Overview

Dataset statistics

Number of variables44
Number of observations88
Missing cells918
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.4 KiB
Average record size in memory377.5 B

Variable types

Categorical20
Text6
DateTime3
Unsupported8
Numeric6
Boolean1

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,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18554/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신일자 is highly imbalanced (52.6%)Imbalance
총인원 is highly imbalanced (59.9%)Imbalance
본사종업원수 is highly imbalanced (59.9%)Imbalance
공장사무직종업원수 is highly imbalanced (59.9%)Imbalance
공장판매직종업원수 is highly imbalanced (59.9%)Imbalance
공장생산직종업원수 is highly imbalanced (59.9%)Imbalance
보증액 is highly imbalanced (59.9%)Imbalance
월세액 is highly imbalanced (59.9%)Imbalance
다중이용업소여부 is highly imbalanced (82.4%)Imbalance
인허가취소일자 has 88 (100.0%) missing valuesMissing
폐업일자 has 21 (23.9%) missing valuesMissing
휴업시작일자 has 88 (100.0%) missing valuesMissing
휴업종료일자 has 88 (100.0%) missing valuesMissing
재개업일자 has 88 (100.0%) missing valuesMissing
전화번호 has 14 (15.9%) missing valuesMissing
도로명주소 has 51 (58.0%) missing valuesMissing
도로명우편번호 has 52 (59.1%) missing valuesMissing
좌표정보(X) has 3 (3.4%) missing valuesMissing
좌표정보(Y) has 3 (3.4%) missing valuesMissing
남성종사자수 has 23 (26.1%) missing valuesMissing
여성종사자수 has 23 (26.1%) missing valuesMissing
건물소유구분명 has 88 (100.0%) missing valuesMissing
다중이용업소여부 has 12 (13.6%) missing valuesMissing
시설총규모 has 12 (13.6%) missing valuesMissing
전통업소지정번호 has 88 (100.0%) missing valuesMissing
전통업소주된음식 has 88 (100.0%) missing valuesMissing
홈페이지 has 88 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 35 (39.8%) zerosZeros
여성종사자수 has 34 (38.6%) zerosZeros

Reproduction

Analysis started2024-04-06 13:10:13.242069
Analysis finished2024-04-06 13:10:14.121495
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
3020000
88 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 88
100.0%

Length

2024-04-06T22:10:14.213902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:14.384323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 88
100.0%

관리번호
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T22:10:14.676501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1936
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

Unique88 ?
Unique (%)100.0%

Sample

1st row3020000-102-1967-03511
2nd row3020000-102-1967-03531
3rd row3020000-102-1967-03577
4th row3020000-102-1968-03535
5th row3020000-102-1968-03553
ValueCountFrequency (%)
3020000-102-1967-03511 1
 
1.1%
3020000-102-1967-03531 1
 
1.1%
3020000-102-2000-07462 1
 
1.1%
3020000-102-2000-07377 1
 
1.1%
3020000-102-2000-07317 1
 
1.1%
3020000-102-1999-07251 1
 
1.1%
3020000-102-1999-07250 1
 
1.1%
3020000-102-1999-07228 1
 
1.1%
3020000-102-1999-07221 1
 
1.1%
3020000-102-1999-03541 1
 
1.1%
Other values (78) 78
88.6%
2024-04-06T22:10:15.188868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 723
37.3%
- 264
 
13.6%
2 241
 
12.4%
1 190
 
9.8%
3 172
 
8.9%
9 99
 
5.1%
5 75
 
3.9%
7 69
 
3.6%
8 46
 
2.4%
4 29
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1672
86.4%
Dash Punctuation 264
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 723
43.2%
2 241
 
14.4%
1 190
 
11.4%
3 172
 
10.3%
9 99
 
5.9%
5 75
 
4.5%
7 69
 
4.1%
8 46
 
2.8%
4 29
 
1.7%
6 28
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1936
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 723
37.3%
- 264
 
13.6%
2 241
 
12.4%
1 190
 
9.8%
3 172
 
8.9%
9 99
 
5.1%
5 75
 
3.9%
7 69
 
3.6%
8 46
 
2.4%
4 29
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 723
37.3%
- 264
 
13.6%
2 241
 
12.4%
1 190
 
9.8%
3 172
 
8.9%
9 99
 
5.1%
5 75
 
3.9%
7 69
 
3.6%
8 46
 
2.4%
4 29
 
1.5%

인허가일자
Date

Distinct83
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
Minimum1967-07-05 00:00:00
Maximum2016-10-26 00:00:00
2024-04-06T22:10:15.450479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:10:15.764098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
3
67 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 67
76.1%
1 21
 
23.9%

Length

2024-04-06T22:10:16.002943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:16.197984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 67
76.1%
1 21
 
23.9%

영업상태명
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
폐업
67 
영업/정상
21 

Length

Max length5
Median length2
Mean length2.7159091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 67
76.1%
영업/정상 21
 
23.9%

Length

2024-04-06T22:10:16.430347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:16.615847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 67
76.1%
영업/정상 21
 
23.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
2
67 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 67
76.1%
1 21
 
23.9%

Length

2024-04-06T22:10:16.841891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:17.065332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 67
76.1%
1 21
 
23.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
폐업
67 
영업
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 67
76.1%
영업 21
 
23.9%

Length

2024-04-06T22:10:17.254529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:17.438699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 67
76.1%
영업 21
 
23.9%

폐업일자
Date

MISSING 

Distinct64
Distinct (%)95.5%
Missing21
Missing (%)23.9%
Memory size836.0 B
Minimum1989-08-18 00:00:00
Maximum2024-03-04 00:00:00
2024-04-06T22:10:17.646353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:10:17.889401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

