Overview

Dataset statistics

Number of variables47
Number of observations348
Missing cells3456
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory137.1 KiB
Average record size in memory403.4 B

Variable types

Categorical20
Text7
DateTime4
Unsupported4
Numeric10
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-19294/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (90.9%)Imbalance
사용끝지하층 is highly imbalanced (50.4%)Imbalance
조건부허가신고사유 is highly imbalanced (84.2%)Imbalance
여성종사자수 is highly imbalanced (63.0%)Imbalance
인허가취소일자 has 348 (100.0%) missing valuesMissing
폐업일자 has 130 (37.4%) missing valuesMissing
휴업시작일자 has 348 (100.0%) missing valuesMissing
휴업종료일자 has 348 (100.0%) missing valuesMissing
재개업일자 has 348 (100.0%) missing valuesMissing
전화번호 has 57 (16.4%) missing valuesMissing
도로명주소 has 77 (22.1%) missing valuesMissing
도로명우편번호 has 80 (23.0%) missing valuesMissing
좌표정보(X) has 4 (1.1%) missing valuesMissing
좌표정보(Y) has 4 (1.1%) missing valuesMissing
건물지상층수 has 128 (36.8%) missing valuesMissing
건물지하층수 has 137 (39.4%) missing valuesMissing
사용시작지상층 has 156 (44.8%) missing valuesMissing
사용끝지상층 has 166 (47.7%) missing valuesMissing
발한실여부 has 89 (25.6%) missing valuesMissing
조건부허가시작일자 has 340 (97.7%) missing valuesMissing
조건부허가종료일자 has 340 (97.7%) missing valuesMissing
남성종사자수 has 267 (76.7%) missing valuesMissing
다중이용업소여부 has 86 (24.7%) 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
건물지상층수 has 103 (29.6%) zerosZeros
건물지하층수 has 136 (39.1%) zerosZeros
사용시작지상층 has 16 (4.6%) zerosZeros
사용끝지상층 has 14 (4.0%) zerosZeros
남성종사자수 has 40 (11.5%) zerosZeros

Reproduction

Analysis started2024-05-11 03:57:37.306240
Analysis finished2024-05-11 03:57:39.395589
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3170000
348 

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 348
100.0%

Length

2024-05-11T03:57:39.702733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:57:40.146071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 348
100.0%

관리번호
Text

UNIQUE 

Distinct348
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T03:57:40.565504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7656
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

Unique348 ?
Unique (%)100.0%

Sample

1st row3170000-206-1991-01637
2nd row3170000-206-1993-01625
3rd row3170000-206-1994-01627
4th row3170000-206-1994-01628
5th row3170000-206-1995-01624
ValueCountFrequency (%)
3170000-206-1991-01637 1
 
0.3%
3170000-206-2015-00006 1
 
0.3%
3170000-206-2015-00014 1
 
0.3%
3170000-206-2015-00013 1
 
0.3%
3170000-206-2015-00012 1
 
0.3%
3170000-206-2015-00011 1
 
0.3%
3170000-206-2015-00010 1
 
0.3%
3170000-206-2015-00009 1
 
0.3%
3170000-206-2015-00008 1
 
0.3%
3170000-206-2015-00020 1
 
0.3%
Other values (338) 338
97.1%
2024-05-11T03:57:41.840449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3426
44.7%
- 1044
 
13.6%
2 825
 
10.8%
1 766
 
10.0%
6 437
 
5.7%
3 433
 
5.7%
7 412
 
5.4%
9 102
 
1.3%
5 74
 
1.0%
4 73
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6612
86.4%
Dash Punctuation 1044
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3426
51.8%
2 825
 
12.5%
1 766
 
11.6%
6 437
 
6.6%
3 433
 
6.5%
7 412
 
6.2%
9 102
 
1.5%
5 74
 
1.1%
4 73
 
1.1%
8 64
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3426
44.7%
- 1044
 
13.6%
2 825
 
10.8%
1 766
 
10.0%
6 437
 
5.7%
3 433
 
5.7%
7 412
 
5.4%
9 102
 
1.3%
5 74
 
1.0%
4 73
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3426
44.7%
- 1044
 
13.6%
2 825
 
10.8%
1 766
 
10.0%
6 437
 
5.7%
3 433
 
5.7%
7 412
 
5.4%
9 102
 
1.3%
5 74
 
1.0%
4 73
 
1.0%
Distinct332
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1991-05-22 00:00:00
Maximum2024-04-18 00:00:00
2024-05-11T03:57:42.303669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:57:42.961136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing348
Missing (%)100.0%
Memory size3.2 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
218 
1
130 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 218
62.6%
1 130
37.4%

