Overview

Dataset statistics

Number of variables44
Number of observations205
Missing cells2296
Missing cells (%)25.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory75.4 KiB
Average record size in memory376.6 B

Variable types

Categorical19
Text6
DateTime4
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18575/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (59.6%)Imbalance
총인원 is highly imbalanced (83.5%)Imbalance
본사종업원수 is highly imbalanced (83.5%)Imbalance
공장사무직종업원수 is highly imbalanced (83.5%)Imbalance
공장판매직종업원수 is highly imbalanced (83.5%)Imbalance
공장생산직종업원수 is highly imbalanced (83.5%)Imbalance
보증액 is highly imbalanced (83.5%)Imbalance
월세액 is highly imbalanced (83.5%)Imbalance
다중이용업소여부 is highly imbalanced (94.4%)Imbalance
인허가취소일자 has 205 (100.0%) missing valuesMissing
폐업일자 has 83 (40.5%) missing valuesMissing
휴업시작일자 has 205 (100.0%) missing valuesMissing
휴업종료일자 has 205 (100.0%) missing valuesMissing
재개업일자 has 205 (100.0%) missing valuesMissing
전화번호 has 54 (26.3%) missing valuesMissing
도로명주소 has 71 (34.6%) missing valuesMissing
도로명우편번호 has 74 (36.1%) missing valuesMissing
남성종사자수 has 135 (65.9%) missing valuesMissing
여성종사자수 has 135 (65.9%) missing valuesMissing
건물소유구분명 has 205 (100.0%) missing valuesMissing
다중이용업소여부 has 50 (24.4%) missing valuesMissing
시설총규모 has 50 (24.4%) missing valuesMissing
전통업소지정번호 has 205 (100.0%) missing valuesMissing
전통업소주된음식 has 205 (100.0%) missing valuesMissing
홈페이지 has 205 (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 58 (28.3%) zerosZeros
여성종사자수 has 57 (27.8%) zerosZeros

Reproduction

Analysis started2024-04-29 19:46:12.395515
Analysis finished2024-04-29 19:46:13.196175
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3230000
205 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 205
100.0%

Length

2024-04-30T04:46:13.257357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:13.332080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 205
100.0%

관리번호
Text

UNIQUE 

Distinct205
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-30T04:46:13.471441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4510
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

Unique205 ?
Unique (%)100.0%

Sample

1st row3230000-102-1977-03619
2nd row3230000-102-1980-03603
3rd row3230000-102-1985-03614
4th row3230000-102-1985-03622
5th row3230000-102-1985-03624
ValueCountFrequency (%)
3230000-102-1977-03619 1
 
0.5%
3230000-102-2003-00005 1
 
0.5%
3230000-102-2004-00002 1
 
0.5%
3230000-102-2004-00003 1
 
0.5%
3230000-102-2004-00004 1
 
0.5%
3230000-102-2004-00005 1
 
0.5%
3230000-102-2005-00001 1
 
0.5%
3230000-102-2005-00002 1
 
0.5%
3230000-102-2005-00003 1
 
0.5%
3230000-102-2005-00004 1
 
0.5%
Other values (195) 195
95.1%
2024-04-30T04:46:13.728529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1735
38.5%
2 634
 
14.1%
- 615
 
13.6%
1 492
 
10.9%
3 487
 
10.8%
9 175
 
3.9%
6 96
 
2.1%
4 78
 
1.7%
5 76
 
1.7%
7 69
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3895
86.4%
Dash Punctuation 615
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1735
44.5%
2 634
 
16.3%
1 492
 
12.6%
3 487
 
12.5%
9 175
 
4.5%
6 96
 
2.5%
4 78
 
2.0%
5 76
 
2.0%
7 69
 
1.8%
8 53
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 615
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1735
38.5%
2 634
 
14.1%
- 615
 
13.6%
1 492
 
10.9%
3 487
 
10.8%
9 175
 
3.9%
6 96
 
2.1%
4 78
 
1.7%
5 76
 
1.7%
7 69
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1735
38.5%
2 634
 
14.1%
- 615
 
13.6%
1 492
 
10.9%
3 487
 
10.8%
9 175
 
3.9%
6 96
 
2.1%
4 78
 
1.7%
5 76
 
1.7%
7 69
 
1.5%

인허가일자
Date

Distinct192
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1977-11-14 00:00:00
Maximum2023-10-10 00:00:00
2024-04-30T04:46:13.845905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:46:13.970582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
122 
1
83 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 122
59.5%
1 83
40.5%

Length

2024-04-30T04:46:14.086529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:14.181828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 122
59.5%
1 83
40.5%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
122 
영업/정상
83 

Length

Max length5
Median length2
Mean length3.2146341
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 122
59.5%
영업/정상 83
40.5%

Length

2024-04-30T04:46:14.278832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:14.378293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
59.5%
영업/정상 83
40.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
122 
1
83 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 122
59.5%
1 83
40.5%

Length

2024-04-30T04:46:14.480736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:14.578009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 122
59.5%
1 83
40.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
122 
영업
83 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 122
59.5%
영업 83
40.5%

Length

2024-04-30T04:46:14.690944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:14.786759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
59.5%
영업 83
40.5%

폐업일자
Date

MISSING 

Distinct114
Distinct (%)93.4%
Missing83
Missing (%)40.5%
Memory size1.7 KiB
Minimum1990-02-06 00:00:00
Maximum2024-04-16 00:00:00
2024-04-30T04:46:14.900612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:46:15.082634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

전화번호
Text

MISSING 

Distinct137
Distinct (%)90.7%
Missing54
Missing (%)26.3%
Memory size1.7 KiB
2024-04-30T04:46:15.410174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8410596
Min length2

