Overview

Dataset statistics

Number of variables47
Number of observations554
Missing cells5508
Missing cells (%)21.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory218.7 KiB
Average record size in memory404.2 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-17973/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (92.8%)Imbalance
위생업태명 is highly imbalanced (71.5%)Imbalance
사용끝지하층 is highly imbalanced (58.2%)Imbalance
여성종사자수 is highly imbalanced (53.3%)Imbalance
남성종사자수 is highly imbalanced (53.3%)Imbalance
다중이용업소여부 is highly imbalanced (97.9%)Imbalance
인허가취소일자 has 554 (100.0%) missing valuesMissing
폐업일자 has 162 (29.2%) missing valuesMissing
휴업시작일자 has 554 (100.0%) missing valuesMissing
휴업종료일자 has 554 (100.0%) missing valuesMissing
재개업일자 has 554 (100.0%) missing valuesMissing
전화번호 has 71 (12.8%) missing valuesMissing
도로명주소 has 198 (35.7%) missing valuesMissing
도로명우편번호 has 207 (37.4%) missing valuesMissing
좌표정보(X) has 28 (5.1%) missing valuesMissing
좌표정보(Y) has 28 (5.1%) missing valuesMissing
건물지상층수 has 225 (40.6%) missing valuesMissing
건물지하층수 has 225 (40.6%) missing valuesMissing
발한실여부 has 83 (15.0%) missing valuesMissing
조건부허가신고사유 has 554 (100.0%) missing valuesMissing
조건부허가시작일자 has 554 (100.0%) missing valuesMissing
조건부허가종료일자 has 554 (100.0%) missing valuesMissing
세탁기수 has 331 (59.7%) missing valuesMissing
다중이용업소여부 has 70 (12.6%) 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
조건부허가신고사유 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
건물지상층수 has 292 (52.7%) zerosZeros
건물지하층수 has 295 (53.2%) zerosZeros
세탁기수 has 51 (9.2%) zerosZeros

Reproduction

Analysis started2024-05-11 06:33:56.854082
Analysis finished2024-05-11 06:33:57.963982
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
3210000
554 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 554
100.0%

Length

2024-05-11T15:33:58.053347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:58.181667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 554
100.0%

관리번호
Text

UNIQUE 

Distinct554
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-05-11T15:33:58.395746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters12188
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

Unique554 ?
Unique (%)100.0%

Sample

1st row3210000-205-1965-00001
2nd row3210000-205-1987-01699
3rd row3210000-205-1987-01702
4th row3210000-205-1987-01705
5th row3210000-205-1987-01709
ValueCountFrequency (%)
3210000-205-1965-00001 1
 
0.2%
3210000-205-2007-00002 1
 
0.2%
3210000-205-2006-00015 1
 
0.2%
3210000-205-2006-00016 1
 
0.2%
3210000-205-2007-00006 1
 
0.2%
3210000-205-2007-00005 1
 
0.2%
3210000-205-2007-00004 1
 
0.2%
3210000-205-2007-00003 1
 
0.2%
3210000-205-2007-00001 1
 
0.2%
3210000-205-2006-00017 1
 
0.2%
Other values (544) 544
98.2%
2024-05-11T15:33:58.904795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4684
38.4%
- 1662
 
13.6%
2 1580
 
13.0%
1 1393
 
11.4%
3 722
 
5.9%
5 690
 
5.7%
9 645
 
5.3%
8 302
 
2.5%
7 204
 
1.7%
6 175
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10526
86.4%
Dash Punctuation 1662
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4684
44.5%
2 1580
 
15.0%
1 1393
 
13.2%
3 722
 
6.9%
5 690
 
6.6%
9 645
 
6.1%
8 302
 
2.9%
7 204
 
1.9%
6 175
 
1.7%
4 131
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1662
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12188
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4684
38.4%
- 1662
 
13.6%
2 1580
 
13.0%
1 1393
 
11.4%
3 722
 
5.9%
5 690
 
5.7%
9 645
 
5.3%
8 302
 
2.5%
7 204
 
1.7%
6 175
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4684
38.4%
- 1662
 
13.6%
2 1580
 
13.0%
1 1393
 
11.4%
3 722
 
5.9%
5 690
 
5.7%
9 645
 
5.3%
8 302
 
2.5%
7 204
 
1.7%
6 175
 
1.4%
Distinct462
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum1965-12-20 00:00:00
Maximum2023-10-23 00:00:00
2024-05-11T15:33:59.142401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:33:59.365621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
3
392 
1
162 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 392
70.8%
1 162
29.2%

Length

2024-05-11T15:33:59.581899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:59.759569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 392
70.8%
1 162
29.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
폐업
392 
영업/정상
162 

Length

Max length5
Median length2
Mean length2.8772563
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 392
70.8%
영업/정상 162
29.2%

Length

2024-05-11T15:33:59.928927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:00.111235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 392
70.8%
영업/정상 162
29.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2
392 
1
162 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 392
70.8%
1 162
29.2%

Length

2024-05-11T15:34:00.294092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:00.466930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 392
70.8%
1 162
29.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
폐업
392 
영업
162 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 392
70.8%
영업 162
29.2%

Length

2024-05-11T15:34:00.640493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:00.785189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 392
70.8%
영업 162
29.2%

폐업일자
Date

MISSING 

Distinct342
Distinct (%)87.2%
Missing162
Missing (%)29.2%
Memory size4.5 KiB
Minimum1994-02-02 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T15:34:01.298635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:34:01.510244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB

전화번호
Text

MISSING 

Distinct457
Distinct (%)94.6%
Missing71
Missing (%)12.8%
Memory size4.5 KiB
2024-05-11T15:34:01.868341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.10352
Min length2

