Overview

Dataset statistics

Number of variables47
Number of observations319
Missing cells3487
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory126.0 KiB
Average record size in memory404.4 B

Variable types

Categorical19
Text8
DateTime4
Unsupported7
Numeric7
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-17434/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
건물소유구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (55.2%)Imbalance
욕실수 is highly imbalanced (53.5%)Imbalance
좌석수 is highly imbalanced (51.8%)Imbalance
여성종사자수 is highly imbalanced (94.5%)Imbalance
남성종사자수 is highly imbalanced (94.5%)Imbalance
인허가취소일자 has 319 (100.0%) missing valuesMissing
폐업일자 has 62 (19.4%) missing valuesMissing
휴업시작일자 has 319 (100.0%) missing valuesMissing
휴업종료일자 has 319 (100.0%) missing valuesMissing
재개업일자 has 319 (100.0%) missing valuesMissing
전화번호 has 5 (1.6%) missing valuesMissing
도로명주소 has 175 (54.9%) missing valuesMissing
도로명우편번호 has 190 (59.6%) missing valuesMissing
좌표정보(X) has 58 (18.2%) missing valuesMissing
좌표정보(Y) has 58 (18.2%) missing valuesMissing
건물지상층수 has 62 (19.4%) missing valuesMissing
사용끝지상층 has 156 (48.9%) missing valuesMissing
한실수 has 53 (16.6%) missing valuesMissing
양실수 has 67 (21.0%) missing valuesMissing
발한실여부 has 25 (7.8%) missing valuesMissing
조건부허가신고사유 has 319 (100.0%) missing valuesMissing
조건부허가시작일자 has 319 (100.0%) missing valuesMissing
조건부허가종료일자 has 319 (100.0%) missing valuesMissing
건물소유구분명 has 318 (99.7%) missing valuesMissing
다중이용업소여부 has 25 (7.8%) 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 95 (29.8%) zerosZeros
한실수 has 78 (24.5%) zerosZeros
양실수 has 94 (29.5%) zerosZeros

Reproduction

Analysis started2024-04-06 13:06:39.457392
Analysis finished2024-04-06 13:06:40.395937
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3070000
319 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 319
100.0%

Length

2024-04-06T22:06:40.490408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:40.595459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 319
100.0%

관리번호
Text

UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T22:06:40.825477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7018
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

Unique319 ?
Unique (%)100.0%

Sample

1st row3070000-201-1960-00033
2nd row3070000-201-1960-00232
3rd row3070000-201-1960-00233
4th row3070000-201-1960-00234
5th row3070000-201-1961-00236
ValueCountFrequency (%)
3070000-201-1960-00033 1
 
0.3%
3070000-201-1982-00096 1
 
0.3%
3070000-201-1982-00051 1
 
0.3%
3070000-201-1982-00041 1
 
0.3%
3070000-201-1981-00195 1
 
0.3%
3070000-201-1981-00194 1
 
0.3%
3070000-201-1981-00193 1
 
0.3%
3070000-201-1981-00184 1
 
0.3%
3070000-201-1981-00153 1
 
0.3%
3070000-201-1981-00057 1
 
0.3%
Other values (309) 309
96.9%
2024-04-06T22:06:41.382047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2903
41.4%
- 957
 
13.6%
1 831
 
11.8%
2 567
 
8.1%
7 505
 
7.2%
3 429
 
6.1%
9 351
 
5.0%
6 175
 
2.5%
8 135
 
1.9%
5 83
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6061
86.4%
Dash Punctuation 957
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2903
47.9%
1 831
 
13.7%
2 567
 
9.4%
7 505
 
8.3%
3 429
 
7.1%
9 351
 
5.8%
6 175
 
2.9%
8 135
 
2.2%
5 83
 
1.4%
4 82
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 957
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7018
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2903
41.4%
- 957
 
13.6%
1 831
 
11.8%
2 567
 
8.1%
7 505
 
7.2%
3 429
 
6.1%
9 351
 
5.0%
6 175
 
2.5%
8 135
 
1.9%
5 83
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2903
41.4%
- 957
 
13.6%
1 831
 
11.8%
2 567
 
8.1%
7 505
 
7.2%
3 429
 
6.1%
9 351
 
5.0%
6 175
 
2.5%
8 135
 
1.9%
5 83
 
1.2%
Distinct302
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1960-12-21 00:00:00
Maximum2017-11-17 00:00:00
2024-04-06T22:06:41.685537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:06:41.978882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3
257 
1
62 

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 (%)
3 257
80.6%
1 62
 
19.4%

Length

2024-04-06T22:06:42.170778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:42.380311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 257
80.6%
1 62
 
19.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
257 
영업/정상
62 

Length

Max length5
Median length2
Mean length2.5830721
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 257
80.6%
영업/정상 62
 
19.4%

Length

2024-04-06T22:06:42.583909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:42.731478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 257
80.6%
영업/정상 62
 
19.4%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2
257 
1
62 

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 (%)
2 257
80.6%
1 62
 
19.4%

Length

2024-04-06T22:06:42.918262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:43.091132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 257
80.6%
1 62
 
19.4%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
257 
영업
62 

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 257
80.6%
영업 62
 
19.4%

Length

2024-04-06T22:06:43.278938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:43.466709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 257
80.6%
영업 62
 
19.4%

폐업일자
Date

MISSING 

Distinct199
Distinct (%)77.4%
Missing62
Missing (%)19.4%
Memory size2.6 KiB
Minimum1992-02-10 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T22:06:43.687908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:06:43.981021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct302
Distinct (%)96.2%
Missing5
Missing (%)1.6%
Memory size2.6 KiB
2024-04-06T22:06:44.453905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.095541
Min length2

