Overview

Dataset statistics

Number of variables47
Number of observations810
Missing cells8131
Missing cells (%)21.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory320.5 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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-17972/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (86.9%)Imbalance
위생업태명 is highly imbalanced (72.3%)Imbalance
사용끝지하층 is highly imbalanced (66.7%)Imbalance
여성종사자수 is highly imbalanced (78.4%)Imbalance
남성종사자수 is highly imbalanced (67.1%)Imbalance
회수건조수 is highly imbalanced (62.0%)Imbalance
인허가취소일자 has 810 (100.0%) missing valuesMissing
폐업일자 has 199 (24.6%) missing valuesMissing
휴업시작일자 has 810 (100.0%) missing valuesMissing
휴업종료일자 has 810 (100.0%) missing valuesMissing
재개업일자 has 810 (100.0%) missing valuesMissing
전화번호 has 68 (8.4%) missing valuesMissing
도로명주소 has 410 (50.6%) missing valuesMissing
도로명우편번호 has 412 (50.9%) missing valuesMissing
좌표정보(X) has 24 (3.0%) missing valuesMissing
좌표정보(Y) has 24 (3.0%) missing valuesMissing
건물지상층수 has 211 (26.0%) missing valuesMissing
건물지하층수 has 369 (45.6%) missing valuesMissing
발한실여부 has 71 (8.8%) missing valuesMissing
조건부허가신고사유 has 810 (100.0%) missing valuesMissing
조건부허가시작일자 has 810 (100.0%) missing valuesMissing
조건부허가종료일자 has 810 (100.0%) missing valuesMissing
세탁기수 has 610 (75.3%) missing valuesMissing
다중이용업소여부 has 63 (7.8%) 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
소재지면적 has 283 (34.9%) zerosZeros
건물지상층수 has 207 (25.6%) zerosZeros
건물지하층수 has 252 (31.1%) zerosZeros
세탁기수 has 63 (7.8%) zerosZeros

Reproduction

Analysis started2024-04-29 19:31:56.709528
Analysis finished2024-04-29 19:31:57.757106
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3200000
810 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 810
100.0%

Length

2024-04-30T04:31:57.832577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:57.913980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 810
100.0%

관리번호
Text

UNIQUE 

Distinct810
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-30T04:31:58.062600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters17820
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

Unique810 ?
Unique (%)100.0%

Sample

1st row3200000-205-1982-00001
2nd row3200000-205-1987-02667
3rd row3200000-205-1987-02668
4th row3200000-205-1987-02669
5th row3200000-205-1987-02670
ValueCountFrequency (%)
3200000-205-1982-00001 1
 
0.1%
3200000-205-2001-00017 1
 
0.1%
3200000-205-2001-00006 1
 
0.1%
3200000-205-2001-00007 1
 
0.1%
3200000-205-2002-00013 1
 
0.1%
3200000-205-2001-00008 1
 
0.1%
3200000-205-2001-00009 1
 
0.1%
3200000-205-2001-00012 1
 
0.1%
3200000-205-2001-00013 1
 
0.1%
3200000-205-2001-00014 1
 
0.1%
Other values (800) 800
98.8%
2024-04-30T04:31:58.350732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7085
39.8%
2 2664
 
14.9%
- 2430
 
13.6%
5 1129
 
6.3%
9 1075
 
6.0%
3 1056
 
5.9%
1 879
 
4.9%
8 532
 
3.0%
7 452
 
2.5%
6 300
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15390
86.4%
Dash Punctuation 2430
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7085
46.0%
2 2664
 
17.3%
5 1129
 
7.3%
9 1075
 
7.0%
3 1056
 
6.9%
1 879
 
5.7%
8 532
 
3.5%
7 452
 
2.9%
6 300
 
1.9%
4 218
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7085
39.8%
2 2664
 
14.9%
- 2430
 
13.6%
5 1129
 
6.3%
9 1075
 
6.0%
3 1056
 
5.9%
1 879
 
4.9%
8 532
 
3.0%
7 452
 
2.5%
6 300
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7085
39.8%
2 2664
 
14.9%
- 2430
 
13.6%
5 1129
 
6.3%
9 1075
 
6.0%
3 1056
 
5.9%
1 879
 
4.9%
8 532
 
3.0%
7 452
 
2.5%
6 300
 
1.7%

인허가일자
Date

Distinct556
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1982-11-09 00:00:00
Maximum2024-02-21 00:00:00
2024-04-30T04:31:58.480726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:58.618175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3
611 
1
199 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 611
75.4%
1 199
 
24.6%

Length

2024-04-30T04:31:58.719389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:58.810447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 611
75.4%
1 199
 
24.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
611 
영업/정상
199 

Length

Max length5
Median length2
Mean length2.737037
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 611
75.4%
영업/정상 199
 
24.6%

Length

2024-04-30T04:31:58.917234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:59.004341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 611
75.4%
영업/정상 199
 
24.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2
611 
1
199 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 611
75.4%
1 199
 
24.6%

Length

2024-04-30T04:31:59.085707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:59.165422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 611
75.4%
1 199
 
24.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
611 
영업
199 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 611
75.4%
영업 199
 
24.6%

Length

2024-04-30T04:31:59.245227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:31:59.359793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 611
75.4%
영업 199
 
24.6%

폐업일자
Date

MISSING 

Distinct478
Distinct (%)78.2%
Missing199
Missing (%)24.6%
Memory size6.5 KiB
Minimum1994-09-27 00:00:00
Maximum2024-03-19 00:00:00
2024-04-30T04:31:59.462389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:31:59.581837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

