Overview

Dataset statistics

Number of variables47
Number of observations519
Missing cells6455
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory204.9 KiB
Average record size in memory404.3 B

Variable types

Categorical16
Text7
DateTime4
Unsupported7
Numeric11
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-17427/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
건물소유구분명 is highly imbalanced (72.2%)Imbalance
여성종사자수 is highly imbalanced (83.3%)Imbalance
남성종사자수 is highly imbalanced (82.9%)Imbalance
다중이용업소여부 is highly imbalanced (95.3%)Imbalance
인허가취소일자 has 519 (100.0%) missing valuesMissing
폐업일자 has 235 (45.3%) missing valuesMissing
휴업시작일자 has 519 (100.0%) missing valuesMissing
휴업종료일자 has 519 (100.0%) missing valuesMissing
재개업일자 has 519 (100.0%) missing valuesMissing
전화번호 has 52 (10.0%) missing valuesMissing
도로명주소 has 203 (39.1%) missing valuesMissing
도로명우편번호 has 210 (40.5%) missing valuesMissing
좌표정보(X) has 43 (8.3%) missing valuesMissing
좌표정보(Y) has 43 (8.3%) missing valuesMissing
건물지상층수 has 230 (44.3%) missing valuesMissing
건물지하층수 has 253 (48.7%) missing valuesMissing
사용시작지상층 has 229 (44.1%) missing valuesMissing
사용끝지상층 has 253 (48.7%) missing valuesMissing
한실수 has 153 (29.5%) missing valuesMissing
양실수 has 214 (41.2%) missing valuesMissing
욕실수 has 169 (32.6%) missing valuesMissing
발한실여부 has 138 (26.6%) missing valuesMissing
좌석수 has 249 (48.0%) missing valuesMissing
조건부허가신고사유 has 519 (100.0%) missing valuesMissing
조건부허가시작일자 has 519 (100.0%) missing valuesMissing
조건부허가종료일자 has 519 (100.0%) missing valuesMissing
다중이용업소여부 has 138 (26.6%) 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 212 (40.8%) zerosZeros
건물지하층수 has 231 (44.5%) zerosZeros
사용시작지상층 has 186 (35.8%) zerosZeros
사용끝지상층 has 23 (4.4%) zerosZeros
한실수 has 75 (14.5%) zerosZeros
양실수 has 127 (24.5%) zerosZeros
욕실수 has 88 (17.0%) zerosZeros
좌석수 has 230 (44.3%) zerosZeros

Reproduction

Analysis started2024-04-29 19:18:04.697062
Analysis finished2024-04-29 19:18:05.718384
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3000000
519 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 519
100.0%

Length

2024-04-30T04:18:05.779353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:05.879538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 519
100.0%

관리번호
Text

UNIQUE 

Distinct519
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-04-30T04:18:06.044276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters11418
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

Unique519 ?
Unique (%)100.0%

Sample

1st row3000000-201-1960-00148
2nd row3000000-201-1960-00266
3rd row3000000-201-1960-00287
4th row3000000-201-1961-00259
5th row3000000-201-1963-00210
ValueCountFrequency (%)
3000000-201-1960-00148 1
 
0.2%
3000000-201-2002-00010 1
 
0.2%
3000000-201-1993-00223 1
 
0.2%
3000000-201-1993-00221 1
 
0.2%
3000000-201-1993-00213 1
 
0.2%
3000000-201-1993-00204 1
 
0.2%
3000000-201-1993-00203 1
 
0.2%
3000000-201-1993-00202 1
 
0.2%
3000000-201-1993-00194 1
 
0.2%
3000000-201-1993-00189 1
 
0.2%
Other values (509) 509
98.1%
2024-04-30T04:18:06.305882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5331
46.7%
- 1557
 
13.6%
1 1217
 
10.7%
2 958
 
8.4%
3 777
 
6.8%
9 527
 
4.6%
8 324
 
2.8%
7 227
 
2.0%
6 199
 
1.7%
4 161
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9861
86.4%
Dash Punctuation 1557
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5331
54.1%
1 1217
 
12.3%
2 958
 
9.7%
3 777
 
7.9%
9 527
 
5.3%
8 324
 
3.3%
7 227
 
2.3%
6 199
 
2.0%
4 161
 
1.6%
5 140
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1557
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11418
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5331
46.7%
- 1557
 
13.6%
1 1217
 
10.7%
2 958
 
8.4%
3 777
 
6.8%
9 527
 
4.6%
8 324
 
2.8%
7 227
 
2.0%
6 199
 
1.7%
4 161
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11418
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5331
46.7%
- 1557
 
13.6%
1 1217
 
10.7%
2 958
 
8.4%
3 777
 
6.8%
9 527
 
4.6%
8 324
 
2.8%
7 227
 
2.0%
6 199
 
1.7%
4 161
 
1.4%
Distinct468
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1960-12-19 00:00:00
Maximum2024-03-25 00:00:00
2024-04-30T04:18:06.424735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:06.552436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3
284 
1
235 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 284
54.7%
1 235
45.3%

Length

2024-04-30T04:18:06.674088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:06.746615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 284
54.7%
1 235
45.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
폐업
284 
영업/정상
235 

Length

Max length5
Median length2
Mean length3.3583815
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 284
54.7%
영업/정상 235
45.3%

Length

2024-04-30T04:18:06.839744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:06.922638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 284
54.7%
영업/정상 235
45.3%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2
284 
1
235 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 284
54.7%
1 235
45.3%

Length

2024-04-30T04:18:07.007004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:07.098502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 284
54.7%
1 235
45.3%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
폐업
284 
영업
235 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 284
54.7%
영업 235
45.3%

Length

2024-04-30T04:18:07.174907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:07.247582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 284
54.7%
영업 235
45.3%

폐업일자
Date

MISSING 

Distinct242
Distinct (%)85.2%
Missing235
Missing (%)45.3%
Memory size4.2 KiB
Minimum1989-07-31 00:00:00
Maximum2024-03-04 00:00:00
2024-04-30T04:18:07.342846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:07.466099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

전화번호
Text

MISSING 

Distinct391
Distinct (%)83.7%
Missing52
Missing (%)10.0%
Memory size4.2 KiB
2024-04-30T04:18:07.694873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.036403
Min length2

Characters and Unicode

Total characters4687
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

Unique378 ?
Unique (%)80.9%

Sample

1st row0207635635
2nd row02 7645537
3rd row0200000000
4th row02 7640550
5th row0264595113
ValueCountFrequency (%)
02 341
40.4%
0200000000 26
 
