Overview

Dataset statistics

Number of variables44
Number of observations220
Missing cells2117
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory80.9 KiB
Average record size in memory376.6 B

Variable types

Categorical20
Text6
DateTime4
Unsupported7
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18557/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총인원 is highly imbalanced (86.9%)Imbalance
본사종업원수 is highly imbalanced (86.9%)Imbalance
공장사무직종업원수 is highly imbalanced (86.9%)Imbalance
공장판매직종업원수 is highly imbalanced (86.9%)Imbalance
공장생산직종업원수 is highly imbalanced (86.9%)Imbalance
보증액 is highly imbalanced (86.9%)Imbalance
월세액 is highly imbalanced (86.9%)Imbalance
다중이용업소여부 is highly imbalanced (60.4%)Imbalance
전통업소주된음식 is highly imbalanced (95.8%)Imbalance
인허가취소일자 has 220 (100.0%) missing valuesMissing
폐업일자 has 53 (24.1%) missing valuesMissing
휴업시작일자 has 220 (100.0%) missing valuesMissing
휴업종료일자 has 220 (100.0%) missing valuesMissing
재개업일자 has 220 (100.0%) missing valuesMissing
전화번호 has 38 (17.3%) missing valuesMissing
도로명주소 has 114 (51.8%) missing valuesMissing
도로명우편번호 has 127 (57.7%) missing valuesMissing
좌표정보(X) has 17 (7.7%) missing valuesMissing
좌표정보(Y) has 17 (7.7%) missing valuesMissing
남성종사자수 has 75 (34.1%) missing valuesMissing
여성종사자수 has 78 (35.5%) missing valuesMissing
건물소유구분명 has 220 (100.0%) missing valuesMissing
다중이용업소여부 has 28 (12.7%) missing valuesMissing
시설총규모 has 28 (12.7%) missing valuesMissing
전통업소지정번호 has 220 (100.0%) missing valuesMissing
홈페이지 has 220 (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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 96 (43.6%) zerosZeros
여성종사자수 has 92 (41.8%) zerosZeros

Reproduction

Analysis started2024-04-17 21:01:00.643355
Analysis finished2024-04-17 21:01:01.158484
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3050000
220 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 220
100.0%

Length

2024-04-18T06:01:01.202684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:01.632970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 220
100.0%

관리번호
Text

UNIQUE 

Distinct220
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-18T06:01:01.769958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4840
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

Unique220 ?
Unique (%)100.0%

Sample

1st row3050000-102-1969-08469
2nd row3050000-102-1969-08470
3rd row3050000-102-1971-08408
4th row3050000-102-1971-08427
5th row3050000-102-1971-08443
ValueCountFrequency (%)
3050000-102-1969-08469 1
 
0.5%
3050000-102-2001-12568 1
 
0.5%
3050000-102-2001-13068 1
 
0.5%
3050000-102-2000-12283 1
 
0.5%
3050000-102-2000-12297 1
 
0.5%
3050000-102-2000-12300 1
 
0.5%
3050000-102-2000-12310 1
 
0.5%
3050000-102-2000-12328 1
 
0.5%
3050000-102-2000-12370 1
 
0.5%
3050000-102-2000-12395 1
 
0.5%
Other values (210) 210
95.5%
2024-04-18T06:01:02.021108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1919
39.6%
- 660
 
13.6%
1 531
 
11.0%
2 423
 
8.7%
5 284
 
5.9%
3 283
 
5.8%
8 236
 
4.9%
9 196
 
4.0%
4 168
 
3.5%
7 76
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4180
86.4%
Dash Punctuation 660
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1919
45.9%
1 531
 
12.7%
2 423
 
10.1%
5 284
 
6.8%
3 283
 
6.8%
8 236
 
5.6%
9 196
 
4.7%
4 168
 
4.0%
7 76
 
1.8%
6 64
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 660
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1919
39.6%
- 660
 
13.6%
1 531
 
11.0%
2 423
 
8.7%
5 284
 
5.9%
3 283
 
5.8%
8 236
 
4.9%
9 196
 
4.0%
4 168
 
3.5%
7 76
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1919
39.6%
- 660
 
13.6%
1 531
 
11.0%
2 423
 
8.7%
5 284
 
5.9%
3 283
 
5.8%
8 236
 
4.9%
9 196
 
4.0%
4 168
 
3.5%
7 76
 
1.6%

인허가일자
Date

Distinct203
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1969-05-02 00:00:00
Maximum2020-07-23 00:00:00
2024-04-18T06:01:02.129425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:02.247898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
167 
1
53 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 167
75.9%
1 53
 
24.1%

Length

2024-04-18T06:01:02.362240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:02.435072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 167
75.9%
1 53
 
24.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
167 
영업/정상
53 

Length

Max length5
Median length2
Mean length2.7227273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 167
75.9%
영업/정상 53
 
24.1%

Length

2024-04-18T06:01:02.522551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:02.603210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 167
75.9%
영업/정상 53
 
24.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2
167 
1
53 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 167
75.9%
1 53
 
24.1%

Length

2024-04-18T06:01:02.683817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:02.778544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 167
75.9%
1 53
 
24.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
167 
영업
53 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 167
75.9%
영업 53
 
24.1%

Length

2024-04-18T06:01:02.858601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:02.936674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 167
75.9%
영업 53
 
24.1%

폐업일자
Date

MISSING 

Distinct149
Distinct (%)89.2%
Missing53
Missing (%)24.1%
Memory size1.8 KiB
Minimum1990-10-19 00:00:00
Maximum2023-11-10 00:00:00
2024-04-18T06:01:03.021494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:03.122193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