Characters and Unicode

Total characters3170
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

Unique292 ?
Unique (%)93.0%

Sample

1st row0209233676
2nd row02 9268484
3rd row0209247009
4th row0209252569
5th row02 9222900
ValueCountFrequency (%)
02 204
37.9%
0209203360 4
 
0.7%
921 3
 
0.6%
929 3
 
0.6%
926 2
 
0.4%
925 2
 
0.4%
9126775 2
 
0.4%
9133652 2
 
0.4%
9139831 2
 
0.4%
9193377 2
 
0.4%
Other values (307) 312
58.0%
2024-04-06T22:06:45.543006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 586
18.5%
0 552
17.4%
9 430
13.6%
1 311
9.8%
248
7.8%
3 220
 
6.9%
8 172
 
5.4%
6 167
 
5.3%
4 167
 
5.3%
7 160
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2922
92.2%
Space Separator 248
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 586
20.1%
0 552
18.9%
9 430
14.7%
1 311
10.6%
3 220
 
7.5%
8 172
 
5.9%
6 167
 
5.7%
4 167
 
5.7%
7 160
 
5.5%
5 157
 
5.4%
Space Separator
ValueCountFrequency (%)
248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 586
18.5%
0 552
17.4%
9 430
13.6%
1 311
9.8%
248
7.8%
3 220
 
6.9%
8 172
 
5.4%
6 167
 
5.3%
4 167
 
5.3%
7 160
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 586
18.5%
0 552
17.4%
9 430
13.6%
1 311
9.8%
248
7.8%
3 220
 
6.9%
8 172
 
5.4%
6 167
 
5.3%
4 167
 
5.3%
7 160
 
5.0%
Distinct234
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T22:06:46.146070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.2257053
Min length3

Characters and Unicode

Total characters1667
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

Unique209 ?
Unique (%)65.5%

Sample

1st row57.06
2nd row120.00
3rd row118.62
4th row.00
5th row.00
ValueCountFrequency (%)
00 41
 
12.9%
42.00 10
 
3.1%
96.00 6
 
1.9%
92.00 4
 
1.3%
66.00 4
 
1.3%
144.00 3
 
0.9%
90.00 3
 
0.9%
190.00 3
 
0.9%
99.00 3
 
0.9%
60.00 3
 
0.9%
Other values (224) 239
74.9%
2024-04-06T22:06:46.912183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 428
25.7%
. 319
19.1%
4 121
 
7.3%
1 121
 
7.3%
5 108
 
6.5%
6 98
 
5.9%
2 95
 
5.7%
9 93
 
5.6%
7 93
 
5.6%
8 89
 
5.3%
Other values (2) 102
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1334
80.0%
Other Punctuation 333
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 428
32.1%
4 121
 
9.1%
1 121
 
9.1%
5 108
 
8.1%
6 98
 
7.3%
2 95
 
7.1%
9 93
 
7.0%
7 93
 
7.0%
8 89
 
6.7%
3 88
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 319
95.8%
, 14
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1667
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 428
25.7%
. 319
19.1%
4 121
 
7.3%
1 121
 
7.3%
5 108
 
6.5%
6 98
 
5.9%
2 95
 
5.7%
9 93
 
5.6%
7 93
 
5.6%
8 89
 
5.3%
Other values (2) 102
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1667
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 428
25.7%
. 319
19.1%
4 121
 
7.3%
1 121
 
7.3%
5 108
 
6.5%
6 98
 
5.9%
2 95
 
5.7%
9 93
 
5.6%
7 93
 
5.6%
8 89
 
5.3%
Other values (2) 102
 
6.1%
Distinct76
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T22:06:47.321543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0407524
Min length6

Characters and Unicode

Total characters1927
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

Unique21 ?
Unique (%)6.6%

Sample

1st row136813
2nd row136044
3rd row136036
4th row136036
5th row136051
ValueCountFrequency (%)
136873 36
 
11.3%
136802 19
 
6.0%
136864 16
 
5.0%
136874 16
 
5.0%
136865 13
 
4.1%
136800 12
 
3.8%
136054 11
 
3.4%
136819 11
 
3.4%
136051 9
 
2.8%
136845 9
 
2.8%
Other values (66) 167
52.4%
2024-04-06T22:06:48.003503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 410
21.3%
1 380
19.7%
6 371
19.3%
8 271
14.1%
0 141
 
7.3%
4 96
 
5.0%
5 96
 
5.0%
7 79
 
4.1%
2 45
 
2.3%
9 25
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1914
99.3%
Dash Punctuation 13
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 410
21.4%
1 380
19.9%
6 371
19.4%
8 271
14.2%
0 141
 
7.4%
4 96
 
5.0%
5 96
 
5.0%
7 79
 
4.1%
2 45
 
2.4%
9 25
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1927
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 410
21.3%
1 380
19.7%
6 371
19.3%
8 271
14.1%
0 141
 
7.3%
4 96
 
5.0%
5 96
 
5.0%
7 79
 
4.1%
2 45
 
2.3%
9 25
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 410
21.3%
1 380
19.7%
6 371
19.3%
8 271
14.1%
0 141
 
7.3%
4 96
 
5.0%
5 96
 
5.0%
7 79
 
4.1%
2 45
 
2.3%
9 25
 
1.3%
Distinct302
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T22:06:48.496212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length22.683386
Min length18

Characters and Unicode

Total characters7236
Distinct characters52
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

