Overview

Dataset statistics

Number of variables44
Number of observations230
Missing cells2560
Missing cells (%)25.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory84.6 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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18567/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (59.2%)Imbalance
총인원 is highly imbalanced (80.3%)Imbalance
본사종업원수 is highly imbalanced (80.3%)Imbalance
공장사무직종업원수 is highly imbalanced (80.3%)Imbalance
공장판매직종업원수 is highly imbalanced (80.3%)Imbalance
공장생산직종업원수 is highly imbalanced (80.3%)Imbalance
보증액 is highly imbalanced (80.3%)Imbalance
월세액 is highly imbalanced (80.3%)Imbalance
인허가취소일자 has 230 (100.0%) missing valuesMissing
폐업일자 has 127 (55.2%) missing valuesMissing
휴업시작일자 has 230 (100.0%) missing valuesMissing
휴업종료일자 has 230 (100.0%) missing valuesMissing
재개업일자 has 230 (100.0%) missing valuesMissing
전화번호 has 65 (28.3%) missing valuesMissing
도로명주소 has 55 (23.9%) missing valuesMissing
도로명우편번호 has 61 (26.5%) missing valuesMissing
남성종사자수 has 135 (58.7%) missing valuesMissing
여성종사자수 has 140 (60.9%) missing valuesMissing
건물소유구분명 has 230 (100.0%) missing valuesMissing
다중이용업소여부 has 66 (28.7%) missing valuesMissing
시설총규모 has 66 (28.7%) missing valuesMissing
전통업소지정번호 has 230 (100.0%) missing valuesMissing
전통업소주된음식 has 230 (100.0%) missing valuesMissing
홈페이지 has 230 (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 30 (13.0%) zerosZeros
여성종사자수 has 24 (10.4%) zerosZeros

Reproduction

Analysis started2024-04-17 17:54:48.548637
Analysis finished2024-04-17 17:54:49.061631
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3150000
230 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 230
100.0%

Length

2024-04-18T02:54:49.108680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:49.173327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 230
100.0%

관리번호
Text

UNIQUE 

Distinct230
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-18T02:54:49.321270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5060
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

Unique230 ?
Unique (%)100.0%

Sample

1st row3150000-102-1977-00755
2nd row3150000-102-1977-00777
3rd row3150000-102-1978-00750
4th row3150000-102-1978-00785
5th row3150000-102-1978-00786
ValueCountFrequency (%)
3150000-102-1977-00755 1
 
0.4%
3150000-102-2002-00003 1
 
0.4%
3150000-102-2002-00005 1
 
0.4%
3150000-102-2002-00006 1
 
0.4%
3150000-102-2003-00001 1
 
0.4%
3150000-102-2004-00001 1
 
0.4%
3150000-102-2004-00002 1
 
0.4%
3150000-102-2004-00003 1
 
0.4%
3150000-102-2007-00001 1
 
0.4%
3150000-102-2007-00002 1
 
0.4%
Other values (220) 220
95.7%
2024-04-18T02:54:49.568766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1990
39.3%
1 696
 
13.8%
- 690
 
13.6%
2 440
 
8.7%
5 287
 
5.7%
3 285
 
5.6%
9 228
 
4.5%
7 190
 
3.8%
8 145
 
2.9%
6 60
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4370
86.4%
Dash Punctuation 690
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1990
45.5%
1 696
 
15.9%
2 440
 
10.1%
5 287
 
6.6%
3 285
 
6.5%
9 228
 
5.2%
7 190
 
4.3%
8 145
 
3.3%
6 60
 
1.4%
4 49
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 690
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5060
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1990
39.3%
1 696
 
13.8%
- 690
 
13.6%
2 440
 
8.7%
5 287
 
5.7%
3 285
 
5.6%
9 228
 
4.5%
7 190
 
3.8%
8 145
 
2.9%
6 60
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1990
39.3%
1 696
 
13.8%
- 690
 
13.6%
2 440
 
8.7%
5 287
 
5.7%
3 285
 
5.6%
9 228
 
4.5%
7 190
 
3.8%
8 145
 
2.9%
6 60
 
1.2%

인허가일자
Date

Distinct203
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1977-08-10 00:00:00
Maximum2023-07-17 00:00:00
2024-04-18T02:54:49.676173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:54:50.031429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
127 
3
103 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 127
55.2%
3 103
44.8%

Length

2024-04-18T02:54:50.132068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:50.199189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 127
55.2%
3 103
44.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
영업/정상
127 
폐업
103 

Length

Max length5
Median length5
Mean length3.6565217
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 127
55.2%
폐업 103
44.8%

Length

2024-04-18T02:54:50.277675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:50.351202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 127
55.2%
폐업 103
44.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
127 
2
103 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 127
55.2%
2 103
44.8%

Length

2024-04-18T02:54:50.422623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:50.489295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 127
55.2%
2 103
44.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
영업
127 
폐업
103 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 127
55.2%
폐업 103
44.8%

Length

2024-04-18T02:54:50.560503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:50.629605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 127
55.2%
폐업 103
44.8%

폐업일자
Date

MISSING 

Distinct95
Distinct (%)92.2%
Missing127
Missing (%)55.2%
Memory size1.9 KiB
Minimum1990-04-28 00:00:00
Maximum2024-01-31 00:00:00
2024-04-18T02:54:50.711730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:54:50.817096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct155
Distinct (%)93.9%
Missing65
Missing (%)28.3%
Memory size1.9 KiB
2024-04-18T02:54:50.985694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.7212121
Min length2

