Overview

Dataset statistics

Number of variables47
Number of observations434
Missing cells3385
Missing cells (%)16.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory171.4 KiB
Average record size in memory404.3 B

Variable types

Categorical24
Text7
DateTime4
Unsupported4
Numeric6
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-17969/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (93.7%)Imbalance
위생업태명 is highly imbalanced (80.3%)Imbalance
발한실여부 is highly imbalanced (88.7%)Imbalance
조건부허가시작일자 is highly imbalanced (97.6%)Imbalance
조건부허가종료일자 is highly imbalanced (97.6%)Imbalance
건물소유구분명 is highly imbalanced (76.2%)Imbalance
여성종사자수 is highly imbalanced (81.2%)Imbalance
남성종사자수 is highly imbalanced (82.8%)Imbalance
회수건조수 is highly imbalanced (51.5%)Imbalance
인허가취소일자 has 434 (100.0%) missing valuesMissing
폐업일자 has 111 (25.6%) missing valuesMissing
휴업시작일자 has 434 (100.0%) missing valuesMissing
휴업종료일자 has 434 (100.0%) missing valuesMissing
재개업일자 has 434 (100.0%) missing valuesMissing
전화번호 has 37 (8.5%) missing valuesMissing
도로명주소 has 230 (53.0%) missing valuesMissing
도로명우편번호 has 233 (53.7%) missing valuesMissing
좌표정보(X) has 15 (3.5%) missing valuesMissing
좌표정보(Y) has 15 (3.5%) missing valuesMissing
건물지상층수 has 196 (45.2%) missing valuesMissing
발한실여부 has 35 (8.1%) missing valuesMissing
조건부허가신고사유 has 433 (99.8%) missing valuesMissing
세탁기수 has 311 (71.7%) missing valuesMissing
다중이용업소여부 has 33 (7.6%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 131 (30.2%) zerosZeros
건물지상층수 has 191 (44.0%) zerosZeros
세탁기수 has 36 (8.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:58:04.417472
Analysis finished2024-05-11 06:58:05.256307
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
3170000
434 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 434
100.0%

Length

2024-05-11T15:58:05.343742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:05.474453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 434
100.0%

관리번호
Text

UNIQUE 

Distinct434
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T15:58:05.700951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9548
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

Unique434 ?
Unique (%)100.0%

Sample

1st row3170000-205-1987-01379
2nd row3170000-205-1987-01381
3rd row3170000-205-1987-01385
4th row3170000-205-1987-01398
5th row3170000-205-1987-01406
ValueCountFrequency (%)
3170000-205-1987-01379 1
 
0.2%
3170000-205-2002-00001 1
 
0.2%
3170000-205-1998-01337 1
 
0.2%
3170000-205-1998-01336 1
 
0.2%
3170000-205-1998-01335 1
 
0.2%
3170000-205-1998-01334 1
 
0.2%
3170000-205-1998-01333 1
 
0.2%
3170000-205-1998-01332 1
 
0.2%
3170000-205-1998-01331 1
 
0.2%
3170000-205-1998-01330 1
 
0.2%
Other values (424) 424
97.7%
2024-05-11T15:58:06.079646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3253
34.1%
- 1302
13.6%
1 1222
 
12.8%
2 703
 
7.4%
3 640
 
6.7%
5 637
 
6.7%
7 626
 
6.6%
9 564
 
5.9%
8 267
 
2.8%
4 199
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8246
86.4%
Dash Punctuation 1302
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3253
39.4%
1 1222
 
14.8%
2 703
 
8.5%
3 640
 
7.8%
5 637
 
7.7%
7 626
 
7.6%
9 564
 
6.8%
8 267
 
3.2%
4 199
 
2.4%
6 135
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9548
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3253
34.1%
- 1302
13.6%
1 1222
 
12.8%
2 703
 
7.4%
3 640
 
6.7%
5 637
 
6.7%
7 626
 
6.6%
9 564
 
5.9%
8 267
 
2.8%
4 199
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3253
34.1%
- 1302
13.6%
1 1222
 
12.8%
2 703
 
7.4%
3 640
 
6.7%
5 637
 
6.7%
7 626
 
6.6%
9 564
 
5.9%
8 267
 
2.8%
4 199
 
2.1%
Distinct302
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum1987-04-15 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T15:58:06.322705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:06.474226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing434
Missing (%)100.0%
Memory size3.9 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
3
323 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 323
74.4%
1 111
 
25.6%

Length

2024-05-11T15:58:06.617081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:06.730449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 323
74.4%
1 111
 
25.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
폐업
323 
영업/정상
111 

Length

Max length5
Median length2
Mean length2.7672811
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 323
74.4%
영업/정상 111
 
25.6%

Length

2024-05-11T15:58:06.901855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:07.037190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 323
74.4%
영업/정상 111
 
25.6%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2
323 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 323
74.4%
1 111
 
25.6%

Length

2024-05-11T15:58:07.193201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:07.335934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 323
74.4%
1 111
 
25.6%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
폐업
323 
영업
111 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 323
74.4%
영업 111
 
25.6%

Length

2024-05-11T15:58:07.480216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:07.665167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 323
74.4%
영업 111
 
25.6%

폐업일자
Date

MISSING 

Distinct233
Distinct (%)72.1%
Missing111
Missing (%)25.6%
Memory size3.5 KiB
Minimum1993-01-06 00:00:00
Maximum2024-03-08 00:00:00
2024-05-11T15:58:07.791837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:07.964087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing434
Missing (%)100.0%
Memory size3.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing434
Missing (%)100.0%
Memory size3.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing434
Missing (%)100.0%
Memory size3.9 KiB