Length

2024-05-11T03:57:43.492579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:57:43.858686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 218
62.6%
1 130
37.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
218 
영업/정상
130 

Length

Max length5
Median length2
Mean length3.1206897
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 218
62.6%
영업/정상 130
37.4%

Length

2024-05-11T03:57:44.236410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:57:44.704834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 218
62.6%
영업/정상 130
37.4%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2
218 
1
130 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 218
62.6%
1 130
37.4%

Length

2024-05-11T03:57:45.204951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:57:45.694069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 218
62.6%
1 130
37.4%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
218 
영업
130 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 218
62.6%
영업 130
37.4%

Length

2024-05-11T03:57:46.052758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:57:46.410276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 218
62.6%
영업 130
37.4%

폐업일자
Date

MISSING 

Distinct187
Distinct (%)85.8%
Missing130
Missing (%)37.4%
Memory size2.8 KiB
Minimum1998-10-30 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T03:57:46.878892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:57:47.440202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing348
Missing (%)100.0%
Memory size3.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing348
Missing (%)100.0%
Memory size3.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing348
Missing (%)100.0%
Memory size3.2 KiB

전화번호
Text

MISSING 

Distinct281
Distinct (%)96.6%
Missing57
Missing (%)16.4%
Memory size2.8 KiB
2024-05-11T03:57:48.333712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.33677
Min length7

Characters and Unicode

Total characters3008
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

Unique271 ?
Unique (%)93.1%

Sample

1st row02 8512327
2nd row0232816961
3rd row02 8053527
4th row02 8053527
5th row02 8942005
ValueCountFrequency (%)
02 187
36.1%
031 5
 
1.0%
070 4
 
0.8%
028930991 2
 
0.4%
8626262 2
 
0.4%
838 2
 
0.4%
891 2
 
0.4%
032 2
 
0.4%
8035086 2
 
0.4%
855 2
 
0.4%
Other values (301) 308
59.5%
2024-05-11T03:57:49.658641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 594
19.7%
2 500
16.6%
8 319
10.6%
265
8.8%
6 216
 
7.2%
5 209
 
6.9%
3 193
 
6.4%
9 187
 
6.2%
4 184
 
6.1%
1 183
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2743
91.2%
Space Separator 265
 
8.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 594
21.7%
2 500
18.2%
8 319
11.6%
6 216
 
7.9%
5 209
 
7.6%
3 193
 
7.0%
9 187
 
6.8%
4 184
 
6.7%
1 183
 
6.7%
7 158
 
5.8%
Space Separator
ValueCountFrequency (%)
265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 594
19.7%
2 500
16.6%
8 319
10.6%
265
8.8%
6 216
 
7.2%
5 209
 
6.9%
3 193
 
6.4%
9 187
 
6.2%
4 184
 
6.1%
1 183
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 594
19.7%
2 500
16.6%
8 319
10.6%
265
8.8%
6 216
 
7.2%
5 209
 
6.9%
3 193
 
6.4%
9 187
 
6.2%
4 184
 
6.1%
1 183
 
6.1%
Distinct231
Distinct (%)66.6%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2024-05-11T03:57:50.975040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8904899
Min length3

Characters and Unicode

Total characters1697
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)56.8%

Sample

1st row.00
2nd row270.60
3rd row.00
4th row.00
5th row55.00
ValueCountFrequency (%)
00 33
 
9.5%
22.86 28
 
8.1%
21.70 8
 
2.3%
33.00 8
 
2.3%
10.00 5
 
1.4%
15.00 4
 
1.2%
24.84 4
 
1.2%
20.00 4
 
1.2%
33.06 3
 
0.9%
16.50 3
 
0.9%
Other values (221) 247
71.2%
2024-05-11T03:57:52.560937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 357
21.0%
. 347
20.4%
2 203
12.0%
1 130
 
7.7%
4 119
 
7.0%
6 117
 
6.9%
8 101
 
6.0%
3 96
 
5.7%
5 92
 
5.4%
7 74
 
4.4%
Other values (2) 61
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1349
79.5%
Other Punctuation 348
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 357
26.5%
2 203
15.0%
1 130
 