Characters and Unicode

Total characters1604
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

Unique150 ?
Unique (%)90.9%

Sample

1st row02 6945858
2nd row0226939000
3rd row02 26057112
4th row0206974142
5th row0226016776
ValueCountFrequency (%)
02 41
 
20.5%
0226957498 2
 
1.0%
0226904113 2
 
1.0%
0226043124 2
 
1.0%
0226064468 2
 
1.0%
0226041919 1
 
0.5%
6976157 1
 
0.5%
20657439 1
 
0.5%
0226957880 1
 
0.5%
0226023644 1
 
0.5%
Other values (146) 146
73.0%
2024-04-18T02:54:51.258725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 346
21.6%
0 337
21.0%
6 262
16.3%
9 133
 
8.3%
5 89
 
5.5%
4 84
 
5.2%
8 81
 
5.0%
7 79
 
4.9%
1 79
 
4.9%
3 75
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1565
97.6%
Space Separator 39
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 346
22.1%
0 337
21.5%
6 262
16.7%
9 133
 
8.5%
5 89
 
5.7%
4 84
 
5.4%
8 81
 
5.2%
7 79
 
5.0%
1 79
 
5.0%
3 75
 
4.8%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 346
21.6%
0 337
21.0%
6 262
16.3%
9 133
 
8.3%
5 89
 
5.5%
4 84
 
5.2%
8 81
 
5.0%
7 79
 
4.9%
1 79
 
4.9%
3 75
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 346
21.6%
0 337
21.0%
6 262
16.3%
9 133
 
8.3%
5 89
 
5.5%
4 84
 
5.2%
8 81
 
5.0%
7 79
 
4.9%
1 79
 
4.9%
3 75
 
4.7%

소재지면적
Text

Distinct219
Distinct (%)95.6%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2024-04-18T02:54:51.561274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.4672489
Min length3

Characters and Unicode

Total characters1252
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

Unique213 ?
Unique (%)93.0%

Sample

1st row153.24
2nd row209.78
3rd row88.34
4th row80.40
5th row215.52
ValueCountFrequency (%)
121.44 3
 
1.3%
85.50 3
 
1.3%
73.65 3
 
1.3%
99.00 3
 
1.3%
78.60 2
 
0.9%
97.00 2
 
0.9%
542.85 1
 
0.4%
407.09 1
 
0.4%
1,270.83 1
 
0.4%
72.09 1
 
0.4%
Other values (209) 209
91.3%
2024-04-18T02:54:51.957321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 229
18.3%
1 128
10.2%
0 118
9.4%
9 114
9.1%
4 111
8.9%
8 107
8.5%
2 97
7.7%
6 96
7.7%
5 89
 
7.1%
7 84
 
6.7%
Other values (2) 79
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020
81.5%
Other Punctuation 232
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 128
12.5%
0 118
11.6%
9 114
11.2%
4 111
10.9%
8 107
10.5%
2 97
9.5%
6 96
9.4%
5 89
8.7%
7 84
8.2%
3 76
7.5%
Other Punctuation
ValueCountFrequency (%)
. 229
98.7%
, 3
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 229
18.3%
1 128
10.2%
0 118
9.4%
9 114
9.1%
4 111
8.9%
8 107
8.5%
2 97
7.7%
6 96
7.7%
5 89
 
7.1%
7 84
 
6.7%
Other values (2) 79
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 229
18.3%
1 128
10.2%
0 118
9.4%
9 114
9.1%
4 111
8.9%
8 107
8.5%
2 97
7.7%
6 96
7.7%
5 89
 
7.1%
7 84
 
6.7%
Other values (2) 79
 
6.3%

소재지우편번호
Categorical

Distinct43
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
157928
34 
157909
27 
157916
24 
157210
21 
157910
12 
Other values (38)
112 

Length

Max length7
Median length6
Mean length6.1826087
Min length6

Unique

Unique20 ?
Unique (%)8.7%

Sample

1st row157881
2nd row157-928
3rd row157-909
4th row157910
5th row157918

Common Values

ValueCountFrequency (%)
157928 34
14.8%
157909 27
 
11.7%
157916 24
 
10.4%
157210 21
 
9.1%
157910 12
 
5.2%
157-210 10
 
4.3%
157915 10
 
4.3%
157-909 8
 
3.5%
157-928 8
 
3.5%
157853 7
 
3.0%
Other values (33) 69
30.0%

Length

2024-04-18T02:54:52.077568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
157928 34
14.8%
157909 27
 
11.7%
157916 24
 
10.4%
157210 21
 
9.1%
157910 12
 
5.2%
157-210 10
 
4.3%
157915 10
 
4.3%
157-909 8
 
3.5%
157-928 8
 
3.5%
157866 7
 
3.0%
Other values (33) 69
30.0%

지번주소
Text

Distinct220
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-18T02:54:52.241123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length29.869565
Min length19

Characters and Unicode

Total characters6870
Distinct characters93
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

Unique210 ?
Unique (%)91.3%

Sample

1st row서울특별시 강서구 화곡동 343-31번지
2nd row서울특별시 강서구 화곡동 1117-15 (지하 1층)
3rd row서울특별시 강서구 화곡동 903-3 (지하 1층)
4th row서울특별시 강서구 화곡동 938-23번지
5th row서울특별시 강서구 화곡동 1006-10번지 (지하 1층) 1호
ValueCountFrequency (%)
서울특별시 230
16.8%
강서구 230
16.8%
화곡동 172
12.6%
지하 111
 