전화번호
Text

MISSING 

Distinct166
Distinct (%)91.2%
Missing38
Missing (%)17.3%
Memory size1.8 KiB
2024-04-18T06:01:03.297091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9395604
Min length2

Characters and Unicode

Total characters1809
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

Unique156 ?
Unique (%)85.7%

Sample

1st row0222178383
2nd row02 9279692
3rd row0209621739
4th row02 9660821
5th row0222177661
ValueCountFrequency (%)
02 49
 
21.5%
0200000000 6
 
2.6%
0222164877 2
 
0.9%
0222166139 2
 
0.9%
0209625611 2
 
0.9%
22164877 2
 
0.9%
0222140727 2
 
0.9%
0222449696 2
 
0.9%
0222150616 2
 
0.9%
0222454000 2
 
0.9%
Other values (157) 157
68.9%
2024-04-18T06:01:03.587350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 499
27.6%
0 345
19.1%
4 154
 
8.5%
6 142
 
7.8%
1 130
 
7.2%
9 121
 
6.7%
3 104
 
5.7%
5 86
 
4.8%
7 85
 
4.7%
8 83
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1749
96.7%
Space Separator 60
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 499
28.5%
0 345
19.7%
4 154
 
8.8%
6 142
 
8.1%
1 130
 
7.4%
9 121
 
6.9%
3 104
 
5.9%
5 86
 
4.9%
7 85
 
4.9%
8 83
 
4.7%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1809
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 499
27.6%
0 345
19.1%
4 154
 
8.5%
6 142
 
7.8%
1 130
 
7.2%
9 121
 
6.7%
3 104
 
5.7%
5 86
 
4.8%
7 85
 
4.7%
8 83
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1809
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 499
27.6%
0 345
19.1%
4 154
 
8.5%
6 142
 
7.8%
1 130
 
7.2%
9 121
 
6.7%
3 104
 
5.7%
5 86
 
4.8%
7 85
 
4.7%
8 83
 
4.6%

소재지면적
Text

Distinct206
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-18T06:01:03.882117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.7681818
Min length5

Characters and Unicode

Total characters1269
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

Unique195 ?
Unique (%)88.6%

Sample

1st row279.36
2nd row226.81
3rd row790.50
4th row97.00
5th row84.87
ValueCountFrequency (%)
520.06 4
 
1.8%
609.73 3
 
1.4%
94.50 2
 
0.9%
300.72 2
 
0.9%
186.00 2
 
0.9%
322.13 2
 
0.9%
147.50 2
 
0.9%
115.86 2
 
0.9%
360.82 2
 
0.9%
97.00 2
 
0.9%
Other values (196) 197
89.5%
2024-04-18T06:01:04.278466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 220
17.3%
1 141
11.1%
0 139
11.0%
2 113
8.9%
9 108
8.5%
6 99
7.8%
4 98
7.7%
8 94
7.4%
3 90
7.1%
7 84
 
6.6%
Other values (2) 83
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1043
82.2%
Other Punctuation 226
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 141
13.5%
0 139
13.3%
2 113
10.8%
9 108
10.4%
6 99
9.5%
4 98
9.4%
8 94
9.0%
3 90
8.6%
7 84
8.1%
5 77
7.4%
Other Punctuation
ValueCountFrequency (%)
. 220
97.3%
, 6
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 220
17.3%
1 141
11.1%
0 139
11.0%
2 113
8.9%
9 108
8.5%
6 99
7.8%
4 98
7.7%
8 94
7.4%
3 90
7.1%
7 84
 
6.6%
Other values (2) 83
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 220
17.3%
1 141
11.1%
0 139
11.0%
2 113
8.9%
9 108
8.5%
6 99
7.8%
4 98
7.7%
8 94
7.4%
3 90
7.1%
7 84
 
6.6%
Other values (2) 83
 
6.5%

소재지우편번호
Categorical

Distinct38
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
130840
58 
130842
29 
130851
24 
130805
21 
130-840
9 
Other values (33)
79 

Length

Max length7
Median length6
Mean length6.0681818
Min length4

Unique

Unique17 ?
Unique (%)7.7%

Sample

1st row130842
2nd row130810
3rd row130010
4th row130876
5th row130854

Common Values

ValueCountFrequency (%)
130840 58
26.4%
130842 29
13.2%
130851 24
10.9%
130805 21
 
9.5%
130-840 9
 
4.1%
130846 8
 
3.6%
130876 6
 
2.7%
130030 5
 
2.3%
130802 5
 
2.3%
130809 5
 
2.3%
Other values (28) 50
22.7%

Length

2024-04-18T06:01:04.391886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
130840 58
26.4%
130842 29
13.2%
130851 24
10.9%
130805 21
 
9.5%
130-840 9
 
4.1%
130846 8
 
3.6%
130876 6
 
2.7%
130802 5
 
2.3%
130809 5
 
2.3%
130030 5
 
2.3%
Other values (28) 50
22.7%

지번주소
Text

Distinct185
Distinct (%)84.9%
Missing2
Missing (%)0.9%
Memory size1.8 KiB
2024-04-18T06:01:04.597895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39.5
Mean length25.825688
Min length20

Characters and Unicode

Total characters5630
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)72.9%

Sample

1st row서울특별시 동대문구 장안동 373-1번지
2nd row서울특별시 동대문구 신설동 76-25 2층
3rd row서울특별시 동대문구 청량리동 176-18번지
4th row서울특별시 동대문구 휘경동 320-2번지
5th row서울특별시 동대문구 전농동 295-7 지하1층
ValueCountFrequency (%)
서울특별시 218
21.7%
동대문구 218
21.7%
장안동 117
 
