Overview

Dataset statistics

Number of variables47
Number of observations250
Missing cells2870
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.0 KiB
Average record size in memory405.5 B

Variable types

Categorical17
Text7
DateTime3
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-17439/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용끝지하층 is highly imbalanced (54.2%)Imbalance
여성종사자수 is highly imbalanced (90.6%)Imbalance
남성종사자수 is highly imbalanced (90.6%)Imbalance
인허가취소일자 has 250 (100.0%) missing valuesMissing
폐업일자 has 89 (35.6%) missing valuesMissing
휴업시작일자 has 250 (100.0%) missing valuesMissing
휴업종료일자 has 250 (100.0%) missing valuesMissing
재개업일자 has 250 (100.0%) missing valuesMissing
전화번호 has 13 (5.2%) missing valuesMissing
도로명주소 has 127 (50.8%) missing valuesMissing
도로명우편번호 has 130 (52.0%) missing valuesMissing
좌표정보(X) has 45 (18.0%) missing valuesMissing
좌표정보(Y) has 45 (18.0%) missing valuesMissing
건물지상층수 has 75 (30.0%) missing valuesMissing
사용시작지상층 has 79 (31.6%) missing valuesMissing
사용끝지상층 has 182 (72.8%) missing valuesMissing
한실수 has 53 (21.2%) missing valuesMissing
양실수 has 71 (28.4%) missing valuesMissing
욕실수 has 71 (28.4%) missing valuesMissing
발한실여부 has 46 (18.4%) missing valuesMissing
좌석수 has 48 (19.2%) missing valuesMissing
조건부허가신고사유 has 250 (100.0%) missing valuesMissing
조건부허가시작일자 has 250 (100.0%) missing valuesMissing
조건부허가종료일자 has 250 (100.0%) missing valuesMissing
다중이용업소여부 has 46 (18.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 135 (54.0%) zerosZeros
사용시작지상층 has 123 (49.2%) zerosZeros
사용끝지상층 has 20 (8.0%) zerosZeros
한실수 has 32 (12.8%) zerosZeros
양실수 has 110 (44.0%) zerosZeros
욕실수 has 110 (44.0%) zerosZeros
좌석수 has 24 (9.6%) zerosZeros

Reproduction

Analysis started2024-05-11 04:56:01.932376
Analysis finished2024-05-11 04:56:03.130638
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3120000
250 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 250
100.0%

Length

2024-05-11T04:56:03.252361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:03.471970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 250
100.0%

관리번호
Text

UNIQUE 

Distinct250
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T04:56:03.769514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5500
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

Unique250 ?
Unique (%)100.0%

Sample

1st row3120000-201-1962-00067
2nd row3120000-201-1963-00040
3rd row3120000-201-1963-00046
4th row3120000-201-1963-01199
5th row3120000-201-1964-00080
ValueCountFrequency (%)
3120000-201-1962-00067 1
 
0.4%
3120000-201-1983-00037 1
 
0.4%
3120000-201-1981-01221 1
 
0.4%
3120000-201-1989-00032 1
 
0.4%
3120000-201-1981-01227 1
 
0.4%
3120000-201-1981-01412 1
 
0.4%
3120000-201-1981-01414 1
 
0.4%
3120000-201-1982-00010 1
 
0.4%
3120000-201-1982-01147 1
 
0.4%
3120000-201-1982-01155 1
 
0.4%
Other values (240) 240
96.0%
2024-05-11T04:56:04.604492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1897
34.5%
1 1022
18.6%
- 750
 
13.6%
2 649
 
11.8%
3 334
 
6.1%
9 318
 
5.8%
7 166
 
3.0%
6 111
 
2.0%
8 104
 
1.9%
4 86
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4750
86.4%
Dash Punctuation 750
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1897
39.9%
1 1022
21.5%
2 649
 
13.7%
3 334
 
7.0%
9 318
 
6.7%
7 166
 
3.5%
6 111
 
2.3%
8 104
 
2.2%
4 86
 
1.8%
5 63
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 750
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1897
34.5%
1 1022
18.6%
- 750
 
13.6%
2 649
 
11.8%
3 334
 
6.1%
9 318
 
5.8%
7 166
 
3.0%
6 111
 
2.0%
8 104
 
1.9%
4 86
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1897
34.5%
1 1022
18.6%
- 750
 
13.6%
2 649
 
11.8%
3 334
 
6.1%
9 318
 
5.8%
7 166
 
3.0%
6 111
 
2.0%
8 104
 
1.9%
4 86
 
1.6%
Distinct239
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1962-11-15 00:00:00
Maximum2023-06-19 00:00:00
2024-05-11T04:56:04.873240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:56:05.151879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3
161 
1
89 

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 (%)
3 161
64.4%
1 89
35.6%

Length

2024-05-11T04:56:05.474810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:05.662494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 161
64.4%
1 89
35.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
161 
영업/정상
89 

Length

Max length5
Median length2
Mean length3.068
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 161
64.4%
영업/정상 89
35.6%

Length

2024-05-11T04:56:06.013354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:06.334482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 161
64.4%
영업/정상 89
35.6%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2
161 
1
89 

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 (%)
2 161
64.4%
1 89
35.6%

Length

2024-05-11T04:56:06.671850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:06.850794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 161
64.4%
1 89
35.6%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
161 
영업
89 

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 161
64.4%
영업 89
35.6%

Length

2024-05-11T04:56:07.233449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:07.474147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 161
64.4%
영업 89
35.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct147
Distinct (%)91.3%
Missing89
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean20053445
Minimum19930723
Maximum20220810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:07.813594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930723
5-th percentile19931229
Q119980312
median20060228
Q320101223
95-th percentile20190325
Maximum20220810
Range290087
Interquartile range (IQR)120911

Descriptive statistics

Standard deviation81810.556
Coefficient of variation (CV)0.004079626
Kurtosis-1.0595483
Mean20053445
Median Absolute Deviation (MAD)69912
Skewness0.18463157
Sum3.2286047 × 109
Variance6.6929671 × 109
MonotonicityNot monotonic
2024-05-11T04:56:08.256928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19931125 6
 
