Overview

Dataset statistics

Number of variables47
Number of observations215
Missing cells2749
Missing cells (%)27.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory85.0 KiB
Average record size in memory404.6 B

Variable types

Categorical18
Text6
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-17450/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
건물지하층수 is highly imbalanced (50.7%)Imbalance
건물소유구분명 is highly imbalanced (78.1%)Imbalance
여성종사자수 is highly imbalanced (84.3%)Imbalance
남성종사자수 is highly imbalanced (84.3%)Imbalance
다중이용업소여부 is highly imbalanced (89.4%)Imbalance
인허가취소일자 has 215 (100.0%) missing valuesMissing
폐업일자 has 78 (36.3%) missing valuesMissing
휴업시작일자 has 215 (100.0%) missing valuesMissing
휴업종료일자 has 215 (100.0%) missing valuesMissing
재개업일자 has 215 (100.0%) missing valuesMissing
전화번호 has 8 (3.7%) missing valuesMissing
도로명주소 has 76 (35.3%) missing valuesMissing
도로명우편번호 has 84 (39.1%) missing valuesMissing
좌표정보(X) has 20 (9.3%) missing valuesMissing
좌표정보(Y) has 20 (9.3%) missing valuesMissing
건물지상층수 has 134 (62.3%) missing valuesMissing
사용시작지상층 has 138 (64.2%) missing valuesMissing
사용끝지상층 has 162 (75.3%) missing valuesMissing
한실수 has 93 (43.3%) missing valuesMissing
양실수 has 81 (37.7%) missing valuesMissing
욕실수 has 102 (47.4%) missing valuesMissing
발한실여부 has 71 (33.0%) missing valuesMissing
좌석수 has 106 (49.3%) missing valuesMissing
조건부허가신고사유 has 215 (100.0%) missing valuesMissing
조건부허가시작일자 has 215 (100.0%) missing valuesMissing
조건부허가종료일자 has 215 (100.0%) missing valuesMissing
다중이용업소여부 has 71 (33.0%) 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 69 (32.1%) zerosZeros
사용시작지상층 has 65 (30.2%) zerosZeros
사용끝지상층 has 41 (19.1%) zerosZeros
한실수 has 27 (12.6%) zerosZeros
양실수 has 14 (6.5%) zerosZeros
욕실수 has 47 (21.9%) zerosZeros
좌석수 has 49 (22.8%) zerosZeros

Reproduction

Analysis started2024-05-11 00:50:49.813678
Analysis finished2024-05-11 00:50:51.344379
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3230000
215 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 215
100.0%

Length

2024-05-11T00:50:51.646917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:52.086474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 215
100.0%

관리번호
Text

UNIQUE 

Distinct215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T00:50:52.733651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4730
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

Unique215 ?
Unique (%)100.0%

Sample

1st row3230000-201-1968-00119
2nd row3230000-201-1969-00007
3rd row3230000-201-1969-00118
4th row3230000-201-1970-00001
5th row3230000-201-1970-00120
ValueCountFrequency (%)
3230000-201-1968-00119 1
 
0.5%
3230000-201-2003-00024 1
 
0.5%
3230000-201-2002-00008 1
 
0.5%
3230000-201-2002-00009 1
 
0.5%
3230000-201-2002-00011 1
 
0.5%
3230000-201-2002-00012 1
 
0.5%
3230000-201-2002-00013 1
 
0.5%
3230000-201-2003-00001 1
 
0.5%
3230000-201-2003-00002 1
 
0.5%
3230000-201-2003-00003 1
 
0.5%
Other values (205) 205
95.3%
2024-05-11T00:50:53.876610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1943
41.1%
- 645
 
13.6%
2 605
 
12.8%
3 533
 
11.3%
1 475
 
10.0%
9 197
 
4.2%
8 132
 
2.8%
7 63
 
1.3%
6 59
 
1.2%
4 45
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4085
86.4%
Dash Punctuation 645
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1943
47.6%
2 605
 
14.8%
3 533
 
13.0%
1 475
 
11.6%
9 197
 
4.8%
8 132
 
3.2%
7 63
 
1.5%
6 59
 
1.4%
4 45
 
1.1%
5 33
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 645
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4730
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1943
41.1%
- 645
 
13.6%
2 605
 
12.8%
3 533
 
11.3%
1 475
 
10.0%
9 197
 
4.2%
8 132
 
2.8%
7 63
 
1.3%
6 59
 
1.2%
4 45
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1943
41.1%
- 645
 
13.6%
2 605
 
12.8%
3 533
 
11.3%
1 475
 
10.0%
9 197
 
4.2%
8 132
 
2.8%
7 63
 
1.3%
6 59
 
1.2%
4 45
 
1.0%
Distinct92
Distinct (%)42.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1968-11-18 00:00:00
Maximum2023-03-07 00:00:00
2024-05-11T00:50:54.463310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:50:55.445277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
137 
1
78 

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 (%)
3 137
63.7%
1 78
36.3%

Length

2024-05-11T00:50:56.061512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:56.628608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 137
63.7%
1 78
36.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
137 
영업/정상
78 

Length

Max length5
Median length2
Mean length3.0883721
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 137
63.7%
영업/정상 78
36.3%

Length

2024-05-11T00:50:57.108862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:57.507882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 137
63.7%
영업/정상 78
36.3%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2
137 
1
78 

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 (%)
2 137
63.7%
1 78
36.3%

Length

2024-05-11T00:50:57.813551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:58.256902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 137
63.7%
1 78
36.3%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
137 
영업
78 

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 137
63.7%
영업 78
36.3%

Length

2024-05-11T00:50:58.806911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:50:59.151538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 137
63.7%
영업 78
36.3%

폐업일자
Date

MISSING 

Distinct107
Distinct (%)78.1%
Missing78
Missing (%)36.3%
Memory size1.8 KiB
Minimum1989-07-03 00:00:00
Maximum2023-03-30 00:00:00
2024-05-11T00:50:59.612580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:00.115230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