11.7%
답십리동 43
 
4.3%
지하1층 35
 
3.5%
전농동 27
 
2.7%
장한로 12
 
1.2%
휘경동 8
 
0.8%
청량리동 7
 
0.7%
용두동 6
 
0.6%
Other values (210) 312
31.1%
2024-04-18T06:01:04.916811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
975
 
17.3%
동 438
 
7.8%
문 227
 
4.0%
대 222
 
3.9%
서 219
 
3.9%
울 218
 
3.9%
특 218
 
3.9%
별 218
 
3.9%
시 218
 
3.9%
구 218
 
3.9%
Other values (63) 2459
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3281
58.3%
Decimal Number 1067
 
19.0%
Space Separator 975
 
17.3%
Dash Punctuation 205
 
3.6%
Close Punctuation 48
 
0.9%
Open Punctuation 48
 
0.9%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 438
13.3%
문 227
 
6.9%
대 222
 
6.8%
서 219
 
6.7%
울 218
 
6.6%
특 218
 
6.6%
별 218
 
6.6%
시 218
 
6.6%
구 218
 
6.6%
지 215
 
6.6%
Other values (48) 870
26.5%
Decimal Number
ValueCountFrequency (%)
3 186
17.4%
6 162
15.2%
1 158
14.8%
2 135
12.7%
4 103
9.7%
5 89
8.3%
7 84
7.9%
9 65
 
6.1%
0 57
 
5.3%
8 28
 
2.6%
Space Separator
ValueCountFrequency (%)
975
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3281
58.3%
Common 2349
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 438
13.3%
문 227
 
6.9%
대 222
 
6.8%
서 219
 
6.7%
울 218
 
6.6%
특 218
 
6.6%
별 218
 
6.6%
시 218
 
6.6%
구 218
 
6.6%
지 215
 
6.6%
Other values (48) 870
26.5%
Common
ValueCountFrequency (%)
975
41.5%
- 205
 
8.7%
3 186
 
7.9%
6 162
 
6.9%
1 158
 
6.7%
2 135
 
5.7%
4 103
 
4.4%
5 89
 
3.8%
7 84
 
3.6%
9 65
 
2.8%
Other values (5) 187
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3281
58.3%
ASCII 2349
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
975
41.5%
- 205
 
8.7%
3 186
 
7.9%
6 162
 
6.9%
1 158
 
6.7%
2 135
 
5.7%
4 103
 
4.4%
5 89
 
3.8%
7 84
 
3.6%
9 65
 
2.8%
Other values (5) 187
 
8.0%
Hangul
ValueCountFrequency (%)
동 438
13.3%
문 227
 
6.9%
대 222
 
6.8%
서 219
 
6.7%
울 218
 
6.6%
특 218
 
6.6%
별 218
 
6.6%
시 218
 
6.6%
구 218
 
6.6%
지 215
 
6.6%
Other values (48) 870
26.5%

도로명주소
Text

MISSING 

Distinct101
Distinct (%)95.3%
Missing114
Missing (%)51.8%
Memory size1.8 KiB
2024-04-18T06:01:05.182981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length31.273585
Min length22

Characters and Unicode

Total characters3315
Distinct characters73
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)91.5%

Sample

1st row서울특별시 동대문구 한빛로 6-1, 2층 (신설동)
2nd row서울특별시 동대문구 회기로 189 (휘경동)
3rd row서울특별시 동대문구 사가정로 111, 지하1층 (전농동)
4th row서울특별시 동대문구 전농로16길 12 (전농동)
5th row서울특별시 동대문구 천호대로 128, 지하1층 (용두동)
ValueCountFrequency (%)
서울특별시 106
16.8%
동대문구 106
16.8%
지하1층 50
 
7.9%
장안동 46
 
7.3%
장한로 40
 
6.3%
천호대로 12
 
1.9%
전농동 11
 
1.7%
답십리동 10
 
1.6%
왕산로 9
 
1.4%
92 8
 
1.3%
Other values (135) 234
37.0%
2024-04-18T06:01:05.545578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
 
15.9%
동 213
 
6.4%
1 160
 
4.8%
장 143
 
4.3%
( 135
 
4.1%
) 135
 
4.1%
로 122
 
3.7%
대 121
 
3.7%
문 117
 
3.5%
울 106
 
3.2%
Other values (63) 1537
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1940
58.5%
Space Separator 526
 
15.9%
Decimal Number 462
 
13.9%
Open Punctuation 135
 
4.1%
Close Punctuation 135
 
4.1%
Other Punctuation 101
 
3.0%
Dash Punctuation 15
 
0.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 213
 
11.0%
장 143
 
7.4%
로 122
 
6.3%
대 121
 
6.2%
문 117
 
6.0%
울 106
 
5.5%
서 106
 
5.5%
특 106
 
5.5%
구 106
 
5.5%
별 106
 
5.5%
Other values (47) 694
35.8%
Decimal Number
ValueCountFrequency (%)
1 160
34.6%
2 86
18.6%
0 33
 
7.1%
4 31
 
6.7%
9 30
 
6.5%
6 28
 
6.1%
3 26
 
5.6%
8 24
 
5.2%
7 23
 
5.0%
5 21
 
4.5%
Space Separator
ValueCountFrequency (%)
526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1940
58.5%
Common 1375
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 213
 
11.0%
장 143
 
7.4%
로 122
 
6.3%
대 121
 
6.2%
문 117
 
6.0%
울 106
 
5.5%
서 106
 
5.5%
특 106
 
5.5%
구 106
 
5.5%
별 106
 
5.5%
Other values (47) 694
35.8%
Common
ValueCountFrequency (%)
526
38.3%
1 160
 
11.6%
( 135
 
9.8%
) 135
 
9.8%
, 101
 
7.3%
2 86
 
6.3%
0 33
 
2.4%
4 31
 
2.3%
9 30
 
2.2%
6 28
 
2.0%
Other values (6) 110
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1940
58.5%
ASCII 1375
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
526
38.3%
1 160
 