2.4%
19971128 3
 
1.2%
20060714 3
 
1.2%
20140613 2
 
0.8%
20190523 2
 
0.8%
20081208 2
 
0.8%
20010303 2
 
0.8%
20030725 2
 
0.8%
20110406 1
 
0.4%
20220810 1
 
0.4%
Other values (137) 137
54.8%
(Missing) 89
35.6%
ValueCountFrequency (%)
19930723 1
 
0.4%
19931125 6
2.4%
19931213 1
 
0.4%
19931229 1
 
0.4%
19940317 1
 
0.4%
19940404 1
 
0.4%
19940412 1
 
0.4%
19940516 1
 
0.4%
19940528 1
 
0.4%
19940909 1
 
0.4%
ValueCountFrequency (%)
20220810 1
0.4%
20201221 1
0.4%
20201102 1
0.4%
20200804 1
0.4%
20200303 1
0.4%
20190820 1
0.4%
20190523 2
0.8%
20190325 1
0.4%
20181109 1
0.4%
20180724 1
0.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct231
Distinct (%)97.5%
Missing13
Missing (%)5.2%
Memory size2.1 KiB
2024-05-11T04:56:08.807758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.016878
Min length2

Characters and Unicode

Total characters2374
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

Unique225 ?
Unique (%)94.9%

Sample

1st row02 3091740
2nd row0203622387
3rd row0203642727
4th row0203624056
5th row0203136951
ValueCountFrequency (%)
02 146
37.5%
3721972 2
 
0.5%
3128523 2
 
0.5%
3927172 2
 
0.5%
395 2
 
0.5%
3732251 2
 
0.5%
3125141 2
 
0.5%
3136870 2
 
0.5%
3124004 1
 
0.3%
0203726483 1
 
0.3%
Other values (227) 227
58.4%
2024-05-11T04:56:09.615623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 454
19.1%
3 437
18.4%
2 419
17.6%
7 165
 
7.0%
156
 
6.6%
1 145
 
6.1%
6 143
 
6.0%
9 134
 
5.6%
4 131
 
5.5%
5 98
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2218
93.4%
Space Separator 156
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 454
20.5%
3 437
19.7%
2 419
18.9%
7 165
 
7.4%
1 145
 
6.5%
6 143
 
6.4%
9 134
 
6.0%
4 131
 
5.9%
5 98
 
4.4%
8 92
 
4.1%
Space Separator
ValueCountFrequency (%)
156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 454
19.1%
3 437
18.4%
2 419
17.6%
7 165
 
7.0%
156
 
6.6%
1 145
 
6.1%
6 143
 
6.0%
9 134
 
5.6%
4 131
 
5.5%
5 98
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 454
19.1%
3 437
18.4%
2 419
17.6%
7 165
 
7.0%
156
 
6.6%
1 145
 
6.1%
6 143
 
6.0%
9 134
 
5.6%
4 131
 
5.5%
5 98
 
4.1%
Distinct213
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T04:56:10.307821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.42
Min length3

Characters and Unicode

Total characters1355
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 (%)83.6%

Sample

1st row126.81
2nd row.00
3rd row59.53
4th row.00
5th row124.10
ValueCountFrequency (%)
00 35
 
14.0%
512.62 2
 
0.8%
59.53 2
 
0.8%
118.80 2
 
0.8%
63,508.68 1
 
0.4%
1101.58 1
 
0.4%
422.55 1
 
0.4%
126.81 1
 
0.4%
1,810.75 1
 
0.4%
66.65 1
 
0.4%
Other values (203) 203
81.2%
2024-05-11T04:56:11.488275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 250
18.5%
0 199
14.7%
1 146
10.8%
6 114
8.4%
7 103
7.6%
8 100
 
7.4%
2 95
 
7.0%
3 89
 
6.6%
4 89
 
6.6%
5 82
 
6.1%
Other values (2) 88
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1091
80.5%
Other Punctuation 264
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 199
18.2%
1 146
13.4%
6 114
10.4%
7 103
9.4%
8 100
9.2%
2 95
8.7%
3 89
8.2%
4 89
8.2%
5 82
7.5%
9 74
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 250
94.7%
, 14
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 250
18.5%
0 199
14.7%
1 146
10.8%
6 114
8.4%
7 103
7.6%
8 100
 
7.4%
2 95
 
7.0%
3 89
 
6.6%
4 89
 
6.6%
5 82
 
6.1%
Other values (2) 88
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 250
18.5%
0 199
14.7%
1 146
10.8%
6 114
8.4%
7 103
7.6%
8 100
 
7.4%
2 95
 
7.0%
3 89
 
6.6%
4 89
 
6.6%
5 82
 
6.1%
Other values (2) 88
 
6.5%
Distinct61
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T04:56:11.943928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.108
Min length6

Characters and Unicode

Total characters1527
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

Unique28 ?
Unique (%)11.2%

Sample

1st row120802
2nd row120020
3rd row120819
4th row120840
5th row120808
ValueCountFrequency (%)
120833 59
23.6%
120805 23
 
9.2%
120809 20
 
8.0%
120834 10
 
4.0%
120857 10
 
4.0%
120-833 9
 
3.6%
120-809 9
 
3.6%
120802 8
 
3.2%
120803 6
 
2.4%
120808 5
 
2.0%
Other values (51) 91
36.4%
2024-05-11T04:56:12.848783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 382
25.0%
2 283
18.5%
1 278
18.2%
8 232
15.2%
3 168
11.0%
5 61
 
4.0%
9 38
 
2.5%
4 27
 
1.8%
- 27
 
1.8%
7 23
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1500
98.2%
Dash Punctuation 27
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 382
25.5%
2 283
18.9%
1 278
18.5%
8 232
15.5%
3 168
11.2%
5 61
 
4.1%
9 38
 
2.5%
4 27
 
1.8%
7 23
 
1.5%
6 8
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1527
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 382
25.0%
2 283
18.5%
1 278
18.2%
8 232
15.2%
3 168
11.0%
5 61
 