전화번호
Text

MISSING 

Distinct371
Distinct (%)93.5%
Missing37
Missing (%)8.5%
Memory size3.5 KiB
2024-05-11T15:58:08.238063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.017632
Min length6

Characters and Unicode

Total characters3977
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

Unique349 ?
Unique (%)87.9%

Sample

1st row02 8054376
2nd row02 8620942
3rd row02 8035106
4th row02 8045267
5th row02 8061047
ValueCountFrequency (%)
02 367
47.1%
0 5
 
0.6%
8919322 3
 
0.4%
8022655 2
 
0.3%
806 2
 
0.3%
8613274 2
 
0.3%
8657629 2
 
0.3%
8655134 2
 
0.3%
8061577 2
 
0.3%
8683787 2
 
0.3%
Other values (376) 390
50.1%
2024-05-11T15:58:08.792120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 777
19.5%
2 595
15.0%
8 595
15.0%
404
10.2%
6 273
 
6.9%
9 248
 
6.2%
3 243
 
6.1%
4 238
 
6.0%
5 221
 
5.6%
7 209
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3573
89.8%
Space Separator 404
 
10.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 777
21.7%
2 595
16.7%
8 595
16.7%
6 273
 
7.6%
9 248
 
6.9%
3 243
 
6.8%
4 238
 
6.7%
5 221
 
6.2%
7 209
 
5.8%
1 174
 
4.9%
Space Separator
ValueCountFrequency (%)
404
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 777
19.5%
2 595
15.0%
8 595
15.0%
404
10.2%
6 273
 
6.9%
9 248
 
6.2%
3 243
 
6.1%
4 238
 
6.0%
5 221
 
5.6%
7 209
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 777
19.5%
2 595
15.0%
8 595
15.0%
404
10.2%
6 273
 
6.9%
9 248
 
6.2%
3 243
 
6.1%
4 238
 
6.0%
5 221
 
5.6%
7 209
 
5.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct246
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.983687
Minimum0
Maximum2297.25
Zeros131
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:08.987165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16.415
Q327.16
95-th percentile106.7535
Maximum2297.25
Range2297.25
Interquartile range (IQR)27.16

Descriptive statistics

Standard deviation129.73837
Coefficient of variation (CV)3.7085391
Kurtosis222.07462
Mean34.983687
Median Absolute Deviation (MAD)16.225
Skewness13.67163
Sum15182.92
Variance16832.045
MonotonicityNot monotonic
2024-05-11T15:58:09.168503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 131
30.2%
33.0 9
 
2.1%
18.0 5
 
1.2%
18.24 3
 
0.7%
14.28 3
 
0.7%
13.6 3
 
0.7%
11.52 3
 
0.7%
15.0 3
 
0.7%
12.0 3
 
0.7%
14.4 3
 
0.7%
Other values (236) 268
61.8%
ValueCountFrequency (%)
0.0 131
30.2%
9.75 1
 
0.2%
11.1 1
 
0.2%
11.46 1
 
0.2%
11.52 3
 
0.7%
11.84 1
 
0.2%
11.88 1
 
0.2%
12.0 3
 
0.7%
12.04 1
 
0.2%
12.15 1
 
0.2%
ValueCountFrequency (%)
2297.25 1
0.2%
969.37 1
0.2%
723.64 1
0.2%
490.5 1
0.2%
310.42 1
0.2%
225.0 1
0.2%
188.04 1
0.2%
186.78 1
0.2%
186.28 1
0.2%
181.85 1
0.2%
Distinct73
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T15:58:09.471517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.062212
Min length6

Characters and Unicode

Total characters2631
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

Unique18 ?
Unique (%)4.1%

Sample

1st row153856
2nd row153813
3rd row153842
4th row153816
5th row153857
ValueCountFrequency (%)
153801 33
 
7.6%
153857 20
 
4.6%
153825 19
 
4.4%
153841 18
 
4.1%
153821 17
 
3.9%
153832 16
 
3.7%
153856 14
 
3.2%
153844 13
 
3.0%
153860 13
 
3.0%
153823 12
 
2.8%
Other values (63) 259
59.7%
2024-05-11T15:58:09.924550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 571
21.7%
3 545
20.7%
5 544
20.7%
8 441
16.8%
0 154
 
5.9%
2 101
 
3.8%
6 94
 
3.6%
4 76
 
2.9%
7 46
 
1.7%
9 32
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2604
99.0%
Dash Punctuation 27
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 571
21.9%
3 545
20.9%
5 544
20.9%
8 441
16.9%
0 154
 
5.9%
2 101
 
3.9%
6 94
 
3.6%
4 76
 
2.9%
7 46
 
1.8%
9 32
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2631
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 571
21.7%
3 545
20.7%
5 544
20.7%
8 441
16.8%
0 154
 
5.9%
2 101
 
3.8%
6 94
 
3.6%
4 76
 
2.9%
7 46
 
1.7%
9 32
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 571
21.7%
3 545
20.7%
5 544
20.7%
8 441
16.8%
0 154
 
5.9%
2 101
 
3.8%
6 94
 
3.6%
4 76
 
2.9%
7 46
 
1.7%
9 32
 
1.2%
Distinct403
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T15:58:10.274398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length45
Mean length24.910138
Min length18

Characters and Unicode

Total characters10811
Distinct characters161
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique374 ?
Unique (%)86.2%

Sample

1st row서울특별시 금천구 시흥동 839-25번지
2nd row서울특별시 금천구 독산동 303-1번지
3rd row서울특별시 금천구 시흥동 243-13번지
4th row서울특별시 금천구 독산동 378-109번지
5th row서울특별시 금천구 시흥동 878-18번지
ValueCountFrequency (%)
금천구 436
22.4%
서울특별시 434
22.3%
독산동 212
 