3.1%
00000 25
 
3.0%
0 15
 
1.8%
070 7
 
0.8%
742 5
 
0.6%
744 4
 
0.5%
765 4
 
0.5%
722 3
 
0.4%
7662121 3
 
0.4%
Other values (401) 411
48.7%
2024-04-30T04:18:08.045282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1059
22.6%
2 843
18.0%
500
10.7%
7 497
10.6%
3 365
 
7.8%
6 339
 
7.2%
4 262
 
5.6%
5 256
 
5.5%
1 217
 
4.6%
8 188
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4187
89.3%
Space Separator 500
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1059
25.3%
2 843
20.1%
7 497
11.9%
3 365
 
8.7%
6 339
 
8.1%
4 262
 
6.3%
5 256
 
6.1%
1 217
 
5.2%
8 188
 
4.5%
9 161
 
3.8%
Space Separator
ValueCountFrequency (%)
500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4687
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1059
22.6%
2 843
18.0%
500
10.7%
7 497
10.6%
3 365
 
7.8%
6 339
 
7.2%
4 262
 
5.6%
5 256
 
5.5%
1 217
 
4.6%
8 188
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1059
22.6%
2 843
18.0%
500
10.7%
7 497
10.6%
3 365
 
7.8%
6 339
 
7.2%
4 262
 
5.6%
5 256
 
5.5%
1 217
 
4.6%
8 188
 
4.0%
Distinct488
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-04-30T04:18:08.335980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.9576108
Min length3

Characters and Unicode

Total characters3092
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

Unique473 ?
Unique (%)91.1%

Sample

1st row99.17
2nd row91.17
3rd row64.93
4th row89.19
5th row82.64
ValueCountFrequency (%)
00 16
 
3.1%
42.98 3
 
0.6%
259.27 3
 
0.6%
170.18 2
 
0.4%
436.00 2
 
0.4%
653.16 2
 
0.4%
200.00 2
 
0.4%
234.71 2
 
0.4%
721.71 2
 
0.4%
260.56 2
 
0.4%
Other values (478) 483
93.1%
2024-04-30T04:18:08.733247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 519
16.8%
0 313
10.1%
1 305
9.9%
2 286
9.2%
4 265
8.6%
3 256
8.3%
5 246
8.0%
8 224
7.2%
7 216
7.0%
6 211
6.8%
Other values (2) 251
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2520
81.5%
Other Punctuation 572
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 313
12.4%
1 305
12.1%
2 286
11.3%
4 265
10.5%
3 256
10.2%
5 246
9.8%
8 224
8.9%
7 216
8.6%
6 211
8.4%
9 198
7.9%
Other Punctuation
ValueCountFrequency (%)
. 519
90.7%
, 53
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3092
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 519
16.8%
0 313
10.1%
1 305
9.9%
2 286
9.2%
4 265
8.6%
3 256
8.3%
5 246
8.0%
8 224
7.2%
7 216
7.0%
6 211
6.8%
Other values (2) 251
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 519
16.8%
0 313
10.1%
1 305
9.9%
2 286
9.2%
4 265
8.6%
3 256
8.3%
5 246
8.0%
8 224
7.2%
7 216
7.0%
6 211
6.8%
Other values (2) 251
8.1%
Distinct106
Distinct (%)20.6%
Missing5
Missing (%)1.0%
Memory size4.2 KiB
2024-04-30T04:18:08.907732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2159533
Min length6

Characters and Unicode

Total characters3195
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

Unique32 ?
Unique (%)6.2%

Sample

1st row110840
2nd row120-855
3rd row110290
4th row110126
5th row110540
ValueCountFrequency (%)
110320 47
 
9.1%
110842 29
 
5.6%
110130 22
 
4.3%
110420 18
 
3.5%
110813 18
 
3.5%
110340 18
 
3.5%
110826 16
 
3.1%
110-111 16
 
3.1%
110-320 15
 
2.9%
110841 15
 
2.9%
Other values (96) 300
58.4%
2024-04-30T04:18:09.204687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1212
37.9%
0 828
25.9%
2 237
 
7.4%
8 225
 
7.0%
3 178
 
5.6%
4 174
 
5.4%
- 111
 
3.5%
5 85
 
2.7%
6 69
 
2.2%
7 44
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3084
96.5%
Dash Punctuation 111
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1212
39.3%
0 828
26.8%
2 237
 
7.7%
8 225
 
7.3%
3 178
 
5.8%
4 174
 
5.6%
5 85
 
2.8%
6 69
 
2.2%
7 44
 
1.4%
9 32
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1212
37.9%
0 828
25.9%
2 237
 
7.4%
8 225
 
7.0%
3 178
 
5.6%
4 174
 
5.4%
- 111
 
3.5%
5 85
 
2.7%
6 69
 
2.2%
7 44
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1212
37.9%
0 828
25.9%
2 237
 
7.4%
8 225
 
7.0%
3 178
 
5.6%
4 174
 
5.4%
- 111
 
3.5%
5 85
 
2.7%
6 69
 
2.2%
7 44
 
1.4%
Distinct505
Distinct (%)98.2%
Missing5
Missing (%)1.0%
Memory size4.2 KiB
2024-04-30T04:18:09.499722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length20.900778
Min length16

Characters and Unicode

Total characters10743
Distinct characters164
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)96.5%

Sample

1st row서울특별시 종로구 창신동 148-1번지
2nd row서울특별시 종로구 창신동 687-20
3rd row서울특별시 종로구 인사동 153-2번지
4th row서울특별시 종로구 종로6가 112-0번지
5th row서울특별시 종로구 창신동 581-8번지
ValueCountFrequency (%)
서울특별시 514
24.4%
종로구 514
24.4%
숭인동 71
 
3.4%
창신동 68
 
3.2%
낙원동 62
 
2.9%
관철동 28
 
1.3%
관수동 22
 
1.0%
익선동 22
 
1.0%
청진동 22
 
1.0%
무악동 21
 
1.0%
Other values (563) 766
36.3%
2024-04-30T04:18:09.906707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1975
18.4%
543
 
5.1%
542
 
5.0%
519
 
4.8%
516
 
4.8%
516
 
4.8%
515
 
4.8%
514
 
4.8%
514
 
4.8%
480
 
4.5%
Other values (154) 4109
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6504
60.5%
Space Separator 1975
 
