Overview

Dataset statistics

Number of variables47
Number of observations296
Missing cells3194
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.9 KiB
Average record size in memory404.4 B

Variable types

Categorical17
Text7
DateTime4
Unsupported7
Numeric10
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-17430/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (60.9%)Imbalance
위생업태명 is highly imbalanced (54.7%)Imbalance
사용끝지하층 is highly imbalanced (54.3%)Imbalance
여성종사자수 is highly imbalanced (82.1%)Imbalance
남성종사자수 is highly imbalanced (82.1%)Imbalance
인허가취소일자 has 296 (100.0%) missing valuesMissing
폐업일자 has 63 (21.3%) missing valuesMissing
휴업시작일자 has 296 (100.0%) missing valuesMissing
휴업종료일자 has 296 (100.0%) missing valuesMissing
재개업일자 has 296 (100.0%) missing valuesMissing
전화번호 has 4 (1.4%) missing valuesMissing
도로명주소 has 183 (61.8%) missing valuesMissing
도로명우편번호 has 187 (63.2%) missing valuesMissing
좌표정보(X) has 44 (14.9%) missing valuesMissing
좌표정보(Y) has 44 (14.9%) missing valuesMissing
건물지상층수 has 51 (17.2%) missing valuesMissing
사용시작지상층 has 53 (17.9%) missing valuesMissing
사용끝지상층 has 176 (59.5%) missing valuesMissing
한실수 has 42 (14.2%) missing valuesMissing
양실수 has 47 (15.9%) missing valuesMissing
욕실수 has 89 (30.1%) missing valuesMissing
발한실여부 has 22 (7.4%) missing valuesMissing
좌석수 has 94 (31.8%) missing valuesMissing
조건부허가신고사유 has 296 (100.0%) missing valuesMissing
조건부허가시작일자 has 296 (100.0%) missing valuesMissing
조건부허가종료일자 has 296 (100.0%) missing valuesMissing
다중이용업소여부 has 22 (7.4%) 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 130 (43.9%) zerosZeros
사용시작지상층 has 131 (44.3%) zerosZeros
사용끝지상층 has 9 (3.0%) zerosZeros
한실수 has 86 (29.1%) zerosZeros
양실수 has 104 (35.1%) zerosZeros
욕실수 has 176 (59.5%) zerosZeros
좌석수 has 186 (62.8%) zerosZeros

Reproduction

Analysis started2024-04-06 11:26:02.063169
Analysis finished2024-04-06 11:26:03.311498
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3030000
296 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 296
100.0%

Length

2024-04-06T20:26:03.769882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:03.922760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 296
100.0%

관리번호
Text

UNIQUE 

Distinct296
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-06T20:26:04.191287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6512
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

Unique296 ?
Unique (%)100.0%

Sample

1st row3030000-201-1960-00140
2nd row3030000-201-1961-00100
3rd row3030000-201-1963-00127
4th row3030000-201-1964-00063
5th row3030000-201-1964-00126
ValueCountFrequency (%)
3030000-201-1960-00140 1
 
0.3%
3030000-201-1998-00153 1
 
0.3%
3030000-201-1997-00188 1
 
0.3%
3030000-201-1996-00183 1
 
0.3%
3030000-201-1996-00182 1
 
0.3%
3030000-201-1996-00154 1
 
0.3%
3030000-201-1994-00180 1
 
0.3%
3030000-201-1994-00179 1
 
0.3%
3030000-201-1994-00176 1
 
0.3%
3030000-201-1994-00111 1
 
0.3%
Other values (286) 286
96.6%
2024-04-06T20:26:04.747763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2825
43.4%
- 888
 
13.6%
1 729
 
11.2%
3 698
 
10.7%
2 558
 
8.6%
9 286
 
4.4%
6 151
 
2.3%
7 132
 
2.0%
8 123
 
1.9%
4 67
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5624
86.4%
Dash Punctuation 888
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2825
50.2%
1 729
 
13.0%
3 698
 
12.4%
2 558
 
9.9%
9 286
 
5.1%
6 151
 
2.7%
7 132
 
2.3%
8 123
 
2.2%
4 67
 
1.2%
5 55
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 888
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6512
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2825
43.4%
- 888
 
13.6%
1 729
 
11.2%
3 698
 
10.7%
2 558
 
8.6%
9 286
 
4.4%
6 151
 
2.3%
7 132
 
2.0%
8 123
 
1.9%
4 67
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2825
43.4%
- 888
 
13.6%
1 729
 
11.2%
3 698
 
10.7%
2 558
 
8.6%
9 286
 
4.4%
6 151
 
2.3%
7 132
 
2.0%
8 123
 
1.9%
4 67
 
1.0%
Distinct253
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1960-12-28 00:00:00
Maximum2020-11-11 00:00:00
2024-04-06T20:26:05.001153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:26:05.233483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3
233 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 233
78.7%
1 63
 
21.3%

Length

2024-04-06T20:26:05.451560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:05.613803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 233
78.7%
1 63
 
21.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
233 
영업/정상
63 

Length

Max length5
Median length2
Mean length2.6385135
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 233
78.7%
영업/정상 63
 
21.3%

Length

2024-04-06T20:26:05.789084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:05.954284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 233
78.7%
영업/정상 63
 
21.3%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2
233 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 233
78.7%
1 63
 
21.3%

Length

2024-04-06T20:26:06.115440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:06.264819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 233
78.7%
1 63
 
21.3%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
233 
영업
63 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 233
78.7%
영업 63
 
21.3%

Length

2024-04-06T20:26:06.457651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:06.641938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 233
78.7%
영업 63
 
21.3%

폐업일자
Date

MISSING 

Distinct181
Distinct (%)77.7%
Missing63
Missing (%)21.3%
Memory size2.4 KiB
Minimum1991-02-18 00:00:00
Maximum2023-10-11 00:00:00
2024-04-06T20:26:06.887323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:26:07.151959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB

전화번호
Text

MISSING 

Distinct259
Distinct (%)88.7%
Missing4
Missing (%)1.4%
Memory size2.4 KiB
2024-04-06T20:26:07.585437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9143836
Min length2