10.9%
시흥동 178
 
9.2%
가산동 45
 
2.3%
1층 21
 
1.1%
지상1층 10
 
0.5%
101호 7
 
0.4%
147-14번지 4
 
0.2%
상가 4
 
0.2%
Other values (513) 592
30.5%
2024-05-11T15:58:10.857488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1885
17.4%
614
 
5.7%
1 543
 
5.0%
456
 
4.2%
441
 
4.1%
441
 
4.1%
438
 
4.1%
438
 
4.1%
437
 
4.0%
435
 
4.0%
Other values (151) 4683
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6096
56.4%
Decimal Number 2322
 
21.5%
Space Separator 1885
 
17.4%
Dash Punctuation 414
 
3.8%
Close Punctuation 35
 
0.3%
Open Punctuation 34
 
0.3%
Uppercase Letter 15
 
0.1%
Lowercase Letter 6
 
0.1%
Other Punctuation 3
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
614
 
10.1%
456
 
7.5%
441
 
7.2%
441
 
7.2%
438
 
7.2%
438
 
7.2%
437
 
7.2%
435
 
7.1%
434
 
7.1%
395
 
6.5%
Other values (121) 1567
25.7%
Decimal Number
ValueCountFrequency (%)
1 543
23.4%
0 268
11.5%
2 265
11.4%
9 223
9.6%
3 221
9.5%
8 204
 
8.8%
4 184
 
7.9%
7 150
 
6.5%
5 139
 
6.0%
6 125
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
26.7%
T 3
20.0%
A 3
20.0%
C 2
13.3%
P 2
13.3%
I 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
p 2
33.3%
c 1
16.7%
t 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 25
71.4%
5
 
14.3%
] 5
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 25
73.5%
5
 
14.7%
[ 4
 
11.8%
Space Separator
ValueCountFrequency (%)
1885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 414
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6096
56.4%
Common 4694
43.4%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
614
 
10.1%
456
 
7.5%
441
 
7.2%
441
 
7.2%
438
 
7.2%
438
 
7.2%
437
 
7.2%
435
 
7.1%
434
 
7.1%
395
 
6.5%
Other values (121) 1567
25.7%
Common
ValueCountFrequency (%)
1885
40.2%
1 543
 
11.6%
- 414
 
8.8%
0 268
 
5.7%
2 265
 
5.6%
9 223
 
4.8%
3 221
 
4.7%
8 204
 
4.3%
4 184
 
3.9%
7 150
 
3.2%
Other values (10) 337
 
7.2%
Latin
ValueCountFrequency (%)
B 4
19.0%
T 3
14.3%
A 3
14.3%
a 2
9.5%
p 2
9.5%
C 2
9.5%
P 2
9.5%
c 1
 
4.8%
t 1
 
4.8%
I 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6096
56.4%
ASCII 4704
43.5%
None 10
 
0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1885
40.1%
1 543
 
11.5%
- 414
 
8.8%
0 268
 
5.7%
2 265
 
5.6%
9 223
 
4.7%
3 221
 
4.7%
8 204
 
4.3%
4 184
 
3.9%
7 150
 
3.2%
Other values (17) 347
 
7.4%
Hangul
ValueCountFrequency (%)
614
 
10.1%
456
 
7.5%
441
 
7.2%
441
 
7.2%
438
 
7.2%
438
 
7.2%
437
 
7.2%
435
 
7.1%
434
 
7.1%
395
 
6.5%
Other values (121) 1567
25.7%
None
ValueCountFrequency (%)
5
50.0%
5
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct201
Distinct (%)98.5%
Missing230
Missing (%)53.0%
Memory size3.5 KiB
2024-05-11T15:58:11.191136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length30.294118
Min length22

Characters and Unicode

Total characters6180
Distinct characters152
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)97.1%

Sample

1st row서울특별시 금천구 독산로21길 15 (시흥동)
2nd row서울특별시 금천구 남부순환로130길 43 (독산동)
3rd row서울특별시 금천구 시흥대로100길 10 (독산동)
4th row서울특별시 금천구 탑골로3길 9 (시흥동)
5th row서울특별시 금천구 시흥대로151길 16 (독산동)
ValueCountFrequency (%)
서울특별시 204
 
17.6%
금천구 204
 
17.6%
독산동 82
 
7.1%
시흥동 74
 
6.4%
1층 29
 
2.5%
가산동 15
 
1.3%
101호 9
 
0.8%
15 8
 
0.7%
시흥대로 8
 
0.7%
금하로 8
 
0.7%
Other values (328) 519
44.7%
2024-05-11T15:58:11.686803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
956
 
15.5%
359
 
5.8%
1 286
 
4.6%
227
 
3.7%
225
 
3.6%
) 218
 
3.5%
( 218
 
3.5%
212
 
3.4%
209
 
3.4%
207
 
3.3%
Other values (142) 3063
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3579
57.9%
Decimal Number 1044
 
16.9%
Space Separator 956
 
15.5%
Close Punctuation 222
 
3.6%
Open Punctuation 222
 
3.6%
Other Punctuation 116
 
1.9%
Dash Punctuation 25
 
0.4%
Uppercase Letter 10
 
0.2%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
359
 
10.0%
227
 
6.3%
225
 
6.3%
212
 
5.9%
209
 
5.8%
207
 
5.8%
207
 
5.8%
205
 
5.7%
205
 
5.7%
204
 
5.7%
Other values (113) 1319
36.9%
Decimal Number
ValueCountFrequency (%)
1 286
27.4%
2 129
12.4%
3 112
 
10.7%
4 96
 
9.2%
0 96
 
9.2%
8 72
 
6.9%
6 70
 
6.7%
7 67
 
6.4%
5 63
 
6.0%
9 53
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
A 2
20.0%
T 2
20.0%
C 1
 
