Overview

Dataset statistics

Number of variables44
Number of observations654
Missing cells7005
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory240.3 KiB
Average record size in memory376.2 B

Variable types

Categorical18
Text7
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18553/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총인원 is highly imbalanced (94.6%)Imbalance
본사종업원수 is highly imbalanced (93.5%)Imbalance
공장사무직종업원수 is highly imbalanced (93.5%)Imbalance
공장판매직종업원수 is highly imbalanced (93.5%)Imbalance
공장생산직종업원수 is highly imbalanced (93.5%)Imbalance
보증액 is highly imbalanced (93.5%)Imbalance
월세액 is highly imbalanced (93.5%)Imbalance
다중이용업소여부 is highly imbalanced (89.5%)Imbalance
인허가취소일자 has 654 (100.0%) missing valuesMissing
폐업일자 has 210 (32.1%) missing valuesMissing
휴업시작일자 has 654 (100.0%) missing valuesMissing
휴업종료일자 has 654 (100.0%) missing valuesMissing
재개업일자 has 654 (100.0%) missing valuesMissing
전화번호 has 94 (14.4%) missing valuesMissing
도로명주소 has 360 (55.0%) missing valuesMissing
도로명우편번호 has 367 (56.1%) missing valuesMissing
좌표정보(X) has 80 (12.2%) missing valuesMissing
좌표정보(Y) has 80 (12.2%) missing valuesMissing
남성종사자수 has 216 (33.0%) missing valuesMissing
여성종사자수 has 218 (33.3%) missing valuesMissing
건물소유구분명 has 654 (100.0%) missing valuesMissing
다중이용업소여부 has 74 (11.3%) missing valuesMissing
시설총규모 has 74 (11.3%) missing valuesMissing
전통업소지정번호 has 654 (100.0%) missing valuesMissing
전통업소주된음식 has 654 (100.0%) missing valuesMissing
홈페이지 has 654 (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 308 (47.1%) zerosZeros
여성종사자수 has 305 (46.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:32:37.982807
Analysis finished2024-05-11 06:32:39.216702
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
3010000
654 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 654
100.0%

Length

2024-05-11T15:32:39.318702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:39.823122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 654
100.0%

관리번호
Text

UNIQUE 

Distinct654
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T15:32:40.113532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters14388
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

Unique654 ?
Unique (%)100.0%

Sample

1st row3010000-102-1904-02602
2nd row3010000-102-1967-02477
3rd row3010000-102-1968-02422
4th row3010000-102-1968-02511
5th row3010000-102-1968-02514
ValueCountFrequency (%)
3010000-102-1904-02602 1
 
0.2%
3010000-102-2002-00020 1
 
0.2%
3010000-102-2002-00001 1
 
0.2%
3010000-102-2002-00009 1
 
0.2%
3010000-102-2002-00002 1
 
0.2%
3010000-102-2002-00003 1
 
0.2%
3010000-102-2002-00004 1
 
0.2%
3010000-102-2002-00005 1
 
0.2%
3010000-102-2002-00006 1
 
0.2%
3010000-102-2002-00007 1
 
0.2%
Other values (644) 644
98.5%
2024-05-11T15:32:40.608881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5779
40.2%
1 2126
 
14.8%
- 1962
 
13.6%
2 1560
 
10.8%
3 915
 
6.4%
9 645
 
4.5%
5 332
 
2.3%
8 291
 
2.0%
6 276
 
1.9%
4 263
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12426
86.4%
Dash Punctuation 1962
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5779
46.5%
1 2126
 
17.1%
2 1560
 
12.6%
3 915
 
7.4%
9 645
 
5.2%
5 332
 
2.7%
8 291
 
2.3%
6 276
 
2.2%
4 263
 
2.1%
7 239
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1962
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5779
40.2%
1 2126
 
14.8%
- 1962
 
13.6%
2 1560
 
10.8%
3 915
 
6.4%
9 645
 
4.5%
5 332
 
2.3%
8 291
 
2.0%
6 276
 
1.9%
4 263
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5779
40.2%
1 2126
 
14.8%
- 1962
 
13.6%
2 1560
 
10.8%
3 915
 
6.4%
9 645
 
4.5%
5 332
 
2.3%
8 291
 
2.0%
6 276
 
1.9%
4 263
 
1.8%
Distinct559
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-02-05 00:00:00
2024-05-11T15:32:40.824491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:32:41.000162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
3
444 
1
210 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 444
67.9%
1 210
32.1%

Length

2024-05-11T15:32:41.205569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:41.345377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 444
67.9%
1 210
32.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
폐업
444 
영업/정상
210 

Length

Max length5
Median length2
Mean length2.9633028
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 444
67.9%
영업/정상 210
32.1%

Length

2024-05-11T15:32:41.508583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:41.650631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 444
67.9%
영업/정상 210
32.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2
444 
1
210 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 444
67.9%
1 210
32.1%

Length

2024-05-11T15:32:41.800999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:41.947986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 444
67.9%
1 210
32.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
폐업
444 
영업
210 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 444
67.9%
영업 210
32.1%

Length

2024-05-11T15:32:42.141862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:42.295193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 444
67.9%
영업 210
32.1%

폐업일자
Date

MISSING 

Distinct366
Distinct (%)82.4%
Missing210
Missing (%)32.1%
Memory size5.2 KiB
Minimum1985-01-16 00:00:00
Maximum2024-03-06 00:00:00
2024-05-11T15:32:42.424740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:32:42.623224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

전화번호
Text

MISSING 

Distinct457
Distinct (%)81.6%
Missing94
Missing (%)14.4%
Memory size5.2 KiB
2024-05-11T15:32:42.933805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6714286
Min length2