4.0%
9 38
 
2.5%
4 27
 
1.8%
- 27
 
1.8%
7 23
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 382
25.0%
2 283
18.5%
1 278
18.2%
8 232
15.2%
3 168
11.0%
5 61
 
4.0%
9 38
 
2.5%
4 27
 
1.8%
- 27
 
1.8%
7 23
 
1.5%
Distinct248
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T04:56:13.529532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length23.184
Min length18

Characters and Unicode

Total characters5796
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)98.4%

Sample

1st row서울특별시 서대문구 남가좌동 124-269번지
2nd row서울특별시 서대문구 미근동 186-0번지
3rd row서울특별시 서대문구 북아현동 126-18번지
4th row서울특별시 서대문구 충정로3가 317-0번지
5th row서울특별시 서대문구 대현동 53-19번지
ValueCountFrequency (%)
서울특별시 250
24.6%
서대문구 250
24.6%
창천동 83
 
8.2%
남가좌동 44
 
4.3%
대현동 35
 
3.4%
홍제동 26
 
2.6%
홍은동 11
 
1.1%
북아현동 11
 
1.1%
연희동 10
 
1.0%
북가좌동 8
 
0.8%
Other values (271) 288
28.3%
2024-05-11T04:56:14.412325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
970
16.7%
500
 
8.6%
285
 
4.9%
- 251
 
4.3%
250
 
4.3%
250
 
4.3%
250
 
4.3%
250
 
4.3%
250
 
4.3%
250
 
4.3%
Other values (43) 2290
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3423
59.1%
Decimal Number 1138
 
19.6%
Space Separator 970
 
16.7%
Dash Punctuation 251
 
4.3%
Other Punctuation 12
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
500
14.6%
285
 
8.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
242
 
7.1%
171
 
5.0%
Other values (28) 725
21.2%
Decimal Number
ValueCountFrequency (%)
1 220
19.3%
2 204
17.9%
0 119
10.5%
3 112
9.8%
9 101
8.9%
5 89
7.8%
4 82
 
7.2%
6 82
 
7.2%
8 77
 
6.8%
7 52
 
4.6%
Space Separator
ValueCountFrequency (%)
970
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 251
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3423
59.1%
Common 2373
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
500
14.6%
285
 
8.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
242
 
7.1%
171
 
5.0%
Other values (28) 725
21.2%
Common
ValueCountFrequency (%)
970
40.9%
- 251
 
10.6%
1 220
 
9.3%
2 204
 
8.6%
0 119
 
5.0%
3 112
 
4.7%
9 101
 
4.3%
5 89
 
3.8%
4 82
 
3.5%
6 82
 
3.5%
Other values (5) 143
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3423
59.1%
ASCII 2373
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
970
40.9%
- 251
 
10.6%
1 220
 
9.3%
2 204
 
8.6%
0 119
 
5.0%
3 112
 
4.7%
9 101
 
4.3%
5 89
 
3.8%
4 82
 
3.5%
6 82
 
3.5%
Other values (5) 143
 
6.0%
Hangul
ValueCountFrequency (%)
500
14.6%
285
 
8.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
250
 
7.3%
242
 
7.1%
171
 
5.0%
Other values (28) 725
21.2%

도로명주소
Text

MISSING 

Distinct123
Distinct (%)100.0%
Missing127
Missing (%)50.8%
Memory size2.1 KiB
2024-05-11T04:56:14.979761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length26.609756
Min length23

Characters and Unicode

Total characters3273
Distinct characters81
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)100.0%

Sample

1st row서울특별시 서대문구 통일로 173-54 (천연동)
2nd row서울특별시 서대문구 통일로40안길 21 (홍제동)
3rd row서울특별시 서대문구 신촌로37길 11 (북아현동)
4th row서울특별시 서대문구 간호대로1길 36 (홍제동)
5th row서울특별시 서대문구 통일로11길 7 (천연동)
ValueCountFrequency (%)
서울특별시 123
19.6%
서대문구 123
19.6%
창천동 48
 
7.7%
연세로2길 18
 
2.9%
대현동 17
 
2.7%
남가좌동 15
 
2.4%
연세로2나길 13
 
2.1%
홍제동 13
 
2.1%
신촌로 9
 
1.4%
홍은동 8
 
1.3%
Other values (159) 239
38.2%
2024-05-11T04:56:16.198614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
503
 
15.4%
248
 
7.6%
148
 
4.5%
124
 
3.8%
123
 
3.8%
( 123
 
3.8%
) 123
 
3.8%
123
 
3.8%
123
 
3.8%
123
 
3.8%
Other values (71) 1512
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2022
61.8%
Space Separator 503
 
15.4%
Decimal Number 431
 
13.2%
Open Punctuation 123
 
3.8%
Close Punctuation 123
 
3.8%
Dash Punctuation 45
 
1.4%
Other Punctuation 25
 
0.8%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
248
 
12.3%
148
 
7.3%
124
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
122
 
6.0%
112
 
5.5%
Other values (55) 653
32.3%
Decimal Number
ValueCountFrequency (%)
1 96
22.3%
2 90
20.9%
4 49
11.4%
3 48
11.1%
5 33
 
7.7%
6 33
 
7.7%
7 27
 
6.3%
8 23
 
5.3%
9 16
 
3.7%
0 16
 
3.7%
Space Separator
ValueCountFrequency (%)
503
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2022
61.8%
Common 1251
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
248
 
12.3%
148
 
7.3%
124
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
122
 
6.0%
112
 
5.5%
Other values (55) 653
32.3%
Common
ValueCountFrequency (%)
503
40.2%
( 123
 
9.8%
) 123
 
9.8%
1 96
 
7.7%
2 90
 
7.2%
4 49
 
3.9%
3 48
 
3.8%
- 45
 
3.6%
5 33
 
2.6%
6 33
 
2.6%
Other values (6) 108
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2022
61.8%
ASCII 1251
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
503
40.2%
( 123
 