9.6%
4 119
 
8.8%
6 117
 
8.7%
8 101
 
7.5%
3 96
 
7.1%
5 92
 
6.8%
7 74
 
5.5%
9 60
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 347
99.7%
, 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1697
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 357
21.0%
. 347
20.4%
2 203
12.0%
1 130
 
7.7%
4 119
 
7.0%
6 117
 
6.9%
8 101
 
6.0%
3 96
 
5.7%
5 92
 
5.4%
7 74
 
4.4%
Other values (2) 61
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 357
21.0%
. 347
20.4%
2 203
12.0%
1 130
 
7.7%
4 119
 
7.0%
6 117
 
6.9%
8 101
 
6.0%
3 96
 
5.7%
5 92
 
5.4%
7 74
 
4.4%
Other values (2) 61
 
3.6%
Distinct80
Distinct (%)23.1%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2024-05-11T03:57:53.300960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1729107
Min length6

Characters and Unicode

Total characters2142
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

Unique32 ?
Unique (%)9.2%

Sample

1st row153823
2nd row153010
3rd row153858
4th row153858
5th row153755
ValueCountFrequency (%)
153863 53
 
15.3%
153803 37
 
10.7%
153755 24
 
6.9%
153801 21
 
6.1%
153802 20
 
5.8%
153-803 12
 
3.5%
153-802 11
 
3.2%
153806 9
 
2.6%
153-755 7
 
2.0%
153813 7
 
2.0%
Other values (70) 146
42.1%
2024-05-11T03:57:54.466953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 490
22.9%
5 439
20.5%
1 405
18.9%
8 284
13.3%
0 165
 
7.7%
6 105
 
4.9%
7 99
 
4.6%
- 60
 
2.8%
2 53
 
2.5%
4 23
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2082
97.2%
Dash Punctuation 60
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 490
23.5%
5 439
21.1%
1 405
19.5%
8 284
13.6%
0 165
 
7.9%
6 105
 
5.0%
7 99
 
4.8%
2 53
 
2.5%
4 23
 
1.1%
9 19
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2142
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 490
22.9%
5 439
20.5%
1 405
18.9%
8 284
13.3%
0 165
 
7.7%
6 105
 
4.9%
7 99
 
4.6%
- 60
 
2.8%
2 53
 
2.5%
4 23
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 490
22.9%
5 439
20.5%
1 405
18.9%
8 284
13.3%
0 165
 
7.7%
6 105
 
4.9%
7 99
 
4.6%
- 60
 
2.8%
2 53
 
2.5%
4 23
 
1.1%
Distinct320
Distinct (%)92.2%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2024-05-11T03:57:55.220684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length31.815562
Min length17

Characters and Unicode

Total characters11040
Distinct characters219
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)87.3%

Sample

1st row서울특별시 금천구 독산동 954-0
2nd row서울특별시 금천구 독산동 286-8 ,13 성빌딩 302호
3rd row서울특별시 금천구 시흥동 904-22
4th row서울특별시 금천구 시흥동 904-14
5th row서울특별시 금천구 시흥동 984 유통상가 16동 211호
ValueCountFrequency (%)
서울특별시 347
 
16.4%
금천구 347
 
16.4%
가산동 145
 
6.8%
시흥동 130
 
6.1%
984 78
 
3.7%
독산동 72
 
3.4%
시흥산업용재유통센타 32
 
1.5%
시흥유통상가 30
 
1.4%
시흥대로 16
 
0.8%
590 13
 
0.6%
Other values (537) 909
42.9%
2024-05-11T03:57:56.600672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1892
 
17.1%
577
 
5.2%
454
 
4.1%
1 453
 
4.1%
351
 
3.2%
351
 
3.2%
351
 
3.2%
349
 
3.2%
348
 
3.2%
347
 
3.1%
Other values (209) 5567
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6242
56.5%
Decimal Number 2488
 
22.5%
Space Separator 1892
 
17.1%
Dash Punctuation 246
 
2.2%
Uppercase Letter 74
 
0.7%
Close Punctuation 44
 
0.4%
Open Punctuation 44
 
0.4%
Other Punctuation 7
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
577
 
9.2%
454
 
7.3%
351
 
5.6%
351
 
5.6%
351
 
5.6%
349
 
5.6%
348
 
5.6%
347
 
5.6%
347
 
5.6%
292
 
4.7%
Other values (171) 2475
39.7%
Uppercase Letter
ValueCountFrequency (%)
B 19
25.7%
T 15
20.3%
I 12
16.2%
A 6
 
