Overview

Dataset statistics

Number of variables47
Number of observations633
Missing cells6533
Missing cells (%)22.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory250.5 KiB
Average record size in memory405.2 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-17968/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (92.5%)Imbalance
위생업태명 is highly imbalanced (65.5%)Imbalance
사용시작지하층 is highly imbalanced (56.4%)Imbalance
사용끝지하층 is highly imbalanced (80.2%)Imbalance
발한실여부 is highly imbalanced (77.2%)Imbalance
세탁기수 is highly imbalanced (69.5%)Imbalance
여성종사자수 is highly imbalanced (82.9%)Imbalance
남성종사자수 is highly imbalanced (82.6%)Imbalance
회수건조수 is highly imbalanced (73.4%)Imbalance
침대수 is highly imbalanced (53.8%)Imbalance
인허가취소일자 has 633 (100.0%) missing valuesMissing
폐업일자 has 147 (23.2%) missing valuesMissing
휴업시작일자 has 633 (100.0%) missing valuesMissing
휴업종료일자 has 633 (100.0%) missing valuesMissing
재개업일자 has 633 (100.0%) missing valuesMissing
전화번호 has 51 (8.1%) missing valuesMissing
소재지우편번호 has 8 (1.3%) missing valuesMissing
도로명주소 has 345 (54.5%) missing valuesMissing
도로명우편번호 has 353 (55.8%) missing valuesMissing
좌표정보(X) has 49 (7.7%) missing valuesMissing
좌표정보(Y) has 49 (7.7%) missing valuesMissing
건물지상층수 has 234 (37.0%) missing valuesMissing
사용시작지상층 has 265 (41.9%) missing valuesMissing
사용끝지상층 has 365 (57.7%) missing valuesMissing
발한실여부 has 117 (18.5%) missing valuesMissing
조건부허가신고사유 has 633 (100.0%) missing valuesMissing
조건부허가시작일자 has 633 (100.0%) missing valuesMissing
조건부허가종료일자 has 633 (100.0%) missing valuesMissing
다중이용업소여부 has 113 (17.9%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
소재지면적 has 177 (28.0%) zerosZeros
건물지상층수 has 154 (24.3%) zerosZeros
사용시작지상층 has 105 (16.6%) zerosZeros

Reproduction

Analysis started2024-05-11 08:30:29.645415
Analysis finished2024-05-11 08:30:30.455484
Duration0.81 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
3160000
633 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 633
100.0%

Length

2024-05-11T17:30:30.508468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:30.584653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 633
100.0%

관리번호
Text

UNIQUE 

Distinct633
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T17:30:30.734688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13926
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

Unique633 ?
Unique (%)100.0%

Sample

1st row3160000-205-1985-01789
2nd row3160000-205-1987-01738
3rd row3160000-205-1987-01739
4th row3160000-205-1987-01740
5th row3160000-205-1987-01741
ValueCountFrequency (%)
3160000-205-1985-01789 1
 
0.2%
3160000-205-2003-00010 1
 
0.2%
3160000-205-2003-00012 1
 
0.2%
3160000-205-2003-00004 1
 
0.2%
3160000-205-2003-00005 1
 
0.2%
3160000-205-2003-00006 1
 
0.2%
3160000-205-2003-00007 1
 
0.2%
3160000-205-2003-00008 1
 
0.2%
3160000-205-2003-00009 1
 
0.2%
3160000-205-2003-00002 1
 
0.2%
Other values (623) 623
98.4%
2024-05-11T17:30:31.021409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5080
36.5%
- 1899
 
13.6%
1 1554
 
11.2%
2 1168
 
8.4%
9 852
 
6.1%
3 839
 
6.0%
5 803
 
5.8%
6 779
 
5.6%
8 472
 
3.4%
7 314
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12027
86.4%
Dash Punctuation 1899
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5080
42.2%
1 1554
 
12.9%
2 1168
 
9.7%
9 852
 
7.1%
3 839
 
7.0%
5 803
 
6.7%
6 779
 
6.5%
8 472
 
3.9%
7 314
 
2.6%
4 166
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1899
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5080
36.5%
- 1899
 
13.6%
1 1554
 
11.2%
2 1168
 
8.4%
9 852
 
6.1%
3 839
 
6.0%
5 803
 
5.8%
6 779
 
5.6%
8 472
 
3.4%
7 314
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5080
36.5%
- 1899
 
13.6%
1 1554
 
11.2%
2 1168
 
8.4%
9 852
 
6.1%
3 839
 
6.0%
5 803
 
5.8%
6 779
 
5.6%
8 472
 
3.4%
7 314
 
2.3%

인허가일자
Date

Distinct427
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1985-06-25 00:00:00
Maximum2023-08-02 00:00:00
2024-05-11T17:30:31.147029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:31.275167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3
486 
1
147 

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
76.8%
1 147
 
23.2%

Length

2024-05-11T17:30:31.393460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:31.477778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 486
76.8%
1 147
 
23.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
486 
영업/정상
147 

Length

Max length5
Median length2
Mean length2.6966825
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 486
76.8%
영업/정상 147
 
23.2%

Length

2024-05-11T17:30:31.582228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:31.679352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 486
76.8%
영업/정상 147
 
23.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2
486 
1
147 

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
76.8%
1 147
 
23.2%

Length

2024-05-11T17:30:31.768747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:31.859131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 486
76.8%
1 147
 
23.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
486 
영업
147 

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
76.8%
영업 147
 
23.2%

Length

2024-05-11T17:30:31.970405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:32.055756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 486
76.8%
영업 147
 
23.2%

폐업일자
Date

MISSING 

Distinct372
Distinct (%)76.5%
Missing147
Missing (%)23.2%
Memory size5.1 KiB
Minimum1988-05-16 00:00:00
Maximum2024-04-08 00:00:00
2024-05-11T17:30:32.153947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:32.288219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

