업시작일자 has 157 (100.0%) missing valuesMissing
휴업종료일자 has 157 (100.0%) missing valuesMissing
재개업일자 has 157 (100.0%) missing valuesMissing
전화번호 has 7 (4.5%) missing valuesMissing
도로명주소 has 46 (29.3%) missing valuesMissing
도로명우편번호 has 47 (29.9%) missing valuesMissing
좌표정보(X) has 5 (3.2%) missing valuesMissing
좌표정보(Y) has 5 (3.2%) missing valuesMissing
건물지상층수 has 70 (44.6%) missing valuesMissing
사용끝지상층 has 81 (51.6%) missing valuesMissing
한실수 has 32 (20.4%) missing valuesMissing
양실수 has 53 (33.8%) missing valuesMissing
욕실수 has 59 (37.6%) missing valuesMissing
발한실여부 has 30 (19.1%) missing valuesMissing
좌석수 has 68 (43.3%) missing valuesMissing
조건부허가신고사유 has 157 (100.0%) missing valuesMissing
조건부허가시작일자 has 157 (100.0%) missing valuesMissing
조건부허가종료일자 has 157 (100.0%) missing valuesMissing
다중이용업소여부 has 30 (19.1%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 61 (38.9%) zerosZeros
사용끝지상층 has 57 (36.3%) zerosZeros
한실수 has 21 (13.4%) zerosZeros
양실수 has 28 (17.8%) zerosZeros
욕실수 has 43 (27.4%) zerosZeros
좌석수 has 64 (40.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:26:10.172335
Analysis finished2024-05-11 06:26:11.652563
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3170000
157 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 157
100.0%

Length

2024-05-11T15:26:11.766259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:11.941765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 157
100.0%

관리번호
Text

UNIQUE 

Distinct157
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:26:12.306841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3454
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

Unique157 ?
Unique (%)100.0%

Sample

1st row3170000-201-1968-00038
2nd row3170000-201-1969-00090
3rd row3170000-201-1970-00039
4th row3170000-201-1970-00040
5th row3170000-201-1970-00041
ValueCountFrequency (%)
3170000-201-1968-00038 1
 
0.6%
3170000-201-1983-00031 1
 
0.6%
3170000-201-1983-00033 1
 
0.6%
3170000-201-1983-00047 1
 
0.6%
3170000-201-1983-00075 1
 
0.6%
3170000-201-1983-00076 1
 
0.6%
3170000-201-1983-00077 1
 
0.6%
3170000-201-1983-00078 1
 
0.6%
3170000-201-1983-00079 1
 
0.6%
3170000-201-1983-00032 1
 
0.6%
Other values (147) 147
93.6%
2024-05-11T15:26:12.925063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1338
38.7%
1 548
15.9%
- 471
 
13.6%
2 251
 
7.3%
7 237
 
6.9%
3 218
 
6.3%
9 167
 
4.8%
8 103
 
3.0%
4 46
 
1.3%
5 40
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2983
86.4%
Dash Punctuation 471
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1338
44.9%
1 548
18.4%
2 251
 
8.4%
7 237
 
7.9%
3 218
 
7.3%
9 167
 
5.6%
8 103
 
3.5%
4 46
 
1.5%
5 40
 
1.3%
6 35
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 471
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3454
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1338
38.7%
1 548
15.9%
- 471
 
13.6%
2 251
 
7.3%
7 237
 
6.9%
3 218
 
6.3%
9 167
 
4.8%
8 103
 
3.0%
4 46
 
1.3%
5 40
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1338
38.7%
1 548
15.9%
- 471
 
13.6%
2 251
 
7.3%
7 237
 
6.9%
3 218
 
6.3%
9 167
 
4.8%
8 103
 
3.0%
4 46
 
1.3%
5 40
 
1.2%
Distinct150
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1968-01-18 00:00:00
Maximum2023-11-17 00:00:00
2024-05-11T15:26:13.210247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:13.516518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
88 
1
69 

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 88
56.1%
1 69
43.9%

Length

2024-05-11T15:26:13.801386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:14.096876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 88
56.1%
1 69
43.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
88 
영업/정상
69 

Length

Max length5
Median length2
Mean length3.3184713
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 88
56.1%
영업/정상 69
43.9%

Length

2024-05-11T15:26:14.319901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:14.611805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
56.1%
영업/정상 69
43.9%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
88 
1
69 

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 88
56.1%
1 69
43.9%

Length

2024-05-11T15:26:14.859306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:15.066600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 88
56.1%
1 69
43.9%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
88 
영업
69 

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 88
56.1%
영업 69
43.9%

Length

2024-05-11T15:26:15.273767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:15.551575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
56.1%
영업 69
43.9%

폐업일자
Date

MISSING 

Distinct84
Distinct (%)95.5%
Missing69
Missing (%)43.9%
Memory size1.4 KiB
Minimum1998-07-15 00:00:00
Maximum2024-02-06 00:00:00
2024-05-11T15:26:15.793843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:16.070868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct150
Distinct (%)100.0%
Missing7
Missing (%)4.5%
Memory size1.4 KiB
2024-05-11T15:26:16.495476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10
Min length9

Characters and Unicode

Total characters1500
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

Unique150 ?
Unique (%)100.0%

Sample

1st row02 8079766
2nd row02 8046578
3rd row02 8049588
4th row02 8085695
5th row02 8959993
ValueCountFrequency (%)
02 142
48.1%
8548282 1
 
0.3%
8033334 1
 
0.3%
8056489 1
 
0.3%
8024671 1
 
0.3%
7776555 1
 
0.3%
8637575 1
 
0.3%
8635954 1
 
0.3%
8632400 1
 
0.3%
8374994 1
 
0.3%
Other values (144) 144
48.8%
2024-05-11T15:26:17.201586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 254
16.9%
2 226
15.1%
8 215
14.3%
146
9.7%
5 134
8.9%
6 104
6.9%
3 104
6.9%
9 91
 