Unique286 ?
Unique (%)89.7%

Sample

1st row서울특별시 성북구 돈암동 13-0번지
2nd row서울특별시 성북구 삼선동4가 142-0번지
3rd row서울특별시 성북구 동소문동6가 80번지
4th row서울특별시 성북구 동소문동6가 141번지
5th row서울특별시 성북구 동선동1가 91-0번지
ValueCountFrequency (%)
서울특별시 319
24.9%
성북구 319
24.9%
하월곡동 72
 
5.6%
길음동 41
 
3.2%
정릉동 37
 
2.9%
종암동 37
 
2.9%
장위동 31
 
2.4%
석관동 23
 
1.8%
동선동4가 12
 
0.9%
동선동1가 11
 
0.9%
Other values (327) 377
29.5%
2024-04-06T22:06:49.177252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1254
17.3%
363
 
5.0%
322
 
4.4%
322
 
4.4%
319
 
4.4%
319
 
4.4%
319
 
4.4%
319
 
4.4%
319
 
4.4%
319
 
4.4%
Other values (42) 3061
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4218
58.3%
Decimal Number 1461
 
20.2%
Space Separator 1254
 
17.3%
Dash Punctuation 300
 
4.1%
Uppercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
363
 
8.6%
322
 
7.6%
322
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
270
 
6.4%
Other values (27) 1027
24.3%
Decimal Number
ValueCountFrequency (%)
1 266
18.2%
2 174
11.9%
3 171
11.7%
8 167
11.4%
4 139
9.5%
5 138
9.4%
0 136
9.3%
6 104
 
7.1%
9 86
 
5.9%
7 80
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
1254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4218
58.3%
Common 3016
41.7%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
363
 
8.6%
322
 
7.6%
322
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
270
 
6.4%
Other values (27) 1027
24.3%
Common
ValueCountFrequency (%)
1254
41.6%
- 300
 
9.9%
1 266
 
8.8%
2 174
 
5.8%
3 171
 
5.7%
8 167
 
5.5%
4 139
 
4.6%
5 138
 
4.6%
0 136
 
4.5%
6 104
 
3.4%
Other values (3) 167
 
5.5%
Latin
ValueCountFrequency (%)
R 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4218
58.3%
ASCII 3018
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1254
41.6%
- 300
 
9.9%
1 266
 
8.8%
2 174
 
5.8%
3 171
 
5.7%
8 167
 
5.5%
4 139
 
4.6%
5 138
 
4.6%
0 136
 
4.5%
6 104
 
3.4%
Other values (5) 169
 
5.6%
Hangul
ValueCountFrequency (%)
363
 
8.6%
322
 
7.6%
322
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
319
 
7.6%
270
 
6.4%
Other values (27) 1027
24.3%

도로명주소
Text

MISSING 

Distinct144
Distinct (%)100.0%
Missing175
Missing (%)54.9%
Memory size2.6 KiB
2024-04-06T22:06:49.657754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length26.034722
Min length22

Characters and Unicode

Total characters3749
Distinct characters79
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

Unique144 ?
Unique (%)100.0%

Sample

1st row서울특별시 성북구 아리랑로2길 18 (동선동4가)
2nd row서울특별시 성북구 동소문로28길 46 (동선동3가)
3rd row서울특별시 성북구 동소문로8길 23 (삼선동4가)
4th row서울특별시 성북구 동소문로42나길 26-22 (하월곡동)
5th row서울특별시 성북구 길음로5길 7 (길음동)
ValueCountFrequency (%)
서울특별시 144
19.9%
성북구 144
19.9%
장위동 21
 
2.9%
하월곡동 21
 
2.9%
종암동 16
 
2.2%
석관동 15
 
2.1%
정릉동 14
 
1.9%
길음동 13
 
1.8%
동선동1가 10
 
1.4%
동선동4가 8
 
1.1%
Other values (214) 316
43.8%
2024-04-06T22:06:50.388128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
578
 
15.4%
202
 
5.4%
144
 
3.8%
144
 
3.8%
144
 
3.8%
144
 
3.8%
144
 
3.8%
144
 
3.8%
144
 
3.8%
) 144
 
3.8%
Other values (69) 1817
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2270
60.5%
Space Separator 578
 
15.4%
Decimal Number 551
 
14.7%
Close Punctuation 144
 
3.8%
Open Punctuation 144
 
3.8%
Dash Punctuation 56
 
1.5%
Other Punctuation 4
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
202
 
8.9%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
Other values (52) 772
34.0%
Decimal Number
ValueCountFrequency (%)
1 110
20.0%
2 86
15.6%
3 76
13.8%
4 66
12.0%
8 42
 
7.6%
0 41
 
7.4%
5 39
 
7.1%
6 36
 
6.5%
7 31
 
5.6%
9 24
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
R 1
50.0%
Space Separator
ValueCountFrequency (%)
578
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2270
60.5%
Common 1477
39.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
202
 
8.9%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
Other values (52) 772
34.0%
Common
ValueCountFrequency (%)
578
39.1%
) 144
 
9.7%
( 144
 
9.7%
1 110
 
7.4%
2 86
 
5.8%
3 76
 
5.1%
4 66
 
4.5%
- 56
 
3.8%
8 42
 
2.8%
0 41
 
2.8%
Other values (5) 134
 
9.1%
Latin
ValueCountFrequency (%)
G 1
50.0%
R 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2270
60.5%
ASCII 1479
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
578
39.1%
) 144
 