전화번호
Text

MISSING 

Distinct69
Distinct (%)93.2%
Missing14
Missing (%)15.9%
Memory size836.0 B
2024-04-06T22:10:18.280205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.4594595
Min length2

Characters and Unicode

Total characters700
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

Unique67 ?
Unique (%)90.5%

Sample

1st row0207959155
2nd row0207949705
3rd row02
4th row02 7927988
5th row0207933885
ValueCountFrequency (%)
02 53
43.1%
7940171 2
 
1.6%
7908285 1
 
0.8%
0207959155 1
 
0.8%
7199034 1
 
0.8%
7126105 1
 
0.8%
0232739051 1
 
0.8%
0207953076 1
 
0.8%
0207125603 1
 
0.8%
7189960 1
 
0.8%
Other values (60) 60
48.8%
2024-04-06T22:10:18.885008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 121
17.3%
2 110
15.7%
7 103
14.7%
9 68
9.7%
1 58
8.3%
3 51
7.3%
50
7.1%
5 45
 
6.4%
4 34
 
4.9%
6 34
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 650
92.9%
Space Separator 50
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 121
18.6%
2 110
16.9%
7 103
15.8%
9 68
10.5%
1 58
8.9%
3 51
7.8%
5 45
 
6.9%
4 34
 
5.2%
6 34
 
5.2%
8 26
 
4.0%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 121
17.3%
2 110
15.7%
7 103
14.7%
9 68
9.7%
1 58
8.3%
3 51
7.3%
50
7.1%
5 45
 
6.4%
4 34
 
4.9%
6 34
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 121
17.3%
2 110
15.7%
7 103
14.7%
9 68
9.7%
1 58
8.3%
3 51
7.3%
50
7.1%
5 45
 
6.4%
4 34
 
4.9%
6 34
 
4.9%

소재지면적
Text

Distinct86
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T22:10:19.330969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.6477273
Min length4

Characters and Unicode

Total characters497
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

Unique84 ?
Unique (%)95.5%

Sample

1st row109.77
2nd row184.92
3rd row235.44
4th row265.72
5th row196.90
ValueCountFrequency (%)
57.74 2
 
2.3%
962.97 2
 
2.3%
188.29 1
 
1.1%
647.40 1
 
1.1%
109.77 1
 
1.1%
121.89 1
 
1.1%
57.82 1
 
1.1%
68.92 1
 
1.1%
46.46 1
 
1.1%
59.35 1
 
1.1%
Other values (76) 76
86.4%
2024-04-06T22:10:20.035850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 88
17.7%
1 57
11.5%
2 49
9.9%
4 45
9.1%
0 45
9.1%
7 39
7.8%
3 39
7.8%
6 35
 
7.0%
8 35
 
7.0%
9 34
 
6.8%
Other values (2) 31
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 407
81.9%
Other Punctuation 90
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 57
14.0%
2 49
12.0%
4 45
11.1%
0 45
11.1%
7 39
9.6%
3 39
9.6%
6 35
8.6%
8 35
8.6%
9 34
8.4%
5 29
7.1%
Other Punctuation
ValueCountFrequency (%)
. 88
97.8%
, 2
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 497
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 88
17.7%
1 57
11.5%
2 49
9.9%
4 45
9.1%
0 45
9.1%
7 39
7.8%
3 39
7.8%
6 35
 
7.0%
8 35
 
7.0%
9 34
 
6.8%
Other values (2) 31
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 88
17.7%
1 57
11.5%
2 49
9.9%
4 45
9.1%
0 45
9.1%
7 39
7.8%
3 39
7.8%
6 35
 
7.0%
8 35
 
7.0%
9 34
 
6.8%
Other values (2) 31
 
6.2%

소재지우편번호
Categorical

Distinct30
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
140821
14 
140863
6 
140847
6 
140871
 
5
140892
 
4
Other values (25)
53 

Length

Max length7
Median length6
Mean length6.0681818
Min length6

Unique

Unique11 ?
Unique (%)12.5%

Sample

1st row140858
2nd row140893
3rd row140-858
4th row140807
5th row140-858

Common Values

ValueCountFrequency (%)
140821 14
15.9%
140863 6
 
6.8%
140847 6
 
6.8%
140871 5
 
5.7%
140892 4
 
4.5%
140872 4
 
4.5%
140807 4
 
4.5%
140848 4
 
4.5%
140806 4
 
4.5%
140160 4
 
4.5%
Other values (20) 33
37.5%

Length

2024-04-06T22:10:20.252539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
140821 14
15.9%
140847 6
 
6.8%
140863 6
 
6.8%
140871 5
 
5.7%
140892 4
 
4.5%
140872 4
 
4.5%
140807 4
 
4.5%
140848 4
 
4.5%
140806 4
 
4.5%
140160 4
 
4.5%
Other values (20) 33
37.5%

지번주소
Text

Distinct85
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T22:10:20.705336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length26.670455
Min length16

Characters and Unicode

Total characters2347
Distinct characters54
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

Unique83 ?
Unique (%)94.3%

Sample

1st row서울특별시 용산구 이태원동 136-2 (지상1층)
2nd row서울특별시 용산구 한남동 736-11번지 (지상3층)
3rd row서울특별시 용산구 이태원동 136-46 (지상1층)
4th row서울특별시 용산구 갈월동 98-1번지
5th row서울특별시 용산구 이태원동 127-2
ValueCountFrequency (%)
서울특별시 88
21.5%
용산구 88
21.5%
지하1층 23
 