전화번호
Text

MISSING 

Distinct525
Distinct (%)90.2%
Missing51
Missing (%)8.1%
Memory size5.1 KiB
2024-05-11T17:30:32.520777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.022337
Min length2

Characters and Unicode

Total characters5833
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

Unique491 ?
Unique (%)84.4%

Sample

1st row0206132201
2nd row02 8545075
3rd row0200000000
4th row02 8631621
5th row02 0
ValueCountFrequency (%)
02 280
32.0%
0 13
 
1.5%
0200000000 9
 
1.0%
00000 6
 
0.7%
070 4
 
0.5%
0226149977 3
 
0.3%
0226879423 2
 
0.2%
8663208 2
 
0.2%
8692572 2
 
0.2%
6832145 2
 
0.2%
Other values (525) 552
63.1%
2024-05-11T17:30:32.836367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1090
18.7%
0 1056
18.1%
6 683
11.7%
8 675
11.6%
5 400
 
6.9%
3 360
 
6.2%
350
 
6.0%
1 345
 
5.9%
4 315
 
5.4%
7 291
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5483
94.0%
Space Separator 350
 
6.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1090
19.9%
0 1056
19.3%
6 683
12.5%
8 675
12.3%
5 400
 
7.3%
3 360
 
6.6%
1 345
 
6.3%
4 315
 
5.7%
7 291
 
5.3%
9 268
 
4.9%
Space Separator
ValueCountFrequency (%)
350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1090
18.7%
0 1056
18.1%
6 683
11.7%
8 675
11.6%
5 400
 
6.9%
3 360
 
6.2%
350
 
6.0%
1 345
 
5.9%
4 315
 
5.4%
7 291
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1090
18.7%
0 1056
18.1%
6 683
11.7%
8 675
11.6%
5 400
 
6.9%
3 360
 
6.2%
350
 
6.0%
1 345
 
5.9%
4 315
 
5.4%
7 291
 
5.0%

소재지면적
Real number (ℝ)

ZEROS 

Distinct197
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.216888
Minimum0
Maximum734.95
Zeros177
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:32.973018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q332.4
95-th percentile76.72
Maximum734.95
Range734.95
Interquartile range (IQR)32.4

Descriptive statistics

Standard deviation50.859396
Coefficient of variation (CV)1.7407534
Kurtosis80.912712
Mean29.216888
Median Absolute Deviation (MAD)9.14
Skewness7.5927495
Sum18494.29
Variance2586.6781
MonotonicityNot monotonic
2024-05-11T17:30:33.101474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 177
28.0%
26.4 75
 
11.8%
33.0 33
 
5.2%
23.1 25
 
3.9%
30.0 16
 
2.5%
16.5 16
 
2.5%
24.0 13
 
2.1%
19.8 12
 
1.9%
29.7 7
 
1.1%
49.5 6
 
0.9%
Other values (187) 253
40.0%
ValueCountFrequency (%)
0.0 177
28.0%
8.96 1
 
0.2%
9.9 3
 
0.5%
12.0 4
 
0.6%
12.81 1
 
0.2%
13.19 1
 
0.2%
13.2 2
 
0.3%
13.72 1
 
0.2%
14.7 1
 
0.2%
14.85 2
 
0.3%
ValueCountFrequency (%)
734.95 1
0.2%
481.5 1
0.2%
474.0 1
0.2%
315.0 1
0.2%
299.41 1
0.2%
284.1 1
0.2%
216.0 1
0.2%
202.0 1
0.2%
201.39 1
0.2%
193.72 1
0.2%

소재지우편번호
Text

MISSING 

Distinct121
Distinct (%)19.4%
Missing8
Missing (%)1.3%
Memory size5.1 KiB
2024-05-11T17:30:33.327440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0336
Min length6

Characters and Unicode

Total characters3771
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

Unique41 ?
Unique (%)6.6%

Sample

1st row152810
2nd row152880
3rd row152888
4th row152856
5th row152886
ValueCountFrequency (%)
152090 24
 
3.8%
152800 21
 
3.4%
152872 19
 
3.0%
152871 18
 
2.9%
152875 17
 
2.7%
152815 16
 
2.6%
152906 15
 
2.4%
152858 15
 
2.4%
152888 15
 
2.4%
152836 15
 
2.4%
Other values (111) 450
72.0%
2024-05-11T17:30:33.648847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 754
20.0%
1 745
19.8%
2 734
19.5%
8 660
17.5%
0 273
 
7.2%
7 127
 
3.4%
3 125
 
3.3%
4 119
 
3.2%
9 112
 
3.0%
6 101
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3750
99.4%
Dash Punctuation 21
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 754
20.1%
1 745
19.9%
2 734
19.6%
8 660
17.6%
0 273
 
7.3%
7 127
 
3.4%
3 125
 
3.3%
4 119
 
3.2%
9 112
 
3.0%
6 101
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3771
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 754
20.0%
1 745
19.8%
2 734
19.5%
8 660
17.5%
0 273
 
7.2%
7 127
 
3.4%
3 125
 
3.3%
4 119
 
3.2%
9 112
 
3.0%
6 101
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3771
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 754
20.0%
1 745
19.8%
2 734
19.5%
8 660
17.5%
0 273
 
7.2%
7 127
 
3.4%
3 125
 
3.3%
4 119
 
3.2%
9 112
 
3.0%
6 101
 
2.7%

지번주소
Text

Distinct592
Distinct (%)94.4%
Missing6
Missing (%)0.9%
Memory size5.1 KiB
2024-05-11T17:30:33.835093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length46
Mean length25.298246
Min length15

Characters and Unicode

Total characters15862
Distinct characters194
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