9.7%
( 144
 
9.7%
1 110
 
7.4%
2 86
 
5.8%
3 76
 
5.1%
4 66
 
4.5%
- 56
 
3.8%
8 42
 
2.8%
0 41
 
2.8%
Other values (7) 136
 
9.2%
Hangul
ValueCountFrequency (%)
202
 
8.9%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
144
 
6.3%
Other values (52) 772
34.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)42.6%
Missing190
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean2785.938
Minimum2700
Maximum2873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:50.626488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2700
5-th percentile2712.8
Q12739
median2787
Q32829
95-th percentile2859
Maximum2873
Range173
Interquartile range (IQR)90

Descriptive statistics

Standard deviation48.207681
Coefficient of variation (CV)0.017303932
Kurtosis-1.216028
Mean2785.938
Median Absolute Deviation (MAD)48
Skewness0.028835362
Sum359386
Variance2323.9805
MonotonicityNot monotonic
2024-04-06T22:06:50.871480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2797 13
 
4.1%
2845 10
 
3.1%
2739 8
 
2.5%
2829 8
 
2.5%
2722 6
 
1.9%
2734 5
 
1.6%
2776 4
 
1.3%
2788 4
 
1.3%
2784 3
 
0.9%
2846 3
 
0.9%
Other values (45) 65
 
20.4%
(Missing) 190
59.6%
ValueCountFrequency (%)
2700 1
 
0.3%
2705 2
 
0.6%
2709 2
 
0.6%
2710 2
 
0.6%
2717 1
 
0.3%
2721 1
 
0.3%
2722 6
1.9%
2725 3
0.9%
2729 1
 
0.3%
2730 1
 
0.3%
ValueCountFrequency (%)
2873 1
 
0.3%
2872 1
 
0.3%
2861 1
 
0.3%
2860 3
0.9%
2859 2
0.6%
2857 1
 
0.3%
2856 1
 
0.3%
2852 1
 
0.3%
2851 1
 
0.3%
2849 2
0.6%
Distinct281
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T22:06:51.377062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length2
Mean length3.0721003
Min length1

Characters and Unicode

Total characters980
Distinct characters209
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)77.7%

Sample

1st row우리
2nd row동도
3rd row대흥여관
4th row다정여관
5th row세창
ValueCountFrequency (%)
호텔 7
 
2.1%
제일 4
 
1.2%
금성 3
 
0.9%
유성 3
 
0.9%
삼호 3
 
0.9%
황해 2
 
0.6%
인수 2
 
0.6%
삼일 2
 
0.6%
대도 2
 
0.6%
대화여관 2
 
0.6%
Other values (284) 310
91.2%
2024-04-06T22:06:52.099215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
7.3%
38
 
3.9%
35
 
3.6%
27
 
2.8%
27
 
2.8%
26
 
2.7%
24
 
2.4%
24
 
2.4%
23
 
2.3%
21
 
2.1%
Other values (199) 663
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 930
94.9%
Space Separator 21
 
2.1%
Uppercase Letter 16
 
1.6%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
72
 
7.7%
38
 
4.1%
35
 
3.8%
27
 
2.9%
27
 
2.9%
26
 
2.8%
24
 
2.6%
24
 
2.6%
23
 
2.5%
21
 
2.3%
Other values (180) 613
65.9%
Uppercase Letter
ValueCountFrequency (%)
H 2
12.5%
A 2
12.5%
L 2
12.5%
E 1
 
6.2%
D 1
 
6.2%
W 1
 
6.2%
T 1
 
6.2%
M 1
 
6.2%
I 1
 
6.2%
V 1
 
6.2%
Other values (3) 3
18.8%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 930
94.9%
Common 33
 
3.4%
Latin 17
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
72
 
7.7%
38
 
4.1%
35
 
3.8%
27
 
2.9%
27
 
2.9%
26
 
2.8%
24
 
2.6%
24
 
2.6%
23
 
2.5%
21
 
2.3%
Other values (180) 613
65.9%
Latin
ValueCountFrequency (%)
H 2
11.8%
A 2
11.8%
L 2
11.8%
E 1
 
5.9%
D 1
 
5.9%
W 1
 
5.9%
1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
I 1
 
5.9%
Other values (4) 4
23.5%
Common
ValueCountFrequency (%)
21
63.6%
) 5
 
15.2%
( 5
 
15.2%
- 1
 
3.0%
? 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 930
94.9%
ASCII 49
 
5.0%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
72
 
7.7%
38
 
4.1%
35
 
3.8%
27
 
2.9%
27
 
2.9%
26
 
2.8%
24
 
2.6%
24
 
2.6%
23
 
2.5%
21
 
2.3%
Other values (180) 613
65.9%
ASCII
ValueCountFrequency (%)
21
42.9%
) 5
 
10.2%
( 5
 
10.2%
H 2
 
4.1%
A 2
 
4.1%
L 2
 
4.1%
- 1
 
2.0%
E 1
 
2.0%
? 1
 
2.0%
D 1
 
2.0%
Other values (8) 8
 
16.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct197
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1999-04-06 00:00:00
Maximum2024-03-22 16:39:08
2024-04-06T22:06:52.338382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:06:52.570236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
225 
U
94 

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 225
70.5%
U 94
29.5%

Length

2024-04-06T22:06:52.756288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:52.922733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 225
70.5%
u 94
29.5%
Distinct75
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:02:00
2024-04-06T22:06:53.082978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:06:53.313347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
여관업
252 
여인숙업
57 
관광호텔
 
7
일반호텔
 
3

Length

Max length4
Median length3
Mean length3.2100313
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 252
79.0%
여인숙업 57
 
