Overview

Dataset statistics

Number of variables47
Number of observations180
Missing cells1686
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.1 KiB
Average record size in memory404.7 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-17431/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (65.8%)Imbalance
건물지상층수 is highly imbalanced (56.4%)Imbalance
건물지하층수 is highly imbalanced (51.9%)Imbalance
건물소유구분명 is highly imbalanced (84.6%)Imbalance
여성종사자수 is highly imbalanced (73.8%)Imbalance
남성종사자수 is highly imbalanced (73.8%)Imbalance
인허가취소일자 has 180 (100.0%) missing valuesMissing
폐업일자 has 67 (37.2%) missing valuesMissing
휴업시작일자 has 180 (100.0%) missing valuesMissing
휴업종료일자 has 180 (100.0%) missing valuesMissing
재개업일자 has 180 (100.0%) missing valuesMissing
전화번호 has 4 (2.2%) missing valuesMissing
도로명주소 has 44 (24.4%) missing valuesMissing
도로명우편번호 has 52 (28.9%) missing valuesMissing
좌표정보(X) has 8 (4.4%) missing valuesMissing
좌표정보(Y) has 8 (4.4%) missing valuesMissing
사용끝지상층 has 99 (55.0%) missing valuesMissing
한실수 has 38 (21.1%) missing valuesMissing
양실수 has 40 (22.2%) missing valuesMissing
발한실여부 has 33 (18.3%) missing valuesMissing
조건부허가신고사유 has 180 (100.0%) missing valuesMissing
조건부허가시작일자 has 180 (100.0%) missing valuesMissing
조건부허가종료일자 has 180 (100.0%) missing valuesMissing
다중이용업소여부 has 33 (18.3%) 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
사용끝지상층 has 69 (38.3%) zerosZeros
한실수 has 59 (32.8%) zerosZeros
양실수 has 10 (5.6%) zerosZeros

Reproduction

Analysis started2024-04-29 19:18:21.225311
Analysis finished2024-04-29 19:18:22.074808
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3040000
180 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 180
100.0%

Length

2024-04-30T04:18:22.149409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:22.240604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 180
100.0%

관리번호
Text

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:18:22.390439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3960
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

Unique180 ?
Unique (%)100.0%

Sample

1st row3040000-201-1964-00001
2nd row3040000-201-1968-00001
3rd row3040000-201-1968-00002
4th row3040000-201-1969-00001
5th row3040000-201-1969-00002
ValueCountFrequency (%)
3040000-201-1964-00001 1
 
0.6%
3040000-201-1983-00028 1
 
0.6%
3040000-201-1983-00039 1
 
0.6%
3040000-201-1983-00031 1
 
0.6%
3040000-201-1983-00032 1
 
0.6%
3040000-201-1983-00033 1
 
0.6%
3040000-201-1983-00034 1
 
0.6%
3040000-201-1983-00035 1
 
0.6%
3040000-201-1983-00036 1
 
0.6%
3040000-201-1983-00037 1
 
0.6%
Other values (170) 170
94.4%
2024-04-30T04:18:22.671737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1711
43.2%
- 540
 
13.6%
1 472
 
11.9%
3 282
 
7.1%
2 280
 
7.1%
4 220
 
5.6%
9 188
 
4.7%
8 122
 
3.1%
7 79
 
2.0%
6 37
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3420
86.4%
Dash Punctuation 540
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1711
50.0%
1 472
 
13.8%
3 282
 
8.2%
2 280
 
8.2%
4 220
 
6.4%
9 188
 
5.5%
8 122
 
3.6%
7 79
 
2.3%
6 37
 
1.1%
5 29
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 540
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1711
43.2%
- 540
 
13.6%
1 472
 
11.9%
3 282
 
7.1%
2 280
 
7.1%
4 220
 
5.6%
9 188
 
4.7%
8 122
 
3.1%
7 79
 
2.0%
6 37
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1711
43.2%
- 540
 
13.6%
1 472
 
11.9%
3 282
 
7.1%
2 280
 
7.1%
4 220
 
5.6%
9 188
 
4.7%
8 122
 
3.1%
7 79
 
2.0%
6 37
 
0.9%
Distinct167
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1964-04-03 00:00:00
Maximum2024-01-22 00:00:00
2024-04-30T04:18:22.808271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:22.943824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
113 
1
67 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 113
62.8%
1 67
37.2%

Length

2024-04-30T04:18:23.054366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:23.134004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 113
62.8%
1 67
37.2%

영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
113 
영업/정상
67 

Length

Max length5
Median length2
Mean length3.1166667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 113
62.8%
영업/정상 67
37.2%

Length

2024-04-30T04:18:23.224458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:23.318419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 113
62.8%
영업/정상 67
37.2%
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2
113 
1
67 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 113
62.8%
1 67
37.2%

Length

2024-04-30T04:18:23.417369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:23.503123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 113
62.8%
1 67
37.2%
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
113 
영업
67 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 113
62.8%
영업 67
37.2%

Length

2024-04-30T04:18:23.591968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:23.670398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 113
62.8%
영업 67
37.2%

폐업일자
Date

MISSING 

Distinct105
Distinct (%)92.9%
Missing67
Missing (%)37.2%
Memory size1.5 KiB
Minimum1995-07-10 00:00:00
Maximum2024-04-11 00:00:00
2024-04-30T04:18:23.764377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:23.878698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct175
Distinct (%)99.4%
Missing4
Missing (%)2.2%
Memory size1.5 KiB
2024-04-30T04:18:24.079221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.227273
Min length10