8.1%
C 4
 
5.4%
O 2
 
2.7%
R 2
 
2.7%
E 2
 
2.7%
W 2
 
2.7%
K 2
 
2.7%
Other values (6) 8
10.8%
Decimal Number
ValueCountFrequency (%)
1 453
18.2%
0 316
12.7%
2 305
12.3%
3 285
11.5%
9 256
10.3%
4 242
9.7%
5 214
8.6%
8 188
7.6%
6 123
 
4.9%
7 106
 
4.3%
Close Punctuation
ValueCountFrequency (%)
] 37
84.1%
) 5
 
11.4%
2
 
4.5%
Open Punctuation
ValueCountFrequency (%)
[ 37
84.1%
( 5
 
11.4%
2
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
1892
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 246
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6242
56.5%
Common 4722
42.8%
Latin 76
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
577
 
9.2%
454
 
7.3%
351
 
5.6%
351
 
5.6%
351
 
5.6%
349
 
5.6%
348
 
5.6%
347
 
5.6%
347
 
5.6%
292
 
4.7%
Other values (171) 2475
39.7%
Common
ValueCountFrequency (%)
1892
40.1%
1 453
 
9.6%
0 316
 
6.7%
2 305
 
6.5%
3 285
 
6.0%
9 256
 
5.4%
- 246
 
5.2%
4 242
 
5.1%
5 214
 
4.5%
8 188
 
4.0%
Other values (10) 325
 
6.9%
Latin
ValueCountFrequency (%)
B 19
25.0%
T 15
19.7%
I 12
15.8%
A 6
 
7.9%
C 4
 
5.3%
O 2
 
2.6%
R 2
 
2.6%
E 2
 
2.6%
W 2
 
2.6%
K 2
 
2.6%
Other values (8) 10
13.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6242
56.5%
ASCII 4794
43.4%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1892
39.5%
1 453
 
9.4%
0 316
 
6.6%
2 305
 
6.4%
3 285
 
5.9%
9 256
 
5.3%
- 246
 
5.1%
4 242
 
5.0%
5 214
 
4.5%
8 188
 
3.9%
Other values (26) 397
 
8.3%
Hangul
ValueCountFrequency (%)
577
 
9.2%
454
 
7.3%
351
 
5.6%
351
 
5.6%
351
 
5.6%
349
 
5.6%
348
 
5.6%
347
 
5.6%
347
 
5.6%
292
 
4.7%
Other values (171) 2475
39.7%
None
ValueCountFrequency (%)
2
50.0%
2
50.0%

도로명주소
Text

MISSING 

Distinct268
Distinct (%)98.9%
Missing77
Missing (%)22.1%
Memory size2.8 KiB
2024-05-11T03:57:57.432051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length41.00738
Min length22

Characters and Unicode

Total characters11113
Distinct characters206
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

Unique265 ?
Unique (%)97.8%

Sample

1st row서울특별시 금천구 시흥대로 97, 16동 211호 (시흥동,유통상가)
2nd row서울특별시 금천구 시흥대로 368, 용구빌딩 6층 601호 (독산동)
3rd row서울특별시 금천구 가산디지털1로 119, B동 103호 (가산동, sk트윈테크타워)
4th row서울특별시 금천구 서부샛길 606, 대성디폴리스지식산업센터 2층 219호 (가산동)
5th row서울특별시 금천구 디지털로9길 47, 한신IT 타워2차 205호 내 에이20호 (가산동)
ValueCountFrequency (%)
서울특별시 271
 
13.3%
금천구 271
 
13.3%
가산동 120
 
5.9%
시흥대로 82
 
4.0%
시흥동 77
 
3.8%
97 62
 
3.0%
가산디지털1로 52
 
2.6%
독산동 43
 
2.1%
가산디지털2로 30
 
1.5%
시흥유통상가 27
 
1.3%
Other values (525) 999
49.1%
2024-05-11T03:57:59.034666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1763
 
15.9%
533
 
4.8%
1 435
 
3.9%
, 375
 
3.4%
374
 
3.4%
339
 
3.1%
2 310
 
2.8%
286
 
2.6%
281
 
2.5%
276
 
2.5%
Other values (196) 6141
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6364
57.3%
Decimal Number 1920
 