10.0%
P 1
 
10.0%
I 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
p 2
33.3%
a 2
33.3%
c 1
16.7%
t 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 218
98.2%
] 2
 
0.9%
2
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 218
98.2%
[ 2
 
0.9%
2
 
0.9%
Space Separator
ValueCountFrequency (%)
956
100.0%
Other Punctuation
ValueCountFrequency (%)
, 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3579
57.9%
Common 2585
41.8%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
359
 
10.0%
227
 
6.3%
225
 
6.3%
212
 
5.9%
209
 
5.8%
207
 
5.8%
207
 
5.8%
205
 
5.7%
205
 
5.7%
204
 
5.7%
Other values (113) 1319
36.9%
Common
ValueCountFrequency (%)
956
37.0%
1 286
 
11.1%
) 218
 
8.4%
( 218
 
8.4%
2 129
 
5.0%
, 116
 
4.5%
3 112
 
4.3%
4 96
 
3.7%
0 96
 
3.7%
8 72
 
2.8%
Other values (9) 286
 
11.1%
Latin
ValueCountFrequency (%)
B 3
18.8%
p 2
12.5%
a 2
12.5%
A 2
12.5%
T 2
12.5%
c 1
 
6.2%
t 1
 
6.2%
C 1
 
6.2%
P 1
 
6.2%
I 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3579
57.9%
ASCII 2597
42.0%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
956
36.8%
1 286
 
11.0%
) 218
 
8.4%
( 218
 
8.4%
2 129
 
5.0%
, 116
 
4.5%
3 112
 
4.3%
4 96
 
3.7%
0 96
 
3.7%
8 72
 
2.8%
Other values (17) 298
 
11.5%
Hangul
ValueCountFrequency (%)
359
 
10.0%
227
 
6.3%
225
 
6.3%
212
 
5.9%
209
 
5.8%
207
 
5.8%
207
 
5.8%
205
 
5.7%
205
 
5.7%
204
 
5.7%
Other values (113) 1319
36.9%
None
ValueCountFrequency (%)
2
50.0%
2
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)49.8%
Missing233
Missing (%)53.7%
Infinite0
Infinite (%)0.0%
Mean8586.8408
Minimum8506
Maximum8657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:11.843076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8506
5-th percentile8521
Q18550
median8581
Q38625
95-th percentile8652
Maximum8657
Range151
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.170644
Coefficient of variation (CV)0.0050275352
Kurtosis-1.2701408
Mean8586.8408
Median Absolute Deviation (MAD)40
Skewness-0.022192197
Sum1725955
Variance1863.7045
MonotonicityNot monotonic
2024-05-11T15:58:11.987014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8625 7
 
1.6%
8619 5
 
1.2%
8637 5
 
1.2%
8621 5
 
1.2%
8586 5
 
1.2%
8529 4
 
0.9%
8570 4
 
0.9%
8537 4
 
0.9%
8618 4
 
0.9%
8638 4
 
0.9%
Other values (90) 154
35.5%
(Missing) 233
53.7%
ValueCountFrequency (%)
8506 1
 
0.2%
8507 1
 
0.2%
8508 2
0.5%
8509 1
 
0.2%
8515 2
0.5%
8520 2
0.5%
8521 3
0.7%
8525 2
0.5%
8527 1
 
0.2%
8528 1
 
0.2%
ValueCountFrequency (%)
8657 2
0.5%
8656 3
0.7%
8655 3
0.7%
8654 1
 
0.2%
8652 2
0.5%
8651 3
0.7%
8649 1
 
0.2%
8648 2
0.5%
8647 2
0.5%
8646 2
0.5%
Distinct320
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T15:58:12.284815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.8294931
Min length1

Characters and Unicode

Total characters1662
Distinct characters234
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

Unique262 ?
Unique (%)60.4%

Sample

1st row삼신사
2nd row신진사
3rd row신화
4th row한창사
5th row유성사
ValueCountFrequency (%)
백조사 11
 
2.5%
백양사 9
 
2.0%
은혜사 6
 
1.3%
현대사 6
 
1.3%
대성사 5
 
1.1%
일류사 5
 
1.1%
태양사 4
 
0.9%
형제사 4
 
0.9%
일광사 4
 
0.9%
중앙사 4
 
0.9%
Other values (319) 390
87.1%
2024-05-11T15:58:12.781792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
253
 
15.2%
94
 
5.7%
86
 
5.2%
56
 
3.4%
41
 
2.5%
38
 
2.3%
36
 
2.2%
36
 
2.2%
36
 
2.2%
28
 
1.7%
Other values (224) 958
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1622
97.6%
Space Separator 14
 
0.8%
Decimal Number 9
 
0.5%
Uppercase Letter 7
 
0.4%
Lowercase Letter 7
 
0.4%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
253
 
15.6%
94
 
5.8%
86
 
5.3%
56
 
3.5%
41
 
2.5%
38
 
2.3%
36
 
2.2%
36
 
2.2%
36
 
2.2%
28
 
1.7%
Other values (205) 918
56.6%
Lowercase Letter
ValueCountFrequency (%)
s 2
28.6%
u 1
14.3%
f 1
14.3%
l 1
14.3%
e 1
14.3%
n 1
14.3%
Decimal Number
ValueCountFrequency (%)
7 4
44.4%
1 2
22.2%
3 1
 
11.1%
4 1
 
11.1%
2 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
K 2
28.6%
O 2
28.6%
G 1
14.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1622
97.6%
Common 26
 