8.1%
1층 101
 
7.4%
지상 38
 
2.8%
마곡동 31
 
2.3%
뉴골든타워 31
 
2.3%
외 20
 
1.5%
2층 16
 
1.2%
Other values (240) 386
28.3%
2024-04-18T02:54:52.524667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1277
18.6%
서 460
 
6.7%
1 455
 
6.6%
지 319
 
4.6%
- 240
 
3.5%
시 235
 
3.4%
동 233
 
3.4%
구 230
 
3.3%
강 230
 
3.3%
울 230
 
3.3%
Other values (83) 2961
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3647
53.1%
Decimal Number 1390
 
20.2%
Space Separator 1277
 
18.6%
Dash Punctuation 240
 
3.5%
Open Punctuation 152
 
2.2%
Close Punctuation 152
 
2.2%
Math Symbol 7
 
0.1%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 460
12.6%
지 319
 
8.7%
시 235
 
6.4%
동 233
 
6.4%
구 230
 
6.3%
강 230
 
6.3%
울 230
 
6.3%
별 230
 
6.3%
특 230
 
6.3%
곡 205
 
5.6%
Other values (64) 1045
28.7%
Decimal Number
ValueCountFrequency (%)
1 455
32.7%
0 142
 
10.2%
9 140
 
10.1%
7 121
 
8.7%
5 110
 
7.9%
3 107
 
7.7%
2 99
 
7.1%
6 96
 
6.9%
4 62
 
4.5%
8 58
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
1277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3647
53.1%
Common 3220
46.9%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 460
12.6%
지 319
 
8.7%
시 235
 
6.4%
동 233
 
6.4%
구 230
 
6.3%
강 230
 
6.3%
울 230
 
6.3%
별 230
 
6.3%
특 230
 
6.3%
곡 205
 
5.6%
Other values (64) 1045
28.7%
Common
ValueCountFrequency (%)
1277
39.7%
1 455
 
14.1%
- 240
 
7.5%
( 152
 
4.7%
) 152
 
4.7%
0 142
 
4.4%
9 140
 
4.3%
7 121
 
3.8%
5 110
 
3.4%
3 107
 
3.3%
Other values (6) 324
 
10.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
o 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3647
53.1%
ASCII 3223
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1277
39.6%
1 455
 
14.1%
- 240
 
7.4%
( 152
 
4.7%
) 152
 
4.7%
0 142
 
4.4%
9 140
 
4.3%
7 121
 
3.8%
5 110
 
3.4%
3 107
 
3.3%
Other values (9) 327
 
10.1%
Hangul
ValueCountFrequency (%)
서 460
12.6%
지 319
 
8.7%
시 235
 
6.4%
동 233
 
6.4%
구 230
 
6.3%
강 230
 
6.3%
울 230
 
6.3%
별 230
 
6.3%
특 230
 
6.3%
곡 205
 
5.6%
Other values (64) 1045
28.7%

도로명주소
Text

MISSING 

Distinct169
Distinct (%)96.6%
Missing55
Missing (%)23.9%
Memory size1.9 KiB
2024-04-18T02:54:52.686883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length49
Mean length36.188571
Min length23

Characters and Unicode

Total characters6333
Distinct characters106
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)93.1%

Sample

1st row서울특별시 강서구 화곡로 320, 지하 1층 (화곡동, 6동)
2nd row서울특별시 강서구 강서로 17, 지하 1층 (화곡동, 1동)
3rd row서울특별시 강서구 강서로 239, 지하 1층 1호 (화곡동, 3동)
4th row서울특별시 강서구 가로공원로76길 6, 지하 1층 (화곡동, 1동)
5th row서울특별시 강서구 강서로 245, 지하 1층 (화곡동, 3동)
ValueCountFrequency (%)
서울특별시 175
 
12.7%
강서구 175
 
12.7%
화곡동 128
 
9.3%
지하 105
 
7.6%
1층 97
 
7.1%
6동 52
 
3.8%
화곡로 48
 
3.5%
1동 45
 
3.3%
마곡중앙6로 31
 
2.3%
89 31
 
2.3%
Other values (213) 487
35.4%
2024-04-18T02:54:52.965627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1199
18.9%
서 391
 
6.2%
동 300
 
4.7%
, 294
 
4.6%
1 262
 
4.1%
곡 247
 
3.9%
강 216
 
3.4%
화 192
 
3.0%
시 180
 
2.8%
) 178
 
2.8%
Other values (96) 2874
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3482
55.0%
Space Separator 1199
 
18.9%
Decimal Number 974
 
15.4%
Other Punctuation 294
 
4.6%
Close Punctuation 178
 
2.8%
Open Punctuation 178
 
2.8%
Dash Punctuation 21
 
0.3%
Math Symbol 5
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 391
 
11.2%
동 300
 
8.6%
곡 247
 
7.1%
강 216
 
6.2%
화 192
 
5.5%
시 180
 
5.2%
로 176
 
5.1%
울 175
 
5.0%
구 175
 
5.0%
별 175
 
5.0%
Other values (78) 1255
36.0%
Decimal Number
ValueCountFrequency (%)
1 262
26.9%
6 142
14.6%
2 111
11.4%
3 97
 
10.0%
8 75
 
7.7%
0 66
 
6.8%
5 61
 
6.3%
4 58
 
6.0%
7 51
 
5.2%
9 51
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
1199
100.0%
Other Punctuation
ValueCountFrequency (%)
, 294
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3482
55.0%
Common 2849
45.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 391
 