18.4%
Decimal Number 1879
 
17.5%
Dash Punctuation 345
 
3.2%
Uppercase Letter 13
 
0.1%
Lowercase Letter 9
 
0.1%
Other Punctuation 8
 
0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
543
 
8.3%
542
 
8.3%
519
 
8.0%
516
 
7.9%
516
 
7.9%
515
 
7.9%
514
 
7.9%
514
 
7.9%
480
 
7.4%
347
 
5.3%
Other values (120) 1498
23.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
15.4%
L 2
15.4%
Y 1
7.7%
E 1
7.7%
T 1
7.7%
G 1
7.7%
U 1
7.7%
C 1
7.7%
K 1
7.7%
H 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 436
23.2%
2 260
13.8%
4 211
11.2%
3 189
10.1%
5 165
 
8.8%
6 149
 
7.9%
0 146
 
7.8%
9 115
 
6.1%
8 106
 
5.6%
7 102
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
l 2
22.2%
g 1
11.1%
u 1
11.1%
h 1
11.1%
o 1
11.1%
t 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
& 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1975
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 345
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6504
60.5%
Common 4217
39.3%
Latin 22
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
543
 
8.3%
542
 
8.3%
519
 
8.0%
516
 
7.9%
516
 
7.9%
515
 
7.9%
514
 
7.9%
514
 
7.9%
480
 
7.4%
347
 
5.3%
Other values (120) 1498
23.0%
Latin
ValueCountFrequency (%)
e 2
 
9.1%
M 2
 
9.1%
L 2
 
9.1%
l 2
 
9.1%
Y 1
 
4.5%
E 1
 
4.5%
T 1
 
4.5%
G 1
 
4.5%
g 1
 
4.5%
u 1
 
4.5%
Other values (8) 8
36.4%
Common
ValueCountFrequency (%)
1975
46.8%
1 436
 
10.3%
- 345
 
8.2%
2 260
 
6.2%
4 211
 
5.0%
3 189
 
4.5%
5 165
 
3.9%
6 149
 
3.5%
0 146
 
3.5%
9 115
 
2.7%
Other values (6) 226
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6504
60.5%
ASCII 4239
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1975
46.6%
1 436
 
10.3%
- 345
 
8.1%
2 260
 
6.1%
4 211
 
5.0%
3 189
 
4.5%
5 165
 
3.9%
6 149
 
3.5%
0 146
 
3.4%
9 115
 
2.7%
Other values (24) 248
 
5.9%
Hangul
ValueCountFrequency (%)
543
 
8.3%
542
 
8.3%
519
 
8.0%
516
 
7.9%
516
 
7.9%
515
 
7.9%
514
 
7.9%
514
 
7.9%
480
 
7.4%
347
 
5.3%
Other values (120) 1498
23.0%

도로명주소
Text

MISSING 

Distinct303
Distinct (%)95.9%
Missing203
Missing (%)39.1%
Memory size4.2 KiB
2024-04-30T04:18:10.188978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length41
Mean length26.579114
Min length22

Characters and Unicode

Total characters8399
Distinct characters180
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)92.1%

Sample

1st row서울특별시 종로구 창신길 9-8 (창신동)
2nd row서울특별시 종로구 창신길 28-7 (창신동)
3rd row서울특별시 종로구 보문로7길 5-1 (숭인동)
4th row서울특별시 종로구 수표로 89-8 (관수동)
5th row서울특별시 종로구 창신1길 6 (창신동)
ValueCountFrequency (%)
서울특별시 316
 
19.1%
종로구 316
 
19.1%
숭인동 49
 
3.0%
창신동 38
 
2.3%
낙원동 36
 
2.2%
관철동 25
 
1.5%
익선동 19
 
1.2%
수표로22길 16
 
1.0%
관수동 16
 
1.0%
난계로29길 14
 
0.8%
Other values (394) 806
48.8%
2024-04-30T04:18:10.583071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1335
 
15.9%
627
 
7.5%
420
 
5.0%
( 321
 
3.8%
) 321
 
3.8%
320
 
3.8%
318
 
3.8%
318
 
3.8%
317
 
3.8%
316
 
3.8%
Other values (170) 3786
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4947
58.9%
Space Separator 1335
 
15.9%
Decimal Number 1266
 
15.1%
Open Punctuation 321
 
3.8%
Close Punctuation 321
 
3.8%
Dash Punctuation 111
 
1.3%
Other Punctuation 64
 
0.8%
Uppercase Letter 13
 
0.2%
Math Symbol 12
 
0.1%
Lowercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
627
12.7%
420
 
8.5%
320
 
6.5%
318
 
6.4%
318
 
6.4%
317
 
6.4%
316
 
6.4%
316
 
6.4%
311
 
6.3%
252
 
5.1%
Other values (135) 1432
28.9%
Uppercase Letter
ValueCountFrequency (%)
M 2
15.4%
L 2
15.4%
O 1
7.7%
U 1
7.7%
C 1
7.7%
K 1
7.7%
Y 1
7.7%
H 1
7.7%
T 1
7.7%
E 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 261
20.6%
2 235
18.6%
6 135
10.7%
3 129
10.2%
4 111
8.8%
5 99
 
7.8%
8 88
 
7.0%
9 83
 
6.6%
7 70
 
5.5%
0 55
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
l 2
22.2%
o 1
11.1%
t 1
11.1%
h 1
11.1%
u 1
11.1%
g 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 63
98.4%
& 1
 
1.6%
Space Separator
ValueCountFrequency (%)
1335
100.0%
Open Punctuation
ValueCountFrequency (%)
( 321
100.0%
Close Punctuation
ValueCountFrequency (%)
) 321
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4947
58.9%
Common 3430
40.8%
Latin 22
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
627
12.7%
420
 
8.5%
320
 
6.5%
318
 
6.4%
318
 
6.4%
317
 
6.4%
316
 
6.4%
316
 
6.4%
311
 
6.3%
252
 
5.1%
Other values (135) 1432
28.9%
Latin
ValueCountFrequency (%)
e 2
 
9.1%
M 2
 
9.1%
l 2
 
9.1%
L 2
 
9.1%
o 1
 
4.5%
t 1
 
4.5%
h 1
 
4.5%
u 1
 
4.5%
O 1
 
4.5%
g 1
 
4.5%
Other values (8) 8
36.4%
Common
ValueCountFrequency (%)
1335
38.9%
( 321
 
9.4%
) 321
 
9.4%
1 261
 
7.6%
2 235
 
6.9%
6 135
 
3.9%
3 129
 
3.8%
4 111
 
3.2%
- 111
 
3.2%
5 99
 
2.9%
Other values (7) 372
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4947
58.9%
ASCII 3452
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1335
38.7%
( 321
 