9.8%
) 123
 
9.8%
1 96
 
7.7%
2 90
 
7.2%
4 49
 
3.9%
3 48
 
3.8%
- 45
 
3.6%
5 33
 
2.6%
6 33
 
2.6%
Other values (6) 108
 
8.6%
Hangul
ValueCountFrequency (%)
248
 
12.3%
148
 
7.3%
124
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
123
 
6.1%
122
 
6.0%
112
 
5.5%
Other values (55) 653
32.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)34.2%
Missing130
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean3735.8333
Minimum3615
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:16.597364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3615
5-th percentile3623
Q13712
median3766
Q33779
95-th percentile3780
Maximum3789
Range174
Interquartile range (IQR)67

Descriptive statistics

Standard deviation56.489507
Coefficient of variation (CV)0.015120992
Kurtosis-0.39944366
Mean3735.8333
Median Absolute Deviation (MAD)14
Skewness-1.0277675
Sum448300
Variance3191.0644
MonotonicityNot monotonic
2024-05-11T04:56:17.023273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3779 28
 
11.2%
3780 15
 
6.0%
3712 12
 
4.8%
3766 10
 
4.0%
3778 7
 
2.8%
3628 3
 
1.2%
3623 3
 
1.2%
3734 3
 
1.2%
3757 3
 
1.2%
3776 2
 
0.8%
Other values (31) 34
 
13.6%
(Missing) 130
52.0%
ValueCountFrequency (%)
3615 2
0.8%
3616 2
0.8%
3619 1
 
0.4%
3623 3
1.2%
3624 1
 
0.4%
3628 3
1.2%
3629 1
 
0.4%
3630 1
 
0.4%
3632 1
 
0.4%
3636 1
 
0.4%
ValueCountFrequency (%)
3789 1
 
0.4%
3786 1
 
0.4%
3785 1
 
0.4%
3781 1
 
0.4%
3780 15
6.0%
3779 28
11.2%
3778 7
 
2.8%
3777 1
 
0.4%
3776 2
 
0.8%
3766 10
 
4.0%
Distinct242
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T04:56:17.564464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length3.668
Min length1

Characters and Unicode

Total characters917
Distinct characters245
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

Unique234 ?
Unique (%)93.6%

Sample

1st row제일
2nd row서대문
3rd row송도장
4th row복현
5th row성민장
ValueCountFrequency (%)
호텔 7
 
2.6%
호스텔 3
 
1.1%
현대 2
 
0.7%
신촌 2
 
0.7%
충남 2
 
0.7%
서진 2
 
0.7%
연희장 2
 
0.7%
은하수 2
 
0.7%
해성 2
 
0.7%
황금 2
 
0.7%
Other values (244) 246
90.4%
2024-05-11T04:56:18.569671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
5.0%
46
 
5.0%
31
 
3.4%
29
 
3.2%
29
 
3.2%
29
 
3.2%
26
 
2.8%
22
 
2.4%
18
 
2.0%
17
 
1.9%
Other values (235) 624
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 821
89.5%
Uppercase Letter 51
 
5.6%
Space Separator 22
 
2.4%
Close Punctuation 7
 
0.8%
Open Punctuation 7
 
0.8%
Decimal Number 6
 
0.7%
Other Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
46
 
5.6%
46
 
5.6%
31
 
3.8%
29
 
3.5%
29
 
3.5%
29
 
3.5%
26
 
3.2%
18
 
2.2%
17
 
2.1%
17
 
2.1%
Other values (204) 533
64.9%
Uppercase Letter
ValueCountFrequency (%)
A 6
11.8%
E 5
 
9.8%
L 5
 
9.8%
N 4
 
7.8%
Y 4
 
7.8%
D 3
 
5.9%
O 3
 
5.9%
T 3
 
5.9%
I 2
 
3.9%
R 2
 
3.9%
Other values (11) 14
27.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 1
 
16.7%
3 1
 
16.7%
4 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
' 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 821
89.5%
Latin 51
 
5.6%
Common 45
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
46
 
5.6%
46
 
5.6%
31
 
3.8%
29
 
3.5%
29
 
3.5%
29
 
3.5%
26
 
3.2%
18
 
2.2%
17
 
2.1%
17
 
2.1%
Other values (204) 533
64.9%
Latin
ValueCountFrequency (%)
A 6
11.8%
E 5
 
9.8%
L 5
 
9.8%
N 4
 
7.8%
Y 4
 
7.8%
D 3
 
5.9%
O 3
 
5.9%
T 3
 
5.9%
I 2
 
3.9%
R 2
 
3.9%
Other values (11) 14
27.5%
Common
ValueCountFrequency (%)
22
48.9%
) 7
 
15.6%
( 7
 
15.6%
2 3
 
6.7%
1 1
 
2.2%
+ 1
 
2.2%
3 1
 
2.2%
4 1
 
2.2%
' 1
 
2.2%
& 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 821
89.5%
ASCII 96
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
46
 
5.6%
46
 
5.6%
31
 
3.8%
29
 
3.5%
29
 
3.5%
29
 
3.5%
26
 
3.2%
18
 
2.2%
17
 
2.1%
17
 
2.1%
Other values (204) 533
64.9%
ASCII
ValueCountFrequency (%)
22
22.9%
) 7
 
7.3%
( 7
 
7.3%
A 6
 
6.2%
E 5
 
5.2%
L 5
 
5.2%
N 4
 
4.2%
Y 4
 
4.2%
D 3
 
3.1%
O 3
 
3.1%
Other values (21) 30
31.2%
Distinct174
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1999-01-12 00:00:00
Maximum2024-05-02 09:33:13
2024-05-11T04:56:18.988761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:56:19.455958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
I
152 
U
98 

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 152
60.8%
U 98
39.2%

Length

2024-05-11T04:56:19.877440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:20.176471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 152
60.8%
u 98
39.2%
Distinct83
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T04:56:20.436280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:56:20.798304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
여인숙업
131 
여관업
93 
일반호텔
 
11
관광호텔
 
10
휴양콘도미니엄업
 
4

Length

Max length8
Median length4
Mean length3.7
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
여인숙업 131
52.4%
여관업 93
37.2%
일반호텔 11
 
