Overview

Dataset statistics

Number of variables47
Number of observations55
Missing cells538
Missing cells (%)20.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.8 KiB
Average record size in memory406.4 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-17441/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (51.5%)Imbalance
건물소유구분명 is highly imbalanced (66.7%)Imbalance
인허가취소일자 has 55 (100.0%) missing valuesMissing
폐업일자 has 16 (29.1%) missing valuesMissing
휴업시작일자 has 55 (100.0%) missing valuesMissing
휴업종료일자 has 55 (100.0%) missing valuesMissing
재개업일자 has 55 (100.0%) missing valuesMissing
도로명주소 has 23 (41.8%) missing valuesMissing
도로명우편번호 has 24 (43.6%) missing valuesMissing
좌표정보(X) has 6 (10.9%) missing valuesMissing
좌표정보(Y) has 6 (10.9%) missing valuesMissing
건물지상층수 has 19 (34.5%) missing valuesMissing
한실수 has 11 (20.0%) missing valuesMissing
양실수 has 13 (23.6%) missing valuesMissing
욕실수 has 15 (27.3%) missing valuesMissing
발한실여부 has 10 (18.2%) missing valuesMissing
조건부허가신고사유 has 55 (100.0%) missing valuesMissing
조건부허가시작일자 has 55 (100.0%) missing valuesMissing
조건부허가종료일자 has 55 (100.0%) missing valuesMissing
다중이용업소여부 has 10 (18.2%) missing valuesMissing
관리번호 has unique valuesUnique
전화번호 has unique valuesUnique
소재지면적 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 5 (9.1%) zerosZeros
한실수 has 7 (12.7%) zerosZeros
양실수 has 2 (3.6%) zerosZeros
욕실수 has 8 (14.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:49:08.066774
Analysis finished2024-05-11 05:49:08.970710
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
3140000
55 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 55
100.0%

Length

2024-05-11T14:49:09.090778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:09.234733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 55
100.0%

관리번호
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2024-05-11T14:49:09.490855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1210
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

Unique55 ?
Unique (%)100.0%

Sample

1st row3140000-201-1971-00047
2nd row3140000-201-1972-00045
3rd row3140000-201-1972-00046
4th row3140000-201-1973-00037
5th row3140000-201-1973-00039
ValueCountFrequency (%)
3140000-201-1971-00047 1
 
1.8%
3140000-201-1983-00017 1
 
1.8%
3140000-201-1983-00020 1
 
1.8%
3140000-201-1983-00021 1
 
1.8%
3140000-201-1983-00022 1
 
1.8%
3140000-201-1983-00036 1
 
1.8%
3140000-201-1983-00041 1
 
1.8%
3140000-201-1984-00012 1
 
1.8%
3140000-201-1984-00013 1
 
1.8%
3140000-201-1984-00014 1
 
1.8%
Other values (45) 45
81.8%
2024-05-11T14:49:10.013825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 478
39.5%
1 184
 
15.2%
- 165
 
13.6%
2 95
 
7.9%
3 86
 
7.1%
4 74
 
6.1%
9 57
 
4.7%
8 45
 
3.7%
7 12
 
1.0%
5 8
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1045
86.4%
Dash Punctuation 165
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 478
45.7%
1 184
 
17.6%
2 95
 
9.1%
3 86
 
8.2%
4 74
 
7.1%
9 57
 
5.5%
8 45
 
4.3%
7 12
 
1.1%
5 8
 
0.8%
6 6
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 478
39.5%
1 184
 
15.2%
- 165
 
13.6%
2 95
 
7.9%
3 86
 
7.1%
4 74
 
6.1%
9 57
 
4.7%
8 45
 
3.7%
7 12
 
1.0%
5 8
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 478
39.5%
1 184
 
15.2%
- 165
 
13.6%
2 95
 
7.9%
3 86
 
7.1%
4 74
 
6.1%
9 57
 
4.7%
8 45
 
3.7%
7 12
 
1.0%
5 8
 
0.7%

인허가일자
Date

Distinct52
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum1971-01-15 00:00:00
Maximum2013-10-14 00:00:00
2024-05-11T14:49:10.248326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:10.625874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
3
39 
1
16 

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 39
70.9%
1 16
29.1%

Length

2024-05-11T14:49:10.858930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:11.029022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 39
70.9%
1 16
29.1%

영업상태명
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
폐업
39 
영업/정상
16 

Length

Max length5
Median length2
Mean length2.8727273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 39
70.9%
영업/정상 16
29.1%

Length

2024-05-11T14:49:11.227326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:11.396736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 39
70.9%
영업/정상 16
29.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
2
39 
1
16 

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 39
70.9%
1 16
29.1%

Length

2024-05-11T14:49:11.555580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:11.737411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 39
70.9%
1 16
29.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
폐업
39 
영업
16 

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 39
70.9%
영업 16
29.1%

Length

2024-05-11T14:49:11.918127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:12.396111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 39
70.9%
영업 16
29.1%

폐업일자
Date

MISSING 

Distinct37
Distinct (%)94.9%
Missing16
Missing (%)29.1%
Memory size572.0 B
Minimum1994-10-27 00:00:00
Maximum2023-08-07 00:00:00
2024-05-11T14:49:12.563952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:12.915978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

전화번호
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2024-05-11T14:49:13.244615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.018182
Min length10

Characters and Unicode

Total characters551
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

Unique55 ?
Unique (%)100.0%

Sample

1st row02 6036542
2nd row0226521887
3rd row02 6022344
4th row0226420017
5th row0226524047
ValueCountFrequency (%)
02 9
 