17.3%
Space Separator 1763
 
15.9%
Other Punctuation 375
 
3.4%
Close Punctuation 289
 
2.6%
Open Punctuation 289
 
2.6%
Uppercase Letter 72
 
0.6%
Dash Punctuation 39
 
0.4%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
533
 
8.4%
374
 
5.9%
339
 
5.3%
286
 
4.5%
281
 
4.4%
276
 
4.3%
276
 
4.3%
272
 
4.3%
272
 
4.3%
271
 
4.3%
Other values (163) 3184
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 16
22.2%
B 14
19.4%
I 12
16.7%
A 8
11.1%
C 4
 
5.6%
O 3
 
4.2%
K 3
 
4.2%
S 2
 
2.8%
R 2
 
2.8%
E 2
 
2.8%
Other values (4) 6
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 435
22.7%
2 310
16.1%
3 232
12.1%
0 221
11.5%
9 171
 
8.9%
7 131
 
6.8%
5 125
 
6.5%
6 109
 
5.7%
4 106
 
5.5%
8 80
 
4.2%
Close Punctuation
ValueCountFrequency (%)
) 276
95.5%
] 13
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 276
95.5%
[ 13
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
1763
100.0%
Other Punctuation
ValueCountFrequency (%)
, 375
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6364
57.3%
Common 4675
42.1%
Latin 74
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
533
 
8.4%
374
 
5.9%
339
 
5.3%
286
 
4.5%
281
 
4.4%
276
 
4.3%
276
 
4.3%
272
 
4.3%
272
 
4.3%
271
 
4.3%
Other values (163) 3184
50.0%
Common
ValueCountFrequency (%)
1763
37.7%
1 435
 
9.3%
, 375
 
8.0%
2 310
 
6.6%
) 276
 
5.9%
( 276
 
5.9%
3 232
 
5.0%
0 221
 
4.7%
9 171
 
3.7%
7 131
 
2.8%
Other values (7) 485
 
10.4%
Latin
ValueCountFrequency (%)
T 16
21.6%
B 14
18.9%
I 12
16.2%
A 8
10.8%
C 4
 
5.4%
O 3
 
4.1%
K 3
 
4.1%
S 2
 
2.7%
R 2
 
2.7%
E 2
 
2.7%
Other values (6) 8
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6364
57.3%
ASCII 4749
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1763
37.1%
1 435
 
9.2%
, 375
 
7.9%
2 310
 
6.5%
) 276
 
5.8%
( 276
 
5.8%
3 232
 
4.9%
0 221
 
4.7%
9 171
 
3.6%
7 131
 
2.8%
Other values (23) 559
 
11.8%
Hangul
ValueCountFrequency (%)
533
 
8.4%
374
 
5.9%
339
 
5.3%
286
 
4.5%
281
 
4.4%
276
 
4.3%
276
 
4.3%
272
 
4.3%
272
 
4.3%
271
 
4.3%
Other values (163) 3184
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct79
Distinct (%)29.5%
Missing80
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean8578.9888
Minimum8500
Maximum8656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:57:59.731682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8504.35
Q18512
median8590
Q38639
95-th percentile8639
Maximum8656
Range156
Interquartile range (IQR)127

Descriptive statistics

Standard deviation53.096724
Coefficient of variation (CV)0.0061891587
Kurtosis-1.462017
Mean8578.9888
Median Absolute Deviation (MAD)49
Skewness-0.2426341
Sum2299169
Variance2819.262
MonotonicityNot monotonic
2024-05-11T03:58:00.297751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8639 62
17.8%
8506 19
 
5.5%
8511 14
 
4.0%
8589 12
 
3.4%
8591 10
 
2.9%
8505 8
 
2.3%
8590 8
 
2.3%
8594 7
 
2.0%
8592 7
 
2.0%
8595 6
 
1.7%
Other values (69) 115
33.0%
(Missing) 80
23.0%
ValueCountFrequency (%)
8500 1
 
0.3%
8501 3
 
0.9%
8502 4
 
1.1%
8503 3
 
0.9%
8504 3
 
0.9%
8505 8
2.3%
8506 19
5.5%
8507 5
 
1.4%
8508 1
 
0.3%
8509 1
 
0.3%
ValueCountFrequency (%)
8656 1
 
0.3%
8655 3
 
0.9%
8654 2
 
0.6%
8653 1
 
0.3%
8652 1
 
0.3%
8644 1
 
0.3%
8639 62
17.8%
8638 4
 
1.1%
8635 1
 
0.3%
8634 1
 
0.3%
Distinct338
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T03:58:01.390160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length8.3390805
Min length2