9.3%
) 321
 
9.3%
1 261
 
7.6%
2 235
 
6.8%
6 135
 
3.9%
3 129
 
3.7%
4 111
 
3.2%
- 111
 
3.2%
5 99
 
2.9%
Other values (25) 394
 
11.4%
Hangul
ValueCountFrequency (%)
627
12.7%
420
 
8.5%
320
 
6.5%
318
 
6.4%
318
 
6.4%
317
 
6.4%
316
 
6.4%
316
 
6.4%
311
 
6.3%
252
 
5.1%
Other values (135) 1432
28.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)21.4%
Missing210
Missing (%)40.5%
Infinite0
Infinite (%)0.0%
Mean3132.4595
Minimum3000
Maximum3198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:10.706870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile3053.8
Q13116
median3132
Q33145
95-th percentile3192
Maximum3198
Range198
Interquartile range (IQR)29

Descriptive statistics

Standard deviation37.590615
Coefficient of variation (CV)0.012000351
Kurtosis1.7541448
Mean3132.4595
Median Absolute Deviation (MAD)14
Skewness-0.67253015
Sum967930
Variance1413.0544
MonotonicityNot monotonic
2024-04-30T04:18:10.831467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3139 33
 
6.4%
3119 21
 
4.0%
3115 20
 
3.9%
3132 18
 
3.5%
3192 16
 
3.1%
3126 15
 
2.9%
3133 14
 
2.7%
3111 11
 
2.1%
3189 10
 
1.9%
3191 8
 
1.5%
Other values (56) 143
27.6%
(Missing) 210
40.5%
ValueCountFrequency (%)
3000 1
 
0.2%
3010 1
 
0.2%
3017 2
 
0.4%
3027 1
 
0.2%
3028 1
 
0.2%
3029 1
 
0.2%
3030 7
1.3%
3041 2
 
0.4%
3073 2
 
0.4%
3074 1
 
0.2%
ValueCountFrequency (%)
3198 1
 
0.2%
3197 1
 
0.2%
3196 2
 
0.4%
3193 3
 
0.6%
3192 16
3.1%
3191 8
1.5%
3190 8
1.5%
3189 10
1.9%
3183 1
 
0.2%
3182 2
 
0.4%
Distinct480
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-04-30T04:18:11.048013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length5.1907514
Min length1

Characters and Unicode

Total characters2694
Distinct characters336
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique447 ?
Unique (%)86.1%

Sample

1st row백금여관
2nd row이지스테이
3rd row강원
4th row삼화
5th row호스텔 바닐라 1
ValueCountFrequency (%)
호텔 34
 
4.9%
호스텔 10
 
1.4%
서울 9
 
1.3%
동대문 7
 
1.0%
hotel 7
 
1.0%
인사동 7
 
1.0%
종로 6
 
0.9%
hostel 5
 
0.7%
삼화 4
 
0.6%
게스트하우스 4
 
0.6%
Other values (539) 601
86.6%
2024-04-30T04:18:11.399769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
6.5%
154
 
5.7%
126
 
4.7%
110
 
4.1%
60
 
2.2%
48
 
1.8%
46
 
1.7%
( 38
 
1.4%
) 38
 
1.4%
35
 
1.3%
Other values (326) 1864
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2013
74.7%
Uppercase Letter 224
 
8.3%
Space Separator 175
 
6.5%
Lowercase Letter 151
 
5.6%
Decimal Number 49
 
1.8%
Open Punctuation 38
 
1.4%
Close Punctuation 38
 
1.4%
Dash Punctuation 3
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
154
 
7.7%
126
 
6.3%
110
 
5.5%
60
 
3.0%
48
 
2.4%
46
 
2.3%
35
 
1.7%
34
 
1.7%
31
 
1.5%
31
 
1.5%
Other values (270) 1338
66.5%
Uppercase Letter
ValueCountFrequency (%)
H 25
11.2%
T 24
 
10.7%
E 23
 
10.3%
O 20
 
8.9%
S 17
 
7.6%
A 16
 
7.1%
L 13
 
5.8%
U 9
 
4.0%
G 8
 
3.6%
N 8
 
3.6%
Other values (14) 61
27.2%
Lowercase Letter
ValueCountFrequency (%)
e 26
17.2%
o 21
13.9%
s 14
9.3%
l 13
8.6%
t 11
 
7.3%
n 10
 
6.6%
a 8
 
5.3%
i 7
 
4.6%
u 7
 
4.6%
d 6
 
4.0%
Other values (7) 28
18.5%
Decimal Number
ValueCountFrequency (%)
2 13
26.5%
1 11
22.4%
3 6
12.2%
4 5
 
10.2%
5 4
 
8.2%
8 4
 
8.2%
0 3
 
6.1%
7 1
 
2.0%
9 1
 
2.0%
6 1
 
2.0%
Space Separator
ValueCountFrequency (%)
175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2010
74.6%
Latin 375
 
13.9%
Common 306
 
11.4%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
154
 
7.7%
126
 
6.3%
110
 
5.5%
60
 
3.0%
48
 
2.4%
46
 
2.3%
35
 
1.7%
34
 
1.7%
31
 
1.5%
31
 
1.5%
Other values (267) 1335
66.4%
Latin
ValueCountFrequency (%)
e 26
 
6.9%
H 25
 
6.7%
T 24
 
6.4%
E 23
 
6.1%
o 21
 
5.6%
O 20
 
5.3%
S 17
 
4.5%
A 16
 
4.3%
s 14
 
3.7%
l 13
 
3.5%
Other values (31) 176
46.9%
Common
ValueCountFrequency (%)
175
57.2%
( 38
 
12.4%
) 38
 
12.4%
2 13
 
4.2%
1 11
 
3.6%
3 6
 
2.0%
4 5
 
1.6%
5 4
 
1.3%
8 4
 
1.3%
0 3
 
1.0%
Other values (5) 9
 
2.9%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2010
74.6%
ASCII 681
 
25.3%
CJK Compat Ideographs 2
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
25.7%
( 38
 
5.6%
) 38
 
5.6%
e 26
 
3.8%
H 25
 
3.7%
T 24
 
3.5%
E 23
 
3.4%
o 21
 
3.1%
O 20
 
2.9%
S 17
 
2.5%
Other values (46) 274
40.2%
Hangul
ValueCountFrequency (%)
154
 
7.7%
126
 
6.3%
110
 
5.5%
60
 
3.0%
48
 
2.4%
46
 
2.3%
35
 
1.7%
34
 
1.7%
31
 
1.5%
31
 
1.5%
Other values (267) 1335
66.4%
CJK Compat Ideographs
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct390
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1999-03-03 00:00:00
Maximum2024-04-01 11:59:54
2024-04-30T04:18:11.521253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:11.814011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
I
288 
U
231 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 288
55.5%
U 231
44.5%