Characters and Unicode

Total characters2895
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

Unique233 ?
Unique (%)79.8%

Sample

1st row0222935393
2nd row02 2344275
3rd row0202925038
4th row0204634045
5th row0222986020
ValueCountFrequency (%)
02 91
 
23.9%
0222383735 3
 
0.8%
0222130360 3
 
0.8%
0222929137 3
 
0.8%
0200000000 3
 
0.8%
0 2
 
0.5%
0222128554 2
 
0.5%
0222472010 2
 
0.5%
0204634545 2
 
0.5%
4634610 2
 
0.5%
Other values (251) 267
70.3%
2024-04-06T20:26:08.188997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 734
25.4%
0 573
19.8%
4 284
 
9.8%
9 232
 
8.0%
6 222
 
7.7%
3 202
 
7.0%
5 160
 
5.5%
1 140
 
4.8%
7 137
 
4.7%
8 112
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2796
96.6%
Space Separator 99
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 734
26.3%
0 573
20.5%
4 284
 
10.2%
9 232
 
8.3%
6 222
 
7.9%
3 202
 
7.2%
5 160
 
5.7%
1 140
 
5.0%
7 137
 
4.9%
8 112
 
4.0%
Space Separator
ValueCountFrequency (%)
99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2895
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 734
25.4%
0 573
19.8%
4 284
 
9.8%
9 232
 
8.0%
6 222
 
7.7%
3 202
 
7.0%
5 160
 
5.5%
1 140
 
4.8%
7 137
 
4.7%
8 112
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2895
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 734
25.4%
0 573
19.8%
4 284
 
9.8%
9 232
 
8.0%
6 222
 
7.7%
3 202
 
7.0%
5 160
 
5.5%
1 140
 
4.8%
7 137
 
4.7%
8 112
 
3.9%
Distinct248
Distinct (%)84.1%
Missing1
Missing (%)0.3%
Memory size2.4 KiB
2024-04-06T20:26:08.866646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.7016949
Min length3

Characters and Unicode

Total characters1682
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

Unique215 ?
Unique (%)72.9%

Sample

1st row187.00
2nd row70.00
3rd row30.55
4th row196.00
5th row69.40
ValueCountFrequency (%)
162.31 5
 
1.7%
00 5
 
1.7%
250.00 4
 
1.4%
71.23 3
 
1.0%
133.36 3
 
1.0%
134.67 3
 
1.0%
478.68 3
 
1.0%
160.00 3
 
1.0%
388.74 3
 
1.0%
214.00 2
 
0.7%
Other values (238) 261
88.5%
2024-04-06T20:26:09.720985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 352
20.9%
. 295
17.5%
1 160
9.5%
2 123
 
7.3%
6 122
 
7.3%
3 114
 
6.8%
7 112
 
6.7%
5 100
 
5.9%
4 99
 
5.9%
8 99
 
5.9%
Other values (2) 106
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1375
81.7%
Other Punctuation 307
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 352
25.6%
1 160
11.6%
2 123
 
8.9%
6 122
 
8.9%
3 114
 
8.3%
7 112
 
8.1%
5 100
 
7.3%
4 99
 
7.2%
8 99
 
7.2%
9 94
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 295
96.1%
, 12
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 352
20.9%
. 295
17.5%
1 160
9.5%
2 123
 
7.3%
6 122
 
7.3%
3 114
 
6.8%
7 112
 
6.7%
5 100
 
5.9%
4 99
 
5.9%
8 99
 
5.9%
Other values (2) 106
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 352
20.9%
. 295
17.5%
1 160
9.5%
2 123
 
7.3%
6 122
 
7.3%
3 114
 
6.8%
7 112
 
6.7%
5 100
 
5.9%
4 99
 
5.9%
8 99
 
5.9%
Other values (2) 106
 
6.3%
Distinct71
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-06T20:26:10.217411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0574324
Min length6

Characters and Unicode

Total characters1793
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)9.1%

Sample

1st row133010
2nd row133805
3rd row133868
4th row133828
5th row133867
ValueCountFrequency (%)
133882 42
 
14.2%
133834 13
 
4.4%
133010 12
 
4.1%
133801 12
 
4.1%
133836 12
 
4.1%
133847 11
 
3.7%
133833 9
 
3.0%
133809 9
 
3.0%
133849 8
 
2.7%
133829 8
 
2.7%
Other values (61) 160
54.1%
2024-04-06T20:26:10.799405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 662
36.9%
1 348
19.4%
8 348
19.4%
2 111
 
6.2%
0 100
 
5.6%
4 61
 
3.4%
6 49
 
2.7%
9 39
 
2.2%
7 34
 
1.9%
5 24
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1776
99.1%
Dash Punctuation 17
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 662
37.3%
1 348
19.6%
8 348
19.6%
2 111
 
6.2%
0 100
 
5.6%
4 61
 
3.4%
6 49
 
2.8%
9 39
 
2.2%
7 34
 
1.9%
5 24
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 662
36.9%
1 348
19.4%
8 348
19.4%
2 111
 
6.2%
0 100
 
5.6%
4 61
 
3.4%
6 49
 
2.7%
9 39
 
2.2%
7 34
 
1.9%
5 24
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 662
36.9%
1 348
19.4%
8 348
19.4%
2 111
 
6.2%
0 100
 
5.6%
4 61
 
3.4%
6 49
 
2.7%
9 39
 
2.2%
7 34
 
1.9%
5 24
 
1.3%
Distinct245
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-06T20:26:11.401087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length22.986486
Min length16

Characters and Unicode

Total characters6804
Distinct characters57
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

Unique207 ?
Unique (%)69.9%

Sample

1st row서울특별시 성동구 상왕십리동 297-3번지
2nd row서울특별시 성동구 금호동3가 166-0번지
3rd row서울특별시 성동구 행당동 317-0번지
4th row서울특별시 성동구 성수동2가 532-53번지
5th row서울특별시 성동구 행당동 214번지
ValueCountFrequency (%)
서울특별시 296
24.8%
성동구 296
24.8%
성수동2가 60
 