1.6%
Latin 14
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
253
 
15.6%
94
 
5.8%
86
 
5.3%
56
 
3.5%
41
 
2.5%
38
 
2.3%
36
 
2.2%
36
 
2.2%
36
 
2.2%
28
 
1.7%
Other values (205) 918
56.6%
Latin
ValueCountFrequency (%)
A 2
14.3%
s 2
14.3%
K 2
14.3%
O 2
14.3%
G 1
7.1%
u 1
7.1%
f 1
7.1%
l 1
7.1%
e 1
7.1%
n 1
7.1%
Common
ValueCountFrequency (%)
14
53.8%
7 4
 
15.4%
1 2
 
7.7%
3 1
 
3.8%
. 1
 
3.8%
( 1
 
3.8%
) 1
 
3.8%
4 1
 
3.8%
2 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1622
97.6%
ASCII 40
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
253
 
15.6%
94
 
5.8%
86
 
5.3%
56
 
3.5%
41
 
2.5%
38
 
2.3%
36
 
2.2%
36
 
2.2%
36
 
2.2%
28
 
1.7%
Other values (205) 918
56.6%
ASCII
ValueCountFrequency (%)
14
35.0%
7 4
 
10.0%
1 2
 
5.0%
A 2
 
5.0%
s 2
 
5.0%
K 2
 
5.0%
O 2
 
5.0%
G 1
 
2.5%
u 1
 
2.5%
f 1
 
2.5%
Other values (9) 9
22.5%
Distinct280
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum1999-04-14 00:00:00
Maximum2024-04-30 15:47:14
2024-05-11T15:58:12.968957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:13.173665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
I
283 
U
151 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 283
65.2%
U 151
34.8%

Length

2024-05-11T15:58:13.322980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:13.744040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 283
65.2%
u 151
34.8%
Distinct101
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T15:58:13.872185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:14.053374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
일반세탁업
428 
운동화전문세탁업
 
3
세탁업 기타
 
2
빨래방업
 
1

Length

Max length8
Median length5
Mean length5.0230415
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 428
98.6%
운동화전문세탁업 3
 
0.7%
세탁업 기타 2
 
0.5%
빨래방업 1
 
0.2%

Length

2024-05-11T15:58:14.227345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:14.409653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 428
98.2%
운동화전문세탁업 3
 
0.7%
세탁업 2
 
0.5%
기타 2
 
0.5%
빨래방업 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct352
Distinct (%)84.0%
Missing15
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean191218.99
Minimum189045.77
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:14.535481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189045.77
5-th percentile190229.33
Q1190927.1
median191311.4
Q3191567.49
95-th percentile192113.36
Maximum192754.35
Range3708.5781
Interquartile range (IQR)640.38216

Descriptive statistics

Standard deviation593.32609
Coefficient of variation (CV)0.0031028618
Kurtosis0.81206904
Mean191218.99
Median Absolute Deviation (MAD)295.59836
Skewness-0.4877374
Sum80120756
Variance352035.84
MonotonicityNot monotonic
2024-05-11T15:58:14.698106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190829.611626985 4
 
0.9%
191190.614295546 3
 
0.7%
191091.478567552 3
 
0.7%
190325.595118095 3
 
0.7%
192327.921963392 3
 
0.7%
191359.859368154 3
 
0.7%
190932.076039993 3
 
0.7%
190232.47138241 3
 
0.7%
191520.592215439 3
 
0.7%
191282.305189152 3
 
0.7%
Other values (342) 388
89.4%
(Missing) 15
 
3.5%
ValueCountFrequency (%)
189045.768055551 1
0.2%
189067.117409684 1
0.2%
189369.53962474 1
0.2%
189550.286970696 1
0.2%
189566.180639191 1
0.2%
189647.046752134 1
0.2%
189691.858978981 2
0.5%
189736.88808904 1
0.2%
189920.540900476 1
0.2%
189951.567774536 1
0.2%
ValueCountFrequency (%)
192754.34619252 3
0.7%
192742.326147617 2
0.5%
192394.502820184 1
 
0.2%
192368.43764933 2
0.5%
192327.921963392 3
0.7%
192324.518969346 1
 
0.2%
192297.91598261 1
 
0.2%
192205.754796883 1
 
0.2%
192202.449367738 1
 
0.2%
192178.918357135 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct352
Distinct (%)84.0%
Missing15
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean440188.92
Minimum436897.47
Maximum442481.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:14.849963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436897.47
5-th percentile438399.01
Q1439110.35
median440267.1
Q3441305.79
95-th percentile441802.22
Maximum442481.67
Range5584.2054
Interquartile range (IQR)2195.4438

Descriptive statistics

Standard deviation1188.0386
Coefficient of variation (CV)0.0026989289
Kurtosis-1.0021187
Mean440188.92
Median Absolute Deviation (MAD)1069.6238
Skewness-0.20619683
Sum1.8443916 × 108
Variance1411435.7
MonotonicityNot monotonic
2024-05-11T15:58:14.991896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441373.610504492 4
 
0.9%
438410.522111193 3
 
0.7%
441501.334511912 3
 
0.7%
441112.08102574 3
 
0.7%
438884.383032237 3
 
0.7%
440387.041361025 3
 
0.7%
439328.50476394 3
 
0.7%
440016.250106997 3
 
0.7%
439454.046201371 3
 
0.7%
438356.170313032 3
 
0.7%
Other values (342) 388
89.4%
(Missing) 15
 
3.5%
ValueCountFrequency (%)
436897.466167682 1
0.2%
436946.358720615 1
0.2%
437632.508826604 1
0.2%
437643.267080931 1
0.2%
437653.726120784 1
0.2%
437708.439019962 1
0.2%
437816.239800826 2
0.5%
437823.090862848 1
0.2%
437835.413003176 1
0.2%
438160.729202982 2
0.5%
ValueCountFrequency (%)
442481.671591951 1
0.2%
442468.112465731 1
0.2%
442354.304734197 2
0.5%
442262.746663668 1
0.2%
441976.745133837 1
0.2%
441958.120709026 1
0.2%
441939.923466561 2
0.5%
441907.532248683 1
0.2%
441883.447774175 1
0.2%
441859.968881566 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
일반세탁업
398 
<NA>
 