14.1%
6036542 1
 
1.6%
0226979394 1
 
1.6%
0226026270 1
 
1.6%
0226030301 1
 
1.6%
0206054616 1
 
1.6%
0206963199 1
 
1.6%
0226428359 1
 
1.6%
6486565 1
 
1.6%
0226467110 1
 
1.6%
Other values (46) 46
71.9%
2024-05-11T14:49:13.910002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 121
22.0%
0 117
21.2%
6 89
16.2%
4 41
 
7.4%
5 37
 
6.7%
9 36
 
6.5%
3 32
 
5.8%
1 27
 
4.9%
8 23
 
4.2%
7 19
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542
98.4%
Space Separator 9
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 121
22.3%
0 117
21.6%
6 89
16.4%
4 41
 
7.6%
5 37
 
6.8%
9 36
 
6.6%
3 32
 
5.9%
1 27
 
5.0%
8 23
 
4.2%
7 19
 
3.5%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 121
22.0%
0 117
21.2%
6 89
16.2%
4 41
 
7.4%
5 37
 
6.7%
9 36
 
6.5%
3 32
 
5.8%
1 27
 
4.9%
8 23
 
4.2%
7 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 121
22.0%
0 117
21.2%
6 89
16.2%
4 41
 
7.4%
5 37
 
6.7%
9 36
 
6.5%
3 32
 
5.8%
1 27
 
4.9%
8 23
 
4.2%
7 19
 
3.4%

소재지면적
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2024-05-11T14:49:14.294305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9272727
Min length3

Characters and Unicode

Total characters326
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

Unique55 ?
Unique (%)100.0%

Sample

1st row195.70
2nd row54.20
3rd row48.66
4th row131.18
5th row44.30
ValueCountFrequency (%)
195.70 1
 
1.8%
00 1
 
1.8%
114.55 1
 
1.8%
263.97 1
 
1.8%
739.84 1
 
1.8%
106.52 1
 
1.8%
60.10 1
 
1.8%
890.90 1
 
1.8%
166.37 1
 
1.8%
283.88 1
 
1.8%
Other values (45) 45
81.8%
2024-05-11T14:49:14.827473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 55
16.9%
2 33
10.1%
8 32
9.8%
1 30
9.2%
5 29
8.9%
4 29
8.9%
3 28
8.6%
0 26
8.0%
6 26
8.0%
9 19
 
5.8%
Other values (2) 19
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 268
82.2%
Other Punctuation 58
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 33
12.3%
8 32
11.9%
1 30
11.2%
5 29
10.8%
4 29
10.8%
3 28
10.4%
0 26
9.7%
6 26
9.7%
9 19
7.1%
7 16
6.0%
Other Punctuation
ValueCountFrequency (%)
. 55
94.8%
, 3
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 55
16.9%
2 33
10.1%
8 32
9.8%
1 30
9.2%
5 29
8.9%
4 29
8.9%
3 28
8.6%
0 26
8.0%
6 26
8.0%
9 19
 
5.8%
Other values (2) 19
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 55
16.9%
2 33
10.1%
8 32
9.8%
1 30
9.2%
5 29
8.9%
4 29
8.9%
3 28
8.6%
0 26
8.0%
6 26
8.0%
9 19
 
5.8%
Other values (2) 19
 
5.8%

소재지우편번호
Categorical

Distinct26
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
158825
5 
158857
4 
158806
 
3
158811
 
3
158864
 
3
Other values (21)
37 

Length

Max length7
Median length6
Mean length6.0545455
Min length6

Unique

Unique10 ?
Unique (%)18.2%

Sample

1st row158849
2nd row158862
3rd row158806
4th row158811
5th row158862

Common Values

ValueCountFrequency (%)
158825 5
 
9.1%
158857 4
 
7.3%
158806 3
 
5.5%
158811 3
 
5.5%
158864 3
 
5.5%
158808 3
 
5.5%
158824 3
 
5.5%
158828 3
 
5.5%
158861 3
 
5.5%
158862 3
 
5.5%
Other values (16) 22
40.0%

Length

2024-05-11T14:49:15.055431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
158825 5
 
9.1%
158857 4
 
7.3%
158806 3
 
5.5%
158811 3
 
5.5%
158864 3
 
5.5%
158808 3
 
5.5%
158824 3
 
5.5%
158828 3
 
5.5%
158861 3
 
5.5%
158862 3
 
5.5%
Other values (16) 22
40.0%

지번주소
Text

Distinct54
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
2024-05-11T14:49:15.417715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length22.4
Min length18

Characters and Unicode

Total characters1232
Distinct characters44
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

Unique53 ?
Unique (%)96.4%

Sample

1st row서울특별시 양천구 신정동 119-57번지
2nd row서울특별시 양천구 신정동 1033-12번지
3rd row서울특별시 양천구 목동 404-156번지
4th row서울특별시 양천구 목동 607-18번지
5th row서울특별시 양천구 신정동 1035-22번지
ValueCountFrequency (%)
서울특별시 55
23.8%
양천구 55
23.8%
신정동 24
10.4%
신월동 20
 
8.7%
목동 11
 
4.8%
145-14번지 2
 
0.9%
2~3층 2
 
0.9%
444-18번지 2
 
0.9%
부곡빌딩 1
 
0.4%
953-1 1
 
0.4%
Other values (58) 58
25.1%
2024-05-11T14:49:16.006162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
17.9%
1 66
 