5.6%
이태원동 17
 
4.1%
동자동 15
 
3.7%
한남동 14
 
3.4%
한강로2가 13
 
3.2%
지상1층 10
 
2.4%
갈월동 8
 
2.0%
원효로2가 6
 
1.5%
Other values (104) 128
31.2%
2024-04-06T22:10:21.488733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
398
 
17.0%
지 114
 
4.9%
1 103
 
4.4%
별 90
 
3.8%
서 89
 
3.8%
시 88
 
3.7%
용 88
 
3.7%
산 88
 
3.7%
구 88
 
3.7%
울 88
 
3.7%
Other values (44) 1113
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1311
55.9%
Decimal Number 457
 
19.5%
Space Separator 398
 
17.0%
Dash Punctuation 87
 
3.7%
Open Punctuation 43
 
1.8%
Close Punctuation 43
 
1.8%
Other Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 114
 
8.7%
별 90
 
6.9%
서 89
 
6.8%
시 88
 
6.7%
용 88
 
6.7%
산 88
 
6.7%
구 88
 
6.7%
울 88
 
6.7%
특 88
 
6.7%
동 77
 
5.9%
Other values (29) 413
31.5%
Decimal Number
ValueCountFrequency (%)
1 103
22.5%
3 79
17.3%
2 77
16.8%
4 42
9.2%
6 37
 
8.1%
7 33
 
7.2%
9 28
 
6.1%
8 20
 
4.4%
5 19
 
4.2%
0 19
 
4.2%
Space Separator
ValueCountFrequency (%)
398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1311
55.9%
Common 1036
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 114
 
8.7%
별 90
 
6.9%
서 89
 
6.8%
시 88
 
6.7%
용 88
 
6.7%
산 88
 
6.7%
구 88
 
6.7%
울 88
 
6.7%
특 88
 
6.7%
동 77
 
5.9%
Other values (29) 413
31.5%
Common
ValueCountFrequency (%)
398
38.4%
1 103
 
9.9%
- 87
 
8.4%
3 79
 
7.6%
2 77
 
7.4%
( 43
 
4.2%
) 43
 
4.2%
4 42
 
4.1%
6 37
 
3.6%
7 33
 
3.2%
Other values (5) 94
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1311
55.9%
ASCII 1036
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
398
38.4%
1 103
 
9.9%
- 87
 
8.4%
3 79
 
7.6%
2 77
 
7.4%
( 43
 
4.2%
) 43
 
4.2%
4 42
 
4.1%
6 37
 
3.6%
7 33
 
3.2%
Other values (5) 94
 
9.1%
Hangul
ValueCountFrequency (%)
지 114
 
8.7%
별 90
 
6.9%
서 89
 
6.8%
시 88
 
6.7%
용 88
 
6.7%
산 88
 
6.7%
구 88
 
6.7%
울 88
 
6.7%
특 88
 
6.7%
동 77
 
5.9%
Other values (29) 413
31.5%

도로명주소
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing51
Missing (%)58.0%
Memory size836.0 B
2024-04-06T22:10:22.206523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length34.459459
Min length26

Characters and Unicode

Total characters1275
Distinct characters75
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

Unique37 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 우사단로14길 16 (이태원동,(지상1층))
2nd row서울특별시 용산구 우사단로 40 (이태원동,(지상1층))
3rd row서울특별시 용산구 이태원로 192, 지하1층 (이태원동)
4th row서울특별시 용산구 우사단로 42 (이태원동,(지상2층))
5th row서울특별시 용산구 새창로 131-6 (원효로2가, 84-1 지하1층)
ValueCountFrequency (%)
서울특별시 37
 
17.4%
용산구 37
 
17.4%
한강대로 9
 
4.2%
이태원로 8
 
3.8%
지하1층 6
 
2.8%
이태원동 5
 
2.3%
원효로2가,(지하1층 4
 
1.9%
한남동 3
 
1.4%
새창로 3
 
1.4%
이태원동,(지상1층 3
 
1.4%
Other values (83) 98
46.0%
2024-04-06T22:10:22.710761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
13.8%
1 62
 
4.9%
( 61
 
4.8%
) 61
 
4.8%
로 47
 
3.7%
2 45
 
3.5%
, 41
 
3.2%
별 39
 
3.1%
서 38
 
3.0%
구 37
 
2.9%
Other values (65) 668
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 721
56.5%
Decimal Number 201
 
15.8%
Space Separator 176
 
13.8%
Open Punctuation 61
 
4.8%
Close Punctuation 61
 
4.8%
Other Punctuation 41
 
3.2%
Dash Punctuation 14
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 47
 
6.5%
별 39
 
5.4%
서 38
 
5.3%
구 37
 
5.1%
산 37
 
5.1%
특 37
 
5.1%
용 37
 
5.1%
울 37
 
5.1%
시 37
 
5.1%
층 35
 
4.9%
Other values (50) 340
47.2%
Decimal Number
ValueCountFrequency (%)
1 62
30.8%
2 45
22.4%
3 27
13.4%
4 16
 
8.0%
6 14
 
7.0%
8 9
 
4.5%
7 8
 
4.0%
9 7
 
3.5%
5 7
 
3.5%
0 6
 
3.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 721
56.5%
Common 554
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 47
 
6.5%
별 39
 
5.4%
서 38
 
5.3%
구 37
 
5.1%
산 37
 
5.1%
특 37
 
5.1%
용 37
 
5.1%
울 37
 
5.1%
시 37
 
5.1%
층 35
 
4.9%
Other values (50) 340
47.2%
Common
ValueCountFrequency (%)
176
31.8%
1 62
 
11.2%
( 61
 
11.0%
) 61
 
11.0%
2 45
 
8.1%
, 41
 
7.4%
3 27
 
4.9%
4 16
 
2.9%
- 14
 
2.5%
6 14
 
2.5%
Other values (5) 37
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 721
56.5%
ASCII 554
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
31.8%
1 62
 