Unique559 ?
Unique (%)89.2%

Sample

1st row서울특별시 구로구 개봉동 262-18번지
2nd row서울특별시 구로구 구로동 1129-19번지
3rd row서울특별시 구로구 신도림동 439-16번지
4th row서울특별시 구로구 구로동 442-46번지
5th row서울특별시 구로구 신도림동 292-45번지
ValueCountFrequency (%)
구로구 629
21.5%
서울특별시 627
21.4%
구로동 235
 
8.0%
개봉동 128
 
4.4%
고척동 88
 
3.0%
오류동 56
 
1.9%
신도림동 37
 
1.3%
가리봉동 35
 
1.2%
1층 24
 
0.8%
상가동 20
 
0.7%
Other values (797) 1045
35.7%
2024-05-11T17:30:34.164782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2772
17.5%
구 1501
 
9.5%
로 872
 
5.5%
동 717
 
4.5%
1 704
 
4.4%
서 629
 
4.0%
시 629
 
4.0%
울 628
 
4.0%
특 627
 
4.0%
별 627
 
4.0%
Other values (184) 6156
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9110
57.4%
Decimal Number 3325
 
21.0%
Space Separator 2772
 
17.5%
Dash Punctuation 549
 
3.5%
Uppercase Letter 37
 
0.2%
Close Punctuation 30
 
0.2%
Open Punctuation 30
 
0.2%
Other Punctuation 8
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1501
16.5%
로 872
9.6%
동 717
 
7.9%
서 629
 
6.9%
시 629
 
6.9%
울 628
 
6.9%
특 627
 
6.9%
별 627
 
6.9%
지 476
 
5.2%
번 450
 
4.9%
Other values (156) 1954
21.4%
Uppercase Letter
ValueCountFrequency (%)
B 8
21.6%
A 6
16.2%
S 6
16.2%
K 5
13.5%
E 3
 
8.1%
I 2
 
5.4%
L 2
 
5.4%
V 1
 
2.7%
G 1
 
2.7%
U 1
 
2.7%
Other values (2) 2
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 704
21.2%
2 506
15.2%
3 338
10.2%
4 325
9.8%
0 311
9.4%
7 283
8.5%
5 255
 
7.7%
6 255
 
7.7%
9 176
 
5.3%
8 172
 
5.2%
Space Separator
ValueCountFrequency (%)
2772
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 549
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9110
57.4%
Common 6714
42.3%
Latin 38
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1501
16.5%
로 872
9.6%
동 717
 
7.9%
서 629
 
6.9%
시 629
 
6.9%
울 628
 
6.9%
특 627
 
6.9%
별 627
 
6.9%
지 476
 
5.2%
번 450
 
4.9%
Other values (156) 1954
21.4%
Common
ValueCountFrequency (%)
2772
41.3%
1 704
 
10.5%
- 549
 
8.2%
2 506
 
7.5%
3 338
 
5.0%
4 325
 
4.8%
0 311
 
4.6%
7 283
 
4.2%
5 255
 
3.8%
6 255
 
3.8%
Other values (5) 416
 
6.2%
Latin
ValueCountFrequency (%)
B 8
21.1%
A 6
15.8%
S 6
15.8%
K 5
13.2%
E 3
 
7.9%
I 2
 
5.3%
L 2
 
5.3%
V 1
 
2.6%
e 1
 
2.6%
G 1
 
2.6%
Other values (3) 3
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9110
57.4%
ASCII 6752
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2772
41.1%
1 704
 
10.4%
- 549
 
8.1%
2 506
 
7.5%
3 338
 
5.0%
4 325
 
4.8%
0 311
 
4.6%
7 283
 
4.2%
5 255
 
3.8%
6 255
 
3.8%
Other values (18) 454
 
6.7%
Hangul
ValueCountFrequency (%)
구 1501
16.5%
로 872
9.6%
동 717
 
7.9%
서 629
 
6.9%
시 629
 
6.9%
울 628
 
6.9%
특 627
 
6.9%
별 627
 
6.9%
지 476
 
5.2%
번 450
 
4.9%
Other values (156) 1954
21.4%

도로명주소
Text

MISSING 

Distinct285
Distinct (%)99.0%
Missing345
Missing (%)54.5%
Memory size5.1 KiB
2024-05-11T17:30:34.430408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length48
Mean length32.809028
Min length22

Characters and Unicode

Total characters9449
Distinct characters196
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

Unique282 ?
Unique (%)97.9%

Sample

1st row서울특별시 구로구 개봉로16길 37-3 (개봉동)
2nd row서울특별시 구로구 구로중앙로12길 21 (구로동)
3rd row서울특별시 구로구 구로동로23길 7-19 (구로동)
4th row서울특별시 구로구 구로중앙로34길 30 (구로동)
5th row서울특별시 구로구 구로동로 203 (구로동,대흥상가 1층 1호)
ValueCountFrequency (%)
서울특별시 288
 
16.7%
구로구 288
 
16.7%
구로동 70
 
4.1%
개봉동 45
 
2.6%
고척동 30
 
1.7%
1층 27
 
1.6%
오류동 26
 
1.5%
상가동 22
 
1.3%
경인로 13
 
0.8%
가리봉동 12
 
0.7%
Other values (526) 900
52.3%
2024-05-11T17:30:34.869479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1435
 
15.2%
구 759
 
8.0%
로 742
 
7.9%
동 399
 
4.2%
1 397
 
4.2%
) 317
 
3.4%
( 317
 
3.4%
서 298
 
3.2%
시 293
 
3.1%
울 290
 
3.1%
Other values (186) 4202
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5484
58.0%
Decimal Number 1593
 
