Overview

Dataset statistics

Number of variables47
Number of observations635
Missing cells6690
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory250.7 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-17958/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (85.3%)Imbalance
위생업태명 is highly imbalanced (78.1%)Imbalance
사용끝지하층 is highly imbalanced (85.8%)Imbalance
건물소유구분명 is highly imbalanced (72.5%)Imbalance
여성종사자수 is highly imbalanced (78.5%)Imbalance
남성종사자수 is highly imbalanced (77.3%)Imbalance
회수건조수 is highly imbalanced (70.7%)Imbalance
인허가취소일자 has 635 (100.0%) missing valuesMissing
폐업일자 has 149 (23.5%) missing valuesMissing
휴업시작일자 has 635 (100.0%) missing valuesMissing
휴업종료일자 has 635 (100.0%) missing valuesMissing
재개업일자 has 635 (100.0%) missing valuesMissing
전화번호 has 46 (7.2%) missing valuesMissing
도로명주소 has 322 (50.7%) missing valuesMissing
도로명우편번호 has 328 (51.7%) missing valuesMissing
좌표정보(X) has 30 (4.7%) missing valuesMissing
좌표정보(Y) has 30 (4.7%) missing valuesMissing
건물지상층수 has 195 (30.7%) missing valuesMissing
사용끝지상층 has 550 (86.6%) missing valuesMissing
발한실여부 has 33 (5.2%) missing valuesMissing
조건부허가신고사유 has 635 (100.0%) missing valuesMissing
조건부허가시작일자 has 635 (100.0%) missing valuesMissing
조건부허가종료일자 has 635 (100.0%) missing valuesMissing
세탁기수 has 536 (84.4%) missing valuesMissing
다중이용업소여부 has 24 (3.8%) 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 398 (62.7%) zerosZeros
사용끝지상층 has 10 (1.6%) zerosZeros
세탁기수 has 17 (2.7%) zerosZeros

Reproduction

Analysis started2024-05-11 08:06:17.121522
Analysis finished2024-05-11 08:06:17.996683
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3060000
635 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 635
100.0%

Length

2024-05-11T17:06:18.071587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:18.178544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 635
100.0%

관리번호
Text

UNIQUE 

Distinct635
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T17:06:18.356842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13970
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

Unique635 ?
Unique (%)100.0%

Sample

1st row3060000-205-1987-01967
2nd row3060000-205-1987-01968
3rd row3060000-205-1987-01969
4th row3060000-205-1987-01970
5th row3060000-205-1987-01971
ValueCountFrequency (%)
3060000-205-1987-01967 1
 
0.2%
3060000-205-1998-02373 1
 
0.2%
3060000-205-1998-02375 1
 
0.2%
3060000-205-1997-02366 1
 
0.2%
3060000-205-1997-02367 1
 
0.2%
3060000-205-1997-02368 1
 
0.2%
3060000-205-1997-02369 1
 
0.2%
3060000-205-1998-02370 1
 
0.2%
3060000-205-1998-02372 1
 
0.2%
3060000-205-1997-02363 1
 
0.2%
Other values (625) 625
98.4%
2024-05-11T17:06:18.677991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5523
39.5%
- 1905
 
13.6%
2 1529
 
10.9%
3 899
 
6.4%
9 846
 
6.1%
1 816
 
5.8%
6 795
 
5.7%
5 765
 
5.5%
8 421
 
3.0%
7 288
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12065
86.4%
Dash Punctuation 1905
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5523
45.8%
2 1529
 
12.7%
3 899
 
7.5%
9 846
 
7.0%
1 816
 
6.8%
6 795
 
6.6%
5 765
 
6.3%
8 421
 
3.5%
7 288
 
2.4%
4 183
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 1905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13970
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5523
39.5%
- 1905
 
13.6%
2 1529
 
10.9%
3 899
 
6.4%
9 846
 
6.1%
1 816
 
5.8%
6 795
 
5.7%
5 765
 
5.5%
8 421
 
3.0%
7 288
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5523
39.5%
- 1905
 
13.6%
2 1529
 
10.9%
3 899
 
6.4%
9 846
 
6.1%
1 816
 
5.8%
6 795
 
5.7%
5 765
 
5.5%
8 421
 
3.0%
7 288
 
2.1%
Distinct425
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1987-07-09 00:00:00
Maximum2022-08-25 00:00:00
2024-05-11T17:06:18.819756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:06:18.985721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3
486 
1
149 

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 (%)
3 486
76.5%
1 149
 
23.5%

Length

2024-05-11T17:06:19.116907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:19.207309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 486
76.5%
1 149
 
23.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
486 
영업/정상
149 

Length

Max length5
Median length2
Mean length2.703937
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 486
76.5%
영업/정상 149
 
23.5%

Length

2024-05-11T17:06:19.308295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:19.412868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 486
76.5%
영업/정상 149
 
23.5%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2
486 
1
149 

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 (%)
2 486
76.5%
1 149
 
23.5%

Length

2024-05-11T17:06:19.518422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:19.620600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 486
76.5%
1 149
 
23.5%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
486 
영업
149 

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 486
76.5%
영업 149
 
23.5%

Length

2024-05-11T17:06:19.730510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:19.832188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 486
76.5%
영업 149
 
23.5%

폐업일자
Date

MISSING 

Distinct430
Distinct (%)88.5%
Missing149
Missing (%)23.5%
Memory size5.1 KiB
Minimum1993-02-11 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T17:06:19.947180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:06:20.317327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