Characters and Unicode

Total characters1486
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

Unique129 ?
Unique (%)85.4%

Sample

1st row02 4143331
2nd row02 4853235
3rd row02 4212065
4th row0204189156
5th row02 4235425
ValueCountFrequency (%)
02 134
45.7%
4230879 3
 
1.0%
4181642 2
 
0.7%
416 2
 
0.7%
412 2
 
0.7%
430 2
 
0.7%
4215902 2
 
0.7%
4171893 2
 
0.7%
4243288 2
 
0.7%
4149797 2
 
0.7%
Other values (138) 140
47.8%
2024-04-30T04:46:16.020911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 277
18.6%
0 257
17.3%
4 214
14.4%
164
11.0%
1 144
9.7%
3 94
 
6.3%
8 80
 
5.4%
5 68
 
4.6%
6 65
 
4.4%
9 63
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1322
89.0%
Space Separator 164
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 277
21.0%
0 257
19.4%
4 214
16.2%
1 144
10.9%
3 94
 
7.1%
8 80
 
6.1%
5 68
 
5.1%
6 65
 
4.9%
9 63
 
4.8%
7 60
 
4.5%
Space Separator
ValueCountFrequency (%)
164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1486
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 277
18.6%
0 257
17.3%
4 214
14.4%
164
11.0%
1 144
9.7%
3 94
 
6.3%
8 80
 
5.4%
5 68
 
4.6%
6 65
 
4.4%
9 63
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 277
18.6%
0 257
17.3%
4 214
14.4%
164
11.0%
1 144
9.7%
3 94
 
6.3%
8 80
 
5.4%
5 68
 
4.6%
6 65
 
4.4%
9 63
 
4.2%

소재지면적
Text

Distinct197
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-30T04:46:16.388656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.6536585
Min length5

Characters and Unicode

Total characters1159
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

Unique189 ?
Unique (%)92.2%

Sample

1st row1,159.63
2nd row134.64
3rd row946.32
4th row163.86
5th row559.62
ValueCountFrequency (%)
166.13 2
 
1.0%
59.04 2
 
1.0%
528.00 2
 
1.0%
109.91 2
 
1.0%
164.37 2
 
1.0%
140.71 2
 
1.0%
61.20 2
 
1.0%
138.94 2
 
1.0%
91.40 1
 
0.5%
92.82 1
 
0.5%
Other values (187) 187
91.2%
2024-04-30T04:46:16.953612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 205
17.7%
1 137
11.8%
8 108
9.3%
0 99
8.5%
4 98
8.5%
6 90
7.8%
2 90
7.8%
9 87
7.5%
3 81
 
7.0%
5 81
 
7.0%
Other values (2) 83
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 948
81.8%
Other Punctuation 211
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 137
14.5%
8 108
11.4%
0 99
10.4%
4 98
10.3%
6 90
9.5%
2 90
9.5%
9 87
9.2%
3 81
8.5%
5 81
8.5%
7 77
8.1%
Other Punctuation
ValueCountFrequency (%)
. 205
97.2%
, 6
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1159
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 205
17.7%
1 137
11.8%
8 108
9.3%
0 99
8.5%
4 98
8.5%
6 90
7.8%
2 90
7.8%
9 87
7.5%
3 81
 
7.0%
5 81
 
7.0%
Other values (2) 83
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 205
17.7%
1 137
11.8%
8 108
9.3%
0 99
8.5%
4 98
8.5%
6 90
7.8%
2 90
7.8%
9 87
7.5%
3 81
 
7.0%
5 81
 
7.0%
Other values (2) 83
7.2%

소재지우편번호
Categorical

Distinct21
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
138827
77 
138861
38 
138805
19 
138803
13 
138-805
11 
Other values (16)
47 

Length

Max length7
Median length6
Mean length6.1756098
Min length6

Unique

Unique6 ?
Unique (%)2.9%

Sample

1st row138842
2nd row138873
3rd row138721
4th row138721
5th row138805

Common Values

ValueCountFrequency (%)
138827 77
37.6%
138861 38
18.5%
138805 19
 
9.3%
138803 13
 
6.3%
138-805 11
 
5.4%
138-827 9
 
4.4%
138-803 7
 
3.4%
138828 5
 
2.4%
138-842 4
 
2.0%
138-861 4
 
2.0%
Other values (11) 18
 
8.8%

Length

2024-04-30T04:46:17.128385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
138827 77
37.6%
138861 38
18.5%
138805 19
 
9.3%
138803 13
 
6.3%
138-805 11
 
5.4%
138-827 9
 
4.4%
138-803 7
 
3.4%
138828 5
 
2.4%
138-842 4
 
2.0%
138-861 4
 
2.0%
Other values (11) 18
 
8.8%

지번주소
Text

Distinct182
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-30T04:46:17.324491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length25.014634
Min length18

Characters and Unicode

Total characters5128
Distinct characters77
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)81.0%

Sample

1st row서울특별시 송파구 석촌동 24-0번지
2nd row서울특별시 송파구 풍납동 481-1번지
3rd row서울특별시 송파구 잠실동 40-1번지 롯데월드 지하3층
4th row서울특별시 송파구 잠실동 40-1번지 롯데월드지하3층
5th row서울특별시 송파구 가락동 99-5번지
ValueCountFrequency (%)
서울특별시 205
20.6%
송파구 205
20.6%
방이동 92
 
9.3%
지하1층 65
 
6.5%
가락동 55
 
5.5%
잠실동 49
 
4.9%
지상2층 14
 
1.4%
79-4 9
 
0.9%
석촌동 8
 
0.8%
79-4번지 8
 
0.8%
Other values (164) 284
28.6%
2024-04-30T04:46:17.652476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
942
18.4%
지 240
 