전화번호
Text

MISSING 

Distinct601
Distinct (%)81.0%
Missing68
Missing (%)8.4%
Memory size6.5 KiB
2024-04-30T04:31:59.795212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.5350404
Min length2

Characters and Unicode

Total characters7075
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique556 ?
Unique (%)74.9%

Sample

1st row02 8625080
2nd row02 0
3rd row02 8893929
4th row02 8838140
5th row02 0
ValueCountFrequency (%)
02 702
47.6%
0 94
 
6.4%
888 3
 
0.2%
878 3
 
0.2%
882 3
 
0.2%
876 3
 
0.2%
8843872 3
 
0.2%
8880309 3
 
0.2%
8784121 3
 
0.2%
8868510 2
 
0.1%
Other values (613) 657
44.5%
2024-04-30T04:32:00.135765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1289
18.2%
0 1137
16.1%
2 1095
15.5%
957
13.5%
7 515
 
7.3%
6 403
 
5.7%
3 378
 
5.3%
5 375
 
5.3%
4 348
 
4.9%
9 289
 
4.1%
Other values (2) 289
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6117
86.5%
Space Separator 957
 
13.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1289
21.1%
0 1137
18.6%
2 1095
17.9%
7 515
 
8.4%
6 403
 
6.6%
3 378
 
6.2%
5 375
 
6.1%
4 348
 
5.7%
9 289
 
4.7%
1 288
 
4.7%
Space Separator
ValueCountFrequency (%)
957
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7075
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1289
18.2%
0 1137
16.1%
2 1095
15.5%
957
13.5%
7 515
 
7.3%
6 403
 
5.7%
3 378
 
5.3%
5 375
 
5.3%
4 348
 
4.9%
9 289
 
4.1%
Other values (2) 289
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7075
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1289
18.2%
0 1137
16.1%
2 1095
15.5%
957
13.5%
7 515
 
7.3%
6 403
 
5.7%
3 378
 
5.3%
5 375
 
5.3%
4 348
 
4.9%
9 289
 
4.1%
Other values (2) 289
 
4.1%

소재지면적
Real number (ℝ)

ZEROS 

Distinct224
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.053877
Minimum0
Maximum434.28
Zeros283
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:00.278632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20.49
Q332.565
95-th percentile59.328
Maximum434.28
Range434.28
Interquartile range (IQR)32.565

Descriptive statistics

Standard deviation29.128642
Coefficient of variation (CV)1.3207946
Kurtosis64.849597
Mean22.053877
Median Absolute Deviation (MAD)16.025
Skewness5.9042447
Sum17863.64
Variance848.47777
MonotonicityNot monotonic
2024-04-30T04:32:00.407326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 283
34.9%
33.0 58
 
7.2%
26.4 42
 
5.2%
23.1 28
 
3.5%
19.8 19
 
2.3%
39.6 14
 
1.7%
24.0 14
 
1.7%
30.0 14
 
1.7%
20.0 13
 
1.6%
29.7 11
 
1.4%
Other values (214) 314
38.8%
ValueCountFrequency (%)
0.0 283
34.9%
6.67 1
 
0.1%
9.6 1
 
0.1%
9.9 1
 
0.1%
10.66 1
 
0.1%
11.04 1
 
0.1%
11.5 1
 
0.1%
11.84 1
 
0.1%
12.0 4
 
0.5%
12.26 1
 
0.1%
ValueCountFrequency (%)
434.28 1
0.1%
311.25 1
0.1%
199.24 1
0.1%
172.74 1
0.1%
171.76 1
0.1%
165.29 1
0.1%
132.0 2
0.2%
125.36 1
0.1%
120.0 1
0.1%
111.0 1
0.1%

소재지우편번호
Text

Distinct132
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-30T04:32:00.640830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.037037
Min length6

Characters and Unicode

Total characters4890
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

Unique35 ?
Unique (%)4.3%

Sample

1st row151888
2nd row151837
3rd row151846
4th row151821
5th row151895
ValueCountFrequency (%)
151050 34
 
4.2%
151015 25
 
3.1%
151903 18
 
2.2%
151859 17
 
2.1%
151895 16
 
2.0%
151803 15
 
1.9%
151845 14
 
1.7%
151802 14
 
1.7%
151809 14
 
1.7%
151893 14
 
1.7%
Other values (122) 629
77.7%
2024-04-30T04:32:00.997833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1803
36.9%
5 1035
21.2%
8 801
16.4%
0 278
 
5.7%
9 232
 
4.7%
3 169
 
3.5%
2 156
 
3.2%
4 143
 
2.9%
7 126
 
2.6%
6 117
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4860
99.4%
Dash Punctuation 30
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1803
37.1%
5 1035
21.3%
8 801
16.5%
0 278
 
5.7%
9 232
 
4.8%
3 169
 
3.5%
2 156
 
3.2%
4 143
 
2.9%
7 126
 
2.6%
6 117
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1803
36.9%
5 1035
21.2%
8 801
16.4%
0 278
 
5.7%
9 232
 
4.7%
3 169
 
3.5%
2 156
 
3.2%
4 143
 
2.9%
7 126
 
2.6%
6 117
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1803
36.9%
5 1035
21.2%
8 801
16.4%
0 278
 
5.7%
9 232
 
4.7%
3 169
 
3.5%
2 156
 
3.2%
4 143
 
2.9%
7 126
 
2.6%
6 117
 
2.4%

지번주소
Text

Distinct747
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-30T04:32:01.240568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length24.188889
Min length17

Characters and Unicode

Total characters19593
Distinct characters117
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