Characters and Unicode

Total characters4880
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

Unique433 ?
Unique (%)89.6%

Sample

1st row02 5911966
2nd row02 5835203
3rd row02 5856250
4th row0205838164
5th row02 0
ValueCountFrequency (%)
02 291
33.0%
593 6
 
0.7%
532 6
 
0.7%
587 5
 
0.6%
534 4
 
0.5%
535 4
 
0.5%
585 4
 
0.5%
536 4
 
0.5%
584 3
 
0.3%
583 3
 
0.3%
Other values (500) 551
62.5%
2024-05-11T15:34:02.550554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 827
16.9%
2 764
15.7%
5 716
14.7%
492
10.1%
3 372
7.6%
8 367
7.5%
7 298
 
6.1%
9 287
 
5.9%
4 280
 
5.7%
1 243
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4388
89.9%
Space Separator 492
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 827
18.8%
2 764
17.4%
5 716
16.3%
3 372
8.5%
8 367
8.4%
7 298
 
6.8%
9 287
 
6.5%
4 280
 
6.4%
1 243
 
5.5%
6 234
 
5.3%
Space Separator
ValueCountFrequency (%)
492
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 827
16.9%
2 764
15.7%
5 716
14.7%
492
10.1%
3 372
7.6%
8 367
7.5%
7 298
 
6.1%
9 287
 
5.9%
4 280
 
5.7%
1 243
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 827
16.9%
2 764
15.7%
5 716
14.7%
492
10.1%
3 372
7.6%
8 367
7.5%
7 298
 
6.1%
9 287
 
5.9%
4 280
 
5.7%
1 243
 
5.0%
Distinct242
Distinct (%)43.8%
Missing2
Missing (%)0.4%
Memory size4.5 KiB
2024-05-11T15:34:03.049190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.3061594
Min length3

Characters and Unicode

Total characters2377
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

Unique199 ?
Unique (%)36.1%

Sample

1st row0.00
2nd row.00
3rd row.00
4th row.00
5th row.00
ValueCountFrequency (%)
00 203
36.8%
33.00 24
 
4.3%
26.40 7
 
1.3%
30.00 6
 
1.1%
27.00 6
 
1.1%
0.00 6
 
1.1%
21.00 6
 
1.1%
45.00 5
 
0.9%
49.50 5
 
0.9%
23.00 5
 
0.9%
Other values (232) 279
50.5%
2024-05-11T15:34:03.774556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 771
32.4%
. 552
23.2%
3 179
 
7.5%
2 173
 
7.3%
4 121
 
5.1%
1 118
 
5.0%
5 115
 
4.8%
6 94
 
4.0%
7 91
 
3.8%
9 90
 
3.8%
Other values (2) 73
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1824
76.7%
Other Punctuation 553
 
23.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 771
42.3%
3 179
 
9.8%
2 173
 
9.5%
4 121
 
6.6%
1 118
 
6.5%
5 115
 
6.3%
6 94
 
5.2%
7 91
 
5.0%
9 90
 
4.9%
8 72
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 552
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 771
32.4%
. 552
23.2%
3 179
 
7.5%
2 173
 
7.3%
4 121
 
5.1%
1 118
 
5.0%
5 115
 
4.8%
6 94
 
4.0%
7 91
 
3.8%
9 90
 
3.8%
Other values (2) 73
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 771
32.4%
. 552
23.2%
3 179
 
7.5%
2 173
 
7.3%
4 121
 
5.1%
1 118
 
5.0%
5 115
 
4.8%
6 94
 
4.0%
7 91
 
3.8%
9 90
 
3.8%
Other values (2) 73
 
3.1%
Distinct133
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-05-11T15:34:04.261312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0613718
Min length6

Characters and Unicode

Total characters3358
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 (%)6.9%

Sample

1st row137-829
2nd row137817
3rd row137060
4th row137818
5th row137846
ValueCountFrequency (%)
137040 28
 
5.1%
137882 17
 
3.1%
137810 15
 
2.7%
137834 13
 
2.3%
137809 12
 
2.2%
137906 11
 
2.0%
137829 11
 
2.0%
137880 10
 
1.8%
137871 10
 
1.8%
137817 9
 
1.6%
Other values (123) 418
75.5%
2024-05-11T15:34:05.004042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 660
19.7%
1 657
19.6%
3 639
19.0%
8 523
15.6%
0 285
8.5%
9 167
 
5.0%
4 131
 
3.9%
6 109
 
3.2%
5 80
 
2.4%
2 73
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3324
99.0%
Dash Punctuation 34
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 660
19.9%
1 657
19.8%
3 639
19.2%
8 523
15.7%
0 285
8.6%
9 167
 
5.0%
4 131
 
3.9%
6 109
 
3.3%
5 80
 
2.4%
2 73
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3358
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 660
19.7%
1 657
19.6%
3 639
19.0%
8 523
15.6%
0 285
8.5%
9 167
 
5.0%
4 131
 
3.9%
6 109
 
3.2%
5 80
 
2.4%
2 73
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 660
19.7%
1 657
19.6%
3 639
19.0%
8 523
15.6%
0 285
8.5%
9 167
 
5.0%
4 131
 
3.9%
6 109
 
3.2%
5 80
 
2.4%
2 73
 
2.2%
Distinct542
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-05-11T15:34:05.484764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length26.65343
Min length18

Characters and Unicode

Total characters14766
Distinct characters200
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique531 ?
Unique (%)95.8%