4.7%
1 224
 
4.4%
- 210
 
4.1%
동 206
 
4.0%
구 205
 
4.0%
울 205
 
4.0%
서 205
 
4.0%
파 205
 
4.0%
시 205
 
4.0%
Other values (67) 2281
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3008
58.7%
Space Separator 942
 
18.4%
Decimal Number 899
 
17.5%
Dash Punctuation 210
 
4.1%
Close Punctuation 23
 
0.4%
Open Punctuation 23
 
0.4%
Other Punctuation 18
 
0.4%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 240
 
8.0%
동 206
 
6.8%
구 205
 
6.8%
울 205
 
6.8%
서 205
 
6.8%
파 205
 
6.8%
시 205
 
6.8%
특 205
 
6.8%
송 205
 
6.8%
별 205
 
6.8%
Other values (49) 922
30.7%
Decimal Number
ValueCountFrequency (%)
1 224
24.9%
4 99
11.0%
3 99
11.0%
9 96
10.7%
2 95
10.6%
7 90
10.0%
8 75
 
8.3%
6 53
 
5.9%
0 39
 
4.3%
5 29
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
A 1
 
20.0%
Space Separator
ValueCountFrequency (%)
942
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3008
58.7%
Common 2115
41.2%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 240
 
8.0%
동 206
 
6.8%
구 205
 
6.8%
울 205
 
6.8%
서 205
 
6.8%
파 205
 
6.8%
시 205
 
6.8%
특 205
 
6.8%
송 205
 
6.8%
별 205
 
6.8%
Other values (49) 922
30.7%
Common
ValueCountFrequency (%)
942
44.5%
1 224
 
10.6%
- 210
 
9.9%
4 99
 
4.7%
3 99
 
4.7%
9 96
 
4.5%
2 95
 
4.5%
7 90
 
4.3%
8 75
 
3.5%
6 53
 
2.5%
Other values (5) 132
 
6.2%
Latin
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
A 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3008
58.7%
ASCII 2120
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
942
44.4%
1 224
 
10.6%
- 210
 
9.9%
4 99
 
4.7%
3 99
 
4.7%
9 96
 
4.5%
2 95
 
4.5%
7 90
 
4.2%
8 75
 
3.5%
6 53
 
2.5%
Other values (8) 137
 
6.5%
Hangul
ValueCountFrequency (%)
지 240
 
8.0%
동 206
 
6.8%
구 205
 
6.8%
울 205
 
6.8%
서 205
 
6.8%
파 205
 
6.8%
시 205
 
6.8%
특 205
 
6.8%
송 205
 
6.8%
별 205
 
6.8%
Other values (49) 922
30.7%

도로명주소
Text

MISSING 

Distinct132
Distinct (%)98.5%
Missing71
Missing (%)34.6%
Memory size1.7 KiB
2024-04-30T04:46:17.851474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length33.932836
Min length22

Characters and Unicode

Total characters4547
Distinct characters88
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

Unique130 ?
Unique (%)97.0%

Sample

1st row서울특별시 송파구 올림픽로 607 (풍납동)
2nd row서울특별시 송파구 오금로11길 47 (방이동)
3rd row서울특별시 송파구 오금로11길 11, 지하1층 (방이동)
4th row서울특별시 송파구 올림픽로 102, 지하1층 (잠실동)
5th row서울특별시 송파구 올림픽로 114, 지하1층 (잠실동)
ValueCountFrequency (%)
서울특별시 134
16.3%
송파구 134
16.3%
지하1층 57
 
6.9%
송파대로28길 45
 
5.5%
방이동 44
 
5.3%
가락동 44
 
5.3%
오금로11길 27
 
3.3%
올림픽로32길 22
 
2.7%
20 16
 
1.9%
잠실동 13
 
1.6%
Other values (133) 287
34.9%
2024-04-30T04:46:18.172333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
689
 
15.2%
1 260
 
5.7%
2 184
 
4.0%
송 182
 
4.0%
파 182
 
4.0%
, 152
 
3.3%
) 146
 
3.2%
( 146
 
3.2%
로 136
 
3.0%
동 135
 
3.0%
Other values (78) 2335
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2590
57.0%
Decimal Number 770
 
16.9%
Space Separator 689
 
15.2%
Other Punctuation 152
 
3.3%
Close Punctuation 146
 
3.2%
Open Punctuation 146
 
3.2%
Dash Punctuation 49
 
1.1%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 182
 
7.0%
파 182
 
7.0%
로 136
 
5.3%
동 135
 
5.2%
울 134
 
5.2%
서 134
 
5.2%
시 134
 
5.2%
특 134
 
5.2%
구 134
 
5.2%
별 134
 
5.2%
Other values (60) 1151
44.4%
Decimal Number
ValueCountFrequency (%)
1 260
33.8%
2 184
23.9%
3 77
 
10.0%
8 67
 
8.7%
0 63
 
8.2%
7 29
 
3.8%
6 25
 
3.2%
9 24
 
3.1%
4 22
 
2.9%
5 19
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
B 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
689
100.0%
Other Punctuation
ValueCountFrequency (%)
, 152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2590
57.0%
Common 1952
42.9%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 182
 
7.0%
파 182
 
7.0%
로 136
 
5.3%
동 135
 
5.2%
울 134
 
5.2%
서 134
 
5.2%
시 134
 
5.2%
특 134
 
5.2%
구 134
 
5.2%
별 134
 
5.2%
Other values (60) 1151
44.4%
Common
ValueCountFrequency (%)
689
35.3%
1 260
 
13.3%
2 184
 
9.4%
, 152
 
7.8%
) 146
 
7.5%
( 146
 
7.5%
3 77
 
3.9%
8 67
 
3.4%
0 63
 
3.2%
- 49
 
2.5%
Other values (5) 119
 
6.1%
Latin
ValueCountFrequency (%)
A 2
40.0%
B 2
40.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2590
57.0%
ASCII 1957
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
689
35.2%
1 260
 