16.9%
Space Separator 1435
 
15.2%
Close Punctuation 317
 
3.4%
Open Punctuation 317
 
3.4%
Other Punctuation 218
 
2.3%
Dash Punctuation 53
 
0.6%
Uppercase Letter 32
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 759
13.8%
로 742
13.5%
동 399
 
7.3%
서 298
 
5.4%
시 293
 
5.3%
울 290
 
5.3%
별 288
 
5.3%
특 288
 
5.3%
길 235
 
4.3%
가 117
 
2.1%
Other values (159) 1775
32.4%
Uppercase Letter
ValueCountFrequency (%)
B 6
18.8%
A 5
15.6%
S 5
15.6%
K 4
12.5%
E 3
9.4%
I 2
 
6.2%
L 2
 
6.2%
V 1
 
3.1%
G 1
 
3.1%
U 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 397
24.9%
2 277
17.4%
0 189
11.9%
3 157
 
9.9%
4 120
 
7.5%
5 119
 
7.5%
8 100
 
6.3%
6 88
 
5.5%
7 88
 
5.5%
9 58
 
3.6%
Space Separator
ValueCountFrequency (%)
1435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Other Punctuation
ValueCountFrequency (%)
, 218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5484
58.0%
Common 3933
41.6%
Latin 32
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 759
13.8%
로 742
13.5%
동 399
 
7.3%
서 298
 
5.4%
시 293
 
5.3%
울 290
 
5.3%
별 288
 
5.3%
특 288
 
5.3%
길 235
 
4.3%
가 117
 
2.1%
Other values (159) 1775
32.4%
Common
ValueCountFrequency (%)
1435
36.5%
1 397
 
10.1%
) 317
 
8.1%
( 317
 
8.1%
2 277
 
7.0%
, 218
 
5.5%
0 189
 
4.8%
3 157
 
4.0%
4 120
 
3.1%
5 119
 
3.0%
Other values (5) 387
 
9.8%
Latin
ValueCountFrequency (%)
B 6
18.8%
A 5
15.6%
S 5
15.6%
K 4
12.5%
E 3
9.4%
I 2
 
6.2%
L 2
 
6.2%
V 1
 
3.1%
G 1
 
3.1%
U 1
 
3.1%
Other values (2) 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5484
58.0%
ASCII 3965
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1435
36.2%
1 397
 
10.0%
) 317
 
8.0%
( 317
 
8.0%
2 277
 
7.0%
, 218
 
5.5%
0 189
 
4.8%
3 157
 
4.0%
4 120
 
3.0%
5 119
 
3.0%
Other values (17) 419
 
10.6%
Hangul
ValueCountFrequency (%)
구 759
13.8%
로 742
13.5%
동 399
 
7.3%
서 298
 
5.4%
시 293
 
5.3%
울 290
 
5.3%
별 288
 
5.3%
특 288
 
5.3%
길 235
 
4.3%
가 117
 
2.1%
Other values (159) 1775
32.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct136
Distinct (%)48.6%
Missing353
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean8293.2464
Minimum8201
Maximum8395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:35.004055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8201
5-th percentile8211
Q18249
median8294
Q38332.25
95-th percentile8378.25
Maximum8395
Range194
Interquartile range (IQR)83.25

Descriptive statistics

Standard deviation52.097991
Coefficient of variation (CV)0.006281978
Kurtosis-1.0094974
Mean8293.2464
Median Absolute Deviation (MAD)43
Skewness0.087106439
Sum2322109
Variance2714.2007
MonotonicityNot monotonic
2024-05-11T17:30:35.131806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8323 6
 
0.9%
8298 5
 
0.8%
8251 5
 
0.8%
8318 5
 
0.8%
8351 4
 
0.6%
8344 4
 
0.6%
8261 4
 
0.6%
8338 4
 
0.6%
8270 4
 
0.6%
8303 4
 
0.6%
Other values (126) 235
37.1%
(Missing) 353
55.8%
ValueCountFrequency (%)
8201 2
0.3%
8202 1
 
0.2%
8205 1
 
0.2%
8206 1
 
0.2%
8207 2
0.3%
8208 3
0.5%
8209 1
 
0.2%
8210 2
0.3%
8211 3
0.5%
8215 1
 
0.2%
ValueCountFrequency (%)
8395 3
0.5%
8393 3
0.5%
8392 2
0.3%
8388 1
 
0.2%
8387 2
0.3%
8384 1
 
0.2%
8383 2
0.3%
8378 1
 
0.2%
8375 2
0.3%
8374 1
 
0.2%

사업장명
Text

Distinct462
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T17:30:35.389735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length4.1279621
Min length1

Characters and Unicode

Total characters2613
Distinct characters299
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

Unique366 ?
Unique (%)57.8%

Sample

1st row백광사
2nd row동명사
3rd row익영사
4th row영동사
5th row백조사
ValueCountFrequency (%)
세탁소 15
 
2.2%
백양사 10
 
1.4%
세탁 8
 
1.2%
현대사 8
 
1.2%
우성사 7
 
1.0%
백조 7
 
1.0%
제일사 6
 
0.9%
백조사 6
 
0.9%
백양 6
 
0.9%
현대세탁 6
 
0.9%
Other values (472) 614
88.6%
2024-05-11T17:30:35.783742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 298
 
11.4%
세 213
 
8.2%
탁 208
 
8.0%
소 111
 
4.2%
대 61
 
2.3%
60
 
2.3%
백 57
 
2.2%
성 56
 
2.1%
크 45
 
1.7%
양 35
 
1.3%
Other values (289) 1469
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2494
95.4%
Space Separator 60
 
2.3%
Uppercase Letter 19
 
0.7%
Decimal Number 13
 
0.5%
Close Punctuation 8
 
0.3%
Open Punctuation 8
 
0.3%
Lowercase Letter 8
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 298
 