Unique689 ?
Unique (%)85.1%

Sample

1st row서울특별시 관악구 신림동 607-83번지
2nd row서울특별시 관악구 봉천동 885-7번지
3rd row서울특별시 관악구 봉천동 1588-32
4th row서울특별시 관악구 봉천동 670-62 지하1층
5th row서울특별시 관악구 신림동 1522-5번지
ValueCountFrequency (%)
서울특별시 810
23.2%
관악구 810
23.2%
신림동 431
12.3%
봉천동 352
 
10.1%
1층 49
 
1.4%
남현동 27
 
0.8%
상가동 7
 
0.2%
2층 6
 
0.2%
1706번지 5
 
0.1%
101호 5
 
0.1%
Other values (830) 990
28.4%
2024-04-30T04:32:01.599115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3399
 
17.3%
1 1026
 
5.2%
동 856
 
4.4%
관 820
 
4.2%
악 820
 
4.2%
시 812
 
4.1%
서 810
 
4.1%
울 810
 
4.1%
특 810
 
4.1%
별 810
 
4.1%
Other values (107) 8620
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11026
56.3%
Decimal Number 4344
 
22.2%
Space Separator 3399
 
17.3%
Dash Punctuation 759
 
3.9%
Uppercase Letter 22
 
0.1%
Open Punctuation 18
 
0.1%
Close Punctuation 18
 
0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 856
 
7.8%
관 820
 
7.4%
악 820
 
7.4%
시 812
 
7.4%
서 810
 
7.3%
울 810
 
7.3%
특 810
 
7.3%
별 810
 
7.3%
구 810
 
7.3%
지 722
 
6.5%
Other values (85) 2946
26.7%
Decimal Number
ValueCountFrequency (%)
1 1026
23.6%
2 472
10.9%
6 456
10.5%
5 448
10.3%
0 385
 
8.9%
3 376
 
8.7%
4 359
 
8.3%
7 301
 
6.9%
8 266
 
6.1%
9 255
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 11
50.0%
B 7
31.8%
R 1
 
4.5%
D 1
 
4.5%
P 1
 
4.5%
T 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
3399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 759
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11026
56.3%
Common 8545
43.6%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 856
 
7.8%
관 820
 
7.4%
악 820
 
7.4%
시 812
 
7.4%
서 810
 
7.3%
울 810
 
7.3%
특 810
 
7.3%
별 810
 
7.3%
구 810
 
7.3%
지 722
 
6.5%
Other values (85) 2946
26.7%
Common
ValueCountFrequency (%)
3399
39.8%
1 1026
 
12.0%
- 759
 
8.9%
2 472
 
5.5%
6 456
 
5.3%
5 448
 
5.2%
0 385
 
4.5%
3 376
 
4.4%
4 359
 
4.2%
7 301
 
3.5%
Other values (6) 564
 
6.6%
Latin
ValueCountFrequency (%)
A 11
50.0%
B 7
31.8%
R 1
 
4.5%
D 1
 
4.5%
P 1
 
4.5%
T 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11026
56.3%
ASCII 8567
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3399
39.7%
1 1026
 
12.0%
- 759
 
8.9%
2 472
 
5.5%
6 456
 
5.3%
5 448
 
5.2%
0 385
 
4.5%
3 376
 
4.4%
4 359
 
4.2%
7 301
 
3.5%
Other values (12) 586
 
6.8%
Hangul
ValueCountFrequency (%)
동 856
 
7.8%
관 820
 
7.4%
악 820
 
7.4%
시 812
 
7.4%
서 810
 
7.3%
울 810
 
7.3%
특 810
 
7.3%
별 810
 
7.3%
구 810
 
7.3%
지 722
 
6.5%
Other values (85) 2946
26.7%

도로명주소
Text

MISSING 

Distinct397
Distinct (%)99.2%
Missing410
Missing (%)50.6%
Memory size6.5 KiB
2024-04-30T04:32:01.844198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length28.4175
Min length21

Characters and Unicode

Total characters11367
Distinct characters158
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

Unique394 ?
Unique (%)98.5%

Sample

1st row서울특별시 관악구 쑥고개로30길 22 (봉천동)
2nd row서울특별시 관악구 봉천로13가길 3 (봉천동, 지하1층)
3rd row서울특별시 관악구 조원로2길 26, 1층 102호 (신림동)
4th row서울특별시 관악구 봉천로23나길 52 (봉천동)
5th row서울특별시 관악구 국회단지길 48 (봉천동)
ValueCountFrequency (%)
서울특별시 400
17.8%
관악구 400
17.8%
신림동 199
 
8.9%
봉천동 151
 
6.7%
1층 73
 
3.3%
12 12
 
0.5%
22 10
 
0.4%
27 10
 
0.4%
2층 9
 
0.4%
25 9
 
0.4%
Other values (503) 972
43.3%
2024-04-30T04:32:02.249352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1845
 
16.2%
1 456
 
4.0%
관 455
 
4.0%
동 448
 
3.9%
악 442
 
3.9%
( 413
 
3.6%
) 413
 
3.6%
서 405
 
3.6%
시 404
 
3.6%
구 404
 
3.6%
Other values (148) 5682
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6721
59.1%
Space Separator 1845
 
16.2%
Decimal Number 1740
 
15.3%
Open Punctuation 413
 
3.6%
Close Punctuation 413
 
3.6%
Other Punctuation 192
 
1.7%
Dash Punctuation 23
 
0.2%
Uppercase Letter 19
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 455
 
6.8%
동 448
 
6.7%
악 442
 
6.6%
서 405
 
6.0%
시 404
 
6.0%
구 404
 
6.0%
울 400
 
6.0%
별 400
 
6.0%
특 400
 
6.0%
길 335
 
5.0%
Other values (125) 2628
39.1%
Decimal Number
ValueCountFrequency (%)
1 456
26.2%
2 302
17.4%
3 201
11.6%
0 172
 