13.3%
2 184
 
9.4%
, 152
 
7.8%
) 146
 
7.5%
( 146
 
7.5%
3 77
 
3.9%
8 67
 
3.4%
0 63
 
3.2%
- 49
 
2.5%
Other values (8) 124
 
6.3%
Hangul
ValueCountFrequency (%)
송 182
 
7.0%
파 182
 
7.0%
로 136
 
5.3%
동 135
 
5.2%
울 134
 
5.2%
서 134
 
5.2%
시 134
 
5.2%
특 134
 
5.2%
구 134
 
5.2%
별 134
 
5.2%
Other values (60) 1151
44.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)9.2%
Missing74
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean5613.9542
Minimum5519
Maximum5719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:18.335246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5519
5-th percentile5542
Q15543
median5556
Q35718
95-th percentile5719
Maximum5719
Range200
Interquartile range (IQR)175

Descriptive statistics

Standard deviation82.621739
Coefficient of variation (CV)0.014717209
Kurtosis-1.7607951
Mean5613.9542
Median Absolute Deviation (MAD)14
Skewness0.43974512
Sum735428
Variance6826.3517
MonotonicityNot monotonic
2024-04-30T04:46:18.534660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5543 31
15.1%
5719 28
 
13.7%
5718 21
 
10.2%
5542 17
 
8.3%
5556 10
 
4.9%
5544 6
 
2.9%
5557 4
 
2.0%
5558 4
 
2.0%
5612 4
 
2.0%
5610 3
 
1.5%
Other values (2) 3
 
1.5%
(Missing) 74
36.1%
ValueCountFrequency (%)
5519 1
 
0.5%
5542 17
8.3%
5543 31
15.1%
5544 6
 
2.9%
5545 2
 
1.0%
5556 10
 
4.9%
5557 4
 
2.0%
5558 4
 
2.0%
5610 3
 
1.5%
5612 4
 
2.0%
ValueCountFrequency (%)
5719 28
13.7%
5718 21
10.2%
5612 4
 
2.0%
5610 3
 
1.5%
5558 4
 
2.0%
5557 4
 
2.0%
5556 10
 
4.9%
5545 2
 
1.0%
5544 6
 
2.9%
5543 31
15.1%

사업장명
Text

Distinct195
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-30T04:46:18.796376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length4.5902439
Min length1

Characters and Unicode

Total characters941
Distinct characters281
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)91.2%

Sample

1st row다이너스티클럽
2nd row티파니
3rd row벨파레나이트
4th row유람선스탠드빠
5th row2002년
ValueCountFrequency (%)
뮤직타운 7
 
2.9%
노래주점 6
 
2.5%
홍콩 4
 
1.7%
스펀지 3
 
1.3%
포인트 2
 
0.8%
에이스 2
 
0.8%
준코뮤직타운 2
 
0.8%
방이점 2
 
0.8%
올림피아나 2
 
0.8%
보물성 2
 
0.8%
Other values (204) 207
86.6%
2024-04-30T04:46:19.230047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
3.7%
스 34
 
3.6%
이 31
 
3.3%
래 26
 
2.8%
노 24
 
2.6%
타 19
 
2.0%
아 19
 
2.0%
운 17
 
1.8%
점 16
 
1.7%
( 15
 
1.6%
Other values (271) 705
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 787
83.6%
Space Separator 35
 
3.7%
Lowercase Letter 33
 
3.5%
Uppercase Letter 28
 
3.0%
Decimal Number 21
 
2.2%
Open Punctuation 15
 
1.6%
Close Punctuation 15
 
1.6%
Math Symbol 3
 
0.3%
Other Punctuation 3
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 34
 
4.3%
이 31
 
3.9%
래 26
 
3.3%
노 24
 
3.0%
타 19
 
2.4%
아 19
 
2.4%
운 17
 
2.2%
점 16
 
2.0%
뮤 15
 
1.9%
직 15
 
1.9%
Other values (228) 571
72.6%
Lowercase Letter
ValueCountFrequency (%)
i 4
12.1%
e 4
12.1%
h 3
9.1%
s 3
9.1%
o 3
9.1%
a 3
9.1%
m 3
9.1%
d 2
 
6.1%
f 2
 
6.1%
r 1
 
3.0%
Other values (5) 5
15.2%
Uppercase Letter
ValueCountFrequency (%)
I 4
14.3%
S 4
14.3%
M 3
10.7%
J 3
10.7%
B 3
10.7%
G 2
7.1%
A 2
7.1%
X 2
7.1%
N 1
 
3.6%
Q 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
2 7
33.3%
1 5
23.8%
0 5
23.8%
7 1
 
4.8%
8 1
 
4.8%
5 1
 
4.8%
6 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
% 1
33.3%
? 1
33.3%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 787
83.6%
Common 93
 
9.9%
Latin 61
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 34
 
4.3%
이 31
 
3.9%
래 26
 
3.3%
노 24
 
3.0%
타 19
 
2.4%
아 19
 
2.4%
운 17
 
2.2%
점 16
 
2.0%
뮤 15
 
1.9%
직 15
 
1.9%
Other values (228) 571
72.6%
Latin
ValueCountFrequency (%)
i 4
 
6.6%
e 4
 
6.6%
I 4
 
6.6%
S 4
 
6.6%
h 3
 
4.9%
s 3
 
4.9%
M 3
 
4.9%
o 3
 
4.9%
J 3
 
4.9%
B 3
 
4.9%
Other values (18) 27
44.3%
Common
ValueCountFrequency (%)
35
37.6%
( 15
16.1%
) 15
16.1%
2 7
 