Sample

1st row서울특별시 서초구 방배동 773-6
2nd row서울특별시 서초구 방배동 431-26번지
3rd row서울특별시 서초구 방배동 487-1번지
4th row서울특별시 서초구 방배동 454-19번지
5th row서울특별시 서초구 방배동 966-41번지
ValueCountFrequency (%)
서울특별시 554
19.6%
서초구 554
19.6%
방배동 174
 
6.2%
서초동 157
 
5.6%
1층 127
 
4.5%
반포동 98
 
3.5%
양재동 61
 
2.2%
잠원동 40
 
1.4%
103호 23
 
0.8%
102호 20
 
0.7%
Other values (751) 1015
36.0%
2024-05-11T15:34:06.236451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2660
18.0%
1291
 
8.7%
1 867
 
5.9%
732
 
5.0%
589
 
4.0%
556
 
3.8%
555
 
3.8%
554
 
3.8%
554
 
3.8%
554
 
3.8%
Other values (190) 5854
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8226
55.7%
Decimal Number 3241
 
21.9%
Space Separator 2660
 
18.0%
Dash Punctuation 489
 
3.3%
Uppercase Letter 48
 
0.3%
Close Punctuation 40
 
0.3%
Open Punctuation 40
 
0.3%
Other Punctuation 18
 
0.1%
Math Symbol 1
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1291
15.7%
732
 
8.9%
589
 
7.2%
556
 
6.8%
555
 
6.7%
554
 
6.7%
554
 
6.7%
554
 
6.7%
419
 
5.1%
363
 
4.4%
Other values (158) 2059
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 21
43.8%
A 6
 
12.5%
K 5
 
10.4%
D 2
 
4.2%
L 2
 
4.2%
E 2
 
4.2%
T 2
 
4.2%
I 2
 
4.2%
P 2
 
4.2%
R 2
 
4.2%
Other values (2) 2
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 867
26.8%
2 395
12.2%
0 337
 
10.4%
3 327
 
10.1%
7 243
 
7.5%
4 241
 
7.4%
8 225
 
6.9%
5 223
 
6.9%
6 219
 
6.8%
9 164
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 16
88.9%
. 2
 
11.1%
Space Separator
ValueCountFrequency (%)
2660
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8226
55.7%
Common 6491
44.0%
Latin 49
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1291
15.7%
732
 
8.9%
589
 
7.2%
556
 
6.8%
555
 
6.7%
554
 
6.7%
554
 
6.7%
554
 
6.7%
419
 
5.1%
363
 
4.4%
Other values (158) 2059
25.0%
Common
ValueCountFrequency (%)
2660
41.0%
1 867
 
13.4%
- 489
 
7.5%
2 395
 
6.1%
0 337
 
5.2%
3 327
 
5.0%
7 243
 
3.7%
4 241
 
3.7%
8 225
 
3.5%
5 223
 
3.4%
Other values (9) 484
 
7.5%
Latin
ValueCountFrequency (%)
B 21
42.9%
A 6
 
12.2%
K 5
 
10.2%
D 2
 
4.1%
L 2
 
4.1%
E 2
 
4.1%
T 2
 
4.1%
I 2
 
4.1%
P 2
 
4.1%
R 2
 
4.1%
Other values (3) 3
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8226
55.7%
ASCII 6537
44.3%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2660
40.7%
1 867
 
13.3%
- 489
 
7.5%
2 395
 
6.0%
0 337
 
5.2%
3 327
 
5.0%
7 243
 
3.7%
4 241
 
3.7%
8 225
 
3.4%
5 223
 
3.4%
Other values (19) 530
 
8.1%
Hangul
ValueCountFrequency (%)
1291
15.7%
732
 
8.9%
589
 
7.2%
556
 
6.8%
555
 
6.7%
554
 
6.7%
554
 
6.7%
554
 
6.7%
419
 
5.1%
363
 
4.4%
Other values (158) 2059
25.0%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct347
Distinct (%)97.5%
Missing198
Missing (%)35.7%
Memory size4.5 KiB
2024-05-11T15:34:06.718867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length32.912921
Min length22

Characters and Unicode

Total characters11717
Distinct characters228
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)94.9%

Sample

1st row서울특별시 서초구 방배로42길 24 (방배동)
2nd row서울특별시 서초구 방배중앙로 50, 1층 (방배동)
3rd row서울특별시 서초구 서초대로22길 27, 1층 103호 (방배동)
4th row서울특별시 서초구 청두곶길 22 (방배동)
5th row서울특별시 서초구 남부순환로287길 42-3 (방배동)
ValueCountFrequency (%)
서울특별시 356
 
16.1%
서초구 356
 
16.1%
1층 86
 
3.9%
방배동 84
 
3.8%
서초동 84
 
3.8%
반포동 39
 
1.8%
잠원동 25
 
1.1%
양재동 24
 
1.1%
103호 20
 
0.9%
102호 17
 
0.8%
Other values (603) 1115
50.5%
2024-05-11T15:34:07.344326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1850
 
15.8%
926
 
7.9%
557
 
4.8%
1 533
 
4.5%
398
 
3.4%
( 366
 
3.1%
) 366
 
3.1%
360
 
3.1%
357
 
3.0%
357
 
3.0%
Other values (218) 5647
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6749
57.6%
Decimal Number 1921
 
16.4%
Space Separator 1850
 
15.8%
Open Punctuation 366
 
3.1%
Close Punctuation 366
 
3.1%
Other Punctuation 353
 
3.0%
Dash Punctuation 63
 
0.5%
Uppercase Letter 47
 
0.4%
Modifier Symbol 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
926
 
13.7%
557
 
8.3%
398
 
5.9%
360
 
5.3%
357
 
5.3%
357
 
5.3%
356
 
5.3%
356
 
5.3%
332
 
4.9%
260
 
3.9%
Other values (187) 2490
36.9%
Uppercase Letter
ValueCountFrequency (%)
B 24
51.1%
A 5
 