전화번호
Text

MISSING 

Distinct565
Distinct (%)95.9%
Missing46
Missing (%)7.2%
Memory size5.1 KiB
2024-05-11T17:06:20.541315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9881154
Min length2

Characters and Unicode

Total characters5883
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

Unique542 ?
Unique (%)92.0%

Sample

1st row02432 9605
2nd row0204358073
3rd row0204923557
4th row0204924013
5th row0204935139
ValueCountFrequency (%)
02 246
28.1%
02435 4
 
0.5%
0234215566 3
 
0.3%
02439 3
 
0.3%
437 3
 
0.3%
02436 3
 
0.3%
4941230 2
 
0.2%
02978 2
 
0.2%
02491 2
 
0.2%
4956872 2
 
0.2%
Other values (584) 604
69.1%
2024-05-11T17:06:20.906584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1148
19.5%
2 970
16.5%
4 788
13.4%
3 611
10.4%
9 532
9.0%
5 342
 
5.8%
7 328
 
5.6%
308
 
5.2%
6 297
 
5.0%
8 285
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5575
94.8%
Space Separator 308
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1148
20.6%
2 970
17.4%
4 788
14.1%
3 611
11.0%
9 532
9.5%
5 342
 
6.1%
7 328
 
5.9%
6 297
 
5.3%
8 285
 
5.1%
1 274
 
4.9%
Space Separator
ValueCountFrequency (%)
308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5883
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1148
19.5%
2 970
16.5%
4 788
13.4%
3 611
10.4%
9 532
9.0%
5 342
 
5.8%
7 328
 
5.6%
308
 
5.2%
6 297
 
5.0%
8 285
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5883
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1148
19.5%
2 970
16.5%
4 788
13.4%
3 611
10.4%
9 532
9.0%
5 342
 
5.8%
7 328
 
5.6%
308
 
5.2%
6 297
 
5.0%
8 285
 
4.8%
Distinct317
Distinct (%)49.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T17:06:21.347891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0094488
Min length3

Characters and Unicode

Total characters3181
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

Unique267 ?
Unique (%)42.0%

Sample

1st row33.30
2nd row33.00
3rd row23.10
4th row16.50
5th row19.80
ValueCountFrequency (%)
23.10 51
 
8.0%
33.00 48
 
7.6%
26.40 42
 
6.6%
00 38
 
6.0%
16.50 25
 
3.9%
19.80 18
 
2.8%
39.60 15
 
2.4%
29.70 10
 
1.6%
30.00 7
 
1.1%
13.20 6
 
0.9%
Other values (307) 375
59.1%
2024-05-11T17:06:21.875548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 635
20.0%
0 634
19.9%
2 336
10.6%
3 329
10.3%
1 314
9.9%
6 208
 
6.5%
4 197
 
6.2%
9 152
 
4.8%
8 143
 
4.5%
5 134
 
4.2%
Other values (2) 99
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2541
79.9%
Other Punctuation 640
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 634
25.0%
2 336
13.2%
3 329
12.9%
1 314
12.4%
6 208
 
8.2%
4 197
 
7.8%
9 152
 
6.0%
8 143
 
5.6%
5 134
 
5.3%
7 94
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 635
99.2%
, 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3181
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 635
20.0%
0 634
19.9%
2 336
10.6%
3 329
10.3%
1 314
9.9%
6 208
 
6.5%
4 197
 
6.2%
9 152
 
4.8%
8 143
 
4.5%
5 134
 
4.2%
Other values (2) 99
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 635
20.0%
0 634
19.9%
2 336
10.6%
3 329
10.3%
1 314
9.9%
6 208
 
6.5%
4 197
 
6.2%
9 152
 
4.8%
8 143
 
4.5%
5 134
 
4.2%
Other values (2) 99
 
3.1%
Distinct97
Distinct (%)15.3%
Missing1
Missing (%)0.2%
Memory size5.1 KiB
2024-05-11T17:06:22.131854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0268139
Min length6

Characters and Unicode

Total characters3821
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

Unique16 ?
Unique (%)2.5%

Sample

1st row131881
2nd row131881
3rd row131882
4th row131882
5th row131875
ValueCountFrequency (%)
131815 17
 
2.7%
131820 17
 
2.7%
131814 17
 
2.7%
131875 16
 
2.5%
131821 15
 
2.4%
131807 15
 
2.4%
131802 15
 
2.4%
131831 15
 
2.4%
131819 14
 
2.2%
131860 14
 
2.2%
Other values (87) 479
75.6%
2024-05-11T17:06:22.492579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1481
38.8%
3 741
19.4%
8 700
18.3%
2 184
 
4.8%
0 149
 
3.9%
7 148
 
3.9%
6 130
 
3.4%
5 126
 
3.3%
4 75
 
2.0%
9 70
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3804
99.6%
Dash Punctuation 17
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1481
38.9%
3 741
19.5%
8 700
18.4%
2 184
 
4.8%
0 149
 
3.9%
7 148
 
3.9%
6 130
 
3.4%
5 126
 
3.3%
4 75
 
2.0%
9 70
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3821
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1481
38.8%
3 741
19.4%
8 700
18.3%
2 184
 
4.8%
0 149
 
3.9%
7 148
 
3.9%
6 130
 
3.4%
5 126
 
3.3%
4 75
 
2.0%
9 70
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1481
38.8%
3 741
19.4%
8 700
18.3%
2 184
 