Characters and Unicode

Total characters5416
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

Unique420 ?
Unique (%)75.0%

Sample

1st row0201768800
2nd row02 7777759
3rd row0207547030
4th row0202650539
5th row02771 4245
ValueCountFrequency (%)
02 244
30.9%
0201768800 29
 
3.7%
0200000000 19
 
2.4%
7522835 3
 
0.4%
7397733 3
 
0.4%
0222662151 3
 
0.4%
7787001 3
 
0.4%
0207767612 2
 
0.3%
7553144 2
 
0.3%
7530590 2
 
0.3%
Other values (453) 480
60.8%
2024-05-11T15:32:43.357860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1230
22.7%
0 1098
20.3%
7 730
13.5%
5 375
 
6.9%
6 357
 
6.6%
3 346
 
6.4%
8 323
 
6.0%
1 296
 
5.5%
251
 
4.6%
4 212
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5165
95.4%
Space Separator 251
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1230
23.8%
0 1098
21.3%
7 730
14.1%
5 375
 
7.3%
6 357
 
6.9%
3 346
 
6.7%
8 323
 
6.3%
1 296
 
5.7%
4 212
 
4.1%
9 198
 
3.8%
Space Separator
ValueCountFrequency (%)
251
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5416
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1230
22.7%
0 1098
20.3%
7 730
13.5%
5 375
 
6.9%
6 357
 
6.6%
3 346
 
6.4%
8 323
 
6.0%
1 296
 
5.5%
251
 
4.6%
4 212
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1230
22.7%
0 1098
20.3%
7 730
13.5%
5 375
 
6.9%
6 357
 
6.6%
3 346
 
6.4%
8 323
 
6.0%
1 296
 
5.5%
251
 
4.6%
4 212
 
3.9%
Distinct597
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T15:32:43.820750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.3654434
Min length3

Characters and Unicode

Total characters3509
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

Unique555 ?
Unique (%)84.9%

Sample

1st row97.70
2nd row81.80
3rd row23.40
4th row165.24
5th row208.69
ValueCountFrequency (%)
99.00 6
 
0.9%
95.00 6
 
0.9%
00 5
 
0.8%
98.00 4
 
0.6%
39.67 3
 
0.5%
83.00 3
 
0.5%
144.13 2
 
0.3%
134.70 2
 
0.3%
109.12 2
 
0.3%
348.00 2
 
0.3%
Other values (587) 619
94.6%
2024-05-11T15:32:44.442996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 654
18.6%
0 375
10.7%
1 323
9.2%
9 310
8.8%
8 287
8.2%
4 276
7.9%
2 274
7.8%
3 265
7.6%
5 260
 
7.4%
6 251
 
7.2%
Other values (2) 234
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2850
81.2%
Other Punctuation 659
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 375
13.2%
1 323
11.3%
9 310
10.9%
8 287
10.1%
4 276
9.7%
2 274
9.6%
3 265
9.3%
5 260
9.1%
6 251
8.8%
7 229
8.0%
Other Punctuation
ValueCountFrequency (%)
. 654
99.2%
, 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3509
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 654
18.6%
0 375
10.7%
1 323
9.2%
9 310
8.8%
8 287
8.2%
4 276
7.9%
2 274
7.8%
3 265
7.6%
5 260
 
7.4%
6 251
 
7.2%
Other values (2) 234
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 654
18.6%
0 375
10.7%
1 323
9.2%
9 310
8.8%
8 287
8.2%
4 276
7.9%
2 274
7.8%
3 265
7.6%
5 260
 
7.4%
6 251
 
7.2%
Other values (2) 234
 
6.7%
Distinct108
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T15:32:44.741808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0733945
Min length6

Characters and Unicode

Total characters3972
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

Unique31 ?
Unique (%)4.7%

Sample

1st row100868
2nd row100080
3rd row100142
4th row100858
5th row100170
ValueCountFrequency (%)
100080 93
 
14.2%
100180 34
 
5.2%
100411 32
 
4.9%
100013 30
 
4.6%
100861 26
 
4.0%
100869 24
 
3.7%
100864 19
 
2.9%
100300 16
 
2.4%
100800 15
 
2.3%
100858 15
 
2.3%
Other values (98) 350
53.5%
2024-05-11T15:32:45.221100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1777
44.7%
1 966
24.3%
8 437
 
11.0%
6 147
 
3.7%
4 143
 
3.6%
3 143
 
3.6%
2 110
 
2.8%
9 78
 
2.0%
5 76
 
1.9%
- 48
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3924
98.8%
Dash Punctuation 48
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1777
45.3%
1 966
24.6%
8 437
 
11.1%
6 147
 
3.7%
4 143
 
3.6%
3 143
 
3.6%
2 110
 
2.8%
9 78
 
2.0%
5 76
 
1.9%
7 47
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3972
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1777
44.7%
1 966
24.3%
8 437
 
11.0%
6 147
 
3.7%
4 143
 
3.6%
3 143
 
3.6%
2 110
 
2.8%
9 78
 
2.0%
5 76
 
1.9%
- 48
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1777
44.7%
1 966
24.3%
8 437
 
11.0%
6 147
 
3.7%
4 143
 
3.6%
3 143
 
3.6%
2 110
 
2.8%
9 78
 
2.0%
5 76
 
1.9%
- 48
 
1.2%
Distinct593
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T15:32:45.573205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length36
Mean length23.747706
Min length16

Characters and Unicode

Total characters15531
Distinct characters119
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

Unique547 ?
Unique (%)83.6%

Sample

1st row서울특별시 중구 황학동 72-0번지
2nd row서울특별시 중구 북창동 120-3번지
3rd row서울특별시 중구 의주로2가 4-6번지
4th row서울특별시 중구 중림동 123-7번지
5th row서울특별시 중구 무교동 1-0번지
ValueCountFrequency (%)
서울특별시 654
22.2%
중구 654
22.2%
지하1층 100
 