5.4%
서 55
 
4.5%
- 55
 
4.5%
특 55
 
4.5%
별 55
 
4.5%
시 55
 
4.5%
양 55
 
4.5%
천 55
 
4.5%
구 55
 
4.5%
Other values (34) 505
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 685
55.6%
Decimal Number 266
 
21.6%
Space Separator 221
 
17.9%
Dash Punctuation 55
 
4.5%
Math Symbol 4
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 55
 
8.0%
특 55
 
8.0%
별 55
 
8.0%
시 55
 
8.0%
양 55
 
8.0%
천 55
 
8.0%
구 55
 
8.0%
울 55
 
8.0%
동 55
 
8.0%
신 44
 
6.4%
Other values (20) 146
21.3%
Decimal Number
ValueCountFrequency (%)
1 66
24.8%
3 31
11.7%
2 30
11.3%
4 25
 
9.4%
0 23
 
8.6%
5 22
 
8.3%
8 21
 
7.9%
9 19
 
7.1%
6 15
 
5.6%
7 14
 
5.3%
Space Separator
ValueCountFrequency (%)
221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 685
55.6%
Common 547
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 55
 
8.0%
특 55
 
8.0%
별 55
 
8.0%
시 55
 
8.0%
양 55
 
8.0%
천 55
 
8.0%
구 55
 
8.0%
울 55
 
8.0%
동 55
 
8.0%
신 44
 
6.4%
Other values (20) 146
21.3%
Common
ValueCountFrequency (%)
221
40.4%
1 66
 
12.1%
- 55
 
10.1%
3 31
 
5.7%
2 30
 
5.5%
4 25
 
4.6%
0 23
 
4.2%
5 22
 
4.0%
8 21
 
3.8%
9 19
 
3.5%
Other values (4) 34
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 685
55.6%
ASCII 547
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
40.4%
1 66
 
12.1%
- 55
 
10.1%
3 31
 
5.7%
2 30
 
5.5%
4 25
 
4.6%
0 23
 
4.2%
5 22
 
4.0%
8 21
 
3.8%
9 19
 
3.5%
Other values (4) 34
 
6.2%
Hangul
ValueCountFrequency (%)
서 55
 
8.0%
특 55
 
8.0%
별 55
 
8.0%
시 55
 
8.0%
양 55
 
8.0%
천 55
 
8.0%
구 55
 
8.0%
울 55
 
8.0%
동 55
 
8.0%
신 44
 
6.4%
Other values (20) 146
21.3%

도로명주소
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing23
Missing (%)41.8%
Memory size572.0 B
2024-05-11T14:49:16.365463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length27.96875
Min length21

Characters and Unicode

Total characters895
Distinct characters63
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

Unique32 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 중앙로43길 3 (신정동)
2nd row서울특별시 양천구 목동중앙북로14길 7, 2층 (목동)
3rd row서울특별시 양천구 신정중앙로 30 (신정동)
4th row서울특별시 양천구 중앙로 233 (신정동)
5th row서울특별시 양천구 중앙로 245, 2~3층 (신정동)
ValueCountFrequency (%)
서울특별시 32
17.3%
양천구 32
17.3%
신월동 13
 
7.0%
신정동 11
 
5.9%
목동 7
 
3.8%
2~3층 6
 
3.2%
가로공원로 5
 
2.7%
2층 4
 
2.2%
중앙로 4
 
2.2%
3층 3
 
1.6%
Other values (57) 68
36.8%
2024-05-11T14:49:16.952312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153
 
17.1%
로 38
 
4.2%
동 35
 
3.9%
천 32
 
3.6%
( 32
 
3.6%
) 32
 
3.6%
구 32
 
3.6%
서 32
 
3.6%
양 32
 
3.6%
시 32
 
3.6%
Other values (53) 445
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 513
57.3%
Space Separator 153
 
17.1%
Decimal Number 128
 
14.3%
Open Punctuation 32
 
3.6%
Close Punctuation 32
 
3.6%
Other Punctuation 23
 
2.6%
Math Symbol 14
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 38
 
7.4%
동 35
 
6.8%
천 32
 
6.2%
구 32
 
6.2%
서 32
 
6.2%
양 32
 
6.2%
시 32
 
6.2%
별 32
 
6.2%
특 32
 
6.2%
울 32
 
6.2%
Other values (38) 184
35.9%
Decimal Number
ValueCountFrequency (%)
3 28
21.9%
2 26
20.3%
1 24
18.8%
6 11
 
8.6%
4 10
 
7.8%
0 7
 
5.5%
7 7
 
5.5%
5 6
 
4.7%
9 6
 
4.7%
8 3
 
2.3%
Space Separator
ValueCountFrequency (%)
153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
57.3%
Common 382
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 38
 
7.4%
동 35
 
6.8%
천 32
 
6.2%
구 32
 
6.2%
서 32
 
6.2%
양 32
 
6.2%
시 32
 
6.2%
별 32
 
6.2%
특 32
 
6.2%
울 32
 
6.2%
Other values (38) 184
35.9%
Common
ValueCountFrequency (%)
153
40.1%
( 32
 
8.4%
) 32
 
8.4%
3 28
 
7.3%
2 26
 
6.8%
1 24
 
6.3%
, 23
 
6.0%
~ 14
 
3.7%
6 11
 
2.9%
4 10
 
2.6%
Other values (5) 29
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 513
57.3%
ASCII 382
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
153
40.1%
( 32
 