Length

2024-04-30T04:18:11.938842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:12.014790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 288
55.5%
u 231
44.5%
Distinct146
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-04-30T04:18:12.099413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:18:12.225215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
여관업
297 
여인숙업
102 
관광호텔
53 
일반호텔
33 
숙박업(생활)
 
22

Length

Max length7
Median length3
Mean length3.6011561
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 297
57.2%
여인숙업 102
 
19.7%
관광호텔 53
 
10.2%
일반호텔 33
 
6.4%
숙박업(생활) 22
 
4.2%
숙박업 기타 12
 
2.3%

Length

2024-04-30T04:18:12.351532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:12.447999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 297
55.9%
여인숙업 102
 
19.2%
관광호텔 53
 
10.0%
일반호텔 33
 
6.2%
숙박업(생활 22
 
4.1%
숙박업 12
 
2.3%
기타 12
 
2.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct432
Distinct (%)90.8%
Missing43
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean199542.47
Minimum196045.61
Maximum201956.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:12.552873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196045.61
5-th percentile196646.34
Q1198816.07
median199120.77
Q3200931.88
95-th percentile201803.87
Maximum201956.89
Range5911.2772
Interquartile range (IQR)2115.8073

Descriptive statistics

Standard deviation1458.7867
Coefficient of variation (CV)0.0073106577
Kurtosis-0.38863749
Mean199542.47
Median Absolute Deviation (MAD)835.15043
Skewness-0.2357039
Sum94982215
Variance2128058.6
MonotonicityNot monotonic
2024-04-30T04:18:12.678633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198995.160911349 4
 
0.8%
199017.61283129 3
 
0.6%
198692.627926952 3
 
0.6%
199037.974854028 3
 
0.6%
201649.840328936 3
 
0.6%
201378.94229242 3
 
0.6%
198469.85451949 2
 
0.4%
199022.300982384 2
 
0.4%
201896.77471979 2
 
0.4%
199028.334386781 2
 
0.4%
Other values (422) 449
86.5%
(Missing) 43
 
8.3%
ValueCountFrequency (%)
196045.610971552 1
0.2%
196203.778423117 1
0.2%
196215.891675956 1
0.2%
196246.132766081 1
0.2%
196257.674735972 1
0.2%
196282.226000237 1
0.2%
196285.571957576 1
0.2%
196296.085453197 1
0.2%
196318.153259189 1
0.2%
196318.323061166 1
0.2%
ValueCountFrequency (%)
201956.888133032 1
0.2%
201949.270716491 1
0.2%
201930.626141344 1
0.2%
201911.277519785 1
0.2%
201909.605791088 1
0.2%
201906.350836688 1
0.2%
201906.310361364 1
0.2%
201905.253700076 1
0.2%
201896.945381012 1
0.2%
201896.77471979 2
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct432
Distinct (%)90.8%
Missing43
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean452375.51
Minimum451804.9
Maximum456529.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:12.799319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451804.9
5-th percentile451880.15
Q1452093.11
median452248.78
Q3452475.93
95-th percentile452972.25
Maximum456529.71
Range4724.8106
Interquartile range (IQR)382.81998

Descriptive statistics

Standard deviation637.59931
Coefficient of variation (CV)0.001409447
Kurtosis24.710651
Mean452375.51
Median Absolute Deviation (MAD)174.12883
Skewness4.5793765
Sum2.1533074 × 108
Variance406532.88
MonotonicityNot monotonic
2024-04-30T04:18:12.922924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452541.684613522 4
 
0.8%
452077.141477996 3
 
0.6%
451865.694333484 3
 
0.6%
451905.533009293 3
 
0.6%
452323.368074798 3
 
0.6%
452482.200375273 3
 
0.6%
452315.746209246 2
 
0.4%
452472.976006603 2
 
0.4%
452680.814985234 2
 
0.4%
452116.660907308 2
 
0.4%
Other values (422) 449
86.5%
(Missing) 43
 
8.3%
ValueCountFrequency (%)
451804.898052916 2
0.4%
451826.54074884 1
0.2%
451827.704774757 1
0.2%
451828.58889242 1
0.2%
451834.817165156 1
0.2%
451841.972789349 1
0.2%
451848.884404147 1
0.2%
451851.540972503 1
0.2%
451851.930284896 1
0.2%
451852.440739439 1
0.2%
ValueCountFrequency (%)
456529.708624294 1
0.2%
456519.922190749 1
0.2%
456478.436790904 1
0.2%
456346.84737021 1
0.2%
456318.690240102 1
0.2%
456278.209690093 1
0.2%
456007.528701216 1
0.2%
456003.295259389 1
0.2%
455368.063963395 1
0.2%
455358.793133704 1
0.2%

위생업태명
Categorical

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
여관업
227 
<NA>
138 
여인숙업
94 
관광호텔
32 
일반호텔
 
16
Other values (2)
 
12

Length

Max length7
Median length4
Mean length3.6262042
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 227
43.7%
<NA> 138
26.6%
여인숙업 94
18.1%
관광호텔 32
 
6.2%
일반호텔 16
 
3.1%
숙박업(생활) 9
 
1.7%
숙박업 기타 3
 
0.6%

Length

2024-04-30T04:18:13.039868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:13.135145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 227
43.5%
na 138
26.4%
여인숙업 94
18.0%
관광호텔 32
 
6.1%
일반호텔 16
 
3.1%
숙박업(생활 9
 
1.7%
숙박업 3
 
0.6%
기타 3
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)5.2%
Missing230
Missing (%)44.3%
Infinite0
Infinite (%)0.0%
Mean1.4775087
Minimum0
Maximum24
Zeros212
Zeros (%)40.8%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:13.238289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8
Maximum24
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1722012
Coefficient of variation (CV)2.1469933
Kurtosis12.317298
Mean1.4775087
Median Absolute Deviation (MAD)0
Skewness3.0255961
Sum427
Variance10.06286
MonotonicityNot monotonic
2024-04-30T04:18:13.335643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 212
40.8%
4 14
 