17.9%
관광호텔 7
 
2.2%
일반호텔 3
 
0.9%

Length

2024-04-06T22:06:53.619040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:53.815660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 252
79.0%
여인숙업 57
 
17.9%
관광호텔 7
 
2.2%
일반호텔 3
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct243
Distinct (%)93.1%
Missing58
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean202587.15
Minimum198545.88
Maximum205580.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:54.039448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198545.88
5-th percentile200423.81
Q1201556.94
median202469.38
Q3203226.07
95-th percentile205277.08
Maximum205580.5
Range7034.6287
Interquartile range (IQR)1669.129

Descriptive statistics

Standard deviation1434.5801
Coefficient of variation (CV)0.0070812988
Kurtosis-0.36910932
Mean202587.15
Median Absolute Deviation (MAD)888.08916
Skewness0.31508208
Sum52875246
Variance2058020.2
MonotonicityNot monotonic
2024-04-06T22:06:54.334139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201664.533763026 3
 
0.9%
203824.046001062 2
 
0.6%
202619.599812013 2
 
0.6%
202860.094604014 2
 
0.6%
202940.234717484 2
 
0.6%
201475.407860987 2
 
0.6%
202449.51357436 2
 
0.6%
200850.193896796 2
 
0.6%
201049.527780624 2
 
0.6%
202713.78210946 2
 
0.6%
Other values (233) 240
75.2%
(Missing) 58
 
18.2%
ValueCountFrequency (%)
198545.876020342 1
0.3%
199713.174970065 1
0.3%
199725.192897081 1
0.3%
199795.161046537 1
0.3%
199888.811127238 1
0.3%
199943.796399318 1
0.3%
199949.578425859 1
0.3%
200188.296858041 1
0.3%
200317.074938573 1
0.3%
200324.337465641 1
0.3%
ValueCountFrequency (%)
205580.504678403 1
0.3%
205462.41559282 1
0.3%
205453.787793222 1
0.3%
205443.816675596 1
0.3%
205392.264342531 1
0.3%
205391.360565606 1
0.3%
205388.728907184 1
0.3%
205356.615067705 1
0.3%
205345.825758709 1
0.3%
205317.200417025 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct243
Distinct (%)93.1%
Missing58
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean455615.03
Minimum453086.01
Maximum457768.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:54.599281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453086.01
5-th percentile453737.26
Q1455055.94
median455851.19
Q3456108.28
95-th percentile456998.41
Maximum457768.97
Range4682.9615
Interquartile range (IQR)1052.3372

Descriptive statistics

Standard deviation960.50886
Coefficient of variation (CV)0.0021081589
Kurtosis-0.08384236
Mean455615.03
Median Absolute Deviation (MAD)424.59127
Skewness-0.51919818
Sum1.1891552 × 108
Variance922577.26
MonotonicityNot monotonic
2024-04-06T22:06:54.879745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455507.600298456 3
 
0.9%
456861.088895287 2
 
0.6%
455854.94506667 2
 
0.6%
455693.708594241 2
 
0.6%
455473.109380906 2
 
0.6%
454112.328962911 2
 
0.6%
455873.836754946 2
 
0.6%
456070.122190143 2
 
0.6%
455639.497263287 2
 
0.6%
455543.570037508 2
 
0.6%
Other values (233) 240
75.2%
(Missing) 58
 
18.2%
ValueCountFrequency (%)
453086.005564526 1
0.3%
453173.250586524 1
0.3%
453235.275904384 1
0.3%
453242.288354045 1
0.3%
453300.747934045 1
0.3%
453337.054032254 1
0.3%
453461.587473314 1
0.3%
453464.491143664 1
0.3%
453638.905671274 1
0.3%
453656.359444246 1
0.3%
ValueCountFrequency (%)
457768.96703203 1
0.3%
457579.215218634 1
0.3%
457515.514536469 1
0.3%
457417.10593059 1
0.3%
457381.568868592 1
0.3%
457350.7682825 1
0.3%
457300.191322841 1
0.3%
457295.842907465 1
0.3%
457295.545092858 1
0.3%
457290.01844922 1
0.3%

위생업태명
Categorical

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
여관업
231 
여인숙업
57 
<NA>
25 
관광호텔
 
4
일반호텔
 
2

Length

Max length4
Median length3
Mean length3.2758621
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 231
72.4%
여인숙업 57
 
17.9%
<NA> 25
 
7.8%
관광호텔 4
 
1.3%
일반호텔 2
 
0.6%

Length

2024-04-06T22:06:55.132608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:55.337245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 231
72.4%
여인숙업 57
 
17.9%
na 25
 
7.8%
관광호텔 4
 
1.3%
일반호텔 2
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)4.3%
Missing62
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean1.7276265
Minimum0
Maximum10
Zeros95
Zeros (%)29.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:55.531341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8508168
Coefficient of variation (CV)1.0713061
Kurtosis3.3306518
Mean1.7276265
Median Absolute Deviation (MAD)1
Skewness1.488906
Sum444
Variance3.4255229
MonotonicityNot monotonic
2024-04-06T22:06:55.732218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 95
29.8%
3 58
18.2%
2 50
15.7%
1 29
 