5.0%
도선동 48
 
4.0%
성수동1가 27
 
2.3%
행당동 25
 
2.1%
용답동 24
 
2.0%
마장동 18
 
1.5%
송정동 15
 
1.3%
금호동3가 14
 
1.2%
Other values (259) 370
31.0%
2024-04-06T20:26:12.283029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1171
17.2%
592
 
8.7%
383
 
5.6%
297
 
4.4%
296
 
4.4%
296
 
4.4%
296
 
4.4%
296
 
4.4%
296
 
4.4%
- 272
 
4.0%
Other values (47) 2609
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3941
57.9%
Decimal Number 1416
 
20.8%
Space Separator 1171
 
17.2%
Dash Punctuation 272
 
4.0%
Other Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
592
15.0%
383
9.7%
297
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
249
 
6.3%
248
 
6.3%
Other values (33) 692
17.6%
Decimal Number
ValueCountFrequency (%)
2 268
18.9%
1 244
17.2%
0 163
11.5%
6 144
10.2%
3 122
8.6%
4 113
8.0%
8 104
 
7.3%
7 88
 
6.2%
9 87
 
6.1%
5 83
 
5.9%
Space Separator
ValueCountFrequency (%)
1171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 272
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3941
57.9%
Common 2863
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
592
15.0%
383
9.7%
297
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
249
 
6.3%
248
 
6.3%
Other values (33) 692
17.6%
Common
ValueCountFrequency (%)
1171
40.9%
- 272
 
9.5%
2 268
 
9.4%
1 244
 
8.5%
0 163
 
5.7%
6 144
 
5.0%
3 122
 
4.3%
4 113
 
3.9%
8 104
 
3.6%
7 88
 
3.1%
Other values (4) 174
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3941
57.9%
ASCII 2863
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1171
40.9%
- 272
 
9.5%
2 268
 
9.4%
1 244
 
8.5%
0 163
 
5.7%
6 144
 
5.0%
3 122
 
4.3%
4 113
 
3.9%
8 104
 
3.6%
7 88
 
3.1%
Other values (4) 174
 
6.1%
Hangul
ValueCountFrequency (%)
592
15.0%
383
9.7%
297
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
296
7.5%
249
 
6.3%
248
 
6.3%
Other values (33) 692
17.6%

도로명주소
Text

MISSING 

Distinct113
Distinct (%)100.0%
Missing183
Missing (%)61.8%
Memory size2.4 KiB
2024-04-06T20:26:12.750685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length27.230088
Min length22

Characters and Unicode

Total characters3077
Distinct characters91
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

Unique113 ?
Unique (%)100.0%

Sample

1st row서울특별시 성동구 금호산2길 39 (금호동3가)
2nd row서울특별시 성동구 성수이로5길 10 (성수동2가)
3rd row서울특별시 성동구 둘레7가길 11 (성수동1가)
4th row서울특별시 성동구 독서당로47길 10 (금호동4가)
5th row서울특별시 성동구 왕십리로 379-6 (하왕십리동)
ValueCountFrequency (%)
서울특별시 113
19.4%
성동구 113
19.4%
도선동 31
 
5.3%
성수동2가 24
 
4.1%
왕십리로22길 14
 
2.4%
왕십리로20길 10
 
1.7%
용답동 9
 
1.5%
금호동3가 9
 
1.5%
성수동1가 9
 
1.5%
송정동 6
 
1.0%
Other values (168) 244
41.9%
2024-04-06T20:26:13.445369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469
 
15.2%
235
 
7.6%
158
 
5.1%
2 127
 
4.1%
1 125
 
4.1%
122
 
4.0%
118
 
3.8%
115
 
3.7%
( 113
 
3.7%
113
 
3.7%
Other values (81) 1382
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1819
59.1%
Decimal Number 496
 
16.1%
Space Separator 469
 
15.2%
Open Punctuation 113
 
3.7%
Close Punctuation 113
 
3.7%
Dash Punctuation 42
 
1.4%
Other Punctuation 20
 
0.6%
Math Symbol 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
235
12.9%
158
 
8.7%
122
 
6.7%
118
 
6.5%
115
 
6.3%
113
 
6.2%
113
 
6.2%
113
 
6.2%
86
 
4.7%
75
 
4.1%
Other values (65) 571
31.4%
Decimal Number
ValueCountFrequency (%)
2 127
25.6%
1 125
25.2%
3 46
 
9.3%
7 35
 
7.1%
0 34
 
6.9%
4 30
 
6.0%
9 30
 
6.0%
8 26
 
5.2%
6 25
 
5.0%
5 18
 
3.6%
Space Separator
ValueCountFrequency (%)
469
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1819
59.1%
Common 1258
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
235
12.9%
158
 
8.7%
122
 
6.7%
118
 
6.5%
115
 
6.3%
113
 
6.2%
113
 
6.2%
113
 
6.2%
86
 
4.7%
75
 
4.1%
Other values (65) 571
31.4%
Common
ValueCountFrequency (%)
469
37.3%
2 127
 
10.1%
1 125
 
9.9%
( 113
 
9.0%
) 113
 
9.0%
3 46
 
3.7%
- 42
 
3.3%
7 35
 
2.8%
0 34
 
2.7%
4 30
 
2.4%
Other values (6) 124
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1819
59.1%
ASCII 1258
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
469
37.3%
2 127
 
10.1%
1 125
 
9.9%
( 113
 
9.0%
) 113
 
9.0%
3 46
 
3.7%
- 42
 
3.3%
7 35
 
2.8%
0 34
 
2.7%
4 30
 
2.4%
Other values (6) 124
 
9.9%
Hangul
ValueCountFrequency (%)
235
12.9%
158
 
8.7%
122
 
6.7%
118
 
6.5%
115
 
6.3%
113
 
6.2%
113
 
6.2%
113
 
6.2%
86
 
4.7%
75
 
4.1%
Other values (65) 571
31.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)35.8%
Missing187
Missing (%)63.2%
Infinite0
Infinite (%)0.0%
Mean4746.2385
Minimum4704
Maximum4808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:13.712013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4704
5-th percentile4707
Q14709
median4730
Q34778
95-th percentile4803.6
Maximum4808
Range104
Interquartile range (IQR)69