11.6%
( 135
 
9.8%
) 135
 
9.8%
, 101
 
7.3%
2 86
 
6.3%
0 33
 
2.4%
4 31
 
2.3%
9 30
 
2.2%
6 28
 
2.0%
Other values (6) 110
 
8.0%
Hangul
ValueCountFrequency (%)
동 213
 
11.0%
장 143
 
7.4%
로 122
 
6.3%
대 121
 
6.2%
문 117
 
6.0%
울 106
 
5.5%
서 106
 
5.5%
특 106
 
5.5%
구 106
 
5.5%
별 106
 
5.5%
Other values (47) 694
35.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)28.0%
Missing127
Missing (%)57.7%
Infinite0
Infinite (%)0.0%
Mean2599.6559
Minimum2400
Maximum2645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:05.647381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2445
Q12580
median2624
Q32639
95-th percentile2641.4
Maximum2645
Range245
Interquartile range (IQR)59

Descriptive statistics

Standard deviation60.715748
Coefficient of variation (CV)0.023355302
Kurtosis2.8361006
Mean2599.6559
Median Absolute Deviation (MAD)15
Skewness-1.8692546
Sum241768
Variance3686.4021
MonotonicityNot monotonic
2024-04-18T06:01:05.750855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2639 26
 
11.8%
2624 13
 
5.9%
2637 9
 
4.1%
2559 6
 
2.7%
2622 5
 
2.3%
2645 5
 
2.3%
2604 3
 
1.4%
2445 3
 
1.4%
2580 3
 
1.4%
2554 2
 
0.9%
Other values (16) 18
 
8.2%
(Missing) 127
57.7%
ValueCountFrequency (%)
2400 1
 
0.5%
2406 1
 
0.5%
2412 1
 
0.5%
2445 3
1.4%
2446 1
 
0.5%
2488 1
 
0.5%
2506 1
 
0.5%
2525 2
0.9%
2547 1
 
0.5%
2554 2
0.9%
ValueCountFrequency (%)
2645 5
 
2.3%
2639 26
11.8%
2637 9
 
4.1%
2636 1
 
0.5%
2633 1
 
0.5%
2625 1
 
0.5%
2624 13
5.9%
2622 5
 
2.3%
2604 3
 
1.4%
2603 1
 
0.5%

사업장명
Text

Distinct202
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-18T06:01:05.983222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.0954545
Min length1

Characters and Unicode

Total characters901
Distinct characters262
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)84.1%

Sample

1st row구찌 구찌
2nd row갤럭시
3rd row태평양
4th row텐프로
5th row에스
ValueCountFrequency (%)
앵콜 3
 
1.3%
탄금대 2
 
0.9%
텐프로 2
 
0.9%
카니발 2
 
0.9%
샤롯데 2
 
0.9%
라벤드 2
 
0.9%
더블클럽 2
 
0.9%
발리 2
 
0.9%
벤즈 2
 
0.9%
워싱턴 2
 
0.9%
Other values (200) 209
90.9%
2024-04-18T06:01:06.324025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 23
 
2.6%
주 23
 
2.6%
노 22
 
2.4%
이 22
 
2.4%
럽 20
 
2.2%
리 19
 
2.1%
아 18
 
2.0%
래 18
 
2.0%
클 16
 
1.8%
바 16
 
1.8%
Other values (252) 704
78.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 846
93.9%
Uppercase Letter 12
 
1.3%
Decimal Number 11
 
1.2%
Space Separator 10
 
1.1%
Lowercase Letter 6
 
0.7%
Close Punctuation 5
 
0.6%
Open Punctuation 5
 
0.6%
Other Punctuation 3
 
0.3%
Dash Punctuation 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 23
 
2.7%
주 23
 
2.7%
노 22
 
2.6%
이 22
 
2.6%
럽 20
 
2.4%
리 19
 
2.2%
아 18
 
2.1%
래 18
 
2.1%
클 16
 
1.9%
바 16
 
1.9%
Other values (227) 649
76.7%
Uppercase Letter
ValueCountFrequency (%)
I 3
25.0%
S 2
16.7%
B 2
16.7%
P 1
 
8.3%
V 1
 
8.3%
A 1
 
8.3%
R 1
 
8.3%
M 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
0 4
36.4%
7 2
18.2%
8 2
18.2%
2 2
18.2%
5 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
f 2
33.3%
o 1
16.7%
g 1
16.7%
n 1
16.7%
a 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
＃ 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 846
93.9%
Common 36
 
4.0%
Latin 19
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 23
 
2.7%
주 23
 
2.7%
노 22
 
2.6%
이 22
 
2.6%
럽 20
 
2.4%
리 19
 
2.2%
아 18
 
2.1%
래 18
 
2.1%
클 16
 
1.9%
바 16
 
1.9%
Other values (227) 649
76.7%
Latin
ValueCountFrequency (%)
I 3
15.8%
S 2
10.5%
f 2
10.5%
B 2
10.5%
o 1
 
5.3%
P 1
 
5.3%
V 1
 
5.3%
Ⅱ 1
 
5.3%
g 1
 
5.3%
A 1
 
5.3%
Other values (4) 4
21.1%
Common
ValueCountFrequency (%)
10
27.8%
) 5
13.9%
( 5
13.9%
0 4
 