9.9%
4 134
 
7.7%
6 125
 
7.2%
5 117
 
6.7%
8 88
 
5.1%
7 87
 
5.0%
9 58
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 8
42.1%
A 7
36.8%
P 1
 
5.3%
R 1
 
5.3%
D 1
 
5.3%
T 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 191
99.5%
. 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1845
100.0%
Open Punctuation
ValueCountFrequency (%)
( 413
100.0%
Close Punctuation
ValueCountFrequency (%)
) 413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6721
59.1%
Common 4627
40.7%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 455
 
6.8%
동 448
 
6.7%
악 442
 
6.6%
서 405
 
6.0%
시 404
 
6.0%
구 404
 
6.0%
울 400
 
6.0%
별 400
 
6.0%
특 400
 
6.0%
길 335
 
5.0%
Other values (125) 2628
39.1%
Common
ValueCountFrequency (%)
1845
39.9%
1 456
 
9.9%
( 413
 
8.9%
) 413
 
8.9%
2 302
 
6.5%
3 201
 
4.3%
, 191
 
4.1%
0 172
 
3.7%
4 134
 
2.9%
6 125
 
2.7%
Other values (7) 375
 
8.1%
Latin
ValueCountFrequency (%)
B 8
42.1%
A 7
36.8%
P 1
 
5.3%
R 1
 
5.3%
D 1
 
5.3%
T 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6721
59.1%
ASCII 4646
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1845
39.7%
1 456
 
9.8%
( 413
 
8.9%
) 413
 
8.9%
2 302
 
6.5%
3 201
 
4.3%
, 191
 
4.1%
0 172
 
3.7%
4 134
 
2.9%
6 125
 
2.7%
Other values (13) 394
 
8.5%
Hangul
ValueCountFrequency (%)
관 455
 
6.8%
동 448
 
6.7%
악 442
 
6.6%
서 405
 
6.0%
시 404
 
6.0%
구 404
 
6.0%
울 400
 
6.0%
별 400
 
6.0%
특 400
 
6.0%
길 335
 
5.0%
Other values (125) 2628
39.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)32.9%
Missing412
Missing (%)50.9%
Infinite0
Infinite (%)0.0%
Mean8781.6558
Minimum8701
Maximum8866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:02.380497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8701
5-th percentile8707
Q18741.25
median8779.5
Q38821
95-th percentile8858
Maximum8866
Range165
Interquartile range (IQR)79.75

Descriptive statistics

Standard deviation48.043427
Coefficient of variation (CV)0.0054708848
Kurtosis-1.1372216
Mean8781.6558
Median Absolute Deviation (MAD)39.5
Skewness0.098755996
Sum3495099
Variance2308.1709
MonotonicityNot monotonic
2024-04-30T04:32:02.667325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8846 9
 
1.1%
8762 8
 
1.0%
8784 8
 
1.0%
8771 7
 
0.9%
8786 7
 
0.9%
8748 7
 
0.9%
8819 6
 
0.7%
8848 6
 
0.7%
8755 6
 
0.7%
8740 6
 
0.7%
Other values (121) 328
40.5%
(Missing) 412
50.9%
ValueCountFrequency (%)
8701 3
0.4%
8702 4
0.5%
8703 2
0.2%
8704 3
0.4%
8705 3
0.4%
8706 4
0.5%
8707 3
0.4%
8709 2
0.2%
8710 1
 
0.1%
8711 4
0.5%
ValueCountFrequency (%)
8866 1
 
0.1%
8865 3
0.4%
8864 2
 
0.2%
8863 3
0.4%
8862 3
0.4%
8860 1
 
0.1%
8859 5
0.6%
8858 3
0.4%
8857 4
0.5%
8856 5
0.6%

사업장명
Text

Distinct566
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-30T04:32:02.943630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length4.1111111
Min length2

Characters and Unicode

Total characters3330
Distinct characters289
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)54.7%

Sample

1st row신림태양
2nd row한양사
3rd row백합사
4th row조양컴퓨터세탁
5th row백성사
ValueCountFrequency (%)
백양사 16
 
1.9%
현대사 14
 
1.6%
백영사 11
 
1.3%
백성사 8
 
0.9%
세탁소 8
 
0.9%
월풀빨래방 7
 
0.8%
명동사 6
 
0.7%
현대세탁 6
 
0.7%
일광사 6
 
0.7%
백양세탁 5
 
0.6%
Other values (572) 763
89.8%
2024-04-30T04:32:03.318235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 318
 
9.5%
세 275
 
8.3%
탁 267
 
8.0%
소 115
 
3.5%
백 84
 
2.5%
성 76
 
2.3%
크 73
 
2.2%
대 69
 
2.1%
리 65
 
2.0%
방 54
 
1.6%
Other values (279) 1934
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3243
97.4%
Space Separator 40
 
1.2%
Decimal Number 31
 
0.9%
Lowercase Letter 11
 
0.3%
Uppercase Letter 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 318
 
9.8%
세 275
 
8.5%
탁 267
 
8.2%
소 115
 
3.5%
백 84
 
2.6%
성 76
 
2.3%
크 73
 
2.3%
대 69
 
2.1%
리 65
 
2.0%
방 54
 
1.7%
Other values (259) 1847
57.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
18.2%
a 2
18.2%
h 1
9.1%
s 1
9.1%
i 1
9.1%
c 1
9.1%
l 1
9.1%
e 1
9.1%
o 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 11
35.5%
4 10
32.3%
1 5
16.1%
9 4
 