11.9%
세 213
 
8.5%
탁 208
 
8.3%
소 111
 
4.5%
대 61
 
2.4%
백 57
 
2.3%
성 56
 
2.2%
크 45
 
1.8%
양 35
 
1.4%
일 34
 
1.4%
Other values (262) 1376
55.2%
Uppercase Letter
ValueCountFrequency (%)
K 3
15.8%
O 3
15.8%
C 3
15.8%
S 2
10.5%
U 2
10.5%
L 1
 
5.3%
G 1
 
5.3%
H 1
 
5.3%
A 1
 
5.3%
M 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
l 1
12.5%
a 1
12.5%
n 1
12.5%
o 1
12.5%
m 1
12.5%
c 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
9 3
23.1%
8 2
 
15.4%
4 1
 
7.7%
2 1
 
7.7%
Space Separator
ValueCountFrequency (%)
60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2494
95.4%
Common 92
 
3.5%
Latin 27
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 298
 
11.9%
세 213
 
8.5%
탁 208
 
8.3%
소 111
 
4.5%
대 61
 
2.4%
백 57
 
2.3%
성 56
 
2.2%
크 45
 
1.8%
양 35
 
1.4%
일 34
 
1.4%
Other values (262) 1376
55.2%
Latin
ValueCountFrequency (%)
K 3
 
11.1%
O 3
 
11.1%
C 3
 
11.1%
S 2
 
7.4%
U 2
 
7.4%
e 2
 
7.4%
l 1
 
3.7%
a 1
 
3.7%
L 1
 
3.7%
n 1
 
3.7%
Other values (8) 8
29.6%
Common
ValueCountFrequency (%)
60
65.2%
) 8
 
8.7%
( 8
 
8.7%
1 6
 
6.5%
9 3
 
3.3%
. 3
 
3.3%
8 2
 
2.2%
4 1
 
1.1%
2 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2494
95.4%
ASCII 119
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 298
 
11.9%
세 213
 
8.5%
탁 208
 
8.3%
소 111
 
4.5%
대 61
 
2.4%
백 57
 
2.3%
성 56
 
2.2%
크 45
 
1.8%
양 35
 
1.4%
일 34
 
1.4%
Other values (262) 1376
55.2%
ASCII
ValueCountFrequency (%)
60
50.4%
) 8
 
6.7%
( 8
 
6.7%
1 6
 
5.0%
9 3
 
2.5%
K 3
 
2.5%
O 3
 
2.5%
C 3
 
2.5%
. 3
 
2.5%
S 2
 
1.7%
Other values (17) 20
 
16.8%

최종수정일자
Date

Distinct363
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1999-02-12 00:00:00
Maximum2024-04-26 15:52:02
2024-05-11T17:30:35.928048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:36.072304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
I
424 
U
209 

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 424
67.0%
U 209
33.0%

Length

2024-05-11T17:30:36.242182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:36.327318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 424
67.0%
u 209
33.0%

데이터갱신일자
Date

Distinct90
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:04:00
2024-05-11T17:30:36.449249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:36.835313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
일반세탁업
622 
운동화전문세탁업
 
6
빨래방업
 
4
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length5.0236967
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 622
98.3%
운동화전문세탁업 6
 
0.9%
빨래방업 4
 
0.6%
세탁업 기타 1
 
0.2%

Length

2024-05-11T17:30:36.979347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:37.097650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 622
98.1%
운동화전문세탁업 6
 
0.9%
빨래방업 4
 
0.6%
세탁업 1
 
0.2%
기타 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct466
Distinct (%)79.8%
Missing49
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean188133.8
Minimum183852.4
Maximum191104.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:37.223700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183852.4
5-th percentile184948.43
Q1186634.87
median188048.13
Q3189921.49
95-th percentile190369.75
Maximum191104.06
Range7251.6558
Interquartile range (IQR)3286.6194

Descriptive statistics

Standard deviation1877.8367
Coefficient of variation (CV)0.0099813895
Kurtosis-1.1472873
Mean188133.8
Median Absolute Deviation (MAD)1736.6127
Skewness-0.33946803
Sum1.0987014 × 108
Variance3526270.6
MonotonicityNot monotonic
2024-05-11T17:30:37.355699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187771.039016092 5
 
0.8%
187151.14950035 5
 
0.8%
188674.995072188 5
 
0.8%
187601.409308013 4
 
0.6%
189372.1910653 4
 
0.6%
186835.172300314 4
 
0.6%
189691.819100824 3
 
0.5%
188850.322284116 3
 
0.5%
187273.582353001 3
 
0.5%
186905.501564017 3
 
0.5%
Other values (456) 545
86.1%
(Missing) 49
 
7.7%
ValueCountFrequency (%)
183852.400997364 2
0.3%
183853.596688736 1
0.2%
183969.570522017 1
0.2%
184018.014359305 1
0.2%
184018.256080314 2
0.3%
184019.610971952 1
0.2%
184038.202591244 1
0.2%
184158.154452529 1
0.2%
184198.098702935 2
0.3%
184200.661623067 2
0.3%
ValueCountFrequency (%)
191104.056779696 1
0.2%
191072.775405392 1
0.2%
191043.451267658 1
0.2%
190952.866035823 1
0.2%
190942.769217577 1
0.2%
190894.508608887 1
0.2%
190788.305181108 1
0.2%
190750.211657268 1
0.2%
190728.045929929 1
0.2%
190570.650459437 2
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct466
Distinct (%)79.8%
Missing49
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean443714.28
Minimum441904
Maximum445650.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:37.499777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441904
5-th percentile442308.13
Q1443041.83
median443749.5
Q3444411.99
95-th percentile445018.07
Maximum445650.18
Range3746.1804
Interquartile range (IQR)1370.157