전화번호
Text

MISSING 

Distinct184
Distinct (%)88.9%
Missing8
Missing (%)3.7%
Memory size1.8 KiB
2024-05-11T00:51:00.911128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.154589
Min length8

Characters and Unicode

Total characters2102
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

Unique165 ?
Unique (%)79.7%

Sample

1st row0204001608
2nd row02 4781878
3rd row0200000000
4th row02 4004362
5th row0200000000
ValueCountFrequency (%)
02 132
36.8%
4130870 4
 
1.1%
4176755 3
 
0.8%
4141263 3
 
0.8%
4150512 3
 
0.8%
02417 3
 
0.8%
4164031 2
 
0.6%
412 2
 
0.6%
4165963 2
 
0.6%
4164161 2
 
0.6%
Other values (190) 203
56.5%
2024-05-11T00:51:02.308217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 446
21.2%
2 358
17.0%
4 293
13.9%
1 253
12.0%
177
 
8.4%
3 126
 
6.0%
5 121
 
5.8%
6 119
 
5.7%
7 77
 
3.7%
8 75
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1925
91.6%
Space Separator 177
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 446
23.2%
2 358
18.6%
4 293
15.2%
1 253
13.1%
3 126
 
6.5%
5 121
 
6.3%
6 119
 
6.2%
7 77
 
4.0%
8 75
 
3.9%
9 57
 
3.0%
Space Separator
ValueCountFrequency (%)
177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 446
21.2%
2 358
17.0%
4 293
13.9%
1 253
12.0%
177
 
8.4%
3 126
 
6.0%
5 121
 
5.8%
6 119
 
5.7%
7 77
 
3.7%
8 75
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 446
21.2%
2 358
17.0%
4 293
13.9%
1 253
12.0%
177
 
8.4%
3 126
 
6.0%
5 121
 
5.8%
6 119
 
5.7%
7 77
 
3.7%
8 75
 
3.6%
Distinct194
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T00:51:03.338505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.3953488
Min length3

Characters and Unicode

Total characters1375
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

Unique183 ?
Unique (%)85.1%

Sample

1st row53.56
2nd row149.85
3rd row10.00
4th row3.23
5th row.00
ValueCountFrequency (%)
00 12
 
5.6%
78.55 2
 
0.9%
1,113.84 2
 
0.9%
648.00 2
 
0.9%
323.64 2
 
0.9%
626.50 2
 
0.9%
357.45 2
 
0.9%
500.24 2
 
0.9%
840.96 2
 
0.9%
58.77 2
 
0.9%
Other values (184) 185
86.0%
2024-05-11T00:51:05.182403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 215
15.6%
0 165
12.0%
1 124
9.0%
6 122
8.9%
4 121
8.8%
5 120
8.7%
8 110
8.0%
9 95
6.9%
2 94
6.8%
3 83
 
6.0%
Other values (2) 126
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1113
80.9%
Other Punctuation 262
 
19.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 165
14.8%
1 124
11.1%
6 122
11.0%
4 121
10.9%
5 120
10.8%
8 110
9.9%
9 95
8.5%
2 94
8.4%
3 83
7.5%
7 79
7.1%
Other Punctuation
ValueCountFrequency (%)
. 215
82.1%
, 47
 
17.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1375
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 215
15.6%
0 165
12.0%
1 124
9.0%
6 122
8.9%
4 121
8.8%
5 120
8.7%
8 110
8.0%
9 95
6.9%
2 94
6.8%
3 83
 
6.0%
Other values (2) 126
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 215
15.6%
0 165
12.0%
1 124
9.0%
6 122
8.9%
4 121
8.8%
5 120
8.7%
8 110
8.0%
9 95
6.9%
2 94
6.8%
3 83
 
6.0%
Other values (2) 126
9.2%
Distinct40
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
138827
44 
138828
35 
138861
26 
138-827
20 
138-861
17 
Other values (35)
73 

Length

Max length7
Median length6
Mean length6.2930233
Min length6

Unique

Unique22 ?
Unique (%)10.2%

Sample

1st row138210
2nd row138210
3rd row138210
4th row138815
5th row138210

Common Values

ValueCountFrequency (%)
138827 44
20.5%
138828 35
16.3%
138861 26
12.1%
138-827 20
9.3%
138-861 17
 
7.9%
138210 15
 
7.0%
138-828 6
 
2.8%
138815 5
 
2.3%
138864 4
 
1.9%
138838 3
 
1.4%
Other values (30) 40
18.6%

Length

2024-05-11T00:51:05.865588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
138827 44
20.5%
138828 35
16.3%
138861 26
12.1%
138-827 20
9.3%
138-861 17
 
7.9%
138210 15
 
7.0%
138-828 6
 
2.8%
138815 5
 
2.3%
138864 4
 
1.9%
138838 3
 
1.4%
Other values (30) 40
18.6%
Distinct186
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T00:51:06.773509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length21
Min length17

Characters and Unicode

Total characters4515
Distinct characters84
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)75.8%

Sample

1st row서울특별시 송파구 장지동 산 314-17번지
2nd row서울특별시 송파구 장지동 산 94-15번지
3rd row서울특별시 송파구 장지동 산 133-0번지
4th row서울특별시 송파구 거여동 208-17번지
5th row서울특별시 송파구 장지동 산 166-0번지
ValueCountFrequency (%)
서울특별시 215
24.0%
송파구 215
24.0%
방이동 107
11.9%
잠실동 52
 
5.8%
15
 
1.7%
장지동 15
 
1.7%
삼전동 10
 
1.1%
거여동 10
 
1.1%
석촌동 6
 
0.7%
가락동 5
 
0.6%
Other values (206) 246
27.5%
2024-05-11T00:51:07.947343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
825
18.3%
217
 
4.8%
217
 
4.8%
215
 
4.8%
215
 
4.8%
215
 
4.8%
215
 
4.8%
215
 
4.8%
215
 
4.8%
215
 
4.8%
Other values (74) 1751
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2681
59.4%
Space Separator 825
 
18.3%
Decimal Number 792
 
17.5%
Dash Punctuation 200
 
4.4%
Uppercase Letter 15
 
0.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
217
 
8.1%
217
 
8.1%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
144
 
5.4%
Other values (49) 598
22.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
20.0%
K 2
13.3%
R 1
 