4.8%
0 149
 
3.9%
7 148
 
3.9%
6 130
 
3.4%
5 126
 
3.3%
4 75
 
2.0%
9 70
 
1.8%
Distinct592
Distinct (%)93.4%
Missing1
Missing (%)0.2%
Memory size5.1 KiB
2024-05-11T17:06:22.759966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length38
Mean length23.397476
Min length17

Characters and Unicode

Total characters14834
Distinct characters131
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

Unique553 ?
Unique (%)87.2%

Sample

1st row서울특별시 중랑구 중화동 304-39번지
2nd row서울특별시 중랑구 중화동 312-46번지
3rd row서울특별시 중랑구 중화동 331-38번지
4th row서울특별시 중랑구 중화동 308-104번지
5th row서울특별시 중랑구 중화동 274-49번지
ValueCountFrequency (%)
서울특별시 634
23.7%
중랑구 634
23.7%
면목동 273
 
10.2%
망우동 85
 
3.2%
묵동 78
 
2.9%
중화동 73
 
2.7%
상봉동 67
 
2.5%
신내동 58
 
2.2%
지상1층 10
 
0.4%
상가동 9
 
0.3%
Other values (667) 752
28.1%
2024-05-11T17:06:23.148427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2632
17.7%
712
 
4.8%
665
 
4.5%
638
 
4.3%
636
 
4.3%
635
 
4.3%
634
 
4.3%
634
 
4.3%
634
 
4.3%
634
 
4.3%
Other values (121) 6380
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8603
58.0%
Decimal Number 3008
 
20.3%
Space Separator 2632
 
17.7%
Dash Punctuation 569
 
3.8%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
712
 
8.3%
665
 
7.7%
638
 
7.4%
636
 
7.4%
635
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
590
 
6.9%
Other values (102) 2191
25.5%
Decimal Number
ValueCountFrequency (%)
1 589
19.6%
2 383
12.7%
3 348
11.6%
4 316
10.5%
0 282
9.4%
5 265
8.8%
6 249
8.3%
7 207
 
6.9%
8 185
 
6.2%
9 184
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
a 1
50.0%
Space Separator
ValueCountFrequency (%)
2632
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 569
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8603
58.0%
Common 6225
42.0%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
712
 
8.3%
665
 
7.7%
638
 
7.4%
636
 
7.4%
635
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
590
 
6.9%
Other values (102) 2191
25.5%
Common
ValueCountFrequency (%)
2632
42.3%
1 589
 
9.5%
- 569
 
9.1%
2 383
 
6.2%
3 348
 
5.6%
4 316
 
5.1%
0 282
 
4.5%
5 265
 
4.3%
6 249
 
4.0%
7 207
 
3.3%
Other values (6) 385
 
6.2%
Latin
ValueCountFrequency (%)
B 4
66.7%
s 1
 
16.7%
a 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8603
58.0%
ASCII 6231
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2632
42.2%
1 589
 
9.5%
- 569
 
9.1%
2 383
 
6.1%
3 348
 
5.6%
4 316
 
5.1%
0 282
 
4.5%
5 265
 
4.3%
6 249
 
4.0%
7 207
 
3.3%
Other values (9) 391
 
6.3%
Hangul
ValueCountFrequency (%)
712
 
8.3%
665
 
7.7%
638
 
7.4%
636
 
7.4%
635
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
634
 
7.4%
590
 
6.9%
Other values (102) 2191
25.5%

도로명주소
Text

MISSING 

Distinct310
Distinct (%)99.0%
Missing322
Missing (%)50.7%
Memory size5.1 KiB
2024-05-11T17:06:23.434720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length50
Mean length28.348243
Min length22

Characters and Unicode

Total characters8873
Distinct characters141
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

Unique307 ?
Unique (%)98.1%

Sample

1st row서울특별시 중랑구 동일로129길 44 (중화동)
2nd row서울특별시 중랑구 봉화산로 13 (중화동)
3rd row서울특별시 중랑구 중랑역로 111 (중화동)
4th row서울특별시 중랑구 동일로144가길 2 (중화동)
5th row서울특별시 중랑구 동일로130길 52 (중화동)
ValueCountFrequency (%)
서울특별시 313
18.3%
중랑구 313
18.3%
면목동 120
 
7.0%
묵동 39
 
2.3%
망우동 35
 
2.0%
중화동 34
 
2.0%
1층 33
 
1.9%
신내동 30
 
1.8%
상봉동 28
 
1.6%
상가동 18
 
1.1%
Other values (406) 747
43.7%
2024-05-11T17:06:23.846549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1397
 
15.7%
404
 
4.6%
381
 
4.3%
1 364
 
4.1%
331
 
3.7%
) 317
 
3.6%
( 317
 
3.6%
315
 
3.6%
315
 
3.6%
314
 
3.5%
Other values (131) 4418
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5282
59.5%
Decimal Number 1421
 
16.0%
Space Separator 1397
 
15.7%
Close Punctuation 317
 
3.6%
Open Punctuation 317
 
3.6%
Other Punctuation 121
 
1.4%
Dash Punctuation 13
 
0.1%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
404
 
7.6%
381
 
7.2%
331
 
6.3%
315
 
6.0%
315
 
6.0%
314
 
5.9%
314
 
5.9%
313
 
5.9%
313
 
5.9%
313
 
5.9%
Other values (112) 1969
37.3%
Decimal Number
ValueCountFrequency (%)
1 364
25.6%
2 179
12.6%
3 136
 