3.4%
북창동 97
 
3.3%
지상2층 49
 
1.7%
광희동1가 38
 
1.3%
2층 36
 
1.2%
황학동 35
 
1.2%
다동 34
 
1.2%
충무로3가 33
 
1.1%
Other values (624) 1211
41.2%
2024-05-11T15:32:46.090235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2870
18.5%
838
 
5.4%
1 797
 
5.1%
669
 
4.3%
662
 
4.3%
656
 
4.2%
654
 
4.2%
654
 
4.2%
654
 
4.2%
654
 
4.2%
Other values (109) 6423
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8747
56.3%
Decimal Number 3008
 
19.4%
Space Separator 2870
 
18.5%
Dash Punctuation 615
 
4.0%
Open Punctuation 128
 
0.8%
Close Punctuation 128
 
0.8%
Other Punctuation 19
 
0.1%
Uppercase Letter 9
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
838
 
9.6%
669
 
7.6%
662
 
7.6%
656
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
526
 
6.0%
411
 
4.7%
Other values (85) 2369
27.1%
Decimal Number
ValueCountFrequency (%)
1 797
26.5%
2 561
18.7%
3 347
11.5%
0 238
 
7.9%
5 219
 
7.3%
4 199
 
6.6%
6 194
 
6.4%
8 168
 
5.6%
9 153
 
5.1%
7 132
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
22.2%
B 1
11.1%
Y 1
11.1%
G 1
11.1%
C 1
11.1%
N 1
11.1%
T 1
11.1%
R 1
11.1%
Space Separator
ValueCountFrequency (%)
2870
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8747
56.3%
Common 6775
43.6%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
838
 
9.6%
669
 
7.6%
662
 
7.6%
656
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
526
 
6.0%
411
 
4.7%
Other values (85) 2369
27.1%
Common
ValueCountFrequency (%)
2870
42.4%
1 797
 
11.8%
- 615
 
9.1%
2 561
 
8.3%
3 347
 
5.1%
0 238
 
3.5%
5 219
 
3.2%
4 199
 
2.9%
6 194
 
2.9%
8 168
 
2.5%
Other values (6) 567
 
8.4%
Latin
ValueCountFrequency (%)
E 2
22.2%
B 1
11.1%
Y 1
11.1%
G 1
11.1%
C 1
11.1%
N 1
11.1%
T 1
11.1%
R 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8747
56.3%
ASCII 6784
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2870
42.3%
1 797
 
11.7%
- 615
 
9.1%
2 561
 
8.3%
3 347
 
5.1%
0 238
 
3.5%
5 219
 
3.2%
4 199
 
2.9%
6 194
 
2.9%
8 168
 
2.5%
Other values (14) 576
 
8.5%
Hangul
ValueCountFrequency (%)
838
 
9.6%
669
 
7.6%
662
 
7.6%
656
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
654
 
7.5%
526
 
6.0%
411
 
4.7%
Other values (85) 2369
27.1%

도로명주소
Text

MISSING 

Distinct286
Distinct (%)97.3%
Missing360
Missing (%)55.0%
Memory size5.2 KiB
2024-05-11T15:32:46.439743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length29.357143
Min length20

Characters and Unicode

Total characters8631
Distinct characters123
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

Unique278 ?
Unique (%)94.6%

Sample

1st row서울특별시 중구 남대문로1길 12 (북창동)
2nd row서울특별시 중구 퇴계로 417 (흥인동)
3rd row서울특별시 중구 퇴계로 213 (충무로4가,외4필지(일흥빌딩 지하1층))
4th row서울특별시 중구 남대문로9길 12 (다동,지하1층)
5th row서울특별시 중구 퇴계로 386-5 (신당동)
ValueCountFrequency (%)
서울특별시 294
 
18.6%
중구 294
 
18.6%
2층 31
 
2.0%
북창동 27
 
1.7%
퇴계로 27
 
1.7%
남대문로1길 26
 
1.6%
지하1층 26
 
1.6%
마른내로 21
 
1.3%
충무로2길 17
 
1.1%
충무로3가 13
 
0.8%
Other values (405) 802
50.8%
2024-05-11T15:32:47.082870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1284
 
14.9%
405
 
4.7%
( 384
 
4.4%
) 384
 
4.4%
1 371
 
4.3%
2 320
 
3.7%
304
 
3.5%
298
 
3.5%
295
 
3.4%
294
 
3.4%
Other values (113) 4292
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4895
56.7%
Decimal Number 1368
 
15.8%
Space Separator 1284
 
14.9%
Open Punctuation 384
 
4.4%
Close Punctuation 384
 
4.4%
Other Punctuation 232
 
2.7%
Dash Punctuation 71
 
0.8%
Uppercase Letter 10
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
405
 
8.3%
304
 
6.2%
298
 
6.1%
295
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
251
 
5.1%
214
 
4.4%
Other values (89) 1952
39.9%
Decimal Number
ValueCountFrequency (%)
1 371
27.1%
2 320
23.4%
3 166
12.1%
4 136
 
9.9%
5 90
 
6.6%
6 89
 
6.5%
7 54
 
3.9%
8 51
 
3.7%
0 46
 
3.4%
9 45
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
20.0%
E 2
20.0%
G 1
10.0%
Y 1
10.0%
R 1
10.0%
T 1
10.0%
N 1
10.0%
C 1
10.0%
Space Separator
ValueCountFrequency (%)
1284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 384
100.0%
Close Punctuation
ValueCountFrequency (%)
) 384
100.0%
Other Punctuation
ValueCountFrequency (%)
, 232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4895
56.7%
Common 3726
43.2%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
405
 