6.7%
J 1
 
6.7%
B 1
 
6.7%
A 1
 
6.7%
O 1
 
6.7%
I 1
 
6.7%
M 1
 
6.7%
H 1
 
6.7%
Other values (2) 2
13.3%
Decimal Number
ValueCountFrequency (%)
1 185
23.4%
4 107
13.5%
8 89
11.2%
3 79
10.0%
2 76
9.6%
9 54
 
6.8%
0 54
 
6.8%
6 53
 
6.7%
7 53
 
6.7%
5 42
 
5.3%
Space Separator
ValueCountFrequency (%)
825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2681
59.4%
Common 1819
40.3%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
217
 
8.1%
217
 
8.1%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
144
 
5.4%
Other values (49) 598
22.3%
Common
ValueCountFrequency (%)
825
45.4%
- 200
 
11.0%
1 185
 
10.2%
4 107
 
5.9%
8 89
 
4.9%
3 79
 
4.3%
2 76
 
4.2%
9 54
 
3.0%
0 54
 
3.0%
6 53
 
2.9%
Other values (3) 97
 
5.3%
Latin
ValueCountFrequency (%)
T 3
20.0%
K 2
13.3%
R 1
 
6.7%
J 1
 
6.7%
B 1
 
6.7%
A 1
 
6.7%
O 1
 
6.7%
I 1
 
6.7%
M 1
 
6.7%
H 1
 
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2681
59.4%
ASCII 1834
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
825
45.0%
- 200
 
10.9%
1 185
 
10.1%
4 107
 
5.8%
8 89
 
4.9%
3 79
 
4.3%
2 76
 
4.1%
9 54
 
2.9%
0 54
 
2.9%
6 53
 
2.9%
Other values (15) 112
 
6.1%
Hangul
ValueCountFrequency (%)
217
 
8.1%
217
 
8.1%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
215
 
8.0%
144
 
5.4%
Other values (49) 598
22.3%

도로명주소
Text

MISSING 

Distinct137
Distinct (%)98.6%
Missing76
Missing (%)35.3%
Memory size1.8 KiB
2024-05-11T00:51:08.558928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length27.374101
Min length22

Characters and Unicode

Total characters3805
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)97.1%

Sample

1st row서울특별시 송파구 성내천로44길 2-3 (마천동)
2nd row서울특별시 송파구 성내천로43길 1 (마천동)
3rd row서울특별시 송파구 마천로56길 2 (거여동)
4th row서울특별시 송파구 마천로 260 (거여동)
5th row서울특별시 송파구 마천로 316 (거여동)
ValueCountFrequency (%)
서울특별시 139
19.3%
송파구 139
19.3%
방이동 71
 
9.9%
오금로11길 41
 
5.7%
잠실동 35
 
4.9%
올림픽로34길 16
 
2.2%
올림픽로12길 14
 
1.9%
백제고분로7길 10
 
1.4%
삼전동 9
 
1.2%
위례성대로2길 6
 
0.8%
Other values (167) 240
33.3%
2024-05-11T00:51:09.552886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
581
 
15.3%
1 210
 
5.5%
148
 
3.9%
148
 
3.9%
139
 
3.7%
139
 
3.7%
( 139
 
3.7%
139
 
3.7%
) 139
 
3.7%
139
 
3.7%
Other values (90) 1884
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2232
58.7%
Decimal Number 601
 
15.8%
Space Separator 581
 
15.3%
Open Punctuation 139
 
3.7%
Close Punctuation 139
 
3.7%
Dash Punctuation 78
 
2.0%
Other Punctuation 21
 
0.6%
Uppercase Letter 11
 
0.3%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
148
 
6.6%
148
 
6.6%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
Other values (66) 824
36.9%
Decimal Number
ValueCountFrequency (%)
1 210
34.9%
2 86
14.3%
3 66
 
11.0%
5 54
 
9.0%
4 51
 
8.5%
7 37
 
6.2%
6 29
 
4.8%
8 26
 
4.3%
9 23
 
3.8%
0 19
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
27.3%
K 2
18.2%
I 1
 
9.1%
M 1
 
9.1%
H 1
 
9.1%
O 1
 
9.1%
E 1
 
9.1%
L 1
 
9.1%
Space Separator
ValueCountFrequency (%)
581
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2232
58.7%
Common 1562
41.1%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
148
 
6.6%
148
 
6.6%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
Other values (66) 824
36.9%
Common
ValueCountFrequency (%)
581
37.2%
1 210
 
13.4%
( 139
 
8.9%
) 139
 
8.9%
2 86
 
5.5%
- 78
 
5.0%
3 66
 
4.2%
5 54
 
3.5%
4 51
 
3.3%
7 37
 
2.4%
Other values (6) 121
 
7.7%
Latin
ValueCountFrequency (%)
T 3
27.3%
K 2
18.2%
I 1
 
9.1%
M 1
 
9.1%
H 1
 
9.1%
O 1
 
9.1%
E 1
 
9.1%
L 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2232
58.7%
ASCII 1573
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
581
36.9%
1 210
 
13.4%
( 139
 
8.8%
) 139
 
8.8%
2 86
 
5.5%
- 78
 
5.0%
3 66
 
4.2%
5 54
 
3.4%
4 51
 
3.2%
7 37
 
2.4%
Other values (14) 132
 
8.4%
Hangul
ValueCountFrequency (%)
148
 
6.6%
148
 
6.6%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
139
 
6.2%
Other values (66) 824
36.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)26.7%
Missing84
Missing (%)39.1%
Infinite0
Infinite (%)0.0%
Mean5577.8855
Minimum5542
Maximum5837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:09.975403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5542
5-th percentile5542
Q15544
median5552
Q35558.5
95-th percentile5742
Maximum5837
Range295
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation66.046795
Coefficient of variation (CV)0.01184083
Kurtosis3.9728358
Mean5577.8855
Median Absolute Deviation (MAD)8
Skewness2.2472938
Sum730703
Variance4362.1791
MonotonicityNot monotonic
2024-05-11T00:51:10.317587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5543 20
 