9.6%
0 127
 
8.9%
5 122
 
8.6%
4 120
 
8.4%
6 113
 
8.0%
9 99
 
7.0%
7 93
 
6.5%
8 68
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 120
99.2%
. 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1397
100.0%
Close Punctuation
ValueCountFrequency (%)
) 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5282
59.5%
Common 3586
40.4%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
404
 
7.6%
381
 
7.2%
331
 
6.3%
315
 
6.0%
315
 
6.0%
314
 
5.9%
314
 
5.9%
313
 
5.9%
313
 
5.9%
313
 
5.9%
Other values (112) 1969
37.3%
Common
ValueCountFrequency (%)
1397
39.0%
1 364
 
10.2%
) 317
 
8.8%
( 317
 
8.8%
2 179
 
5.0%
3 136
 
3.8%
0 127
 
3.5%
5 122
 
3.4%
4 120
 
3.3%
, 120
 
3.3%
Other values (6) 387
 
10.8%
Latin
ValueCountFrequency (%)
A 3
60.0%
B 1
 
20.0%
s 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5282
59.5%
ASCII 3591
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1397
38.9%
1 364
 
10.1%
) 317
 
8.8%
( 317
 
8.8%
2 179
 
5.0%
3 136
 
3.8%
0 127
 
3.5%
5 122
 
3.4%
4 120
 
3.3%
, 120
 
3.3%
Other values (9) 392
 
10.9%
Hangul
ValueCountFrequency (%)
404
 
7.6%
381
 
7.2%
331
 
6.3%
315
 
6.0%
315
 
6.0%
314
 
5.9%
314
 
5.9%
313
 
5.9%
313
 
5.9%
313
 
5.9%
Other values (112) 1969
37.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct176
Distinct (%)57.3%
Missing328
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean2131
Minimum2001
Maximum2259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:24.020807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2012.3
Q12058
median2136
Q32204
95-th percentile2248.4
Maximum2259
Range258
Interquartile range (IQR)146

Descriptive statistics

Standard deviation78.348893
Coefficient of variation (CV)0.036766257
Kurtosis-1.3154017
Mean2131
Median Absolute Deviation (MAD)72
Skewness-0.016658336
Sum654217
Variance6138.549
MonotonicityNot monotonic
2024-05-11T17:06:24.179438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2244 5
 
0.8%
2034 5
 
0.8%
2208 4
 
0.6%
2180 4
 
0.6%
2245 4
 
0.6%
2141 4
 
0.6%
2054 4
 
0.6%
2095 4
 
0.6%
2066 4
 
0.6%
2249 3
 
0.5%
Other values (166) 266
41.9%
(Missing) 328
51.7%
ValueCountFrequency (%)
2001 1
 
0.2%
2002 1
 
0.2%
2003 3
0.5%
2004 2
0.3%
2006 2
0.3%
2007 1
 
0.2%
2008 1
 
0.2%
2010 1
 
0.2%
2011 3
0.5%
2012 1
 
0.2%
ValueCountFrequency (%)
2259 2
0.3%
2257 1
 
0.2%
2256 1
 
0.2%
2255 3
0.5%
2253 3
0.5%
2252 3
0.5%
2249 3
0.5%
2247 1
 
0.2%
2246 1
 
0.2%
2245 4
0.6%
Distinct441
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T17:06:24.498761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length4.1291339
Min length2

Characters and Unicode

Total characters2622
Distinct characters278
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

Unique340 ?
Unique (%)53.5%

Sample

1st row매일사
2nd row원일사
3rd row정든사
4th row우리사
5th row광일사
ValueCountFrequency (%)
백양사 14
 
2.1%
중앙사 10
 
1.5%
제일사 10
 
1.5%
백조사 9
 
1.4%
현대사 7
 
1.1%
태양사 7
 
1.1%
일류사 5
 
0.8%
백성사 5
 
0.8%
대성사 5
 
0.8%
제일세탁소 5
 
0.8%
Other values (443) 585
88.4%
2024-05-11T17:06:24.933868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
312
 
11.9%
219
 
8.4%
217
 
8.3%
132
 
5.0%
71
 
2.7%
62
 
2.4%
51
 
1.9%
47
 
1.8%
39
 
1.5%
39
 
1.5%
Other values (268) 1433
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2545
97.1%
Lowercase Letter 28
 
1.1%
Space Separator 27
 
1.0%
Decimal Number 6
 
0.2%
Open Punctuation 5
 
0.2%
Close Punctuation 5
 
0.2%
Uppercase Letter 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
312
 
12.3%
219
 
8.6%
217
 
8.5%
132
 
5.2%
71
 
2.8%
62
 
2.4%
51
 
2.0%
47
 
1.8%
39
 
1.5%
39
 
1.5%
Other values (246) 1356
53.3%
Lowercase Letter
ValueCountFrequency (%)
a 7
25.0%
w 4
14.3%
h 4
14.3%
s 4
14.3%
n 3
10.7%
d 2
 
7.1%
y 1
 
3.6%
r 1
 
3.6%
e 1
 
3.6%
l 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 1
 
16.7%
4 1
 
16.7%
0 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
G 1
25.0%
D 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2545
97.1%
Common 45
 
1.7%
Latin 32
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
312
 
12.3%
219
 
8.6%
217
 
8.5%
132
 
5.2%
71
 
2.8%
62
 
2.4%
51
 
2.0%
47
 
1.8%
39
 
1.5%
39
 
1.5%
Other values (246) 1356
53.3%
Latin
ValueCountFrequency (%)
a 7
21.9%
w 4
12.5%
h 4
12.5%
s 4
12.5%
n 3
9.4%
d 2
 