10.6%
K 3
 
6.4%
E 2
 
4.3%
I 2
 
4.3%
P 2
 
4.3%
R 2
 
4.3%
D 1
 
2.1%
1
 
2.1%
G 1
 
2.1%
Other values (4) 4
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 533
27.7%
2 299
15.6%
0 202
 
10.5%
3 195
 
10.2%
4 163
 
8.5%
5 139
 
7.2%
7 116
 
6.0%
6 105
 
5.5%
8 85
 
4.4%
9 84
 
4.4%
Space Separator
ValueCountFrequency (%)
1850
100.0%
Open Punctuation
ValueCountFrequency (%)
( 366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 366
100.0%
Other Punctuation
ValueCountFrequency (%)
, 353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6749
57.6%
Common 4920
42.0%
Latin 48
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
926
 
13.7%
557
 
8.3%
398
 
5.9%
360
 
5.3%
357
 
5.3%
357
 
5.3%
356
 
5.3%
356
 
5.3%
332
 
4.9%
260
 
3.9%
Other values (187) 2490
36.9%
Common
ValueCountFrequency (%)
1850
37.6%
1 533
 
10.8%
( 366
 
7.4%
) 366
 
7.4%
, 353
 
7.2%
2 299
 
6.1%
0 202
 
4.1%
3 195
 
4.0%
4 163
 
3.3%
5 139
 
2.8%
Other values (6) 454
 
9.2%
Latin
ValueCountFrequency (%)
B 24
50.0%
A 5
 
10.4%
K 3
 
6.2%
E 2
 
4.2%
I 2
 
4.2%
P 2
 
4.2%
R 2
 
4.2%
D 1
 
2.1%
1
 
2.1%
G 1
 
2.1%
Other values (5) 5
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6749
57.6%
ASCII 4966
42.4%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1850
37.3%
1 533
 
10.7%
( 366
 
7.4%
) 366
 
7.4%
, 353
 
7.1%
2 299
 
6.0%
0 202
 
4.1%
3 195
 
3.9%
4 163
 
3.3%
5 139
 
2.8%
Other values (19) 500
 
10.1%
Hangul
ValueCountFrequency (%)
926
 
13.7%
557
 
8.3%
398
 
5.9%
360
 
5.3%
357
 
5.3%
357
 
5.3%
356
 
5.3%
356
 
5.3%
332
 
4.9%
260
 
3.9%
Other values (187) 2490
36.9%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct168
Distinct (%)48.4%
Missing207
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean6641.6311
Minimum6501
Maximum6803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:07.548799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6501
5-th percentile6515.6
Q16563
median6645
Q36709
95-th percentile6778.7
Maximum6803
Range302
Interquartile range (IQR)146

Descriptive statistics

Standard deviation84.407126
Coefficient of variation (CV)0.012708795
Kurtosis-1.1490759
Mean6641.6311
Median Absolute Deviation (MAD)73
Skewness0.090034802
Sum2304646
Variance7124.563
MonotonicityNot monotonic
2024-05-11T15:34:07.752653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6602 7
 
1.3%
6762 6
 
1.1%
6536 6
 
1.1%
6547 5
 
0.9%
6540 5
 
0.9%
6649 5
 
0.9%
6654 5
 
0.9%
6563 5
 
0.9%
6527 5
 
0.9%
6697 5
 
0.9%
Other values (158) 293
52.9%
(Missing) 207
37.4%
ValueCountFrequency (%)
6501 2
0.4%
6502 3
0.5%
6503 3
0.5%
6506 2
0.4%
6509 4
0.7%
6514 3
0.5%
6515 1
 
0.2%
6517 1
 
0.2%
6518 1
 
0.2%
6519 1
 
0.2%
ValueCountFrequency (%)
6803 1
 
0.2%
6802 1
 
0.2%
6800 1
 
0.2%
6798 1
 
0.2%
6793 1
 
0.2%
6789 1
 
0.2%
6788 1
 
0.2%
6786 4
0.7%
6785 1
 
0.2%
6784 1
 
0.2%
Distinct424
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-05-11T15:34:08.129346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length5.2292419
Min length2

Characters and Unicode

Total characters2897
Distinct characters297
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

Unique350 ?
Unique (%)63.2%

Sample

1st row방배사
2nd row백영세탁
3rd row에덴세탁
4th row한진세탁
5th row미광세탁
ValueCountFrequency (%)
세탁 25
 
3.9%
현대세탁 11
 
1.7%
현대세탁소 10
 
1.6%
세탁소 10
 
1.6%
크린토피아 8
 
1.2%
크리닝 8
 
1.2%
노블레스 6
 
0.9%
명품 6
 
0.9%
현대 6
 
0.9%
한강세탁소 6
 
0.9%
Other values (423) 544
85.0%
2024-05-11T15:34:08.791236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
363
 
12.5%
356
 
12.3%
168
 
5.8%
105
 
3.6%
86
 
3.0%
74
 
2.6%
55
 
1.9%
53
 
1.8%
51
 
1.8%
51
 
1.8%
Other values (287) 1535
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2767
95.5%
Space Separator 86
 