Descriptive statistics

Standard deviation38.0606
Coefficient of variation (CV)0.008019108
Kurtosis-1.6082721
Mean4746.2385
Median Absolute Deviation (MAD)23
Skewness0.32838087
Sum517340
Variance1448.6092
MonotonicityNot monotonic
2024-04-06T20:26:13.944380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4709 29
 
9.8%
4775 7
 
2.4%
4801 6
 
2.0%
4808 5
 
1.7%
4730 5
 
1.7%
4776 5
 
1.7%
4795 4
 
1.4%
4708 3
 
1.0%
4707 3
 
1.0%
4725 3
 
1.0%
Other values (29) 39
 
13.2%
(Missing) 187
63.2%
ValueCountFrequency (%)
4704 2
 
0.7%
4705 2
 
0.7%
4707 3
 
1.0%
4708 3
 
1.0%
4709 29
9.8%
4710 2
 
0.7%
4714 1
 
0.3%
4715 1
 
0.3%
4718 2
 
0.7%
4724 2
 
0.7%
ValueCountFrequency (%)
4808 5
1.7%
4804 1
 
0.3%
4803 2
 
0.7%
4801 6
2.0%
4796 1
 
0.3%
4795 4
1.4%
4794 1
 
0.3%
4792 2
 
0.7%
4790 1
 
0.3%
4786 1
 
0.3%
Distinct236
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-06T20:26:14.515987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length4.277027
Min length1

Characters and Unicode

Total characters1266
Distinct characters206
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

Unique192 ?
Unique (%)64.9%

Sample

1st row낙원
2nd row복래여관
3rd row일오
4th row금봉
5th row행당
ValueCountFrequency (%)
성일여관 6
 
1.9%
대흥장여관 5
 
1.6%
서중여관 4
 
1.3%
호텔 4
 
1.3%
모텔 4
 
1.3%
호수장여관 3
 
0.9%
유성장여관 3
 
0.9%
신흥 3
 
0.9%
대도여관 3
 
0.9%
성수여관 3
 
0.9%
Other values (237) 280
88.1%
2024-04-06T20:26:15.308755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
 
11.6%
134
 
10.6%
77
 
6.1%
49
 
3.9%
45
 
3.6%
31
 
2.4%
30
 
2.4%
26
 
2.1%
26
 
2.1%
22
 
1.7%
Other values (196) 679
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1177
93.0%
Uppercase Letter 43
 
3.4%
Space Separator 22
 
1.7%
Lowercase Letter 9
 
0.7%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
147
 
12.5%
134
 
11.4%
77
 
6.5%
49
 
4.2%
45
 
3.8%
31
 
2.6%
30
 
2.5%
26
 
2.2%
26
 
2.2%
22
 
1.9%
Other values (166) 590
50.1%
Uppercase Letter
ValueCountFrequency (%)
O 6
14.0%
U 5
11.6%
N 4
9.3%
L 4
9.3%
T 4
9.3%
H 3
 
7.0%
A 3
 
7.0%
R 2
 
4.7%
E 2
 
4.7%
S 2
 
4.7%
Other values (7) 8
18.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
22.2%
n 1
11.1%
o 1
11.1%
g 1
11.1%
r 1
11.1%
t 1
11.1%
s 1
11.1%
y 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
7 1
33.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1177
93.0%
Latin 52
 
4.1%
Common 37
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
147
 
12.5%
134
 
11.4%
77
 
6.5%
49
 
4.2%
45
 
3.8%
31
 
2.6%
30
 
2.5%
26
 
2.2%
26
 
2.2%
22
 
1.9%
Other values (166) 590
50.1%
Latin
ValueCountFrequency (%)
O 6
 
11.5%
U 5
 
9.6%
N 4
 
7.7%
L 4
 
7.7%
T 4
 
7.7%
H 3
 
5.8%
A 3
 
5.8%
R 2
 
3.8%
E 2
 
3.8%
a 2
 
3.8%
Other values (15) 17
32.7%
Common
ValueCountFrequency (%)
22
59.5%
) 6
 
16.2%
( 6
 
16.2%
2 2
 
5.4%
7 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1177
93.0%
ASCII 89
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
147
 
12.5%
134
 
11.4%
77
 
6.5%
49
 
4.2%
45
 
3.8%
31
 
2.6%
30
 
2.5%
26
 
2.2%
26
 
2.2%
22
 
1.9%
Other values (166) 590
50.1%
ASCII
ValueCountFrequency (%)
22
24.7%
) 6
 
6.7%
O 6
 
6.7%
( 6
 
6.7%
U 5
 
5.6%
N 4
 
4.5%
L 4
 
4.5%
T 4
 
4.5%
H 3
 
3.4%
A 3
 
3.4%
Other values (20) 26
29.2%
Distinct195
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1999-07-03 00:00:00
Maximum2024-04-04 13:33:27
2024-04-06T20:26:15.533139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:26:15.763211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
I
214 
U
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 214
72.3%
U 82
 
27.7%

Length

2024-04-06T20:26:15.992288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:16.142275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 214
72.3%
u 82
 
27.7%
Distinct64
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T20:26:16.315249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:26:16.523184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
여관업
244 
휴양콘도미니엄업
 
23
여인숙업
 
15
관광호텔
 
7
일반호텔
 
5

Length

Max length8
Median length3
Mean length3.5
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 244
82.4%
휴양콘도미니엄업 23
 
7.8%
여인숙업 15
 
5.1%
관광호텔 7
 
2.4%
일반호텔 5
 
1.7%
숙박업 기타 2
 
0.7%

Length

2024-04-06T20:26:16.772246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:16.986174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 244
81.9%
휴양콘도미니엄업 23
 
7.7%
여인숙업 15
 
5.0%
관광호텔 7
 
2.3%
일반호텔 5
 
1.7%
숙박업 2
 
0.7%
기타 2
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct175
Distinct (%)69.4%
Missing44
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean203699.63
Minimum201324.94
Maximum206137.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:17.246032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201324.94
5-th percentile201763.59
Q1203004.72
median203221.05
Q3204775.56
95-th percentile205513.82
Maximum206137.99
Range4813.0478
Interquartile range (IQR)1770.8353