11.2%
( 61
 
11.0%
) 61
 
11.0%
2 45
 
8.1%
, 41
 
7.4%
3 27
 
4.9%
4 16
 
2.9%
- 14
 
2.5%
6 14
 
2.5%
Other values (5) 37
 
6.7%
Hangul
ValueCountFrequency (%)
로 47
 
6.5%
별 39
 
5.4%
서 38
 
5.3%
구 37
 
5.1%
산 37
 
5.1%
특 37
 
5.1%
용 37
 
5.1%
울 37
 
5.1%
시 37
 
5.1%
층 35
 
4.9%
Other values (50) 340
47.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)55.6%
Missing52
Missing (%)59.1%
Infinite0
Infinite (%)0.0%
Mean4368.7222
Minimum4320
Maximum4427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:22.935884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4320
5-th percentile4320
Q14349.75
median4364
Q34394
95-th percentile4409.25
Maximum4427
Range107
Interquartile range (IQR)44.25

Descriptive statistics

Standard deviation29.856429
Coefficient of variation (CV)0.0068341331
Kurtosis-0.82851718
Mean4368.7222
Median Absolute Deviation (MAD)18.5
Skewness0.019292039
Sum157274
Variance891.40635
MonotonicityNot monotonic
2024-04-06T22:10:23.181754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
4320 4
 
4.5%
4400 3
 
3.4%
4352 3
 
3.4%
4363 3
 
3.4%
4405 3
 
3.4%
4349 2
 
2.3%
4390 2
 
2.3%
4364 2
 
2.3%
4382 2
 
2.3%
4350 2
 
2.3%
Other values (10) 10
 
11.4%
(Missing) 52
59.1%
ValueCountFrequency (%)
4320 4
4.5%
4322 1
 
1.1%
4345 1
 
1.1%
4347 1
 
1.1%
4349 2
2.3%
4350 2
2.3%
4352 3
3.4%
4363 3
3.4%
4364 2
2.3%
4366 1
 
1.1%
ValueCountFrequency (%)
4427 1
 
1.1%
4419 1
 
1.1%
4406 1
 
1.1%
4405 3
3.4%
4400 3
3.4%
4392 1
 
1.1%
4390 2
2.3%
4382 2
2.3%
4373 1
 
1.1%
4367 1
 
1.1%

사업장명
Text

Distinct86
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T22:10:23.631568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length4.5568182
Min length1

Characters and Unicode

Total characters401
Distinct characters175
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)95.5%

Sample

1st row그랜드올아프리클럽
2nd row제임스
3rd row킹크럽
4th row황금마차
5th row퍼블릭서울
ValueCountFrequency (%)
탈렌트 2
 
2.1%
가요리믹스 2
 
2.1%
백악관 2
 
2.1%
이태원별밤 1
 
1.0%
데이앤나이트 1
 
1.0%
동경 1
 
1.0%
타임 1
 
1.0%
백제 1
 
1.0%
세븐 1
 
1.0%
쎈스 1
 
1.0%
Other values (83) 83
86.5%
2024-04-06T22:10:24.334132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 19
 
4.7%
스 14
 
3.5%
크 9
 
2.2%
럽 8
 
2.0%
8
 
2.0%
지 7
 
1.7%
드 7
 
1.7%
도 6
 
1.5%
가 6
 
1.5%
리 6
 
1.5%
Other values (165) 311
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 377
94.0%
Space Separator 8
 
2.0%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Lowercase Letter 4
 
1.0%
Decimal Number 3
 
0.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
5.0%
스 14
 
3.7%
크 9
 
2.4%
럽 8
 
2.1%
지 7
 
1.9%
드 7
 
1.9%
도 6
 
1.6%
가 6
 
1.6%
리 6
 
1.6%
카 6
 
1.6%
Other values (155) 289
76.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
g 1
25.0%
a 1
25.0%
c 1
25.0%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 377
94.0%
Common 20
 
5.0%
Latin 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 19
 
5.0%
스 14
 
3.7%
크 9
 
2.4%
럽 8
 
2.1%
지 7
 
1.9%
드 7
 
1.9%
도 6
 
1.6%
가 6
 
1.6%
리 6
 
1.6%
카 6
 
1.6%
Other values (155) 289
76.7%
Common
ValueCountFrequency (%)
8
40.0%
) 4
20.0%
( 4
20.0%
0 2
 
10.0%
- 1
 
5.0%
2 1
 
5.0%
Latin
ValueCountFrequency (%)
e 1
25.0%
g 1
25.0%
a 1
25.0%
c 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 377
94.0%
ASCII 24
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 19
 
5.0%
스 14
 
3.7%
크 9
 
2.4%
럽 8
 
2.1%
지 7
 
1.9%
드 7
 
1.9%
도 6
 
1.6%
가 6
 
1.6%
리 6
 
1.6%
카 6
 
1.6%
Other values (155) 289
76.7%
ASCII
ValueCountFrequency (%)
8
33.3%
) 4
16.7%
( 4
16.7%
0 2
 
8.3%
- 1
 
4.2%
2 1
 
4.2%
e 1
 
4.2%
g 1
 
4.2%
a 1
 
4.2%
c 1
 
4.2%

최종수정일자
Date

Distinct68
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
Minimum1999-02-03 00:00:00
Maximum2024-03-04 09:20:46
2024-04-06T22:10:24.516601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:10:24.731805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
I
62 
U
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 62
70.5%
U 26
29.5%