Descriptive statistics

Standard deviation846.6793
Coefficient of variation (CV)0.0019081633
Kurtosis-0.85130061
Mean443714.28
Median Absolute Deviation (MAD)676.07741
Skewness-0.072515005
Sum2.5912914 × 108
Variance716865.84
MonotonicityNot monotonic
2024-05-11T17:30:37.643718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443682.345373776 5
 
0.8%
444544.592000758 5
 
0.8%
443749.503020388 5
 
0.8%
444490.834046357 4
 
0.6%
444854.451693268 4
 
0.6%
442508.979734929 4
 
0.6%
445265.191940304 3
 
0.5%
443942.074745249 3
 
0.5%
443984.69680266 3
 
0.5%
443011.128133101 3
 
0.5%
Other values (456) 545
86.1%
(Missing) 49
 
7.7%
ValueCountFrequency (%)
441904.00354486 2
0.3%
441923.997508266 1
0.2%
441929.408155687 1
0.2%
441936.248166266 1
0.2%
441940.976817713 1
0.2%
441956.193184116 1
0.2%
441987.223126688 1
0.2%
441990.571101897 1
0.2%
441998.93960348 1
0.2%
442014.853365258 1
0.2%
ValueCountFrequency (%)
445650.183972882 1
 
0.2%
445556.641493041 1
 
0.2%
445430.97917589 2
0.3%
445381.540711693 2
0.3%
445367.425944571 1
 
0.2%
445265.753646808 1
 
0.2%
445265.191940304 3
0.5%
445262.493847028 1
 
0.2%
445250.538868558 2
0.3%
445223.965179138 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
일반세탁업
511 
<NA>
113 
운동화전문세탁업
 
4
빨래방업
 
4
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.835703
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 511
80.7%
<NA> 113
 
17.9%
운동화전문세탁업 4
 
0.6%
빨래방업 4
 
0.6%
세탁업 기타 1
 
0.2%

Length

2024-05-11T17:30:37.800996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:37.920405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 511
80.6%
na 113
 
17.8%
운동화전문세탁업 4
 
0.6%
빨래방업 4
 
0.6%
세탁업 1
 
0.2%
기타 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)2.5%
Missing234
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean1.7343358
Minimum0
Maximum17
Zeros154
Zeros (%)24.3%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:38.035841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8030123
Coefficient of variation (CV)1.0395981
Kurtosis12.583447
Mean1.7343358
Median Absolute Deviation (MAD)2
Skewness1.994154
Sum692
Variance3.2508533
MonotonicityNot monotonic
2024-05-11T17:30:38.144446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 154
24.3%
2 83
 
13.1%
3 78
 
12.3%
4 45
 
7.1%
1 26
 
4.1%
5 9
 
1.4%
10 1
 
0.2%
6 1
 
0.2%
17 1
 
0.2%
8 1
 
0.2%
(Missing) 234
37.0%
ValueCountFrequency (%)
0 154
24.3%
1 26
 
4.1%
2 83
13.1%
3 78
12.3%
4 45
 
7.1%
5 9
 
1.4%
6 1
 
0.2%
8 1
 
0.2%
10 1
 
0.2%
17 1
 
0.2%
ValueCountFrequency (%)
17 1
 
0.2%
10 1
 
0.2%
8 1
 
0.2%
6 1
 
0.2%
5 9
 
1.4%
4 45
 
7.1%
3 78
12.3%
2 83
13.1%
1 26
 
4.1%
0 154
24.3%

건물지하층수
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
322 
0
167 
1
141 
2
 
2
5
 
1

Length

Max length4
Median length4
Mean length2.5260664
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row0
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 322
50.9%
0 167
26.4%
1 141
22.3%
2 2
 
0.3%
5 1
 
0.2%

Length

2024-05-11T17:30:38.280837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:38.404910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 322
50.9%
0 167
26.4%
1 141
22.3%
2 2
 
0.3%
5 1
 
0.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.6%
Missing265
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean0.88586957
Minimum0
Maximum5
Zeros105
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:38.495766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.74410768
Coefficient of variation (CV)0.83997432
Kurtosis5.4229444
Mean0.88586957
Median Absolute Deviation (MAD)0
Skewness1.3839291
Sum326
Variance0.55369624
MonotonicityNot monotonic
2024-05-11T17:30:38.605412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 212
33.5%
0 105
 
16.6%
2 45
 
7.1%
3 2
 
0.3%
5 2
 
0.3%
4 2
 
0.3%
(Missing) 265
41.9%
ValueCountFrequency (%)
0 105
16.6%
1 212
33.5%
2 45
 
7.1%
3 2
 
0.3%
4 2
 
0.3%
5 2
 
0.3%
ValueCountFrequency (%)
5 2
 
0.3%
4 2
 
0.3%
3 2
 
0.3%
2 45
 
7.1%
1 212
33.5%
0 105
16.6%

사용끝지상층
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)2.2%
Missing365
Missing (%)57.7%
Infinite0
Infinite (%)0.0%
Mean1.2126866
Minimum0
Maximum5
Zeros6
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T17:30:38.716774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.60235762
Coefficient of variation (CV)0.49671336
Kurtosis13.937939
Mean1.2126866
Median Absolute Deviation (MAD)0
Skewness2.9801661
Sum325
Variance0.3628347
MonotonicityNot monotonic
2024-05-11T17:30:38.816511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 211
33.3%
2 45
 
7.1%
0 6
 
0.9%
3 2
 
0.3%
5 2
 
0.3%
4 2
 
0.3%
(Missing) 365
57.7%
ValueCountFrequency (%)
0 6
 
0.9%
1 211
33.3%
2 45
 
7.1%
3 2
 
0.3%
4 2
 
0.3%
5 2
 
0.3%
ValueCountFrequency (%)
5 2
 
0.3%
4 2
 
0.3%
3 2
 
0.3%
2 45
 
7.1%
1 211
33.3%
0 6
 
0.9%

사용시작지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
497 
0
120 
1
 
15
2
 
1

Length

Max length4
Median length4
Mean length3.3554502
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 497
78.5%
0 120
 