Descriptive statistics

Standard deviation1214.9988
Coefficient of variation (CV)0.0059646587
Kurtosis-1.0809244
Mean203699.63
Median Absolute Deviation (MAD)1070.1691
Skewness0.031541238
Sum51332307
Variance1476222
MonotonicityNot monotonic
2024-04-06T20:26:17.514128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203012.210016159 5
 
1.7%
201540.816056093 4
 
1.4%
205272.642435581 4
 
1.4%
205220.003183223 4
 
1.4%
203072.199779294 4
 
1.4%
203022.766796271 3
 
1.0%
205306.029406852 3
 
1.0%
203890.561480364 3
 
1.0%
205392.012101901 3
 
1.0%
205439.135324883 3
 
1.0%
Other values (165) 216
73.0%
(Missing) 44
 
14.9%
ValueCountFrequency (%)
201324.939748336 1
 
0.3%
201362.539270161 1
 
0.3%
201466.79455042 1
 
0.3%
201540.816056093 4
1.4%
201624.790471502 1
 
0.3%
201680.377815983 2
0.7%
201694.635966791 1
 
0.3%
201756.747102689 1
 
0.3%
201763.590804487 2
0.7%
201772.760328013 2
0.7%
ValueCountFrequency (%)
206137.987508843 1
 
0.3%
206132.824684921 1
 
0.3%
206016.020665011 1
 
0.3%
206013.245913655 1
 
0.3%
205815.829656243 3
1.0%
205789.178044843 1
 
0.3%
205691.85538777 1
 
0.3%
205577.807757117 3
1.0%
205543.417245819 1
 
0.3%
205489.613027786 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct175
Distinct (%)69.4%
Missing44
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean450231.99
Minimum448048.1
Maximum452105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:17.747650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448048.1
5-th percentile448360.09
Q1449500.24
median450164.54
Q3451252.34
95-th percentile451678.9
Maximum452105
Range4056.9027
Interquartile range (IQR)1752.1052

Descriptive statistics

Standard deviation1124.9715
Coefficient of variation (CV)0.0024986485
Kurtosis-1.2335766
Mean450231.99
Median Absolute Deviation (MAD)1030.3369
Skewness-0.21384763
Sum1.1345846 × 108
Variance1265560.8
MonotonicityNot monotonic
2024-04-06T20:26:18.335537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451593.020659103 5
 
1.7%
449583.320151741 4
 
1.4%
451018.390117182 4
 
1.4%
451027.81302408 4
 
1.4%
452078.178251908 4
 
1.4%
451196.323937953 3
 
1.0%
451019.471122131 3
 
1.0%
449451.649253664 3
 
1.0%
448574.610941774 3
 
1.0%
449503.255963531 3
 
1.0%
Other values (165) 216
73.0%
(Missing) 44
 
14.9%
ValueCountFrequency (%)
448048.100431282 1
 
0.3%
448091.193949861 1
 
0.3%
448110.015207528 3
1.0%
448218.537284997 2
0.7%
448257.827060612 1
 
0.3%
448262.798166062 1
 
0.3%
448316.19064182 1
 
0.3%
448322.110363804 1
 
0.3%
448348.966392057 1
 
0.3%
448359.828772105 1
 
0.3%
ValueCountFrequency (%)
452105.00310132 1
 
0.3%
452078.178251908 4
1.4%
451926.803771454 2
0.7%
451896.110743119 1
 
0.3%
451810.376973679 2
0.7%
451760.013894149 1
 
0.3%
451690.355652243 1
 
0.3%
451678.899658 2
0.7%
451630.740026295 2
0.7%
451625.282444 1
 
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
여관업
227 
휴양콘도미니엄업
23 
<NA>
 
22
여인숙업
 
15
관광호텔
 
5
Other values (2)
 
4

Length

Max length8
Median length3
Mean length3.5506757
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 227
76.7%
휴양콘도미니엄업 23
 
7.8%
<NA> 22
 
7.4%
여인숙업 15
 
5.1%
관광호텔 5
 
1.7%
일반호텔 3
 
1.0%
숙박업 기타 1
 
0.3%

Length

2024-04-06T20:26:18.836451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:19.170895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 227
76.4%
휴양콘도미니엄업 23
 
7.7%
na 22
 
7.4%
여인숙업 15
 
5.1%
관광호텔 5
 
1.7%
일반호텔 3
 
1.0%
숙박업 1
 
0.3%
기타 1
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)4.5%
Missing51
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean1.5836735
Minimum0
Maximum10
Zeros130
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:19.570940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0660554
Coefficient of variation (CV)1.3045968
Kurtosis2.0709979
Mean1.5836735
Median Absolute Deviation (MAD)0
Skewness1.4049253
Sum388
Variance4.2685848
MonotonicityNot monotonic
2024-04-06T20:26:20.061484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 130
43.9%
2 37
 
12.5%
3 36
 
12.2%
4 18
 
6.1%
6 9
 
3.0%
5 5
 
1.7%
1 4
 
1.4%
7 2
 
0.7%
10 2
 
0.7%
9 1
 
0.3%
(Missing) 51
 
17.2%
ValueCountFrequency (%)
0 130
43.9%
1 4
 
1.4%
2 37
 
12.5%
3 36
 
12.2%
4 18
 
6.1%
5 5
 
1.7%
6 9
 
3.0%
7 2
 
0.7%
8 1
 
0.3%
9 1
 
0.3%
ValueCountFrequency (%)
10 2
 
0.7%
9 1
 
0.3%
8 1
 
0.3%
7 2
 
0.7%
6 9
 
3.0%
5 5
 
1.7%
4 18
6.1%
3 36
12.2%
2 37
12.5%
1 4
 
1.4%
Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
143 
1
83 
<NA>
66 
2
 
4

Length

Max length4
Median length1
Mean length1.6689189
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 143
48.3%
1 83
28.0%
<NA> 66
22.3%
2 4
 
1.4%

Length

2024-04-06T20:26:20.553830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:20.790132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 143
48.3%
1 83
28.0%
na 66
22.3%
2 4
 