33
세탁업 기타
 
1
운동화전문세탁업
 
1
빨래방업
 
1

Length

Max length8
Median length5
Mean length4.9308756
Min length4

Unique

Unique3 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 398
91.7%
<NA> 33
 
7.6%
세탁업 기타 1
 
0.2%
운동화전문세탁업 1
 
0.2%
빨래방업 1
 
0.2%

Length

2024-05-11T15:58:15.155452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:15.362985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 398
91.5%
na 33
 
7.6%
세탁업 1
 
0.2%
기타 1
 
0.2%
운동화전문세탁업 1
 
0.2%
빨래방업 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)4.2%
Missing196
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean0.64705882
Minimum0
Maximum15
Zeros191
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:15.512480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.15
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6616206
Coefficient of variation (CV)2.567959
Kurtosis26.504861
Mean0.64705882
Median Absolute Deviation (MAD)0
Skewness4.2473778
Sum154
Variance2.7609829
MonotonicityNot monotonic
2024-05-11T15:58:15.652017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 191
44.0%
3 16
 
3.7%
2 15
 
3.5%
4 5
 
1.2%
1 4
 
0.9%
5 3
 
0.7%
9 1
 
0.2%
15 1
 
0.2%
6 1
 
0.2%
7 1
 
0.2%
(Missing) 196
45.2%
ValueCountFrequency (%)
0 191
44.0%
1 4
 
0.9%
2 15
 
3.5%
3 16
 
3.7%
4 5
 
1.2%
5 3
 
0.7%
6 1
 
0.2%
7 1
 
0.2%
9 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
9 1
 
0.2%
7 1
 
0.2%
6 1
 
0.2%
5 3
 
0.7%
4 5
 
1.2%
3 16
 
3.7%
2 15
 
3.5%
1 4
 
0.9%
0 191
44.0%
Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
202 
0
194 
1
34 
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length2.3963134
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 202
46.5%
0 194
44.7%
1 34
 
7.8%
2 2
 
0.5%
3 1
 
0.2%
5 1
 
0.2%

Length

2024-05-11T15:58:15.825212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:15.975977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
46.5%
0 194
44.7%
1 34
 
7.8%
2 2
 
0.5%
3 1
 
0.2%
5 1
 
0.2%
Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
208 
0
179 
1
44 
2
 
3

Length

Max length4
Median length1
Mean length2.437788
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 208
47.9%
0 179
41.2%
1 44
 
10.1%
2 3
 
0.7%

Length

2024-05-11T15:58:16.149943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:16.265591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 208
47.9%
0 179
41.2%
1 44
 
10.1%
2 3
 
0.7%
Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
312 
0
80 
1
39 
2
 
3

Length

Max length4
Median length4
Mean length3.156682
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 312
71.9%
0 80
 
18.4%
1 39
 
9.0%
2 3
 
0.7%

Length

2024-05-11T15:58:16.392593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:16.527799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 312
71.9%
0 80
 
18.4%
1 39
 
9.0%
2 3
 
0.7%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
227 
0
201 
1
 
6

Length

Max length4
Median length4
Mean length2.5691244
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 227
52.3%
0 201
46.3%
1 6
 
1.4%

Length

2024-05-11T15:58:16.669227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:16.805503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 227
52.3%
0 201
46.3%
1 6
 
1.4%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
328 
0
100 
1
 
6

Length

Max length4
Median length4
Mean length3.2672811
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 328
75.6%
0 100
 
23.0%
1 6
 
1.4%

Length

2024-05-11T15:58:16.950398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:17.083278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 328
75.6%
0 100
 
23.0%
1 6
 
1.4%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
219 
<NA>
215 

Length

Max length4
Median length1
Mean length2.4861751
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 219
50.5%
<NA> 215
49.5%

Length

2024-05-11T15:58:17.242601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:17.391818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 219
50.5%
na 215
49.5%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
219 
<NA>
215 

Length

Max length4
Median length1
Mean length2.4861751
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 219
50.5%
<NA> 215
49.5%

Length

2024-05-11T15:58:17.597893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:17.731961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 219
50.5%
na 215
49.5%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
219 
<NA>
215 

Length

Max length4
Median length1
Mean length2.4861751
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 219
50.5%
<NA> 215
49.5%

Length

2024-05-11T15:58:17.874740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:17.995902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 219
50.5%
na 215
49.5%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing35
Missing (%)8.1%
Memory size1000.0 B
False
393 
True
 
6
(Missing)
 
35
ValueCountFrequency (%)
False 393
90.6%
True 6
 
1.4%
(Missing) 35
 
8.1%
2024-05-11T15:58:18.110806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
219 
<NA>
214 
3
 
1

Length

Max length4
Median length1
Mean length2.4792627
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 219
50.5%
<NA> 214
49.3%
3 1
 
0.2%

Length

2024-05-11T15:58:18.250196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:18.384392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 219
50.5%
na 214
49.3%
3 1
 
0.2%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing433
Missing (%)99.8%
Memory size3.5 KiB
2024-05-11T15:58:18.568442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters31
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row준공인가전 사용허가 기한에 따라 조건부 신고이므로 조건부기간 만료시 영업신고증 재교부
ValueCountFrequency (%)
준공인가전 1
10.0%
사용허가 1
10.0%
기한에 1
10.0%
따라 1
10.0%
조건부 1
10.0%
신고이므로 1
10.0%
조건부기간 1
10.0%
만료시 1
10.0%
영업신고증 1
10.0%
재교부 1
10.0%
2024-05-11T15:58:18.937620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
19.1%
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
Other values (21) 21
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38
80.9%
Space Separator 9
 