8.3%
304
 
6.2%
298
 
6.1%
295
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
251
 
5.1%
214
 
4.4%
Other values (89) 1952
39.9%
Common
ValueCountFrequency (%)
1284
34.5%
( 384
 
10.3%
) 384
 
10.3%
1 371
 
10.0%
2 320
 
8.6%
, 232
 
6.2%
3 166
 
4.5%
4 136
 
3.7%
5 90
 
2.4%
6 89
 
2.4%
Other values (6) 270
 
7.2%
Latin
ValueCountFrequency (%)
B 2
20.0%
E 2
20.0%
G 1
10.0%
Y 1
10.0%
R 1
10.0%
T 1
10.0%
N 1
10.0%
C 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4895
56.7%
ASCII 3736
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1284
34.4%
( 384
 
10.3%
) 384
 
10.3%
1 371
 
9.9%
2 320
 
8.6%
, 232
 
6.2%
3 166
 
4.4%
4 136
 
3.6%
5 90
 
2.4%
6 89
 
2.4%
Other values (14) 280
 
7.5%
Hangul
ValueCountFrequency (%)
405
 
8.3%
304
 
6.2%
298
 
6.1%
295
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
294
 
6.0%
251
 
5.1%
214
 
4.4%
Other values (89) 1952
39.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)16.0%
Missing367
Missing (%)56.1%
Infinite0
Infinite (%)0.0%
Mean4549.878
Minimum4507
Maximum4635
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:47.273361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4507
5-th percentile4520
Q14527
median4554
Q34561
95-th percentile4577
Maximum4635
Range128
Interquartile range (IQR)34

Descriptive statistics

Standard deviation24.240544
Coefficient of variation (CV)0.0053277348
Kurtosis2.840079
Mean4549.878
Median Absolute Deviation (MAD)8
Skewness1.2289096
Sum1305815
Variance587.60396
MonotonicityNot monotonic
2024-05-11T15:32:47.473570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
4526 38
 
5.8%
4561 32
 
4.9%
4556 22
 
3.4%
4555 18
 
2.8%
4557 13
 
2.0%
4554 13
 
2.0%
4550 13
 
2.0%
4576 12
 
1.8%
4527 9
 
1.4%
4546 8
 
1.2%
Other values (36) 109
 
16.7%
(Missing) 367
56.1%
ValueCountFrequency (%)
4507 4
 
0.6%
4512 3
 
0.5%
4514 5
 
0.8%
4520 4
 
0.6%
4521 4
 
0.6%
4522 6
 
0.9%
4523 6
 
0.9%
4526 38
5.8%
4527 9
 
1.4%
4529 2
 
0.3%
ValueCountFrequency (%)
4635 2
 
0.3%
4634 1
 
0.2%
4631 4
 
0.6%
4627 2
 
0.3%
4624 2
 
0.3%
4611 3
 
0.5%
4577 4
 
0.6%
4576 12
1.8%
4575 2
 
0.3%
4574 1
 
0.2%
Distinct571
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T15:32:47.840913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length4.353211
Min length1

Characters and Unicode

Total characters2847
Distinct characters463
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique508 ?
Unique (%)77.7%

Sample

1st row한신그릴
2nd row폭스
3rd row오비치킨
4th row무지개-룸싸롱
5th row힐탑
ValueCountFrequency (%)
폭스 6
 
0.9%
보물섬 6
 
0.9%
초원의집 4
 
0.6%
빠담빠담 4
 
0.6%
초심 3
 
0.4%
노래밤 3
 
0.4%
노래주점 3
 
0.4%
club 3
 
0.4%
노래클럽 3
 
0.4%
시카고 3
 
0.4%
Other values (590) 663
94.6%
2024-05-11T15:32:48.411241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
129
 
4.5%
128
 
4.5%
82
 
2.9%
56
 
2.0%
56
 
2.0%
47
 
1.7%
47
 
1.7%
43
 
1.5%
40
 
1.4%
34
 
1.2%
Other values (453) 2185
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2560
89.9%
Uppercase Letter 73
 
2.6%
Lowercase Letter 67
 
2.4%
Space Separator 47
 
1.7%
Open Punctuation 26
 
0.9%
Close Punctuation 26
 
0.9%
Decimal Number 24
 
0.8%
Other Punctuation 16
 
0.6%
Dash Punctuation 6
 
0.2%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
129
 
5.0%
128
 
5.0%
82
 
3.2%
56
 
2.2%
56
 
2.2%
47
 
1.8%
43
 
1.7%
40
 
1.6%
34
 
1.3%
34
 
1.3%
Other values (394) 1911
74.6%
Uppercase Letter
ValueCountFrequency (%)
B 9
 
12.3%
L 6
 
8.2%
U 6
 
8.2%
A 5
 
6.8%
S 5
 
6.8%
W 4
 
5.5%
I 4
 
5.5%
O 4
 
5.5%
T 4
 
5.5%
N 3
 
4.1%
Other values (11) 23
31.5%
Lowercase Letter
ValueCountFrequency (%)
i 7
10.4%
e 7
10.4%
o 6
 
9.0%
y 5
 
7.5%
c 5
 
7.5%
l 5
 
7.5%
a 4
 
6.0%
s 4
 
6.0%
n 4
 
6.0%
r 3
 
4.5%
Other values (11) 17
25.4%
Decimal Number
ValueCountFrequency (%)
0 6
25.0%
2 6
25.0%
7 3
12.5%
1 3
12.5%
8 2
 