8.4%
) 32
 
8.4%
3 28
 
7.3%
2 26
 
6.8%
1 24
 
6.3%
, 23
 
6.0%
~ 14
 
3.7%
6 11
 
2.9%
4 10
 
2.6%
Other values (5) 29
 
7.6%
Hangul
ValueCountFrequency (%)
로 38
 
7.4%
동 35
 
6.8%
천 32
 
6.2%
구 32
 
6.2%
서 32
 
6.2%
양 32
 
6.2%
시 32
 
6.2%
별 32
 
6.2%
특 32
 
6.2%
울 32
 
6.2%
Other values (38) 184
35.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)74.2%
Missing24
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean7975.4194
Minimum7905
Maximum8082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:17.171820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7905
5-th percentile7906
Q17920
median7966
Q38026.5
95-th percentile8079.5
Maximum8082
Range177
Interquartile range (IQR)106.5

Descriptive statistics

Standard deviation63.199564
Coefficient of variation (CV)0.0079242936
Kurtosis-1.2339227
Mean7975.4194
Median Absolute Deviation (MAD)54
Skewness0.5047063
Sum247238
Variance3994.1849
MonotonicityNot monotonic
2024-05-11T14:49:17.414760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
7907 3
 
5.5%
7968 2
 
3.6%
7920 2
 
3.6%
7923 2
 
3.6%
8073 2
 
3.6%
8082 2
 
3.6%
7906 2
 
3.6%
8028 1
 
1.8%
7917 1
 
1.8%
8026 1
 
1.8%
Other values (13) 13
23.6%
(Missing) 24
43.6%
ValueCountFrequency (%)
7905 1
 
1.8%
7906 2
3.6%
7907 3
5.5%
7917 1
 
1.8%
7920 2
3.6%
7923 2
3.6%
7937 1
 
1.8%
7940 1
 
1.8%
7943 1
 
1.8%
7946 1
 
1.8%
ValueCountFrequency (%)
8082 2
3.6%
8077 1
1.8%
8073 2
3.6%
8063 1
1.8%
8028 1
1.8%
8027 1
1.8%
8026 1
1.8%
8020 1
1.8%
8007 1
1.8%
7999 1
1.8%

사업장명
Text

Distinct54
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
2024-05-11T14:49:17.863643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.6727273
Min length3

Characters and Unicode

Total characters257
Distinct characters101
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

Unique53 ?
Unique (%)96.4%

Sample

1st row화신여인숙
2nd row신정여인숙
3rd row중앙여인숙
4th row등마루여관
5th row궁전여인숙
ValueCountFrequency (%)
제일여관 2
 
3.5%
약수여관 1
 
1.8%
로즈모텔 1
 
1.8%
모텔메종 1
 
1.8%
고려여관 1
 
1.8%
이브모텔 1
 
1.8%
아도호텔(ado 1
 
1.8%
hotel 1
 
1.8%
동선여관 1
 
1.8%
남미여인숙 1
 
1.8%
Other values (46) 46
80.7%
2024-05-11T14:49:18.498056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
여 30
 
11.7%
관 22
 
8.6%
텔 16
 
6.2%
모 14
 
5.4%
장 9
 
3.5%
숙 9
 
3.5%
인 9
 
3.5%
신 7
 
2.7%
스 6
 
2.3%
( 4
 
1.6%
Other values (91) 131
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 230
89.5%
Uppercase Letter 11
 
4.3%
Open Punctuation 4
 
1.6%
Close Punctuation 4
 
1.6%
Lowercase Letter 4
 
1.6%
Space Separator 2
 
0.8%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 30
 
13.0%
관 22
 
9.6%
텔 16
 
7.0%
모 14
 
6.1%
장 9
 
3.9%
숙 9
 
3.9%
인 9
 
3.9%
신 7
 
3.0%
스 6
 
2.6%
월 4
 
1.7%
Other values (73) 104
45.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
A 2
18.2%
Q 1
9.1%
D 1
9.1%
O 1
9.1%
H 1
9.1%
B 1
9.1%
T 1
9.1%
Y 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
t 1
25.0%
e 1
25.0%
l 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
5 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 230
89.5%
Latin 15
 
5.8%
Common 12
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 30
 
13.0%
관 22
 
9.6%
텔 16
 
7.0%
모 14
 
6.1%
장 9
 
3.9%
숙 9
 
3.9%
인 9
 
3.9%
신 7
 
3.0%
스 6
 
2.6%
월 4
 
1.7%
Other values (73) 104
45.2%
Latin
ValueCountFrequency (%)
S 2
13.3%
A 2
13.3%
Q 1
 
6.7%
D 1
 
6.7%
O 1
 
6.7%
H 1
 
6.7%
o 1
 
6.7%
B 1
 
6.7%
t 1
 
6.7%
e 1
 
6.7%
Other values (3) 3
20.0%
Common
ValueCountFrequency (%)
( 4
33.3%
) 4
33.3%
2
16.7%
2 1
 
8.3%
5 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 230
89.5%
ASCII 27
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
여 30
 
13.0%
관 22
 
9.6%
텔 16
 
7.0%
모 14
 
6.1%
장 9
 
3.9%
숙 9
 
3.9%
인 9
 
3.9%
신 7
 
3.0%
스 6
 
2.6%
월 4
 
1.7%
Other values (73) 104
45.2%
ASCII
ValueCountFrequency (%)
( 4
14.8%
) 4
14.8%
S 2
 