9.3%
5544 18
 
8.4%
5545 17
 
7.9%
5556 12
 
5.6%
5558 9
 
4.2%
5557 9
 
4.2%
5542 9
 
4.2%
5735 3
 
1.4%
5719 3
 
1.4%
5594 2
 
0.9%
Other values (25) 29
 
13.5%
(Missing) 84
39.1%
ValueCountFrequency (%)
5542 9
4.2%
5543 20
9.3%
5544 18
8.4%
5545 17
7.9%
5551 1
 
0.5%
5552 2
 
0.9%
5554 1
 
0.5%
5556 12
5.6%
5557 9
4.2%
5558 9
4.2%
ValueCountFrequency (%)
5837 1
 
0.5%
5807 1
 
0.5%
5765 2
0.9%
5763 1
 
0.5%
5759 1
 
0.5%
5749 1
 
0.5%
5735 3
1.4%
5719 3
1.4%
5713 1
 
0.5%
5697 1
 
0.5%
Distinct204
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T00:51:10.737114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length4.944186
Min length1

Characters and Unicode

Total characters1063
Distinct characters267
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)89.8%

Sample

1st row경기
2nd row조호
3rd row설악
4th row부흥
5th row대흥
ValueCountFrequency (%)
호텔 23
 
8.0%
모텔 9
 
3.1%
hotel 5
 
1.7%
잠실 3
 
1.0%
3
 
1.0%
체리 2
 
0.7%
서일장 2
 
0.7%
쉐르벨 2
 
0.7%
im 2
 
0.7%
tm모텔 2
 
0.7%
Other values (217) 234
81.5%
2024-05-11T00:51:11.420054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
 
8.8%
73
 
6.9%
64
 
6.0%
31
 
2.9%
24
 
2.3%
24
 
2.3%
24
 
2.3%
23
 
2.2%
22
 
2.1%
( 17
 
1.6%
Other values (257) 667
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 841
79.1%
Uppercase Letter 77
 
7.2%
Space Separator 73
 
6.9%
Lowercase Letter 18
 
1.7%
Open Punctuation 17
 
1.6%
Close Punctuation 17
 
1.6%
Decimal Number 17
 
1.6%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
94
 
11.2%
64
 
7.6%
31
 
3.7%
24
 
2.9%
24
 
2.9%
24
 
2.9%
23
 
2.7%
22
 
2.6%
16
 
1.9%
15
 
1.8%
Other values (211) 504
59.9%
Uppercase Letter
ValueCountFrequency (%)
T 10
13.0%
H 9
11.7%
E 9
11.7%
L 7
9.1%
O 7
9.1%
M 7
9.1%
I 5
 
6.5%
A 3
 
3.9%
R 3
 
3.9%
N 3
 
3.9%
Other values (11) 14
18.2%
Lowercase Letter
ValueCountFrequency (%)
n 3
16.7%
e 3
16.7%
a 2
11.1%
i 2
11.1%
z 1
 
5.6%
v 1
 
5.6%
l 1
 
5.6%
t 1
 
5.6%
s 1
 
5.6%
o 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
2 7
41.2%
4 2
 
11.8%
0 2
 
11.8%
3 2
 
11.8%
1 1
 
5.9%
7 1
 
5.9%
6 1
 
5.9%
5 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 840
79.0%
Common 127
 
11.9%
Latin 95
 
8.9%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
94
 
11.2%
64
 
7.6%
31
 
3.7%
24
 
2.9%
24
 
2.9%
24
 
2.9%
23
 
2.7%
22
 
2.6%
16
 
1.9%
15
 
1.8%
Other values (210) 503
59.9%
Latin
ValueCountFrequency (%)
T 10
 
10.5%
H 9
 
9.5%
E 9
 
9.5%
L 7
 
7.4%
O 7
 
7.4%
M 7
 
7.4%
I 5
 
5.3%
n 3
 
3.2%
A 3
 
3.2%
e 3
 
3.2%
Other values (23) 32
33.7%
Common
ValueCountFrequency (%)
73
57.5%
( 17
 
13.4%
) 17
 
13.4%
2 7
 
5.5%
. 2
 
1.6%
4 2
 
1.6%
0 2
 
1.6%
3 2
 
1.6%
1 1
 
0.8%
& 1
 
0.8%
Other values (3) 3
 
2.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 840
79.0%
ASCII 222
 
20.9%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
94
 
11.2%
64
 
7.6%
31
 
3.7%
24
 
2.9%
24
 
2.9%
24
 
2.9%
23
 
2.7%
22
 
2.6%
16
 
1.9%
15
 
1.8%
Other values (210) 503
59.9%
ASCII
ValueCountFrequency (%)
73
32.9%
( 17
 
7.7%
) 17
 
7.7%
T 10
 
4.5%
H 9
 
4.1%
E 9
 
4.1%
L 7
 
3.2%
2 7
 
3.2%
O 7
 
3.2%
M 7
 
3.2%
Other values (36) 59
26.6%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct166
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2000-03-14 00:00:00
Maximum2024-05-09 16:59:15
2024-05-11T00:51:11.686740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:11.964375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
I
116 
U
99 

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 116
54.0%
U 99
46.0%

Length

2024-05-11T00:51:12.338070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:12.663123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 116
54.0%
u 99
46.0%
Distinct51
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:01:00
2024-05-11T00:51:13.006361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:51:13.364132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
여관업
142 
일반호텔
24 
관광호텔
24 
여인숙업
16 
숙박업 기타
 
7
Other values (2)
 
2

Length

Max length8
Median length3
Mean length3.4372093
Min length3

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 142
66.0%
일반호텔 24
 
11.2%
관광호텔 24
 
11.2%
여인숙업 16
 
7.4%
숙박업 기타 7
 
3.3%
휴양콘도미니엄업 1
 
0.5%
숙박업(생활) 1
 
0.5%

Length

2024-05-11T00:51:13.875374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:14.253904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 142
64.0%
일반호텔 24
 