2.7%
2 14
 
2.7%
5 14
 
2.7%
7 6
 
1.2%
1 4
 
0.8%
11 4
 
0.8%
6 4
 
0.8%
8 4
 
0.8%
3 4
 
0.8%
Other values (5) 9
 
1.7%
(Missing) 230
44.3%
ValueCountFrequency (%)
0 212
40.8%
1 4
 
0.8%
2 14
 
2.7%
3 4
 
0.8%
4 14
 
2.7%
5 14
 
2.7%
6 4
 
0.8%
7 6
 
1.2%
8 4
 
0.8%
9 3
 
0.6%
ValueCountFrequency (%)
24 1
 
0.2%
18 1
 
0.2%
13 2
 
0.4%
11 4
 
0.8%
10 2
 
0.4%
9 3
 
0.6%
8 4
 
0.8%
7 6
1.2%
6 4
 
0.8%
5 14
2.7%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.6%
Missing253
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean0.22556391
Minimum0
Maximum6
Zeros231
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:13.426180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.75
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.72285118
Coefficient of variation (CV)3.2046402
Kurtosis25.953001
Mean0.22556391
Median Absolute Deviation (MAD)0
Skewness4.5828277
Sum60
Variance0.52251383
MonotonicityNot monotonic
2024-04-30T04:18:13.516990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 231
44.5%
1 21
 
4.0%
2 9
 
1.7%
3 2
 
0.4%
6 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
(Missing) 253
48.7%
ValueCountFrequency (%)
0 231
44.5%
1 21
 
4.0%
2 9
 
1.7%
3 2
 
0.4%
4 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 1
 
0.2%
4 1
 
0.2%
3 2
 
0.4%
2 9
 
1.7%
1 21
 
4.0%
0 231
44.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)3.1%
Missing229
Missing (%)44.1%
Infinite0
Infinite (%)0.0%
Mean0.73448276
Minimum0
Maximum10
Zeros186
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:13.605615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4487259
Coefficient of variation (CV)1.9724438
Kurtosis13.36513
Mean0.73448276
Median Absolute Deviation (MAD)0
Skewness3.2493091
Sum213
Variance2.0988068
MonotonicityNot monotonic
2024-04-30T04:18:13.687987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 186
35.8%
1 59
 
11.4%
2 22
 
4.2%
4 8
 
1.5%
3 6
 
1.2%
5 5
 
1.0%
8 2
 
0.4%
10 1
 
0.2%
9 1
 
0.2%
(Missing) 229
44.1%
ValueCountFrequency (%)
0 186
35.8%
1 59
 
11.4%
2 22
 
4.2%
3 6
 
1.2%
4 8
 
1.5%
5 5
 
1.0%
8 2
 
0.4%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
9 1
 
0.2%
8 2
 
0.4%
5 5
 
1.0%
4 8
 
1.5%
3 6
 
1.2%
2 22
 
4.2%
1 59
 
11.4%
0 186
35.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)6.4%
Missing253
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean4.7255639
Minimum0
Maximum25
Zeros23
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:13.775337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median5
Q35
95-th percentile9
Maximum25
Range25
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.950514
Coefficient of variation (CV)0.62437289
Kurtosis14.793432
Mean4.7255639
Median Absolute Deviation (MAD)1
Skewness2.5741536
Sum1257
Variance8.7055327
MonotonicityNot monotonic
2024-04-30T04:18:13.861176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
5 131
25.2%
4 38
 
7.3%
0 23
 
4.4%
3 14
 
2.7%
7 13
 
2.5%
2 13
 
2.5%
6 8
 
1.5%
1 6
 
1.2%
8 5
 
1.0%
9 3
 
0.6%
Other values (7) 12
 
2.3%
(Missing) 253
48.7%
ValueCountFrequency (%)
0 23
 
4.4%
1 6
 
1.2%
2 13
 
2.5%
3 14
 
2.7%
4 38
 
7.3%
5 131
25.2%
6 8
 
1.5%
7 13
 
2.5%
8 5
 
1.0%
9 3
 
0.6%
ValueCountFrequency (%)
25 1
 
0.2%
23 1
 
0.2%
18 1
 
0.2%
13 3
 
0.6%
12 1
 
0.2%
11 3
 
0.6%
10 2
 
0.4%
9 3
 
0.6%
8 5
 
1.0%
7 13
2.5%
Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
264 
0
239 
1
 
14
2
 
2

Length

Max length4
Median length4
Mean length2.5260116
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 264
50.9%
0 239
46.1%
1 14
 
2.7%
2 2
 
0.4%

Length

2024-04-30T04:18:13.969407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:14.059471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 264
50.9%
0 239
46.1%
1 14
 
2.7%
2 2
 
0.4%
Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
369 
0
135 
1
 
13
2
 
2

Length

Max length4
Median length4
Mean length3.132948
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 369
71.1%
0 135
 
26.0%
1 13
 
2.5%
2 2
 
0.4%

Length

2024-04-30T04:18:14.152655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:14.236099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
71.1%
0 135
 
26.0%
1 13
 
2.5%
2 2
 
0.4%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)9.6%
Missing153
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean9.9726776
Minimum0
Maximum37
Zeros75
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:14.345786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q314
95-th percentile23
Maximum37
Range37
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.4733731
Coefficient of variation (CV)0.74938481
Kurtosis0.75334615
Mean9.9726776
Median Absolute Deviation (MAD)4
Skewness0.63928514
Sum3650
Variance55.851306
MonotonicityNot monotonic
2024-04-30T04:18:14.478963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 75
14.5%
10 46
 
8.9%
11 26
 
5.0%
12 24
 
4.6%
13 23
 
4.4%
8 18
 
3.5%
16 18
 
3.5%
14 16
 
3.1%
9 14
 
2.7%
15 12
 
2.3%
Other values (25) 94
18.1%
(Missing) 153
29.5%
ValueCountFrequency (%)
0 75
14.5%
1 2
 
0.4%
2 6
 
1.2%
3 5
 
1.0%
4 6
 
1.2%
5 7
 
1.3%
6 9
 
1.7%
7 9
 
1.7%
8 18
 
3.5%
9 14
 
2.7%
ValueCountFrequency (%)
37 1
 
0.2%
36 1
 
0.2%
34 1
 
0.2%
33 1
 
0.2%
31 3
0.6%
30 1
 
0.2%
29 2
0.4%
28 1
 
0.2%
26 1
 
0.2%
25 2
0.4%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct66
Distinct (%)21.6%
Missing214
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean19.980328
Minimum0
Maximum363
Zeros127
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:14.597786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q320
95-th percentile62
Maximum363
Range363
Interquartile range (IQR)20