3.0%
Lowercase Letter 15
 
0.5%
Uppercase Letter 12
 
0.4%
Open Punctuation 5
 
0.2%
Close Punctuation 4
 
0.1%
Decimal Number 4
 
0.1%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
363
 
13.1%
356
 
12.9%
168
 
6.1%
105
 
3.8%
74
 
2.7%
55
 
2.0%
53
 
1.9%
51
 
1.8%
51
 
1.8%
46
 
1.7%
Other values (258) 1445
52.2%
Lowercase Letter
ValueCountFrequency (%)
y 3
20.0%
v 2
13.3%
n 2
13.3%
e 2
13.3%
i 1
 
6.7%
r 1
 
6.7%
d 1
 
6.7%
u 1
 
6.7%
a 1
 
6.7%
s 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
G 2
16.7%
L 2
16.7%
S 1
8.3%
Y 1
8.3%
U 1
8.3%
C 1
8.3%
P 1
8.3%
H 1
8.3%
W 1
8.3%
J 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
4 1
25.0%
Other Punctuation
ValueCountFrequency (%)
? 2
66.7%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2767
95.5%
Common 103
 
3.6%
Latin 27
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
363
 
13.1%
356
 
12.9%
168
 
6.1%
105
 
3.8%
74
 
2.7%
55
 
2.0%
53
 
1.9%
51
 
1.8%
51
 
1.8%
46
 
1.7%
Other values (258) 1445
52.2%
Latin
ValueCountFrequency (%)
y 3
 
11.1%
v 2
 
7.4%
n 2
 
7.4%
G 2
 
7.4%
L 2
 
7.4%
e 2
 
7.4%
S 1
 
3.7%
i 1
 
3.7%
r 1
 
3.7%
d 1
 
3.7%
Other values (10) 10
37.0%
Common
ValueCountFrequency (%)
86
83.5%
( 5
 
4.9%
) 4
 
3.9%
2 2
 
1.9%
? 2
 
1.9%
1 1
 
1.0%
4 1
 
1.0%
- 1
 
1.0%
' 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2767
95.5%
ASCII 130
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
363
 
13.1%
356
 
12.9%
168
 
6.1%
105
 
3.8%
74
 
2.7%
55
 
2.0%
53
 
1.9%
51
 
1.8%
51
 
1.8%
46
 
1.7%
Other values (258) 1445
52.2%
ASCII
ValueCountFrequency (%)
86
66.2%
( 5
 
3.8%
) 4
 
3.1%
y 3
 
2.3%
2 2
 
1.5%
v 2
 
1.5%
? 2
 
1.5%
n 2
 
1.5%
G 2
 
1.5%
L 2
 
1.5%
Other values (19) 20
 
15.4%
Distinct453
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2000-01-25 00:00:00
Maximum2024-04-04 14:49:57
2024-05-11T15:34:09.041357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:34:09.289107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
I
339 
U
215 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 339
61.2%
U 215
38.8%

Length

2024-05-11T15:34:09.492726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:09.632688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 339
61.2%
u 215
38.8%
Distinct136
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-05-11T15:34:09.843457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:34:10.153191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
일반세탁업
545 
빨래방업
 
5
세탁업 기타
 
2
운동화전문세탁업
 
2

Length

Max length8
Median length5
Mean length5.0054152
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 545
98.4%
빨래방업 5
 
0.9%
세탁업 기타 2
 
0.4%
운동화전문세탁업 2
 
0.4%

Length

2024-05-11T15:34:10.451212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:10.660693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 545
98.0%
빨래방업 5
 
0.9%
세탁업 2
 
0.4%
기타 2
 
0.4%
운동화전문세탁업 2
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct409
Distinct (%)77.8%
Missing28
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean200890.35
Minimum198389.02
Maximum208126.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:10.890099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198389.02
5-th percentile198604.38
Q1199390.78
median201034.4
Q3201861.13
95-th percentile203794.64
Maximum208126.42
Range9737.3989
Interquartile range (IQR)2470.3518

Descriptive statistics

Standard deviation1637.4535
Coefficient of variation (CV)0.0081509814
Kurtosis-0.018309959
Mean200890.35
Median Absolute Deviation (MAD)1210.979
Skewness0.43564173
Sum1.0566832 × 108
Variance2681253.9
MonotonicityNot monotonic
2024-05-11T15:34:11.142583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202245.377899369 6
 
1.1%
201472.668856726 6
 
1.1%
199448.513021585 6
 
1.1%
200010.868613477 5
 
0.9%
200800.417027918 4
 
0.7%
201945.128259 4
 
0.7%
200005.626362552 4
 
0.7%
200706.565400409 4
 
0.7%
201648.514021987 3
 
0.5%
203977.433862613 3
 
0.5%
Other values (399) 481
86.8%
(Missing) 28
 
5.1%
ValueCountFrequency (%)
198389.022273532 1
 
0.2%
198432.354182494 3
0.5%
198468.076641337 1
 
0.2%
198487.574139642 1
 
0.2%
198498.060625675 1
 
0.2%
198502.492194238 1
 
0.2%
198506.458385404 1
 
0.2%
198507.549345185 1
 
0.2%
198507.645953028 1
 
0.2%
198512.866027886 1
 
0.2%
ValueCountFrequency (%)
208126.421170058 1
 
0.2%
206527.143128753 1
 
0.2%
205634.311119598 1
 
0.2%
204921.170288976 1
 
0.2%
204819.172335192 1
 
0.2%
204442.386253547 1
 
0.2%
204428.320643004 1
 
0.2%
204021.6 1
 
0.2%
203987.77391572 1
 
0.2%
203977.433862613 3
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct409
Distinct (%)77.8%
Missing28
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean443073.76
Minimum438685.13
Maximum446565.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:11.468765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438685.13
5-th percentile440820.13
Q1442169.8
median442923.48
Q3444193.27
95-th percentile445455.08
Maximum446565.03
Range7879.902
Interquartile range (IQR)2023.4704