8.3%
5 2
 
8.3%
4 1
 
4.2%
3 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 14
87.5%
/ 1
 
6.2%
& 1
 
6.2%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2560
89.9%
Common 145
 
5.1%
Latin 142
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
129
 
5.0%
128
 
5.0%
82
 
3.2%
56
 
2.2%
56
 
2.2%
47
 
1.8%
43
 
1.7%
40
 
1.6%
34
 
1.3%
34
 
1.3%
Other values (394) 1911
74.6%
Latin
ValueCountFrequency (%)
B 9
 
6.3%
i 7
 
4.9%
e 7
 
4.9%
L 6
 
4.2%
U 6
 
4.2%
o 6
 
4.2%
A 5
 
3.5%
y 5
 
3.5%
c 5
 
3.5%
S 5
 
3.5%
Other values (34) 81
57.0%
Common
ValueCountFrequency (%)
47
32.4%
( 26
17.9%
) 26
17.9%
. 14
 
9.7%
0 6
 
4.1%
- 6
 
4.1%
2 6
 
4.1%
7 3
 
2.1%
1 3
 
2.1%
8 2
 
1.4%
Other values (5) 6
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2560
89.9%
ASCII 285
 
10.0%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
129
 
5.0%
128
 
5.0%
82
 
3.2%
56
 
2.2%
56
 
2.2%
47
 
1.8%
43
 
1.7%
40
 
1.6%
34
 
1.3%
34
 
1.3%
Other values (394) 1911
74.6%
ASCII
ValueCountFrequency (%)
47
 
16.5%
( 26
 
9.1%
) 26
 
9.1%
. 14
 
4.9%
B 9
 
3.2%
i 7
 
2.5%
e 7
 
2.5%
L 6
 
2.1%
0 6
 
2.1%
U 6
 
2.1%
Other values (47) 131
46.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct525
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum1999-03-08 00:00:00
Maximum2024-05-08 17:09:33
2024-05-11T15:32:48.601875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:32:48.815228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
I
497 
U
157 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 497
76.0%
U 157
 
24.0%

Length

2024-05-11T15:32:49.044824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:49.196654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 497
76.0%
u 157
 
24.0%
Distinct139
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:00:00
2024-05-11T15:32:49.342518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:32:49.500163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct12
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
룸살롱
377 
기타
63 
간이주점
45 
비어(바)살롱
 
37
극장식당
 
34
Other values (7)
98 

Length

Max length12
Median length3
Mean length3.5902141
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row극장식당
2nd row룸살롱
3rd row간이주점
4th row룸살롱
5th row룸살롱

Common Values

ValueCountFrequency (%)
룸살롱 377
57.6%
기타 63
 
9.6%
간이주점 45
 
6.9%
비어(바)살롱 37
 
5.7%
극장식당 34
 
5.2%
카바레 34
 
5.2%
스텐드바 21
 
3.2%
관광호텔나이트(디스코) 14
 
2.1%
노래클럽 12
 
1.8%
고고(디스코)클럽 10
 
1.5%
Other values (2) 7
 
1.1%

Length

2024-05-11T15:32:49.667699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 377
57.6%
기타 63
 
9.6%
간이주점 45
 
6.9%
비어(바)살롱 37
 
5.7%
극장식당 34
 
5.2%
카바레 34
 
5.2%
스텐드바 21
 
3.2%
관광호텔나이트(디스코 14
 
2.1%
노래클럽 12
 
1.8%
고고(디스코)클럽 10
 
1.5%
Other values (2) 7
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct425
Distinct (%)74.0%
Missing80
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean199054.17
Minimum196606.64
Maximum201978.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:49.829976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196606.64
5-th percentile197663.37
Q1197978.77
median199034.53
Q3199739.53
95-th percentile201567.12
Maximum201978.07
Range5371.4375
Interquartile range (IQR)1760.7641

Descriptive statistics

Standard deviation1175.8254
Coefficient of variation (CV)0.0059070622
Kurtosis-0.40213414
Mean199054.17
Median Absolute Deviation (MAD)1032.955
Skewness0.63493365
Sum1.142571 × 108
Variance1382565.3
MonotonicityNot monotonic
2024-05-11T15:32:50.033841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199521.200809167 6
 
0.9%
198264.78394422 5
 
0.8%
201607.807763324 4
 
0.6%
198911.806393959 4
 
0.6%
199550.506270874 4
 
0.6%
197975.542794467 4
 
0.6%
197967.218104208 4
 
0.6%
197958.262545842 4
 
0.6%
197959.810582847 3
 
0.5%
198178.211981516 3
 
0.5%
Other values (415) 533
81.5%
(Missing) 80
 
12.2%
ValueCountFrequency (%)
196606.636582259 1
0.2%
196662.44522421 1
0.2%
196888.387871053 1
0.2%
196896.258515802 1
0.2%
197105.004965738 2
0.3%
197183.087076662 1
0.2%
197185.873726348 1
0.2%
197192.687794504 1
0.2%
197192.810434102 1
0.2%
197194.856744366 1
0.2%
ValueCountFrequency (%)
201978.074072669 1
0.2%
201947.084297972 2
0.3%
201822.293139332 1
0.2%
201776.488974424 1
0.2%
201775.039015385 1
0.2%
201767.085427754 1
0.2%
201762.765771009 1
0.2%
201754.443294141 1
0.2%
201742.687156116 1
0.2%
201682.714803667 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct425
Distinct (%)74.0%
Missing80
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean451266.2
Minimum449793.6
Maximum451945.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:50.202265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449793.6
5-th percentile450665.11
Q1451087.64
median451228.11
Q3451511.05
95-th percentile451740.89
Maximum451945.76
Range2152.1505
Interquartile range (IQR)423.41692

Descriptive statistics

Standard deviation328.31632
Coefficient of variation (CV)0.00072754466
Kurtosis1.8298812
Mean451266.2
Median Absolute Deviation (MAD)199.23973
Skewness-0.83862883
Sum2.590268 × 108
Variance107791.61
MonotonicityNot monotonic
2024-05-11T15:32:50.775223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451751.424132583 6
 