7.4%
A 2
 
7.4%
2
 
7.4%
Q 1
 
3.7%
D 1
 
3.7%
O 1
 
3.7%
H 1
 
3.7%
o 1
 
3.7%
Other values (8) 8
29.6%

최종수정일자
Date

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum1999-01-21 00:00:00
Maximum2024-05-02 13:27:20
2024-05-11T14:49:18.739829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:18.979867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
I
28 
U
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 28
50.9%
U 27
49.1%

Length

2024-05-11T14:49:19.223702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:19.380483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 28
50.9%
u 27
49.1%

데이터갱신일자
Date

Distinct22
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T14:49:19.537519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:19.752110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
여관업
45 
여인숙업
9 
관광호텔
 
1

Length

Max length4
Median length3
Mean length3.1818182
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 45
81.8%
여인숙업 9
 
16.4%
관광호텔 1
 
1.8%

Length

2024-05-11T14:49:19.981795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:20.156869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 45
81.8%
여인숙업 9
 
16.4%
관광호텔 1
 
1.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)85.7%
Missing6
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean186800.5
Minimum184783.4
Maximum188994.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:20.339045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184783.4
5-th percentile184844.88
Q1185398.81
median187006.45
Q3187871.36
95-th percentile188897.68
Maximum188994.19
Range4210.7919
Interquartile range (IQR)2472.5492

Descriptive statistics

Standard deviation1350.428
Coefficient of variation (CV)0.0072292526
Kurtosis-1.2325327
Mean186800.5
Median Absolute Deviation (MAD)1020.9547
Skewness-0.037561438
Sum9153224.5
Variance1823655.8
MonotonicityNot monotonic
2024-05-11T14:49:20.587186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
187871.363218228 2
 
3.6%
185985.497026543 2
 
3.6%
184783.397041118 2
 
3.6%
184844.878863426 2
 
3.6%
185307.072104229 2
 
3.6%
187310.712769643 2
 
3.6%
185398.814014343 2
 
3.6%
185469.109541377 1
 
1.8%
185197.262475103 1
 
1.8%
187068.485002706 1
 
1.8%
Other values (32) 32
58.2%
(Missing) 6
 
10.9%
ValueCountFrequency (%)
184783.397041118 2
3.6%
184844.878863426 2
3.6%
184869.073160302 1
1.8%
184937.934422527 1
1.8%
185127.293665419 1
1.8%
185197.262475103 1
1.8%
185208.280665837 1
1.8%
185211.725366486 1
1.8%
185307.072104229 2
3.6%
185398.814014343 2
3.6%
ValueCountFrequency (%)
188994.188904759 1
1.8%
188954.524397407 1
1.8%
188898.570471747 1
1.8%
188896.339430664 1
1.8%
188753.288154681 1
1.8%
188745.013891943 1
1.8%
188669.485919056 1
1.8%
188113.202568586 1
1.8%
188086.35930417 1
1.8%
187928.484023216 1
1.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)85.7%
Missing6
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean447601.25
Minimum446121.25
Maximum449753.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:20.796368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446121.25
5-th percentile446391.4
Q1446742.22
median447430.43
Q3448292.51
95-th percentile449588.17
Maximum449753.16
Range3631.9119
Interquartile range (IQR)1550.2916

Descriptive statistics

Standard deviation1047.0635
Coefficient of variation (CV)0.0023392774
Kurtosis-0.66609927
Mean447601.25
Median Absolute Deviation (MAD)800.04225
Skewness0.62263988
Sum21932461
Variance1096342
MonotonicityNot monotonic
2024-05-11T14:49:21.032761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
447430.427686132 2
 
3.6%
446788.082284481 2
 
3.6%
448230.469938283 2
 
3.6%
448097.763211272 2
 
3.6%
448328.26558548 2
 
3.6%
446579.81892943 2
 
3.6%
447554.222430098 2
 
3.6%
447552.415105958 1
 
1.8%
448435.911091764 1
 
1.8%
446986.600322735 1
 
1.8%
Other values (32) 32
58.2%
(Missing) 6
 
10.9%
ValueCountFrequency (%)
446121.246509433 1
1.8%
446232.133867397 1
1.8%
446386.541360966 1
1.8%
446398.691184621 1
1.8%
446438.939151406 1
1.8%
446440.340498805 1
1.8%
446574.078381435 1
1.8%
446579.81892943 2
3.6%
446594.155713333 1
1.8%
446596.353632929 1
1.8%
ValueCountFrequency (%)
449753.158413664 1
1.8%
449714.789164209 1
1.8%
449714.65984941 1
1.8%
449398.438608253 1
1.8%
449388.09592117 1
1.8%
449387.338524372 1
1.8%
449310.579030311 1
1.8%
448587.55610848 1
1.8%
448435.911091764 1
1.8%
448328.26558548 2
3.6%

위생업태명
Categorical

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
여관업
37 
<NA>
10 
여인숙업
8 

Length

Max length4
Median length3
Mean length3.3272727
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 37
67.3%
<NA> 10
 
18.2%
여인숙업 8
 
14.5%

Length

2024-05-11T14:49:21.293082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:21.527145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 37
67.3%
na 10
 
18.2%
여인숙업 8
 
14.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)16.7%
Missing19
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean2.4722222
Minimum0
Maximum5
Zeros5
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:21.702983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3198725
Coefficient of variation (CV)0.53388102
Kurtosis-0.25204037
Mean2.4722222
Median Absolute Deviation (MAD)1
Skewness-0.64691015
Sum89
Variance1.7420635
MonotonicityNot monotonic
2024-05-11T14:49:21.911685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 17
30.9%
2 5
 