Length

2024-04-06T22:10:24.976989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:25.165352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 62
70.5%
u 26
29.5%

데이터갱신일자
Categorical

IMBALANCE 

Distinct24
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
2018-08-31 23:59:59.0
62 
2021-11-30 02:40:00.0
 
4
2022-12-06 21:00:00.0
 
1
2023-12-01 00:04:00.0
 
1
2021-08-29 02:40:00.0
 
1
Other values (19)
19 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique22 ?
Unique (%)25.0%

Sample

1st row2021-12-07 00:07:00.0
2nd row2018-08-31 23:59:59.0
3rd row2022-12-06 21:00:00.0
4th row2018-08-31 23:59:59.0
5th row2023-12-01 00:04:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 62
70.5%
2021-11-30 02:40:00.0 4
 
4.5%
2022-12-06 21:00:00.0 1
 
1.1%
2023-12-01 00:04:00.0 1
 
1.1%
2021-08-29 02:40:00.0 1
 
1.1%
2018-10-07 02:36:58.0 1
 
1.1%
2020-06-27 02:40:00.0 1
 
1.1%
2021-12-09 00:03:00.0 1
 
1.1%
2021-06-25 02:40:00.0 1
 
1.1%
2021-08-25 02:40:00.0 1
 
1.1%
Other values (14) 14
 
15.9%

Length

2024-04-06T22:10:25.437802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 62
35.2%
23:59:59.0 62
35.2%
02:40:00.0 12
 
6.8%
2021-11-30 4
 
2.3%
22:03:00.0 2
 
1.1%
2021-12-03 2
 
1.1%
00:06:00.0 2
 
1.1%
2023-12-01 2
 
1.1%
21:00:00.0 2
 
1.1%
2019-07-06 1
 
0.6%
Other values (25) 25
14.2%

업태구분명
Categorical

Distinct10
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size836.0 B
룸살롱
22 
스텐드바
21 
카바레
16 
간이주점
8 
비어(바)살롱
7 
Other values (5)
14 

Length

Max length12
Median length9
Mean length4.6818182
Min length2

Unique

Unique3 ?
Unique (%)3.4%

Sample

1st row스텐드바
2nd row카바레
3rd row카바레
4th row스텐드바
5th row관광호텔나이트(카바레)

Common Values

ValueCountFrequency (%)
룸살롱 22
25.0%
스텐드바 21
23.9%
카바레 16
18.2%
간이주점 8
 
9.1%
비어(바)살롱 7
 
8.0%
관광호텔나이트(디스코) 6
 
6.8%
고고(디스코)클럽 5
 
5.7%
관광호텔나이트(카바레) 1
 
1.1%
요정 1
 
1.1%
기타 1
 
1.1%

Length

2024-04-06T22:10:25.710571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:26.034012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
룸살롱 22
25.0%
스텐드바 21
23.9%
카바레 16
18.2%
간이주점 8
 
9.1%
비어(바)살롱 7
 
8.0%
관광호텔나이트(디스코 6
 
6.8%
고고(디스코)클럽 5
 
5.7%
관광호텔나이트(카바레 1
 
1.1%
요정 1
 
1.1%
기타 1
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)82.4%
Missing3
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean198064.28
Minimum196005.84
Maximum200837.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:26.411674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196005.84
5-th percentile196267.9
Q1197285.38
median197438.59
Q3199363.6
95-th percentile200036.07
Maximum200837.14
Range4831.3001
Interquartile range (IQR)2078.215

Descriptive statistics

Standard deviation1287.7801
Coefficient of variation (CV)0.0065018292
Kurtosis-1.1960863
Mean198064.28
Median Absolute Deviation (MAD)841.27431
Skewness0.41428137
Sum16835464
Variance1658377.7
MonotonicityNot monotonic
2024-04-06T22:10:26.708471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197428.35615065 3
 
3.4%
199774.471653899 3
 
3.4%
199337.628628981 3
 
3.4%
200051.482987952 2
 
2.3%
197419.958202485 2
 
2.3%
199363.595799729 2
 
2.3%
197951.289653971 2
 
2.3%
197438.591644015 2
 
2.3%
197415.273841519 2
 
2.3%
199387.896366941 2
 
2.3%
Other values (60) 62
70.5%
(Missing) 3
 
3.4%
ValueCountFrequency (%)
196005.836412851 1
1.1%
196147.046126753 1
1.1%
196189.205036161 1
1.1%
196200.099737911 1
1.1%
196243.289518577 1
1.1%
196366.353581497 1
1.1%
196506.975091736 1
1.1%
196513.012097934 1
1.1%
196534.284541859 1
1.1%
196546.598003309 1
1.1%
ValueCountFrequency (%)
200837.136549128 1
 
1.1%
200581.026842911 1
 
1.1%
200108.265049038 1
 
1.1%
200051.482987952 2
2.3%
199974.400997613 1
 
1.1%
199956.90188004 2
2.3%
199847.221805123 1
 
1.1%
199774.471653899 3
3.4%
199737.097413554 1
 
1.1%
199675.289712107 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)82.4%
Missing3
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean448370.84
Minimum446252.34
Maximum450230.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:27.014959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446252.34
5-th percentile447303.9
Q1447894.64
median448110.57
Q3449015.37
95-th percentile449824.72
Maximum450230.9
Range3978.5604
Interquartile range (IQR)1120.7315

Descriptive statistics

Standard deviation896.85257
Coefficient of variation (CV)0.0020002473
Kurtosis-0.33157172
Mean448370.84
Median Absolute Deviation (MAD)463.30955
Skewness0.22635747
Sum38111521
Variance804344.53
MonotonicityNot monotonic
2024-04-06T22:10:27.321280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449787.335823493 3
 