1.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.9%
Missing53
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean0.73662551
Minimum0
Maximum10
Zeros131
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:20.937027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0968475
Coefficient of variation (CV)1.4890165
Kurtosis21.94825
Mean0.73662551
Median Absolute Deviation (MAD)0
Skewness3.3799735
Sum179
Variance1.2030745
MonotonicityNot monotonic
2024-04-06T20:26:21.145980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 131
44.3%
1 65
22.0%
2 38
 
12.8%
3 6
 
2.0%
4 1
 
0.3%
10 1
 
0.3%
6 1
 
0.3%
(Missing) 53
17.9%
ValueCountFrequency (%)
0 131
44.3%
1 65
22.0%
2 38
 
12.8%
3 6
 
2.0%
4 1
 
0.3%
6 1
 
0.3%
10 1
 
0.3%
ValueCountFrequency (%)
10 1
 
0.3%
6 1
 
0.3%
4 1
 
0.3%
3 6
 
2.0%
2 38
 
12.8%
1 65
22.0%
0 131
44.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)9.2%
Missing176
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean2.9166667
Minimum0
Maximum10
Zeros9
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:21.353693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33.25
95-th percentile6.05
Maximum10
Range10
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation1.9514413
Coefficient of variation (CV)0.6690656
Kurtosis2.590372
Mean2.9166667
Median Absolute Deviation (MAD)1
Skewness1.3953265
Sum350
Variance3.8081232
MonotonicityNot monotonic
2024-04-06T20:26:21.527179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 50
 
16.9%
3 25
 
8.4%
4 11
 
3.7%
0 9
 
3.0%
6 9
 
3.0%
1 6
 
2.0%
5 4
 
1.4%
7 2
 
0.7%
10 2
 
0.7%
9 1
 
0.3%
(Missing) 176
59.5%
ValueCountFrequency (%)
0 9
 
3.0%
1 6
 
2.0%
2 50
16.9%
3 25
8.4%
4 11
 
3.7%
5 4
 
1.4%
6 9
 
3.0%
7 2
 
0.7%
8 1
 
0.3%
9 1
 
0.3%
ValueCountFrequency (%)
10 2
 
0.7%
9 1
 
0.3%
8 1
 
0.3%
7 2
 
0.7%
6 9
 
3.0%
5 4
 
1.4%
4 11
 
3.7%
3 25
8.4%
2 50
16.9%
1 6
 
2.0%
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
199 
<NA>
93 
1
 
4

Length

Max length4
Median length1
Mean length1.9425676
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 199
67.2%
<NA> 93
31.4%
1 4
 
1.4%

Length

2024-04-06T20:26:21.731422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:21.894303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 199
67.2%
na 93
31.4%
1 4
 
1.4%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
216 
0
77 
1
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.1891892
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
73.0%
0 77
 
26.0%
1 2
 
0.7%
2 1
 
0.3%

Length

2024-04-06T20:26:22.095062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:22.370611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
73.0%
0 77
 
26.0%
1 2
 
0.7%
2 1
 
0.3%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)9.8%
Missing42
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean6.2874016
Minimum0
Maximum37
Zeros86
Zeros (%)29.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:22.684594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q311
95-th percentile19
Maximum37
Range37
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.7390725
Coefficient of variation (CV)1.0718374
Kurtosis1.300304
Mean6.2874016
Median Absolute Deviation (MAD)4
Skewness1.0896854
Sum1597
Variance45.415098
MonotonicityNot monotonic
2024-04-06T20:26:22.987664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 86
29.1%
4 14
 
4.7%
7 13
 
4.4%
10 12
 
4.1%
15 12
 
4.1%
6 12
 
4.1%
1 12
 
4.1%
3 11
 
3.7%
12 11
 
3.7%
9 9
 
3.0%
Other values (15) 62
20.9%
(Missing) 42
14.2%
ValueCountFrequency (%)
0 86
29.1%
1 12
 
4.1%
2 7
 
2.4%
3 11
 
3.7%
4 14
 
4.7%
5 4
 
1.4%
6 12
 
4.1%
7 13
 
4.4%
8 7
 
2.4%
9 9
 
3.0%
ValueCountFrequency (%)
37 1
 
0.3%
32 1
 
0.3%
22 2
 
0.7%
21 3
 
1.0%
20 5
1.7%
19 2
 
0.7%
18 2
 
0.7%
17 3
 
1.0%
16 6
2.0%
15 12
4.1%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)18.1%
Missing47
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean10.148594
Minimum0
Maximum64
Zeros104
Zeros (%)35.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:23.329981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q317
95-th percentile35.6
Maximum64
Range64
Interquartile range (IQR)17

Descriptive statistics

Standard deviation12.53857
Coefficient of variation (CV)1.2354982
Kurtosis2.4861373
Mean10.148594
Median Absolute Deviation (MAD)6
Skewness1.525212
Sum2527
Variance157.21573
MonotonicityNot monotonic
2024-04-06T20:26:23.650730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 104
35.1%
11 10
 
3.4%
9 9
 
3.0%
16 7
 
2.4%
22 7
 
2.4%
5 7
 
2.4%
6 7
 
2.4%
25 6
 
2.0%
10 6
 
2.0%
7 6
 
2.0%
Other values (35) 80
27.0%
(Missing) 47
15.9%
ValueCountFrequency (%)
0 104
35.1%
1 2
 
0.7%
2 1
 
0.3%
3 1
 
0.3%
4 4
 
1.4%
5 7
 
2.4%
6 7
 
2.4%
7 6
 
2.0%
8 5
 
1.7%
9 9
 
3.0%
ValueCountFrequency (%)
64 1
0.3%
56 1
0.3%
54 1
0.3%
53 1
0.3%
49 1
0.3%
45 2
0.7%
42 1
0.3%
40 1
0.3%
39 2
0.7%
38 1
0.3%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)9.2%
Missing89
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean2.9323671
Minimum0
Maximum50
Zeros176
Zeros (%)59.5%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:23.888316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24.7
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.2893818
Coefficient of variation (CV)2.8268567
Kurtosis11.112873
Mean2.9323671
Median Absolute Deviation (MAD)0
Skewness3.2399874
Sum607
Variance68.71385
MonotonicityNot monotonic
2024-04-06T20:26:24.126971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 176
59.5%
12 4
 