4.4%
관광호텔 10
 
4.0%
휴양콘도미니엄업 4
 
1.6%
숙박업 기타 1
 
0.4%

Length

2024-05-11T04:56:21.057130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:21.258206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여인숙업 131
52.2%
여관업 93
37.1%
일반호텔 11
 
4.4%
관광호텔 10
 
4.0%
휴양콘도미니엄업 4
 
1.6%
숙박업 1
 
0.4%
기타 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)92.7%
Missing45
Missing (%)18.0%
Infinite0
Infinite (%)0.0%
Mean194536.38
Minimum191519.13
Maximum197075.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:21.591095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191519.13
5-th percentile192399.12
Q1194382.11
median194526.36
Q3194993.02
95-th percentile196740.75
Maximum197075.88
Range5556.7467
Interquartile range (IQR)610.90683

Descriptive statistics

Standard deviation1139.6269
Coefficient of variation (CV)0.0058581689
Kurtosis0.50522574
Mean194536.38
Median Absolute Deviation (MAD)403.3888
Skewness-0.2342953
Sum39879957
Variance1298749.6
MonotonicityNot monotonic
2024-05-11T04:56:22.012586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194574.530081333 2
 
0.8%
194454.969703299 2
 
0.8%
194597.942628915 2
 
0.8%
194586.831531122 2
 
0.8%
194848.133274367 2
 
0.8%
194447.060323027 2
 
0.8%
194457.023858579 2
 
0.8%
194999.4083346 2
 
0.8%
194480.306771392 2
 
0.8%
192397.290057286 2
 
0.8%
Other values (180) 185
74.0%
(Missing) 45
 
18.0%
ValueCountFrequency (%)
191519.132033814 1
0.4%
191604.289576468 1
0.4%
192070.057430303 1
0.4%
192075.651626684 1
0.4%
192112.287100613 1
0.4%
192308.045608077 1
0.4%
192364.592285441 1
0.4%
192388.528876889 1
0.4%
192391.505116576 1
0.4%
192397.290057286 2
0.8%
ValueCountFrequency (%)
197075.878707576 1
0.4%
197062.406516 1
0.4%
197047.270174452 1
0.4%
197037.539093025 1
0.4%
196905.977564996 1
0.4%
196877.162430406 1
0.4%
196828.111633702 1
0.4%
196799.630350773 1
0.4%
196797.885705475 1
0.4%
196792.540708934 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)92.7%
Missing45
Missing (%)18.0%
Infinite0
Infinite (%)0.0%
Mean451466.39
Minimum450404.71
Maximum454759.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:22.426274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450404.71
5-th percentile450443.41
Q1450506.33
median450650.79
Q3451993.6
95-th percentile454431.59
Maximum454759.27
Range4354.5645
Interquartile range (IQR)1487.2721

Descriptive statistics

Standard deviation1328.0874
Coefficient of variation (CV)0.0029417194
Kurtosis0.15938314
Mean451466.39
Median Absolute Deviation (MAD)193.34873
Skewness1.2248719
Sum92550610
Variance1763816.2
MonotonicityNot monotonic
2024-05-11T04:56:22.851363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450458.653697609 2
 
0.8%
450450.019449555 2
 
0.8%
450471.896571617 2
 
0.8%
450464.551719663 2
 
0.8%
450596.325543619 2
 
0.8%
450457.441284914 2
 
0.8%
450494.565629791 2
 
0.8%
450621.380693446 2
 
0.8%
450474.002106087 2
 
0.8%
451993.60064571 2
 
0.8%
Other values (180) 185
74.0%
(Missing) 45
 
18.0%
ValueCountFrequency (%)
450404.707893709 1
0.4%
450415.649392505 1
0.4%
450423.937320003 1
0.4%
450428.281096865 1
0.4%
450430.870126098 1
0.4%
450431.225117309 1
0.4%
450431.708419531 1
0.4%
450435.795072547 1
0.4%
450439.833191026 1
0.4%
450440.740130342 1
0.4%
ValueCountFrequency (%)
454759.272404208 1
0.4%
454650.246355239 1
0.4%
454613.506151917 1
0.4%
454568.619607816 1
0.4%
454558.993051098 1
0.4%
454544.769561853 1
0.4%
454533.360571483 1
0.4%
454458.718616558 1
0.4%
454455.066823351 1
0.4%
454441.785418774 1
0.4%

위생업태명
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
여인숙업
121 
여관업
73 
<NA>
46 
관광호텔
 
5
일반호텔
 
5

Length

Max length4
Median length4
Mean length3.708
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여인숙업 121
48.4%
여관업 73
29.2%
<NA> 46
 
18.4%
관광호텔 5
 
2.0%
일반호텔 5
 
2.0%

Length

2024-05-11T04:56:23.325508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:23.559554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여인숙업 121
48.4%
여관업 73
29.2%
na 46
 
18.4%
관광호텔 5
 
2.0%
일반호텔 5
 
2.0%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.3%
Missing75
Missing (%)30.0%
Infinite0
Infinite (%)0.0%
Mean1.36
Minimum0
Maximum13
Zeros135
Zeros (%)54.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:23.753627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7774958
Coefficient of variation (CV)2.0422763
Kurtosis2.973671
Mean1.36
Median Absolute Deviation (MAD)0
Skewness1.9820308
Sum238
Variance7.7144828
MonotonicityNot monotonic
2024-05-11T04:56:23.976453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 135
54.0%
4 9
 