11.2%
동 300
 
8.6%
곡 247
 
7.1%
강 216
 
6.2%
화 192
 
5.5%
시 180
 
5.2%
로 176
 
5.1%
울 175
 
5.0%
구 175
 
5.0%
별 175
 
5.0%
Other values (78) 1255
36.0%
Common
ValueCountFrequency (%)
1199
42.1%
, 294
 
10.3%
1 262
 
9.2%
) 178
 
6.2%
( 178
 
6.2%
6 142
 
5.0%
2 111
 
3.9%
3 97
 
3.4%
8 75
 
2.6%
0 66
 
2.3%
Other values (6) 247
 
8.7%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3482
55.0%
ASCII 2851
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1199
42.1%
, 294
 
10.3%
1 262
 
9.2%
) 178
 
6.2%
( 178
 
6.2%
6 142
 
5.0%
2 111
 
3.9%
3 97
 
3.4%
8 75
 
2.6%
0 66
 
2.3%
Other values (8) 249
 
8.7%
Hangul
ValueCountFrequency (%)
서 391
 
11.2%
동 300
 
8.6%
곡 247
 
7.1%
강 216
 
6.2%
화 192
 
5.5%
시 180
 
5.2%
로 176
 
5.1%
울 175
 
5.0%
구 175
 
5.0%
별 175
 
5.0%
Other values (78) 1255
36.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)20.1%
Missing61
Missing (%)26.5%
Infinite0
Infinite (%)0.0%
Mean7723.6686
Minimum7527
Maximum7803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:53.061580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7527
5-th percentile7622
Q17658
median7751
Q37778
95-th percentile7803
Maximum7803
Range276
Interquartile range (IQR)120

Descriptive statistics

Standard deviation68.8242
Coefficient of variation (CV)0.0089108173
Kurtosis-0.5739169
Mean7723.6686
Median Absolute Deviation (MAD)52
Skewness-0.53446281
Sum1305300
Variance4736.7705
MonotonicityNot monotonic
2024-04-18T02:54:53.150336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
7803 31
13.5%
7658 21
 
9.1%
7777 16
 
7.0%
7775 14
 
6.1%
7778 14
 
6.1%
7686 11
 
4.8%
7653 8
 
3.5%
7687 5
 
2.2%
7678 4
 
1.7%
7774 4
 
1.7%
Other values (24) 41
17.8%
(Missing) 61
26.5%
ValueCountFrequency (%)
7527 2
 
0.9%
7539 1
 
0.4%
7557 2
 
0.9%
7607 1
 
0.4%
7620 2
 
0.9%
7622 3
 
1.3%
7623 1
 
0.4%
7649 4
1.7%
7653 8
3.5%
7654 1
 
0.4%
ValueCountFrequency (%)
7803 31
13.5%
7778 14
6.1%
7777 16
7.0%
7776 2
 
0.9%
7775 14
6.1%
7774 4
 
1.7%
7773 1
 
0.4%
7761 1
 
0.4%
7760 1
 
0.4%
7751 1
 
0.4%

사업장명
Text

Distinct210
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-18T02:54:53.381829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length10
Mean length4.4826087
Min length1

Characters and Unicode

Total characters1031
Distinct characters267
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique196 ?
Unique (%)85.2%

Sample

1st row사랑방
2nd row애플
3rd row샤넬노래바
4th row수궁주점
5th row팡팡노래바
ValueCountFrequency (%)
노래바 10
 
3.9%
황진이 4
 
1.6%
귀족 3
 
1.2%
힐링노래바 3
 
1.2%
팡팡노래바 3
 
1.2%
승리노래바 3
 
1.2%
에프엠 2
 
0.8%
노래주점 2
 
0.8%
명품 2
 
0.8%
별밤 2
 
0.8%
Other values (211) 223
86.8%
2024-04-18T02:54:53.725600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 90
 
8.7%
래 87
 
8.4%
바 58
 
5.6%
27
 
2.6%
이 25
 
2.4%
스 17
 
1.6%
타 15
 
1.5%
럽 14
 
1.4%
리 13
 
1.3%
팡 13
 
1.3%
Other values (257) 672
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 953
92.4%
Space Separator 27
 
2.6%
Uppercase Letter 15
 
1.5%
Decimal Number 12
 
1.2%
Open Punctuation 7
 
0.7%
Close Punctuation 7
 
0.7%
Lowercase Letter 5
 
0.5%
Other Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 90
 
9.4%
래 87
 
9.1%
바 58
 
6.1%
이 25
 
2.6%
스 17
 
1.8%
타 15
 
1.6%
럽 14
 
1.5%
리 13
 
1.4%
팡 13
 
1.4%
비 13
 
1.4%
Other values (238) 608
63.8%
Uppercase Letter
ValueCountFrequency (%)
S 4
26.7%
B 4
26.7%
O 3
20.0%
D 2
13.3%
M 1
 
6.7%
K 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
3 3
25.0%
2 3
25.0%
1 3
25.0%
4 1
 
8.3%
5 1
 
8.3%
6 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
80.0%
w 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
, 1
 
20.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 952
92.3%
Common 58
 
5.6%
Latin 20
 
1.9%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 90
 
9.5%
래 87
 
9.1%
바 58
 
6.1%
이 25
 
2.6%
스 17
 
1.8%
타 15
 
1.6%
럽 14
 
1.5%
리 13
 
1.4%
팡 13
 
1.4%
비 13
 
1.4%
Other values (237) 607
63.8%
Common
ValueCountFrequency (%)
27
46.6%
( 7
 
12.1%
) 7
 
12.1%
. 4
 
6.9%
3 3
 
5.2%
2 3
 
5.2%
1 3
 
5.2%
4 1
 
1.7%
, 1
 
1.7%
5 1
 
1.7%
Latin
ValueCountFrequency (%)
S 4
20.0%
e 4
20.0%
B 4
20.0%
O 3
15.0%
D 2
10.0%
M 1
 