9.1%
4 5
 
9.1%
0 5
 
9.1%
1 3
 
5.5%
5 1
 
1.8%
(Missing) 19
34.5%
ValueCountFrequency (%)
0 5
 
9.1%
1 3
 
5.5%
2 5
 
9.1%
3 17
30.9%
4 5
 
9.1%
5 1
 
1.8%
ValueCountFrequency (%)
5 1
 
1.8%
4 5
 
9.1%
3 17
30.9%
2 5
 
9.1%
1 3
 
5.5%
0 5
 
9.1%

건물지하층수
Categorical

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
25 
0
23 
1
7 

Length

Max length4
Median length1
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
45.5%
0 23
41.8%
1 7
 
12.7%

Length

2024-05-11T14:49:22.150767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:22.355784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
45.5%
0 23
41.8%
1 7
 
12.7%

사용시작지상층
Categorical

Distinct5
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
19 
1
14 
2
14 
0
5 
3
3 

Length

Max length4
Median length1
Mean length2.0363636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
34.5%
1 14
25.5%
2 14
25.5%
0 5
 
9.1%
3 3
 
5.5%

Length

2024-05-11T14:49:22.536144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:22.709336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
34.5%
1 14
25.5%
2 14
25.5%
0 5
 
9.1%
3 3
 
5.5%

사용끝지상층
Categorical

Distinct6
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
24 
3
14 
2
10 
1
3 
4
3 

Length

Max length4
Median length1
Mean length2.3090909
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 24
43.6%
3 14
25.5%
2 10
18.2%
1 3
 
5.5%
4 3
 
5.5%
5 1
 
1.8%

Length

2024-05-11T14:49:22.927798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:23.134157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
43.6%
3 14
25.5%
2 10
18.2%
1 3
 
5.5%
4 3
 
5.5%
5 1
 
1.8%

사용시작지하층
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
30 
0
25 

Length

Max length4
Median length4
Mean length2.6363636
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> 30
54.5%
0 25
45.5%

Length

2024-05-11T14:49:23.364758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:23.535754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
54.5%
0 25
45.5%

사용끝지하층
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
35 
0
20 

Length

Max length4
Median length4
Mean length2.9090909
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> 35
63.6%
0 20
36.4%

Length

2024-05-11T14:49:23.733051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:23.926077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
63.6%
0 20
36.4%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)31.8%
Missing11
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean4.2045455
Minimum0
Maximum17
Zeros7
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:24.066317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35.25
95-th percentile11.85
Maximum17
Range17
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation4.2839861
Coefficient of variation (CV)1.018894
Kurtosis0.85532789
Mean4.2045455
Median Absolute Deviation (MAD)2
Skewness1.2470628
Sum185
Variance18.352537
MonotonicityNot monotonic
2024-05-11T14:49:24.264383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 8
14.5%
0 7
12.7%
3 6
10.9%
2 5
9.1%
5 4
 
7.3%
4 3
 
5.5%
11 3
 
5.5%
8 2
 
3.6%
9 1
 
1.8%
12 1
 
1.8%
Other values (4) 4
 
7.3%
(Missing) 11
20.0%
ValueCountFrequency (%)
0 7
12.7%
1 8
14.5%
2 5
9.1%
3 6
10.9%
4 3
 
5.5%
5 4
7.3%
6 1
 
1.8%
8 2
 
3.6%
9 1
 
1.8%
10 1
 
1.8%
ValueCountFrequency (%)
17 1
 
1.8%
14 1
 
1.8%
12 1
 
1.8%
11 3
5.5%
10 1
 
1.8%
9 1
 
1.8%
8 2
3.6%
6 1
 
1.8%
5 4
7.3%
4 3
5.5%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)45.2%
Missing13
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean12.309524
Minimum0
Maximum40
Zeros2
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:24.469264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17.25
median10.5
Q315.75
95-th percentile25
Maximum40
Range40
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation8.1912746
Coefficient of variation (CV)0.66544204
Kurtosis2.1909857
Mean12.309524
Median Absolute Deviation (MAD)4.5
Skewness1.2556421
Sum517
Variance67.09698
MonotonicityNot monotonic
2024-05-11T14:49:24.694776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8 6
10.9%
10 4
 
7.3%
16 4
 
7.3%
12 4
 
7.3%
7 3
 
5.5%
25 3
 
5.5%
15 3
 
5.5%
4 2
 
3.6%
0 2
 
3.6%
3 2
 
3.6%
Other values (9) 9
16.4%
(Missing) 13
23.6%
ValueCountFrequency (%)
0 2
 
3.6%
3 2
 
3.6%
4 2
 
3.6%
5 1
 
1.8%
6 1
 
1.8%
7 3
5.5%
8 6
10.9%
10 4
7.3%
11 1
 
1.8%
12 4
7.3%
ValueCountFrequency (%)
40 1
 
1.8%
30 1
 
1.8%
25 3
5.5%
24 1
 
1.8%
19 1
 
1.8%
16 4
7.3%
15 3
5.5%
14 1
 
1.8%
13 1
 
1.8%
12 4
7.3%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)62.5%
Missing15
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum0
Maximum33
Zeros8
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size627.0 B
2024-05-11T14:49:24.932449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median12
Q319
95-th percentile28.05
Maximum33
Range33
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.334249
Coefficient of variation (CV)0.74673992
Kurtosis-0.79685563
Mean12.5
Median Absolute Deviation (MAD)7.5
Skewness0.24074162
Sum500
Variance87.128205
MonotonicityNot monotonic
2024-05-11T14:49:25.122428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 8
14.5%
17 3
 