Descriptive statistics

Standard deviation47.160277
Coefficient of variation (CV)2.3603355
Kurtosis28.484194
Mean19.980328
Median Absolute Deviation (MAD)6
Skewness5.0190035
Sum6094
Variance2224.0917
MonotonicityNot monotonic
2024-04-30T04:18:14.711328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 127
24.5%
6 12
 
2.3%
10 12
 
2.3%
14 9
 
1.7%
5 9
 
1.7%
7 7
 
1.3%
19 7
 
1.3%
29 6
 
1.2%
9 6
 
1.2%
23 5
 
1.0%
Other values (56) 105
20.2%
(Missing) 214
41.2%
ValueCountFrequency (%)
0 127
24.5%
1 3
 
0.6%
2 3
 
0.6%
3 2
 
0.4%
4 1
 
0.2%
5 9
 
1.7%
6 12
 
2.3%
7 7
 
1.3%
8 5
 
1.0%
9 6
 
1.2%
ValueCountFrequency (%)
363 1
0.2%
339 1
0.2%
317 1
0.2%
299 1
0.2%
287 1
0.2%
213 2
0.4%
139 1
0.2%
127 1
0.2%
107 1
0.2%
101 1
0.2%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct39
Distinct (%)11.1%
Missing169
Missing (%)32.6%
Infinite0
Infinite (%)0.0%
Mean8.86
Minimum0
Maximum301
Zeros88
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:14.827812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median3.5
Q312
95-th percentile28
Maximum301
Range301
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation19.045876
Coefficient of variation (CV)2.1496474
Kurtosis160.72701
Mean8.86
Median Absolute Deviation (MAD)3.5
Skewness10.968894
Sum3101
Variance362.74539
MonotonicityNot monotonic
2024-04-30T04:18:14.927491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 88
17.0%
1 63
 
12.1%
10 29
 
5.6%
2 16
 
3.1%
11 15
 
2.9%
12 15
 
2.9%
6 10
 
1.9%
7 9
 
1.7%
13 9
 
1.7%
18 8
 
1.5%
Other values (29) 88
17.0%
(Missing) 169
32.6%
ValueCountFrequency (%)
0 88
17.0%
1 63
12.1%
2 16
 
3.1%
3 8
 
1.5%
4 3
 
0.6%
5 2
 
0.4%
6 10
 
1.9%
7 9
 
1.7%
8 6
 
1.2%
9 5
 
1.0%
ValueCountFrequency (%)
301 1
 
0.2%
104 1
 
0.2%
72 1
 
0.2%
51 1
 
0.2%
43 1
 
0.2%
36 1
 
0.2%
34 2
0.4%
33 2
0.4%
31 3
0.6%
30 3
0.6%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.5%
Missing138
Missing (%)26.6%
Memory size1.1 KiB
True
305 
False
76 
(Missing)
138 
ValueCountFrequency (%)
True 305
58.8%
False 76
 
14.6%
(Missing) 138
26.6%
2024-04-30T04:18:15.017401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)8.5%
Missing249
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean3.5851852
Minimum0
Maximum216
Zeros230
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-04-30T04:18:15.102216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.55
Maximum216
Range216
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.241823
Coefficient of variation (CV)5.0881117
Kurtosis82.426673
Mean3.5851852
Median Absolute Deviation (MAD)0
Skewness8.3245955
Sum968
Variance332.76409
MonotonicityNot monotonic
2024-04-30T04:18:15.202644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 230
44.3%
5 7
 
1.3%
1 5
 
1.0%
3 3
 
0.6%
2 3
 
0.6%
4 3
 
0.6%
62 2
 
0.4%
60 2
 
0.4%
144 1
 
0.2%
25 1
 
0.2%
Other values (13) 13
 
2.5%
(Missing) 249
48.0%
ValueCountFrequency (%)
0 230
44.3%
1 5
 
1.0%
2 3
 
0.6%
3 3
 
0.6%
4 3
 
0.6%
5 7
 
1.3%
6 1
 
0.2%
7 1
 
0.2%
10 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
216 1
0.2%
144 1
0.2%
68 1
0.2%
62 2
0.4%
60 2
0.4%
43 1
0.2%
36 1
0.2%
26 1
0.2%
25 1
0.2%
19 1
0.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing519
Missing (%)100.0%
Memory size4.7 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
482 
자가
 
21
임대
 
16

Length

Max length4
Median length4
Mean length3.8574181
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> 482
92.9%
자가 21
 
4.0%
임대 16
 
3.1%

Length

2024-04-30T04:18:15.305194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:15.388535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 482
92.9%
자가 21
 
4.0%
임대 16
 
3.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
366 
0
153 

Length

Max length4
Median length4
Mean length3.1156069
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 366
70.5%
0 153
29.5%

Length

2024-04-30T04:18:15.498996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:15.586780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 366
70.5%
0 153
29.5%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
490 
0
 
27
4
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.8323699
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 490
94.4%
0 27
 
5.2%
4 1
 
0.2%
1 1
 
0.2%

Length

2024-04-30T04:18:15.897099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:15.977405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 490
94.4%
0 27
 
5.2%
4 1
 
0.2%
1 1
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
490 
0
 
26
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.8323699
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 490
94.4%
0 26
 
5.0%
1 2
 
0.4%
3 1
 
0.2%

Length

2024-04-30T04:18:16.064772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:16.152726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 490
94.4%
0 26
 
5.0%
1 2
 
0.4%
3 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
367 
0
152 

Length

Max length4
Median length4
Mean length3.1213873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
70.7%
0 152
29.3%

Length

2024-04-30T04:18:16.247254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:16.343257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
70.7%
0 152
29.3%

침대수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
367 
0
152 

Length

Max length4
Median length4
Mean length3.1213873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
70.7%
0 152
29.3%

Length

2024-04-30T04:18:16.458425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:18:16.561979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
70.7%
0 152
29.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing138
Missing (%)26.6%
Memory size1.1 KiB
False
379 
True
 