5.0%
K 1
 
5.0%
w 1
 
5.0%
Han
ValueCountFrequency (%)
情 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 952
92.3%
ASCII 78
 
7.6%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
노 90
 
9.5%
래 87
 
9.1%
바 58
 
6.1%
이 25
 
2.6%
스 17
 
1.8%
타 15
 
1.6%
럽 14
 
1.5%
리 13
 
1.4%
팡 13
 
1.4%
비 13
 
1.4%
Other values (237) 607
63.8%
ASCII
ValueCountFrequency (%)
27
34.6%
( 7
 
9.0%
) 7
 
9.0%
S 4
 
5.1%
e 4
 
5.1%
B 4
 
5.1%
. 4
 
5.1%
O 3
 
3.8%
3 3
 
3.8%
2 3
 
3.8%
Other values (9) 12
15.4%
CJK
ValueCountFrequency (%)
情 1
100.0%

최종수정일자
Date

Distinct216
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2000-01-26 00:00:00
Maximum2024-04-03 13:55:33
2024-04-18T02:54:53.839029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:54:53.945453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
U
128 
I
102 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 128
55.7%
I 102
44.3%

Length

2024-04-18T02:54:54.050999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:54.121667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 128
55.7%
i 102
44.3%

데이터갱신일자
Date

Distinct121
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-18T02:54:54.198886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:54:54.299549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct9
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
룸살롱
180 
카바레
21 
노래클럽
 
8
고고(디스코)클럽
 
6
간이주점
 
5
Other values (4)
 
10

Length

Max length12
Median length3
Mean length3.3956522
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row룸살롱
2nd row카바레
3rd row룸살롱
4th row룸살롱
5th row룸살롱

Common Values

ValueCountFrequency (%)
룸살롱 180
78.3%
카바레 21
 
9.1%
노래클럽 8
 
3.5%
고고(디스코)클럽 6
 
2.6%
간이주점 5
 
2.2%
비어(바)살롱 4
 
1.7%
관광호텔나이트(디스코) 3
 
1.3%
기타 2
 
0.9%
스텐드바 1
 
0.4%

Length

2024-04-18T02:54:54.397667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:54.491644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
룸살롱 180
78.3%
카바레 21
 
9.1%
노래클럽 8
 
3.5%
고고(디스코)클럽 6
 
2.6%
간이주점 5
 
2.2%
비어(바)살롱 4
 
1.7%
관광호텔나이트(디스코 3
 
1.3%
기타 2
 
0.9%
스텐드바 1
 
0.4%

좌표정보(X)
Real number (ℝ)

Distinct149
Distinct (%)65.4%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean186073.09
Minimum182914.77
Maximum189200.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:54.618129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182914.77
5-th percentile183129.64
Q1185554.3
median186391.5
Q3186682.13
95-th percentile186880.34
Maximum189200.15
Range6285.377
Interquartile range (IQR)1127.8321

Descriptive statistics

Standard deviation1063.8784
Coefficient of variation (CV)0.0057175295
Kurtosis3.3596584
Mean186073.09
Median Absolute Deviation (MAD)369.55259
Skewness-1.2580424
Sum42424665
Variance1131837.2
MonotonicityNot monotonic
2024-04-18T02:54:54.748510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185553.0 21
 
9.1%
185554.299381324 10
 
4.3%
186301.687755524 5
 
2.2%
186780.470195989 4
 
1.7%
186742.624404896 4
 
1.7%
186437.390021875 4
 
1.7%
185803.611845769 4
 
1.7%
186355.084186229 3
 
1.3%
186657.899817438 3
 
1.3%
186397.14456266 3
 
1.3%
Other values (139) 167
72.6%
ValueCountFrequency (%)
182914.770762913 2
0.9%
182924.505322144 1
0.4%
182940.995178251 1
0.4%
182963.925350795 2
0.9%
183042.639859252 1
0.4%
183095.853129506 1
0.4%
183102.245899868 1
0.4%
183118.280868805 1
0.4%
183119.924231899 2
0.9%
183147.678410643 1
0.4%
ValueCountFrequency (%)
189200.147733153 1
0.4%
189172.250232972 1
0.4%
189156.529751731 1
0.4%
189036.252426103 1
0.4%
187851.415781065 1
0.4%
187052.323132425 1
0.4%
187030.425999035 1
0.4%
187020.243445713 1
0.4%
186908.920793249 2
0.9%
186892.947389352 2
0.9%

좌표정보(Y)
Real number (ℝ)

Distinct149
Distinct (%)65.4%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean449441.04
Minimum447358.64
Maximum451956.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:54.871340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447358.64
5-th percentile447406.34
Q1447664.96
median449937.84
Q3450268.11
95-th percentile451105.03
Maximum451956.8
Range4598.163
Interquartile range (IQR)2603.1508

Descriptive statistics

Standard deviation1323.9495
Coefficient of variation (CV)0.002945769
Kurtosis-1.1638689
Mean449441.04
Median Absolute Deviation (MAD)942.16058
Skewness-0.43513753
Sum1.0247256 × 108
Variance1752842.2
MonotonicityNot monotonic
2024-04-18T02:54:54.970170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450880.0 21
 