1.4%
25 4
 
1.4%
11 3
 
1.0%
20 3
 
1.0%
26 2
 
0.7%
18 2
 
0.7%
1 2
 
0.7%
32 1
 
0.3%
16 1
 
0.3%
Other values (9) 9
 
3.0%
(Missing) 89
30.1%
ValueCountFrequency (%)
0 176
59.5%
1 2
 
0.7%
3 1
 
0.3%
10 1
 
0.3%
11 3
 
1.0%
12 4
 
1.4%
13 1
 
0.3%
15 1
 
0.3%
16 1
 
0.3%
18 2
 
0.7%
ValueCountFrequency (%)
50 1
 
0.3%
45 1
 
0.3%
41 1
 
0.3%
32 1
 
0.3%
27 1
 
0.3%
26 2
0.7%
25 4
1.4%
24 1
 
0.3%
20 3
1.0%
18 2
0.7%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.7%
Missing22
Missing (%)7.4%
Memory size724.0 B
True
215 
False
59 
(Missing)
22 
ValueCountFrequency (%)
True 215
72.6%
False 59
 
19.9%
(Missing) 22
 
7.4%
2024-04-06T20:26:24.383556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.9%
Missing94
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean1.5
Minimum0
Maximum41
Zeros186
Zeros (%)62.8%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-06T20:26:24.579532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.9
Maximum41
Range41
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.7209139
Coefficient of variation (CV)3.8139426
Kurtosis18.367665
Mean1.5
Median Absolute Deviation (MAD)0
Skewness4.1860419
Sum303
Variance32.728856
MonotonicityNot monotonic
2024-04-06T20:26:24.784906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 186
62.8%
25 4
 
1.4%
4 2
 
0.7%
20 2
 
0.7%
12 1
 
0.3%
11 1
 
0.3%
13 1
 
0.3%
15 1
 
0.3%
16 1
 
0.3%
41 1
 
0.3%
Other values (2) 2
 
0.7%
(Missing) 94
31.8%
ValueCountFrequency (%)
0 186
62.8%
4 2
 
0.7%
11 1
 
0.3%
12 1
 
0.3%
13 1
 
0.3%
15 1
 
0.3%
16 1
 
0.3%
20 2
 
0.7%
23 1
 
0.3%
24 1
 
0.3%
ValueCountFrequency (%)
41 1
 
0.3%
25 4
1.4%
24 1
 
0.3%
23 1
 
0.3%
20 2
0.7%
16 1
 
0.3%
15 1
 
0.3%
13 1
 
0.3%
12 1
 
0.3%
11 1
 
0.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing296
Missing (%)100.0%
Memory size2.7 KiB
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
186 
자가
61 
임대
49 

Length

Max length4
Median length4
Mean length3.2567568
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 186
62.8%
자가 61
 
20.6%
임대 49
 
16.6%

Length

2024-04-06T20:26:24.995323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:25.180657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 186
62.8%
자가 61
 
20.6%
임대 49
 
16.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
217 
0
79 

Length

Max length4
Median length4
Mean length3.1993243
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> 217
73.3%
0 79
 
26.7%

Length

2024-04-06T20:26:25.347955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:25.498592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
73.3%
0 79
 
26.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
288 
0
 
8

Length

Max length4
Median length4
Mean length3.9189189
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> 288
97.3%
0 8
 
2.7%

Length

2024-04-06T20:26:25.679996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:25.865491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 288
97.3%
0 8
 
2.7%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
288 
0
 
8

Length

Max length4
Median length4
Mean length3.9189189
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> 288
97.3%
0 8
 
2.7%

Length

2024-04-06T20:26:26.060374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:26.235316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 288
97.3%
0 8
 
2.7%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
217 
0
79 

Length

Max length4
Median length4
Mean length3.1993243
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> 217
73.3%
0 79
 
26.7%

Length

2024-04-06T20:26:26.406598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:26.581108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
73.3%
0 79
 
26.7%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
217 
0
79 

Length

Max length4
Median length4
Mean length3.1993243
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> 217
73.3%
0 79
 
26.7%

Length

2024-04-06T20:26:26.736075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:26:26.909333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
73.3%
0 79
 
26.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing22
Missing (%)7.4%
Memory size724.0 B
False
274 
(Missing)
 