3.6%
8 7
 
2.8%
5 6
 
2.4%
3 4
 
1.6%
7 4
 
1.6%
9 3
 
1.2%
2 2
 
0.8%
6 2
 
0.8%
10 2
 
0.8%
(Missing) 75
30.0%
ValueCountFrequency (%)
0 135
54.0%
2 2
 
0.8%
3 4
 
1.6%
4 9
 
3.6%
5 6
 
2.4%
6 2
 
0.8%
7 4
 
1.6%
8 7
 
2.8%
9 3
 
1.2%
10 2
 
0.8%
ValueCountFrequency (%)
13 1
 
0.4%
10 2
 
0.8%
9 3
 
1.2%
8 7
2.8%
7 4
1.6%
6 2
 
0.8%
5 6
2.4%
4 9
3.6%
3 4
1.6%
2 2
 
0.8%
Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
135 
<NA>
75 
1
36 
2
 
4

Length

Max length4
Median length1
Mean length1.9
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 135
54.0%
<NA> 75
30.0%
1 36
 
14.4%
2 4
 
1.6%

Length

2024-05-11T04:56:24.285780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:24.623116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 135
54.0%
na 75
30.0%
1 36
 
14.4%
2 4
 
1.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.5%
Missing79
Missing (%)31.6%
Infinite0
Infinite (%)0.0%
Mean0.48538012
Minimum0
Maximum9
Zeros123
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:24.936563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0367184
Coefficient of variation (CV)2.1358897
Kurtosis26.811416
Mean0.48538012
Median Absolute Deviation (MAD)0
Skewness4.1098334
Sum83
Variance1.074785
MonotonicityNot monotonic
2024-05-11T04:56:25.270499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 123
49.2%
1 26
 
10.4%
2 16
 
6.4%
3 4
 
1.6%
4 1
 
0.4%
9 1
 
0.4%
(Missing) 79
31.6%
ValueCountFrequency (%)
0 123
49.2%
1 26
 
10.4%
2 16
 
6.4%
3 4
 
1.6%
4 1
 
0.4%
9 1
 
0.4%
ValueCountFrequency (%)
9 1
 
0.4%
4 1
 
0.4%
3 4
 
1.6%
2 16
 
6.4%
1 26
 
10.4%
0 123
49.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)16.2%
Missing182
Missing (%)72.8%
Infinite0
Infinite (%)0.0%
Mean3.5
Minimum0
Maximum13
Zeros20
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:25.594040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q35.25
95-th percentile9
Maximum13
Range13
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation3.1928091
Coefficient of variation (CV)0.91223117
Kurtosis-0.30201337
Mean3.5
Median Absolute Deviation (MAD)3
Skewness0.65342162
Sum238
Variance10.19403
MonotonicityNot monotonic
2024-05-11T04:56:25.963666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 20
 
8.0%
2 10
 
4.0%
4 10
 
4.0%
8 6
 
2.4%
5 5
 
2.0%
3 5
 
2.0%
7 4
 
1.6%
9 4
 
1.6%
6 2
 
0.8%
13 1
 
0.4%
(Missing) 182
72.8%
ValueCountFrequency (%)
0 20
8.0%
1 1
 
0.4%
2 10
4.0%
3 5
 
2.0%
4 10
4.0%
5 5
 
2.0%
6 2
 
0.8%
7 4
 
1.6%
8 6
 
2.4%
9 4
 
1.6%
ValueCountFrequency (%)
13 1
 
0.4%
9 4
 
1.6%
8 6
2.4%
7 4
 
1.6%
6 2
 
0.8%
5 5
2.0%
4 10
4.0%
3 5
2.0%
2 10
4.0%
1 1
 
0.4%
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
159 
<NA>
86 
1
 
5

Length

Max length4
Median length1
Mean length2.032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 159
63.6%
<NA> 86
34.4%
1 5
 
2.0%

Length

2024-05-11T04:56:26.369534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:26.701724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 159
63.6%
na 86
34.4%
1 5
 
2.0%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
189 
0
56 
1
 
4
2
 
1

Length

Max length4
Median length4
Mean length3.268
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 189
75.6%
0 56
 
22.4%
1 4
 
1.6%
2 1
 
0.4%

Length

2024-05-11T04:56:27.198480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:27.518491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 189
75.6%
0 56
 
22.4%
1 4
 
1.6%
2 1
 
0.4%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)13.7%
Missing53
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean9.2639594
Minimum0
Maximum35
Zeros32
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:28.058933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median9
Q313
95-th percentile21
Maximum35
Range35
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.6025173
Coefficient of variation (CV)0.71271009
Kurtosis0.65062287
Mean9.2639594
Median Absolute Deviation (MAD)4
Skewness0.57735998
Sum1825
Variance43.593235
MonotonicityNot monotonic
2024-05-11T04:56:28.499491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 32
12.8%
11 15
 
6.0%
8 15
 
6.0%
10 15
 
6.0%
6 14
 
5.6%
12 12
 
4.8%
13 11
 
4.4%
16 10
 
4.0%
5 10
 
4.0%
14 9
 
3.6%
Other values (17) 54
21.6%
(Missing) 53
21.2%
ValueCountFrequency (%)
0 32
12.8%
1 1
 
0.4%
2 6
 
2.4%
3 6
 
2.4%
4 1
 
0.4%
5 10
 
4.0%
6 14
5.6%
7 5
 
2.0%
8 15
6.0%
9 9
 
3.6%
ValueCountFrequency (%)
35 1
 
0.4%
28 1
 
0.4%
27 2
 
0.8%
25 1
 
0.4%
22 2
 
0.8%
21 5
2.0%
20 1
 
0.4%
19 1
 
0.4%
18 4
1.6%
17 5
2.0%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)19.6%
Missing71
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean10.486034
Minimum0
Maximum500
Zeros110
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:28.904483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314.5
95-th percentile33.3
Maximum500
Range500
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation38.687506
Coefficient of variation (CV)3.6894318
Kurtosis145.91928
Mean10.486034
Median Absolute Deviation (MAD)0
Skewness11.535052
Sum1877
Variance1496.7231
MonotonicityNot monotonic
2024-05-11T04:56:29.376012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 110
44.0%
14 6
 