10.8%
관광호텔 24
 
10.8%
여인숙업 16
 
7.2%
숙박업 7
 
3.2%
기타 7
 
3.2%
휴양콘도미니엄업 1
 
0.5%
숙박업(생활 1
 
0.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)74.4%
Missing20
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean209227.02
Minimum206938.63
Maximum213646.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:14.683895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206938.63
5-th percentile206982.73
Q1207698.74
median209652.36
Q3209952.72
95-th percentile212779.33
Maximum213646.08
Range6707.4463
Interquartile range (IQR)2253.9864

Descriptive statistics

Standard deviation1548.098
Coefficient of variation (CV)0.0073991303
Kurtosis0.6419925
Mean209227.02
Median Absolute Deviation (MAD)356.31932
Skewness0.45445328
Sum40799269
Variance2396607.4
MonotonicityNot monotonic
2024-05-11T00:51:15.135717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207029.789351375 4
 
1.9%
209595.213143028 3
 
1.4%
209775.184828447 3
 
1.4%
206938.63231936 3
 
1.4%
209958.01408096 3
 
1.4%
209952.723404381 3
 
1.4%
209703.236398411 3
 
1.4%
209786.364073326 3
 
1.4%
207220.229888603 3
 
1.4%
207148.374688088 3
 
1.4%
Other values (135) 164
76.3%
(Missing) 20
 
9.3%
ValueCountFrequency (%)
206938.63231936 3
1.4%
206941.757489986 1
 
0.5%
206952.668934766 1
 
0.5%
206956.849156975 2
0.9%
206959.130061112 1
 
0.5%
206977.208647612 2
0.9%
206985.089505143 1
 
0.5%
206999.298639306 2
0.9%
207029.789351375 4
1.9%
207055.16119649 1
 
0.5%
ValueCountFrequency (%)
213646.078651347 1
0.5%
213582.888080425 1
0.5%
213521.631897031 2
0.9%
213277.174882208 1
0.5%
213252.720434881 1
0.5%
213237.254517152 1
0.5%
213134.259009874 1
0.5%
212821.306425777 1
0.5%
212804.289399942 1
0.5%
212768.639964757 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)74.4%
Missing20
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean445460.89
Minimum442053.23
Maximum446539.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:15.961664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442053.23
5-th percentile443618.93
Q1445407.09
median445904.5
Q3445969.36
95-th percentile446033.35
Maximum446539.28
Range4486.0514
Interquartile range (IQR)562.26944

Descriptive statistics

Standard deviation779.94651
Coefficient of variation (CV)0.0017508754
Kurtosis3.1953367
Mean445460.89
Median Absolute Deviation (MAD)131.67429
Skewness-1.8476486
Sum86864873
Variance608316.56
MonotonicityNot monotonic
2024-05-11T00:51:16.482811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445407.090356997 4
 
1.9%
445912.216884712 3
 
1.4%
446018.887942218 3
 
1.4%
445429.645738463 3
 
1.4%
445978.258014242 3
 
1.4%
445967.54108678 3
 
1.4%
445978.115421557 3
 
1.4%
446039.870841503 3
 
1.4%
445454.538924885 3
 
1.4%
445418.562120928 3
 
1.4%
Other values (135) 164
76.3%
(Missing) 20
 
9.3%
ValueCountFrequency (%)
442053.227933005 1
0.5%
442611.394350958 1
0.5%
442886.334532857 1
0.5%
443379.607400665 2
0.9%
443484.595603431 1
0.5%
443523.095659369 1
0.5%
443526.648866499 1
0.5%
443549.893536475 1
0.5%
443577.623684933 1
0.5%
443636.639692272 1
0.5%
ValueCountFrequency (%)
446539.279382444 1
 
0.5%
446061.095454637 1
 
0.5%
446059.613892034 2
0.9%
446039.870841503 3
1.4%
446036.170082623 2
0.9%
446034.863019263 1
 
0.5%
446032.706725406 1
 
0.5%
446026.086162523 1
 
0.5%
446023.925869536 1
 
0.5%
446021.218821193 2
0.9%

위생업태명
Categorical

Distinct8
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
여관업
98 
<NA>
71 
여인숙업
13 
일반호텔
13 
관광호텔
12 
Other values (3)
 
8

Length

Max length8
Median length4
Mean length3.6325581
Min length3

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 98
45.6%
<NA> 71
33.0%
여인숙업 13
 
6.0%
일반호텔 13
 
6.0%
관광호텔 12
 
5.6%
숙박업 기타 6
 
2.8%
휴양콘도미니엄업 1
 
0.5%
숙박업(생활) 1
 
0.5%

Length

2024-05-11T00:51:16.962210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:17.541890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 98
44.3%
na 71
32.1%
여인숙업 13
 
5.9%
일반호텔 13
 
5.9%
관광호텔 12
 
5.4%
숙박업 6
 
2.7%
기타 6
 
2.7%
휴양콘도미니엄업 1
 
0.5%
숙박업(생활 1
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)9.9%
Missing134
Missing (%)62.3%
Infinite0
Infinite (%)0.0%
Mean1.3703704
Minimum0
Maximum19
Zeros69
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:18.188012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.7697627
Coefficient of variation (CV)2.7509079
Kurtosis10.090332
Mean1.3703704
Median Absolute Deviation (MAD)0
Skewness3.1432394
Sum111
Variance14.211111
MonotonicityNot monotonic
2024-05-11T00:51:18.611366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 69
32.1%
7 3
 
1.4%
8 3
 
1.4%
16 2
 
0.9%
4 1
 
0.5%
6 1
 
0.5%
5 1
 
0.5%
19 1
 
0.5%
(Missing) 134
62.3%
ValueCountFrequency (%)
0 69
32.1%
4 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
7 3
 
1.4%
8 3
 
1.4%
16 2
 
0.9%
19 1
 
0.5%
ValueCountFrequency (%)
19 1
 
0.5%
16 2
 
0.9%
8 3
 
1.4%
7 3
 
1.4%
6 1
 
0.5%
5 1
 
0.5%
4 1
 
0.5%
0 69
32.1%

건물지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
134 
0
69 
1
 
7
5
 
2
2
 
2

Length

Max length4
Median length4
Mean length2.8697674
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 134
62.3%
0 69
32.1%
1 7
 