6.2%
L 1
 
3.1%
G 1
 
3.1%
y 1
 
3.1%
r 1
 
3.1%
Other values (4) 4
12.5%
Common
ValueCountFrequency (%)
27
60.0%
( 5
 
11.1%
) 5
 
11.1%
2 3
 
6.7%
& 2
 
4.4%
1 1
 
2.2%
4 1
 
2.2%
0 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2545
97.1%
ASCII 77
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
312
 
12.3%
219
 
8.6%
217
 
8.5%
132
 
5.2%
71
 
2.8%
62
 
2.4%
51
 
2.0%
47
 
1.8%
39
 
1.5%
39
 
1.5%
Other values (246) 1356
53.3%
ASCII
ValueCountFrequency (%)
27
35.1%
a 7
 
9.1%
( 5
 
6.5%
) 5
 
6.5%
w 4
 
5.2%
h 4
 
5.2%
s 4
 
5.2%
2 3
 
3.9%
n 3
 
3.9%
d 2
 
2.6%
Other values (12) 13
16.9%
Distinct372
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1999-09-09 00:00:00
Maximum2024-05-07 15:16:37
2024-05-11T17:06:25.075494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:06:25.221174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
I
515 
U
120 

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 515
81.1%
U 120
 
18.9%

Length

2024-05-11T17:06:25.359784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:25.492176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 515
81.1%
u 120
 
18.9%
Distinct110
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T17:06:25.600326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:06:25.760406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
일반세탁업
614 
운동화전문세탁업
 
17
빨래방업
 
4

Length

Max length8
Median length5
Mean length5.0740157
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 614
96.7%
운동화전문세탁업 17
 
2.7%
빨래방업 4
 
0.6%

Length

2024-05-11T17:06:25.916439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:26.040352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 614
96.7%
운동화전문세탁업 17
 
2.7%
빨래방업 4
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct519
Distinct (%)85.8%
Missing30
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean207656.36
Minimum206274.55
Maximum210012.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:26.175284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206274.55
5-th percentile206560.65
Q1207071.39
median207571.41
Q3208240.54
95-th percentile208948.43
Maximum210012.43
Range3737.8798
Interquartile range (IQR)1169.1435

Descriptive statistics

Standard deviation767.34856
Coefficient of variation (CV)0.0036952808
Kurtosis-0.54809811
Mean207656.36
Median Absolute Deviation (MAD)572.36962
Skewness0.39960588
Sum1.256321 × 108
Variance588823.82
MonotonicityNot monotonic
2024-05-11T17:06:26.310760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208536.163679365 4
 
0.6%
208294.257367707 4
 
0.6%
207163.791145804 4
 
0.6%
208283.548205106 4
 
0.6%
208294.31154469 4
 
0.6%
207310.971185677 4
 
0.6%
206434.297984115 3
 
0.5%
208712.166756703 3
 
0.5%
207718.222107219 3
 
0.5%
207966.140189875 3
 
0.5%
Other values (509) 569
89.6%
(Missing) 30
 
4.7%
ValueCountFrequency (%)
206274.552791693 1
0.2%
206284.507804641 1
0.2%
206334.874206066 1
0.2%
206354.102450875 1
0.2%
206373.441217193 1
0.2%
206399.57342087 1
0.2%
206400.509608473 1
0.2%
206404.41703852 2
0.3%
206405.52212193 1
0.2%
206406.000530975 1
0.2%
ValueCountFrequency (%)
210012.432600907 1
0.2%
209931.172836 1
0.2%
209892.628462066 1
0.2%
209625.385161432 1
0.2%
209500.286764629 1
0.2%
209481.672616843 1
0.2%
209455.150864288 1
0.2%
209420.004596737 2
0.3%
209356.0 1
0.2%
209353.326092817 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct519
Distinct (%)85.8%
Missing30
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean454713.5
Minimum452075.95
Maximum457495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:26.457955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452075.95
5-th percentile452674.81
Q1453797.46
median454619.06
Q3455579.75
95-th percentile456910.36
Maximum457495
Range5419.0514
Interquartile range (IQR)1782.2937

Descriptive statistics

Standard deviation1268.5586
Coefficient of variation (CV)0.0027897975
Kurtosis-0.74163207
Mean454713.5
Median Absolute Deviation (MAD)914.40682
Skewness0.14748709
Sum2.7510167 × 108
Variance1609240.9
MonotonicityNot monotonic
2024-05-11T17:06:26.602467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456379.478717154 4
 
0.6%
456632.108607443 4
 
0.6%
454984.412728653 4
 
0.6%
456330.49095806 4
 
0.6%
455843.287574845 4
 
0.6%
455576.151443154 4
 
0.6%
456466.677674703 3
 
0.5%
456514.547270291 3
 
0.5%
457174.958326298 3
 
0.5%
456995.441709842 3
 
0.5%
Other values (509) 569
89.6%
(Missing) 30
 
4.7%
ValueCountFrequency (%)
452075.948613979 2
0.3%
452127.833751152 1
0.2%
452153.414412476 1
0.2%
452160.826169813 1
0.2%
452162.834244001 1
0.2%
452239.160908325 1
0.2%
452240.753287278 1
0.2%
452276.659297917 1
0.2%
452290.247747455 1
0.2%
452336.396167841 1
0.2%
ValueCountFrequency (%)
457495.0 1
 