3.4%
448110.566487329 3
 
3.4%
447413.487156381 3
 
3.4%
448360.483775726 2
 
2.3%
449748.570991334 2
 
2.3%
448050.926289223 2
 
2.3%
446252.339785985 2
 
2.3%
449834.071482352 2
 
2.3%
449711.639432389 2
 
2.3%
448055.04886957 2
 
2.3%
Other values (60) 62
70.5%
(Missing) 3
 
3.4%
ValueCountFrequency (%)
446252.339785985 2
2.3%
446427.314850602 1
 
1.1%
447132.311493856 1
 
1.1%
447279.469998459 1
 
1.1%
447401.612187669 1
 
1.1%
447413.487156381 3
3.4%
447445.54985585 1
 
1.1%
447495.959261 1
 
1.1%
447564.708643528 1
 
1.1%
447574.960080544 1
 
1.1%
ValueCountFrequency (%)
450230.900231927 1
 
1.1%
449948.947811997 1
 
1.1%
449859.024584273 1
 
1.1%
449834.071482352 2
2.3%
449787.335823493 3
3.4%
449757.093478161 1
 
1.1%
449748.570991334 2
2.3%
449729.163439693 1
 
1.1%
449711.639432389 2
2.3%
449704.653699163 1
 
1.1%

위생업태명
Categorical

Distinct9
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size836.0 B
룸살롱
21 
스텐드바
19 
카바레
14 
<NA>
12 
간이주점
7 
Other values (4)
15 

Length

Max length12
Median length9
Mean length4.4545455
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 21
23.9%
스텐드바 19
21.6%
카바레 14
15.9%
<NA> 12
13.6%
간이주점 7
 
8.0%
고고(디스코)클럽 5
 
5.7%
관광호텔나이트(디스코) 5
 
5.7%
비어(바)살롱 4
 
4.5%
요정 1
 
1.1%

Length

2024-04-06T22:10:27.603165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:27.842334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
룸살롱 21
23.9%
스텐드바 19
21.6%
카바레 14
15.9%
na 12
13.6%
간이주점 7
 
8.0%
고고(디스코)클럽 5
 
5.7%
관광호텔나이트(디스코 5
 
5.7%
비어(바)살롱 4
 
4.5%
요정 1
 
1.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)16.9%
Missing23
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean1.9230769
Minimum0
Maximum20
Zeros35
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:28.038056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile9.2
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.6670309
Coefficient of variation (CV)1.9068561
Kurtosis11.247888
Mean1.9230769
Median Absolute Deviation (MAD)0
Skewness3.1449058
Sum125
Variance13.447115
MonotonicityNot monotonic
2024-04-06T22:10:28.321093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 35
39.8%
2 7
 
8.0%
1 7
 
8.0%
3 6
 
6.8%
5 3
 
3.4%
4 2
 
2.3%
12 1
 
1.1%
20 1
 
1.1%
15 1
 
1.1%
6 1
 
1.1%
(Missing) 23
26.1%
ValueCountFrequency (%)
0 35
39.8%
1 7
 
8.0%
2 7
 
8.0%
3 6
 
6.8%
4 2
 
2.3%
5 3
 
3.4%
6 1
 
1.1%
10 1
 
1.1%
12 1
 
1.1%
15 1
 
1.1%
ValueCountFrequency (%)
20 1
 
1.1%
15 1
 
1.1%
12 1
 
1.1%
10 1
 
1.1%
6 1
 
1.1%
5 3
3.4%
4 2
 
2.3%
3 6
6.8%
2 7
8.0%
1 7
8.0%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)15.4%
Missing23
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean1.9538462
Minimum0
Maximum21
Zeros34
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:28.598921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5.8
Maximum21
Range21
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.5682225
Coefficient of variation (CV)1.8262556
Kurtosis14.428193
Mean1.9538462
Median Absolute Deviation (MAD)0
Skewness3.4177951
Sum127
Variance12.732212
MonotonicityNot monotonic
2024-04-06T22:10:28.782449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 34
38.6%
2 7
 
8.0%
3 6
 
6.8%
1 6
 
6.8%
5 5
 
5.7%
4 3
 
3.4%
6 1
 
1.1%
21 1
 
1.1%
15 1
 
1.1%
10 1
 
1.1%
(Missing) 23
26.1%
ValueCountFrequency (%)
0 34
38.6%
1 6
 
6.8%
2 7
 
8.0%
3 6
 
6.8%
4 3
 
3.4%
5 5
 
5.7%
6 1
 
1.1%
10 1
 
1.1%
15 1
 
1.1%
21 1
 
1.1%
ValueCountFrequency (%)
21 1
 
1.1%
15 1
 
1.1%
10 1
 
1.1%
6 1
 
1.1%
5 5
 
5.7%
4 3
 
3.4%
3 6
 
6.8%
2 7
 
8.0%
1 6
 
6.8%
0 34
38.6%

영업장주변구분명
Categorical

Distinct4
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
34 
기타
26 
유흥업소밀집지역
25 
주택가주변
 
3

Length

Max length8
Median length5
Mean length4.5795455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
38.6%
기타 26
29.5%
유흥업소밀집지역 25
28.4%
주택가주변 3
 
3.4%

Length

2024-04-06T22:10:29.050747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:29.267015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
38.6%
기타 26
29.5%
유흥업소밀집지역 25
28.4%
주택가주변 3
 
3.4%

등급구분명
Categorical

Distinct8
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
37 
지도
18 
을
13 
갑
8 
기타
8 
Other values (3)
4 