6.1%
4 89
 
5.9%
7 70
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1354
90.3%
Space Separator 146
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 254
18.8%
2 226
16.7%
8 215
15.9%
5 134
9.9%
6 104
7.7%
3 104
7.7%
9 91
 
6.7%
4 89
 
6.6%
7 70
 
5.2%
1 67
 
4.9%
Space Separator
ValueCountFrequency (%)
146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 254
16.9%
2 226
15.1%
8 215
14.3%
146
9.7%
5 134
8.9%
6 104
6.9%
3 104
6.9%
9 91
 
6.1%
4 89
 
5.9%
7 70
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 254
16.9%
2 226
15.1%
8 215
14.3%
146
9.7%
5 134
8.9%
6 104
6.9%
3 104
6.9%
9 91
 
6.1%
4 89
 
5.9%
7 70
 
4.7%
Distinct145
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:26:17.810842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.8280255
Min length3

Characters and Unicode

Total characters915
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

Unique144 ?
Unique (%)91.7%

Sample

1st row105.83
2nd row53.22
3rd row111.77
4th row441.52
5th row146.84
ValueCountFrequency (%)
00 13
 
8.3%
105.83 1
 
0.6%
381.30 1
 
0.6%
261.48 1
 
0.6%
636.32 1
 
0.6%
360.83 1
 
0.6%
468.57 1
 
0.6%
433.89 1
 
0.6%
569.82 1
 
0.6%
1,607.00 1
 
0.6%
Other values (135) 135
86.0%
2024-05-11T15:26:18.837720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 157
17.2%
1 121
13.2%
0 114
12.5%
2 84
9.2%
4 70
7.7%
8 63
6.9%
3 61
 
6.7%
6 61
 
6.7%
5 60
 
6.6%
9 53
 
5.8%
Other values (2) 71
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 739
80.8%
Other Punctuation 176
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 121
16.4%
0 114
15.4%
2 84
11.4%
4 70
9.5%
8 63
8.5%
3 61
8.3%
6 61
8.3%
5 60
8.1%
9 53
7.2%
7 52
7.0%
Other Punctuation
ValueCountFrequency (%)
. 157
89.2%
, 19
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
Common 915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 157
17.2%
1 121
13.2%
0 114
12.5%
2 84
9.2%
4 70
7.7%
8 63
6.9%
3 61
 
6.7%
6 61
 
6.7%
5 60
 
6.6%
9 53
 
5.8%
Other values (2) 71
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 157
17.2%
1 121
13.2%
0 114
12.5%
2 84
9.2%
4 70
7.7%
8 63
6.9%
3 61
 
6.7%
6 61
 
6.7%
5 60
 
6.6%
9 53
 
5.8%
Other values (2) 71
7.8%
Distinct41
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
153801
44 
153864
18 
153858
10 
153857
10 
153-801
Other values (36)
68 

Length

Max length7
Median length6
Mean length6.1401274
Min length6

Unique

Unique19 ?
Unique (%)12.1%

Sample

1st row153858
2nd row153-863
3rd row153864
4th row153858
5th row153858

Common Values

ValueCountFrequency (%)
153801 44
28.0%
153864 18
11.5%
153858 10
 
6.4%
153857 10
 
6.4%
153-801 7
 
4.5%
153821 7
 
4.5%
153829 6
 
3.8%
153813 4
 
2.5%
153825 4
 
2.5%
153839 3
 
1.9%
Other values (31) 44
28.0%

Length

2024-05-11T15:26:19.130321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
153801 44
28.0%
153864 18
11.5%
153858 10
 
6.4%
153857 10
 
6.4%
153-801 7
 
4.5%
153821 7
 
4.5%
153829 6
 
3.8%
153813 4
 
2.5%
153825 4
 
2.5%
153839 3
 
1.9%
Other values (31) 44
28.0%
Distinct155
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:26:19.739324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length23.44586
Min length19

Characters and Unicode

Total characters3681
Distinct characters59
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)97.5%

Sample

1st row서울특별시 금천구 시흥동 883-2번지 [시흥대로 455]
2nd row서울특별시 금천구 시흥동 984-23
3rd row서울특별시 금천구 시흥동 995-55번지 [금천로 227-1]
4th row서울특별시 금천구 시흥동 888-17
5th row서울특별시 금천구 시흥동 891-20
ValueCountFrequency (%)
서울특별시 157
23.0%
금천구 157
23.0%
가산동 56
 
8.2%
시흥동 56
 
8.2%
독산동 45
 
6.6%
금천로 8
 
1.2%
구로동길 5
 
0.7%
140-79번지 2
 
0.3%
발소길 2
 
0.3%
독산동길 2
 
0.3%
Other values (189) 192
28.2%
2024-05-11T15:26:20.644186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
652
17.7%
217
 
5.9%
1 172
 
4.7%
- 166
 
4.5%
166
 
4.5%
166
 
4.5%
164
 
4.5%
162
 
4.4%
157
 
4.3%
157
 
4.3%
Other values (49) 1502
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1975
53.7%
Decimal Number 838
22.8%
Space Separator 652
 
17.7%
Dash Punctuation 166
 
4.5%
Close Punctuation 25
 
0.7%
Open Punctuation 25
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
217
11.0%
166
8.4%
166
8.4%
164
8.3%
162
8.2%
157
7.9%
157
7.9%
157
7.9%
157
7.9%
104
 
5.3%
Other values (35) 368
18.6%
Decimal Number
ValueCountFrequency (%)
1 172
20.5%
2 105
12.5%
9 103
12.3%
3 85
10.1%
8 79
9.4%
0 73
8.7%
4 71
8.5%
5 71
8.5%
6 42
 
5.0%
7 37
 
4.4%
Space Separator
ValueCountFrequency (%)
652
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%
Close Punctuation
ValueCountFrequency (%)
] 25
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1975
53.7%
Common 1706
46.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
217
11.0%
166
8.4%
166
8.4%
164
8.3%
162
8.2%
157
7.9%
157
7.9%
157
7.9%
157
7.9%
104
 