Characters and Unicode

Total characters1800
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

Unique174 ?
Unique (%)98.9%

Sample

1st row02 4504425
2nd row02 4648905
3rd row02 4635280
4th row02 457 0778
5th row02 4656604
ValueCountFrequency (%)
02 162
45.0%
456 4
 
1.1%
466 3
 
0.8%
4646273 2
 
0.6%
00 2
 
0.6%
020000 2
 
0.6%
4641381 1
 
0.3%
4633525 1
 
0.3%
4585256 1
 
0.3%
4547570 1
 
0.3%
Other values (181) 181
50.3%
2024-04-30T04:18:24.426326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 289
16.1%
4 278
15.4%
2 267
14.8%
208
11.6%
6 168
9.3%
5 128
7.1%
7 123
6.8%
3 110
 
6.1%
1 88
 
4.9%
9 74
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1592
88.4%
Space Separator 208
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 289
18.2%
4 278
17.5%
2 267
16.8%
6 168
10.6%
5 128
8.0%
7 123
7.7%
3 110
 
6.9%
1 88
 
5.5%
9 74
 
4.6%
8 67
 
4.2%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 289
16.1%
4 278
15.4%
2 267
14.8%
208
11.6%
6 168
9.3%
5 128
7.1%
7 123
6.8%
3 110
 
6.1%
1 88
 
4.9%
9 74
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 289
16.1%
4 278
15.4%
2 267
14.8%
208
11.6%
6 168
9.3%
5 128
7.1%
7 123
6.8%
3 110
 
6.1%
1 88
 
4.9%
9 74
 
4.1%
Distinct175
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:18:24.740891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.8166667
Min length3

Characters and Unicode

Total characters1047
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

Unique173 ?
Unique (%)96.1%

Sample

1st row35314.55
2nd row52.82
3rd row180.16
4th row194.94
5th row68.00
ValueCountFrequency (%)
00 5
 
2.8%
5,568.11 2
 
1.1%
4,325.11 1
 
0.6%
213.78 1
 
0.6%
134.40 1
 
0.6%
188.42 1
 
0.6%
35314.55 1
 
0.6%
219.29 1
 
0.6%
68.57 1
 
0.6%
170.97 1
 
0.6%
Other values (165) 165
91.7%
2024-04-30T04:18:25.162225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 180
17.2%
1 135
12.9%
0 112
10.7%
2 103
9.8%
4 85
8.1%
8 77
7.4%
5 74
7.1%
3 74
7.1%
9 68
 
6.5%
6 64
 
6.1%
Other values (2) 75
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 856
81.8%
Other Punctuation 191
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 135
15.8%
0 112
13.1%
2 103
12.0%
4 85
9.9%
8 77
9.0%
5 74
8.6%
3 74
8.6%
9 68
7.9%
6 64
7.5%
7 64
7.5%
Other Punctuation
ValueCountFrequency (%)
. 180
94.2%
, 11
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1047
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 180
17.2%
1 135
12.9%
0 112
10.7%
2 103
9.8%
4 85
8.1%
8 77
7.4%
5 74
7.1%
3 74
7.1%
9 68
 
6.5%
6 64
 
6.1%
Other values (2) 75
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 180
17.2%
1 135
12.9%
0 112
10.7%
2 103
9.8%
4 85
8.1%
8 77
7.4%
5 74
7.1%
3 74
7.1%
9 68
 
6.5%
6 64
 
6.1%
Other values (2) 75
7.2%
Distinct70
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:18:25.370562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0944444
Min length6

Characters and Unicode

Total characters1097
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

Unique40 ?
Unique (%)22.2%

Sample

1st row143-800
2nd row143915
3rd row143915
4th row143961
5th row143846
ValueCountFrequency (%)
143916 35
 
19.4%
143838 11
 
6.1%
143819 8
 
4.4%
143915 8
 
4.4%
143840 7
 
3.9%
143912 6
 
3.3%
143-916 5
 
2.8%
143190 4
 
2.2%
143903 4
 
2.2%
143890 4
 
2.2%
Other values (60) 88
48.9%
2024-04-30T04:18:25.690660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 274
25.0%
4 211
19.2%
3 203
18.5%
8 112
10.2%
9 111
10.1%
6 53
 
4.8%
0 50
 
4.6%
2 32
 
2.9%
5 25
 
2.3%
- 17
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1080
98.5%
Dash Punctuation 17
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 274
25.4%
4 211
19.5%
3 203
18.8%
8 112
10.4%
9 111
10.3%
6 53
 
4.9%
0 50
 
4.6%
2 32
 
3.0%
5 25
 
2.3%
7 9
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1097
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 274
25.0%
4 211
19.2%
3 203
18.5%
8 112
10.2%
9 111
10.1%
6 53
 
4.8%
0 50
 
4.6%
2 32
 
2.9%
5 25
 
2.3%
- 17
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 274
25.0%
4 211
19.2%
3 203
18.5%
8 112
10.2%
9 111
10.1%
6 53
 
4.8%
0 50
 
4.6%
2 32
 
2.9%
5 25
 
2.3%
- 17
 
1.5%
Distinct176
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:18:25.979484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length21.916667
Min length18

Characters and Unicode

Total characters3945
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)95.6%

Sample

1st row서울특별시 광진구 광장동 22-1
2nd row서울특별시 광진구 화양동 115-8번지
3rd row서울특별시 광진구 화양동 111-129번지
4th row서울특별시 광진구 구의동 228-7
5th row서울특별시 광진구 자양동 236-64번지
ValueCountFrequency (%)
서울특별시 180
24.3%
광진구 180
24.3%
화양동 53
 