Characters and Unicode

Total characters2902
Distinct characters295
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique329 ?
Unique (%)94.5%

Sample

1st row세명용역(주)
2nd row국제공신(주)
3rd row기우실업
4th row기우실업
5th row(주)대천종합관리
ValueCountFrequency (%)
주식회사 52
 
12.5%
레스컴코리아(주 3
 
0.7%
대박환경 2
 
0.5%
주)한스시설관리 2
 
0.5%
주)인투웍스 2
 
0.5%
주)태전종합관리 2
 
0.5%
거양종합관리(주 2
 
0.5%
주)나루에이치알디 2
 
0.5%
미광기업(주 2
 
0.5%
스마일종합관리시스템 2
 
0.5%
Other values (343) 346
83.0%
2024-05-11T03:58:03.086213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
274
 
9.4%
( 218
 
7.5%
) 218
 
7.5%
128
 
4.4%
82
 
2.8%
73
 
2.5%
71
 
2.4%
69
 
2.4%
67
 
2.3%
66
 
2.3%
Other values (285) 1636
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2362
81.4%
Open Punctuation 218
 
7.5%
Close Punctuation 218
 
7.5%
Space Separator 69
 
2.4%
Uppercase Letter 16
 
0.6%
Lowercase Letter 15
 
0.5%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
274
 
11.6%
128
 
5.4%
82
 
3.5%
73
 
3.1%
71
 
3.0%
67
 
2.8%
66
 
2.8%
62
 
2.6%
40
 
1.7%
35
 
1.5%
Other values (260) 1464
62.0%
Uppercase Letter
ValueCountFrequency (%)
C 4
25.0%
S 2
12.5%
T 2
12.5%
R 1
 
6.2%
E 1
 
6.2%
B 1
 
6.2%
K 1
 
6.2%
A 1
 
6.2%
N 1
 
6.2%
I 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
r 3
20.0%
p 2
13.3%
e 2
13.3%
a 2
13.3%
n 2
13.3%
t 1
 
6.7%
l 1
 
6.7%
c 1
 
6.7%
o 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
& 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 218
100.0%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2362
81.4%
Common 509
 
17.5%
Latin 31
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
274
 
11.6%
128
 
5.4%
82
 
3.5%
73
 
3.1%
71
 
3.0%
67
 
2.8%
66
 
2.8%
62
 
2.6%
40
 
1.7%
35
 
1.5%
Other values (260) 1464
62.0%
Latin
ValueCountFrequency (%)
C 4
 
12.9%
r 3
 
9.7%
S 2
 
6.5%
p 2
 
6.5%
e 2
 
6.5%
a 2
 
6.5%
n 2
 
6.5%
T 2
 
6.5%
R 1
 
3.2%
E 1
 
3.2%
Other values (10) 10
32.3%
Common
ValueCountFrequency (%)
( 218
42.8%
) 218
42.8%
69
 
13.6%
. 3
 
0.6%
& 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2362
81.4%
ASCII 540
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
274
 
11.6%
128
 
5.4%
82
 
3.5%
73
 
3.1%
71
 
3.0%
67
 
2.8%
66
 
2.8%
62
 
2.6%
40
 
1.7%
35
 
1.5%
Other values (260) 1464
62.0%
ASCII
ValueCountFrequency (%)
( 218
40.4%
) 218
40.4%
69
 
12.8%
C 4
 
0.7%
. 3
 
0.6%
r 3
 
0.6%
S 2
 
0.4%
p 2
 
0.4%
e 2
 
0.4%
a 2
 
0.4%
Other values (15) 17
 
3.1%
Distinct334
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2002-01-13 00:00:00
Maximum2024-05-03 09:35:53
2024-05-11T03:58:03.759797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:04.313362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
I
184 
U
164 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 184
52.9%
U 164
47.1%

Length

2024-05-11T03:58:04.880346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:05.295319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 184
52.9%
u 164
47.1%
Distinct143
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T03:58:05.811803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:06.506383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
건물위생관리업
344 
건물위생관리업 기타
 
4

Length

Max length10
Median length7
Mean length7.0344828
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 344
98.9%
건물위생관리업 기타 4
 