7.5%
1 5
 
5.4%
0 5
 
5.4%
~ 3
 
3.2%
7 1
 
1.1%
8 1
 
1.1%
- 1
 
1.1%
Other values (5) 5
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 787
83.6%
ASCII 154
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
22.7%
( 15
 
9.7%
) 15
 
9.7%
2 7
 
4.5%
1 5
 
3.2%
0 5
 
3.2%
i 4
 
2.6%
e 4
 
2.6%
I 4
 
2.6%
S 4
 
2.6%
Other values (33) 56
36.4%
Hangul
ValueCountFrequency (%)
스 34
 
4.3%
이 31
 
3.9%
래 26
 
3.3%
노 24
 
3.0%
타 19
 
2.4%
아 19
 
2.4%
운 17
 
2.2%
점 16
 
2.0%
뮤 15
 
1.9%
직 15
 
1.9%
Other values (228) 571
72.6%

최종수정일자
Date

Distinct181
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2002-09-04 00:00:00
Maximum2024-04-24 13:17:27
2024-04-30T04:46:19.346690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:46:19.466325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
112 
U
93 

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 112
54.6%
U 93
45.4%

Length

2024-04-30T04:46:19.582532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:19.659056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 112
54.6%
u 93
45.4%

데이터갱신일자
Date

Distinct85
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-04-30T04:46:19.753229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:46:20.041398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct11
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
룸살롱
158 
카바레
17 
비어(바)살롱
 
8
기타
 
8
고고(디스코)클럽
 
3
Other values (6)
 
11

Length

Max length12
Median length3
Mean length3.4146341
Min length2

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st row룸살롱
2nd row룸살롱
3rd row고고(디스코)클럽
4th row카바레
5th row스텐드바

Common Values

ValueCountFrequency (%)
룸살롱 158
77.1%
카바레 17
 
8.3%
비어(바)살롱 8
 
3.9%
기타 8
 
3.9%
고고(디스코)클럽 3
 
1.5%
스텐드바 3
 
1.5%
관광호텔나이트(디스코) 3
 
1.5%
간이주점 2
 
1.0%
관광호텔나이트(카바레) 1
 
0.5%
극장식당 1
 
0.5%

Length

2024-04-30T04:46:20.152293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 158
77.1%
카바레 17
 
8.3%
비어(바)살롱 8
 
3.9%
기타 8
 
3.9%
고고(디스코)클럽 3
 
1.5%
스텐드바 3
 
1.5%
관광호텔나이트(디스코 3
 
1.5%
간이주점 2
 
1.0%
관광호텔나이트(카바레 1
 
0.5%
극장식당 1
 
0.5%

좌표정보(X)
Real number (ℝ)

Distinct85
Distinct (%)41.9%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean209279.95
Minimum206919.48
Maximum210729.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:20.265950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206919.48
5-th percentile206964.46
Q1208589.36
median209586.72
Q3210430.49
95-th percentile210562.9
Maximum210729.46
Range3809.9815
Interquartile range (IQR)1841.1316

Descriptive statistics

Standard deviation1236.4423
Coefficient of variation (CV)0.0059080781
Kurtosis-0.58362649
Mean209279.95
Median Absolute Deviation (MAD)870.21506
Skewness-0.8971062
Sum42483830
Variance1528789.5
MonotonicityNot monotonic
2024-04-30T04:46:20.382812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210562.900849903 17
 
8.3%
210491.321883503 8
 
3.9%
209573.227434185 6
 
2.9%
210456.932121326 6
 
2.9%
210491.688890281 6
 
2.9%
209966.124550614 6
 
2.9%
209556.120065618 5
 
2.4%
208589.363343145 5
 
2.4%
209563.395932094 5
 
2.4%
209542.74681331 5
 
2.4%
Other values (75) 134
65.4%
ValueCountFrequency (%)
206919.478094926 1
 
0.5%
206945.449731532 3
1.5%
206949.842815831 3
1.5%
206964.414977305 4
2.0%
206964.839324643 1
 
0.5%
206967.655618396 1
 
0.5%
206978.093333333 1
 
0.5%
206999.298639306 2
1.0%
207004.830567831 1
 
0.5%
207045.010076729 3
1.5%
ValueCountFrequency (%)
210729.459633931 1
 
0.5%
210658.051559152 4
 
2.0%
210591.787825479 2
 
1.0%
210562.900849903 17
8.3%
210491.688890281 6
 
2.9%
210491.321883503 8
3.9%
210481.077142289 3
 
1.5%
210463.282485743 3
 
1.5%
210456.932121326 6
 
2.9%
210431.832858016 1
 
0.5%

좌표정보(Y)
Real number (ℝ)

Distinct85
Distinct (%)41.9%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean445145.57
Minimum443448.89
Maximum448202.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:20.505191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443448.89
5-th percentile443508.22
Q1443620.61
median445471.97
Q3445913.54
95-th percentile446001.45
Maximum448202.43
Range4753.5397
Interquartile range (IQR)2292.9259

Descriptive statistics

Standard deviation1017.5848
Coefficient of variation (CV)0.0022859597
Kurtosis-0.75417075
Mean445145.57
Median Absolute Deviation (MAD)451.09538
Skewness-0.70621275
Sum90364550
Variance1035478.9
MonotonicityNot monotonic
2024-04-30T04:46:20.618952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443555.864703206 17
 