5.5%
4 2
 
3.6%
12 2
 
3.6%
11 2
 
3.6%
19 2
 
3.6%
10 2
 
3.6%
8 2
 
3.6%
9 1
 
1.8%
27 1
 
1.8%
Other values (15) 15
27.3%
(Missing) 15
27.3%
ValueCountFrequency (%)
0 8
14.5%
3 1
 
1.8%
4 2
 
3.6%
6 1
 
1.8%
8 2
 
3.6%
9 1
 
1.8%
10 2
 
3.6%
11 2
 
3.6%
12 2
 
3.6%
13 1
 
1.8%
ValueCountFrequency (%)
33 1
1.8%
29 1
1.8%
28 1
1.8%
27 1
1.8%
24 1
1.8%
23 1
1.8%
22 1
1.8%
21 1
1.8%
20 1
1.8%
19 2
3.6%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)4.4%
Missing10
Missing (%)18.2%
Memory size242.0 B
True
39 
False
6 
(Missing)
10 
ValueCountFrequency (%)
True 39
70.9%
False 6
 
10.9%
(Missing) 10
 
18.2%
2024-05-11T14:49:25.303416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct4
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
0
32 
<NA>
21 
11
 
1
28
 
1

Length

Max length4
Median length1
Mean length2.1818182
Min length1

Unique

Unique2 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 32
58.2%
<NA> 21
38.2%
11 1
 
1.8%
28 1
 
1.8%

Length

2024-05-11T14:49:25.859903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:26.035779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 32
58.2%
na 21
38.2%
11 1
 
1.8%
28 1
 
1.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)100.0%
Memory size627.0 B

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
50 
임대
 
3
자가
 
2

Length

Max length4
Median length4
Mean length3.8181818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
90.9%
임대 3
 
5.5%
자가 2
 
3.6%

Length

2024-05-11T14:49:26.232922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:26.402462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
90.9%
임대 3
 
5.5%
자가 2
 
3.6%

세탁기수
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
30 
0
25 

Length

Max length4
Median length4
Mean length2.6363636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
54.5%
0 25
45.5%

Length

2024-05-11T14:49:26.561524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:26.726211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
54.5%
0 25
45.5%

여성종사자수
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
47 
0
8 

Length

Max length4
Median length4
Mean length3.5636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 47
85.5%
0 8
 
14.5%

Length

2024-05-11T14:49:26.932764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:27.073733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
85.5%
0 8
 
14.5%

남성종사자수
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
47 
0
8 

Length

Max length4
Median length4
Mean length3.5636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 47
85.5%
0 8
 
14.5%

Length

2024-05-11T14:49:27.238621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:27.391208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
85.5%
0 8
 
14.5%

회수건조수
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
35 
0
20 

Length

Max length4
Median length4
Mean length2.9090909
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> 35
63.6%
0 20
36.4%

Length

2024-05-11T14:49:27.534251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:27.699941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
63.6%
0 20
36.4%

침대수
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
35 
0
20 

Length

Max length4
Median length4
Mean length2.9090909
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> 35
63.6%
0 20
36.4%

Length

2024-05-11T14:49:27.858174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:28.007569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
63.6%
0 20
36.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.2%
Missing10
Missing (%)18.2%
Memory size242.0 B
False
45 
(Missing)
10 
ValueCountFrequency (%)
False 45
81.8%
(Missing) 10
 