11.1%
7 2
 
5.6%
8 2
 
5.6%
. 2
 
5.6%
- 2
 
5.6%
2 2
 
5.6%
＃ 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 846
93.9%
ASCII 53
 
5.9%
None 1
 
0.1%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 23
 
2.7%
주 23
 
2.7%
노 22
 
2.6%
이 22
 
2.6%
럽 20
 
2.4%
리 19
 
2.2%
아 18
 
2.1%
래 18
 
2.1%
클 16
 
1.9%
바 16
 
1.9%
Other values (227) 649
76.7%
ASCII
ValueCountFrequency (%)
10
18.9%
) 5
 
9.4%
( 5
 
9.4%
0 4
 
7.5%
I 3
 
5.7%
7 2
 
3.8%
8 2
 
3.8%
S 2
 
3.8%
. 2
 
3.8%
- 2
 
3.8%
Other values (13) 16
30.2%
None
ValueCountFrequency (%)
＃ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct186
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1999-12-14 00:00:00
Maximum2024-04-09 14:22:15
2024-04-18T06:01:06.429270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:06.530824image/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 size1.8 KiB
I
154 
U
66 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 154
70.0%
U 66
30.0%

Length

2024-04-18T06:01:06.639504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:06.723389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 154
70.0%
u 66
30.0%

데이터갱신일자
Date

Distinct64
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:01:00
2024-04-18T06:01:06.827809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:01:06.937833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct12
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
룸살롱
141 
카바레
22 
스텐드바
20 
비어(바)살롱
15 
고고(디스코)클럽
 
5
Other values (7)
17 

Length

Max length12
Median length3
Mean length3.7772727
Min length2

Unique

Unique3 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 141
64.1%
카바레 22
 
10.0%
스텐드바 20
 
9.1%
비어(바)살롱 15
 
6.8%
고고(디스코)클럽 5
 
2.3%
간이주점 5
 
2.3%
관광호텔나이트(디스코) 4
 
1.8%
노래클럽 3
 
1.4%
관광호텔나이트(카바레) 2
 
0.9%
요정 1
 
0.5%
Other values (2) 2
 
0.9%

Length

2024-04-18T06:01:07.043948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 141
64.1%
카바레 22
 
10.0%
스텐드바 20
 
9.1%
비어(바)살롱 15
 
6.8%
고고(디스코)클럽 5
 
2.3%
간이주점 5
 
2.3%
관광호텔나이트(디스코 4
 
1.8%
노래클럽 3
 
1.4%
관광호텔나이트(카바레 2
 
0.9%
요정 1
 
0.5%
Other values (2) 2
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)56.7%
Missing17
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean205376.6
Minimum202090.99
Maximum206295.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:07.144985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202090.99
5-th percentile203757.01
Q1204735.36
median205998.37
Q3206144.35
95-th percentile206255.33
Maximum206295.6
Range4204.6127
Interquartile range (IQR)1408.9887

Descriptive statistics

Standard deviation986.88917
Coefficient of variation (CV)0.0048052659
Kurtosis0.33579452
Mean205376.6
Median Absolute Deviation (MAD)248.68201
Skewness-1.052831
Sum41691450
Variance973950.24
MonotonicityNot monotonic
2024-04-18T06:01:07.251781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206162.986259812 6
 
2.7%
206143.713444885 5
 
2.3%
206231.420255296 5
 
2.3%
204901.263300148 4
 
1.8%
204802.884455346 4
 
1.8%
206199.953197537 4
 
1.8%
203757.008715438 4
 
1.8%
206097.029464604 4
 
1.8%
203904.268269626 4
 
1.8%
206057.985138022 3
 
1.4%
Other values (105) 160
72.7%
(Missing) 17
 
7.7%
ValueCountFrequency (%)
202090.987353843 2
0.9%
202116.938316772 1
 
0.5%
203082.865189471 1
 
0.5%
203155.504921512 1
 
0.5%
203257.607703086 1
 
0.5%
203341.366235945 1
 
0.5%
203358.086492638 1
 
0.5%
203613.502302469 1
 
0.5%
203727.459358046 1
 
0.5%
203757.008715438 4
1.8%
ValueCountFrequency (%)
206295.600068259 1
 
0.5%
206281.642488779 1
 
0.5%
206280.849675503 1
 
0.5%
206279.689993328 3
1.4%
206275.752951579 2
0.9%
206269.105763658 2
0.9%
206255.326876991 3
1.4%
206247.056427436 1
 
0.5%
206246.145219342 1
 
0.5%
206239.099846845 1
 
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)56.7%
Missing17
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean452252.71
Minimum451025.9
Maximum455771.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:07.355486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451025.9
5-th percentile451178.52
Q1451814.92
median451997.93
Q3452814.78
95-th percentile454087.76
Maximum455771.62
Range4745.718
Interquartile range (IQR)999.8601

Descriptive statistics

Standard deviation869.56457
Coefficient of variation (CV)0.0019227404
Kurtosis3.3634468
Mean452252.71
Median Absolute Deviation (MAD)226.39198
Skewness1.6133796
Sum91807301
Variance756142.54
MonotonicityNot monotonic
2024-04-18T06:01:07.459959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451957.496740385 6
 
2.7%
451918.270046244 5
 
2.3%
452041.476809255 5
 
2.3%
451439.040451239 4
 
1.8%
451543.494717439 4
 
1.8%
451997.934849601 4
 
1.8%
452923.162315716 4
 
1.8%
451827.438245305 4
 
1.8%
452972.731550191 4
 
1.8%
451879.220901722 3
 
1.4%
Other values (105) 160
72.7%
(Missing) 17
 
7.7%
ValueCountFrequency (%)
451025.902075739 1
0.5%
451038.454241239 1
0.5%
451053.76563095 2
0.9%
451057.528462082 2
0.9%
451065.321633611 2
0.9%
451070.709075884 1
0.5%
451080.986788942 1
0.5%
451170.628868201 1
0.5%
451249.571870528 2
0.9%
451252.386694413 1
0.5%
ValueCountFrequency (%)
455771.62005247 1
0.5%
455651.759148378 1
0.5%
455648.594299927 1
0.5%
455520.929097871 1
0.5%
454289.920176996 1
0.5%
454273.621685626 1
0.5%
454263.792000066 1
0.5%
454203.717217672 1
0.5%
454149.049376394 2
0.9%
454094.532255786 1
0.5%