8.3%
443569.763243482 8
 
3.9%
445919.352243106 6
 
2.9%
443484.595603431 6
 
2.9%
443508.221246366 6
 
2.9%
446059.613892034 6
 
2.9%
445891.245190572 5
 
2.4%
445455.90405262 5
 
2.4%
445948.756207391 5
 
2.4%
445930.621574388 5
 
2.4%
Other values (75) 134
65.4%
ValueCountFrequency (%)
443448.892122874 3
 
1.5%
443465.4592322 1
 
0.5%
443484.595603431 6
 
2.9%
443508.221246366 6
 
2.9%
443526.648866499 1
 
0.5%
443549.893536475 3
 
1.5%
443555.864703206 17
8.3%
443562.753075246 3
 
1.5%
443569.763243482 8
3.9%
443574.427660288 2
 
1.0%
ValueCountFrequency (%)
448202.431833539 1
 
0.5%
446059.613892034 6
2.9%
446040.044744713 2
 
1.0%
446023.390115824 1
 
0.5%
446001.946449307 1
 
0.5%
445996.934629074 1
 
0.5%
445980.015712662 1
 
0.5%
445976.018710511 4
2.0%
445965.47506444 2
 
1.0%
445965.355231537 1
 
0.5%

위생업태명
Categorical

Distinct11
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
룸살롱
121 
<NA>
50 
카바레
14 
비어(바)살롱
 
8
고고(디스코)클럽
 
3
Other values (6)
 
9

Length

Max length12
Median length3
Mean length3.6390244
Min length2

Unique

Unique4 ?
Unique (%)2.0%

Sample

1st row룸살롱
2nd row룸살롱
3rd row고고(디스코)클럽
4th row카바레
5th row스텐드바

Common Values

ValueCountFrequency (%)
룸살롱 121
59.0%
<NA> 50
24.4%
카바레 14
 
6.8%
비어(바)살롱 8
 
3.9%
고고(디스코)클럽 3
 
1.5%
스텐드바 3
 
1.5%
관광호텔나이트(디스코) 2
 
1.0%
관광호텔나이트(카바레) 1
 
0.5%
극장식당 1
 
0.5%
기타 1
 
0.5%

Length

2024-04-30T04:46:20.729262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 121
59.0%
na 50
24.4%
카바레 14
 
6.8%
비어(바)살롱 8
 
3.9%
고고(디스코)클럽 3
 
1.5%
스텐드바 3
 
1.5%
관광호텔나이트(디스코 2
 
1.0%
관광호텔나이트(카바레 1
 
0.5%
극장식당 1
 
0.5%
기타 1
 
0.5%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.0%
Missing135
Missing (%)65.9%
Infinite0
Infinite (%)0.0%
Mean0.71428571
Minimum0
Maximum15
Zeros58
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:20.824523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4797315
Coefficient of variation (CV)3.4716241
Kurtosis21.820227
Mean0.71428571
Median Absolute Deviation (MAD)0
Skewness4.5528955
Sum50
Variance6.1490683
MonotonicityNot monotonic
2024-04-30T04:46:20.918880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 58
28.3%
1 6
 
2.9%
4 2
 
1.0%
7 1
 
0.5%
15 1
 
0.5%
12 1
 
0.5%
2 1
 
0.5%
(Missing) 135
65.9%
ValueCountFrequency (%)
0 58
28.3%
1 6
 
2.9%
2 1
 
0.5%
4 2
 
1.0%
7 1
 
0.5%
12 1
 
0.5%
15 1
 
0.5%
ValueCountFrequency (%)
15 1
 
0.5%
12 1
 
0.5%
7 1
 
0.5%
4 2
 
1.0%
2 1
 
0.5%
1 6
 
2.9%
0 58
28.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.0%
Missing135
Missing (%)65.9%
Infinite0
Infinite (%)0.0%
Mean0.61428571
Minimum0
Maximum9
Zeros57
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:21.019111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.55
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.608788
Coefficient of variation (CV)2.6189572
Kurtosis11.663391
Mean0.61428571
Median Absolute Deviation (MAD)0
Skewness3.2378118
Sum43
Variance2.5881988
MonotonicityNot monotonic
2024-04-30T04:46:21.103612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 57
27.8%
2 3
 
1.5%
5 3
 
1.5%
1 3
 
1.5%
3 2
 
1.0%
9 1
 
0.5%
4 1
 
0.5%
(Missing) 135
65.9%
ValueCountFrequency (%)
0 57
27.8%
1 3
 
1.5%
2 3
 
1.5%
3 2
 
1.0%
4 1
 
0.5%
5 3
 
1.5%
9 1
 
0.5%
ValueCountFrequency (%)
9 1
 
0.5%
5 3
 
1.5%
4 1
 
0.5%
3 2
 
1.0%
2 3
 
1.5%
1 3
 
1.5%
0 57
27.8%

영업장주변구분명
Categorical

Distinct7
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
120 
유흥업소밀집지역
55 
기타
24 
주택가주변
 
3
아파트지역
 
1
Other values (2)
 
2

Length

Max length8
Median length4
Mean length4.897561
Min length2

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st row주택가주변
2nd row주택가주변
3rd row유흥업소밀집지역
4th row유흥업소밀집지역
5th row유흥업소밀집지역

Common Values

ValueCountFrequency (%)
<NA> 120
58.5%
유흥업소밀집지역 55
26.8%
기타 24
 
11.7%
주택가주변 3
 
1.5%
아파트지역 1
 
0.5%
학교정화(상대) 1
 
0.5%
학교정화(절대) 1
 
0.5%

Length

2024-04-30T04:46:21.207151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:21.320713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
58.5%
유흥업소밀집지역 55
26.8%
기타 24
 