9.1%
4 13
 
4.1%
8 5
 
1.6%
5 2
 
0.6%
7 2
 
0.6%
10 1
 
0.3%
6 1
 
0.3%
(Missing) 62
19.4%
ValueCountFrequency (%)
0 95
29.8%
1 29
 
9.1%
2 50
15.7%
3 58
18.2%
4 13
 
4.1%
5 2
 
0.6%
6 1
 
0.3%
7 2
 
0.6%
8 5
 
1.6%
9 1
 
0.3%
ValueCountFrequency (%)
10 1
 
0.3%
9 1
 
0.3%
8 5
 
1.6%
7 2
 
0.6%
6 1
 
0.3%
5 2
 
0.6%
4 13
 
4.1%
3 58
18.2%
2 50
15.7%
1 29
9.1%
Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
150 
<NA>
140 
1
27 
3
 
1
11
 
1

Length

Max length4
Median length1
Mean length2.3197492
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 150
47.0%
<NA> 140
43.9%
1 27
 
8.5%
3 1
 
0.3%
11 1
 
0.3%

Length

2024-04-06T22:06:55.952485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:56.174501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
47.0%
na 140
43.9%
1 27
 
8.5%
3 1
 
0.3%
11 1
 
0.3%
Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
1
101 
0
96 
<NA>
63 
2
47 
3
12 

Length

Max length4
Median length1
Mean length1.5924765
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 101
31.7%
0 96
30.1%
<NA> 63
19.7%
2 47
14.7%
3 12
 
3.8%

Length

2024-04-06T22:06:56.429438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:56.598592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 101
31.7%
0 96
30.1%
na 63
19.7%
2 47
14.7%
3 12
 
3.8%

사용끝지상층
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)6.1%
Missing156
Missing (%)48.9%
Infinite0
Infinite (%)0.0%
Mean2.5092025
Minimum0
Maximum9
Zeros3
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:56.747065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile5.9
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5688641
Coefficient of variation (CV)0.62524413
Kurtosis5.0856484
Mean2.5092025
Median Absolute Deviation (MAD)1
Skewness1.9685901
Sum409
Variance2.4613345
MonotonicityNot monotonic
2024-04-06T22:06:56.918827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 57
 
17.9%
3 50
 
15.7%
1 34
 
10.7%
4 8
 
2.5%
8 5
 
1.6%
0 3
 
0.9%
5 2
 
0.6%
7 2
 
0.6%
6 1
 
0.3%
9 1
 
0.3%
(Missing) 156
48.9%
ValueCountFrequency (%)
0 3
 
0.9%
1 34
10.7%
2 57
17.9%
3 50
15.7%
4 8
 
2.5%
5 2
 
0.6%
6 1
 
0.3%
7 2
 
0.6%
8 5
 
1.6%
9 1
 
0.3%
ValueCountFrequency (%)
9 1
 
0.3%
8 5
 
1.6%
7 2
 
0.6%
6 1
 
0.3%
5 2
 
0.6%
4 8
 
2.5%
3 50
15.7%
2 57
17.9%
1 34
10.7%
0 3
 
0.9%
Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
161 
<NA>
148 
1
 
10

Length

Max length4
Median length1
Mean length2.3918495
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 161
50.5%
<NA> 148
46.4%
1 10
 
3.1%

Length

2024-04-06T22:06:57.104025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:57.282771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 161
50.5%
na 148
46.4%
1 10
 
3.1%
Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
240 
0
68 
1
 
11

Length

Max length4
Median length4
Mean length3.2570533
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> 240
75.2%
0 68
 
21.3%
1 11
 
3.4%

Length

2024-04-06T22:06:57.480832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:57.637159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
75.2%
0 68
 
21.3%
1 11
 
3.4%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)7.5%
Missing53
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean4.6804511
Minimum0
Maximum20
Zeros78
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:57.816507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q38
95-th percentile13
Maximum20
Range20
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.7487191
Coefficient of variation (CV)1.0145858
Kurtosis-0.10267902
Mean4.6804511
Median Absolute Deviation (MAD)3
Skewness0.87303689
Sum1245
Variance22.550333
MonotonicityNot monotonic
2024-04-06T22:06:58.035901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 78
24.5%
2 25
 
7.8%
3 21
 
6.6%
1 15
 
4.7%
5 15
 
4.7%
6 15
 
4.7%
7 14
 
4.4%
10 13
 
4.1%
4 12
 
3.8%
8 11
 
3.4%
Other values (10) 47
14.7%
(Missing) 53
16.6%
ValueCountFrequency (%)
0 78
24.5%
1 15
 
4.7%
2 25
 
7.8%
3 21
 
6.6%
4 12
 
3.8%
5 15
 
4.7%
6 15
 
4.7%
7 14
 
4.4%
8 11
 
3.4%
9 9
 
2.8%
ValueCountFrequency (%)
20 1
 
0.3%
18 2
 
0.6%
17 2
 
0.6%
16 3
 
0.9%
15 1
 
0.3%
14 4
 
1.3%
13 8
2.5%
12 7
2.2%
11 10
3.1%
10 13
4.1%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)13.1%
Missing67
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean8.0992063
Minimum0
Maximum122
Zeros94
Zeros (%)29.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T22:06:58.265418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q311.25
95-th percentile28.9
Maximum122
Range122
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation11.918134
Coefficient of variation (CV)1.4715187
Kurtosis33.96483
Mean8.0992063
Median Absolute Deviation (MAD)6
Skewness4.4292345
Sum2041
Variance142.04191
MonotonicityNot monotonic
2024-04-06T22:06:58.437789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 94
29.5%
6 16
 
5.0%
10 16
 
5.0%
8 15
 
4.7%
3 13
 
4.1%
12 11
 
3.4%
14 11
 
3.4%
9 9
 
2.8%
11 7
 
2.2%
4 7
 
2.2%
Other values (23) 53
16.6%
(Missing) 67
21.0%
ValueCountFrequency (%)
0 94
29.5%
2 3
 