7.2%
중곡동 40
 
5.4%
구의동 31
 
4.2%
자양동 25
 
3.4%
군자동 22
 
3.0%
광장동 6
 
0.8%
능동 3
 
0.4%
2,3층 3
 
0.4%
Other values (192) 198
26.7%
2024-04-30T04:18:26.427970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
708
17.9%
211
 
5.3%
186
 
4.7%
- 182
 
4.6%
180
 
4.6%
180
 
4.6%
180
 
4.6%
180
 
4.6%
180
 
4.6%
180
 
4.6%
Other values (41) 1578
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2246
56.9%
Decimal Number 797
 
20.2%
Space Separator 708
 
17.9%
Dash Punctuation 182
 
4.6%
Other Punctuation 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
211
9.4%
186
 
8.3%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
121
 
5.4%
Other values (28) 468
20.8%
Decimal Number
ValueCountFrequency (%)
1 163
20.5%
2 143
17.9%
3 99
12.4%
4 70
8.8%
5 65
 
8.2%
6 65
 
8.2%
7 60
 
7.5%
0 56
 
7.0%
9 41
 
5.1%
8 35
 
4.4%
Space Separator
ValueCountFrequency (%)
708
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2246
56.9%
Common 1699
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
211
9.4%
186
 
8.3%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
121
 
5.4%
Other values (28) 468
20.8%
Common
ValueCountFrequency (%)
708
41.7%
- 182
 
10.7%
1 163
 
9.6%
2 143
 
8.4%
3 99
 
5.8%
4 70
 
4.1%
5 65
 
3.8%
6 65
 
3.8%
7 60
 
3.5%
0 56
 
3.3%
Other values (3) 88
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2246
56.9%
ASCII 1699
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
708
41.7%
- 182
 
10.7%
1 163
 
9.6%
2 143
 
8.4%
3 99
 
5.8%
4 70
 
4.1%
5 65
 
3.8%
6 65
 
3.8%
7 60
 
3.5%
0 56
 
3.3%
Other values (3) 88
 
5.2%
Hangul
ValueCountFrequency (%)
211
9.4%
186
 
8.3%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
180
 
8.0%
121
 
5.4%
Other values (28) 468
20.8%

도로명주소
Text

MISSING 

Distinct134
Distinct (%)98.5%
Missing44
Missing (%)24.4%
Memory size1.5 KiB
2024-04-30T04:18:26.716996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length24.992647
Min length22

Characters and Unicode

Total characters3399
Distinct characters84
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

Unique132 ?
Unique (%)97.1%

Sample

1st row서울특별시 광진구 워커힐로 177 (광장동)
2nd row서울특별시 광진구 능동로19길 44 (화양동)
3rd row서울특별시 광진구 구의로16길 9 (구의동)
4th row서울특별시 광진구 뚝섬로 475-6 (자양동)
5th row서울특별시 광진구 답십리로82길 38 (중곡동)
ValueCountFrequency (%)
서울특별시 136
19.7%
광진구 136
19.7%
화양동 40
 
5.8%
중곡동 29
 
4.2%
동일로 25
 
3.6%
구의동 24
 
3.5%
자양동 18
 
2.6%
아차산로 13
 
1.9%
천호대로 11
 
1.6%
군자동 10
 
1.4%
Other values (173) 249
36.0%
2024-04-30T04:18:27.217453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
555
 
16.3%
187
 
5.5%
164
 
4.8%
159
 
4.7%
136
 
4.0%
) 136
 
4.0%
136
 
4.0%
136
 
4.0%
( 136
 
4.0%
136
 
4.0%
Other values (74) 1518
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2056
60.5%
Space Separator 555
 
16.3%
Decimal Number 469
 
13.8%
Close Punctuation 136
 
4.0%
Open Punctuation 136
 
4.0%
Other Punctuation 26
 
0.8%
Dash Punctuation 20
 
0.6%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
187
 
9.1%
164
 
8.0%
159
 
7.7%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
Other values (57) 594
28.9%
Decimal Number
ValueCountFrequency (%)
1 84
17.9%
3 65
13.9%
2 60
12.8%
4 51
10.9%
6 42
9.0%
5 41
8.7%
7 38
8.1%
0 31
 
6.6%
9 29
 
6.2%
8 28
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 25
96.2%
. 1
 
3.8%
Space Separator
ValueCountFrequency (%)
555
100.0%
Close Punctuation
ValueCountFrequency (%)
) 136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2056
60.5%
Common 1343
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
187
 
9.1%
164
 
8.0%
159
 
7.7%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
Other values (57) 594
28.9%
Common
ValueCountFrequency (%)
555
41.3%
) 136
 
10.1%
( 136
 
10.1%
1 84
 
6.3%
3 65
 
4.8%
2 60
 
4.5%
4 51
 
3.8%
6 42
 
3.1%
5 41
 
3.1%
7 38
 
2.8%
Other values (7) 135
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2056
60.5%
ASCII 1343
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
555
41.3%
) 136
 
10.1%
( 136
 
10.1%
1 84
 
6.3%
3 65
 
4.8%
2 60
 
4.5%
4 51
 
3.8%
6 42
 
3.1%
5 41
 
3.1%
7 38
 
2.8%
Other values (7) 135
 
10.1%
Hangul
ValueCountFrequency (%)
187
 
9.1%
164
 
8.0%
159
 
7.7%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
136
 
6.6%
Other values (57) 594
28.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)49.2%
Missing52
Missing (%)28.9%
Infinite0
Infinite (%)0.0%
Mean4995.1406
Minimum4900
Maximum5116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:27.362126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4900
5-th percentile4903
Q14960.75
median5007
Q35031.5
95-th percentile5080
Maximum5116
Range216
Interquartile range (IQR)70.75