1.1%

Length

2024-05-11T03:58:07.306010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:07.826349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 348
98.9%
기타 4
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct166
Distinct (%)48.3%
Missing4
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean190534.76
Minimum189016.47
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:08.568610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189016.47
5-th percentile189353.05
Q1189778.77
median190850.81
Q3191226.29
95-th percentile191608.6
Maximum192754.35
Range3737.8804
Interquartile range (IQR)1447.5129

Descriptive statistics

Standard deviation839.8876
Coefficient of variation (CV)0.0044080545
Kurtosis-1.0554265
Mean190534.76
Median Absolute Deviation (MAD)624.82146
Skewness-0.019005461
Sum65543957
Variance705411.18
MonotonicityNot monotonic
2024-05-11T03:58:09.209394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191226.287379467 82
 
23.6%
189369.53962474 10
 
2.9%
189686.475000033 8
 
2.3%
190050.903572929 7
 
2.0%
189364.095969911 5
 
1.4%
189978.050925581 5
 
1.4%
189788.849463856 5
 
1.4%
189188.74756733 5
 
1.4%
189504.258704224 4
 
1.1%
189538.020935968 4
 
1.1%
Other values (156) 209
60.1%
ValueCountFrequency (%)
189016.465808265 1
 
0.3%
189055.138252216 3
0.9%
189089.927764903 1
 
0.3%
189127.981104583 1
 
0.3%
189174.558570016 1
 
0.3%
189188.74756733 5
1.4%
189202.600232089 3
0.9%
189208.487613747 1
 
0.3%
189353.050637528 3
0.9%
189364.095969911 5
1.4%
ValueCountFrequency (%)
192754.34619252 3
0.9%
192513.506810363 1
 
0.3%
192368.43764933 1
 
0.3%
192292.287116125 1
 
0.3%
191936.282312791 2
0.6%
191924.359561902 1
 
0.3%
191901.802729439 1
 
0.3%
191860.284053667 2
0.6%
191854.695514393 1
 
0.3%
191762.815391328 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct166
Distinct (%)48.3%
Missing4
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean440145.73
Minimum436888.77
Maximum442636.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:09.651363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436888.77
5-th percentile437914.06
Q1437914.06
median440684.46
Q3441629.36
95-th percentile442061.76
Maximum442636.32
Range5747.5466
Interquartile range (IQR)3715.2984

Descriptive statistics

Standard deviation1617.5207
Coefficient of variation (CV)0.0036749663
Kurtosis-1.4167068
Mean440145.73
Median Absolute Deviation (MAD)1160.4995
Skewness-0.36830436
Sum1.5141013 × 108
Variance2616373.3
MonotonicityNot monotonic
2024-05-11T03:58:10.070796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
437914.06299827 82
 
23.6%
441629.361414684 10
 
2.9%
440870.092608694 8
 
2.3%
440523.497478209 7
 
2.0%
441746.981529543 5
 
1.4%
440363.954453659 5
 
1.4%
441731.610478567 5
 
1.4%
441601.047932709 5
 
1.4%
441390.738560411 4
 
1.1%
441982.427934953 4
 
1.1%
Other values (156) 209
60.1%
ValueCountFrequency (%)
436888.773525926 1
 
0.3%
436953.782824253 1
 
0.3%
437044.063129093 1
 
0.3%
437524.860687326 1
 
0.3%
437562.242368734 2
 
0.6%
437720.936273177 1
 
0.3%
437914.06299827 82
23.6%
438251.799466626 1
 
0.3%
438356.170313032 1
 
0.3%
438358.367852933 1
 
0.3%
ValueCountFrequency (%)
442636.320100968 1
 
0.3%
442569.300676147 1
 
0.3%
442493.020182986 3
0.9%
442460.505542105 1
 
0.3%
442354.701937123 1
 
0.3%
442320.784167212 1
 
0.3%
442309.174987731 1
 
0.3%
442298.784420302 1
 
0.3%
442275.414485308 1
 
0.3%
442201.740263751 1
 
0.3%

위생업태명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
건물위생관리업
261 
<NA>
86 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.2672414
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 261
75.0%
<NA> 86
 
24.7%
건물위생관리업 기타 1
 
0.3%

Length

2024-05-11T03:58:10.491288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:10.791027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 262
75.1%
na 86
 
24.6%
기타 1
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)8.2%
Missing128
Missing (%)36.8%
Infinite0
Infinite (%)0.0%
Mean2.8409091
Minimum0
Maximum20
Zeros103
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:11.338900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33.25
95-th percentile14
Maximum20
Range20
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation4.1111452
Coefficient of variation (CV)1.4471231
Kurtosis3.849231
Mean2.8409091
Median Absolute Deviation (MAD)2
Skewness2.0157112
Sum625
Variance16.901515
MonotonicityNot monotonic
2024-05-11T03:58:11.708207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 103
29.6%
3 46
 