3.3%
5 2
 
0.9%
2 2
 
0.9%
3 1
 
0.5%

Length

2024-05-11T00:51:19.227527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:19.627052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
62.3%
0 69
32.1%
1 7
 
3.3%
5 2
 
0.9%
2 2
 
0.9%
3 1
 
0.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.8%
Missing138
Missing (%)64.2%
Infinite0
Infinite (%)0.0%
Mean0.49350649
Minimum0
Maximum17
Zeros65
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:19.931354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1251834
Coefficient of variation (CV)4.3062928
Kurtosis49.988447
Mean0.49350649
Median Absolute Deviation (MAD)0
Skewness6.7395622
Sum38
Variance4.5164046
MonotonicityNot monotonic
2024-05-11T00:51:20.261198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 65
30.2%
1 7
 
3.3%
2 2
 
0.9%
3 1
 
0.5%
17 1
 
0.5%
7 1
 
0.5%
(Missing) 138
64.2%
ValueCountFrequency (%)
0 65
30.2%
1 7
 
3.3%
2 2
 
0.9%
3 1
 
0.5%
7 1
 
0.5%
17 1
 
0.5%
ValueCountFrequency (%)
17 1
 
0.5%
7 1
 
0.5%
3 1
 
0.5%
2 2
 
0.9%
1 7
 
3.3%
0 65
30.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)20.8%
Missing162
Missing (%)75.3%
Infinite0
Infinite (%)0.0%
Mean2.3773585
Minimum0
Maximum31
Zeros41
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:20.944601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.8
Maximum31
Range31
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8316986
Coefficient of variation (CV)2.4530161
Kurtosis11.829715
Mean2.3773585
Median Absolute Deviation (MAD)0
Skewness3.2407717
Sum126
Variance34.008708
MonotonicityNot monotonic
2024-05-11T00:51:21.302530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 41
 
19.1%
6 2
 
0.9%
8 2
 
0.9%
7 1
 
0.5%
4 1
 
0.5%
2 1
 
0.5%
5 1
 
0.5%
19 1
 
0.5%
16 1
 
0.5%
31 1
 
0.5%
(Missing) 162
75.3%
ValueCountFrequency (%)
0 41
19.1%
2 1
 
0.5%
4 1
 
0.5%
5 1
 
0.5%
6 2
 
0.9%
7 1
 
0.5%
8 2
 
0.9%
14 1
 
0.5%
16 1
 
0.5%
19 1
 
0.5%
ValueCountFrequency (%)
31 1
0.5%
19 1
0.5%
16 1
0.5%
14 1
0.5%
8 2
0.9%
7 1
0.5%
6 2
0.9%
5 1
0.5%
4 1
0.5%
2 1
0.5%
Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
141 
0
70 
1
 
3
5
 
1

Length

Max length4
Median length4
Mean length2.9674419
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 141
65.6%
0 70
32.6%
1 3
 
1.4%
5 1
 
0.5%

Length

2024-05-11T00:51:21.744767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:22.117852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
65.6%
0 70
32.6%
1 3
 
1.4%
5 1
 
0.5%
Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
165 
0
46 
1
 
4

Length

Max length4
Median length4
Mean length3.3023256
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> 165
76.7%
0 46
 
21.4%
1 4
 
1.9%

Length

2024-05-11T00:51:22.535076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:22.879823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 165
76.7%
0 46
 
21.4%
1 4
 
1.9%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)22.1%
Missing93
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean8.7704918
Minimum0
Maximum60
Zeros27
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:23.257302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7.5
Q312
95-th percentile21.9
Maximum60
Range60
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.0551906
Coefficient of variation (CV)1.032461
Kurtosis9.4459127
Mean8.7704918
Median Absolute Deviation (MAD)5
Skewness2.3766807
Sum1070
Variance81.996477
MonotonicityNot monotonic
2024-05-11T00:51:23.645994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 27
 
12.6%
10 11
 
5.1%
6 10
 
4.7%
8 8
 
3.7%
7 7
 
3.3%
9 7
 
3.3%
5 6
 
2.8%
13 4
 
1.9%
16 4
 
1.9%
12 4
 
1.9%
Other values (17) 34
 
15.8%
(Missing) 93
43.3%
ValueCountFrequency (%)
0 27
12.6%
1 3
 
1.4%
2 3
 
1.4%
3 3
 
1.4%
4 2
 
0.9%
5 6
 
2.8%
6 10
 
4.7%
7 7
 
3.3%
8 8
 
3.7%
9 7
 
3.3%
ValueCountFrequency (%)
60 1
 
0.5%
44 1
 
0.5%
37 1
 
0.5%
29 1
 
0.5%
26 1
 
0.5%
23 1
 
0.5%
22 1
 
0.5%
20 3
1.4%
19 3
1.4%
18 3
1.4%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct50
Distinct (%)37.3%
Missing81
Missing (%)37.7%
Infinite0
Infinite (%)0.0%
Mean31.731343
Minimum0
Maximum472
Zeros14
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:24.147559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median22
Q330
95-th percentile64.75
Maximum472
Range472
Interquartile range (IQR)15

Descriptive statistics

Standard deviation56.530272
Coefficient of variation (CV)1.7815279
Kurtosis41.706674
Mean31.731343
Median Absolute Deviation (MAD)7.5
Skewness6.1207813
Sum4252
Variance3195.6716
MonotonicityNot monotonic
2024-05-11T00:51:24.642114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14
 
6.5%
15 10
 
4.7%
20 9
 
4.2%
22 8
 
3.7%
24 6
 
2.8%
27 6
 
2.8%
23 6
 
2.8%
16 6
 
2.8%
30 5
 
2.3%
14 4
 
1.9%
Other values (40) 60
27.9%
(Missing) 81
37.7%
ValueCountFrequency (%)
0 14
6.5%
1 1
 