Descriptive statistics

Standard deviation53.656935
Coefficient of variation (CV)0.010741827
Kurtosis-0.71910799
Mean4995.1406
Median Absolute Deviation (MAD)32
Skewness-0.16872264
Sum639378
Variance2879.0667
MonotonicityNot monotonic
2024-04-30T04:18:27.509120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5007 19
 
10.6%
5008 7
 
3.9%
5002 5
 
2.8%
4931 4
 
2.2%
4903 4
 
2.2%
5009 4
 
2.2%
4996 3
 
1.7%
4976 3
 
1.7%
5044 3
 
1.7%
5081 3
 
1.7%
Other values (53) 73
40.6%
(Missing) 52
28.9%
ValueCountFrequency (%)
4900 2
1.1%
4902 2
1.1%
4903 4
2.2%
4905 1
 
0.6%
4908 1
 
0.6%
4911 2
1.1%
4912 1
 
0.6%
4914 1
 
0.6%
4918 2
1.1%
4919 1
 
0.6%
ValueCountFrequency (%)
5116 1
 
0.6%
5093 1
 
0.6%
5092 1
 
0.6%
5081 3
1.7%
5080 3
1.7%
5073 2
1.1%
5072 1
 
0.6%
5071 2
1.1%
5068 1
 
0.6%
5065 1
 
0.6%
Distinct173
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:18:27.806241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length4.7777778
Min length1

Characters and Unicode

Total characters860
Distinct characters219
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)92.2%

Sample

1st row워커힐
2nd row대원장여관
3rd row뉴서울장여관
4th row올인
5th row동궁여관
ValueCountFrequency (%)
신흥여인숙 2
 
1.0%
몰디브 2
 
1.0%
올인 2
 
1.0%
건대 2
 
1.0%
서울장여관 2
 
1.0%
모텔 2
 
1.0%
호텔더디자이너스건대 2
 
1.0%
동궁여관 2
 
1.0%
정모텔 2
 
1.0%
에이삼일사(a314 1
 
0.5%
Other values (175) 175
90.2%
2024-04-30T04:18:28.210008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
8.6%
66
 
7.7%
65
 
7.6%
55
 
6.4%
42
 
4.9%
23
 
2.7%
17
 
2.0%
14
 
1.6%
13
 
1.5%
13
 
1.5%
Other values (209) 478
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 788
91.6%
Uppercase Letter 18
 
2.1%
Space Separator 14
 
1.6%
Lowercase Letter 13
 
1.5%
Decimal Number 9
 
1.0%
Open Punctuation 8
 
0.9%
Close Punctuation 8
 
0.9%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
74
 
9.4%
66
 
8.4%
65
 
8.2%
55
 
7.0%
42
 
5.3%
23
 
2.9%
17
 
2.2%
13
 
1.6%
13
 
1.6%
13
 
1.6%
Other values (175) 407
51.6%
Uppercase Letter
ValueCountFrequency (%)
H 3
16.7%
S 2
11.1%
A 2
11.1%
Y 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
W 1
 
5.6%
L 1
 
5.6%
Q 1
 
5.6%
P 1
 
5.6%
Other values (4) 4
22.2%
Lowercase Letter
ValueCountFrequency (%)
o 2
15.4%
e 2
15.4%
u 2
15.4%
n 2
15.4%
s 1
7.7%
a 1
7.7%
l 1
7.7%
t 1
7.7%
i 1
7.7%
Decimal Number
ValueCountFrequency (%)
2 2
22.2%
5 2
22.2%
0 2
22.2%
3 1
11.1%
4 1
11.1%
1 1
11.1%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 788
91.6%
Common 41
 
4.8%
Latin 31
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
74
 
9.4%
66
 
8.4%
65
 
8.2%
55
 
7.0%
42
 
5.3%
23
 
2.9%
17
 
2.2%
13
 
1.6%
13
 
1.6%
13
 
1.6%
Other values (175) 407
51.6%
Latin
ValueCountFrequency (%)
H 3
 
9.7%
o 2
 
6.5%
e 2
 
6.5%
u 2
 
6.5%
n 2
 
6.5%
S 2
 
6.5%
A 2
 
6.5%
Y 1
 
3.2%
T 1
 
3.2%
I 1
 
3.2%
Other values (13) 13
41.9%
Common
ValueCountFrequency (%)
14
34.1%
( 8
19.5%
) 8
19.5%
2 2
 
4.9%
5 2
 
4.9%
0 2
 
4.9%
3 1
 
2.4%
4 1
 
2.4%
1 1
 
2.4%
& 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 788
91.6%
ASCII 72
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
74
 
9.4%
66
 
8.4%
65
 
8.2%
55
 
7.0%
42
 
5.3%
23
 
2.9%
17
 
2.2%
13
 
1.6%
13
 
1.6%
13
 
1.6%
Other values (175) 407
51.6%
ASCII
ValueCountFrequency (%)
14
19.4%
( 8
 
11.1%
) 8
 
11.1%
H 3
 
4.2%
o 2
 
2.8%
e 2
 
2.8%
u 2
 
2.8%
n 2
 
2.8%
S 2
 
2.8%
A 2
 
2.8%
Other values (24) 27
37.5%
Distinct168
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2002-01-30 00:00:00
Maximum2024-04-11 10:46:18
2024-04-30T04:18:28.503515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:28.611560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
U
104 
I
76 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 104
57.8%
I 76
42.2%