12.9%
6 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
W 1
25.0%
K 1
25.0%
O 1
25.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3243
97.4%
Common 72
 
2.2%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 318
 
9.8%
세 275
 
8.5%
탁 267
 
8.2%
소 115
 
3.5%
백 84
 
2.6%
성 76
 
2.3%
크 73
 
2.3%
대 69
 
2.1%
리 65
 
2.0%
방 54
 
1.7%
Other values (259) 1847
57.0%
Latin
ValueCountFrequency (%)
n 2
13.3%
a 2
13.3%
C 1
 
6.7%
h 1
 
6.7%
s 1
 
6.7%
W 1
 
6.7%
i 1
 
6.7%
K 1
 
6.7%
c 1
 
6.7%
l 1
 
6.7%
Other values (3) 3
20.0%
Common
ValueCountFrequency (%)
40
55.6%
2 11
 
15.3%
4 10
 
13.9%
1 5
 
6.9%
9 4
 
5.6%
6 1
 
1.4%
, 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3243
97.4%
ASCII 87
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 318
 
9.8%
세 275
 
8.5%
탁 267
 
8.2%
소 115
 
3.5%
백 84
 
2.6%
성 76
 
2.3%
크 73
 
2.3%
대 69
 
2.1%
리 65
 
2.0%
방 54
 
1.7%
Other values (259) 1847
57.0%
ASCII
ValueCountFrequency (%)
40
46.0%
2 11
 
12.6%
4 10
 
11.5%
1 5
 
5.7%
9 4
 
4.6%
n 2
 
2.3%
a 2
 
2.3%
C 1
 
1.1%
h 1
 
1.1%
s 1
 
1.1%
Other values (10) 10
 
11.5%

최종수정일자
Date

Distinct485
Distinct (%)59.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1999-05-03 00:00:00
Maximum2024-03-20 15:01:00
2024-04-30T04:32:03.447816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:03.582145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
I
644 
U
166 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 644
79.5%
U 166
 
20.5%

Length

2024-04-30T04:32:03.698113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:03.787554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 644
79.5%
u 166
 
20.5%

데이터갱신일자
Date

Distinct140
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:09:00
2024-04-30T04:32:03.878669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:04.003295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
일반세탁업
781 
빨래방업
 
19
운동화전문세탁업
 
9
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length5.0111111
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 781
96.4%
빨래방업 19
 
2.3%
운동화전문세탁업 9
 
1.1%
세탁업 기타 1
 
0.1%

Length

2024-04-30T04:32:04.143538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:04.244768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 781
96.3%
빨래방업 19
 
2.3%
운동화전문세탁업 9
 
1.1%
세탁업 1
 
0.1%
기타 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct653
Distinct (%)83.1%
Missing24
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean194466.62
Minimum191151.56
Maximum198288.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:04.342049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191151.56
5-th percentile192174.72
Q1193238.6
median194383.87
Q3195599.69
95-th percentile197036.03
Maximum198288.01
Range7136.4537
Interquartile range (IQR)2361.082

Descriptive statistics

Standard deviation1563.5283
Coefficient of variation (CV)0.0080400857
Kurtosis-0.62793164
Mean194466.62
Median Absolute Deviation (MAD)1180.266
Skewness0.19559015
Sum1.5285076 × 108
Variance2444620.7
MonotonicityNot monotonic
2024-04-30T04:32:04.461655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196350.708293561 6
 
0.7%
193957.944323928 5
 
0.6%
196257.833652996 5
 
0.6%
191482.323760618 4
 
0.5%
194577.924146084 4
 
0.5%
195045.515107949 4
 
0.5%
195563.161650411 4
 
0.5%
194969.715720332 3
 
0.4%
195084.631134892 3
 
0.4%
194290.725417009 3
 
0.4%
Other values (643) 745
92.0%
(Missing) 24
 
3.0%
ValueCountFrequency (%)
191151.556121381 1
0.1%
191165.482135481 1
0.1%
191197.279239099 1
0.1%
191228.411082685 1
0.1%
191240.601085883 2
0.2%
191244.074940777 1
0.1%
191267.931278367 1
0.1%
191271.013025107 1
0.1%
191306.065659 1
0.1%
191389.450907979 1
0.1%
ValueCountFrequency (%)
198288.009848713 1
0.1%
198220.406233499 1
0.1%
198206.437327566 1
0.1%
198099.509961504 1
0.1%
198016.966616995 2
0.2%
198005.940059879 1
0.1%
197998.032358432 1
0.1%
197967.638880255 1
0.1%
197932.052774817 1
0.1%
197895.722663856 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct653
Distinct (%)83.1%
Missing24
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean441870.74
Minimum439663.59
Maximum443547.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:04.604666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439663.59
5-th percentile440483.08
Q1441255.79
median442008.67
Q3442532.44
95-th percentile443056.96
Maximum443547.05
Range3883.4641
Interquartile range (IQR)1276.6462

Descriptive statistics

Standard deviation822.23443
Coefficient of variation (CV)0.0018608031
Kurtosis-0.67761218
Mean441870.74
Median Absolute Deviation (MAD)616.12336
Skewness-0.3540002
Sum3.473104 × 108
Variance676069.46
MonotonicityNot monotonic
2024-04-30T04:32:04.740654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442532.440501316 6
 