0.9%
451746.92183856 5
 
0.8%
451587.013088711 4
 
0.6%
451032.316115194 4
 
0.6%
451392.219693582 4
 
0.6%
451036.126342809 4
 
0.6%
451154.283066178 4
 
0.6%
451056.146350148 4
 
0.6%
451024.329639965 3
 
0.5%
451722.239559759 3
 
0.5%
Other values (415) 533
81.5%
(Missing) 80
 
12.2%
ValueCountFrequency (%)
449793.604957251 1
0.2%
449877.44410054 2
0.3%
449946.116521469 1
0.2%
449997.636812952 1
0.2%
450226.893783082 1
0.2%
450237.029417625 1
0.2%
450337.580626313 1
0.2%
450497.460903907 1
0.2%
450568.540959567 1
0.2%
450572.520549429 1
0.2%
ValueCountFrequency (%)
451945.75542127 1
0.2%
451871.658487352 1
0.2%
451862.646668658 1
0.2%
451844.350705494 1
0.2%
451827.973207366 1
0.2%
451824.947293681 1
0.2%
451805.656731189 1
0.2%
451801.208127592 1
0.2%
451800.856699532 1
0.2%
451792.729933373 1
0.2%

위생업태명
Categorical

Distinct13
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
룸살롱
333 
<NA>
74 
기타
46 
간이주점
41 
비어(바)살롱
35 
Other values (8)
125 

Length

Max length12
Median length3
Mean length3.7003058
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row극장식당
2nd row룸살롱
3rd row간이주점
4th row룸살롱
5th row룸살롱

Common Values

ValueCountFrequency (%)
룸살롱 333
50.9%
<NA> 74
 
11.3%
기타 46
 
7.0%
간이주점 41
 
6.3%
비어(바)살롱 35
 
5.4%
카바레 34
 
5.2%
극장식당 33
 
5.0%
스텐드바 19
 
2.9%
관광호텔나이트(디스코) 14
 
2.1%
고고(디스코)클럽 10
 
1.5%
Other values (3) 15
 
2.3%

Length

2024-05-11T15:32:50.947423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 333
50.9%
na 74
 
11.3%
기타 46
 
7.0%
간이주점 41
 
6.3%
비어(바)살롱 35
 
5.4%
카바레 34
 
5.2%
극장식당 33
 
5.0%
스텐드바 19
 
2.9%
관광호텔나이트(디스코 14
 
2.1%
고고(디스코)클럽 10
 
1.5%
Other values (3) 15
 
2.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)3.2%
Missing216
Missing (%)33.0%
Infinite0
Infinite (%)0.0%
Mean1.2648402
Minimum0
Maximum25
Zeros308
Zeros (%)47.1%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:51.142093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum25
Range25
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.85391
Coefficient of variation (CV)2.2563404
Kurtosis18.758187
Mean1.2648402
Median Absolute Deviation (MAD)0
Skewness3.6746305
Sum554
Variance8.1448021
MonotonicityNot monotonic
2024-05-11T15:32:51.456512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 308
47.1%
1 33
 
5.0%
2 20
 
3.1%
4 18
 
2.8%
5 18
 
2.8%
3 11
 
1.7%
8 8
 
1.2%
7 6
 
0.9%
6 6
 
0.9%
10 3
 
0.5%
Other values (4) 7
 
1.1%
(Missing) 216
33.0%
ValueCountFrequency (%)
0 308
47.1%
1 33
 
5.0%
2 20
 
3.1%
3 11
 
1.7%
4 18
 
2.8%
5 18
 
2.8%
6 6
 
0.9%
7 6
 
0.9%
8 8
 
1.2%
10 3
 
0.5%
ValueCountFrequency (%)
25 1
 
0.2%
20 1
 
0.2%
15 3
 
0.5%
12 2
 
0.3%
10 3
 
0.5%
8 8
1.2%
7 6
 
0.9%
6 6
 
0.9%
5 18
2.8%
4 18
2.8%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)4.4%
Missing218
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean1.5665138
Minimum0
Maximum20
Zeros305
Zeros (%)46.6%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:51.663702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation3.2331157
Coefficient of variation (CV)2.0638923
Kurtosis7.8408264
Mean1.5665138
Median Absolute Deviation (MAD)0
Skewness2.6593142
Sum683
Variance10.453037
MonotonicityNot monotonic
2024-05-11T15:32:51.837523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 305
46.6%
3 23
 
3.5%
2 23
 
3.5%
1 15
 
2.3%
4 11
 
1.7%
5 10
 
1.5%
6 10
 
1.5%
8 9
 
1.4%
7 7
 
1.1%
9 6
 
0.9%
Other values (9) 17
 
2.6%
(Missing) 218
33.3%
ValueCountFrequency (%)
0 305
46.6%
1 15
 
2.3%
2 23
 
3.5%
3 23
 
3.5%
4 11
 
1.7%
5 10
 
1.5%
6 10
 
1.5%
7 7
 
1.1%
8 9
 
1.4%
9 6
 
0.9%
ValueCountFrequency (%)
20 1
 
0.2%
19 1
 
0.2%
17 1
 
0.2%
15 2
 
0.3%
14 1
 
0.2%
13 3
0.5%
12 2
 
0.3%
11 1
 
0.2%
10 5
0.8%
9 6
0.9%
Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
271 
기타
201 
유흥업소밀집지역
168 
아파트지역
 
6
주택가주변
 
4
Other values (2)
 
4

Length

Max length8
Median length7
Mean length4.4510703
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 271
41.4%
기타 201
30.7%
유흥업소밀집지역 168
25.7%
아파트지역 6
 