Length

2024-04-30T04:18:28.727126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:28.822204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 104
57.8%
i 76
42.2%
Distinct91
Distinct (%)50.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:03:00
2024-04-30T04:18:28.945334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:29.153991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
여관업
154 
관광호텔
 
14
여인숙업
 
10
일반호텔
 
1
숙박업(생활)
 
1

Length

Max length7
Median length3
Mean length3.1611111
Min length3

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 154
85.6%
관광호텔 14
 
7.8%
여인숙업 10
 
5.6%
일반호텔 1
 
0.6%
숙박업(생활) 1
 
0.6%

Length

2024-04-30T04:18:29.327843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:29.471352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 154
85.6%
관광호텔 14
 
7.8%
여인숙업 10
 
5.6%
일반호텔 1
 
0.6%
숙박업(생활 1
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct165
Distinct (%)95.9%
Missing8
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean206813.04
Minimum205310.29
Maximum209775.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:29.617194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205310.29
5-th percentile205656.37
Q1206007.25
median206757.84
Q3207480.26
95-th percentile208176.23
Maximum209775.27
Range4464.9821
Interquartile range (IQR)1473.0083

Descriptive statistics

Standard deviation918.49152
Coefficient of variation (CV)0.0044411683
Kurtosis0.1845825
Mean206813.04
Median Absolute Deviation (MAD)744.55333
Skewness0.66743763
Sum35571843
Variance843626.67
MonotonicityNot monotonic
2024-04-30T04:18:29.761231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206038.869513525 2
 
1.1%
207889.562789686 2
 
1.1%
205540.082598602 2
 
1.1%
206698.893815455 2
 
1.1%
206715.163962974 2
 
1.1%
205880.867136 2
 
1.1%
206041.488817405 2
 
1.1%
207545.867307934 1
 
0.6%
206790.345939184 1
 
0.6%
207124.932077141 1
 
0.6%
Other values (155) 155
86.1%
(Missing) 8
 
4.4%
ValueCountFrequency (%)
205310.285709458 1
0.6%
205321.284730435 1
0.6%
205329.672408805 1
0.6%
205391.382375241 1
0.6%
205477.134659707 1
0.6%
205519.120649001 1
0.6%
205540.082598602 2
1.1%
205572.347699585 1
0.6%
205725.117770632 1
0.6%
205747.652768191 1
0.6%
ValueCountFrequency (%)
209775.267831522 1
0.6%
209602.113978282 1
0.6%
209407.745384399 1
0.6%
209375.068351656 1
0.6%
209162.470345601 1
0.6%
208413.473710547 1
0.6%
208263.69457561 1
0.6%
208261.748825555 1
0.6%
208197.480705123 1
0.6%
208158.850031488 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct165
Distinct (%)95.9%
Missing8
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean449692.52
Minimum447609.77
Maximum452094.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:29.874152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447609.77
5-th percentile448199.74
Q1449142.6
median449466.13
Q3450478.12
95-th percentile451809.58
Maximum452094.74
Range4484.9756
Interquartile range (IQR)1335.5175

Descriptive statistics

Standard deviation1047.9417
Coefficient of variation (CV)0.0023303516
Kurtosis-0.31675639
Mean449692.52
Median Absolute Deviation (MAD)796.41416
Skewness0.40632884
Sum77347114
Variance1098181.8
MonotonicityNot monotonic
2024-04-30T04:18:29.979199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449844.379971087 2
 
1.1%
449643.691169752 2
 
1.1%
448702.306849626 2
 
1.1%
450714.384110768 2
 
1.1%
450559.947859031 2
 
1.1%
449459.297399 2
 
1.1%
449522.62415745 2
 
1.1%
448350.983197315 1
 
0.6%
448383.572348438 1
 
0.6%
447721.059102855 1
 
0.6%
Other values (155) 155
86.1%
(Missing) 8
 
4.4%
ValueCountFrequency (%)
447609.765976299 1
0.6%
447721.059102855 1
0.6%
447746.321126737 1
0.6%
447806.088004584 1
0.6%
447913.032479407 1
0.6%
447944.009297941 1
0.6%
447952.966391874 1
0.6%
447994.805558304 1
0.6%
448183.850317743 1
0.6%
448212.742081082 1
0.6%
ValueCountFrequency (%)
452094.741574905 1
0.6%
452051.909676563 1
0.6%
452051.730320809 1
0.6%
452012.470712384 1
0.6%
451942.725870556 1
0.6%
451935.251493803 1
0.6%
451928.745163603 1
0.6%
451906.887051862 1
0.6%
451840.405435241 1
0.6%
451784.351747486 1
0.6%

위생업태명
Categorical

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
여관업
128 
<NA>
33 
여인숙업
 
10
관광호텔
 
8
일반호텔
 
1

Length

Max length4
Median length3
Mean length3.2888889
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 128
71.1%
<NA> 33
 
18.3%
여인숙업 10
 
5.6%
관광호텔 8
 
4.4%
일반호텔 1
 
0.6%

Length

2024-04-30T04:18:30.092669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:30.213904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 128
71.1%
na 33
 
18.3%
여인숙업 10
 
5.6%
관광호텔 8
 
4.4%
일반호텔 1
 
0.6%

건물지상층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
111 
<NA>
65 
9
 
1
17
 
1
10
 
1

Length

Max length4
Median length1
Mean length2.1
Min length1

Unique

Unique4 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 111
61.7%
<NA> 65
36.1%
9 1
 