0.7%
441437.774867372 5
 
0.6%
443341.379446435 5
 
0.6%
442299.546196793 4
 
0.5%
442073.476608666 4
 
0.5%
443011.455007816 4
 
0.5%
443064.437566493 4
 
0.5%
442811.136885268 3
 
0.4%
442661.670322754 3
 
0.4%
440567.154669883 3
 
0.4%
Other values (643) 745
92.0%
(Missing) 24
 
3.0%
ValueCountFrequency (%)
439663.585570958 1
 
0.1%
439787.715563055 3
0.4%
439853.488919065 2
0.2%
439885.315238411 2
0.2%
439898.027808319 1
 
0.1%
439930.472976395 1
 
0.1%
440039.102875244 2
0.2%
440040.309820942 2
0.2%
440058.926731613 1
 
0.1%
440063.920325898 1
 
0.1%
ValueCountFrequency (%)
443547.049696825 2
 
0.2%
443437.692580028 1
 
0.1%
443341.379446435 5
0.6%
443318.975050877 1
 
0.1%
443290.713662991 2
 
0.2%
443287.794417958 1
 
0.1%
443273.487218185 2
 
0.2%
443270.944256046 1
 
0.1%
443249.486620296 1
 
0.1%
443238.64427036 1
 
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
일반세탁업
719 
<NA>
 
63
빨래방업
 
19
운동화전문세탁업
 
8
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.9296296
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 719
88.8%
<NA> 63
 
7.8%
빨래방업 19
 
2.3%
운동화전문세탁업 8
 
1.0%
세탁업 기타 1
 
0.1%

Length

2024-04-30T04:32:04.862571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:04.978506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 719
88.7%
na 63
 
7.8%
빨래방업 19
 
2.3%
운동화전문세탁업 8
 
1.0%
세탁업 1
 
0.1%
기타 1
 
0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)1.8%
Missing211
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean1.8631052
Minimum0
Maximum18
Zeros207
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:05.081161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile5
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0053335
Coefficient of variation (CV)1.0763394
Kurtosis15.224186
Mean1.8631052
Median Absolute Deviation (MAD)2
Skewness2.53068
Sum1116
Variance4.0213622
MonotonicityNot monotonic
2024-04-30T04:32:05.191888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 207
25.6%
2 121
14.9%
3 88
10.9%
4 77
 
9.5%
1 70
 
8.6%
5 23
 
2.8%
6 9
 
1.1%
17 1
 
0.1%
13 1
 
0.1%
15 1
 
0.1%
(Missing) 211
26.0%
ValueCountFrequency (%)
0 207
25.6%
1 70
 
8.6%
2 121
14.9%
3 88
10.9%
4 77
 
9.5%
5 23
 
2.8%
6 9
 
1.1%
13 1
 
0.1%
15 1
 
0.1%
17 1
 
0.1%
ValueCountFrequency (%)
18 1
 
0.1%
17 1
 
0.1%
15 1
 
0.1%
13 1
 
0.1%
6 9
 
1.1%
5 23
 
2.8%
4 77
9.5%
3 88
10.9%
2 121
14.9%
1 70
8.6%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.4%
Missing369
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean0.47165533
Minimum0
Maximum5
Zeros252
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:05.303038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.62503762
Coefficient of variation (CV)1.3252
Kurtosis8.4088738
Mean0.47165533
Median Absolute Deviation (MAD)0
Skewness1.9307553
Sum208
Variance0.39067203
MonotonicityNot monotonic
2024-04-30T04:32:05.390171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 252
31.1%
1 178
22.0%
2 6
 
0.7%
3 3
 
0.4%
4 1
 
0.1%
5 1
 
0.1%
(Missing) 369
45.6%
ValueCountFrequency (%)
0 252
31.1%
1 178
22.0%
2 6
 
0.7%
3 3
 
0.4%
4 1
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 1
 
0.1%
3 3
 
0.4%
2 6
 
0.7%
1 178
22.0%
0 252
31.1%

사용시작지상층
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
1
396 
<NA>
226 
0
156 
2
 
25
3
 
5

Length

Max length4
Median length1
Mean length1.837037
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 396
48.9%
<NA> 226
27.9%
0 156
 
19.3%
2 25
 
3.1%
3 5
 
0.6%
4 2
 
0.2%

Length

2024-04-30T04:32:05.491216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:05.588769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 396
48.9%
na 226
27.9%
0 156
 
19.3%
2 25
 
3.1%
3 5
 
0.6%
4 2
 
0.2%

사용끝지상층
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
1
412 
<NA>
350 
2
 
24
0
 
17
3
 
5

Length

Max length4
Median length1
Mean length2.2962963
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 412
50.9%
<NA> 350
43.2%
2 24
 
3.0%
0 17
 
2.1%
3 5
 
0.6%
4 2
 
0.2%

Length

2024-04-30T04:32:05.693269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:05.797192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 412
50.9%
na 350
43.2%
2 24
 
3.0%
0 17
 
2.1%
3 5
 
0.6%
4 2
 
0.2%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
566 
0
219 
1
 
24
2
 
1

Length

Max length4
Median length4
Mean length3.0962963
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 566
69.9%
0 219
 
27.0%
1 24
 
3.0%
2 1
 
0.1%

Length

2024-04-30T04:32:05.904527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:06.015147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 566
69.9%
0 219
 
27.0%
1 24
 
3.0%
2 1
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
705 
0
80 
1
 
24
2
 
1

Length

Max length4
Median length4
Mean length3.6111111
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 705
87.0%
0 80
 
9.9%
1 24
 
3.0%
2 1
 
0.1%

Length

2024-04-30T04:32:06.129369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:06.245425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 705
87.0%
0 80
 
9.9%
1 24
 
3.0%
2 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
495 
0
315 

Length

Max length4
Median length4
Mean length2.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 495
61.1%
0 315
38.9%