19.0%
1 15
 
2.4%
2 1
 
0.2%

Length

2024-05-11T17:30:38.935247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:39.037269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 497
78.5%
0 120
 
19.0%
1 15
 
2.4%
2 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
595 
0
 
22
1
 
15
2
 
1

Length

Max length4
Median length4
Mean length3.8199052
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> 595
94.0%
0 22
 
3.5%
1 15
 
2.4%
2 1
 
0.2%

Length

2024-05-11T17:30:39.140875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:39.251153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 595
94.0%
0 22
 
3.5%
1 15
 
2.4%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
456 
0
177 

Length

Max length4
Median length4
Mean length3.1611374
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 456
72.0%
0 177
 
28.0%

Length

2024-05-11T17:30:39.364484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:39.464207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
72.0%
0 177
 
28.0%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
456 
0
177 

Length

Max length4
Median length4
Mean length3.1611374
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 456
72.0%
0 177
 
28.0%

Length

2024-05-11T17:30:39.569227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:39.652983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
72.0%
0 177
 
28.0%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
456 
0
177 

Length

Max length4
Median length4
Mean length3.1611374
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 456
72.0%
0 177
 
28.0%

Length

2024-05-11T17:30:39.748507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:39.834199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
72.0%
0 177
 
28.0%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing117
Missing (%)18.5%
Memory size1.4 KiB
False
497 
True
 
19
(Missing)
117 
ValueCountFrequency (%)
False 497
78.5%
True 19
 
3.0%
(Missing) 117
 
18.5%
2024-05-11T17:30:39.904446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
456 
0
177 

Length

Max length4
Median length4
Mean length3.1611374
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 456
72.0%
0 177
 
28.0%

Length

2024-05-11T17:30:39.996642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:40.102477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
72.0%
0 177
 
28.0%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing633
Missing (%)100.0%
Memory size5.7 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
398 
임대
221 
자가
 
14

Length

Max length4
Median length4
Mean length3.2575039
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 398
62.9%
임대 221
34.9%
자가 14
 
2.2%

Length

2024-05-11T17:30:40.213354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:40.328963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 398
62.9%
임대 221
34.9%
자가 14
 
2.2%

세탁기수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
553 
1
 
29
0
 
22
2
 
22
3
 
6

Length

Max length4
Median length4
Mean length3.6208531
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> 553
87.4%
1 29
 
4.6%
0 22
 
3.5%
2 22
 
3.5%
3 6
 
0.9%
4 1
 
0.2%

Length

2024-05-11T17:30:40.438863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:40.548593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
87.4%
1 29
 
4.6%
0 22
 
3.5%
2 22
 
3.5%
3 6
 
0.9%
4 1
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
606 
0
 
25
1
 
2

Length

Max length4
Median length4
Mean length3.8720379
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> 606
95.7%
0 25
 
3.9%
1 2
 
0.3%

Length

2024-05-11T17:30:40.678483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:40.793721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 606
95.7%
0 25
 
3.9%
1 2
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
606 
0
 
24
1
 
3

Length

Max length4
Median length4
Mean length3.8720379
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> 606
95.7%
0 24
 
3.8%
1 3
 
0.5%

Length

2024-05-11T17:30:40.900380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:41.001830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 606
95.7%
0 24
 
3.8%
1 3
 
0.5%

회수건조수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
567 
0
 
36
1
 
26
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.6872038
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> 567
89.6%
0 36
 
5.7%
1 26
 
4.1%
2 3
 
0.5%
3 1
 
0.2%

Length

2024-05-11T17:30:41.110306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:41.203251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 567
89.6%
0 36
 
5.7%
1 26
 
4.1%
2 3
 
0.5%
3 1
 
0.2%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
571 
0
62 

Length

Max length4
Median length4
Mean length3.7061611
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> 571
90.2%
0 62
 
9.8%

Length

2024-05-11T17:30:41.303488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:41.391784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 571
90.2%
0 62
 
9.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing113
Missing (%)17.9%
Memory size1.4 KiB
False
520 
(Missing)
113 
ValueCountFrequency (%)
False 520
82.1%
(Missing) 113
 