0.9%
주택가주변 4
 
0.6%
학교정화(상대) 3
 
0.5%
결혼예식장주변 1
 
0.2%

Length

2024-05-11T15:32:52.075012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:52.299076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 271
41.4%
기타 201
30.7%
유흥업소밀집지역 168
25.7%
아파트지역 6
 
0.9%
주택가주변 4
 
0.6%
학교정화(상대 3
 
0.5%
결혼예식장주변 1
 
0.2%

등급구분명
Categorical

Distinct8
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
303 
기타
161 
65 
지도
63 
 
28
Other values (3)
34 

Length

Max length4
Median length2
Mean length2.7844037
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 303
46.3%
기타 161
24.6%
65
 
9.9%
지도 63
 
9.6%
28
 
4.3%
우수 22
 
3.4%
자율 11
 
1.7%
관리 1
 
0.2%

Length

2024-05-11T15:32:52.510599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:52.694781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 303
46.3%
기타 161
24.6%
65
 
9.9%
지도 63
 
9.6%
28
 
4.3%
우수 22
 
3.4%
자율 11
 
1.7%
관리 1
 
0.2%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
상수도전용
429 
<NA>
221 
상수도(음용)지하수(주방용)겸용
 
4

Length

Max length17
Median length5
Mean length4.735474
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 429
65.6%
<NA> 221
33.8%
상수도(음용)지하수(주방용)겸용 4
 
0.6%

Length

2024-05-11T15:32:52.921251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:53.086736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 429
65.6%
na 221
33.8%
상수도(음용)지하수(주방용)겸용 4
 
0.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
650 
0
 
4

Length

Max length4
Median length4
Mean length3.9816514
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> 650
99.4%
0 4
 
0.6%

Length

2024-05-11T15:32:53.289293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:53.484404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 650
99.4%
0 4
 
0.6%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:53.685565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:53.900397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:54.105623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:54.288238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:54.494689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:54.673015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:54.857849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:55.021532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:55.177241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:55.358837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
649 
0
 
5

Length

Max length4
Median length4
Mean length3.9770642
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> 649
99.2%
0 5
 
0.8%

Length

2024-05-11T15:32:55.556329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:32:55.747336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 649
99.2%
0 5
 
0.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing74
Missing (%)11.3%
Memory size1.4 KiB
False
572 
True
 
8
(Missing)
74 
ValueCountFrequency (%)
False 572
87.5%
True 8
 
1.2%
(Missing) 74
 
11.3%
2024-05-11T15:32:55.936138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct536
Distinct (%)92.4%
Missing74
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean147.82728
Minimum0
Maximum1589.31
Zeros5
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:32:56.142980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile29.146
Q165.1925
median94.01
Q3144.915
95-th percentile449.082
Maximum1589.31
Range1589.31
Interquartile range (IQR)79.7225

Descriptive statistics

Standard deviation169.8077
Coefficient of variation (CV)1.1486899
Kurtosis18.388584
Mean147.82728
Median Absolute Deviation (MAD)34.395
Skewness3.6644102
Sum85739.82
Variance28834.654
MonotonicityNot monotonic
2024-05-11T15:32:56.422155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5
 