0.6%
17 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%

Length

2024-04-30T04:18:30.336767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:30.441608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 111
61.7%
na 65
36.1%
9 1
 
0.6%
17 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%

건물지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
111 
<NA>
65 
1
 
2
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length2.0833333
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 111
61.7%
<NA> 65
36.1%
1 2
 
1.1%
3 1
 
0.6%
2 1
 
0.6%

Length

2024-04-30T04:18:30.598257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:30.702672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 111
61.7%
na 65
36.1%
1 2
 
1.1%
3 1
 
0.6%
2 1
 
0.6%
Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
102 
<NA>
66 
1
 
10
2
 
1
5
 
1

Length

Max length4
Median length1
Mean length2.1
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 102
56.7%
<NA> 66
36.7%
1 10
 
5.6%
2 1
 
0.6%
5 1
 
0.6%

Length

2024-04-30T04:18:30.809011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:30.920449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 102
56.7%
na 66
36.7%
1 10
 
5.6%
2 1
 
0.6%
5 1
 
0.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)12.3%
Missing99
Missing (%)55.0%
Infinite0
Infinite (%)0.0%
Mean1.2716049
Minimum0
Maximum20
Zeros69
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:31.009865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9370431
Coefficient of variation (CV)3.0961213
Kurtosis12.65018
Mean1.2716049
Median Absolute Deviation (MAD)0
Skewness3.5887922
Sum103
Variance15.500309
MonotonicityNot monotonic
2024-04-30T04:18:31.127130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 69
38.3%
3 4
 
2.2%
2 1
 
0.6%
4 1
 
0.6%
20 1
 
0.6%
17 1
 
0.6%
10 1
 
0.6%
18 1
 
0.6%
11 1
 
0.6%
9 1
 
0.6%
(Missing) 99
55.0%
ValueCountFrequency (%)
0 69
38.3%
2 1
 
0.6%
3 4
 
2.2%
4 1
 
0.6%
9 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%
17 1
 
0.6%
18 1
 
0.6%
20 1
 
0.6%
ValueCountFrequency (%)
20 1
 
0.6%
18 1
 
0.6%
17 1
 
0.6%
11 1
 
0.6%
10 1
 
0.6%
9 1
 
0.6%
4 1
 
0.6%
3 4
 
2.2%
2 1
 
0.6%
0 69
38.3%
Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
109 
<NA>
66 
1
 
4
3
 
1

Length

Max length4
Median length1
Mean length2.1
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 109
60.6%
<NA> 66
36.7%
1 4
 
2.2%
3 1
 
0.6%

Length

2024-04-30T04:18:31.273487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:31.364718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 109
60.6%
na 66
36.7%
1 4
 
2.2%
3 1
 
0.6%
Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
99 
0
76 
1
 
4
2
 
1

Length

Max length4
Median length4
Mean length2.65
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
55.0%
0 76
42.2%
1 4
 
2.2%
2 1
 
0.6%

Length

2024-04-30T04:18:31.462295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:31.574092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
55.0%
0 76
42.2%
1 4
 
2.2%
2 1
 
0.6%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)12.0%
Missing38
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean3.6760563
Minimum0
Maximum35
Zeros59
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:31.682890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q35
95-th percentile11
Maximum35
Range35
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.2734438
Coefficient of variation (CV)1.4345384
Kurtosis13.461709
Mean3.6760563
Median Absolute Deviation (MAD)2.5
Skewness3.0120716
Sum522
Variance27.80921
MonotonicityNot monotonic
2024-04-30T04:18:31.803504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 59
32.8%
4 16
 
8.9%
3 16
 
8.9%
2 10
 
5.6%
5 9
 
5.0%
10 8
 
4.4%
11 5
 
2.8%
6 4
 
2.2%
1 2
 
1.1%
13 2
 
1.1%
Other values (7) 11
 
6.1%
(Missing) 38
21.1%
ValueCountFrequency (%)
0 59
32.8%
1 2
 
1.1%
2 10
 
5.6%
3 16
 
8.9%
4 16
 
8.9%
5 9
 
5.0%
6 4
 
2.2%
7 2
 
1.1%
8 2
 
1.1%
9 2
 
1.1%
ValueCountFrequency (%)
35 1
 
0.6%
32 1
 
0.6%
19 1
 
0.6%
13 2
 
1.1%
12 2
 
1.1%
11 5
2.8%
10 8
4.4%
9 2
 
1.1%
8 2
 
1.1%
7 2
 
1.1%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)29.3%
Missing40
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean17.95
Minimum0
Maximum100
Zeros10
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-30T04:18:31.916744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median12
Q323
95-th percentile54.1
Maximum100
Range100
Interquartile range (IQR)15

Descriptive statistics

Standard deviation17.588553
Coefficient of variation (CV)0.97986367
Kurtosis7.3677324
Mean17.95
Median Absolute Deviation (MAD)5
Skewness2.5251403
Sum2513
Variance309.35719
MonotonicityNot monotonic
2024-04-30T04:18:32.036142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
10 16
 
8.9%
8 16
 
8.9%
12 10
 
5.6%
0 10
 
5.6%
14 8
 
4.4%
7 5
 
2.8%
9 5
 
2.8%
24 5
 
2.8%
16 4
 
2.2%
18 4
 
2.2%
Other values (31) 57
31.7%
(Missing) 40
22.2%
ValueCountFrequency (%)
0 10
5.6%
2 1
 