11.7%
주택가주변 3
 
1.5%
아파트지역 1
 
0.5%
학교정화(상대 1
 
0.5%
학교정화(절대 1
 
0.5%

등급구분명
Categorical

Distinct8
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
136 
기타
39 
자율
 
12
지도
 
6
우수
 
5
Other values (3)
 
7

Length

Max length4
Median length4
Mean length3.297561
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row기타
2nd row기타
3rd row우수
4th row지도
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 136
66.3%
기타 39
 
19.0%
자율 12
 
5.9%
지도 6
 
2.9%
우수 5
 
2.4%
갑 3
 
1.5%
을 3
 
1.5%
관리 1
 
0.5%

Length

2024-04-30T04:46:21.443704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:21.547253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
66.3%
기타 39
 
19.0%
자율 12
 
5.9%
지도 6
 
2.9%
우수 5
 
2.4%
갑 3
 
1.5%
을 3
 
1.5%
관리 1
 
0.5%

급수시설구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
158 
상수도전용
46 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.2878049
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 158
77.1%
상수도전용 46
 
22.4%
상수도(음용)지하수(주방용)겸용 1
 
0.5%

Length

2024-04-30T04:46:21.673136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:21.772694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 158
77.1%
상수도전용 46
 
22.4%
상수도(음용)지하수(주방용)겸용 1
 
0.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:21.862712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:21.952646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.058622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:22.159538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.248297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:22.333685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.428091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:22.510975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.614299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:22.700101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.787733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:22.886563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
0
 
5

Length

Max length4
Median length4
Mean length3.9268293
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> 200
97.6%
0 5
 
2.4%

Length

2024-04-30T04:46:22.986464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:46:23.081827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
97.6%
0 5
 
2.4%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.3%
Missing50
Missing (%)24.4%
Memory size542.0 B
False
154 
True
 
1
(Missing)
50 
ValueCountFrequency (%)
False 154
75.1%
True 1
 
0.5%
(Missing) 50
 
24.4%
2024-04-30T04:46:23.154513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)96.8%
Missing50
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean236.62419
Minimum38.2
Maximum1224.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-30T04:46:23.252978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.2
5-th percentile59.04
Q188.36
median133.98
Q3264
95-th percentile831.642
Maximum1224.5
Range1186.3
Interquartile range (IQR)175.64

Descriptive statistics

Standard deviation253.85082
Coefficient of variation (CV)1.0728016
Kurtosis4.2558324
Mean236.62419
Median Absolute Deviation (MAD)55.62
Skewness2.1641784
Sum36676.75
Variance64440.237
MonotonicityNot monotonic
2024-04-30T04:46:23.377634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
109.91 2
 