Length

Max length4
Median length2
Mean length2.6022727
Min length1

Unique

Unique2 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 37
42.0%
지도 18
20.5%
을 13
 
14.8%
갑 8
 
9.1%
기타 8
 
9.1%
자율 2
 
2.3%
관리 1
 
1.1%
우수 1
 
1.1%

Length

2024-04-06T22:10:29.497211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:29.710426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
42.0%
지도 18
20.5%
을 13
 
14.8%
갑 8
 
9.1%
기타 8
 
9.1%
자율 2
 
2.3%
관리 1
 
1.1%
우수 1
 
1.1%

급수시설구분명
Categorical

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
상수도전용
54 
<NA>
34 

Length

Max length5
Median length5
Mean length4.6136364
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 54
61.4%
<NA> 34
38.6%

Length

2024-04-06T22:10:29.978892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:30.190755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 54
61.4%
na 34
38.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:30.432468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:30.633936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:30.847018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:31.074090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:31.374537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:31.605701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:31.818307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:32.028603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:32.192447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:32.376315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:32.542573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:32.712620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size836.0 B
<NA>
81 
0
 
7

Length

Max length4
Median length4
Mean length3.7613636
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> 81
92.0%
0 7
 
8.0%

Length

2024-04-06T22:10:32.905119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:10:33.099374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
92.0%
0 7
 
8.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)2.6%
Missing12
Missing (%)13.6%
Memory size308.0 B
False
74 
True
 
2
(Missing)
12 
ValueCountFrequency (%)
False 74
84.1%
True 2
 
2.3%
(Missing) 12
 
13.6%
2024-04-06T22:10:33.294514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)100.0%
Missing12
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean238.84
Minimum1
Maximum2023.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T22:10:33.486238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.6225
Q158.9475
median116.795
Q3212.6175
95-th percentile941.955
Maximum2023.34
Range2022.34
Interquartile range (IQR)153.67

Descriptive statistics

Standard deviation335.92887
Coefficient of variation (CV)1.4065017
Kurtosis10.556243
Mean238.84
Median Absolute Deviation (MAD)67.815
Skewness2.9214567
Sum18151.84
Variance112848.21
MonotonicityNot monotonic
2024-04-06T22:10:33.748690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.13 1
 