2
(Missing)
138 
ValueCountFrequency (%)
False 379
73.0%
True 2
 
0.4%
(Missing) 138
 
26.6%
2024-04-30T04:18:16.638806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030000003000000-201-1960-0014819601219<NA>3폐업2폐업19931221<NA><NA><NA>020763563599.17110840서울특별시 종로구 창신동 148-1번지<NA><NA>백금여관2001-09-29 00:00:00I2018-08-31 23:59:59.0여관업201035.35757452256.067309여관업000<NA>0<NA>14014Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130000003000000-201-1960-002661960-12-19<NA>1영업/정상1영업<NA><NA><NA><NA>02 764553791.17120-855서울특별시 종로구 창신동 687-20서울특별시 종로구 창신길 9-8 (창신동)3101이지스테이2023-10-30 09:33:19U2022-11-01 00:01:00.0여관업200827.196168452228.128469<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230000003000000-201-1960-0028719601230<NA>3폐업2폐업19940228<NA><NA><NA>020000000064.93110290서울특별시 종로구 인사동 153-2번지<NA><NA>강원2001-11-20 00:00:00I2018-08-31 23:59:59.0여인숙업198721.150253452189.728779여인숙업000<NA>0<NA>1101Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330000003000000-201-1961-0025919611130<NA>3폐업2폐업19970313<NA><NA><NA>02 764055089.19110126서울특별시 종로구 종로6가 112-0번지<NA><NA>삼화2001-11-20 00:00:00I2018-08-31 23:59:59.0여관업200625.032207452143.431069여관업000<NA>0<NA>11011Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430000003000000-201-1963-0021019630726<NA>1영업/정상1영업<NA><NA><NA><NA>026459511382.64110540서울특별시 종로구 창신동 581-8번지서울특별시 종로구 창신길 28-7 (창신동)3106호스텔 바닐라 12019-06-04 09:57:10U2019-06-06 02:40:00.0여관업200915.355545452286.287835여관업00070010010Y0<NA><NA><NA><NA>0<NA><NA>00N
530000003000000-201-1963-0027619630627<NA>3폐업2폐업19960106<NA><NA><NA>02 730543245.43110813서울특별시 종로구 무악동 45-36번지<NA><NA>영천2001-09-29 00:00:00I2018-08-31 23:59:59.0여인숙업196282.226452444.459912여인숙업000<NA>0<NA>1101Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630000003000000-201-1963-0027719630627<NA>3폐업2폐업20100623<NA><NA><NA>02 738240523.43110813서울특별시 종로구 무악동 46-53번지<NA><NA>현저여인숙2004-01-16 00:00:00I2018-08-31 23:59:59.0여인숙업196321.560456452417.924126여인숙업<NA><NA><NA>5<NA><NA>6<NA><NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730000003000000-201-1963-0035219630129<NA>3폐업2폐업20010725<NA><NA><NA>02 764929484.54110863서울특별시 종로구 숭인동 94-0번지<NA><NA>봉산2001-08-28 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>1402Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830000003000000-201-1964-0026119640411<NA>3폐업2폐업20011231<NA><NA><NA>02 7628565101.33110126서울특별시 종로구 종로6가 21-2번지<NA><NA>진희2002-07-15 00:00:00I2018-08-31 23:59:59.0여관업200611.127043452235.891284여관업000<NA>0<NA>12010Y0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930000003000000-201-1965-001741965-05-10<NA>1영업/정상1영업<NA><NA><NA><NA>02 9276393141.95110-827서울특별시 종로구 숭인동 339서울특별시 종로구 보문로7길 5-1 (숭인동)3111메종호텔2023-06-19 11:34:02U2022-12-05 22:01:00.0여관업201930.626141452794.664952<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
50930000003000000-214-2020-0000120200121<NA>1영업/정상1영업<NA><NA><NA><NA>0262635577582.17110450서울특별시 종로구 원남동 226-1번지서울특별시 종로구 동순라길 98 (원남동)3136종로 스테이2020-01-21 14:17:26I2020-01-23 00:23:24.0숙박업(생활)199591.565032452530.682866숙박업(생활)0013110200N0<NA><NA><NA>자가00000Y
51030000003000000-214-2020-000022020-03-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>425.02110-111서울특별시 종로구 관철동 18-10서울특별시 종로구 우정국로2길 29, 4~5층 (관철동)3189UH SUITE2023-07-03 09:42:23U2022-12-07 00:05:00.0숙박업(생활)198581.075058451932.290555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51130000003000000-214-2020-000032020-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>026349078182.51110-111서울특별시 종로구 관철동 14-6서울특별시 종로구 삼일대로19길 22, 4층 (관철동)3190어 베터 플레이스 (A BETTER PLACE)2023-10-30 13:14:57U2022-11-01 00:01:00.0숙박업(생활)198724.740257451930.754248<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51230000003000000-214-2020-0000420070904<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45,510.23110320서울특별시 종로구 낙원동 272 로담코 인사빌딩서울특별시 종로구 인사동4길 18, 로담코 인사빌딩 (낙원동)3163오라카이 인사동 스위츠2020-08-21 20:05:01U2020-08-23 02:40:00.0숙박업(생활)198811.497418452301.907781숙박업(생활)<NA><NA><NA><NA><NA><NA><NA>213<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
51330000003000000-214-2021-000012021-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>365.04110-340서울특별시 종로구 익선동 89서울특별시 종로구 삼일대로32가길 38 (익선동)3132킹스가든2023-10-30 13:19:00U2022-11-01 00:01:00.0숙박업(생활)199022.300982452472.976007<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51430000003000000-214-2023-000012023-02-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.98110-450서울특별시 종로구 원남동 233 종로하루서울특별시 종로구 창경궁로21가길 5-3, 종로하루 (원남동)3136종로하루2023-10-30 11:26:04U2022-11-01 00:01:00.0숙박업(생활)199626.352161452520.392539<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51530000003000000-214-2023-000022023-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1785.87110-340서울특별시 종로구 익선동 53서울특별시 종로구 돈화문로11나길 53, 1~9층 (익선동)3132어반스테이 부티크 익선2023-10-18 14:56:11U2022-10-30 22:00:00.0숙박업(생활)198998.999624452520.878594<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51630000003000000-214-2023-000032023-07-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>453.91110-470서울특별시 종로구 연지동 179서울특별시 종로구 종로31길 50-7 (연지동)3129Maison2023-07-25 14:03:23I2022-12-06 22:07:00.0숙박업(생활)199847.981505452305.325465<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51730000003000000-214-2023-000042023-08-14<NA>3폐업2폐업2023-08-17<NA><NA><NA><NA>2520.55110-420서울특별시 종로구 관수동 18-1서울특별시 종로구 수표로18길 5 (관수동)3192누보2023-08-17 14:53:09U2022-12-07 23:09:00.0숙박업(생활)199037.974854451905.533009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51830000003000000-214-2023-000052023-10-13<NA>1영업/정상1영업<NA><NA><NA><NA>02 725 0203283.87110-111서울특별시 종로구 관철동 14-9 3층,4층,5층서울특별시 종로구 삼일대로19길 28, 3~5층 (관철동)3190밸류플레이스2023-10-13 14:22:38I2022-10-30 23:05:00.0숙박업(생활)198694.787532451930.899507<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>