5.3%
Other values (35) 368
18.6%
Common
ValueCountFrequency (%)
652
38.2%
1 172
 
10.1%
- 166
 
9.7%
2 105
 
6.2%
9 103
 
6.0%
3 85
 
5.0%
8 79
 
4.6%
0 73
 
4.3%
4 71
 
4.2%
5 71
 
4.2%
Other values (4) 129
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1975
53.7%
ASCII 1706
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
652
38.2%
1 172
 
10.1%
- 166
 
9.7%
2 105
 
6.2%
9 103
 
6.0%
3 85
 
5.0%
8 79
 
4.6%
0 73
 
4.3%
4 71
 
4.2%
5 71
 
4.2%
Other values (4) 129
 
7.6%
Hangul
ValueCountFrequency (%)
217
11.0%
166
8.4%
166
8.4%
164
8.3%
162
8.2%
157
7.9%
157
7.9%
157
7.9%
157
7.9%
104
 
5.3%
Other values (35) 368
18.6%

도로명주소
Text

MISSING 

Distinct111
Distinct (%)100.0%
Missing46
Missing (%)29.3%
Memory size1.4 KiB
2024-05-11T15:26:21.294070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length25.873874
Min length20

Characters and Unicode

Total characters2872
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)100.0%

Sample

1st row서울특별시 금천구 시흥대로 89 (시흥동)
2nd row서울특별시 금천구 시흥대로54길 43 (시흥동)
3rd row서울특별시 금천구 시흥대로56길 20 (시흥동)
4th row서울특별시 금천구 금하로9길 4-22 (시흥동)
5th row서울특별시 금천구 시흥대로61길 30 (시흥동)
ValueCountFrequency (%)
서울특별시 111
19.7%
금천구 111
19.7%
독산동 39
 
6.9%
가산동 39
 
6.9%
시흥동 29
 
5.2%
독산로 18
 
3.2%
시흥대로 9
 
1.6%
가산로 7
 
1.2%
남부순환로108길 6
 
1.1%
남부순환로 5
 
0.9%
Other values (138) 189
33.6%
2024-05-11T15:26:22.288338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
452
 
15.7%
180
 
6.3%
114
 
4.0%
112
 
3.9%
112
 
3.9%
111
 
3.9%
111
 
3.9%
111
 
3.9%
111
 
3.9%
111
 
3.9%
Other values (56) 1347
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1722
60.0%
Space Separator 452
 
15.7%
Decimal Number 436
 
15.2%
Open Punctuation 113
 
3.9%
Close Punctuation 113
 
3.9%
Dash Punctuation 27
 
0.9%
Other Punctuation 8
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
180
 
10.5%
114
 
6.6%
112
 
6.5%
112
 
6.5%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
110
 
6.4%
Other values (38) 539
31.3%
Decimal Number
ValueCountFrequency (%)
1 100
22.9%
2 70
16.1%
3 57
13.1%
5 40
 
9.2%
8 38
 
8.7%
0 33
 
7.6%
6 32
 
7.3%
4 30
 
6.9%
9 19
 
4.4%
7 17
 
3.9%
Open Punctuation
ValueCountFrequency (%)
( 110
97.3%
[ 3
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 110
97.3%
] 3
 
2.7%
Space Separator
ValueCountFrequency (%)
452
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1722
60.0%
Common 1150
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
180
 
10.5%
114
 
6.6%
112
 
6.5%
112
 
6.5%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
110
 
6.4%
Other values (38) 539
31.3%
Common
ValueCountFrequency (%)
452
39.3%
( 110
 
9.6%
) 110
 
9.6%
1 100
 
8.7%
2 70
 
6.1%
3 57
 
5.0%
5 40
 
3.5%
8 38
 
3.3%
0 33
 
2.9%
6 32
 
2.8%
Other values (8) 108
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1722
60.0%
ASCII 1150
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
452
39.3%
( 110
 
9.6%
) 110
 
9.6%
1 100
 
8.7%
2 70
 
6.1%
3 57
 
5.0%
5 40
 
3.5%
8 38
 
3.3%
0 33
 
2.9%
6 32
 
2.8%
Other values (8) 108
 
9.4%
Hangul
ValueCountFrequency (%)
180
 
10.5%
114
 
6.6%
112
 
6.5%
112
 
6.5%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
111
 
6.4%
110
 
6.4%
Other values (38) 539
31.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)40.9%
Missing47
Missing (%)29.9%
Infinite0
Infinite (%)0.0%
Mean8566.3091
Minimum8505
Maximum8642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:22.700190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8505
5-th percentile8509
Q18523
median8548.5
Q38621
95-th percentile8632
Maximum8642
Range137
Interquartile range (IQR)98

Descriptive statistics

Standard deviation48.350165
Coefficient of variation (CV)0.0056442237
Kurtosis-1.666405
Mean8566.3091
Median Absolute Deviation (MAD)35
Skewness0.24940311
Sum942294
Variance2337.7384
MonotonicityNot monotonic
2024-05-11T15:26:23.072825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
8515 10
 
6.4%
8632 8
 
5.1%
8628 8
 
5.1%
8527 8
 
5.1%
8512 6
 
3.8%
8528 6
 
3.8%
8509 5
 
3.2%
8626 4
 
2.5%
8541 3
 
1.9%
8602 3
 
1.9%
Other values (35) 49
31.2%
(Missing) 47
29.9%
ValueCountFrequency (%)
8505 2
 