1.1%
62.0 1
 
1.1%
68.92 1
 
1.1%
57.74 1
 
1.1%
46.46 1
 
1.1%
59.35 1
 
1.1%
106.15 1
 
1.1%
73.37 1
 
1.1%
121.89 1
 
1.1%
2023.34 1
 
1.1%
Other values (66) 66
75.0%
(Missing) 12
 
13.6%
ValueCountFrequency (%)
1.0 1
1.1%
23.12 1
1.1%
28.8 1
1.1%
31.49 1
1.1%
33.0 1
1.1%
34.04 1
1.1%
37.21 1
1.1%
39.76 1
1.1%
41.82 1
1.1%
43.19 1
1.1%
ValueCountFrequency (%)
2023.34 1
1.1%
1111.66 1
1.1%
987.2 1
1.1%
962.97 1
1.1%
934.95 1
1.1%
879.09 1
1.1%
844.37 1
1.1%
780.0 1
1.1%
716.44 1
1.1%
647.4 1
1.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing88
Missing (%)100.0%
Memory size924.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030200003020000-102-1967-0351119670705<NA>1영업/정상1영업<NA><NA><NA><NA>0207959155109.77140858서울특별시 용산구 이태원동 136-2 (지상1층)서울특별시 용산구 우사단로14길 16 (이태원동,(지상1층))4405그랜드올아프리클럽2022-07-05 15:56:12U2021-12-07 00:07:00.0스텐드바199627.327719447981.33922<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130200003020000-102-1967-0353119671228<NA>3폐업2폐업20101202<NA><NA><NA>0207949705184.92140893서울특별시 용산구 한남동 736-11번지 (지상3층)<NA><NA>제임스2009-01-02 15:00:17I2018-08-31 23:59:59.0카바레199675.289712448030.294524카바레24유흥업소밀집지역갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N184.92<NA><NA><NA>
230200003020000-102-1967-035771967-12-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>235.44140-858서울특별시 용산구 이태원동 136-46 (지상1층)서울특별시 용산구 우사단로 40 (이태원동,(지상1층))4405킹크럽2023-07-28 13:45:56U2022-12-06 21:00:00.0카바레199563.529585447939.08505<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
330200003020000-102-1968-0353519680205<NA>3폐업2폐업20040629<NA><NA><NA>02265.72140807서울특별시 용산구 갈월동 98-1번지<NA><NA>황금마차2000-08-09 00:00:00I2018-08-31 23:59:59.0스텐드바197464.296282448824.302251스텐드바00유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N265.72<NA><NA><NA>
430200003020000-102-1968-035531968-11-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 7927988196.90140-858서울특별시 용산구 이태원동 127-2서울특별시 용산구 이태원로 192, 지하1층 (이태원동)4406퍼블릭서울2024-01-02 13:49:55U2023-12-01 00:04:00.0관광호텔나이트(카바레)199520.280405448012.047529<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
530200003020000-102-1969-0355919691222<NA>3폐업2폐업20020318<NA><NA><NA>0207933885206.11140858서울특별시 용산구 이태원동 126-16번지<NA><NA>럭키크럽2002-04-13 00:00:00I2018-08-31 23:59:59.0카바레199563.353058447985.100399카바레24유흥업소밀집지역갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N206.11<NA><NA><NA>
630200003020000-102-1970-0353019700420<NA>3폐업2폐업20210827<NA><NA><NA><NA>207.45140858서울특별시 용산구 이태원동 136-45 (지상2층)서울특별시 용산구 우사단로 42 (이태원동,(지상2층))4405테마2021-08-27 16:15:10U2021-08-29 02:40:00.0카바레199557.034319447959.847009카바레00<NA><NA><NA>00000<NA>00Y207.45<NA><NA><NA>
730200003020000-102-1971-0352719710223<NA>3폐업2폐업20041124<NA><NA><NA>02 7147758126.39140848서울특별시 용산구 원효로3가 51-37번지<NA><NA>아파치2004-11-24 00:00:00I2018-08-31 23:59:59.0카바레196189.205036447894.643407카바레00유흥업소밀집지역갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N126.39<NA><NA><NA>
830200003020000-102-1971-0354419710417<NA>3폐업2폐업19980430<NA><NA><NA>02 7145825263.89140806서울특별시 용산구 갈월동 69-3번지<NA><NA>패션2001-09-27 00:00:00I2018-08-31 23:59:59.0고고(디스코)클럽197425.478613449166.662964고고(디스코)클럽123유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N263.89<NA><NA><NA>
930200003020000-102-1971-0355719710825<NA>3폐업2폐업20010202<NA><NA><NA>02 793247187.50140889서울특별시 용산구 한남동 107-10번지<NA><NA>한남회관2001-09-27 00:00:00I2018-08-31 23:59:59.0스텐드바200581.026843447647.256933스텐드바42기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N87.5<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
7830200003020000-102-2002-0000320000317<NA>3폐업2폐업20051102<NA><NA><NA>02 706734649.29140821서울특별시 용산구 동자동 43-21번지<NA><NA>백만불2004-02-06 00:00:00I2018-08-31 23:59:59.0룸살롱197441.679143449859.024584룸살롱00유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.29<NA><NA><NA>
7930200003020000-102-2002-0000420000603<NA>3폐업2폐업20140529<NA><NA><NA>023211697528.80140821서울특별시 용산구 동자동 43-37번지서울특별시 용산구 한강대로 351-1 (동자동, 43-37 지상1층)4320홍재2013-04-04 10:24:21I2018-08-31 23:59:59.0카바레197415.273842449711.639432카바레<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N28.8<NA><NA><NA>
8030200003020000-102-2003-0000120030510<NA>3폐업2폐업20091116<NA><NA><NA><NA>48.44140821서울특별시 용산구 동자동 43-24번지 (지상 1층)<NA><NA>강촌비즈니스2003-06-11 00:00:00I2018-08-31 23:59:59.0룸살롱197438.591644449834.071482룸살롱00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.44<NA><NA><NA>
8130200003020000-102-2004-0000120040108<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.00140872서울특별시 용산구 한강로2가 115-1번지 (지하1층)서울특별시 용산구 한강대로 132 (한강로2가,(지하1층))43820022015-10-16 16:00:39I2018-08-31 23:59:59.0룸살롱197285.380806447648.148743룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N61.0<NA><NA><NA>
8230200003020000-102-2006-0000120060109<NA>3폐업2폐업20111205<NA><NA><NA>02 7940171962.97140863서울특별시 용산구 이태원동 108-9번지 외8필지(지하2층)<NA><NA>(주)하드록카페이태원2008-12-31 10:35:07I2018-08-31 23:59:59.0관광호텔나이트(디스코)199387.896367448055.04887관광호텔나이트(디스코)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N962.97<NA><NA><NA>
8330200003020000-102-2012-0000120120217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>384.54140863서울특별시 용산구 이태원동 116-1번지 해밀턴호텔 별관 2층서울특별시 용산구 이태원로27가길 26 (이태원동, 해밀턴호텔 별관2층)4350글램2017-07-19 11:47:36I2018-08-31 23:59:59.0비어(바)살롱199357.144448100.802303비어(바)살롱1010유흥업소밀집지역우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N384.54<NA><NA><NA>
8430200003020000-102-2012-0000220120501<NA>1영업/정상1영업<NA><NA><NA><NA>02 7493249334.82140863서울특별시 용산구 이태원동 116-1번지 해밀턴관광호텔 별관2층서울특별시 용산구 이태원로27가길 26 (이태원동, 116-1 해밀턴관광호텔 별관2층)4350데이앤나이트2017-08-25 13:39:44I2018-08-31 23:59:59.0관광호텔나이트(디스코)199357.144448100.802303관광호텔나이트(디스코)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N334.82<NA><NA><NA>
8530200003020000-102-2013-000012013-01-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>962.97140-863서울특별시 용산구 이태원동 108-9 해밀튼호텔 지하2층서울특별시 용산구 이태원로 지하 179 (이태원동, 해밀튼호텔 지하2층)<NA>이태원별밤2023-12-20 13:27:07U2022-11-01 22:03:00.0비어(바)살롱199387.896367448055.04887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8630200003020000-102-2014-000012014-09-11<NA>3폐업2폐업2024-03-04<NA><NA><NA><NA>138.33140-860서울특별시 용산구 이태원동 22-76서울특별시 용산구 장문로 23, 지하3층 (이태원동, 캐피탈관광호텔)4392세븐2024-03-04 09:20:46U2023-12-03 00:06:00.0비어(바)살롱199337.628629447413.487156<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8730200003020000-102-2016-0000120161026<NA>1영업/정상1영업<NA><NA><NA><NA><NA>985.05140893서울특별시 용산구 한남동 737-25 지하1층서울특별시 용산구 이태원로 221, 지하1층 (한남동, 임피리얼팰리스 부티크호텔)4349메이드2022-04-21 11:21:28U2021-12-03 22:03:00.0관광호텔나이트(디스코)199774.471654448110.566487<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>