0.5%
3 1
 
0.5%
6 2
 
0.9%
7 1
 
0.5%
8 2
 
0.9%
10 2
 
0.9%
11 2
 
0.9%
13 1
 
0.5%
14 4
 
1.9%
ValueCountFrequency (%)
472 1
0.5%
403 1
0.5%
220 1
0.5%
160 1
0.5%
82 1
0.5%
71 1
0.5%
68 1
0.5%
63 1
0.5%
58 1
0.5%
54 1
0.5%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)28.3%
Missing102
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean20.654867
Minimum0
Maximum257
Zeros47
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:25.020681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q330
95-th percentile52.2
Maximum257
Range257
Interquartile range (IQR)30

Descriptive statistics

Standard deviation28.712793
Coefficient of variation (CV)1.3901224
Kurtosis40.482801
Mean20.654867
Median Absolute Deviation (MAD)21
Skewness5.0808022
Sum2334
Variance824.42446
MonotonicityNot monotonic
2024-05-11T00:51:25.433803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 47
21.9%
24 8
 
3.7%
30 7
 
3.3%
28 4
 
1.9%
29 4
 
1.9%
36 3
 
1.4%
25 3
 
1.4%
33 3
 
1.4%
27 3
 
1.4%
43 2
 
0.9%
Other values (22) 29
 
13.5%
(Missing) 102
47.4%
ValueCountFrequency (%)
0 47
21.9%
3 1
 
0.5%
16 1
 
0.5%
19 1
 
0.5%
20 2
 
0.9%
21 1
 
0.5%
22 2
 
0.9%
23 1
 
0.5%
24 8
 
3.7%
25 3
 
1.4%
ValueCountFrequency (%)
257 1
0.5%
64 1
0.5%
60 1
0.5%
56 1
0.5%
54 2
0.9%
51 2
0.9%
50 1
0.5%
45 1
0.5%
44 1
0.5%
43 2
0.9%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.4%
Missing71
Missing (%)33.0%
Memory size562.0 B
True
99 
False
45 
(Missing)
71 
ValueCountFrequency (%)
True 99
46.0%
False 45
20.9%
(Missing) 71
33.0%
2024-05-11T00:51:25.785631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)33.9%
Missing106
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean27.422018
Minimum0
Maximum880
Zeros49
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T00:51:26.136613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q330
95-th percentile80
Maximum880
Range880
Interquartile range (IQR)30

Descriptive statistics

Standard deviation87.305582
Coefficient of variation (CV)3.1837767
Kurtosis86.048082
Mean27.422018
Median Absolute Deviation (MAD)14
Skewness8.8490719
Sum2989
Variance7622.2647
MonotonicityNot monotonic
2024-05-11T00:51:26.544435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 49
22.8%
20 5
 
2.3%
30 5
 
2.3%
15 4
 
1.9%
14 4
 
1.9%
22 4
 
1.9%
16 3
 
1.4%
32 3
 
1.4%
40 2
 
0.9%
34 2
 
0.9%
Other values (27) 28
 
13.0%
(Missing) 106
49.3%
ValueCountFrequency (%)
0 49
22.8%
3 1
 
0.5%
10 1
 
0.5%
11 1
 
0.5%
14 4
 
1.9%
15 4
 
1.9%
16 3
 
1.4%
17 1
 
0.5%
18 1
 
0.5%
19 1
 
0.5%
ValueCountFrequency (%)
880 1
0.5%
168 1
0.5%
144 1
0.5%
108 1
0.5%
96 1
0.5%
88 1
0.5%
68 1
0.5%
64 1
0.5%
58 1
0.5%
54 1
0.5%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
203 
자가
 
10
임대
 
2

Length

Max length4
Median length4
Mean length3.8883721
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> 203
94.4%
자가 10
 
4.7%
임대 2
 
0.9%

Length

2024-05-11T00:51:27.007012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:27.436457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 203
94.4%
자가 10
 
4.7%
임대 2
 
0.9%

세탁기수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
160 
0
55 

Length

Max length4
Median length4
Mean length3.2325581
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> 160
74.4%
0 55
 
25.6%

Length

2024-05-11T00:51:27.862441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:28.210552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 160
74.4%
0 55
 
25.6%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
207 
0
 
7
15
 
1

Length

Max length4
Median length4
Mean length3.8930233
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 207
96.3%
0 7
 
3.3%
15 1
 
0.5%

Length

2024-05-11T00:51:28.643951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:29.088629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 207
96.3%
0 7
 
3.3%
15 1
 
0.5%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
207 
0
 
7
10
 
1

Length

Max length4
Median length4
Mean length3.8930233
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 207
96.3%
0 7
 
3.3%
10 1
 
0.5%

Length

2024-05-11T00:51:29.472310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:29.836652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 207
96.3%
0 7
 
3.3%
10 1
 
0.5%

회수건조수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
164 
0
51 

Length

Max length4
Median length4
Mean length3.2883721
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> 164
76.3%
0 51
 
23.7%

Length

2024-05-11T00:51:30.233576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:30.597809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 164
76.3%
0 51
 
23.7%

침대수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
165 
0
50 

Length

Max length4
Median length4
Mean length3.3023256
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> 165
76.7%
0 50
 
23.3%

Length

2024-05-11T00:51:30.974631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:51:31.334643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 165
76.7%
0 50
 
23.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.4%
Missing71
Missing (%)33.0%
Memory size562.0 B
False
142 
True
 