17.9%
2024-05-11T17:30:41.457917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031600003160000-205-1985-0178919850625<NA>3폐업2폐업20160926<NA><NA><NA>020613220126.4152810서울특별시 구로구 개봉동 262-18번지서울특별시 구로구 개봉로16길 37-3 (개봉동)8332백광사2004-12-16 00:00:00I2018-08-31 23:59:59.0일반세탁업187392.547553443131.763881일반세탁업2111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
131600003160000-205-1987-0173819870421<NA>3폐업2폐업19940521<NA><NA><NA>02 85450750.0152880서울특별시 구로구 구로동 1129-19번지<NA><NA>동명사2001-09-26 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
231600003160000-205-1987-0173919870430<NA>3폐업2폐업20030213<NA><NA><NA>02000000000.0152888서울특별시 구로구 신도림동 439-16번지<NA><NA>익영사2003-02-13 00:00:00I2018-08-31 23:59:59.0일반세탁업189721.067422444881.866521일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331600003160000-205-1987-0174019870519<NA>3폐업2폐업19960729<NA><NA><NA>02 86316210.0152856서울특별시 구로구 구로동 442-46번지<NA><NA>영동사2001-09-26 00:00:00I2018-08-31 23:59:59.0일반세탁업189969.529776443973.012422일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431600003160000-205-1987-0174119870519<NA>3폐업2폐업19990513<NA><NA><NA>02 00.0152886서울특별시 구로구 신도림동 292-45번지<NA><NA>백조사2001-09-26 00:00:00I2018-08-31 23:59:59.0일반세탁업189162.246075445221.889843일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531600003160000-205-1987-0174219870519<NA>3폐업2폐업19960626<NA><NA><NA>02 86312450.0152862서울특별시 구로구 구로동 571-16번지<NA><NA>세림사2001-09-26 00:00:00I2018-08-31 23:59:59.0일반세탁업189728.257578444488.556949일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631600003160000-205-1987-0174319870519<NA>3폐업2폐업19970605<NA><NA><NA>02 85313530.0152862서울특별시 구로구 구로동 551-62번지<NA><NA>신흥사2001-09-26 00:00:00I2018-08-31 23:59:59.0일반세탁업189808.078111444462.51487일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731600003160000-205-1987-0174419870605<NA>3폐업2폐업20020213<NA><NA><NA>02085443080.0152871서울특별시 구로구 구로동 720-24번지<NA><NA>한성사2003-02-13 00:00:00I2018-08-31 23:59:59.0일반세탁업189670.905565442863.104187일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831600003160000-205-1987-0174519870605<NA>3폐업2폐업19960506<NA><NA><NA>02 86348490.0152871서울특별시 구로구 구로동 726-32번지<NA><NA>시민사2001-09-26 00:00:00I2018-08-31 23:59:59.0일반세탁업189642.1481443090.245179일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931600003160000-205-1987-017461987-06-05<NA>3폐업2폐업2023-09-04<NA><NA><NA>02 855934413.2152-845서울특별시 구로구 구로동 129-23서울특별시 구로구 구로중앙로12길 21 (구로동)8304희망사2023-09-04 16:02:48U2022-12-09 00:06:00.0일반세탁업190418.75156443402.628598<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
62331600003160000-205-2019-0000120190909<NA>3폐업2폐업20210914<NA><NA><NA><NA>48.4152846서울특별시 구로구 구로동 136-34 서준빌딩서울특별시 구로구 구로중앙로 35, 서준빌딩 1층 (구로동)8306제니크린2021-09-14 10:12:26U2021-09-16 02:40:00.0일반세탁업190232.2836443416.936388일반세탁업000000000N0<NA><NA><NA><NA>10010N
62431600003160000-205-2020-0000120200706<NA>3폐업2폐업20220822<NA><NA><NA><NA>33.0152801서울특별시 구로구 가리봉동 127-2서울특별시 구로구 남부순환로105라길 20, 1층 (가리봉동)8387쌍둥이 세탁소2022-08-22 13:30:52U2021-12-07 22:04:00.0일반세탁업190174.027552442031.723667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62531600003160000-205-2020-0000220200915<NA>1영업/정상1영업<NA><NA><NA><NA>070 8283390993.0152906서울특별시 구로구 온수동 118-4 온수탑빌딩서울특별시 구로구 부일로1가길 25, 온수탑빌딩 1층 102호 및 103호 (온수동)8261유모차(UMOCHA)2020-09-15 15:07:03I2020-09-17 00:23:12.0일반세탁업183969.570522443237.956199일반세탁업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>20000N
62631600003160000-205-2021-0000120210326<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.86152825서울특별시 구로구 고척동 60-34 제니스스포츠클럽 A동서울특별시 구로구 안양천로539길 11, 제니스스포츠클럽 A동 1층 (고척동)8220스포츠 워시 하키2021-03-26 15:32:37I2021-03-28 00:22:59.0일반세탁업188459.808425444722.121127일반세탁업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>20000N
62731600003160000-205-2021-0000220211210<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0152815서울특별시 구로구 개봉동 359-5서울특별시 구로구 개봉로3길 17, 1층 (개봉동)8353운동화손세탁이불2022-07-15 14:22:48U2021-12-06 23:07:00.0운동화전문세탁업187136.551672442681.742372<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62831600003160000-205-2022-0000120220105<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.65152090서울특별시 구로구 개봉동 476 한마을아파트서울특별시 구로구 경인로 382, 제상가1동 108호 (개봉동, 한마을아파트)8275모아세탁2022-07-15 14:04:32U2021-12-06 23:07:00.0일반세탁업187771.039016443682.345374<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62931600003160000-205-2022-000022022-05-03<NA>3폐업2폐업2024-03-11<NA><NA><NA>02 853927427.0152-844서울특별시 구로구 구로동 112-2 102호서울특별시 구로구 공원로7길 37, 102호 (구로동)8294드림세탁소2024-03-11 12:51:49U2023-12-02 23:03:00.0일반세탁업189958.627837444352.491698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63031600003160000-205-2023-0000120230102<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.49152720서울특별시 구로구 구로동 650-4 SK허브수 A동 110호서울특별시 구로구 구일로10길 27, SK허브수 A동 110호 (구로동)8323세탁1192023-01-02 12:35:02I2022-12-01 00:04:00.0일반세탁업188674.995072443749.50302<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63131600003160000-205-2023-000022023-06-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0152-841서울특별시 구로구 구로동 95-9 101호서울특별시 구로구 구로중앙로18길 44, 1층 101호 (구로동)8303참조은세탁2023-06-02 13:50:47I2022-12-06 00:04:00.0운동화전문세탁업190350.71869443717.368678<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63231600003160000-205-2023-000032023-08-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>184.96152-883서울특별시 구로구 궁동 204-9서울특별시 구로구 부일로 951, 지층(동쪽),2층 201(동쪽),202(서쪽)호 (궁동)8256세탁좋은날2023-08-02 14:03:39I2022-12-08 00:04:00.0일반세탁업185161.368667443476.111617<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>