2.4%
15 5
 
2.0%
11 4
 
1.6%
17 3
 
1.2%
12 3
 
1.2%
19 3
 
1.2%
9 3
 
1.2%
4 3
 
1.2%
21 3
 
1.2%
Other values (25) 36
 
14.4%
(Missing) 71
28.4%
ValueCountFrequency (%)
0 110
44.0%
4 3
 
1.2%
6 2
 
0.8%
8 1
 
0.4%
9 3
 
1.2%
10 2
 
0.8%
11 4
 
1.6%
12 3
 
1.2%
14 6
 
2.4%
15 5
 
2.0%
ValueCountFrequency (%)
500 1
0.4%
55 1
0.4%
47 1
0.4%
45 1
0.4%
44 1
0.4%
41 1
0.4%
38 1
0.4%
37 1
0.4%
36 1
0.4%
33 1
0.4%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)17.9%
Missing71
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean9.4692737
Minimum0
Maximum503
Zeros110
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:29.764283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313
95-th percentile28.2
Maximum503
Range503
Interquartile range (IQR)13

Descriptive statistics

Standard deviation38.534574
Coefficient of variation (CV)4.0694329
Kurtosis153.30985
Mean9.4692737
Median Absolute Deviation (MAD)0
Skewness11.950257
Sum1695
Variance1484.9134
MonotonicityNot monotonic
2024-05-11T04:56:30.190685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 110
44.0%
10 4
 
1.6%
5 4
 
1.6%
20 4
 
1.6%
16 4
 
1.6%
17 4
 
1.6%
25 4
 
1.6%
21 4
 
1.6%
12 3
 
1.2%
8 3
 
1.2%
Other values (22) 35
 
14.0%
(Missing) 71
28.4%
ValueCountFrequency (%)
0 110
44.0%
1 1
 
0.4%
2 2
 
0.8%
5 4
 
1.6%
6 2
 
0.8%
8 3
 
1.2%
9 2
 
0.8%
10 4
 
1.6%
11 2
 
0.8%
12 3
 
1.2%
ValueCountFrequency (%)
503 1
0.4%
50 1
0.4%
39 1
0.4%
38 1
0.4%
35 1
0.4%
34 1
0.4%
33 2
0.8%
30 1
0.4%
28 1
0.4%
27 2
0.8%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.0%
Missing46
Missing (%)18.4%
Memory size632.0 B
True
175 
False
29 
(Missing)
46 
ValueCountFrequency (%)
True 175
70.0%
False 29
 
11.6%
(Missing) 46
 
18.4%
2024-05-11T04:56:30.729466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)17.8%
Missing48
Missing (%)19.2%
Infinite0
Infinite (%)0.0%
Mean22.861386
Minimum0
Maximum1533
Zeros24
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T04:56:31.023540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median12
Q318.75
95-th percentile49.9
Maximum1533
Range1533
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation107.7214
Coefficient of variation (CV)4.7119367
Kurtosis194.94017
Mean22.861386
Median Absolute Deviation (MAD)4
Skewness13.846315
Sum4618
Variance11603.901
MonotonicityNot monotonic
2024-05-11T04:56:31.399596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 24
 
9.6%
10 18
 
7.2%
12 15
 
6.0%
11 15
 
6.0%
8 14
 
5.6%
9 12
 
4.8%
13 10
 
4.0%
20 10
 
4.0%
14 10
 
4.0%
17 7
 
2.8%
Other values (26) 67
26.8%
(Missing) 48
19.2%
ValueCountFrequency (%)
0 24
9.6%
5 3
 
1.2%
6 6
 
2.4%
7 3
 
1.2%
8 14
5.6%
9 12
4.8%
10 18
7.2%
11 15
6.0%
12 15
6.0%
13 10
4.0%
ValueCountFrequency (%)
1533 1
 
0.4%
100 1
 
0.4%
76 1
 
0.4%
70 1
 
0.4%
66 2
0.8%
60 1
 
0.4%
52 1
 
0.4%
50 3
1.2%
48 1
 
0.4%
40 2
0.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
210 
임대
22 
자가
 
18

Length

Max length4
Median length4
Mean length3.68
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> 210
84.0%
임대 22
 
8.8%
자가 18
 
7.2%

Length

2024-05-11T04:56:31.754202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:32.091246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 210
84.0%
임대 22
 
8.8%
자가 18
 
7.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
185 
0
65 

Length

Max length4
Median length4
Mean length3.22
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> 185
74.0%
0 65
 
26.0%

Length

2024-05-11T04:56:32.376816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:32.576374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 185
74.0%
0 65
 
26.0%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
247 
0
 
3

Length

Max length4
Median length4
Mean length3.964
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> 247
98.8%
0 3
 
1.2%

Length

2024-05-11T04:56:32.784307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:33.050633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
98.8%
0 3
 
1.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
247 
0
 
3

Length

Max length4
Median length4
Mean length3.964
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> 247
98.8%
0 3
 
1.2%

Length

2024-05-11T04:56:33.452780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:33.741940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
98.8%
0 3
 
1.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
189 
0
61 

Length

Max length4
Median length4
Mean length3.268
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> 189
75.6%
0 61
 
24.4%

Length

2024-05-11T04:56:34.096679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:34.432530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 189
75.6%
0 61
 
24.4%

침대수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
189 
0
61 

Length

Max length4
Median length4
Mean length3.268
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> 189
75.6%
0 61
 
24.4%

Length

2024-05-11T04:56:34.791785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:35.115438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 189
75.6%
0 61
 
24.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing46
Missing (%)18.4%
Memory size632.0 B
False
204 
(Missing)
46 
ValueCountFrequency (%)
False 204
81.6%
(Missing) 46
 
