Overview

Dataset statistics

Number of variables47
Number of observations438
Missing cells4006
Missing cells (%)19.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory172.9 KiB
Average record size in memory404.3 B

Variable types

Categorical22
Text6
DateTime4
Unsupported6
Numeric7
Boolean2

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,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-17954/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (93.8%)Imbalance
위생업태명 is highly imbalanced (84.5%)Imbalance
사용끝지상층 is highly imbalanced (65.9%)Imbalance
사용끝지하층 is highly imbalanced (83.4%)Imbalance
조건부허가신고사유 is highly imbalanced (94.1%)Imbalance
건물소유구분명 is highly imbalanced (75.6%)Imbalance
여성종사자수 is highly imbalanced (77.1%)Imbalance
남성종사자수 is highly imbalanced (75.9%)Imbalance
회수건조수 is highly imbalanced (67.5%)Imbalance
인허가취소일자 has 438 (100.0%) missing valuesMissing
폐업일자 has 89 (20.3%) missing valuesMissing
휴업시작일자 has 438 (100.0%) missing valuesMissing
휴업종료일자 has 438 (100.0%) missing valuesMissing
재개업일자 has 438 (100.0%) missing valuesMissing
전화번호 has 22 (5.0%) missing valuesMissing
도로명주소 has 244 (55.7%) missing valuesMissing
도로명우편번호 has 246 (56.2%) missing valuesMissing
좌표정보(X) has 26 (5.9%) missing valuesMissing
좌표정보(Y) has 26 (5.9%) missing valuesMissing
건물지상층수 has 153 (34.9%) missing valuesMissing
건물지하층수 has 172 (39.3%) missing valuesMissing
발한실여부 has 26 (5.9%) missing valuesMissing
조건부허가시작일자 has 438 (100.0%) missing valuesMissing
조건부허가종료일자 has 438 (100.0%) missing valuesMissing
세탁기수 has 357 (81.5%) missing valuesMissing
다중이용업소여부 has 17 (3.9%) 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
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 191 (43.6%) zerosZeros
건물지상층수 has 239 (54.6%) zerosZeros
건물지하층수 has 252 (57.5%) zerosZeros
세탁기수 has 17 (3.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:31:23.440891
Analysis finished2024-04-29 19:31:24.375523
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3020000
438 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3020000 438
100.0%

Length

2024-04-30T04:31:24.440882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:24.529765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 438
100.0%

관리번호
Text

UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:31:24.680840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9636
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

Unique438 ?
Unique (%)100.0%

Sample

1st row3020000-205-1987-01590
2nd row3020000-205-1987-01591
3rd row3020000-205-1987-01592
4th row3020000-205-1987-01593
5th row3020000-205-1987-01596
ValueCountFrequency (%)
3020000-205-1987-01590 1
 
0.2%
3020000-205-2000-01688 1
 
0.2%
3020000-205-2001-01691 1
 
0.2%
3020000-205-2001-01690 1
 
0.2%
3020000-205-2001-01689 1
 
0.2%
3020000-205-2001-01688 1
 
0.2%
3020000-205-2001-01686 1
 
0.2%
3020000-205-2000-01694 1
 
0.2%
3020000-205-2000-01693 1
 
0.2%
3020000-205-2000-01692 1
 
0.2%
Other values (428) 428
97.7%
2024-04-30T04:31:24.969690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3842
39.9%
- 1314
 
13.6%
2 1165
 
12.1%
1 766
 
7.9%
5 643
 
6.7%
3 556
 
5.8%
9 520
 
5.4%
8 276
 
2.9%
6 201
 
2.1%
4 194
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8322
86.4%
Dash Punctuation 1314
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3842
46.2%
2 1165
 
14.0%
1 766
 
9.2%
5 643
 
7.7%
3 556
 
6.7%
9 520
 
6.2%
8 276
 
3.3%
6 201
 
2.4%
4 194
 
2.3%
7 159
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3842
39.9%
- 1314
 
13.6%
2 1165
 
12.1%
1 766
 
7.9%
5 643
 
6.7%
3 556
 
5.8%
9 520
 
5.4%
8 276
 
2.9%
6 201
 
2.1%
4 194
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3842
39.9%
- 1314
 
13.6%
2 1165
 
12.1%
1 766
 
7.9%
5 643
 
6.7%
3 556
 
5.8%
9 520
 
5.4%
8 276
 
2.9%
6 201
 
2.1%
4 194
 
2.0%

인허가일자
Date

Distinct303
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1987-01-14 00:00:00
Maximum2024-03-15 00:00:00
2024-04-30T04:31:25.109776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:25.225202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3
349 
1
89 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 349
79.7%
1 89
 
20.3%

Length

2024-04-30T04:31:25.336832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:25.415869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 349
79.7%
1 89
 
20.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
349 
영업/정상
89 

Length

Max length5
Median length2
Mean length2.609589
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 349
79.7%
영업/정상 89
 
20.3%

Length

2024-04-30T04:31:25.506116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:25.589937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 349
79.7%
영업/정상 89
 
20.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2
349 
1
89 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 349
79.7%
1 89
 
20.3%

Length

2024-04-30T04:31:25.673028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:25.749768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 349
79.7%
1 89
 
20.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
349 
영업
89 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 349
79.7%
영업 89
 
20.3%

Length

2024-04-30T04:31:25.829384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:25.907874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 349
79.7%
영업 89
 
20.3%

폐업일자
Date

MISSING 

Distinct287
Distinct (%)82.2%
Missing89
Missing (%)20.3%
Memory size3.6 KiB
Minimum1990-09-07 00:00:00
Maximum2024-04-16 00:00:00
2024-04-30T04:31:26.017769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:26.141265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