위생업태명
Categorical

Distinct13
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
룸살롱
121 
<NA>
28 
카바레
21 
스텐드바
17 
비어(바)살롱
14 
Other values (8)
19 

Length

Max length12
Median length3
Mean length3.8590909
Min length2

Unique

Unique4 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 121
55.0%
<NA> 28
 
12.7%
카바레 21
 
9.5%
스텐드바 17
 
7.7%
비어(바)살롱 14
 
6.4%
고고(디스코)클럽 5
 
2.3%
관광호텔나이트(디스코) 4
 
1.8%
간이주점 4
 
1.8%
관광호텔나이트(카바레) 2
 
0.9%
요정 1
 
0.5%
Other values (3) 3
 
1.4%

Length

2024-04-18T06:01:07.559128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 121
55.0%
na 28
 
12.7%
카바레 21
 
9.5%
스텐드바 17
 
7.7%
비어(바)살롱 14
 
6.4%
고고(디스코)클럽 5
 
2.3%
관광호텔나이트(디스코 4
 
1.8%
간이주점 4
 
1.8%
관광호텔나이트(카바레 2
 
0.9%
요정 1
 
0.5%
Other values (3) 3
 
1.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)6.9%
Missing75
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean1.5655172
Minimum0
Maximum20
Zeros96
Zeros (%)43.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:07.640225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8.4
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.4777343
Coefficient of variation (CV)2.2214602
Kurtosis15.334575
Mean1.5655172
Median Absolute Deviation (MAD)0
Skewness3.6269306
Sum227
Variance12.094636
MonotonicityNot monotonic
2024-04-18T06:01:07.723873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 96
43.6%
2 12
 
5.5%
4 8
 
3.6%
3 8
 
3.6%
1 7
 
3.2%
5 5
 
2.3%
10 4
 
1.8%
20 3
 
1.4%
6 1
 
0.5%
9 1
 
0.5%
(Missing) 75
34.1%
ValueCountFrequency (%)
0 96
43.6%
1 7
 
3.2%
2 12
 
5.5%
3 8
 
3.6%
4 8
 
3.6%
5 5
 
2.3%
6 1
 
0.5%
9 1
 
0.5%
10 4
 
1.8%
20 3
 
1.4%
ValueCountFrequency (%)
20 3
 
1.4%
10 4
 
1.8%
9 1
 
0.5%
6 1
 
0.5%
5 5
 
2.3%
4 8
 
3.6%
3 8
 
3.6%
2 12
 
5.5%
1 7
 
3.2%
0 96
43.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)10.6%
Missing78
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean2.0985915
Minimum0
Maximum15
Zeros92
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:07.807176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6733849
Coefficient of variation (CV)1.7504049
Kurtosis1.8740912
Mean2.0985915
Median Absolute Deviation (MAD)0
Skewness1.734985
Sum298
Variance13.493757
MonotonicityNot monotonic
2024-04-18T06:01:07.888938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 92
41.8%
2 8
 
3.6%
10 7
 
3.2%
3 7
 
3.2%
1 5
 
2.3%
5 3
 
1.4%
9 3
 
1.4%
7 3
 
1.4%
8 3
 
1.4%
4 3
 
1.4%
Other values (5) 8
 
3.6%
(Missing) 78
35.5%
ValueCountFrequency (%)
0 92
41.8%
1 5
 
2.3%
2 8
 
3.6%
3 7
 
3.2%
4 3
 
1.4%
5 3
 
1.4%
6 2
 
0.9%
7 3
 
1.4%
8 3
 
1.4%
9 3
 
1.4%
ValueCountFrequency (%)
15 1
 
0.5%
14 1
 
0.5%
12 2
 
0.9%
11 2
 
0.9%
10 7
3.2%
9 3
1.4%
8 3
1.4%
7 3
1.4%
6 2
 
0.9%
5 3
1.4%

영업장주변구분명
Categorical

Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
유흥업소밀집지역
96 
<NA>
77 
기타
40 
학교정화(상대)
 
3
주택가주변
 
2

Length

Max length8
Median length7
Mean length5.4727273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유흥업소밀집지역 96
43.6%
<NA> 77
35.0%
기타 40
18.2%
학교정화(상대) 3
 
1.4%
주택가주변 2
 
0.9%
결혼예식장주변 2
 
0.9%

Length

2024-04-18T06:01:07.987418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.088732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥업소밀집지역 96
43.6%
na 77
35.0%
기타 40
18.2%
학교정화(상대 3
 
1.4%
주택가주변 2
 
0.9%
결혼예식장주변 2
 
0.9%

등급구분명
Categorical

Distinct8
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
95 
기타
56 
지도
32 
갑
17 
을
14 
Other values (3)
 
6

Length

Max length4
Median length2
Mean length2.7227273
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 95
43.2%
기타 56
25.5%
지도 32
 
14.5%
갑 17
 
7.7%
을 14
 
6.4%
관리 3
 
1.4%
자율 2
 
0.9%
우수 1
 
0.5%

Length

2024-04-18T06:01:08.184901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.301250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
43.2%
기타 56
25.5%
지도 32
 