18.4%
2024-05-11T04:56:35.396457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031200003120000-201-1962-0006719621115<NA>3폐업2폐업20090706<NA><NA><NA>02 3091740126.81120802서울특별시 서대문구 남가좌동 124-269번지<NA><NA>제일2003-06-25 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>1800Y18<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131200003120000-201-1963-0004019630730<NA>3폐업2폐업19990527<NA><NA><NA>0203622387.00120020서울특별시 서대문구 미근동 186-0번지<NA><NA>서대문2002-04-09 00:00:00I2018-08-31 23:59:59.0여인숙업197037.539093451333.74306여인숙업000<NA>0<NA>1400N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231200003120000-201-1963-0004619630628<NA>3폐업2폐업20040917<NA><NA><NA>020364272759.53120819서울특별시 서대문구 북아현동 126-18번지<NA><NA>송도장2003-06-14 00:00:00I2018-08-31 23:59:59.0여인숙업196160.903589450588.901582여인숙업<NA><NA><NA><NA><NA><NA>12<NA><NA>Y12<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331200003120000-201-1963-0119919630627<NA>3폐업2폐업19931213<NA><NA><NA>0203624056.00120840서울특별시 서대문구 충정로3가 317-0번지<NA><NA>복현2001-10-04 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>1100Y11<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431200003120000-201-1964-0008019640626<NA>3폐업2폐업20050216<NA><NA><NA>0203136951124.10120808서울특별시 서대문구 대현동 53-19번지<NA><NA>성민장2008-01-17 11:27:38I2018-08-31 23:59:59.0여인숙업195199.621501450662.619706여인숙업000<NA>0<NA>1600Y16<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531200003120000-201-1964-0008419640317<NA>3폐업2폐업19940404<NA><NA><NA>0203628024.00120808서울특별시 서대문구 대현동 34-23번지<NA><NA>안도2001-10-04 00:00:00I2018-08-31 23:59:59.0여인숙업195047.001271450799.549308여인숙업000<NA>0<NA>600Y6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631200003120000-201-1964-0117319640601<NA>3폐업2폐업20050317<NA><NA><NA>020392108329.10120819서울특별시 서대문구 북아현동 130-19번지<NA><NA>금강2003-06-14 00:00:00I2018-08-31 23:59:59.0여인숙업196101.903849450727.635046여인숙업<NA><NA><NA><NA><NA><NA>6<NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731200003120000-201-1964-0118319641114<NA>3폐업2폐업20180501<NA><NA><NA>02 362200068.28120040서울특별시 서대문구 천연동 13-13번지서울특별시 서대문구 통일로 173-54 (천연동)3734원앙2018-05-01 09:31:46I2018-08-31 23:59:59.0여인숙업196582.719397451843.277743여인숙업0012001100Y11<NA><NA><NA><NA>0<NA><NA>00N
831200003120000-201-1965-0003919650810<NA>3폐업2폐업19931125<NA><NA><NA>0203927713.00120833서울특별시 서대문구 창천동 2-2번지<NA><NA>개성2001-10-04 00:00:00I2018-08-31 23:59:59.0여인숙업194481.546942450761.182989여인숙업000<NA>0<NA>0141N14<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931200003120000-201-1965-0116819650810<NA>3폐업2폐업20010924<NA><NA><NA>0203340741.00120834서울특별시 서대문구 창천동 30-4번지<NA><NA>경화2002-04-09 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000<NA>0<NA>0170Y17<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
24031200003120000-201-2016-0000120160512<NA>1영업/정상1영업<NA><NA><NA><NA>02 39311991,785.00120833서울특별시 서대문구 창천동 18-81번지서울특별시 서대문구 연세로2가길 3 (창천동)3779신촌라싸 관광호텔2017-06-23 13:23:03I2018-08-31 23:59:59.0관광호텔194391.169588450428.281097관광호텔132113120410N0<NA><NA><NA>자가00000N
24131200003120000-201-2016-0000220161019<NA>1영업/정상1영업<NA><NA><NA><NA>070 88123755402.48120834서울특별시 서대문구 창천동 31-92 8,9,10층서울특별시 서대문구 명물길 19, 8,9,10층 (창천동)377624게스트하우스 신촌에비뉴엘점2022-11-15 09:04:23U2021-10-31 23:07:00.0관광호텔194425.547743450629.487978<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24231200003120000-201-2017-000012017-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>512.62120-809서울특별시 서대문구 대현동 101-17 8층서울특별시 서대문구 신촌로 155, 8층 (대현동)3766서울그랜드호스텔이대2024-01-18 13:48:25U2023-11-30 22:00:00.0관광호텔194929.75081450514.690947<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24331200003120000-201-2017-000022017-06-13<NA>1영업/정상1영업<NA><NA><NA><NA>02 393 2415512.62120-809서울특별시 서대문구 대현동 101-17 6층서울특별시 서대문구 신촌로 155, 6층 (대현동)37662023-08-07 16:48:00U2022-12-08 00:09:00.0관광호텔194929.75081450514.690947<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24431200003120000-201-2018-0000120180619<NA>1영업/정상1영업<NA><NA><NA><NA>02 313 70031,670.64120833서울특별시 서대문구 창천동 29-56번지서울특별시 서대문구 연세로2나길 5 (창천동)3779밀하우스2019-12-30 17:04:15U2020-01-01 02:40:00.0관광호텔194447.060323450457.441285관광호텔0091110470N0<NA><NA><NA>자가00000N
24531200003120000-201-2020-0000120200319<NA>1영업/정상1영업<NA><NA><NA><NA>021,324.68120809서울특별시 서대문구 대현동 104-48번지 은하빌딩서울특별시 서대문구 신촌로 141, 은하빌딩 6,7,8층 (대현동)3780위고인 호스텔2020-03-19 12:51:33I2020-03-21 00:23:22.0관광호텔194770.272306450529.307303관광호텔00<NA><NA><NA><NA>0450N0<NA><NA><NA>자가00000N
24631200003120000-214-2015-000012015-01-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 36467301356.30120-809서울특별시 서대문구 대현동 104-5서울특별시 서대문구 신촌역로 7 (대현동)3780신촌 에버에이트 레지던스호텔2023-02-07 10:01:52U2022-12-02 00:09:00.0휴양콘도미니엄업194855.910937450573.690449<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24731200003120000-214-2020-000012020-03-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>304.70120-809서울특별시 서대문구 대현동 90-37 4,5,6,7,8층서울특별시 서대문구 이화여대1안길 15, 4,5,6,7,8층 (대현동)3766디케이하우스2023-02-07 10:03:55U2022-12-02 00:09:00.0휴양콘도미니엄업195004.191374450587.216691<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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