전화번호
Text

MISSING 

Distinct385
Distinct (%)92.5%
Missing22
Missing (%)5.0%
Memory size3.6 KiB
2024-04-30T04:31:26.362469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9110577
Min length2

Characters and Unicode

Total characters4123
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

Unique366 ?
Unique (%)88.0%

Sample

1st row0207989713
2nd row0207938974
3rd row02 7198887
4th row0207950702
5th row02 7946859
ValueCountFrequency (%)
02 240
34.3%
0200000000 10
 
1.4%
797 7
 
1.0%
0 4
 
0.6%
00000 4
 
0.6%
7146427 3
 
0.4%
713 3
 
0.4%
798 3
 
0.4%
7542430 2
 
0.3%
711 2
 
0.3%
Other values (393) 422
60.3%
2024-04-30T04:31:26.683960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 815
19.8%
7 596
14.5%
2 586
14.2%
9 394
9.6%
348
8.4%
1 269
 
6.5%
4 242
 
5.9%
5 238
 
5.8%
3 221
 
5.4%
6 212
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3775
91.6%
Space Separator 348
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 815
21.6%
7 596
15.8%
2 586
15.5%
9 394
10.4%
1 269
 
7.1%
4 242
 
6.4%
5 238
 
6.3%
3 221
 
5.9%
6 212
 
5.6%
8 202
 
5.4%
Space Separator
ValueCountFrequency (%)
348
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4123
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 815
19.8%
7 596
14.5%
2 586
14.2%
9 394
9.6%
348
8.4%
1 269
 
6.5%
4 242
 
5.9%
5 238
 
5.8%
3 221
 
5.4%
6 212
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 815
19.8%
7 596
14.5%
2 586
14.2%
9 394
9.6%
348
8.4%
1 269
 
6.5%
4 242
 
5.9%
5 238
 
5.8%
3 221
 
5.4%
6 212
 
5.1%

소재지면적
Real number (ℝ)

ZEROS 

Distinct184
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.643973
Minimum0
Maximum765.81
Zeros191
Zeros (%)43.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:26.834911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16.75
Q341
95-th percentile115.109
Maximum765.81
Range765.81
Interquartile range (IQR)41

Descriptive statistics

Standard deviation58.678104
Coefficient of variation (CV)1.8543217
Kurtosis61.881509
Mean31.643973
Median Absolute Deviation (MAD)16.75
Skewness6.1975861
Sum13860.06
Variance3443.1199
MonotonicityNot monotonic
2024-04-30T04:31:26.967891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 191
43.6%
33.0 14
 
3.2%
23.1 7
 
1.6%
41.0 6
 
1.4%
26.4 5
 
1.1%
36.0 5
 
1.1%
49.5 4
 
0.9%
44.14 4
 
0.9%
66.0 4
 
0.9%
52.8 3
 
0.7%
Other values (174) 195
44.5%
ValueCountFrequency (%)
0.0 191
43.6%
6.6 1
 
0.2%
9.27 1
 
0.2%
9.79 1
 
0.2%
9.9 2
 
0.5%
10.2 1
 
0.2%
11.17 1
 
0.2%
12.0 1
 
0.2%
12.01 1
 
0.2%
12.15 1
 
0.2%
ValueCountFrequency (%)
765.81 1
0.2%
410.0 1
0.2%
297.0 2
0.5%
282.12 1
0.2%
223.85 1
0.2%
211.79 1
0.2%
200.5 1
0.2%
178.55 1
0.2%
167.9 1
0.2%
166.94 1
0.2%

소재지우편번호
Text

Distinct113
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:31:27.333898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0319635
Min length6

Characters and Unicode

Total characters2642
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

Unique38 ?
Unique (%)8.7%

Sample

1st row140780
2nd row140881
3rd row140897
4th row140843
5th row140865
ValueCountFrequency (%)
140909 16
 
3.7%
140823 15
 
3.4%
140833 14
 
3.2%
140857 13
 
3.0%
140824 13
 
3.0%
140011 10
 
2.3%
140900 10
 
2.3%
140906 9
 
2.1%
140901 9
 
2.1%
140863 9
 
2.1%
Other values (103) 320
73.1%
2024-04-30T04:31:27.771243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 627
23.7%
1 562
21.3%
4 504
19.1%
8 350
13.2%
9 147
 
5.6%
3 118
 
4.5%
2 106
 
4.0%
6 78
 
3.0%
7 69
 
2.6%
5 67
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2628
99.5%
Dash Punctuation 14
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 627
23.9%
1 562
21.4%
4 504
19.2%
8 350
13.3%
9 147
 
5.6%
3 118
 
4.5%
2 106
 
4.0%
6 78
 
3.0%
7 69
 
2.6%
5 67
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2642
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 627
23.7%
1 562
21.3%
4 504
19.1%
8 350
13.2%
9 147
 
5.6%
3 118
 
4.5%
2 106
 
4.0%
6 78
 
3.0%
7 69
 
2.6%
5 67
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 627
23.7%
1 562
21.3%
4 504
19.1%
8 350
13.2%
9 147
 
5.6%
3 118
 
4.5%
2 106
 
4.0%
6 78
 
3.0%
7 69
 
2.6%
5 67
 
2.5%

지번주소
Text

Distinct409
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:31:27.995596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length40
Mean length24.579909
Min length18

Characters and Unicode

Total characters10766
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique384 ?
Unique (%)87.7%