Descriptive statistics

Standard deviation1434.1919
Coefficient of variation (CV)0.0032369145
Kurtosis-0.13086149
Mean443073.76
Median Absolute Deviation (MAD)928.73181
Skewness-0.014952674
Sum2.330568 × 108
Variance2056906.4
MonotonicityNot monotonic
2024-05-11T15:34:11.802119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442987.986999742 6
 
1.1%
444193.267014675 6
 
1.1%
444800.550772527 6
 
1.1%
441810.188560916 5
 
0.9%
444989.874340522 4
 
0.7%
444423.971934 4
 
0.7%
444680.521703344 4
 
0.7%
444349.181060423 4
 
0.7%
445084.627505619 3
 
0.5%
441126.798408487 3
 
0.5%
Other values (399) 481
86.8%
(Missing) 28
 
5.1%
ValueCountFrequency (%)
438685.126668674 1
0.2%
438769.485852873 1
0.2%
438918.090853339 1
0.2%
439131.445623862 1
0.2%
439470.889363188 1
0.2%
439588.856362211 1
0.2%
439673.170422023 1
0.2%
439881.740443559 1
0.2%
439961.430440504 2
0.4%
439988.378011805 1
0.2%
ValueCountFrequency (%)
446565.028672992 3
0.5%
446247.719636035 1
 
0.2%
446115.079072598 1
 
0.2%
445993.159516362 1
 
0.2%
445992.459343379 2
0.4%
445971.21278915 1
 
0.2%
445884.973 1
 
0.2%
445836.03987153 1
 
0.2%
445824.056378303 1
 
0.2%
445792.191399183 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
일반세탁업
477 
<NA>
70 
빨래방업
 
3
세탁업 기타
 
2
운동화전문세탁업
 
2

Length

Max length8
Median length5
Mean length4.8826715
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 477
86.1%
<NA> 70
 
12.6%
빨래방업 3
 
0.5%
세탁업 기타 2
 
0.4%
운동화전문세탁업 2
 
0.4%

Length

2024-05-11T15:34:12.129060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:12.390168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 477
85.8%
na 70
 
12.6%
빨래방업 3
 
0.5%
세탁업 2
 
0.4%
기타 2
 
0.4%
운동화전문세탁업 2
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)3.0%
Missing225
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean0.58358663
Minimum0
Maximum25
Zeros292
Zeros (%)52.7%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:12.573374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum25
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4754597
Coefficient of variation (CV)4.2418033
Kurtosis56.438512
Mean0.58358663
Median Absolute Deviation (MAD)0
Skewness6.9758395
Sum192
Variance6.1279005
MonotonicityNot monotonic
2024-05-11T15:34:12.819622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 292
52.7%
5 9
 
1.6%
2 7
 
1.3%
3 7
 
1.3%
4 7
 
1.3%
1 3
 
0.5%
21 1
 
0.2%
25 1
 
0.2%
15 1
 
0.2%
20 1
 
0.2%
(Missing) 225
40.6%
ValueCountFrequency (%)
0 292
52.7%
1 3
 
0.5%
2 7
 
1.3%
3 7
 
1.3%
4 7
 
1.3%
5 9
 
1.6%
15 1
 
0.2%
20 1
 
0.2%
21 1
 
0.2%
25 1
 
0.2%
ValueCountFrequency (%)
25 1
 
0.2%
21 1
 
0.2%
20 1
 
0.2%
15 1
 
0.2%
5 9
 
1.6%
4 7
 
1.3%
3 7
 
1.3%
2 7
 
1.3%
1 3
 
0.5%
0 292
52.7%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.8%
Missing225
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean0.17629179
Minimum0
Maximum7
Zeros295
Zeros (%)53.2%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:13.026684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.75662738
Coefficient of variation (CV)4.2919036
Kurtosis54.516727
Mean0.17629179
Median Absolute Deviation (MAD)0
Skewness6.9178771
Sum58
Variance0.57248499
MonotonicityNot monotonic
2024-05-11T15:34:13.233773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 295
53.2%
1 27
 
4.9%
2 3
 
0.5%
7 2
 
0.4%
6 1
 
0.2%
5 1
 
0.2%
(Missing) 225
40.6%
ValueCountFrequency (%)
0 295
53.2%
1 27
 
4.9%
2 3
 
0.5%
5 1
 
0.2%
6 1
 
0.2%
7 2
 
0.4%
ValueCountFrequency (%)
7 2
 
0.4%
6 1
 
0.2%
5 1
 
0.2%
2 3
 
0.5%
1 27
 
4.9%
0 295
53.2%
Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
213 
0
154 
1
153 
2
34 

Length

Max length4
Median length1
Mean length2.1534296
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 213
38.4%
0 154
27.8%
1 153
27.6%
2 34
 
6.1%

Length

2024-05-11T15:34:13.581605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:13.843415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 213
38.4%
0 154
27.8%
1 153
27.6%
2 34
 
6.1%
Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
324 
1
152 
0
43 
2
35 

Length

Max length4
Median length4
Mean length2.7545126
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> 324
58.5%
1 152
27.4%
0 43
 
7.8%
2 35
 
6.3%

Length

2024-05-11T15:34:14.234352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:14.457461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 324
58.5%
1 152
27.4%
0 43
 
7.8%
2 35
 
6.3%
Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
320 
0
202 
1
 
30
4
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.732852
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 320
57.8%
0 202
36.5%
1 30
 
5.4%
4 1
 
0.2%
2 1
 
0.2%

Length

2024-05-11T15:34:14.713620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:14.972855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 320
57.8%
0 202
36.5%
1 30
 