9.1%
450891.312361248 10
 
4.3%
447468.61600408 5
 
2.2%
450119.939314207 4
 
1.7%
450021.683309823 4
 
1.7%
447472.670706556 4
 
1.7%
447396.45923655 4
 
1.7%
447404.189780345 3
 
1.3%
450054.478268775 3
 
1.3%
447525.601346498 3
 
1.3%
Other values (139) 167
72.6%
ValueCountFrequency (%)
447358.637705214 1
 
0.4%
447360.27075665 1
 
0.4%
447360.483643506 1
 
0.4%
447380.297316673 1
 
0.4%
447396.45923655 4
1.7%
447404.189780345 3
1.3%
447405.536849132 1
 
0.4%
447407.818736501 1
 
0.4%
447417.889884789 1
 
0.4%
447429.674761034 3
1.3%
ValueCountFrequency (%)
451956.80073079 1
0.4%
451907.410307195 1
0.4%
451399.992756058 1
0.4%
451273.211597643 2
0.9%
451268.389266826 2
0.9%
451207.059791662 1
0.4%
451175.952498834 1
0.4%
451174.11874841 1
0.4%
451105.609040835 2
0.9%
451103.946915643 1
0.4%

위생업태명
Categorical

Distinct10
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
룸살롱
129 
<NA>
66 
카바레
14 
고고(디스코)클럽
 
5
노래클럽
 
5
Other values (5)
 
11

Length

Max length12
Median length3
Mean length3.5782609
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 129
56.1%
<NA> 66
28.7%
카바레 14
 
6.1%
고고(디스코)클럽 5
 
2.2%
노래클럽 5
 
2.2%
비어(바)살롱 3
 
1.3%
간이주점 3
 
1.3%
관광호텔나이트(디스코) 2
 
0.9%
기타 2
 
0.9%
스텐드바 1
 
0.4%

Length

2024-04-18T02:54:55.066463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:55.173614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
룸살롱 129
56.1%
na 66
28.7%
카바레 14
 
6.1%
고고(디스코)클럽 5
 
2.2%
노래클럽 5
 
2.2%
비어(바)살롱 3
 
1.3%
간이주점 3
 
1.3%
관광호텔나이트(디스코 2
 
0.9%
기타 2
 
0.9%
스텐드바 1
 
0.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)7.4%
Missing135
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean1.3052632
Minimum0
Maximum7
Zeros30
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:55.257605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4445325
Coefficient of variation (CV)1.1066983
Kurtosis3.6377583
Mean1.3052632
Median Absolute Deviation (MAD)1
Skewness1.7833829
Sum124
Variance2.0866741
MonotonicityNot monotonic
2024-04-18T02:54:55.337278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 33
 
14.3%
0 30
 
13.0%
2 22
 
9.6%
5 5
 
2.2%
3 3
 
1.3%
7 1
 
0.4%
6 1
 
0.4%
(Missing) 135
58.7%
ValueCountFrequency (%)
0 30
13.0%
1 33
14.3%
2 22
9.6%
3 3
 
1.3%
5 5
 
2.2%
6 1
 
0.4%
7 1
 
0.4%
ValueCountFrequency (%)
7 1
 
0.4%
6 1
 
0.4%
5 5
 
2.2%
3 3
 
1.3%
2 22
9.6%
1 33
14.3%
0 30
13.0%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)10.0%
Missing140
Missing (%)60.9%
Infinite0
Infinite (%)0.0%
Mean2.4444444
Minimum0
Maximum25
Zeros24
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:55.423405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile7
Maximum25
Range25
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.298318
Coefficient of variation (CV)1.3493119
Kurtosis24.394726
Mean2.4444444
Median Absolute Deviation (MAD)1
Skewness4.0720516
Sum220
Variance10.878901
MonotonicityNot monotonic
2024-04-18T02:54:55.514109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 24
 
10.4%
2 20
 
8.7%
1 15
 
6.5%
3 12
 
5.2%
5 8
 
3.5%
4 5
 
2.2%
10 3
 
1.3%
7 2
 
0.9%
25 1
 
0.4%
(Missing) 140
60.9%
ValueCountFrequency (%)
0 24
10.4%
1 15
6.5%
2 20
8.7%
3 12
5.2%
4 5
 
2.2%
5 8
 
3.5%
7 2
 
0.9%
10 3
 
1.3%
25 1
 
0.4%
ValueCountFrequency (%)
25 1
 
0.4%
10 3
 
1.3%
7 2
 
0.9%
5 8
 
3.5%
4 5
 
2.2%
3 12
5.2%
2 20
8.7%
1 15
6.5%
0 24
10.4%

영업장주변구분명
Categorical

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
137 
유흥업소밀집지역
65 
기타
23 
학교정화(상대)
 
3
아파트지역
 
1

Length

Max length8
Median length4
Mean length4.9913043
Min length2

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 137
59.6%
유흥업소밀집지역 65
28.3%
기타 23
 
10.0%
학교정화(상대) 3
 
1.3%
아파트지역 1
 
0.4%
주택가주변 1
 
0.4%

Length

2024-04-18T02:54:55.628440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:55.973873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
59.6%
유흥업소밀집지역 65
28.3%
기타 23
 
10.0%
학교정화(상대 3
 
1.3%
아파트지역 1
 
0.4%
주택가주변 1
 
0.4%

등급구분명
Categorical

Distinct7
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
160 
자율
36 
기타
19 
갑
 