Sample

1st row서울특별시 용산구 한강로3가 40-171번지
2nd row서울특별시 용산구 한강로3가 40-731번지
3rd row서울특별시 용산구 효창동 5-398번지
4th row서울특별시 용산구 용산동5가 1-13번지
5th row서울특별시 용산구 이태원동 130-7번지
ValueCountFrequency (%)
서울특별시 438
22.7%
용산구 438
22.7%
이태원동 52
 
2.7%
한남동 50
 
2.6%
이촌동 40
 
2.1%
보광동 38
 
2.0%
후암동 31
 
1.6%
1층 29
 
1.5%
용산동2가 28
 
1.4%
한강로3가 17
 
0.9%
Other values (502) 772
39.9%
2024-04-30T04:31:28.372469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1900
17.6%
용 496
 
4.6%
산 496
 
4.6%
1 484
 
4.5%
서 456
 
4.2%
시 442
 
4.1%
울 439
 
4.1%
특 438
 
4.1%
별 438
 
4.1%
구 438
 
4.1%
Other values (126) 4739
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6281
58.3%
Decimal Number 2153
 
20.0%
Space Separator 1900
 
17.6%
Dash Punctuation 407
 
3.8%
Uppercase Letter 11
 
0.1%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 496
 
7.9%
산 496
 
7.9%
서 456
 
7.3%
시 442
 
7.0%
울 439
 
7.0%
특 438
 
7.0%
별 438
 
7.0%
구 438
 
7.0%
지 416
 
6.6%
동 413
 
6.6%
Other values (103) 1809
28.8%
Decimal Number
ValueCountFrequency (%)
1 484
22.5%
2 360
16.7%
3 270
12.5%
0 197
9.2%
5 194
9.0%
6 178
 
8.3%
4 159
 
7.4%
7 120
 
5.6%
8 102
 
4.7%
9 89
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
27.3%
C 2
18.2%
J 2
18.2%
D 2
18.2%
L 1
 
9.1%
G 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 5
83.3%
[ 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 5
83.3%
] 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1900
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 407
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6281
58.3%
Common 4474
41.6%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 496
 
7.9%
산 496
 
7.9%
서 456
 
7.3%
시 442
 
7.0%
울 439
 
7.0%
특 438
 
7.0%
별 438
 
7.0%
구 438
 
7.0%
지 416
 
6.6%
동 413
 
6.6%
Other values (103) 1809
28.8%
Common
ValueCountFrequency (%)
1900
42.5%
1 484
 
10.8%
- 407
 
9.1%
2 360
 
8.0%
3 270
 
6.0%
0 197
 
4.4%
5 194
 
4.3%
6 178
 
4.0%
4 159
 
3.6%
7 120
 
2.7%
Other values (7) 205
 
4.6%
Latin
ValueCountFrequency (%)
B 3
27.3%
C 2
18.2%
J 2
18.2%
D 2
18.2%
L 1
 
9.1%
G 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6281
58.3%
ASCII 4485
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1900
42.4%
1 484
 
10.8%
- 407
 
9.1%
2 360
 
8.0%
3 270
 
6.0%
0 197
 
4.4%
5 194
 
4.3%
6 178
 
4.0%
4 159
 
3.5%
7 120
 
2.7%
Other values (13) 216
 
4.8%
Hangul
ValueCountFrequency (%)
용 496
 
7.9%
산 496
 
7.9%
서 456
 
7.3%
시 442
 
7.0%
울 439
 
7.0%
특 438
 
7.0%
별 438
 
7.0%
구 438
 
7.0%
지 416
 
6.6%
동 413
 
6.6%
Other values (103) 1809
28.8%

도로명주소
Text

MISSING 

Distinct191
Distinct (%)98.5%
Missing244
Missing (%)55.7%
Memory size3.6 KiB
2024-04-30T04:31:28.700358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length45
Mean length30.783505
Min length21

Characters and Unicode

Total characters5972
Distinct characters156
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)96.9%

Sample

1st row서울특별시 용산구 효창원로69길 14 (효창동)
2nd row서울특별시 용산구 이태원로26길 15 (이태원동)
3rd row서울특별시 용산구 효창원로98길 13, 1층 (청파동1가)
4th row서울특별시 용산구 백범로79길 81, 1층 (효창동, 효성빌라)
5th row서울특별시 용산구 신흥로 30 (용산동2가)
ValueCountFrequency (%)
서울특별시 194
 
17.4%
용산구 194
 
17.4%
1층 25
 
2.2%
이태원동 21
 
1.9%
이촌동 16
 
1.4%
보광동 16
 
1.4%
한남동 12
 
1.1%
한강대로 11
 
1.0%
후암동 11
 
1.0%
용산동2가 9
 
0.8%
Other values (347) 605
54.3%
2024-04-30T04:31:29.168296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
920
 
15.4%
1 246
 
4.1%
로 230
 
3.9%
용 224
 
3.8%
산 224
 
3.8%
서 216
 
3.6%
시 200
 
3.3%
울 196
 
3.3%
( 195
 
3.3%
) 195
 
3.3%
Other values (146) 3126
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3529
59.1%
Decimal Number 966
 
16.2%
Space Separator 920
 
15.4%
Open Punctuation 195
 
3.3%
Close Punctuation 195
 
3.3%
Other Punctuation 118
 
2.0%
Dash Punctuation 37
 
0.6%
Uppercase Letter 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 230
 
6.5%
용 224
 
6.3%
산 224
 
6.3%
서 216
 
6.1%
시 200
 
5.7%
울 196
 
5.6%
구 195
 
5.5%
별 194
 
5.5%
특 194
 
5.5%
동 187
 
5.3%
Other values (125) 1469
41.6%
Decimal Number
ValueCountFrequency (%)
1 246
25.5%
2 159
16.5%
3 109
11.3%
0 96
 