0.2%
457446.479605 1
 
0.2%
457380.933864584 1
 
0.2%
457312.013557238 1
 
0.2%
457288.817618457 2
0.3%
457250.150407813 1
 
0.2%
457231.281307235 1
 
0.2%
457210.837407128 1
 
0.2%
457189.008135581 1
 
0.2%
457174.958326298 3
0.5%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
일반세탁업
593 
<NA>
 
24
운동화전문세탁업
 
14
빨래방업
 
4

Length

Max length8
Median length5
Mean length5.0220472
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 593
93.4%
<NA> 24
 
3.8%
운동화전문세탁업 14
 
2.2%
빨래방업 4
 
0.6%

Length

2024-05-11T17:06:26.744762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:26.861176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 593
93.4%
na 24
 
3.8%
운동화전문세탁업 14
 
2.2%
빨래방업 4
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.6%
Missing195
Missing (%)30.7%
Infinite0
Infinite (%)0.0%
Mean0.29545455
Minimum0
Maximum28
Zeros398
Zeros (%)62.7%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:26.962106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum28
Range28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5565212
Coefficient of variation (CV)5.2682257
Kurtosis230.03478
Mean0.29545455
Median Absolute Deviation (MAD)0
Skewness13.433395
Sum130
Variance2.4227583
MonotonicityNot monotonic
2024-05-11T17:06:27.070987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 398
62.7%
1 12
 
1.9%
3 11
 
1.7%
2 9
 
1.4%
4 6
 
0.9%
5 3
 
0.5%
28 1
 
0.2%
(Missing) 195
30.7%
ValueCountFrequency (%)
0 398
62.7%
1 12
 
1.9%
2 9
 
1.4%
3 11
 
1.7%
4 6
 
0.9%
5 3
 
0.5%
28 1
 
0.2%
ValueCountFrequency (%)
28 1
 
0.2%
5 3
 
0.5%
4 6
 
0.9%
3 11
 
1.7%
2 9
 
1.4%
1 12
 
1.9%
0 398
62.7%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
420 
<NA>
209 
1
 
6

Length

Max length4
Median length1
Mean length1.9874016
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 420
66.1%
<NA> 209
32.9%
1 6
 
0.9%

Length

2024-05-11T17:06:27.193324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:27.319946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 420
66.1%
na 209
32.9%
1 6
 
0.9%
Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
338 
<NA>
183 
1
100 
2
 
13
3
 
1

Length

Max length4
Median length1
Mean length1.8645669
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 338
53.2%
<NA> 183
28.8%
1 100
 
15.7%
2 13
 
2.0%
3 1
 
0.2%

Length

2024-05-11T17:06:27.442149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:27.569957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 338
53.2%
na 183
28.8%
1 100
 
15.7%
2 13
 
2.0%
3 1
 
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)10.6%
Missing550
Missing (%)86.6%
Infinite0
Infinite (%)0.0%
Mean7.2235294
Minimum0
Maximum205
Zeros10
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:27.690061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile4.8
Maximum205
Range205
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.339708
Coefficient of variation (CV)4.061686
Kurtosis28.514063
Mean7.2235294
Median Absolute Deviation (MAD)0
Skewness5.1808787
Sum614
Variance860.81849
MonotonicityNot monotonic
2024-05-11T17:06:27.787232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 60
 
9.4%
0 10
 
1.6%
2 9
 
1.4%
5 1
 
0.2%
4 1
 
0.2%
111 1
 
0.2%
106 1
 
0.2%
105 1
 
0.2%
205 1
 
0.2%
(Missing) 550
86.6%
ValueCountFrequency (%)
0 10
 
1.6%
1 60
9.4%
2 9
 
1.4%
4 1
 
0.2%
5 1
 
0.2%
105 1
 
0.2%
106 1
 
0.2%
111 1
 
0.2%
205 1
 
0.2%
ValueCountFrequency (%)
205 1
 
0.2%
111 1
 
0.2%
106 1
 
0.2%
105 1
 
0.2%
5 1
 
0.2%
4 1
 
0.2%
2 9
 
1.4%
1 60
9.4%
0 10
 
1.6%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
351 
<NA>
278 
1
 
6

Length

Max length4
Median length1
Mean length2.3133858
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 351
55.3%
<NA> 278
43.8%
1 6
 
0.9%

Length

2024-05-11T17:06:27.904016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:28.015940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 351
55.3%
na 278
43.8%
1 6
 
0.9%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
615 
0
 
16
1
 
4

Length

Max length4
Median length4
Mean length3.9055118
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> 615
96.9%
0 16
 
2.5%
1 4
 
0.6%

Length

2024-05-11T17:06:28.135801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:28.260402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 615
96.9%
0 16
 
2.5%
1 4
 
0.6%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
423 
<NA>
212 

Length

Max length4
Median length1
Mean length2.0015748
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
66.6%
<NA> 212
33.4%

Length

2024-05-11T17:06:28.373811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:28.479961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
66.6%
na 212
33.4%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
423 
<NA>
212 

Length

Max length4
Median length1
Mean length2.0015748
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
66.6%
<NA> 212
33.4%

Length

2024-05-11T17:06:28.585901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:28.686338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
66.6%
na 212
33.4%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
423 
<NA>
212 

Length

Max length4
Median length1
Mean length2.0015748
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
66.6%
<NA> 212
33.4%

Length

2024-05-11T17:06:28.802842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:28.925459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
66.6%
na 212
33.4%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing33
Missing (%)5.2%
Memory size1.4 KiB
False
602 
(Missing)
 