14.5%
갑 17
 
7.7%
을 14
 
6.4%
관리 3
 
1.4%
자율 2
 
0.9%
우수 1
 
0.5%

급수시설구분명
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
상수도전용
143 
<NA>
75 
상수도(음용)지하수(주방용)겸용
 
1
전용상수도(특정시설의 자가용 수도)
 
1

Length

Max length19
Median length5
Mean length4.7772727
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 143
65.0%
<NA> 75
34.1%
상수도(음용)지하수(주방용)겸용 1
 
0.5%
전용상수도(특정시설의 자가용 수도) 1
 
0.5%

Length

2024-04-18T06:01:08.399712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.480772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 143
64.4%
na 75
33.8%
상수도(음용)지하수(주방용)겸용 1
 
0.5%
전용상수도(특정시설의 1
 
0.5%
자가용 1
 
0.5%
수도 1
 
0.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:08.569328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.645824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:08.731319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.807587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:08.886844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:08.975965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:09.054840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:09.136086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:09.222750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:09.302007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:09.380582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:09.456918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
216 
0
 
4

Length

Max length4
Median length4
Mean length3.9454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
98.2%
0 4
 
1.8%

Length

2024-04-18T06:01:09.536623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:09.612191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
98.2%
0 4
 
1.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.0%
Missing28
Missing (%)12.7%
Memory size572.0 B
False
177 
True
 
15
(Missing)
28 
ValueCountFrequency (%)
False 177
80.5%
True 15
 
6.8%
(Missing) 28
 
12.7%
2024-04-18T06:01:09.678765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct179
Distinct (%)93.2%
Missing28
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean271.06177
Minimum21.08
Maximum1210.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-18T06:01:09.760610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.08
5-th percentile63.216
Q197.5175
median183.67
Q3336.6525
95-th percentile742.144
Maximum1210.05
Range1188.97
Interquartile range (IQR)239.135

Descriptive statistics

Standard deviation242.86986
Coefficient of variation (CV)0.89599453
Kurtosis3.5472494
Mean271.06177
Median Absolute Deviation (MAD)96.07
Skewness1.8570186
Sum52043.86
Variance58985.77
MonotonicityNot monotonic
2024-04-18T06:01:10.277777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
520.06 4
 
1.8%
609.73 3
 
1.4%
322.13 2
 
0.9%
360.82 2
 
0.9%
115.86 2
 
0.9%
94.5 2
 
0.9%
186.0 2
 
0.9%
300.72 2
 
0.9%
226.81 2
 
0.9%
97.0 2
 
0.9%
Other values (169) 169
76.8%
(Missing) 28
 
12.7%
ValueCountFrequency (%)
21.08 1
0.5%
26.36 1
0.5%
27.12 1
0.5%
30.8 1
0.5%
40.19 1
0.5%
43.08 1
0.5%
43.6 1
0.5%
52.2 1
0.5%
55.86 1
0.5%
62.16 1
0.5%
ValueCountFrequency (%)
1210.05 1
0.5%
1175.63 1
0.5%
1172.39 1
0.5%
1124.35 1
0.5%
1037.55 1
0.5%
1014.68 1
0.5%
980.0 1
0.5%
870.89 1
0.5%
839.46 1
0.5%
790.5 1
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

전통업소주된음식
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
219 
0
 
1

Length

Max length4
Median length4
Mean length3.9863636
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
99.5%
0 1
 
0.5%

Length

2024-04-18T06:01:10.377417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:01:10.453214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
99.5%
0 1
 