9.9%
4 78
 
8.1%
6 74
 
7.7%
5 63
 
6.5%
7 49
 
5.1%
8 47
 
4.9%
9 45
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 5
41.7%
D 3
25.0%
J 1
 
8.3%
C 1
 
8.3%
L 1
 
8.3%
G 1
 
8.3%
Space Separator
ValueCountFrequency (%)
920
100.0%
Open Punctuation
ValueCountFrequency (%)
( 195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 195
100.0%
Other Punctuation
ValueCountFrequency (%)
, 118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3529
59.1%
Common 2431
40.7%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 230
 
6.5%
용 224
 
6.3%
산 224
 
6.3%
서 216
 
6.1%
시 200
 
5.7%
울 196
 
5.6%
구 195
 
5.5%
별 194
 
5.5%
특 194
 
5.5%
동 187
 
5.3%
Other values (125) 1469
41.6%
Common
ValueCountFrequency (%)
920
37.8%
1 246
 
10.1%
( 195
 
8.0%
) 195
 
8.0%
2 159
 
6.5%
, 118
 
4.9%
3 109
 
4.5%
0 96
 
3.9%
4 78
 
3.2%
6 74
 
3.0%
Other values (5) 241
 
9.9%
Latin
ValueCountFrequency (%)
B 5
41.7%
D 3
25.0%
J 1
 
8.3%
C 1
 
8.3%
L 1
 
8.3%
G 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3529
59.1%
ASCII 2443
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
920
37.7%
1 246
 
10.1%
( 195
 
8.0%
) 195
 
8.0%
2 159
 
6.5%
, 118
 
4.8%
3 109
 
4.5%
0 96
 
3.9%
4 78
 
3.2%
6 74
 
3.0%
Other values (11) 253
 
10.4%
Hangul
ValueCountFrequency (%)
로 230
 
6.5%
용 224
 
6.3%
산 224
 
6.3%
서 216
 
6.1%
시 200
 
5.7%
울 196
 
5.6%
구 195
 
5.5%
별 194
 
5.5%
특 194
 
5.5%
동 187
 
5.3%
Other values (125) 1469
41.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)45.8%
Missing246
Missing (%)56.2%
Infinite0
Infinite (%)0.0%
Mean4362.3906
Minimum4300
Maximum4427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:29.324656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4305
Q14328
median4366.5
Q34392
95-th percentile4420.8
Maximum4427
Range127
Interquartile range (IQR)64

Descriptive statistics

Standard deviation37.473879
Coefficient of variation (CV)0.0085902164
Kurtosis-1.2921641
Mean4362.3906
Median Absolute Deviation (MAD)32.5
Skewness-0.0052336238
Sum837579
Variance1404.2916
MonotonicityNot monotonic
2024-04-30T04:31:29.535950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4374 8
 
1.8%
4339 7
 
1.6%
4382 7
 
1.6%
4423 7
 
1.6%
4385 6
 
1.4%
4391 6
 
1.4%
4304 5
 
1.1%
4322 5
 
1.1%
4344 4
 
0.9%
4316 4
 
0.9%
Other values (78) 133
30.4%
(Missing) 246
56.2%
ValueCountFrequency (%)
4300 1
 
0.2%
4302 1
 
0.2%
4303 2
 
0.5%
4304 5
1.1%
4305 3
0.7%
4306 1
 
0.2%
4307 2
 
0.5%
4309 1
 
0.2%
4310 1
 
0.2%
4311 1
 
0.2%
ValueCountFrequency (%)
4427 1
 
0.2%
4426 1
 
0.2%
4424 1
 
0.2%
4423 7
1.6%
4419 2
 
0.5%
4417 1
 
0.2%
4415 4
0.9%
4414 1
 
0.2%
4413 3
0.7%
4412 1
 
0.2%

사업장명
Text

Distinct326
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:31:29.932709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length4.5799087
Min length2

Characters and Unicode

Total characters2006
Distinct characters235
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)61.4%

Sample

1st row임상사
2nd row승리사
3rd row백양사
4th row한진사
5th row민경사
ValueCountFrequency (%)
백양사 17
 
3.6%
백조사 7
 
1.5%
미미사 6
 
1.3%
미미세탁소 6
 
1.3%
세탁소 6
 
1.3%
현대세탁소 5
 
1.1%
월풀빨래방 5
 
1.1%
현대사 4
 
0.9%
제일사 4
 
0.9%
우리세탁소 4
 
0.9%
Other values (330) 406
86.4%
2024-04-30T04:31:30.497178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 208
 
10.4%
세 135
 
6.7%
탁 131
 
6.5%
소 90
 
4.5%
미 65
 
3.2%
크 54
 
2.7%
리 49
 
2.4%
백 45
 
2.2%
양 42
 
2.1%
래 36
 
1.8%
Other values (225) 1151
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1923
95.9%
Space Separator 32
 
1.6%
Decimal Number 20
 
1.0%
Close Punctuation 12
 
0.6%
Open Punctuation 12
 
0.6%
Uppercase Letter 4
 
0.2%
Other Punctuation 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 208
 
10.8%
세 135
 
7.0%
탁 131
 
6.8%
소 90
 
4.7%
미 65
 
3.4%
크 54
 
2.8%
리 49
 
2.5%
백 45
 
2.3%
양 42
 
2.2%
래 36
 
1.9%
Other values (212) 1068
55.5%
Decimal Number
ValueCountFrequency (%)
1 9
45.0%
2 5
25.0%
9 3
 
15.0%
4 3
 
15.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
T 1
25.0%
K 1
25.0%
M 1
25.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1923
95.9%
Common 78
 