Length

2024-04-30T04:32:06.359470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:06.467911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 495
61.1%
0 315
38.9%

양실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
495 
0
315 

Length

Max length4
Median length4
Mean length2.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 495
61.1%
0 315
38.9%

Length

2024-04-30T04:32:06.573790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:06.671870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 495
61.1%
0 315
38.9%

욕실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
495 
0
315 

Length

Max length4
Median length4
Mean length2.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 495
61.1%
0 315
38.9%

Length

2024-04-30T04:32:06.762804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:06.869306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 495
61.1%
0 315
38.9%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing71
Missing (%)8.8%
Memory size1.7 KiB
False
739 
(Missing)
 
71
ValueCountFrequency (%)
False 739
91.2%
(Missing) 71
 
8.8%
2024-04-30T04:32:06.947622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
495 
0
315 

Length

Max length4
Median length4
Mean length2.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 495
61.1%
0 315
38.9%

Length

2024-04-30T04:32:07.037302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:07.130743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 495
61.1%
0 315
38.9%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
602 
임대
197 
자가
 
11

Length

Max length4
Median length4
Mean length3.4864198
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> 602
74.3%
임대 197
 
24.3%
자가 11
 
1.4%

Length

2024-04-30T04:32:07.237329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:07.349602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 602
74.3%
임대 197
 
24.3%
자가 11
 
1.4%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)4.0%
Missing610
Missing (%)75.3%
Infinite0
Infinite (%)0.0%
Mean1.425
Minimum0
Maximum11
Zeros63
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-30T04:32:07.435268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4542867
Coefficient of variation (CV)1.0205521
Kurtosis8.631788
Mean1.425
Median Absolute Deviation (MAD)1
Skewness1.9226455
Sum285
Variance2.1149497
MonotonicityNot monotonic
2024-04-30T04:32:07.737610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 63
 
7.8%
1 54
 
6.7%
2 42
 
5.2%
3 29
 
3.6%
4 7
 
0.9%
5 3
 
0.4%
11 1
 
0.1%
6 1
 
0.1%
(Missing) 610
75.3%
ValueCountFrequency (%)
0 63
7.8%
1 54
6.7%
2 42
5.2%
3 29
3.6%
4 7
 
0.9%
5 3
 
0.4%
6 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
6 1
 
0.1%
5 3
 
0.4%
4 7
 
0.9%
3 29
3.6%
2 42
5.2%
1 54
6.7%
0 63
7.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
760 
0
 
49
1
 
1

Length

Max length4
Median length4
Mean length3.8148148
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 760
93.8%
0 49
 
6.0%
1 1
 
0.1%

Length

2024-04-30T04:32:07.850987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:07.940474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 760
93.8%
0 49
 
6.0%
1 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
761 
0
 
49

Length

Max length4
Median length4
Mean length3.8185185
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 761
94.0%
0 49
 
6.0%

Length

2024-04-30T04:32:08.052240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:08.143359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 761
94.0%
0 49
 
6.0%

회수건조수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
643 
0
104 
1
 
56
2
 
3
4
 
3

Length

Max length4
Median length4
Mean length3.3814815
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 643
79.4%
0 104
 
12.8%
1 56
 
6.9%
2 3
 
0.4%
4 3
 
0.4%
3 1
 
0.1%

Length

2024-04-30T04:32:08.239637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:08.349979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 643
79.4%
0 104
 
12.8%
1 56
 
6.9%
2 3
 
0.4%
4 3
 
0.4%
3 1
 
0.1%

침대수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
646 
0
164 

Length

Max length4
Median length4
Mean length3.3925926
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 646
79.8%
0 164
 
20.2%

Length

2024-04-30T04:32:08.466873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:08.557796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 646
79.8%
0 164
 
20.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing63
Missing (%)7.8%
Memory size1.7 KiB
False
747 
(Missing)
 