0.6%
3 1
 
0.6%
4 2
 
1.1%
5 2
 
1.1%
6 1
 
0.6%
7 5
 
2.8%
8 16
8.9%
9 5
 
2.8%
10 16
8.9%
ValueCountFrequency (%)
100 1
0.6%
86 1
0.6%
84 2
1.1%
75 2
1.1%
56 1
0.6%
54 1
0.6%
40 2
1.1%
39 2
1.1%
38 1
0.6%
37 1
0.6%

욕실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
115 
<NA>
65 

Length

Max length4
Median length1
Mean length2.0833333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 115
63.9%
<NA> 65
36.1%

Length

2024-04-30T04:18:32.169907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:32.269547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 115
63.9%
na 65
36.1%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.4%
Missing33
Missing (%)18.3%
Memory size492.0 B
False
114 
True
33 
(Missing)
33 
ValueCountFrequency (%)
False 114
63.3%
True 33
 
18.3%
(Missing) 33
 
18.3%
2024-04-30T04:18:32.353999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
114 
<NA>
65 
168
 
1

Length

Max length4
Median length1
Mean length2.0944444
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
63.3%
<NA> 65
36.1%
168 1
 
0.6%

Length

2024-04-30T04:18:32.464041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:32.578960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
63.3%
na 65
36.1%
168 1
 
0.6%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing180
Missing (%)100.0%
Memory size1.7 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
176 
자가
 
4

Length

Max length4
Median length4
Mean length3.9555556
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> 176
97.8%
자가 4
 
2.2%

Length

2024-04-30T04:18:32.707612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:32.811170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
97.8%
자가 4
 
2.2%

세탁기수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
98 
0
82 

Length

Max length4
Median length4
Mean length2.6333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 98
54.4%
0 82
45.6%

Length

2024-04-30T04:18:32.912332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:33.010874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
54.4%
0 82
45.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
172 
0
 
8

Length

Max length4
Median length4
Mean length3.8666667
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> 172
95.6%
0 8
 
4.4%

Length

2024-04-30T04:18:33.100773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:33.417085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 172
95.6%
0 8
 
4.4%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
172 
0
 
8

Length

Max length4
Median length4
Mean length3.8666667
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> 172
95.6%
0 8
 
4.4%

Length

2024-04-30T04:18:33.506770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:33.591267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 172
95.6%
0 8
 
4.4%

회수건조수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
98 
0
82 

Length

Max length4
Median length4
Mean length2.6333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 98
54.4%
0 82
45.6%

Length

2024-04-30T04:18:33.681616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:33.790007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
54.4%
0 82
45.6%

침대수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
98 
0
82 

Length

Max length4
Median length4
Mean length2.6333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 98
54.4%
0 82
45.6%

Length

2024-04-30T04:18:33.887164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:33.986859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
54.4%
0 82
45.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing33
Missing (%)18.3%
Memory size492.0 B
False
147 
(Missing)
33 
ValueCountFrequency (%)
False 147
81.7%
(Missing) 33
 