3.9%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 208
 
10.8%
세 135
 
7.0%
탁 131
 
6.8%
소 90
 
4.7%
미 65
 
3.4%
크 54
 
2.8%
리 49
 
2.5%
백 45
 
2.3%
양 42
 
2.2%
래 36
 
1.9%
Other values (212) 1068
55.5%
Common
ValueCountFrequency (%)
32
41.0%
) 12
 
15.4%
( 12
 
15.4%
1 9
 
11.5%
2 5
 
6.4%
9 3
 
3.8%
4 3
 
3.8%
. 2
 
2.6%
Latin
ValueCountFrequency (%)
L 1
20.0%
T 1
20.0%
K 1
20.0%
M 1
20.0%
r 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1923
95.9%
ASCII 83
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 208
 
10.8%
세 135
 
7.0%
탁 131
 
6.8%
소 90
 
4.7%
미 65
 
3.4%
크 54
 
2.8%
리 49
 
2.5%
백 45
 
2.3%
양 42
 
2.2%
래 36
 
1.9%
Other values (212) 1068
55.5%
ASCII
ValueCountFrequency (%)
32
38.6%
) 12
 
14.5%
( 12
 
14.5%
1 9
 
10.8%
2 5
 
6.0%
9 3
 
3.6%
4 3
 
3.6%
. 2
 
2.4%
L 1
 
1.2%
T 1
 
1.2%
Other values (3) 3
 
3.6%

최종수정일자
Date

Distinct281
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1999-02-08 00:00:00
Maximum2024-04-16 13:36:33
2024-04-30T04:31:30.686895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:30.871957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
I
368 
U
70 

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 368
84.0%
U 70
 
16.0%

Length

2024-04-30T04:31:31.075861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:31.189806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 368
84.0%
u 70
 
16.0%

데이터갱신일자
Date

Distinct69
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-04-30T04:31:31.276793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:31.558379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
일반세탁업
432 
세탁업 기타
 
3
빨래방업
 
2
운동화전문세탁업
 
1

Length

Max length8
Median length5
Mean length5.0091324
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 432
98.6%
세탁업 기타 3
 
0.7%
빨래방업 2
 
0.5%
운동화전문세탁업 1
 
0.2%

Length

2024-04-30T04:31:31.692991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:31.801674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 432
98.0%
세탁업 3
 
0.7%
기타 3
 
0.7%
빨래방업 2
 
0.5%
운동화전문세탁업 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct337
Distinct (%)81.8%
Missing26
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean198064.47
Minimum195266.36
Maximum200786.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:31.912147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195266.36
5-th percentile195947.09
Q1196969.81
median197716.55
Q3199485.18
95-th percentile200245.41
Maximum200786.75
Range5520.3896
Interquartile range (IQR)2515.3695

Descriptive statistics

Standard deviation1423.535
Coefficient of variation (CV)0.0071872307
Kurtosis-1.2274864
Mean198064.47
Median Absolute Deviation (MAD)1180.3595
Skewness0.14054491
Sum81602561
Variance2026452
MonotonicityNot monotonic
2024-04-30T04:31:32.046124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196149.859380737 5
 
1.1%
197194.757574283 4
 
0.9%
199835.852006798 4
 
0.9%
199675.289712107 4
 
0.9%
195996.462170988 4
 
0.9%
196969.809433334 3
 
0.7%
197542.687282146 3
 
0.7%
197679.255159437 3
 
0.7%
195936.18328447 3
 
0.7%
199183.775191974 3
 
0.7%
Other values (327) 376
85.8%
(Missing) 26
 
5.9%
ValueCountFrequency (%)
195266.362355276 2
0.5%
195515.18314741 1
0.2%
195544.606275448 2
0.5%
195565.493588098 1
0.2%
195708.959326024 1
0.2%
195758.260949987 1
0.2%
195828.64255647 1
0.2%
195849.48675824 1
0.2%
195880.341189913 1
0.2%
195883.073859259 1
0.2%
ValueCountFrequency (%)
200786.751951771 1
0.2%
200709.749866443 1
0.2%
200693.652523916 1
0.2%
200676.581104561 1
0.2%
200648.866223783 1
0.2%
200628.554655257 1
0.2%
200626.06966197 1
0.2%
200624.747166374 1
0.2%
200614.319913696 2
0.5%
200445.904829677 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct337
Distinct (%)81.8%
Missing26
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean448235.63
Minimum446194.35
Maximum450161.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:32.171503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446194.35
5-th percentile446657.77
Q1447579.28
median448093.61
Q3448988.37
95-th percentile449874.6
Maximum450161.84
Range3967.4869
Interquartile range (IQR)1409.0962

Descriptive statistics

Standard deviation983.18762
Coefficient of variation (CV)0.0021934615
Kurtosis-0.82695698
Mean448235.63
Median Absolute Deviation (MAD)661.96972
Skewness0.142466
Sum1.8467308 × 108
Variance966657.89
MonotonicityNot monotonic
2024-04-30T04:31:32.323483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448581.975861465 5
 
1.1%
448455.338450919 4
 
0.9%
447804.013707552 4
 
0.9%
448030.294524199 4
 
0.9%
447016.989874534 4
 
0.9%
449677.13756829 3
 
0.7%
448325.294355232 3
 
0.7%
446425.373848781 3
 
0.7%
447052.565741975 3
 
0.7%
448573.144638514 3
 
0.7%
Other values (327) 376
85.8%
(Missing) 26
 
5.9%
ValueCountFrequency (%)
446194.350546744 1
 
0.2%
446248.255892098 1
 
0.2%
446262.544080318 2
0.5%
446361.295910071 1
 
0.2%
446425.373848781 3
0.7%
446461.724458253 1
 
0.2%
446492.478755935 1
 
0.2%
446510.928737718 2
0.5%
446521.047069429 1
 
0.2%
446524.508385914 2
0.5%
ValueCountFrequency (%)
450161.83746991 1
 
0.2%
450150.14820076 1
 
0.2%
450123.296271573 1
 
0.2%
450111.271922946 1
 
0.2%
450087.738751886 1
 
0.2%
450086.186702519 2
0.5%
450080.821136306 2
0.5%
450066.198984826 1
 
0.2%
450052.426977089 1
 
0.2%
449988.563126511 3
0.7%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
일반세탁업
415 
<NA>
 