5.4%
4 1
 
0.2%
2 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
431 
0
91 
1
 
30
4
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.333935
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 431
77.8%
0 91
 
16.4%
1 30
 
5.4%
4 1
 
0.2%
2 1
 
0.2%

Length

2024-05-11T15:34:15.278569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:15.582468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 431
77.8%
0 91
 
16.4%
1 30
 
5.4%
4 1
 
0.2%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
0
322 
<NA>
232 

Length

Max length4
Median length1
Mean length2.2563177
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 322
58.1%
<NA> 232
41.9%

Length

2024-05-11T15:34:15.869385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:16.146715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 322
58.1%
na 232
41.9%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
0
322 
<NA>
232 

Length

Max length4
Median length1
Mean length2.2563177
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 322
58.1%
<NA> 232
41.9%

Length

2024-05-11T15:34:16.482477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:16.762687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 322
58.1%
na 232
41.9%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
0
322 
<NA>
232 

Length

Max length4
Median length1
Mean length2.2563177
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 322
58.1%
<NA> 232
41.9%

Length

2024-05-11T15:34:17.619008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:17.940296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 322
58.1%
na 232
41.9%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing83
Missing (%)15.0%
Memory size1.2 KiB
False
471 
(Missing)
83 
ValueCountFrequency (%)
False 471
85.0%
(Missing) 83
 
15.0%
2024-05-11T15:34:18.104801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
0
318 
<NA>
236 

Length

Max length4
Median length1
Mean length2.2779783
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 318
57.4%
<NA> 236
42.6%

Length

2024-05-11T15:34:18.317314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:18.512543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 318
57.4%
na 236
42.6%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing554
Missing (%)100.0%
Memory size5.0 KiB
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
402 
임대
145 
자가
 
7

Length

Max length4
Median length4
Mean length3.4512635
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> 402
72.6%
임대 145
 
26.2%
자가 7
 
1.3%

Length

2024-05-11T15:34:18.795851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:19.011606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
72.6%
임대 145
 
26.2%
자가 7
 
1.3%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.0%
Missing331
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean1.8340807
Minimum0
Maximum8
Zeros51
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T15:34:19.175843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4.9
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5695024
Coefficient of variation (CV)0.85574336
Kurtosis2.0483583
Mean1.8340807
Median Absolute Deviation (MAD)1
Skewness1.1594413
Sum409
Variance2.4633378
MonotonicityNot monotonic
2024-05-11T15:34:19.420543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 65
 
11.7%
0 51
 
9.2%
1 45
 
8.1%
3 41
 
7.4%
4 9
 
1.6%
6 4
 
0.7%
7 4
 
0.7%
5 3
 
0.5%
8 1
 
0.2%
(Missing) 331
59.7%
ValueCountFrequency (%)
0 51
9.2%
1 45
8.1%
2 65
11.7%
3 41
7.4%
4 9
 
1.6%
5 3
 
0.5%
6 4
 
0.7%
7 4
 
0.7%
8 1
 
0.2%
ValueCountFrequency (%)
8 1
 
0.2%
7 4
 
0.7%
6 4
 
0.7%
5 3
 
0.5%
4 9
 
1.6%
3 41
7.4%
2 65
11.7%
1 45
8.1%
0 51
9.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
499 
0
55 

Length

Max length4
Median length4
Mean length3.7021661
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> 499
90.1%
0 55
 
9.9%

Length

2024-05-11T15:34:19.731416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:19.945512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 499
90.1%
0 55
 
9.9%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
499 
0
55 

Length

Max length4
Median length4
Mean length3.7021661
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> 499
90.1%
0 55
 
9.9%

Length

2024-05-11T15:34:20.178050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:20.370666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 499
90.1%
0 55
 
9.9%

회수건조수
Categorical

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
372 
0
103 
1
75 
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.0144404
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> 372
67.1%
0 103
 
18.6%
1 75
 
13.5%
2 3
 
0.5%
3 1
 
0.2%

Length

2024-05-11T15:34:20.568939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:20.803100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 372
67.1%
0 103
 
18.6%
1 75
 
13.5%
2 3
 
0.5%
3 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
376 
0
178 

Length

Max length4
Median length4
Mean length3.0361011
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> 376
67.9%
0 178
32.1%

Length

2024-05-11T15:34:21.050157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:21.310718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 376
67.9%
0 178
32.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing70
Missing (%)12.6%
Memory size1.2 KiB
False
483 
True
 