1.3%
8509 5
3.2%
8512 6
3.8%
8515 10
6.4%
8518 1
 
0.6%
8521 1
 
0.6%
8522 2
 
1.3%
8523 2
 
1.3%
8526 3
 
1.9%
8527 8
5.1%
ValueCountFrequency (%)
8642 1
 
0.6%
8639 1
 
0.6%
8638 1
 
0.6%
8632 8
5.1%
8630 1
 
0.6%
8629 1
 
0.6%
8628 8
5.1%
8626 4
2.5%
8625 1
 
0.6%
8623 1
 
0.6%
Distinct145
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:26:23.785568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length14
Mean length4.522293
Min length2

Characters and Unicode

Total characters710
Distinct characters200
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

Unique135 ?
Unique (%)86.0%

Sample

1st row서울여인숙
2nd row화성여인숙
3rd row산호장
4th row가림모텔
5th row청명여관
ValueCountFrequency (%)
모텔 4
 
2.3%
서울여인숙 3
 
1.7%
대림장 3
 
1.7%
은성장 2
 
1.1%
스카이모텔 2
 
1.1%
대호 2
 
1.1%
덕수여인숙 2
 
1.1%
온천장 2
 
1.1%
강남여인숙 2
 
1.1%
독산 2
 
1.1%
Other values (149) 151
86.3%
2024-05-11T15:26:24.780962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
6.1%
41
 
5.8%
40
 
5.6%
39
 
5.5%
34
 
4.8%
29
 
4.1%
18
 
2.5%
18
 
2.5%
15
 
2.1%
13
 
1.8%
Other values (190) 420
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 642
90.4%
Space Separator 18
 
2.5%
Uppercase Letter 17
 
2.4%
Lowercase Letter 12
 
1.7%
Decimal Number 11
 
1.5%
Close Punctuation 4
 
0.6%
Open Punctuation 4
 
0.6%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
43
 
6.7%
41
 
6.4%
40
 
6.2%
39
 
6.1%
34
 
5.3%
29
 
4.5%
18
 
2.8%
15
 
2.3%
13
 
2.0%
12
 
1.9%
Other values (161) 358
55.8%
Uppercase Letter
ValueCountFrequency (%)
M 3
17.6%
S 3
17.6%
N 2
11.8%
O 2
11.8%
G 2
11.8%
I 1
 
5.9%
D 1
 
5.9%
V 1
 
5.9%
E 1
 
5.9%
H 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
a 4
33.3%
y 2
16.7%
l 2
16.7%
t 1
 
8.3%
e 1
 
8.3%
s 1
 
8.3%
n 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
3 2
18.2%
5 2
18.2%
2 2
18.2%
0 2
18.2%
4 1
9.1%
8 1
9.1%
6 1
9.1%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 642
90.4%
Common 39
 
5.5%
Latin 29
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
43
 
6.7%
41
 
6.4%
40
 
6.2%
39
 
6.1%
34
 
5.3%
29
 
4.5%
18
 
2.8%
15
 
2.3%
13
 
2.0%
12
 
1.9%
Other values (161) 358
55.8%
Latin
ValueCountFrequency (%)
a 4
13.8%
M 3
10.3%
S 3
10.3%
y 2
 
6.9%
N 2
 
6.9%
O 2
 
6.9%
G 2
 
6.9%
l 2
 
6.9%
I 1
 
3.4%
D 1
 
3.4%
Other values (7) 7
24.1%
Common
ValueCountFrequency (%)
18
46.2%
) 4
 
10.3%
( 4
 
10.3%
3 2
 
5.1%
5 2
 
5.1%
2 2
 
5.1%
0 2
 
5.1%
. 1
 
2.6%
4 1
 
2.6%
8 1
 
2.6%
Other values (2) 2
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 642
90.4%
ASCII 68
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
43
 
6.7%
41
 
6.4%
40
 
6.2%
39
 
6.1%
34
 
5.3%
29
 
4.5%
18
 
2.8%
15
 
2.3%
13
 
2.0%
12
 
1.9%
Other values (161) 358
55.8%
ASCII
ValueCountFrequency (%)
18
26.5%
) 4
 
5.9%
a 4
 
5.9%
( 4
 
5.9%
M 3
 
4.4%
S 3
 
4.4%
y 2
 
2.9%
N 2
 
2.9%
O 2
 
2.9%
3 2
 
2.9%
Other values (19) 24
35.3%
Distinct150
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1999-06-30 00:00:00
Maximum2024-04-29 16:42:14
2024-05-11T15:26:25.113990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:25.430037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
U
94 
I
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 94
59.9%
I 63
40.1%

Length

2024-05-11T15:26:25.727679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:25.915018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 94
59.9%
i 63
40.1%
Distinct67
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T15:26:26.114651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:26.407274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
여관업
88 
여인숙업
54 
관광호텔
숙박업(생활)
 
5
일반호텔
 
1

Length

Max length7
Median length3
Mean length3.5350318
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 88
56.1%
여인숙업 54
34.4%
관광호텔 9
 
5.7%
숙박업(생활) 5
 
3.2%
일반호텔 1
 
0.6%

Length

2024-05-11T15:26:26.747264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:26.978596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 88
56.1%
여인숙업 54
34.4%
관광호텔 9
 
5.7%
숙박업(생활 5
 
3.2%
일반호텔 1
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct146
Distinct (%)96.1%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean190776.74
Minimum189045.77
Maximum191924.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:27.236727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189045.77
5-th percentile189940.44
Q1190288.55
median190925.9
Q3191253.49
95-th percentile191466.61
Maximum191924.07
Range2878.3026
Interquartile range (IQR)964.94563

Descriptive statistics

Standard deviation558.59198
Coefficient of variation (CV)0.0029279879
Kurtosis-0.20776708
Mean190776.74
Median Absolute Deviation (MAD)427.2518
Skewness-0.49728466
Sum28998065
Variance312025
MonotonicityNot monotonic
2024-05-11T15:26:27.492352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190148.881786423 2
 