6
지도
 
5
Other values (2)
 
4

Length

Max length4
Median length4
Mean length3.3565217
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
69.6%
자율 36
 
15.7%
기타 19
 
8.3%
갑 6
 
2.6%
지도 5
 
2.2%
을 2
 
0.9%
관리 2
 
0.9%

Length

2024-04-18T02:54:56.063231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.155938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 160
69.6%
자율 36
 
15.7%
기타 19
 
8.3%
갑 6
 
2.6%
지도 5
 
2.2%
을 2
 
0.9%
관리 2
 
0.9%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
상수도전용
116 
<NA>
114 

Length

Max length5
Median length5
Mean length4.5043478
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 116
50.4%
<NA> 114
49.6%

Length

2024-04-18T02:54:56.244553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.315913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 116
50.4%
na 114
49.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:56.407993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.476177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:56.552111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.622939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:56.700133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.787116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:56.859786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:56.932084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:57.004573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:57.077757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:57.151654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:57.219812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
223 
0
 
7

Length

Max length4
Median length4
Mean length3.9086957
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> 223
97.0%
0 7
 
3.0%

Length

2024-04-18T02:54:57.293720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:54:57.366774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
97.0%
0 7
 
3.0%

다중이용업소여부
Boolean

MISSING 

Distinct2
Distinct (%)1.2%
Missing66
Missing (%)28.7%
Memory size592.0 B
False
112 
True
52 
(Missing)
66 
ValueCountFrequency (%)
False 112
48.7%
True 52
22.6%
(Missing) 66
28.7%
2024-04-18T02:54:57.427770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)96.3%
Missing66
Missing (%)28.7%
Infinite0
Infinite (%)0.0%
Mean165.8478
Minimum0
Maximum1194.25
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-18T02:54:57.512815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.357
Q182.2075
median104.125
Q3187.23
95-th percentile508.047
Maximum1194.25
Range1194.25
Interquartile range (IQR)105.0225

Descriptive statistics

Standard deviation167.3813
Coefficient of variation (CV)1.0092464
Kurtosis14.893647
Mean165.8478
Median Absolute Deviation (MAD)34.755
Skewness3.4158816
Sum27199.04
Variance28016.5
MonotonicityNot monotonic
2024-04-18T02:54:57.617512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121.44 3
 