1.0%
138.94 2
 
1.0%
166.13 2
 
1.0%
164.37 2
 
1.0%
59.04 2
 
1.0%
48.86 1
 
0.5%
229.02 1
 
0.5%
153.9 1
 
0.5%
71.46 1
 
0.5%
70.39 1
 
0.5%
Other values (140) 140
68.3%
(Missing) 50
 
24.4%
ValueCountFrequency (%)
38.2 1
0.5%
44.45 1
0.5%
48.86 1
0.5%
55.15 1
0.5%
55.6 1
0.5%
56.24 1
0.5%
58.43 1
0.5%
59.04 2
1.0%
60.88 1
0.5%
61.2 1
0.5%
ValueCountFrequency (%)
1224.5 1
0.5%
1159.63 1
0.5%
1103.67 1
0.5%
1059.24 1
0.5%
1049.85 1
0.5%
1031.87 1
0.5%
946.32 1
0.5%
941.99 1
0.5%
784.35 1
0.5%
750.17 1
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing205
Missing (%)100.0%
Memory size1.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032300003230000-102-1977-0361919771114<NA>3폐업2폐업20070913<NA><NA><NA>02 41433311,159.63138842서울특별시 송파구 석촌동 24-0번지<NA><NA>다이너스티클럽2003-01-24 00:00:00I2018-08-31 23:59:59.0룸살롱208684.121024444900.075661룸살롱00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N1159.63<NA><NA><NA>
132300003230000-102-1980-0360319800304<NA>1영업/정상1영업<NA><NA><NA><NA>02 4853235134.64138873서울특별시 송파구 풍납동 481-1번지서울특별시 송파구 올림픽로 607 (풍납동)5519티파니2008-09-26 15:40:51I2018-08-31 23:59:59.0룸살롱210729.459634448202.431834룸살롱00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N134.64<NA><NA><NA>
232300003230000-102-1985-0361419850418<NA>3폐업2폐업20000508<NA><NA><NA>02 4212065946.32138721서울특별시 송파구 잠실동 40-1번지 롯데월드 지하3층<NA><NA>벨파레나이트2003-01-24 00:00:00I2018-08-31 23:59:59.0고고(디스코)클럽208589.363343445455.904053고고(디스코)클럽00유흥업소밀집지역우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N946.32<NA><NA><NA>
332300003230000-102-1985-0362219851028<NA>3폐업2폐업19900918<NA><NA><NA>0204189156163.86138721서울특별시 송파구 잠실동 40-1번지 롯데월드지하3층<NA><NA>유람선스탠드빠2003-03-28 00:00:00I2018-08-31 23:59:59.0카바레208589.363343445455.904053카바레12유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N163.86<NA><NA><NA>
432300003230000-102-1985-0362419850410<NA>3폐업2폐업19970425<NA><NA><NA>02 4235425559.62138805서울특별시 송파구 가락동 99-5번지<NA><NA>2002년2003-01-24 00:00:00I2018-08-31 23:59:59.0스텐드바210481.077142443448.892123스텐드바13유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N559.62<NA><NA><NA>
532300003230000-102-1986-0360219861220<NA>3폐업2폐업20110224<NA><NA><NA>02 4227943295.92138827서울특별시 송파구 방이동 37-2번지<NA><NA>카네기2005-06-02 00:00:00I2018-08-31 23:59:59.0카바레209630.559399445882.786141카바레00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N295.92<NA><NA><NA>
632300003230000-102-1986-0362319861220<NA>3폐업2폐업19971230<NA><NA><NA>02 4167481483.60138861서울특별시 송파구 잠실동 182-0번지<NA><NA>빅트2003-01-24 00:00:00I2018-08-31 23:59:59.0스텐드바207203.878704445431.920595스텐드바15유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N483.6<NA><NA><NA>
732300003230000-102-1988-0361619880420<NA>3폐업2폐업20080103<NA><NA><NA>02 4175181588.58138861서울특별시 송파구 잠실동 175번지<NA><NA>뉴월드컵2003-01-24 00:00:00I2018-08-31 23:59:59.0카바레206919.478095445370.201675카바레79유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N588.58<NA><NA><NA>
832300003230000-102-1988-0362519880627<NA>1영업/정상1영업<NA><NA><NA><NA>02 4208538375.06138828서울특별시 송파구 방이동 46-3번지서울특별시 송파구 오금로11길 47 (방이동)5544관광월드컵스텐드바2017-11-28 15:09:37I2018-08-31 23:59:59.0스텐드바209868.080809445956.537235스텐드바<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N375.06<NA><NA><NA>
932300003230000-102-1988-0362819880901<NA>3폐업2폐업19961228<NA><NA><NA>02 00000238.92138915서울특별시 송파구 잠실동 40-1번지<NA><NA>윈저바2003-01-24 00:00:00I2018-08-31 23:59:59.0비어(바)살롱208589.363343445455.904053비어(바)살롱44기타지도상수도(음용)지하수(주방용)겸용<NA><NA><NA><NA><NA><NA><NA><NA>N238.92<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
19532300003230000-102-2017-000042017-05-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.41138-805서울특별시 송파구 가락동 98-7서울특별시 송파구 송파대로28길 13, 지하1층 101호 (가락동, 거북이빌딩)5719골드12024-04-24 13:17:27U2023-12-03 22:06:00.0룸살롱210491.321884443569.763243<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19632300003230000-102-2018-0000120180629<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.30138803서울특별시 송파구 가락동 79-4 세화빌딩서울특별시 송파구 송파대로28길 20, 세화빌딩 지하1층 102,103호 (가락동)5718뉴홍콩2022-05-23 15:15:28U2021-12-04 22:05:00.0간이주점210562.90085443555.864703<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19732300003230000-102-2019-000012019-02-11<NA>3폐업2폐업2023-12-04<NA><NA><NA><NA>52.54138-827서울특별시 송파구 방이동 34-4 타임모텔 지하1층 102호서울특별시 송파구 올림픽로32길 4, 타임모텔 지하1층 102호 (방이동)5542스펀지 뮤직타운2023-12-04 17:21:43U2022-11-02 00:06:00.0룸살롱209542.746813445930.621574<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19832300003230000-102-2019-0000220190712<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1,031.87138844서울특별시 송파구 석촌동 158번지 호텔 레이크 지하2층서울특별시 송파구 석촌호수로 216, 호텔 레이크 지하2층 (석촌동)5610나인2020-06-08 15:34:03U2020-06-10 02:40:00.0룸살롱208851.639894444965.423277룸살롱<NA><NA>주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y1031.87<NA><NA><NA>
19932300003230000-102-2021-000012021-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>91.44138-713서울특별시 송파구 가락동 79-5 밀리아나2차오피스텔서울특별시 송파구 송파대로28길 24, 밀리아나2차오피스텔 2층 208,210호 (가락동)5718샴푸2024-02-01 15:38:55U2023-12-02 00:03:00.0룸살롱210591.787825443574.42766<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20032300003230000-102-2021-000022021-03-24<NA>3폐업2폐업2023-12-05<NA><NA><NA><NA>565.43138-842서울특별시 송파구 석촌동 1-7 로사나관광호텔 지하1층서울특별시 송파구 삼학사로 98, 로사나관광호텔 지하1층 (석촌동)5612윈투2023-11-20 09:43:14U2022-10-31 22:02:00.0룸살롱208554.799609444868.795427<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20132300003230000-102-2021-000032021-06-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.88138-803서울특별시 송파구 가락동 79-4 세화빌딩 지하1층 106-1호서울특별시 송파구 송파대로28길 20, 세화빌딩 지하1층 106-1호 (가락동)5718지중해2024-03-26 10:01:11U2023-12-02 22:08:00.0룸살롱210562.90085443555.864703<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20232300003230000-102-2022-0000120220621<NA>1영업/정상1영업<NA><NA><NA><NA><NA>140.71138827서울특별시 송파구 방이동 34-9 B1호서울특별시 송파구 올림픽로32길 14 (방이동)5542Ace뮤직타운2022-06-21 09:31:05I2021-12-05 22:03:00.0기타209568.288855445854.428066<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20332300003230000-102-2023-000022023-06-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>565.00138-842서울특별시 송파구 석촌동 1-7 로사나관광호텔서울특별시 송파구 삼학사로 98, 로사나관광호텔 지하2층 (석촌동)5612더뉴윈2023-06-29 18:02:08I2022-12-07 00:01:00.0룸살롱208554.799609444868.795427<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20432300003230000-102-2023-000032023-10-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>135.30138-805서울특별시 송파구 가락동 98-7 거북이빌딩 지하1층 107호서울특별시 송파구 송파대로28길 13, 거북이빌딩 지하1층 107호 (가락동)5719벤츠2023-10-10 14:32:32I2022-10-30 23:02:00.0룸살롱210491.321884443569.763243<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>