1.3%
190098.918650186 2
 
1.3%
190167.933272327 2
 
1.3%
190078.821709506 2
 
1.3%
190930.759909591 2
 
1.3%
190068.729745035 2
 
1.3%
190668.161430053 1
 
0.6%
190734.125570838 1
 
0.6%
191269.237466342 1
 
0.6%
191570.376413897 1
 
0.6%
Other values (136) 136
86.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
189045.768055551 1
0.6%
189046.547983753 1
0.6%
189621.964629027 1
0.6%
189683.494602093 1
0.6%
189693.316961667 1
0.6%
189736.88808904 1
0.6%
189766.845217023 1
0.6%
189919.971505268 1
0.6%
189957.184460904 1
0.6%
190008.123794906 1
0.6%
ValueCountFrequency (%)
191924.070619779 1
0.6%
191850.626105531 1
0.6%
191625.663303875 1
0.6%
191625.036933287 1
0.6%
191574.924293529 1
0.6%
191570.376413897 1
0.6%
191551.821907807 1
0.6%
191466.962552887 1
0.6%
191466.314553538 1
0.6%
191464.300734106 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct146
Distinct (%)96.1%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean440556.47
Minimum437779.97
Maximum442280.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:27.744553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437779.97
5-th percentile438945.63
Q1439154.69
median440922.28
Q3441791.63
95-th percentile441919.14
Maximum442280.46
Range4500.4979
Interquartile range (IQR)2636.9401

Descriptive statistics

Standard deviation1215.223
Coefficient of variation (CV)0.0027583818
Kurtosis-1.4727981
Mean440556.47
Median Absolute Deviation (MAD)923.20442
Skewness-0.26043153
Sum66964583
Variance1476766.9
MonotonicityNot monotonic
2024-05-11T15:26:28.037897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441801.145736064 2
 
1.3%
441873.000933179 2
 
1.3%
441818.394728263 2
 
1.3%
441909.433868313 2
 
1.3%
439050.144252294 2
 
1.3%
441921.822515904 2
 
1.3%
441118.006804771 1
 
0.6%
441028.013466643 1
 
0.6%
440737.627819565 1
 
0.6%
439554.609051948 1
 
0.6%
Other values (136) 136
86.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
437779.96705305 1
0.6%
438230.700875708 1
0.6%
438711.14083163 1
0.6%
438731.508615452 1
0.6%
438751.842732006 1
0.6%
438784.952009822 1
0.6%
438804.943966274 1
0.6%
438935.568524755 1
0.6%
438953.867911208 1
0.6%
438953.968598731 1
0.6%
ValueCountFrequency (%)
442280.46499288 1
0.6%
442262.746663668 1
0.6%
442248.968604575 1
0.6%
442244.988394894 1
0.6%
442237.925214279 1
0.6%
441930.422346464 1
0.6%
441921.822515904 2
1.3%
441916.949685778 1
0.6%
441909.433868313 2
1.3%
441893.577383115 1
0.6%

위생업태명
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
여관업
75 
여인숙업
44 
<NA>
30 
관광호텔
 
4
숙박업(생활)
 
4

Length

Max length7
Median length4
Mean length3.5987261
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 75
47.8%
여인숙업 44
28.0%
<NA> 30
 
19.1%
관광호텔 4
 
2.5%
숙박업(생활) 4
 
2.5%

Length

2024-05-11T15:26:28.677800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:28.882595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 75
47.8%
여인숙업 44
28.0%
na 30
 
19.1%
관광호텔 4
 
2.5%
숙박업(생활 4
 
2.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)12.6%
Missing70
Missing (%)44.6%
Infinite0
Infinite (%)0.0%
Mean2.0229885
Minimum0
Maximum20
Zeros61
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:29.089932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.5
95-th percentile9.7
Maximum20
Range20
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation3.8397463
Coefficient of variation (CV)1.8980564
Kurtosis5.3549782
Mean2.0229885
Median Absolute Deviation (MAD)0
Skewness2.207109
Sum176
Variance14.743651
MonotonicityNot monotonic
2024-05-11T15:26:29.247686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 61
38.9%
8 6
 
3.8%
3 4
 
2.5%
2 4
 
2.5%
5 4
 
2.5%
9 2
 
1.3%
10 2
 
1.3%
6 1
 
0.6%
13 1
 
0.6%
20 1
 
0.6%
(Missing) 70
44.6%
ValueCountFrequency (%)
0 61
38.9%
2 4
 
2.5%
3 4
 
2.5%
5 4
 
2.5%
6 1
 
0.6%
8 6
 
3.8%
9 2
 
1.3%
10 2
 
1.3%
11 1
 
0.6%
13 1
 
0.6%
ValueCountFrequency (%)
20 1
 
0.6%
13 1
 
0.6%
11 1
 
0.6%
10 2
 
1.3%
9 2
 
1.3%
8 6
3.8%
6 1
 
0.6%
5 4
2.5%
3 4
2.5%
2 4
2.5%
Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
72 
0
63 
1
15 
2
 
4
3
 
3

Length

Max length4
Median length1
Mean length2.3757962
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 72
45.9%
0 63
40.1%
1 15
 
9.6%
2 4
 
2.5%
3 3
 
1.9%

Length

2024-05-11T15:26:29.421091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:29.583400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 72
45.9%
0 63
40.1%
1 15
 
9.6%
2 4
 
2.5%
3 3
 
1.9%
Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
73 
0
63 
1
14 
2
 
5
3
 
1

Length

Max length4
Median length1
Mean length2.4012739
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 73
46.5%
0 63
40.1%
1 14
 
8.9%
2 5
 
3.2%
3 1
 
0.6%
10 1
 
0.6%

Length

2024-05-11T15:26:29.769027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:29.941584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
46.5%
0 63
40.1%
1 14
 
8.9%
2 5
 
3.2%
3 1
 
0.6%
10 1
 
0.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)15.8%
Missing81
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean1.5789474
Minimum0
Maximum20
Zeros57
Zeros (%)36.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:30.134328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile8.25
Maximum20
Range20
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation3.6194407
Coefficient of variation (CV)2.2923124
Kurtosis9.6285829
Mean1.5789474
Median Absolute Deviation (MAD)0
Skewness2.9136271
Sum120
Variance13.100351
MonotonicityNot monotonic
2024-05-11T15:26:30.336205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 57
36.3%
2 4
 