0.8%
95.0 5
 
0.8%
98.0 4
 
0.6%
99.0 3
 
0.5%
83.0 3
 
0.5%
42.2 2
 
0.3%
134.7 2
 
0.3%
90.69 2
 
0.3%
14.55 2
 
0.3%
98.66 2
 
0.3%
Other values (526) 550
84.1%
(Missing) 74
 
11.3%
ValueCountFrequency (%)
0.0 5
0.8%
3.4 1
 
0.2%
6.8 1
 
0.2%
10.0 1
 
0.2%
10.97 1
 
0.2%
13.62 1
 
0.2%
14.55 2
 
0.3%
16.71 1
 
0.2%
16.93 1
 
0.2%
17.18 1
 
0.2%
ValueCountFrequency (%)
1589.31 1
0.2%
1239.68 1
0.2%
1090.32 1
0.2%
1060.68 1
0.2%
1054.54 1
0.2%
953.8 1
0.2%
950.6 1
0.2%
924.02 1
0.2%
862.37 1
0.2%
734.27 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing654
Missing (%)100.0%
Memory size5.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-102-1904-0260219040808<NA>3폐업2폐업19930902<NA><NA><NA>020176880097.70100868서울특별시 중구 황학동 72-0번지<NA><NA>한신그릴2001-10-08 00:00:00I2018-08-31 23:59:59.0극장식당<NA><NA>극장식당03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.7<NA><NA><NA>
130100003010000-102-1967-0247719671010<NA>1영업/정상1영업<NA><NA><NA><NA>02 777775981.80100080서울특별시 중구 북창동 120-3번지서울특별시 중구 남대문로1길 12 (북창동)4526폭스2015-01-08 10:11:39I2018-08-31 23:59:59.0룸살롱197956.487296451034.327544룸살롱<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N81.8<NA><NA><NA>
230100003010000-102-1968-0242219680725<NA>3폐업2폐업19910605<NA><NA><NA>020754703023.40100142서울특별시 중구 의주로2가 4-6번지<NA><NA>오비치킨2001-10-08 00:00:00I2018-08-31 23:59:59.0간이주점<NA><NA>간이주점01기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.4<NA><NA><NA>
330100003010000-102-1968-0251119681109<NA>3폐업2폐업19911223<NA><NA><NA>0202650539165.24100858서울특별시 중구 중림동 123-7번지<NA><NA>무지개-룸싸롱2001-10-08 00:00:00I2018-08-31 23:59:59.0룸살롱<NA><NA>룸살롱22유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N165.24<NA><NA><NA>
430100003010000-102-1968-0251419681231<NA>3폐업2폐업20070523<NA><NA><NA>02771 4245208.69100170서울특별시 중구 무교동 1-0번지<NA><NA>힐탑2006-09-19 00:00:00I2018-08-31 23:59:59.0룸살롱198126.501925451827.973207룸살롱00유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N208.69<NA><NA><NA>
530100003010000-102-1970-0261119700131<NA>3폐업2폐업19920509<NA><NA><NA>0207767411.00100142서울특별시 중구 의주로2가 82-0번지<NA><NA>회림2001-10-08 00:00:00I2018-08-31 23:59:59.0극장식당<NA><NA>극장식당710기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630100003010000-102-1971-0255619710615<NA>3폐업2폐업19910202<NA><NA><NA>0209234986277.83100871서울특별시 중구 황학동 2478-0번지<NA><NA>뉴관광-바2001-10-08 00:00:00I2018-08-31 23:59:59.0비어(바)살롱201947.084298451473.964193비어(바)살롱817유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N277.83<NA><NA><NA>
730100003010000-102-1971-0261019710415<NA>3폐업2폐업19901012<NA><NA><NA>0200000000495.81100858서울특별시 중구 중림동 83-5번지<NA><NA>영스타2001-10-08 00:00:00I2018-08-31 23:59:59.0극장식당<NA><NA>극장식당813유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N495.81<NA><NA><NA>
830100003010000-102-1971-0262919710415<NA>3폐업2폐업19901012<NA><NA><NA>0200000000495.81100858서울특별시 중구 중림동 83-5번지<NA><NA>영스타2001-10-08 00:00:00I2018-08-31 23:59:59.0관광호텔나이트(디스코)<NA><NA>관광호텔나이트(디스코)813유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N495.81<NA><NA><NA>
930100003010000-102-1972-0249219721110<NA>3폐업2폐업20060428<NA><NA><NA>0202730167241.68100411서울특별시 중구 광희동1가 143-1번지<NA><NA>보물섬2004-05-17 00:00:00I2018-08-31 23:59:59.0룸살롱<NA><NA>룸살롱1020유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N241.68<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
64430100003010000-102-2019-0000120191209<NA>3폐업2폐업20210602<NA><NA><NA><NA>129.32100864서울특별시 중구 태평로2가 69-3 청남빌딩서울특별시 중구 세종대로 76, 청남빌딩 4층 (태평로2가)4526세븐2021-06-02 18:04:03U2021-06-04 02:40:00.0룸살롱197894.932406451176.283415룸살롱3<NA>유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y129.32<NA><NA><NA>
64530100003010000-102-2020-0000120200203<NA>3폐업2폐업20200914<NA><NA><NA><NA>81.08100230서울특별시 중구 수표동 35-16서울특별시 중구 수표로 68, 2층 (수표동)4543뉴코리아2020-09-14 13:24:07U2020-09-16 02:40:00.0기타199030.806204451659.586959기타<NA><NA>기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N81.08<NA><NA><NA>
64630100003010000-102-2020-0000220200709<NA>1영업/정상1영업<NA><NA><NA><NA><NA>83.70100869서울특별시 중구 황학동 371-38 신라여관서울특별시 중구 퇴계로83길 12-16, 2층 (황학동)4576구찌2020-07-09 15:57:45I2020-07-11 00:23:16.0룸살롱201596.080774451564.777815룸살롱<NA><NA>기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N83.7<NA><NA><NA>
64730100003010000-102-2021-0000120210126<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.95100013서울특별시 중구 충무로3가 28-2서울특별시 중구 수표로6길 37-1, 2층 (충무로3가)4555찐노래2021-01-25 17:58:14I2021-01-27 00:23:03.0노래클럽199268.778511451180.536452노래클럽1<NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y85.95<NA><NA><NA>
64830100003010000-102-2022-0000120220823<NA>1영업/정상1영업<NA><NA><NA><NA><NA>389.88100080서울특별시 중구 북창동 122서울특별시 중구 남대문로1길 8-1, 지하1-2층 (북창동)4526마이코 이자까야2022-08-23 14:55:45I2021-12-07 22:05:00.0간이주점197959.810583451024.32964<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64930100003010000-102-2022-000022022-09-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>391.17100-863서울특별시 중구 충무로4가 125-3 일흥빌딩서울특별시 중구 퇴계로 213, 일흥빌딩 지하1층 (충무로4가)4557포인트2023-07-24 16:06:31U2022-12-06 22:06:00.0룸살롱199532.084459451067.19473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65030100003010000-102-2022-0000320221006<NA>1영업/정상1영업<NA><NA><NA><NA><NA>98.35100196서울특별시 중구 을지로6가 23서울특별시 중구 을지로 254, 지하1층 B102호 (을지로6가)4561로얄노래타운2022-11-01 12:48:42U2021-11-01 00:03:00.0노래클럽200488.771189451524.878308<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65130100003010000-102-2022-0000520221228<NA>1영업/정상1영업<NA><NA><NA><NA><NA>193.75100411서울특별시 중구 광희동1가 145-2서울특별시 중구 을지로44길 18-4, 동대문디플레이스 지하2층 (광희동1가)4561VIP2022-12-28 11:04:00I2021-11-01 21:00:00.0노래클럽200488.594169451461.820381<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65230100003010000-102-2023-000022023-12-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>160.38100-032서울특별시 중구 저동2가 7-5 서광빌딩서울특별시 중구 수표로 42-13, 서광빌딩 1층 (저동2가)4550쇼부2024-01-24 15:52:34U2023-11-30 22:06:00.0기타199089.190194451457.433935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65330100003010000-102-2024-000012024-02-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>414.54100-861서울특별시 중구 충무로2가 52-1 해보라인쇄서울특별시 중구 퇴계로 161, 해보라인쇄 지하1~지상2층 (충무로2가)4553슈퍼소울서울2024-02-05 16:46:03I2023-12-02 00:07:00.0기타199045.158247451026.931527<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>