33
ValueCountFrequency (%)
False 602
94.8%
(Missing) 33
 
5.2%
2024-05-11T17:06:29.018424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
423 
<NA>
211 
5
 
1

Length

Max length4
Median length1
Mean length1.9968504
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
66.6%
<NA> 211
33.2%
5 1
 
0.2%

Length

2024-05-11T17:06:29.136350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:29.240223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
66.6%
na 211
33.2%
5 1
 
0.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing635
Missing (%)100.0%
Memory size5.7 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
605 
임대
 
30

Length

Max length4
Median length4
Mean length3.9055118
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> 605
95.3%
임대 30
 
4.7%

Length

2024-05-11T17:06:29.635789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:29.768099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 605
95.3%
임대 30
 
4.7%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)7.1%
Missing536
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean1.4747475
Minimum0
Maximum6
Zeros17
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:06:29.856118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1459194
Coefficient of variation (CV)0.77702755
Kurtosis2.3101493
Mean1.4747475
Median Absolute Deviation (MAD)1
Skewness1.1843775
Sum146
Variance1.3131313
MonotonicityNot monotonic
2024-05-11T17:06:29.951928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 40
 
6.3%
2 29
 
4.6%
0 17
 
2.7%
3 7
 
1.1%
4 4
 
0.6%
6 1
 
0.2%
5 1
 
0.2%
(Missing) 536
84.4%
ValueCountFrequency (%)
0 17
2.7%
1 40
6.3%
2 29
4.6%
3 7
 
1.1%
4 4
 
0.6%
5 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 1
 
0.2%
4 4
 
0.6%
3 7
 
1.1%
2 29
4.6%
1 40
6.3%
0 17
2.7%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
600 
0
 
30
1
 
5

Length

Max length4
Median length4
Mean length3.8346457
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> 600
94.5%
0 30
 
4.7%
1 5
 
0.8%

Length

2024-05-11T17:06:30.072262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:30.179443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 600
94.5%
0 30
 
4.7%
1 5
 
0.8%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
600 
0
 
22
1
 
13

Length

Max length4
Median length4
Mean length3.8346457
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> 600
94.5%
0 22
 
3.5%
1 13
 
2.0%

Length

2024-05-11T17:06:30.303369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:30.434850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 600
94.5%
0 22
 
3.5%
1 13
 
2.0%

회수건조수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
561 
1
 
37
0
 
31
2
 
5
8
 
1

Length

Max length4
Median length4
Mean length3.6503937
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> 561
88.3%
1 37
 
5.8%
0 31
 
4.9%
2 5
 
0.8%
8 1
 
0.2%

Length

2024-05-11T17:06:30.548531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:30.670240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 561
88.3%
1 37
 
5.8%
0 31
 
4.9%
2 5
 
0.8%
8 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
565 
0
70 

Length

Max length4
Median length4
Mean length3.6692913
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> 565
89.0%
0 70
 
11.0%

Length

2024-05-11T17:06:30.790267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:06:30.886976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 565
89.0%
0 70
 
11.0%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing24
Missing (%)3.8%
Memory size1.4 KiB
False
611 
(Missing)
 