63
ValueCountFrequency (%)
False 747
92.2%
(Missing) 63
 
7.8%
2024-04-30T04:32:08.626098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032000003200000-205-1982-0000119821109<NA>3폐업2폐업20030430<NA><NA><NA>02 86250800.0151888서울특별시 관악구 신림동 607-83번지<NA><NA>신림태양2003-04-24 00:00:00I2018-08-31 23:59:59.0일반세탁업192663.439417441454.333317일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132000003200000-205-1987-0266719870901<NA>3폐업2폐업20030411<NA><NA><NA>02 00.0151837서울특별시 관악구 봉천동 885-7번지<NA><NA>한양사2003-04-15 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232000003200000-205-1987-0266819870901<NA>3폐업2폐업20211030<NA><NA><NA>02 889392939.6151846서울특별시 관악구 봉천동 1588-32서울특별시 관악구 쑥고개로30길 22 (봉천동)8832백합사2021-10-25 13:47:33U2021-10-27 02:40:00.0일반세탁업195532.631552441742.479999일반세탁업301100000N0<NA><NA><NA><NA>00000N
332000003200000-205-1987-0266919870901<NA>1영업/정상1영업<NA><NA><NA><NA>02 883814034.0151821서울특별시 관악구 봉천동 670-62 지하1층서울특별시 관악구 봉천로13가길 3 (봉천동, 지하1층)8720조양컴퓨터세탁2022-11-09 16:50:54U2021-10-31 23:01:00.0일반세탁업193785.988631442985.601235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
432000003200000-205-1987-0267019870901<NA>3폐업2폐업19970317<NA><NA><NA>02 00.0151895서울특별시 관악구 신림동 1522-5번지<NA><NA>백성사2001-12-03 00:00:00I2018-08-31 23:59:59.0일반세탁업194175.723385440838.133079일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532000003200000-205-1987-0267119870901<NA>3폐업2폐업19970129<NA><NA><NA>02 00.0151895서울특별시 관악구 신림동 1538-1번지<NA><NA>백양사2001-09-29 00:00:00I2018-08-31 23:59:59.0일반세탁업194392.776559440777.949534일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632000003200000-205-1987-0267219870901<NA>3폐업2폐업20030214<NA><NA><NA>02 88775920.0151895서울특별시 관악구 신림동 1524-9번지<NA><NA>광성사2003-02-26 00:00:00I2018-08-31 23:59:59.0일반세탁업194101.184978440870.810556일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732000003200000-205-1987-0267319870901<NA>3폐업2폐업20030430<NA><NA><NA>02 00.0151856서울특별시 관악구 신림동 122-27번지<NA><NA>광명사2003-04-24 00:00:00I2018-08-31 23:59:59.0일반세탁업194487.468199441059.934684일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832000003200000-205-1987-0267419870915<NA>1영업/정상1영업<NA><NA><NA><NA>02 863390631.0151903서울특별시 관악구 신림동 1655-35번지서울특별시 관악구 조원로2길 26, 1층 102호 (신림동)8769제일세탁2019-07-04 13:52:11U2019-07-06 02:40:00.0일반세탁업191267.931278442263.733212일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932000003200000-205-1987-0267519870915<NA>3폐업2폐업20180730<NA><NA><NA>02 88480510.0151913서울특별시 관악구 봉천동 952-9번지서울특별시 관악구 봉천로23나길 52 (봉천동)8717복음세탁소2018-07-30 14:55:56I2018-08-31 23:59:59.0일반세탁업194465.827595442731.37499일반세탁업<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
80032000003200000-205-2020-0000120200924<NA>1영업/정상1영업<NA><NA><NA><NA><NA>171.76151860서울특별시 관악구 신림동 253-8서울특별시 관악구 대학길 90 (신림동)8819화이트크린, 라이프크린2022-03-18 15:35:13U2022-03-20 02:40:00.0일반세탁업194398.040992440500.997607일반세탁업001<NA><NA><NA>000N0<NA><NA><NA><NA>10000N
80132000003200000-205-2020-0000220201013<NA>1영업/정상1영업<NA><NA><NA><NA>02 887235850.0151890서울특별시 관악구 신림동 1420-1서울특별시 관악구 남부순환로185길 33, 1층 (신림동)8754대한민국 세탁소2020-10-13 09:37:37I2020-10-15 00:23:10.0일반세탁업193921.422461442661.192841일반세탁업0011<NA><NA>000N0<NA><NA><NA>임대10010N
80232000003200000-205-2020-000032020-12-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>199.24151-877서울특별시 관악구 신림동 570-2서울특별시 관악구 조원중앙로 24, 1층 (신림동)8765명품위키세탁소2023-08-07 11:07:12U2022-12-08 00:09:00.0일반세탁업191612.791095442164.010289<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
80332000003200000-205-2021-0000120210128<NA>1영업/정상1영업<NA><NA><NA><NA><NA>80.81151849서울특별시 관악구 봉천동 1673-1서울특별시 관악구 남부순환로231길 10 (봉천동)8739클린케이 운동화 이불 빨래방2021-01-28 13:19:57I2021-01-30 00:23:03.0운동화전문세탁업196110.287318442007.526899운동화전문세탁업001<NA>1<NA>000N0<NA><NA><NA><NA>60000N
80432000003200000-205-2021-0000220210219<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.0151873서울특별시 관악구 신림동 513-23서울특별시 관악구 남부순환로153길 53 (신림동)8762백설사 세탁소2021-02-19 11:44:19I2021-02-21 00:23:01.0일반세탁업192443.972471442501.001144일반세탁업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>20000N
80532000003200000-205-2021-0000320210728<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0151826서울특별시 관악구 봉천동 622-61서울특별시 관악구 은천로 83-1 (봉천동)8715구두 운동화 빨래방2021-07-28 13:12:31I2021-07-30 00:22:51.0운동화전문세탁업195030.712739442759.389334운동화전문세탁업001100000N0<NA><NA><NA><NA>30000N
80632000003200000-205-2022-000012022-02-10<NA>3폐업2폐업2023-09-07<NA><NA><NA><NA>6.67151-015서울특별시 관악구 신림동 1713-12 주공2300프라자서울특별시 관악구 호암로 401, 주공2300프라자 205호 (신림동)8848동산 세탁소2023-09-07 10:21:14U2022-12-09 00:09:00.0일반세탁업193380.123306439885.315238<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
80732000003200000-205-2023-000012023-03-23<NA>1영업/정상1영업<NA><NA><NA><NA>02889 057130.0151-845서울특별시 관악구 봉천동 1522-2서울특별시 관악구 장군봉1길 20, 1층 (봉천동)8784명동크리닝2023-03-23 09:53:30I2022-12-02 22:05:00.0일반세탁업194730.053727442179.162073<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
80832000003200000-205-2023-000022023-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.4151-822서울특별시 관악구 봉천동 872-37서울특별시 관악구 봉천로45길 12, 1층 (봉천동)8748사랑세탁소2023-05-02 15:34:00I2022-12-05 00:04:00.0일반세탁업195463.73825442335.900488<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
80932000003200000-205-2024-000012024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>92.4151-913서울특별시 관악구 봉천동 955-1서울특별시 관악구 봉천로23나길 24, 2층 (봉천동)8719클린케어2024-02-26 16:11:51U2023-12-01 22:08:00.0일반세탁업194328.60995442744.269804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>