2.5%
8 4
 
2.5%
3 3
 
1.9%
4 1
 
0.6%
1 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%
13 1
 
0.6%
20 1
 
0.6%
Other values (2) 2
 
1.3%
(Missing) 81
51.6%
ValueCountFrequency (%)
0 57
36.3%
1 1
 
0.6%
2 4
 
2.5%
3 3
 
1.9%
4 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
8 4
 
2.5%
9 1
 
0.6%
11 1
 
0.6%
ValueCountFrequency (%)
20 1
 
0.6%
13 1
 
0.6%
11 1
 
0.6%
9 1
 
0.6%
8 4
2.5%
7 1
 
0.6%
6 1
 
0.6%
4 1
 
0.6%
3 3
1.9%
2 4
2.5%
Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
75 
0
75 
1
 
6
2
 
1

Length

Max length4
Median length1
Mean length2.433121
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 75
47.8%
0 75
47.8%
1 6
 
3.8%
2 1
 
0.6%

Length

2024-05-11T15:26:30.533536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:30.674696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 75
47.8%
0 75
47.8%
1 6
 
3.8%
2 1
 
0.6%
Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
83 
0
69 
2
 
2
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length2.5859873
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 83
52.9%
0 69
43.9%
2 2
 
1.3%
1 2
 
1.3%
3 1
 
0.6%

Length

2024-05-11T15:26:30.859432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:31.056962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 83
52.9%
0 69
43.9%
2 2
 
1.3%
1 2
 
1.3%
3 1
 
0.6%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)17.6%
Missing32
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean7.864
Minimum0
Maximum83
Zeros21
Zeros (%)13.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:31.289919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q310
95-th percentile15.8
Maximum83
Range83
Interquartile range (IQR)8

Descriptive statistics

Standard deviation9.7553492
Coefficient of variation (CV)1.2405073
Kurtosis31.496997
Mean7.864
Median Absolute Deviation (MAD)4
Skewness4.7405356
Sum983
Variance95.166839
MonotonicityNot monotonic
2024-05-11T15:26:31.453001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 21
13.4%
9 13
8.3%
8 11
 
7.0%
10 9
 
5.7%
4 9
 
5.7%
6 7
 
4.5%
11 7
 
4.5%
1 6
 
3.8%
3 6
 
3.8%
2 6
 
3.8%
Other values (12) 30
19.1%
(Missing) 32
20.4%
ValueCountFrequency (%)
0 21
13.4%
1 6
 
3.8%
2 6
 
3.8%
3 6
 
3.8%
4 9
5.7%
5 5
 
3.2%
6 7
 
4.5%
7 2
 
1.3%
8 11
7.0%
9 13
8.3%
ValueCountFrequency (%)
83 1
 
0.6%
53 1
 
0.6%
37 1
 
0.6%
26 1
 
0.6%
17 2
 
1.3%
16 1
 
0.6%
15 2
 
1.3%
14 3
1.9%
13 5
3.2%
12 6
3.8%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct38
Distinct (%)36.5%
Missing53
Missing (%)33.8%
Infinite0
Infinite (%)0.0%
Mean15.980769
Minimum0
Maximum176
Zeros28
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:31.634230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q317.25
95-th percentile51.95
Maximum176
Range176
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation23.777684
Coefficient of variation (CV)1.4878936
Kurtosis21.165322
Mean15.980769
Median Absolute Deviation (MAD)9
Skewness3.8801638
Sum1662
Variance565.37827
MonotonicityNot monotonic
2024-05-11T15:26:31.906320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 28
17.8%
14 7
 
4.5%
8 5
 
3.2%
13 4
 
2.5%
10 4
 
2.5%
11 4
 
2.5%
16 3
 
1.9%
17 3
 
1.9%
9 3
 
1.9%
2 3
 
1.9%
Other values (28) 40
25.5%
(Missing) 53
33.8%
ValueCountFrequency (%)
0 28
17.8%
2 3
 
1.9%
3 1
 
0.6%
4 3
 
1.9%
5 3
 
1.9%
6 1
 
0.6%
7 2
 
1.3%
8 5
 
3.2%
9 3
 
1.9%
10 4
 
2.5%
ValueCountFrequency (%)
176 1
0.6%
109 1
0.6%
72 1
0.6%
56 1
0.6%
55 1
0.6%
53 1
0.6%
46 2
1.3%
44 1
0.6%
43 1
0.6%
42 1
0.6%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)22.4%
Missing59
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean10.091837
Minimum0
Maximum43
Zeros43
Zeros (%)27.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:32.137499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10.5
Q318
95-th percentile29.15
Maximum43
Range43
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.536228
Coefficient of variation (CV)1.0440347
Kurtosis-0.36744746
Mean10.091837
Median Absolute Deviation (MAD)10.5
Skewness0.65042159
Sum989
Variance111.0121
MonotonicityNot monotonic
2024-05-11T15:26:32.339604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 43
27.4%
18 8
 
5.1%
17 6
 
3.8%
11 4
 
2.5%
16 4
 
2.5%
10 3
 
1.9%
21 3
 
1.9%
14 3
 
1.9%
5 3
 
1.9%
12 3
 
1.9%
Other values (12) 18
 
11.5%
(Missing) 59
37.6%
ValueCountFrequency (%)
0 43
27.4%
5 3
 
1.9%
10 3
 
1.9%
11 4
 
2.5%
12 3
 
1.9%
13 2
 
1.3%
14 3
 
1.9%
15 1
 
0.6%
16 4
 
2.5%
17 6
 
3.8%
ValueCountFrequency (%)
43 1
 
0.6%
35 1
 
0.6%
31 1
 
0.6%
30 2
1.3%
29 1
 
0.6%
26 2
1.3%
25 2
1.3%
24 1
 
0.6%
23 2
1.3%
21 3
1.9%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.6%
Missing30
Missing (%)19.1%
Memory size446.0 B
True
106 
False
21 
(Missing)
30 
ValueCountFrequency (%)
True 106
67.5%
False 21
 