24
ValueCountFrequency (%)
False 611
96.2%
(Missing) 24
 
3.8%
2024-05-11T17:06:30.963347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030600003060000-205-1987-0196719870709<NA>3폐업2폐업20090401<NA><NA><NA>02432 960533.30131881서울특별시 중랑구 중화동 304-39번지<NA><NA>매일사2007-04-30 00:00:00I2018-08-31 23:59:59.0일반세탁업206834.549921455337.961272일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130600003060000-205-1987-0196819870709<NA>3폐업2폐업20150721<NA><NA><NA>020435807333.00131881서울특별시 중랑구 중화동 312-46번지서울특별시 중랑구 동일로129길 44 (중화동)2101원일사2006-06-02 00:00:00I2018-08-31 23:59:59.0일반세탁업206764.954499455285.811747일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230600003060000-205-1987-0196919870709<NA>3폐업2폐업20140123<NA><NA><NA>020492355723.10131882서울특별시 중랑구 중화동 331-38번지서울특별시 중랑구 봉화산로 13 (중화동)2016정든사2002-10-31 00:00:00I2018-08-31 23:59:59.0일반세탁업206628.590175455486.860717일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330600003060000-205-1987-0197019870709<NA>3폐업2폐업20160316<NA><NA><NA>020492401316.50131882서울특별시 중랑구 중화동 308-104번지서울특별시 중랑구 중랑역로 111 (중화동)2015우리사2006-06-02 00:00:00I2018-08-31 23:59:59.0일반세탁업206747.303635455681.399545일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430600003060000-205-1987-0197119870709<NA>3폐업2폐업20100121<NA><NA><NA>020493513919.80131875서울특별시 중랑구 중화동 274-49번지<NA><NA>광일사2006-01-09 00:00:00I2018-08-31 23:59:59.0일반세탁업207156.708327456033.608456일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530600003060000-205-1987-0197219870709<NA>1영업/정상1영업<NA><NA><NA><NA>020493699533.00131875서울특별시 중랑구 중화동 279-1번지서울특별시 중랑구 동일로144가길 2 (중화동)2047화랑사2006-01-09 00:00:00I2018-08-31 23:59:59.0일반세탁업207046.063815455906.342875일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630600003060000-205-1987-0197319870709<NA>3폐업2폐업20060913<NA><NA><NA>020495108523.10131876서울특별시 중랑구 중화동 285-8번지<NA><NA>충남사2006-01-09 00:00:00I2018-08-31 23:59:59.0일반세탁업206999.039169455643.576028일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730600003060000-205-1987-0197419870709<NA>1영업/정상1영업<NA><NA><NA><NA>020493456123.10131876서울특별시 중랑구 중화동 148-126번지서울특별시 중랑구 동일로130길 52 (중화동)2093동아세탁소2006-01-09 00:00:00I2018-08-31 23:59:59.0일반세탁업207257.190383455322.89857일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830600003060000-205-1987-0197519870709<NA>3폐업2폐업20060207<NA><NA><NA>020491311633.00131875서울특별시 중랑구 중화동 1-3번지<NA><NA>대명사2006-02-07 00:00:00I2018-08-31 23:59:59.0일반세탁업207583.252393455472.803343일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930600003060000-205-1987-0197619870709<NA>3폐업2폐업20130131<NA><NA><NA>020436938131.20131876서울특별시 중랑구 중화동 157-17번지서울특별시 중랑구 봉화산로26길 48 (중화동)<NA>선경사2012-04-04 14:50:52I2018-08-31 23:59:59.0일반세탁업207308.215421455272.26179일반세탁업<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
62530600003060000-205-2019-000062019-08-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>83.24131-817서울특별시 중랑구 면목동 213-8서울특별시 중랑구 면목로84길 5, 1층 (면목동)2155백영세탁2024-02-05 15:58:33I2023-12-02 00:07:00.0일반세탁업207621.862152454414.368966<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62630600003060000-205-2020-0000120200514<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.00131822서울특별시 중랑구 면목동 172-10번지서울특별시 중랑구 동일로95길 21, 1층 (면목동)2232명품세탁소2020-05-14 14:26:22I2020-05-16 00:23:20.0일반세탁업206856.56308453608.427203일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>11110N
62730600003060000-205-2020-0000220200826<NA>1영업/정상1영업<NA><NA><NA><NA>02 22098640165.00131860서울특별시 중랑구 상봉동 121-72서울특별시 중랑구 동일로114길 37, 지하1층 서쪽호 (상봉동)2136대성2020-08-26 16:34:10I2020-08-28 00:23:13.0일반세탁업207196.73834454610.267752일반세탁업00<NA><NA>11000N0<NA><NA><NA><NA>30180N
62830600003060000-205-2020-0000320201005<NA>1영업/정상1영업<NA><NA><NA><NA>023421311719.35131873서울특별시 중랑구 신내동 661 신내대명아파트서울특별시 중랑구 봉화산로 189, 신내대명아파트 상가동 211호 (신내동)2043신내 일일세탁2020-10-05 16:18:44I2020-10-07 00:23:11.0일반세탁업208231.356512456138.417215일반세탁업0022<NA><NA>000N0<NA><NA><NA><NA>21010N
62930600003060000-205-2020-0000420201208<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.88131811서울특별시 중랑구 면목동 42-33 대원슈퍼서울특별시 중랑구 용마산로93길 39, 대원슈퍼 1층 (면목동)2201삼성세탁2021-02-17 09:24:48I2021-02-19 00:23:01.0일반세탁업208292.372251454098.084101일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>30110N
63030600003060000-205-2021-0000120210111<NA>1영업/정상1영업<NA><NA><NA><NA>02 436888025.00131821서울특별시 중랑구 면목동 158-31서울특별시 중랑구 동일로92길 25, 1층 (면목동)2224아이파크명품세탁소2021-01-11 13:41:27I2021-01-13 00:23:04.0일반세탁업207118.991322453475.991927일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>11110N
63130600003060000-205-2021-0000220210113<NA>3폐업2폐업20210125<NA><NA><NA><NA>23.10131821서울특별시 중랑구 면목동 158-48 킴스빌서울특별시 중랑구 동일로92길 35, 킴스빌 A동 1층 102호 (면목동)2224센트럴 세탁소2021-01-25 13:28:17U2021-01-27 02:40:00.0일반세탁업207159.075447453482.087013일반세탁업0011<NA><NA>000N0<NA><NA><NA><NA>10110N
63230600003060000-205-2021-0000320210917<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00131826서울특별시 중랑구 면목동 368-1서울특별시 중랑구 면목로 267, 1층 101호 (면목동)2244마마운동화이불빨래방 면목점2021-09-17 15:08:58I2021-09-19 00:22:48.0일반세탁업207506.958969452706.73631일반세탁업100000000N0<NA><NA><NA><NA>20120N
63330600003060000-205-2021-0000420211021<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.77131772서울특별시 중랑구 중화동 450 중화한신아파트서울특별시 중랑구 동일로 752, 상가동 204호 (중화동, 중화한신아파트)2095한신세탁소2021-10-21 18:04:48I2021-10-23 00:23:02.0일반세탁업207163.791146454984.412729일반세탁업000000000N0<NA><NA><NA><NA>10010N
63430600003060000-205-2022-000012022-08-25<NA>3폐업2폐업2024-02-28<NA><NA><NA><NA>28.00131-230서울특별시 중랑구 망우동 610 신내역 금강펜테리움 센트럴파크 104호서울특별시 중랑구 용마산로136길 160, 104호 (망우동, 신내역 금강펜테리움 센트럴파크)2057금강명품세탁2024-02-28 10:54:49U2023-12-03 00:01:00.0일반세탁업209625.385161456321.340185<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>