2
(Missing)
71 
ValueCountFrequency (%)
False 142
66.0%
True 2
 
0.9%
(Missing) 71
33.0%
2024-05-11T00:51:31.692444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032300003230000-201-1968-0011919681118<NA>3폐업2폐업19930210<NA><NA><NA>020400160853.56138210서울특별시 송파구 장지동 산 314-17번지<NA><NA>경기2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>700Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132300003230000-201-1969-0000719690919<NA>3폐업2폐업19960612<NA><NA><NA>02 4781878149.85138210서울특별시 송파구 장지동 산 94-15번지<NA><NA>조호2002-09-04 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>700Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232300003230000-201-1969-0011819690623<NA>3폐업2폐업19921110<NA><NA><NA>020000000010.00138210서울특별시 송파구 장지동 산 133-0번지<NA><NA>설악2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>800Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332300003230000-201-1970-0000119701229<NA>3폐업2폐업20000814<NA><NA><NA>02 40043623.23138815서울특별시 송파구 거여동 208-17번지<NA><NA>부흥2002-10-11 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>000Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432300003230000-201-1970-0012019700727<NA>3폐업2폐업19900328<NA><NA><NA>0200000000.00138210서울특별시 송파구 장지동 산 166-0번지<NA><NA>대흥2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>500Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532300003230000-201-1970-0012119700605<NA>3폐업2폐업19930824<NA><NA><NA>020408492178.55138210서울특별시 송파구 장지동 산 186-1번지<NA><NA>동성2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>900Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632300003230000-201-1970-0012219701224<NA>3폐업2폐업19960306<NA><NA><NA>02 402944378.55138210서울특별시 송파구 장지동 산 300-2번지<NA><NA>충북2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>900Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732300003230000-201-1971-0000919711201<NA>3폐업2폐업19950707<NA><NA><NA>02 406042958.77138210서울특별시 송파구 장지동 산 207-3번지<NA><NA>삼화2002-09-04 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832300003230000-201-1971-0010919711201<NA>3폐업2폐업19950707<NA><NA><NA>02 0000058.77138210서울특별시 송파구 장지동 산 207-3번지<NA><NA>삼화2002-09-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>710N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932300003230000-201-1971-0011219710818<NA>3폐업2폐업20030226<NA><NA><NA>020400316649.86138814서울특별시 송파구 거여동 181-406번지<NA><NA>한성2003-04-18 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업<NA><NA><NA><NA><NA><NA>12<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
20532300003230000-201-2018-0000220181029<NA>3폐업2폐업20230111<NA><NA><NA>02 41308701,260.98138861서울특별시 송파구 잠실동 178-1 J BAR서울특별시 송파구 올림픽로8길 11, 아이호텔 3~8층 (잠실동)5556아이호텔2023-01-11 09:22:31U2022-11-30 23:04:00.0여관업207029.789351445407.090357<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20632300003230000-201-2019-0000120190717<NA>1영업/정상1영업<NA><NA><NA><NA>02 423 43002,983.46138861서울특별시 송파구 잠실동 180-10번지서울특별시 송파구 올림픽로12길 4-17 (잠실동)5557호텔 더 캐슬(신천)2019-07-18 09:38:31I2019-07-19 02:21:45.0관광호텔207163.343016445433.784924관광호텔16200000680N0<NA><NA><NA><NA>00000N
20732300003230000-201-2019-000022019-12-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 409 5919969.15138-802서울특별시 송파구 가락동 73-1 관광호텔서울특별시 송파구 송이로 104, 관광호텔 (가락동)5713부티크호텔 XYM2023-10-27 13:56:44U2022-10-30 22:09:00.0관광호텔210664.369854443861.184408<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20832300003230000-201-2019-0000320191220<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,650.53138827서울특별시 송파구 방이동 36-17번지 호텔 더 캐슬서울특별시 송파구 올림픽로32길 7, 호텔 더 캐슬 (방이동)5543호텔 더 캐슬(방이1)2019-12-20 12:15:09I2019-12-22 00:23:25.0관광호텔209573.227434445919.352243관광호텔00116<NA><NA>0630N0<NA><NA><NA>자가00000N
20932300003230000-201-2021-0000120210608<NA>1영업/정상1영업<NA><NA><NA><NA>02 412 22201,487.08138827서울특별시 송파구 방이동 36-2서울특별시 송파구 올림픽로32길 7-1 (방이동)5543호텔 더 캐슬(방이2)2021-06-08 14:29:04I2021-06-10 00:22:55.0관광호텔209577.22506445907.610177관광호텔162<NA><NA><NA><NA>0410N0<NA><NA><NA>자가00000Y
21032300003230000-201-2021-0000220210708<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27,795.00138934서울특별시 송파구 신천동 29-1 KT송파타워서울특별시 송파구 잠실로 209, KT송파타워 17~31층 (신천동)5552소피텔 앰배서더 서울호텔 앤 서비스드 레지던스2021-07-08 16:57:37I2021-07-10 00:22:52.0관광호텔209338.12868445745.524217관광호텔0017310004030N0<NA><NA><NA>임대00000Y
21132300003230000-201-2022-000012022-11-30<NA>3폐업2폐업2023-02-17<NA><NA><NA>02 598 02452261.42138-861서울특별시 송파구 잠실동 176-9 모텔 폼서울특별시 송파구 백제고분로7길 7-13, 모텔 폼 (잠실동)5556폼 호텔2023-02-17 14:27:55U2022-12-01 23:09:00.0일반호텔206956.849157445427.396129<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21232300003230000-201-2022-000022022-11-30<NA>3폐업2폐업2023-02-17<NA><NA><NA>02 598 02451394.99138-861서울특별시 송파구 잠실동 176-1 다비드호텔서울특별시 송파구 백제고분로7길 3-16, 다비드호텔 (잠실동)5556봄 호텔2023-02-17 14:26:40U2022-12-01 23:09:00.0일반호텔206938.632319445429.645738<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21332300003230000-201-2023-000012023-03-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>996.20138-826서울특별시 송파구 문정동 61-15 메리제인호텔서울특별시 송파구 송파대로20길 6 (문정동, 메리제인호텔)5807메리제인2023-10-27 13:59:07U2022-10-30 22:09:00.0관광호텔210857.025716442611.394351<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21432300003230000-214-2021-0000120210708<NA>1영업/정상1영업<NA><NA><NA><NA>02 2040318814,654.94138934서울특별시 송파구 신천동 29-1 KT송파타워서울특별시 송파구 잠실로 209, KT송파타워 7층~14층 (신천동)5552소피텔 앰배서더 서울호텔 앤 서비스드 레지던스2022-01-12 14:09:37U2022-01-14 02:40:00.0숙박업(생활)209338.12868445745.524217숙박업(생활)007140001600N0<NA><NA><NA><NA>00000N