13.4%
(Missing) 30
 
19.1%
2024-05-11T15:26:32.547021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)16.9%
Missing68
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean6.8089888
Minimum0
Maximum58
Zeros64
Zeros (%)40.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:26:32.722733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314
95-th percentile34
Maximum58
Range58
Interquartile range (IQR)14

Descriptive statistics

Standard deviation12.663366
Coefficient of variation (CV)1.8598012
Kurtosis3.755136
Mean6.8089888
Median Absolute Deviation (MAD)0
Skewness2.0033381
Sum606
Variance160.36083
MonotonicityNot monotonic
2024-05-11T15:26:32.911927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 64
40.8%
14 5
 
3.2%
18 3
 
1.9%
20 2
 
1.3%
30 2
 
1.3%
38 2
 
1.3%
22 2
 
1.3%
34 2
 
1.3%
17 1
 
0.6%
15 1
 
0.6%
Other values (5) 5
 
3.2%
(Missing) 68
43.3%
ValueCountFrequency (%)
0 64
40.8%
10 1
 
0.6%
14 5
 
3.2%
15 1
 
0.6%
16 1
 
0.6%
17 1
 
0.6%
18 3
 
1.9%
20 2
 
1.3%
22 2
 
1.3%
28 1
 
0.6%
ValueCountFrequency (%)
58 1
 
0.6%
50 1
 
0.6%
38 2
1.3%
34 2
1.3%
30 2
1.3%
28 1
 
0.6%
22 2
1.3%
20 2
1.3%
18 3
1.9%
17 1
 
0.6%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing157
Missing (%)100.0%
Memory size1.5 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
136 
자가
15 
임대
 
6

Length

Max length4
Median length4
Mean length3.7324841
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 136
86.6%
자가 15
 
9.6%
임대 6
 
3.8%

Length

2024-05-11T15:26:33.148914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:33.344842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
86.6%
자가 15
 
9.6%
임대 6
 
3.8%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
83 
0
74 

Length

Max length4
Median length4
Mean length2.5859873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 83
52.9%
0 74
47.1%

Length

2024-05-11T15:26:33.556864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:33.751740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 83
52.9%
0 74
47.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
0
 
4
20
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.8789809
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
95.5%
0 4
 
2.5%
20 2
 
1.3%
2 1
 
0.6%

Length

2024-05-11T15:26:33.944195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:34.146436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
95.5%
0 4
 
2.5%
20 2
 
1.3%
2 1
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
0
 
3
35
 
1
10
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.8789809
Min length1

Unique

Unique4 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
95.5%
0 3
 
1.9%
35 1
 
0.6%
10 1
 
0.6%
1 1
 
0.6%
5 1
 
0.6%

Length

2024-05-11T15:26:34.360507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:34.597404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
95.5%
0 3
 
1.9%
35 1
 
0.6%
10 1
 
0.6%
1 1
 
0.6%
5 1
 
0.6%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
84 
0
73 

Length

Max length4
Median length4
Mean length2.6050955
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
53.5%
0 73
46.5%

Length

2024-05-11T15:26:34.805151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:34.994277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
53.5%
0 73
46.5%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
84 
0
73 

Length

Max length4
Median length4
Mean length2.6050955
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
53.5%
0 73
46.5%

Length

2024-05-11T15:26:35.178553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:35.370376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
53.5%
0 73
46.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.6%
Missing30
Missing (%)19.1%
Memory size446.0 B
False
125 
True
 