22
ValueCountFrequency (%)
False 274
92.6%
(Missing) 22
 
7.4%
2024-04-06T20:26:27.032786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030300003030000-201-1960-0014019601228<NA>3폐업2폐업20100419<NA><NA><NA>0222935393187.00133010서울특별시 성동구 상왕십리동 297-3번지<NA><NA>낙원2003-11-27 00:00:00I2018-08-31 23:59:59.0여관업202043.730329451570.239083여관업2112<NA><NA>71<NA>Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
130300003030000-201-1961-0010019610630<NA>1영업/정상1영업<NA><NA><NA><NA>02 234427570.00133805서울특별시 성동구 금호동3가 166-0번지서울특별시 성동구 금호산2길 39 (금호동3가)4729복래여관2020-03-16 10:22:01U2020-03-18 02:40:00.0여관업202046.447067449598.848511여관업2012001001N0<NA><NA><NA>임대0<NA><NA>00N
230300003030000-201-1963-0012719630211<NA>3폐업2폐업20020305<NA><NA><NA>020292503830.55133868서울특별시 성동구 행당동 317-0번지<NA><NA>일오2002-03-05 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>600Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330300003030000-201-1964-0006319640709<NA>3폐업2폐업20160812<NA><NA><NA>0204634045196.00133828서울특별시 성동구 성수동2가 532-53번지서울특별시 성동구 성수이로5길 10 (성수동2가)4775금봉2011-05-02 11:28:06I2018-08-31 23:59:59.0여관업204652.945639448316.190642여관업2112<NA><NA>27<NA>Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
430300003030000-201-1964-0012619640910<NA>3폐업2폐업20100303<NA><NA><NA>022298602069.40133867서울특별시 성동구 행당동 214번지<NA><NA>행당2007-04-27 00:00:00I2018-08-31 23:59:59.0여관업203148.44726450897.512653여관업1<NA>11<NA><NA>6<NA><NA>Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
530300003030000-201-1965-0002919650917<NA>3폐업2폐업20060621<NA><NA><NA>02 461724388.00133829서울특별시 성동구 성수동2가 579-0번지<NA><NA>호수장여관2004-06-16 00:00:00I2018-08-31 23:59:59.0여관업204854.154202448262.798166여관업2<NA>12<NA><NA><NA>11<NA>Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
630300003030000-201-1965-0006119651210<NA>3폐업2폐업19970714<NA><NA><NA>02 463426425.08133828서울특별시 성동구 성수동2가 532-62번지<NA><NA>청주여관2001-09-25 00:00:00I2018-08-31 23:59:59.0여관업204631.241238448366.600534여관업000<NA>0<NA>000Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730300003030000-201-1965-0010319651026<NA>3폐업2폐업19990823<NA><NA><NA>0222914554128.12133805서울특별시 성동구 금호동3가 420-0번지<NA><NA>옥천여관2001-09-25 00:00:00I2018-08-31 23:59:59.0여관업201833.804518449573.097223여관업000<NA>0<NA>1100Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830300003030000-201-1965-0012819651104<NA>3폐업2폐업20020305<NA><NA><NA>020293966563.15133868서울특별시 성동구 행당동 317-74번지<NA><NA>동아2002-03-05 00:00:00I2018-08-31 23:59:59.0여관업202729.635865450664.244163여관업000<NA>0<NA>900Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930300003030000-201-1966-0004919660114<NA>1영업/정상1영업<NA><NA><NA><NA>0204647264164.00133820서울특별시 성동구 성수동1가 371-1번지서울특별시 성동구 둘레7가길 11 (성수동1가)4775명성2020-03-16 10:23:32U2020-03-18 02:40:00.0여관업204296.478868448322.110364여관업000000900Y0<NA><NA><NA><NA>0<NA><NA>00N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
28630300003030000-201-2003-0001620030225<NA>3폐업2폐업20201123<NA><NA><NA>02 4987850209.00133826서울특별시 성동구 성수동2가 269-77서울특별시 성동구 연무장18길 14 (성수동2가)4786로망스모텔2020-11-23 12:09:44U2020-11-25 02:40:00.0여관업205392.012102448574.610942여관업0000002100N0<NA><NA><NA><NA>0<NA><NA>00N
28730300003030000-201-2003-0001820031222<NA>3폐업2폐업20170630<NA><NA><NA>000222946643<NA>133801서울특별시 성동구 금호동1가 1803번지 1804-1서울특별시 성동구 금호로 58 (금호동1가,1804-1)4718유정여관2017-06-30 11:11:32I2018-08-31 23:59:59.0여인숙업202233.303208449584.037574여인숙업42<NA><NA>127<NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
28830300003030000-201-2004-0000120040517<NA>1영업/정상1영업<NA><NA><NA><NA>0002229926681,136.00133040서울특별시 성동구 도선동 29-1번지 ,30호2필지서울특별시 성동구 왕십리로20길 10 (도선동,,30호2필지)4709에이치호텔2018-06-01 15:28:49I2018-08-31 23:59:59.0여관업203039.972826451146.997606여관업8118110380N0<NA><NA><NA>자가0<NA><NA>00N
28930300003030000-201-2008-0000220080916<NA>1영업/정상1영업<NA><NA><NA><NA>02 92209612,635.00133882서울특별시 성동구 도선동 72번지서울특별시 성동구 왕십리로20길 19 (도선동)4709아모렉스관광호텔2018-02-21 11:18:17I2018-08-31 23:59:59.0관광호텔203048.430959451270.852835관광호텔102310000560N0<NA><NA><NA>자가0<NA><NA>00N
29030300003030000-201-2014-000012014-04-14<NA>1영업/정상1영업<NA><NA><NA><NA>02229800703085.50133-882서울특별시 성동구 도선동 86서울특별시 성동구 무학로2길 47 (도선동)4709호텔 컬리넌 왕십리2023-10-25 14:46:20U2022-10-30 22:08:00.0관광호텔203006.379794451150.696474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29130300003030000-201-2014-000022014-09-22<NA>1영업/정상1영업<NA><NA><NA><NA>02462 96102008.93133-835서울특별시 성동구 성수동2가 317-5서울특별시 성동구 성수이로 96, 3층~11층 (성수동2가)4783호텔 포코 POCO2023-10-25 14:47:02U2022-10-30 22:08:00.0일반호텔204971.645551449023.019694<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29230300003030000-201-2016-0000120160420<NA>3폐업2폐업20190527<NA><NA><NA>02221527271,117.80133847서울특별시 성동구 용답동 228-12번지서울특별시 성동구 자동차시장1길 27 (용답동)4808호텔272019-05-27 17:21:54U2019-05-29 02:40:00.0관광호텔205288.987166451015.467879관광호텔4114110270N0<NA><NA><NA><NA>00000N
29330300003030000-201-2016-0000220160811<NA>1영업/정상1영업<NA><NA><NA><NA>02229859002,027.58133882서울특별시 성동구 도선동 27번지서울특별시 성동구 무학로2길 51, 지하1층~지상10층 (도선동)4709포레스타호텔2018-02-21 11:33:01I2018-08-31 23:59:59.0관광호텔203046.092496451125.947965관광호텔102100100530N0<NA><NA><NA>자가00000N
29430300003030000-201-2017-0000120170308<NA>1영업/정상1영업<NA><NA><NA><NA>0222983650640.30133858서울특별시 성동구 하왕십리동 966-68번지 6~10층서울특별시 성동구 왕십리로 339-1, 6~10층 (하왕십리동)4710케이그랜드호스텔2018-07-09 15:50:08I2018-08-31 23:59:59.0숙박업 기타202756.732461451193.426474숙박업 기타00610000220N0<NA><NA><NA><NA>00000N
29530300003030000-201-2020-0000120201111<NA>1영업/정상1영업<NA><NA><NA><NA><NA>419.85133882서울특별시 성동구 도선동 110 브르네장여관서울특별시 성동구 왕십리로22길 17-1, 1~5층 (도선동)4709부르네 모텔2022-06-29 16:53:37U2021-12-07 00:01:00.0숙박업 기타203014.999035451269.829436<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>