18.3%
2024-04-30T04:18:34.061374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030400003040000-201-1964-000011964-04-03<NA>1영업/정상1영업<NA><NA><NA><NA>02 450442535314.55143-800서울특별시 광진구 광장동 22-1서울특별시 광진구 워커힐로 177 (광장동)4963워커힐2023-05-04 10:11:44U2022-12-05 00:07:00.0관광호텔209775.267832450327.577093<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130400003040000-201-1968-0000119680801<NA>3폐업2폐업20171227<NA><NA><NA>02 464890552.82143915서울특별시 광진구 화양동 115-8번지서울특별시 광진구 능동로19길 44 (화양동)5009대원장여관2017-12-27 11:05:48I2018-08-31 23:59:59.0여관업206230.137613449477.471659여관업000000280N0<NA><NA><NA><NA>0<NA><NA>00N
230400003040000-201-1968-0000219681108<NA>3폐업2폐업20061020<NA><NA><NA>02 4635280180.16143915서울특별시 광진구 화양동 111-129번지<NA><NA>뉴서울장여관2002-02-04 00:00:00I2018-08-31 23:59:59.0여관업206409.225508449399.181857여관업000<NA>0<NA>1000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330400003040000-201-1969-0000119690709<NA>3폐업2폐업20210118<NA><NA><NA>02 457 0778194.94143961서울특별시 광진구 구의동 228-7서울특별시 광진구 구의로16길 9 (구의동)5033올인2021-01-18 09:31:58U2021-01-20 02:40:00.0여관업207976.829406449075.181117여관업0000000160Y0<NA><NA><NA><NA>0<NA><NA>00N
430400003040000-201-1969-0000219690625<NA>3폐업2폐업20191119<NA><NA><NA>02 465660468.00143846서울특별시 광진구 자양동 236-64번지서울특별시 광진구 뚝섬로 475-6 (자양동)5080동궁여관2019-11-19 14:50:41U2019-11-21 02:40:00.0여관업205519.120649448299.291013여관업000000380N0<NA><NA><NA><NA>0<NA><NA>00N
530400003040000-201-1969-0000319691206<NA>3폐업2폐업20180528<NA><NA><NA>02 4613040131.90143902서울특별시 광진구 중곡동 212-13번지서울특별시 광진구 답십리로82길 38 (중곡동)4902대림여관2018-05-28 09:12:47I2018-08-31 23:59:59.0여관업207208.850173451942.725871여관업0000004100N0<NA><NA><NA><NA>0<NA><NA>00N
630400003040000-201-1969-0000419691021<NA>3폐업2폐업20120217<NA><NA><NA>02 4977279108.28143916서울특별시 광진구 화양동 17-55번지<NA><NA>수도장여관2010-05-17 11:16:41I2018-08-31 23:59:59.0여관업206084.819279449348.522635여관업0000005120N0<NA><NA><NA><NA>0<NA><NA>00N
730400003040000-201-1970-0000719700702<NA>3폐업2폐업20080905<NA><NA><NA>02 469970750.00143902서울특별시 광진구 중곡동 196-11번지<NA><NA>도원여관2003-08-01 00:00:00I2018-08-31 23:59:59.0여관업207343.773689451935.251494여관업<NA><NA><NA><NA><NA><NA>38<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830400003040000-201-1970-0000819700825<NA>1영업/정상1영업<NA><NA><NA><NA>02 463198164.74143916서울특별시 광진구 화양동 23-39번지서울특별시 광진구 동일로 168 (화양동)5007큐(Q)2018-11-30 16:01:14U2018-12-04 02:40:00.0여관업205850.752898449421.557205여관업0000003140Y0<NA><NA><NA><NA>0<NA><NA>00N
930400003040000-201-1970-000091970-08-10<NA>1영업/정상1영업<NA><NA><NA><NA>02 463204389.00143-917서울특별시 광진구 화양동 41-3서울특별시 광진구 동일로 148 (화양동)5014그랜드모텔2023-10-04 15:31:47U2022-10-31 00:06:00.0여관업205776.113128449246.304001<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
17030400003040000-201-2016-0000120160617<NA>3폐업2폐업20190612<NA><NA><NA>02 466 78515,568.11143912서울특별시 광진구 중곡동 638-3번지서울특별시 광진구 천호대로 521 (중곡동)4920호텔더디자이너스건대2019-06-12 15:57:28U2019-06-14 02:40:00.0관광호텔206698.893815450714.384111관광호텔93<NA><NA><NA><NA>0750N0<NA><NA><NA>자가00000N
17130400003040000-201-2017-0000120170523<NA>1영업/정상1영업<NA><NA><NA><NA>02 456 12615,959.76143847서울특별시 광진구 능동 276-1 220-1, 220-3서울특별시 광진구 천호대로 560 (능동)4985호텔부티크나인2021-05-06 11:48:31U2021-05-08 02:40:00.0관광호텔207010.871584450476.132985관광호텔172117120860N0<NA><NA><NA>자가00000N
17230400003040000-201-2017-0000220170523<NA>1영업/정상1영업<NA><NA><NA><NA>02 49915851,998.15143840서울특별시 광진구 군자동 350-1 350-2, 350-3서울특별시 광진구 동일로 214 (군자동)5002호텔컬리넌 건대22022-03-08 15:16:23U2022-03-10 02:40:00.0관광호텔206049.041722449837.413487관광호텔101110110560N0<NA><NA><NA>자가00000N
17330400003040000-201-2018-000012018-01-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 499 86162950.75143-916서울특별시 광진구 화양동 24-15서울특별시 광진구 동일로 156 (화양동)5013에이치에비뉴 호텔 건대점2023-03-13 17:06:07U2022-12-02 23:05:00.0관광호텔205814.775584449312.470283<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17430400003040000-201-2018-0000220180206<NA>1영업/정상1영업<NA><NA><NA><NA>02 463 56784,325.11143916서울특별시 광진구 화양동 23-15번지서울특별시 광진구 동일로 172 (화양동)5007호텔더디자이너스 프리미어 건대2018-02-06 16:38:13I2018-08-31 23:59:59.0관광호텔205879.36567449454.63856관광호텔001181101000N0<NA><NA><NA><NA>00000N
17530400003040000-201-2018-0000320180621<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,484.97143842서울특별시 광진구 자양동 24-6 호텔케이월드서울특별시 광진구 동일로 90, 호텔케이월드 (자양동)5071호텔케이월드2021-08-12 14:02:19U2021-08-14 02:40:00.0관광호텔205540.082599448702.30685관광호텔111111110540N0<NA><NA><NA>자가00000N
17630400003040000-201-2019-0000120190612<NA>1영업/정상1영업<NA><NA><NA><NA>02 224632325,568.11143912서울특별시 광진구 중곡동 638-3번지 호텔 더디자이너스 건대서울특별시 광진구 천호대로 521, 호텔 더디자이너스 건대 지하3~지상9층 (중곡동)4920호텔더디자이너스건대2020-04-22 17:49:41U2020-04-24 02:40:00.0관광호텔206698.893815450714.384111관광호텔0019310750N0<NA><NA><NA><NA>00000N
17730400003040000-201-2023-000012023-01-31<NA>1영업/정상1영업<NA><NA><NA><NA>02 456 32712060.00143-808서울특별시 광진구 광장동 327-1서울특별시 광진구 아차산로76가길 12 (광장동)4969나무호텔2023-01-31 17:13:55I2022-12-02 00:02:00.0관광호텔209407.745384449459.252995<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17830400003040000-201-2024-000012024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 466 7843225.00143-916서울특별시 광진구 화양동 18-32서울특별시 광진구 광나루로 354 (화양동)5008호스텔 온기2024-01-19 13:37:31U2023-11-30 22:01:00.0관광호텔206041.488817449522.624157<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17930400003040000-214-2024-000012024-01-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1086.48143-916서울특별시 광진구 화양동 23-3서울특별시 광진구 동일로30길 10 (화양동)5007하일호스텔2024-01-22 13:50:27I2023-11-30 22:04:00.0숙박업(생활)205913.766726449481.459609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>