0.5%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-102-1969-0846919691008<NA>3폐업2폐업20100617<NA><NA><NA>0222178383279.36130842서울특별시 동대문구 장안동 373-1번지<NA><NA>구찌 구찌2009-11-27 14:36:05I2018-08-31 23:59:59.0룸살롱206090.638551451942.985372룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N279.36<NA><NA><NA>
130500003050000-102-1969-0847019690502<NA>3폐업2폐업20211201<NA><NA><NA>02 9279692226.81130810서울특별시 동대문구 신설동 76-25 2층서울특별시 동대문구 한빛로 6-1, 2층 (신설동)2580갤럭시2021-12-01 13:44:04U2021-12-03 02:40:00.0룸살롱202090.987354452678.65109룸살롱00<NA><NA><NA>00000<NA>00N226.81<NA><NA><NA>
230500003050000-102-1971-0840819710113<NA>3폐업2폐업19930906<NA><NA><NA>0209621739790.50130010서울특별시 동대문구 청량리동 176-18번지<NA><NA>태평양2002-01-16 00:00:00I2018-08-31 23:59:59.0카바레<NA><NA>카바레1010유흥업소밀집지역을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N790.5<NA><NA><NA>
330500003050000-102-1971-0842719710223<NA>3폐업2폐업20151106<NA><NA><NA>02 966082197.00130876서울특별시 동대문구 휘경동 320-2번지서울특별시 동대문구 회기로 189 (휘경동)2445텐프로2011-10-31 16:00:17I2018-08-31 23:59:59.0룸살롱204948.788846454203.717218룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N97.0<NA><NA><NA>
430500003050000-102-1971-0844319710819<NA>3폐업2폐업20220404<NA><NA><NA>022217766184.87130854서울특별시 동대문구 전농동 295-7 지하1층서울특별시 동대문구 사가정로 111, 지하1층 (전농동)2547에스2022-04-04 17:23:37U2021-12-04 00:07:00.0스텐드바204957.73396452803.961455<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
530500003050000-102-1971-084621971-02-12<NA>1영업/정상1영업<NA><NA><NA><NA>0222265470121.38130-854서울특별시 동대문구 전농동 295-307서울특별시 동대문구 전농로16길 12 (전농동)2506명품2023-07-03 14:02:47U2022-12-07 00:05:00.0비어(바)살롱205044.405819452884.212184<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
630500003050000-102-1971-0847119710827<NA>3폐업2폐업20050614<NA><NA><NA>0222448281133.39130842서울특별시 동대문구 장안동 372-12번지<NA><NA>파라오2003-05-06 00:00:00I2018-08-31 23:59:59.0룸살롱206121.805291452003.863719룸살롱00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N133.39<NA><NA><NA>
730500003050000-102-1973-0842819730411<NA>1영업/정상1영업<NA><NA><NA><NA>02 962844185.41130817서울특별시 동대문구 용두동 36-1서울특별시 동대문구 천호대로 128, 지하1층 (용두동)2590아마죤2021-05-14 17:37:03U2021-05-16 02:40:00.0스텐드바203257.607703452402.428558스텐드바22기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y85.41<NA><NA><NA>
830500003050000-102-1973-0846819731229<NA>3폐업2폐업20130717<NA><NA><NA><NA>94.92130876서울특별시 동대문구 휘경동 321-26번지 (지상2층) (이문로 38)<NA><NA>코리아2009-07-06 11:57:41I2018-08-31 23:59:59.0룸살롱204935.973734454273.621686룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N94.92<NA><NA><NA>
930500003050000-102-1973-0851019731117<NA>3폐업2폐업19911220<NA><NA><NA>020922668675.84130810서울특별시 동대문구 신설동 76-28번지<NA><NA>은호일식2001-09-29 00:00:00I2018-08-31 23:59:59.0요정<NA><NA>요정45기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.84<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
21030500003050000-102-2017-0000220170831<NA>1영업/정상1영업<NA><NA><NA><NA><NA>398.00<NA><NA>서울특별시 동대문구 장한로21길 8, 지하1층 (장안동)2624피아노2021-03-16 12:12:23U2021-03-18 02:40:00.0룸살롱206091.537163451990.224278룸살롱12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y398.0<NA><NA><NA>
21130500003050000-102-2018-0000120180524<NA>3폐업2폐업20230119<NA><NA><NA><NA>206.15130840서울특별시 동대문구 장안동 364-2서울특별시 동대문구 장한로 86, 지하1층 (장안동)<NA>슈퍼맨2023-01-19 15:37:48U2022-11-30 22:01:00.0노래클럽206076.898359451784.7336<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21230500003050000-102-2018-0000220180713<NA>3폐업2폐업20190225<NA><NA><NA><NA>473.00130851서울특별시 동대문구 전농동 622-1번지서울특별시 동대문구 답십리로 9, 2층 (전농동)2559시대스탠드빠2019-02-25 10:56:18U2019-02-27 02:40:00.0스텐드바203757.008715452923.162316스텐드바<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y473.0<NA><NA><NA>
21330500003050000-102-2018-0000320181105<NA>1영업/정상1영업<NA><NA><NA><NA><NA>273.78130840서울특별시 동대문구 장안동 366-2서울특별시 동대문구 장한로24길 8, 지상2층 (장안동)2639하트2022-10-27 17:32:02U2021-10-30 22:09:00.0간이주점206231.420255452041.476809<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21430500003050000-102-2019-0000120190208<NA>3폐업2폐업20200515<NA><NA><NA><NA>1,172.39130846서울특별시 동대문구 장안동 465-2번지서울특별시 동대문구 장한로2길 36, 지상2~3층 (장안동)2645오프(off)2020-05-15 13:54:51U2020-05-17 02:40:00.0고고(디스코)클럽205851.797111451057.528462고고(디스코)클럽<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y1172.39<NA><NA><NA>
21530500003050000-102-2019-0000220190225<NA>3폐업2폐업20210426<NA><NA><NA>02 9664578124.12130851서울특별시 동대문구 전농동 622-1서울특별시 동대문구 답십리로 9, 지층 (전농동)2559시대스탠드바 70802021-04-26 15:26:10U2021-04-28 02:40:00.0스텐드바203757.008715452923.162316스텐드바<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y124.12<NA><NA><NA>
21630500003050000-102-2019-0000320190902<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.72130842서울특별시 동대문구 장안동 372-4서울특별시 동대문구 장한로 111, 지상2층 (장안동)2624조아죽네2022-08-04 10:27:45U2021-12-08 00:07:00.0룸살롱206133.550473452026.803255<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21730500003050000-102-2019-0000420191016<NA>3폐업2폐업20200521<NA><NA><NA><NA>1,175.63130840서울특별시 동대문구 장안동 366-7번지 경남관광호텔서울특별시 동대문구 장한로 110, 경남관광호텔 지하1층 (장안동)2639경남호텔나이트클럽2020-05-21 12:54:16U2020-05-23 02:40:00.0고고(디스코)클럽206199.953198451997.93485고고(디스코)클럽<NA><NA>유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y1175.63<NA><NA><NA>
21830500003050000-102-2019-0000520191111<NA>1영업/정상1영업<NA><NA><NA><NA><NA>55.86130842서울특별시 동대문구 장안동 372-3서울특별시 동대문구 장한로 111-1, 지하1층 (장안동)2624썸엔썸노래바2021-10-27 14:30:58U2021-10-29 02:40:00.0룸살롱206144.348296452047.885951룸살롱<NA><NA>유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y55.86<NA><NA><NA>
21930500003050000-102-2020-000012020-07-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>113.48130-842서울특별시 동대문구 장안동 372-14 (지하2층)서울특별시 동대문구 장한로21길 8, 지하2층 (장안동)2624첼로2024-03-11 14:58:13U2023-12-02 23:04:00.0룸살롱206091.537163451990.224278<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>