18.2%
2024-05-11T14:49:28.124791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031400003140000-201-1971-0004719710115<NA>3폐업2폐업20030207<NA><NA><NA>02 6036542195.70158849서울특별시 양천구 신정동 119-57번지<NA><NA>화신여인숙2003-11-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업<NA><NA><NA><NA><NA><NA>9<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131400003140000-201-1972-0004519721108<NA>3폐업2폐업20130617<NA><NA><NA>022652188754.20158862서울특별시 양천구 신정동 1033-12번지<NA><NA>신정여인숙2013-03-15 09:40:32I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업101100350N0<NA><NA><NA><NA>0<NA><NA>00N
231400003140000-201-1972-0004619720111<NA>3폐업2폐업19990816<NA><NA><NA>02 602234448.66158806서울특별시 양천구 목동 404-156번지<NA><NA>중앙여인숙1999-08-18 00:00:00I2018-08-31 23:59:59.0여인숙업188954.524397446824.338405여인숙업<NA><NA><NA><NA><NA><NA>120<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331400003140000-201-1973-0003719731126<NA>3폐업2폐업20080521<NA><NA><NA>0226420017131.18158811서울특별시 양천구 목동 607-18번지<NA><NA>등마루여관2008-01-03 16:13:07I2018-08-31 23:59:59.0여관업188086.359304449714.659849여관업3013<NA><NA>2100Y0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
431400003140000-201-1973-0003919730719<NA>3폐업2폐업20120302<NA><NA><NA>022652404744.30158862서울특별시 양천구 신정동 1035-22번지<NA><NA>궁전여인숙2008-01-03 17:04:35I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업1011<NA><NA>430Y0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
531400003140000-201-1974-0004419740122<NA>3폐업2폐업20130210<NA><NA><NA>022608801463.34158864서울특별시 양천구 신정동 1183-2번지서울특별시 양천구 중앙로43길 3 (신정동)8073신옥여인숙2005-01-17 00:00:00I2018-08-31 23:59:59.0여인숙업186877.63363446438.939151여인숙업2<NA>12<NA><NA>8<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631400003140000-201-1979-0004319791109<NA>3폐업2폐업20220510<NA><NA><NA>022645358682.67158809서울특별시 양천구 목동 527-5서울특별시 양천구 목동중앙북로14길 7, 2층 (목동)7972강촌여인숙2022-05-10 09:38:31U2021-12-04 23:02:00.0여인숙업188745.013892449310.57903<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731400003140000-201-1980-0003819800512<NA>3폐업2폐업19990816<NA><NA><NA>0206940541983.20158808서울특별시 양천구 목동 515-0번지<NA><NA>남촌여관1999-08-18 00:00:00I2018-08-31 23:59:59.0여관업188898.570472449388.095921여관업<NA><NA><NA><NA><NA><NA>1133Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831400003140000-201-1980-0004219801025<NA>3폐업2폐업20120110<NA><NA><NA>022642156857.55158862서울특별시 양천구 신정동 1035-14번지<NA><NA>서강여인숙2008-01-03 17:04:11I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업2012<NA><NA>640Y0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
931400003140000-201-1981-0000719811226<NA>3폐업2폐업20030228<NA><NA><NA>02060569081,731.25158857서울특별시 양천구 신정동 900-21번지<NA><NA>화성장2004-02-09 00:00:00I2018-08-31 23:59:59.0여관업187890.858025447260.880711여관업<NA><NA><NA><NA><NA><NA>141529Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
4531400003140000-201-1989-0003019890706<NA>1영업/정상1영업<NA><NA><NA><NA>0226546176296.44158806서울특별시 양천구 목동 404-115 1~4층서울특별시 양천구 신목로 94, 1~4층 (목동)8007도운모텔2022-01-14 11:04:00U2022-01-16 02:40:00.0여관업188896.339431446749.650078여관업40240021621Y0<NA><NA><NA><NA>00000N
4631400003140000-201-1989-0003519890721<NA>1영업/정상1영업<NA><NA><NA><NA>0226463577258.77158806서울특별시 양천구 목동 406-316서울특별시 양천구 신목로 119, 2~3층 (목동)7999잠모텔2022-12-12 17:07:35U2021-11-01 23:04:00.0여관업188994.188905446989.957415<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4731400003140000-201-2002-0000120020426<NA>3폐업2폐업20130502<NA><NA><NA>0226054616128.71158828서울특별시 양천구 신월동 145-14번지 1,2층서울특별시 양천구 남부순환로 361 (신월동,1,2층)7920제일여관2012-09-28 13:17:05I2018-08-31 23:59:59.0여관업184844.878863448097.763211여관업3122<NA><NA>380N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
4831400003140000-201-2002-0000220020729<NA>3폐업2폐업20071022<NA><NA><NA>0226070609428.96158864서울특별시 양천구 신정동 1183-3번지<NA><NA>뉴신정장2007-10-17 16:10:17I2018-08-31 23:59:59.0여관업186889.944225446440.340499여관업3<NA>23<NA><NA>316<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
4931400003140000-201-2002-000032002-08-12<NA>1영업/정상1영업<NA><NA><NA><NA>0220655200332.61158-827서울특별시 양천구 신월동 122-15 3층서울특별시 양천구 곰달래로 25, 3층 (신월동)7923왕실장2024-03-21 09:13:50U2023-12-02 22:03:00.0여관업185398.814014447554.22243<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5031400003140000-201-2002-0000420020903<NA>3폐업2폐업20150923<NA><NA><NA>0226081128181.33158833서울특별시 양천구 신월동 444-18번지서울특별시 양천구 월정로 37 (신월동)<NA>신월장2008-01-03 16:52:27I2018-08-31 23:59:59.0여관업185985.497027446788.082284여관업2012<NA><NA>1150N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
5131400003140000-201-2002-0000520020906<NA>1영업/정상1영업<NA><NA><NA><NA>02269533441,254.48158857서울특별시 양천구 신정동 898-11서울특별시 양천구 목동로 229, 1~5층 (신정동)7937모카모텔2022-01-14 11:06:06U2022-01-16 02:40:00.0여관업187871.363218447430.427686여관업5115001400N0<NA><NA><NA>자가00000N
5231400003140000-201-2002-0000620021017<NA>1영업/정상1영업<NA><NA><NA><NA>0226486565245.90158861서울특별시 양천구 신정동 1027-2서울특별시 양천구 신월로 326, 2~3층 (신정동)8082토마토2022-07-26 15:58:23U2021-12-06 22:08:00.0여관업187310.71277446579.818929<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5331400003140000-201-2003-0000120030210<NA>1영업/정상1영업<NA><NA><NA><NA>0226973500150.18158824서울특별시 양천구 신월동 50-4 2층서울특별시 양천구 가로공원로 113, 2층 (신월동)7905로즈모텔2022-01-14 11:07:44U2022-01-16 02:40:00.0여관업184783.397041448230.469938여관업3022001100N0<NA><NA><NA>자가00000N
5431400003140000-201-2013-0000120131014<NA>1영업/정상1영업<NA><NA><NA><NA>02269973562,257.68158825서울특별시 양천구 신월동 87-13 비관광호텔서울특별시 양천구 가로공원로 167, 캠프관광호텔 지하 1~10층 (신월동)7907캠프관광호텔2022-12-13 16:30:13U2021-11-01 23:05:00.0관광호텔185307.072104448328.265585<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>