0.9%
3 13
 
4.1%
4 7
 
2.2%
5 5
 
1.6%
6 16
 
5.0%
7 4
 
1.3%
8 15
 
4.7%
9 9
 
2.8%
10 16
 
5.0%
ValueCountFrequency (%)
122 1
 
0.3%
48 2
0.6%
43 1
 
0.3%
42 3
0.9%
41 1
 
0.3%
38 1
 
0.3%
32 1
 
0.3%
31 2
0.6%
30 1
 
0.3%
28 1
 
0.3%

욕실수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
169 
<NA>
147 
17
 
1
50
 
1
32
 
1

Length

Max length4
Median length1
Mean length2.3918495
Min length1

Unique

Unique3 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
53.0%
<NA> 147
46.1%
17 1
 
0.3%
50 1
 
0.3%
32 1
 
0.3%

Length

2024-04-06T22:06:58.614858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:58.793376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
53.0%
na 147
46.1%
17 1
 
0.3%
50 1
 
0.3%
32 1
 
0.3%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.7%
Missing25
Missing (%)7.8%
Memory size770.0 B
True
236 
False
58 
(Missing)
25 
ValueCountFrequency (%)
True 236
74.0%
False 58
 
18.2%
(Missing) 25
 
7.8%
2024-04-06T22:06:58.963886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
169 
<NA>
145 
1
 
3
4
 
1
64
 
1

Length

Max length4
Median length1
Mean length2.3667712
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
53.0%
<NA> 145
45.5%
1 3
 
0.9%
4 1
 
0.3%
64 1
 
0.3%

Length

2024-04-06T22:06:59.150098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:06:59.352360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
53.0%
na 145
45.5%
1 3
 
0.9%
4 1
 
0.3%
64 1
 
0.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing319
Missing (%)100.0%
Memory size2.9 KiB

건물소유구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing318
Missing (%)99.7%
Memory size2.6 KiB
2024-04-06T22:06:59.502031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자가
ValueCountFrequency (%)
자가 1
100.0%
2024-04-06T22:07:00.327608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
240 
0
79 

Length

Max length4
Median length4
Mean length3.2570533
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> 240
75.2%
0 79
 
24.8%

Length

2024-04-06T22:07:00.508287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:07:00.651109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
75.2%
0 79
 
24.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
317 
0
 
2

Length

Max length4
Median length4
Mean length3.9811912
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> 317
99.4%
0 2
 
0.6%

Length

2024-04-06T22:07:00.844554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:07:01.018061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 317
99.4%
0 2
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
317 
0
 
2

Length

Max length4
Median length4
Mean length3.9811912
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> 317
99.4%
0 2
 
0.6%

Length

2024-04-06T22:07:01.177539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:07:01.328490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 317
99.4%
0 2
 
0.6%

회수건조수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
242 
0
77 

Length

Max length4
Median length4
Mean length3.2758621
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> 242
75.9%
0 77
 
24.1%

Length

2024-04-06T22:07:01.505375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:07:01.678071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 242
75.9%
0 77
 
24.1%

침대수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
242 
0
77 

Length

Max length4
Median length4
Mean length3.2758621
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> 242
75.9%
0 77
 
24.1%

Length

2024-04-06T22:07:01.868333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:07:02.042926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 242
75.9%
0 77
 
24.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing25
Missing (%)7.8%
Memory size770.0 B
False
294 
(Missing)
 