19.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
7.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Other values (20) 20
52.6%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38
80.9%
Common 9
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
7.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Other values (20) 20
52.6%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38
80.9%
ASCII 9
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
100.0%
Hangul
ValueCountFrequency (%)
3
 
7.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Other values (20) 20
52.6%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
433 
20111219
 
1

Length

Max length8
Median length4
Mean length4.0092166
Min length4

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> 433
99.8%
20111219 1
 
0.2%

Length

2024-05-11T15:58:19.109691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:19.257231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 433
99.8%
20111219 1
 
0.2%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
433 
20120929
 
1

Length

Max length8
Median length4
Mean length4.0092166
Min length4

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> 433
99.8%
20120929 1
 
0.2%

Length

2024-05-11T15:58:19.402378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:19.535752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 433
99.8%
20120929 1
 
0.2%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
404 
임대
 
29
자가
 
1

Length

Max length4
Median length4
Mean length3.8617512
Min length2

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> 404
93.1%
임대 29
 
6.7%
자가 1
 
0.2%

Length

2024-05-11T15:58:19.684646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:19.883467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 404
93.1%
임대 29
 
6.7%
자가 1
 
0.2%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)5.7%
Missing311
Missing (%)71.7%
Infinite0
Infinite (%)0.0%
Mean1.5284553
Minimum0
Maximum10
Zeros36
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T15:58:19.999649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4839314
Coefficient of variation (CV)0.97087004
Kurtosis9.9219055
Mean1.5284553
Median Absolute Deviation (MAD)1
Skewness2.1850838
Sum188
Variance2.2020525
MonotonicityNot monotonic
2024-05-11T15:58:20.121385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 45
 
10.4%
0 36
 
8.3%
1 22
 
5.1%
3 14
 
3.2%
4 4
 
0.9%
10 1
 
0.2%
8 1
 
0.2%
(Missing) 311
71.7%
ValueCountFrequency (%)
0 36
8.3%
1 22
5.1%
2 45
10.4%
3 14
 
3.2%
4 4
 
0.9%
8 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
8 1
 
0.2%
4 4
 
0.9%
3 14
 
3.2%
2 45
10.4%
1 22
5.1%
0 36
8.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
414 
0
 
17
1
 
3

Length

Max length4
Median length4
Mean length3.8617512
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> 414
95.4%
0 17
 
3.9%
1 3
 
0.7%

Length

2024-05-11T15:58:20.264086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:20.401867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 414
95.4%
0 17
 
3.9%
1 3
 
0.7%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
415 
0
 
18
1
 
1

Length

Max length4
Median length4
Mean length3.8686636
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> 415
95.6%
0 18
 
4.1%
1 1
 
0.2%

Length

2024-05-11T15:58:20.530685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:20.655584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 415
95.6%
0 18
 
4.1%
1 1
 
0.2%

회수건조수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
319 
0
67 
1
46 
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.2050691
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
73.5%
0 67
 
15.4%
1 46
 
10.6%
2 1
 
0.2%
4 1
 
0.2%

Length

2024-05-11T15:58:20.815406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:20.989622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
73.5%
0 67
 
15.4%
1 46
 
10.6%
2 1
 
0.2%
4 1
 
0.2%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
319 
0
115 

Length

Max length4
Median length4
Mean length3.2050691
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
73.5%
0 115
 
26.5%

Length

2024-05-11T15:58:21.156038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:21.285394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
73.5%
0 115
 
26.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing33
Missing (%)7.6%
Memory size1000.0 B
False
401 
(Missing)
 