17
세탁업 기타
 
3
빨래방업
 
2
운동화전문세탁업
 
1

Length

Max length8
Median length5
Mean length4.9703196
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 415
94.7%
<NA> 17
 
3.9%
세탁업 기타 3
 
0.7%
빨래방업 2
 
0.5%
운동화전문세탁업 1
 
0.2%

Length

2024-04-30T04:31:32.486186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:32.610994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 415
94.1%
na 17
 
3.9%
세탁업 3
 
0.7%
기타 3
 
0.7%
빨래방업 2
 
0.5%
운동화전문세탁업 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)4.2%
Missing153
Missing (%)34.9%
Infinite0
Infinite (%)0.0%
Mean0.85964912
Minimum0
Maximum40
Zeros239
Zeros (%)54.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:32.725163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.8
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9736748
Coefficient of variation (CV)4.622438
Kurtosis67.036464
Mean0.85964912
Median Absolute Deviation (MAD)0
Skewness7.8133544
Sum245
Variance15.790091
MonotonicityNot monotonic
2024-04-30T04:31:32.833372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 239
54.6%
2 11
 
2.5%
1 11
 
2.5%
3 9
 
2.1%
4 5
 
1.1%
5 3
 
0.7%
15 2
 
0.5%
6 1
 
0.2%
7 1
 
0.2%
37 1
 
0.2%
Other values (2) 2
 
0.5%
(Missing) 153
34.9%
ValueCountFrequency (%)
0 239
54.6%
1 11
 
2.5%
2 11
 
2.5%
3 9
 
2.1%
4 5
 
1.1%
5 3
 
0.7%
6 1
 
0.2%
7 1
 
0.2%
15 2
 
0.5%
30 1
 
0.2%
ValueCountFrequency (%)
40 1
 
0.2%
37 1
 
0.2%
30 1
 
0.2%
15 2
 
0.5%
7 1
 
0.2%
6 1
 
0.2%
5 3
 
0.7%
4 5
1.1%
3 9
2.1%
2 11
2.5%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.6%
Missing172
Missing (%)39.3%
Infinite0
Infinite (%)0.0%
Mean0.11654135
Minimum0
Maximum6
Zeros252
Zeros (%)57.5%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:32.942071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.75
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61854125
Coefficient of variation (CV)5.307483
Kurtosis52.49007
Mean0.11654135
Median Absolute Deviation (MAD)0
Skewness6.8625811
Sum31
Variance0.38259328
MonotonicityNot monotonic
2024-04-30T04:31:33.030930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 252
57.5%
1 7
 
1.6%
2 3
 
0.7%
3 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
(Missing) 172
39.3%
ValueCountFrequency (%)
0 252
57.5%
1 7
 
1.6%
2 3
 
0.7%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
2 3
 
0.7%
1 7
 
1.6%
0 252
57.5%

사용시작지상층
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
193 
<NA>
175 
1
63 
2
 
6
20
 
1

Length

Max length4
Median length1
Mean length2.2009132
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 193
44.1%
<NA> 175
40.0%
1 63
 
14.4%
2 6
 
1.4%
20 1
 
0.2%

Length

2024-04-30T04:31:33.144938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:33.249266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 193
44.1%
na 175
40.0%
1 63
 
14.4%
2 6
 
1.4%
20 1
 
0.2%

사용끝지상층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
371 
1
49 
0
 
12
2
 
5
20
 
1

Length

Max length4
Median length4
Mean length3.543379
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
84.7%
1 49
 
11.2%
0 12
 
2.7%
2 5
 
1.1%
20 1
 
0.2%

Length

2024-04-30T04:31:33.369388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:33.478518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
84.7%
1 49
 
11.2%
0 12
 
2.7%
2 5
 
1.1%
20 1
 
0.2%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
232 
0
197 
1
 
8
2
 
1

Length

Max length4
Median length4
Mean length2.5890411
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 232
53.0%
0 197
45.0%
1 8
 
1.8%
2 1
 
0.2%

Length

2024-04-30T04:31:33.597883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:33.692955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
53.0%
0 197
45.0%
1 8
 
1.8%
2 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
417 
0
 
14
1
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.8561644
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 417
95.2%
0 14
 
3.2%
1 6
 
1.4%
2 1
 
0.2%

Length

2024-04-30T04:31:33.797508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:33.887138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 417
95.2%
0 14
 
3.2%
1 6
 
1.4%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
256 
<NA>
182 

Length

Max length4
Median length1
Mean length2.2465753
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 256
58.4%
<NA> 182
41.6%

Length

2024-04-30T04:31:33.978889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:34.063627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 256
58.4%
na 182
41.6%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
256 
<NA>
182 

Length

Max length4
Median length1
Mean length2.2465753
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 256
58.4%
<NA> 182
41.6%

Length

2024-04-30T04:31:34.150552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:34.248552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 256
58.4%
na 182
41.6%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
256 
<NA>
182 

Length

Max length4
Median length1
Mean length2.2465753
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 256
58.4%
<NA> 182
41.6%