1.3%
78.6 2
 
0.9%
73.65 2
 
0.9%
0.0 2
 
0.9%
97.0 2
 
0.9%
132.47 1
 
0.4%
84.48 1
 
0.4%
72.44 1
 
0.4%
99.21 1
 
0.4%
69.45 1
 
0.4%
Other values (148) 148
64.3%
(Missing) 66
28.7%
ValueCountFrequency (%)
0.0 2
0.9%
20.47 1
0.4%
38.78 1
0.4%
42.04 1
0.4%
45.9 1
0.4%
54.11 1
0.4%
55.24 1
0.4%
56.7 1
0.4%
61.08 1
0.4%
62.4 1
0.4%
ValueCountFrequency (%)
1194.25 1
0.4%
1052.0 1
0.4%
921.9 1
0.4%
568.3 1
0.4%
547.13 1
0.4%
542.85 1
0.4%
533.25 1
0.4%
523.07 1
0.4%
512.13 1
0.4%
484.91 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing230
Missing (%)100.0%
Memory size2.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031500003150000-102-1977-0075519770810<NA>3폐업2폐업20050928<NA><NA><NA>02 6945858153.24157881서울특별시 강서구 화곡동 343-31번지<NA><NA>사랑방2004-04-12 00:00:00I2018-08-31 23:59:59.0룸살롱186347.306715447755.73614룸살롱22기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N153.24<NA><NA><NA>
131500003150000-102-1977-007771977-09-17<NA>1영업/정상1영업<NA><NA><NA><NA>0226939000209.78157-928서울특별시 강서구 화곡동 1117-15 (지하 1층)서울특별시 강서구 화곡로 320, 지하 1층 (화곡동, 6동)7658애플2023-06-09 10:40:06U2022-12-05 23:01:00.0카바레186720.89236450028.161482<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231500003150000-102-1978-007501978-07-01<NA>1영업/정상1영업<NA><NA><NA><NA>02 2605711288.34157-909서울특별시 강서구 화곡동 903-3 (지하 1층)서울특별시 강서구 강서로 17, 지하 1층 (화곡동, 1동)7778샤넬노래바2024-01-22 10:01:28U2023-11-30 22:04:00.0룸살롱186473.612062447474.632068<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331500003150000-102-1978-0078519780501<NA>3폐업2폐업19980630<NA><NA><NA>020697414280.40157910서울특별시 강서구 화곡동 938-23번지<NA><NA>수궁주점2011-02-08 13:41:29I2018-08-31 23:59:59.0룸살롱185744.43921447538.415878룸살롱23유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N80.4<NA><NA><NA>
431500003150000-102-1978-0078619780626<NA>1영업/정상1영업<NA><NA><NA><NA><NA>215.52157918서울특별시 강서구 화곡동 1006-10번지 (지하 1층) 1호서울특별시 강서구 강서로 239, 지하 1층 1호 (화곡동, 3동)7705팡팡노래바2016-08-10 09:35:35I2018-08-31 23:59:59.0룸살롱185436.074265449449.262454룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N215.52<NA><NA><NA>
531500003150000-102-1979-007471979-08-26<NA>1영업/정상1영업<NA><NA><NA><NA>0226016776114.64157-884서울특별시 강서구 화곡동 372-3 (지하 1층)서울특별시 강서구 가로공원로76길 6, 지하 1층 (화곡동, 1동)7761로망스2023-08-16 11:43:42U2022-12-07 23:08:00.0룸살롱185520.500773448289.439635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
631500003150000-102-1979-0076219790602<NA>1영업/정상1영업<NA><NA><NA><NA>022604602789.84157918서울특별시 강서구 화곡동 1006-3 (지하 1층)서울특별시 강서구 강서로 245, 지하 1층 (화곡동, 3동)7705오렌지 노래바2022-06-10 13:56:08U2021-12-05 23:02:00.0룸살롱185438.34133449492.230136<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731500003150000-102-1979-0077519790618<NA>3폐업2폐업20120102<NA><NA><NA>02 693486891.38157925서울특별시 강서구 화곡동 1070-8번지<NA><NA>퀸2007-07-27 10:02:12I2018-08-31 23:59:59.0룸살롱185323.854746448640.215487룸살롱00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N91.38<NA><NA><NA>
831500003150000-102-1979-0816119790423<NA>1영업/정상1영업<NA><NA><NA><NA>022606275196.42157880서울특별시 강서구 화곡동 342-55 (지하 1층)서울특별시 강서구 강서로 34, 지하 1층 (화곡동, 8동)7760팡팡노래바2023-01-02 14:55:54U2022-12-01 00:04:00.0룸살롱186453.187638447642.840238<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931500003150000-102-1980-0072619800306<NA>3폐업2폐업20020909<NA><NA><NA>020664555286.70157827서울특별시 강서구 내발산동 667-2번지<NA><NA>까치2002-09-09 00:00:00I2018-08-31 23:59:59.0카바레185511.580534450320.239205카바레12기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N86.7<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
22031500003150000-102-2022-0000220220126<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.46157909서울특별시 강서구 화곡동 901-15 시온빌딩 301호서울특별시 강서구 강서로7길 35, 시온빌딩 3층 301호 (화곡동)7777나인노래바2022-01-26 12:26:15I2022-01-28 00:22:39.0룸살롱186301.687756447468.616004룸살롱00<NA><NA>상수도전용00000<NA>00Y85.46<NA><NA><NA>
22131500003150000-102-2022-0000320220204<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.40157909서울특별시 강서구 화곡동 901-15 시온빌딩 201호서울특별시 강서구 강서로7길 35, 시온빌딩 2층 201호 (화곡동)7777스타노래바2022-02-04 15:54:10I2022-02-08 00:22:38.0룸살롱186301.687756447468.616004룸살롱00<NA><NA>상수도전용00000<NA>00Y62.4<NA><NA><NA>
22231500003150000-102-2022-0000420220404<NA>1영업/정상1영업<NA><NA><NA><NA><NA>81.69157909서울특별시 강서구 화곡동 901-15 시온빌딩 지하1층서울특별시 강서구 강서로7길 35, 시온빌딩 지하1층 (화곡동)7777로마노래바2022-10-13 14:20:18U2021-10-30 23:05:00.0룸살롱186301.687756447468.616004<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22331500003150000-102-2022-0000520220413<NA>1영업/정상1영업<NA><NA><NA><NA><NA>58.62157909서울특별시 강서구 화곡동 901-15 시온빌딩 501호서울특별시 강서구 강서로7길 35, 시온빌딩 5층 501호 (화곡동)7777힐링노래바2022-09-07 14:17:48U2021-12-08 23:01:00.0룸살롱186301.687756447468.616004<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22431500003150000-102-2022-000062022-11-14<NA>3폐업2폐업2023-12-07<NA><NA><NA><NA>444.30157-928서울특별시 강서구 화곡동 1117-10 지하1층서울특별시 강서구 화곡로 318-1, 지하1층 (화곡동)7658강구 별밤2023-12-07 07:51:22U2022-11-02 00:09:00.0노래클럽186712.75199450014.905649<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22531500003150000-102-2023-000012023-03-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>94.22157-909서울특별시 강서구 화곡동 902-10 2층서울특별시 강서구 강서로7길 19, 2층 (화곡동)7777휴노래바2023-11-04 09:51:05U2022-11-01 00:06:00.0룸살롱186380.634607447481.210076<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22631500003150000-102-2023-000022023-04-04<NA>3폐업2폐업2023-04-11<NA><NA><NA><NA>85.50157-910서울특별시 강서구 화곡동 936-3 2층서울특별시 강서구 곰달래로16길 26, 2층 (화곡동)7775골든노래팡2023-04-11 09:53:16U2022-12-03 23:03:00.0룸살롱185799.419614447429.674761<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22731500003150000-102-2023-000042023-05-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.50157-910서울특별시 강서구 화곡동 936-3 3층서울특별시 강서구 곰달래로16길 26, 3층 (화곡동)7775디올노래팡2023-12-14 14:50:22U2022-11-01 23:06:00.0룸살롱185799.419614447429.674761<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22831500003150000-102-2023-000052023-05-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.50157-910서울특별시 강서구 화곡동 936-3 4층서울특별시 강서구 곰달래로16길 26, 4층 (화곡동)7775골든노래타운4층2023-05-18 17:35:49I2022-12-04 22:00:00.0룸살롱185799.419614447429.674761<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22931500003150000-102-2023-000062023-07-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.67157-909서울특별시 강서구 화곡동 901-1 네스트인 Bo1호서울특별시 강서구 강서로7길 23, 네스트인 B01호 (화곡동)7777티파니노래바2023-10-10 11:30:00I2022-10-30 23:02:00.0룸살롱186354.662866447475.102501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>