33
ValueCountFrequency (%)
False 401
92.4%
(Missing) 33
 
7.6%
2024-05-11T15:58:21.401547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031700003170000-205-1987-0137919870509<NA>1영업/정상1영업<NA><NA><NA><NA>02 805437618.0153856서울특별시 금천구 시흥동 839-25번지서울특별시 금천구 독산로21길 15 (시흥동)8627삼신사2019-07-11 11:08:01U2019-07-13 02:40:00.0일반세탁업191544.937384439057.535514일반세탁업000000000N0<NA><NA><NA><NA>0<NA><NA>10N
131700003170000-205-1987-0138119870429<NA>3폐업2폐업20010710<NA><NA><NA>02 86209420.0153813서울특별시 금천구 독산동 303-1번지<NA><NA>신진사2001-07-10 00:00:00I2018-08-31 23:59:59.0일반세탁업190325.595118441112.081026일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231700003170000-205-1987-0138519870623<NA>3폐업2폐업19980418<NA><NA><NA>02 80351060.0153842서울특별시 금천구 시흥동 243-13번지<NA><NA>신화2002-01-13 00:00:00I2018-08-31 23:59:59.0일반세탁업192324.518969438689.692089일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331700003170000-205-1987-0139819870501<NA>3폐업2폐업20091224<NA><NA><NA>02 804526714.4153816서울특별시 금천구 독산동 378-109번지<NA><NA>한창사2003-12-23 00:00:00I2018-08-31 23:59:59.0일반세탁업191510.944577440408.153264일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431700003170000-205-1987-0140619870416<NA>3폐업2폐업20031208<NA><NA><NA>02 80610470.0153857서울특별시 금천구 시흥동 878-18번지<NA><NA>유성사2003-02-19 00:00:00I2018-08-31 23:59:59.0일반세탁업191402.986623439238.787893일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531700003170000-205-1987-0140719870609<NA>3폐업2폐업20051228<NA><NA><NA>02 864870812.48153801서울특별시 금천구 가산동 237-91번지<NA><NA>수노아사2003-12-23 00:00:00I2018-08-31 23:59:59.0일반세탁업190164.325496441121.719335일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631700003170000-205-1987-0140919870508<NA>1영업/정상1영업<NA><NA><NA><NA>02 862140415.74153820서울특별시 금천구 독산동 905-4번지서울특별시 금천구 남부순환로130길 43 (독산동)8549충남사2020-06-11 15:20:37U2020-06-13 02:40:00.0일반세탁업191850.710785441843.538066일반세탁업000000000N0<NA><NA><NA><NA>2<NA><NA>00N
731700003170000-205-1987-0141019870429<NA>3폐업2폐업20190703<NA><NA><NA><NA>15.48153832서울특별시 금천구 독산동 1055-2번지서울특별시 금천구 시흥대로100길 10 (독산동)8619동양사2019-07-03 09:41:26U2019-07-05 02:40:00.0일반세탁업190922.132908440135.828931일반세탁업000000000N0<NA><NA><NA><NA>1<NA><NA>00N
831700003170000-205-1987-0141319870515<NA>1영업/정상1영업<NA><NA><NA><NA>02 803379415.34153841서울특별시 금천구 시흥동 220-61번지서울특별시 금천구 탑골로3길 9 (시흥동)8575고려사2020-03-27 14:11:54U2020-03-29 02:40:00.0일반세탁업192108.807654438914.977256일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931700003170000-205-1987-0141519870429<NA>3폐업2폐업20040602<NA><NA><NA>02 854699212.0153814서울특별시 금천구 독산동 335-1번지<NA><NA>백양사2004-06-02 00:00:00I2018-08-31 23:59:59.0일반세탁업190227.548355441115.250957일반세탁업<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
42431700003170000-205-2021-0000220210823<NA>1영업/정상1영업<NA><NA><NA><NA><NA>107.93153803서울특별시 금천구 가산동 371-37 에스티엑스브이타워서울특별시 금천구 가산디지털1로 128, 에스티엑스브이타워 B136호 (가산동)8507조은프로소싱2021-12-28 16:21:53U2021-12-31 02:40:00.0일반세탁업189647.046752441677.096205일반세탁업010000000N0<NA><NA><NA><NA>30040N
42531700003170000-205-2021-0000320210924<NA>3폐업2폐업20220928<NA><NA><NA><NA>0.0153863서울특별시 금천구 시흥동 985 한영상가서울특별시 금천구 시흥대로39길 16, 한영상가 나동 120호 (시흥동)8638맨숀세탁소2022-09-28 11:33:09U2021-10-31 00:01:00.0일반세탁업191266.732178438395.806834<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42631700003170000-205-2023-000012023-02-02<NA>3폐업2폐업2024-02-06<NA><NA><NA>02 555 12170.0153-813서울특별시 금천구 독산동 331-43서울특별시 금천구 범안로15길 4, 1층 (독산동)8586A1A12024-02-06 11:21:43U2023-12-02 00:08:00.0일반세탁업190503.687488440514.335744<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42731700003170000-205-2023-000022023-02-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>79.52153-832서울특별시 금천구 독산동 1061-38서울특별시 금천구 시흥대로94길 24, 1층 (독산동)8619운동화빨래방2023-05-30 11:08:55U2022-12-06 00:01:00.0운동화전문세탁업191015.804238440021.81305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42831700003170000-205-2023-000032023-07-03<NA>3폐업2폐업2024-02-06<NA><NA><NA><NA>76.2153-030서울특별시 금천구 시흥동 1026 남서울힐스테이트서울특별시 금천구 시흥대로 165, 313(1단지상가)동 101호 (시흥동, 남서울힐스테이트)8637명품세탁2024-02-06 12:35:49U2023-12-02 00:08:00.0일반세탁업191190.614296438410.522111<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42931700003170000-205-2023-000042023-07-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>148.76153-823서울특별시 금천구 독산동 967-12 청룡빌딩서울특별시 금천구 시흥대로 480, 청룡빌딩 1층 2호 (독산동)8540창조 크리닝2024-04-15 13:24:37U2023-12-03 23:07:00.0일반세탁업190996.914193441563.015154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43031700003170000-205-2024-000012024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>76.0153-030서울특별시 금천구 시흥동 1026 남서울힐스테이트서울특별시 금천구 시흥대로 165, 313동 1층 101호 (시흥동, 남서울힐스테이트)8637명품세탁2024-02-06 12:40:44I2023-12-02 00:08:00.0일반세탁업191190.614296438410.522111<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43131700003170000-205-2024-000022024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.0153-808서울특별시 금천구 독산동 181-1서울특별시 금천구 독산로80길 11-12, 103호 (독산동)8555일광세탁소2024-03-21 13:50:22I2023-12-02 22:03:00.0일반세탁업191434.37611441057.000113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43231700003170000-205-2024-000032024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>83.91153-864서울특별시 금천구 시흥동 989-9 스카이아파트서울특별시 금천구 시흥대로47길 35, 102, 103호 (시흥동, 스카이아파트)8636세기사2024-04-19 15:56:51I2023-12-03 22:01:00.0일반세탁업191106.016949438602.864289<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43331700003170000-205-2024-000042024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA>026978890270.11153-768서울특별시 금천구 가산동 550-1 IT캐슬서울특별시 금천구 가산디지털2로 98, IT캐슬 2동 114호 (가산동)8506주식회사 바이오스타줄기세포기술연구원2024-04-22 15:43:09I2023-12-03 22:04:00.0일반세탁업189369.539625441629.361415<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>