25
ValueCountFrequency (%)
False 294
92.2%
(Missing) 25
 
7.8%
2024-04-06T22:07:02.253850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030700003070000-201-1960-0003319601231<NA>3폐업2폐업19951113<NA><NA><NA>020923367657.06136813서울특별시 성북구 돈암동 13-0번지<NA><NA>우리2001-09-27 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>1100Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130700003070000-201-1960-0023219601228<NA>3폐업2폐업19940414<NA><NA><NA>02 9268484120.00136044서울특별시 성북구 삼선동4가 142-0번지<NA><NA>동도2001-09-27 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>1300Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230700003070000-201-1960-0023319601221<NA>3폐업2폐업20060918<NA><NA><NA>0209247009118.62136036서울특별시 성북구 동소문동6가 80번지<NA><NA>대흥여관2003-12-31 00:00:00I2018-08-31 23:59:59.0여관업201233.372939454558.157551여관업3<NA>12<NA><NA>210<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330700003070000-201-1960-0023419601228<NA>3폐업2폐업20011220<NA><NA><NA>0209252569.00136036서울특별시 성북구 동소문동6가 141번지<NA><NA>다정여관2002-02-06 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
430700003070000-201-1961-0023619610812<NA>3폐업2폐업19990402<NA><NA><NA>02 9222900.00136051서울특별시 성북구 동선동1가 91-0번지<NA><NA>세창1999-04-06 00:00:00I2018-08-31 23:59:59.0여관업201545.340113454475.241423여관업000<NA>0<NA>0200Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530700003070000-201-1963-0001519630705<NA>1영업/정상1영업<NA><NA><NA><NA>02 921 9939594.00136054서울특별시 성북구 동선동4가 101번지서울특별시 성북구 아리랑로2길 18 (동선동4가)2829엠(M)2019-01-07 09:32:57U2019-01-09 02:40:00.0여관업201466.696193454582.393839여관업3133110200Y0<NA><NA><NA><NA>0<NA><NA>00N
630700003070000-201-1963-0001719630809<NA>3폐업2폐업20220518<NA><NA><NA><NA>104.00136053서울특별시 성북구 동선동3가 41-1서울특별시 성북구 동소문로28길 46 (동선동3가)<NA>스톡홀름2022-05-17 16:35:26U2021-12-04 23:09:00.0여관업201784.444592454840.717989<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730700003070000-201-1964-0019819640618<NA>1영업/정상1영업<NA><NA><NA><NA>02 926 5656544.75136044서울특별시 성북구 삼선동4가 9-6서울특별시 성북구 동소문로8길 23 (삼선동4가)2861메이호텔2022-04-25 14:27:16U2021-12-03 22:07:00.0여관업200842.852192454067.720851<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830700003070000-201-1965-0001819650320<NA>3폐업2폐업19930910<NA><NA><NA>0209234689.00136081서울특별시 성북구 보문동1가 102-0번지<NA><NA>평화2001-09-27 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000<NA>0<NA>000Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930700003070000-201-1965-0002119650201<NA>3폐업2폐업20051012<NA><NA><NA>02 988406544.06136800서울특별시 성북구 길음동 32-6번지<NA><NA>선일2003-02-26 00:00:00I2018-08-31 23:59:59.0여관업202527.168193456589.216239여관업2<NA>12<NA><NA>62<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
30930700003070000-201-2002-0001620021227<NA>1영업/정상1영업<NA><NA><NA><NA>02 960196885.75136819서울특별시 성북구 석관동 332-575번지서울특별시 성북구 돌곶이로9길 1-4 (석관동)2788초원2019-01-07 17:00:37U2019-01-09 02:40:00.0여인숙업205298.96037456051.429265여인숙업101100250N0<NA><NA><NA><NA>0<NA><NA>00N
31030700003070000-201-2003-0000120030108<NA>1영업/정상1영업<NA><NA><NA><NA>02 914361466.00136845서울특별시 성북구 정릉동 416-10서울특별시 성북구 보국문로 7-6 (정릉동)2710삼미장2021-01-28 14:37:18U2021-01-30 02:40:00.0여관업200915.111099455885.729398여관업302300280N0<NA><NA><NA><NA>0<NA><NA>00N
31130700003070000-201-2003-0000220030414<NA>3폐업2폐업20210608<NA><NA><NA>02 92135331,523.13136044서울특별시 성북구 삼선동4가 351-1 ,2서울특별시 성북구 보문로 184 (삼선동4가,,2)2847호텔파라오2021-06-08 15:29:09U2021-06-10 02:40:00.0여관업201255.685388454248.230353여관업7127000430N0<NA><NA><NA><NA>0<NA><NA>00N
31230700003070000-201-2003-0000320031125<NA>1영업/정상1영업<NA><NA><NA><NA>02 92791911,478.16136035서울특별시 성북구 동소문동5가 59-4번지서울특별시 성북구 동소문로18길 24-20 (동소문동5가)2846호텔 월드스테이2020-01-22 14:58:31U2020-01-24 02:40:00.0여관업201314.102389454353.398686여관업8138000480N0<NA><NA><NA><NA>0<NA><NA>00N
31330700003070000-201-2004-0000120040130<NA>1영업/정상1영업<NA><NA><NA><NA>02 92120801,479.65136051서울특별시 성북구 동선동1가 92-20번지서울특별시 성북구 동소문로20나길 39 (동선동1가)2845D?H 네상스2019-06-18 10:43:42U2019-06-20 02:40:00.0관광호텔201563.230549454500.673992관광호텔8138000300N0<NA><NA><NA><NA>0<NA><NA>00N
31430700003070000-201-2005-0000120051121<NA>1영업/정상1영업<NA><NA><NA><NA>02 9289393673.30136051서울특별시 성북구 동선동1가 2-10번지서울특별시 성북구 동소문로20나길 5 (동선동1가)2845파브모텔2019-01-09 11:31:12U2019-01-11 02:40:00.0여관업201427.611335454413.978458여관업7117002200N0<NA><NA><NA>자가0<NA><NA>00N
31530700003070000-201-2015-0000120150903<NA>1영업/정상1영업<NA><NA><NA><NA>02 925 70009,551.17136054서울특별시 성북구 동선동4가 26서울특별시 성북구 아리랑로 8 (동선동4가)2829베스트웨스턴 아리랑힐 동대문 호텔2022-05-25 14:43:28U2021-12-04 22:08:00.0관광호텔201393.678553454585.851177<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31630700003070000-201-2015-0000220151021<NA>3폐업2폐업20220518<NA><NA><NA>02 926 88834,209.22136074서울특별시 성북구 안암동4가 48서울특별시 성북구 안암로 25 (안암동4가)2857리첸카운티2022-05-17 16:36:44U2021-12-04 23:09:00.0일반호텔202157.393393453086.005565<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31730700003070000-201-2017-000012017-11-06<NA>1영업/정상1영업<NA><NA><NA><NA>02 929 96302154.27136-051서울특별시 성북구 동선동1가 120-1서울특별시 성북구 동소문로 130 (동선동1가)2845에이치에비뉴호텔 성신여대점2023-12-29 14:21:01U2022-11-01 21:01:00.0관광호텔201618.705033454656.759126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31830700003070000-201-2017-0000220171117<NA>1영업/정상1영업<NA><NA><NA><NA>02 921 99012,107.30136051서울특별시 성북구 동선동1가 120-12번지서울특별시 성북구 동소문로 126 (동선동1가)2845호텔 디 아티스트 성신여대점2018-10-19 15:43:27U2018-10-21 02:36:21.0관광호텔201587.018199454621.644167관광호텔21100000480N0<NA><NA><NA><NA>00000N