Length

2024-04-30T04:31:34.341231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:34.427683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 256
58.4%
na 182
41.6%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing26
Missing (%)5.9%
Memory size1008.0 B
False
412 
(Missing)
 
26
ValueCountFrequency (%)
False 412
94.1%
(Missing) 26
 
5.9%
2024-04-30T04:31:34.510931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
256 
<NA>
182 

Length

Max length4
Median length1
Mean length2.2465753
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 256
58.4%
<NA> 182
41.6%

Length

2024-04-30T04:31:34.615304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:34.727049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 256
58.4%
na 182
41.6%

조건부허가신고사유
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
435 
보건위생과-32299(2019.12.5)
 
3

Length

Max length22
Median length4
Mean length4.1232877
Min length4

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> 435
99.3%
보건위생과-32299(2019.12.5) 3
 
0.7%

Length

2024-04-30T04:31:34.833357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:34.927146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 435
99.3%
보건위생과-32299(2019.12.5 3
 
0.7%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing438
Missing (%)100.0%
Memory size4.0 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
410 
임대
 
23
자가
 
5

Length

Max length4
Median length4
Mean length3.8721461
Min length2

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> 410
93.6%
임대 23
 
5.3%
자가 5
 
1.1%

Length

2024-04-30T04:31:35.024332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:35.113969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
93.6%
임대 23
 
5.3%
자가 5
 
1.1%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)9.9%
Missing357
Missing (%)81.5%
Infinite0
Infinite (%)0.0%
Mean2.0617284
Minimum0
Maximum11
Zeros17
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:31:35.187756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.798233
Coefficient of variation (CV)0.87219685
Kurtosis6.7387881
Mean2.0617284
Median Absolute Deviation (MAD)1
Skewness1.7965019
Sum167
Variance3.233642
MonotonicityNot monotonic
2024-04-30T04:31:35.273931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 25
 
5.7%
0 17
 
3.9%
3 13
 
3.0%
1 13
 
3.0%
4 8
 
1.8%
5 3
 
0.7%
7 1
 
0.2%
11 1
 
0.2%
(Missing) 357
81.5%
ValueCountFrequency (%)
0 17
3.9%
1 13
3.0%
2 25
5.7%
3 13
3.0%
4 8
 
1.8%
5 3
 
0.7%
7 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
11 1
 
0.2%
7 1
 
0.2%
5 3
 
0.7%
4 8
 
1.8%
3 13
3.0%
2 25
5.7%
1 13
3.0%
0 17
3.9%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
402 
0
 
32
1
 
3
8
 
1

Length

Max length4
Median length4
Mean length3.7534247
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
91.8%
0 32
 
7.3%
1 3
 
0.7%
8 1
 
0.2%

Length

2024-04-30T04:31:35.367771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:35.460435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
91.8%
0 32
 
7.3%
1 3
 
0.7%
8 1
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
402 
0
 
28
1
 
7
12
 
1

Length

Max length4
Median length4
Mean length3.7557078
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
91.8%
0 28
 
6.4%
1 7
 
1.6%
12 1
 
0.2%

Length

2024-04-30T04:31:35.549006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:35.634841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
91.8%
0 28
 
6.4%
1 7
 
1.6%
12 1
 
0.2%

회수건조수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
380 
1
 
27
0
 
25
2
 
5
8
 
1

Length

Max length4
Median length4
Mean length3.6027397
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 380
86.8%
1 27
 
6.2%
0 25
 
5.7%
2 5
 
1.1%
8 1
 
0.2%

Length

2024-04-30T04:31:35.732044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:35.832886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 380
86.8%
1 27
 
6.2%
0 25
 
5.7%
2 5
 
1.1%
8 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
383 
0
55 

Length

Max length4
Median length4
Mean length3.6232877
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> 383
87.4%
0 55
 
12.6%

Length

2024-04-30T04:31:35.935869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:36.038690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 383
87.4%
0 55
 
12.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing17
Missing (%)3.9%
Memory size1008.0 B
False
421 
(Missing)
 