1
(Missing)
70 
ValueCountFrequency (%)
False 483
87.2%
True 1
 
0.2%
(Missing) 70
 
12.6%
2024-05-11T15:34:21.451915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032100003210000-205-1965-000011965-12-20<NA>3폐업2폐업2023-04-17<NA><NA><NA>02 59119660.00137-829서울특별시 서초구 방배동 773-6서울특별시 서초구 방배로42길 24 (방배동)6584방배사2023-04-17 19:31:42U2022-12-03 23:09:00.0일반세탁업199025.213767443620.01254<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132100003210000-205-1987-0169919870723<NA>3폐업2폐업20030404<NA><NA><NA>02 5835203.00137817서울특별시 서초구 방배동 431-26번지<NA><NA>백영세탁2003-05-09 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
232100003210000-205-1987-0170219870921<NA>3폐업2폐업19981125<NA><NA><NA>02 5856250.00137060서울특별시 서초구 방배동 487-1번지<NA><NA>에덴세탁2001-09-29 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
332100003210000-205-1987-0170519871103<NA>3폐업2폐업20100406<NA><NA><NA>0205838164.00137818서울특별시 서초구 방배동 454-19번지<NA><NA>한진세탁2003-05-22 00:00:00I2018-08-31 23:59:59.0일반세탁업198487.57414441917.818548일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432100003210000-205-1987-0170919871204<NA>3폐업2폐업19980318<NA><NA><NA>02 0.00137846서울특별시 서초구 방배동 966-41번지<NA><NA>미광세탁2001-09-29 00:00:00I2018-08-31 23:59:59.0일반세탁업199037.800578442347.39707일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532100003210000-205-1987-017101987-12-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 583044523.00137-844서울특별시 서초구 방배동 931-27서울특별시 서초구 방배중앙로 50, 1층 (방배동)6680한미세탁소2023-12-28 15:15:18U2022-11-01 21:00:00.0일반세탁업199153.995099442452.139332<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632100003210000-205-1987-0172019870921<NA>3폐업2폐업19951020<NA><NA><NA>02 5902717.00137837서울특별시 서초구 방배동 850-32번지<NA><NA>금강세탁2001-09-29 00:00:00I2018-08-31 23:59:59.0일반세탁업199391.448911443026.487622일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732100003210000-205-1987-0172419870921<NA>3폐업2폐업20200319<NA><NA><NA>020583956727.25137844서울특별시 서초구 방배동 935-1번지 103호서울특별시 서초구 서초대로22길 27, 1층 103호 (방배동)6672영화세탁2020-03-19 15:26:19U2020-03-21 02:40:00.0일반세탁업199327.100924442652.527175일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832100003210000-205-1987-017261987-09-21<NA>3폐업2폐업2023-10-06<NA><NA><NA>02058425750.00137-819서울특별시 서초구 방배동 469-1서울특별시 서초구 청두곶길 22 (방배동)6690남양세탁2023-10-06 15:29:37U2022-10-31 00:08:00.0일반세탁업198640.182352441820.46638<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
932100003210000-205-1987-0172719870921<NA>3폐업2폐업19980212<NA><NA><NA>02 5933258.00137834서울특별시 서초구 방배동 828-30번지<NA><NA>삼성세탁2001-09-29 00:00:00I2018-08-31 23:59:59.0일반세탁업198752.540348442860.797156일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
54432100003210000-205-2022-0000320221107<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.45137873서울특별시 서초구 서초동 1550-15 리우빌딩서울특별시 서초구 반포대로26길 15, 1층 (서초동)6648뷔뷔스 런드리(vyvy's 런드리)2022-11-07 15:46:26I2021-11-01 00:09:00.0일반세탁업200818.310098443134.369185<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54532100003210000-205-2022-0000420221226<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.02137859서울특별시 서초구 서초동 1335 207호서울특별시 서초구 효령로 403, 그랑몰 207호 (서초동)6630알파명품크리닝2022-12-26 13:53:50I2021-11-01 22:08:00.0일반세탁업202245.377899442987.987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54632100003210000-205-2022-0000520221230<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.94137963서울특별시 서초구 서초동 1593-7 서초이오빌서울특별시 서초구 효령로53길 45, 지하1층 B103호 (서초동, 서초이오빌)6652센트럴세탁소2022-12-30 10:27:01I2022-12-01 00:01:00.0일반세탁업201070.374374442706.851935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54732100003210000-205-2023-000012023-05-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.36137-070서울특별시 서초구 서초동 1757-1서울특별시 서초구 효령로 403, 1층 131호 (서초동)6630자이명품세탁2023-11-08 14:10:57U2022-10-31 23:01:00.0일반세탁업202245.377899442987.987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54832100003210000-205-2023-000022023-07-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.30137-070서울특별시 서초구 서초동 1757 서초그랑자이서울특별시 서초구 효령로 391, 1동 1층 125호 (서초동, 서초그랑자이)6630크린화이트2023-07-17 16:02:49I2022-12-06 23:09:00.0일반세탁업202245.377899442987.987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54932100003210000-205-2023-000032023-07-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.50137-865서울특별시 서초구 서초동 1436-1 현대상가(서쪽단지) 1층 102호서울특별시 서초구 효령로68길 9-2, 현대상가(서쪽단지) 1층 102호 (서초동)6723현대세탁소2023-07-26 13:29:14I2022-12-06 22:08:00.0일반세탁업202044.926542442642.000688<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55032100003210000-205-2023-000042023-08-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>128.56137-180서울특별시 서초구 내곡동 1-1459<NA><NA>와이크리닝(Y-크리닝)2023-08-16 11:29:38I2022-12-07 23:08:00.0일반세탁업206527.143129440277.374862<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55132100003210000-205-2023-000052023-09-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.00137-040서울특별시 서초구 반포동 0 원베일리 스퀘어서울특별시 서초구 반포대로 291, 원베일리 스퀘어 B105호 (반포동)6506원베일리 참좋은세탁소2023-09-15 12:28:52I2022-12-08 23:07:00.0일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55232100003210000-205-2023-000062023-10-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.80137-040서울특별시 서초구 반포동 0 원베일리 스퀘어서울특별시 서초구 반포대로 291, 원베일리 스퀘어 B1층 B144호, B145호 (반포동)6506원베일리 그레이스 세탁2023-11-28 15:18:04U2022-10-31 21:00:00.0일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55332100003210000-205-2023-000072023-04-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.34137-853서울특별시 서초구 방배동 2762-22 리츠하우스 지하1층 B01호서울특별시 서초구 전원말6길 2, 지하1층 B01호 (방배동, 리츠하우스)6761유일세탁소2024-02-01 10:48:53I2023-12-02 00:03:00.0일반세탁업199012.155193440442.34304<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>