2
(Missing)
30 
ValueCountFrequency (%)
False 125
79.6%
True 2
 
1.3%
(Missing) 30
 
19.1%
2024-05-11T15:26:35.581766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031700003170000-201-1968-0003819680118<NA>3폐업2폐업20110504<NA><NA><NA>02 8079766105.83153858서울특별시 금천구 시흥동 883-2번지 [시흥대로 455]<NA><NA>서울여인숙2010-11-03 17:42:16I2018-08-31 23:59:59.0여관업191178.177948439162.168009여관업3<NA><NA><NA><NA><NA>15<NA><NA>Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
131700003170000-201-1969-000901969-12-22<NA>3폐업2폐업2024-02-06<NA><NA><NA>02 804657853.22153-863서울특별시 금천구 시흥동 984-23서울특별시 금천구 시흥대로 89 (시흥동)8639화성여인숙2024-02-06 11:24:48U2023-12-02 00:08:00.0여인숙업191361.557993437779.967053<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231700003170000-201-1970-0003919700113<NA>3폐업2폐업20100126<NA><NA><NA>02 8049588111.77153864서울특별시 금천구 시흥동 995-55번지 [금천로 227-1]<NA><NA>산호장2008-12-11 08:30:08I2018-08-31 23:59:59.0여관업191000.001385439094.880915여관업3113<NA><NA>132<NA>Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
331700003170000-201-1970-0004019700825<NA>3폐업2폐업20210430<NA><NA><NA>02 8085695441.52153858서울특별시 금천구 시흥동 888-17서울특별시 금천구 시흥대로54길 43 (시흥동)8628가림모텔2021-04-30 15:14:14U2021-05-02 02:40:00.0여관업191291.9911439032.583497여관업00000041421Y17<NA><NA><NA><NA>0<NA><NA>00N
431700003170000-201-1970-0004119701014<NA>3폐업2폐업20221227<NA><NA><NA>02 8959993146.84153858서울특별시 금천구 시흥동 891-20서울특별시 금천구 시흥대로56길 20 (시흥동)8629청명여관2022-12-27 10:36:40U2021-11-01 22:09:00.0여관업191327.055178438935.568525<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531700003170000-201-1970-0009119701026<NA>3폐업2폐업20050913<NA><NA><NA>02 802597059.11153864서울특별시 금천구 시흥동 998-6번지<NA><NA>송월여인숙2003-12-23 00:00:00I2018-08-31 23:59:59.0여인숙업190908.865497439094.636276여인숙업<NA><NA><NA><NA><NA><NA>12<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631700003170000-201-1970-0009219701216<NA>1영업/정상1영업<NA><NA><NA><NA>02 8058592151.41153857서울특별시 금천구 시흥동 879-95서울특별시 금천구 금하로9길 4-22 (시흥동)8626용궁여인숙2021-04-22 09:26:08U2021-04-24 02:40:00.0여인숙업191354.198851439128.318804여인숙업000000900Y0<NA><NA><NA><NA>0<NA><NA>00N
731700003170000-201-1971-0000619710114<NA>3폐업2폐업19980821<NA><NA><NA>02 8541452.00153844서울특별시 금천구 시흥동 265-5번지<NA><NA>해운장2002-01-13 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>1300Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831700003170000-201-1971-0000719710810<NA>3폐업2폐업20130603<NA><NA><NA>02 802957250.74153864서울특별시 금천구 시흥동 995-53번지서울특별시 금천구 시흥대로61길 30 (시흥동)8632경화2012-09-25 14:23:13I2018-08-31 23:59:59.0여관업190996.579111439083.411971여관업000000720Y0<NA><NA><NA><NA>0<NA><NA>00N
931700003170000-201-1971-0000819710914<NA>3폐업2폐업20030222<NA><NA><NA>02 8058459.00153859서울특별시 금천구 시흥동 911-0번지<NA><NA>영화장2003-02-22 00:00:00I2018-08-31 23:59:59.0여관업191850.626106438751.842732여관업<NA><NA><NA><NA><NA><NA>8<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14731700003170000-201-2017-0000220171120<NA>3폐업2폐업20220307<NA><NA><NA>02 85371116,160.42153801서울특별시 금천구 가산동 139-8서울특별시 금천구 벚꽃로56길 190 (가산동)8512호텔해담채가산2022-03-07 10:18:59U2022-03-10 02:40:00.0관광호텔190089.940594441930.422346관광호텔2021201201760N0<NA><NA><NA><NA>0201000N
14831700003170000-201-2019-000012019-05-29<NA>1영업/정상1영업<NA><NA><NA><NA>02209640208703.63153-010서울특별시 금천구 독산동 1156 금천롯데캐슬골드파크4차서울특별시 금천구 시흥대로 315 (독산동)8608엠디호텔 독산2024-03-25 10:43:28U2023-12-02 22:07:00.0관광호텔190799.832999439885.941303<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14931700003170000-201-2019-000022019-11-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 8948888982.80153-858서울특별시 금천구 시흥동 888-11서울특별시 금천구 시흥대로56길 15, 트리플8호텔 (시흥동)8628트리플8호텔2023-09-26 10:11:49U2022-12-08 22:08:00.0관광호텔191301.371054438953.867911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15031700003170000-201-2023-000012023-08-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>299.83153-801서울특별시 금천구 가산동 139-18서울특별시 금천구 디지털로11길 8, 4~5층 (가산동)8512레지던스20402023-08-11 15:40:24I2022-12-07 23:03:00.0여관업190098.91865441873.000933<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15131700003170000-201-2023-000022023-11-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4639.00153-813서울특별시 금천구 독산동 296-2서울특별시 금천구 시흥대로123길 66 (독산동)8523팔팔호텔2023-11-17 14:43:18I2022-10-31 23:09:00.0관광호텔190668.16143441118.006805<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15231700003170000-214-2018-000012018-09-17<NA>1영업/정상1영업<NA><NA><NA><NA>02 88327006008.89153-814서울특별시 금천구 독산동 336-28서울특별시 금천구 벚꽃로 182 (독산동)8526홈즈스테이 지밸리 가산(HOMES Stay G-Valley Gasan)2024-04-29 16:42:14U2023-12-05 00:01:00.0숙박업(생활)190008.123795441016.56196<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15331700003170000-214-2018-0000220181217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,605.13153801서울특별시 금천구 가산동 238-74서울특별시 금천구 벚꽃로 204 (가산동)8518바모스2022-03-02 17:26:12U2022-03-04 02:40:00.0숙박업(생활)189919.971505441209.131323숙박업(생활)1021002083100N0<NA><NA><NA>자가00000N
15431700003170000-214-2020-0000120200519<NA>1영업/정상1영업<NA><NA><NA><NA>02 85531102,137.72153814서울특별시 금천구 독산동 335-8서울특별시 금천구 두산로5길 7, 스텔라이호텔 (독산동)8526스텔라이호텔2020-09-11 14:50:14U2020-09-13 02:40:00.0숙박업(생활)190204.539881440974.712402숙박업(생활)111111110720N0<NA><NA><NA>자가02100Y
15531700003170000-214-2021-0000120210423<NA>1영업/정상1영업<NA><NA><NA><NA>0285609331,770.38153814서울특별시 금천구 독산동 335-21서울특별시 금천구 가산로3길 103 (독산동)8526위너스2021-04-23 10:06:22I2021-04-25 00:22:57.0숙박업(생활)190183.499829441092.525925숙박업(생활)102<NA><NA><NA><NA>5300N0<NA><NA><NA>자가00500Y
15631700003170000-214-2022-0000120220218<NA>1영업/정상1영업<NA><NA><NA><NA><NA>998.44153829서울특별시 금천구 독산동 1006-112서울특별시 금천구 범안로12길 29-29 (독산동)8602로즈데일 인 독산2022-02-24 10:06:56U2022-02-26 02:40:00.0숙박업(생활)190517.410148440300.104174숙박업(생활)9119111530N0<NA><NA><NA>자가00000N