17
ValueCountFrequency (%)
False 421
96.1%
(Missing) 17
 
3.9%
2024-04-30T04:31:36.109924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030200003020000-205-1987-0159019871029<NA>3폐업2폐업20070824<NA><NA><NA>0207989713115.04140780서울특별시 용산구 한강로3가 40-171번지<NA><NA>임상사2007-06-21 00:00:00I2018-08-31 23:59:59.0일반세탁업196672.4209447097.91176일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130200003020000-205-1987-0159119871029<NA>3폐업2폐업20021230<NA><NA><NA>020793897427.0140881서울특별시 용산구 한강로3가 40-731번지<NA><NA>승리사2003-03-04 00:00:00I2018-08-31 23:59:59.0일반세탁업196624.645439447023.421962일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230200003020000-205-1987-0159219871117<NA>3폐업2폐업20160819<NA><NA><NA>02 7198887211.79140897서울특별시 용산구 효창동 5-398번지서울특별시 용산구 효창원로69길 14 (효창동)4319백양사1999-02-10 00:00:00I2018-08-31 23:59:59.0일반세탁업196525.881563448852.018921일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330200003020000-205-1987-0159319871215<NA>3폐업2폐업20031130<NA><NA><NA>0207950702130.0140843서울특별시 용산구 용산동5가 1-13번지<NA><NA>한진사2003-04-11 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430200003020000-205-1987-0159619870114<NA>1영업/정상1영업<NA><NA><NA><NA>02 794685943.56140865서울특별시 용산구 이태원동 130-7번지서울특별시 용산구 이태원로26길 15 (이태원동)4391민경사2001-09-27 00:00:00I2018-08-31 23:59:59.0일반세탁업199346.288217447948.847337일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530200003020000-205-1987-0160719870618<NA>3폐업2폐업19960103<NA><NA><NA>02 71279270.0140070서울특별시 용산구 도원동 8-64번지<NA><NA>삼양사2001-09-27 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630200003020000-205-1987-016081987-06-18<NA>1영업/정상1영업<NA><NA><NA><NA>02071893450.0140-868서울특별시 용산구 청파동1가 1-152서울특별시 용산구 효창원로98길 13, 1층 (청파동1가)4306연봉사2023-07-21 11:34:57U2022-12-06 22:03:00.0일반세탁업196778.621451449688.386129<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730200003020000-205-1987-0160919870618<NA>1영업/정상1영업<NA><NA><NA><NA>020719273118.0140897서울특별시 용산구 효창동 5-675번지 효성빌라서울특별시 용산구 백범로79길 81, 1층 (효창동, 효성빌라)4317청백사2019-06-18 14:26:23U2019-06-20 02:40:00.0일반세탁업196797.850245448895.969315일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830200003020000-205-1987-0161019870618<NA>3폐업2폐업19961231<NA><NA><NA>02 75424390.0140821서울특별시 용산구 동자동 35-89번지<NA><NA>국도사2001-09-27 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930200003020000-205-1987-0161119870618<NA>3폐업2폐업20150626<NA><NA><NA>02079541360.0140842서울특별시 용산구 용산동2가 45-12번지서울특별시 용산구 신흥로 30 (용산동2가)4339백양사2003-02-26 00:00:00I2018-08-31 23:59:59.0일반세탁업198802.694645448754.636552일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
42830200003020000-205-2020-0000420200820<NA>1영업/정상1영업<NA><NA><NA><NA>02 798462065.46140012서울특별시 용산구 한강로2가 422 래미안용산 더 센트럴서울특별시 용산구 한강대로 95, 지하1층 108호 (한강로2가, 래미안용산 더 센트럴)4378더 센트럴 명품 세탁2021-12-20 15:04:34U2021-12-22 02:40:00.0일반세탁업197011.0447404.0일반세탁업00<NA><NA>22000N0<NA><NA><NA><NA>20020N
42930200003020000-205-2020-0000520200821<NA>3폐업2폐업20211129<NA><NA><NA>02 714642714.35140909서울특별시 용산구 이촌동 203-69 이촌상가서울특별시 용산구 이촌로18길 21-6, 이촌상가 (이촌동)4374마스터크리닝2021-11-29 11:14:04U2021-12-01 02:40:00.0일반세탁업195936.183284447052.565742일반세탁업000000000N0<NA><NA><NA><NA>30010N
43030200003020000-205-2020-0000620200909<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.77140882서울특별시 용산구 한강로3가 63-70서울특별시 용산구 서빙고로 17, 1층 139호 (한강로3가)4387해링턴세탁소2020-10-21 10:38:42U2020-10-23 02:40:00.0일반세탁업197071.403206447073.622842일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
43130200003020000-205-2020-0000720201020<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.64140906서울특별시 용산구 이촌동 301-10 로얄상가서울특별시 용산구 이촌로 245, 2층 206호 (이촌동, 로얄상가)4423미미세탁소2020-10-20 11:35:01I2020-10-22 00:23:10.0일반세탁업197679.255159446425.373849일반세탁업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>20010N
43230200003020000-205-2021-000012021-01-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.13140-909서울특별시 용산구 이촌동 203-62 1층서울특별시 용산구 이촌로18길 21-47, 1층 (이촌동)4374대림세탁소2023-11-17 14:00:56U2022-10-31 23:09:00.0일반세탁업195996.462171447016.989875<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43330200003020000-205-2021-0000220210504<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.0140901서울특별시 용산구 후암동 244-79 남산리치빌서울특별시 용산구 후암로28길 38, 1층 (후암동)4331영미세탁2021-05-04 16:12:13I2021-05-06 00:22:56.0빨래방업198101.445233449672.909205빨래방업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>00000N
43430200003020000-205-2021-0000320210825<NA>1영업/정상1영업<NA><NA><NA><NA>0708850667733.0140801서울특별시 용산구 갈월동 8-13서울특별시 용산구 한강대로96길 8, 1층 (갈월동)4334우리동네휴빨래방2021-08-25 11:21:07I2021-08-27 00:22:50.0빨래방업197490.508411449477.169285빨래방업000000000N0<NA><NA><NA><NA>40000N
43530200003020000-205-2022-0000120220113<NA>3폐업2폐업20220125<NA><NA><NA><NA>25.08140901서울특별시 용산구 후암동 353-2서울특별시 용산구 두텁바위로58길 18, 1층 (후암동)4328진양세탁2022-01-25 13:25:58U2022-01-27 02:40:00.0일반세탁업198376.98397449698.546073일반세탁업000000000N0<NA><NA><NA><NA>20110N
43630200003020000-205-2024-000012024-01-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 319 794813.2140-821서울특별시 용산구 동자동 30-14서울특별시 용산구 한강대로102길 21, 1층 (동자동)4334그린프라자2024-01-16 15:13:34I2023-11-30 23:08:00.0일반세탁업197567.565732449711.913452<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43730200003020000-205-2024-000022024-03-15<NA>1영업/정상1영업<NA><NA><NA><NA>02 797 845653.93140-909서울특별시 용산구 이촌동 203-8서울특별시 용산구 이촌로 68-1, 1층 제2호 (이촌동)4374제일세탁소2024-03-15 14:47:29I2023-12-02 23:07:00.0일반세탁업196064.430679447074.37889<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>