13.2%
5 13
 
3.7%
4 13
 
3.7%
2 11
 
3.2%
14 5
 
1.4%
15 5
 
1.4%
1 5
 
1.4%
8 3
 
0.9%
9 3
 
0.9%
Other values (8) 13
 
3.7%
(Missing) 128
36.8%
ValueCountFrequency (%)
0 103
29.6%
1 5
 
1.4%
2 11
 
3.2%
3 46
13.2%
4 13
 
3.7%
5 13
 
3.7%
6 2
 
0.6%
7 3
 
0.9%
8 3
 
0.9%
9 3
 
0.9%
ValueCountFrequency (%)
20 1
 
0.3%
18 1
 
0.3%
16 2
 
0.6%
15 5
1.4%
14 5
1.4%
12 1
 
0.3%
11 2
 
0.6%
10 1
 
0.3%
9 3
0.9%
8 3
0.9%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.8%
Missing137
Missing (%)39.4%
Infinite0
Infinite (%)0.0%
Mean0.54028436
Minimum0
Maximum6
Zeros136
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:12.139765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.95220942
Coefficient of variation (CV)1.7624227
Kurtosis10.337492
Mean0.54028436
Median Absolute Deviation (MAD)0
Skewness2.7401397
Sum114
Variance0.90670278
MonotonicityNot monotonic
2024-05-11T03:58:12.504332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 136
39.1%
1 53
 
15.2%
2 12
 
3.4%
3 7
 
2.0%
6 2
 
0.6%
4 1
 
0.3%
(Missing) 137
39.4%
ValueCountFrequency (%)
0 136
39.1%
1 53
 
15.2%
2 12
 
3.4%
3 7
 
2.0%
4 1
 
0.3%
6 2
 
0.6%
ValueCountFrequency (%)
6 2
 
0.6%
4 1
 
0.3%
3 7
 
2.0%
2 12
 
3.4%
1 53
 
15.2%
0 136
39.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)7.8%
Missing156
Missing (%)44.8%
Infinite0
Infinite (%)0.0%
Mean3.2239583
Minimum0
Maximum22
Zeros16
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:12.734884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile9
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.0744427
Coefficient of variation (CV)0.95362358
Kurtosis10.669384
Mean3.2239583
Median Absolute Deviation (MAD)1
Skewness2.7818547
Sum619
Variance9.4521979
MonotonicityNot monotonic
2024-05-11T03:58:13.060500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 48
 
13.8%
3 46
 
13.2%
1 29
 
8.3%
4 19
 
5.5%
0 16
 
4.6%
5 13
 
3.7%
8 5
 
1.4%
10 3
 
0.9%
15 3
 
0.9%
7 3
 
0.9%
Other values (5) 7
 
2.0%
(Missing) 156
44.8%
ValueCountFrequency (%)
0 16
 
4.6%
1 29
8.3%
2 48
13.8%
3 46
13.2%
4 19
 
5.5%
5 13
 
3.7%
6 2
 
0.6%
7 3
 
0.9%
8 5
 
1.4%
9 2
 
0.6%
ValueCountFrequency (%)
22 1
 
0.3%
16 1
 
0.3%
15 3
 
0.9%
11 1
 
0.3%
10 3
 
0.9%
9 2
 
0.6%
8 5
 
1.4%
7 3
 
0.9%
6 2
 
0.6%
5 13
3.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)8.2%
Missing166
Missing (%)47.7%
Infinite0
Infinite (%)0.0%
Mean3.2307692
Minimum0
Maximum22
Zeros14
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:13.375424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile9
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.0936646
Coefficient of variation (CV)0.95756286
Kurtosis11.013157
Mean3.2307692
Median Absolute Deviation (MAD)1
Skewness2.8648399
Sum588
Variance9.5707607
MonotonicityNot monotonic
2024-05-11T03:58:13.717369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3 49
 
14.1%
2 43
 
12.4%
1 28
 
8.0%
4 19
 
5.5%
0 14
 
4.0%
5 10
 
2.9%
8 4
 
1.1%
10 3
 
0.9%
15 3
 
0.9%
7 3
 
0.9%
Other values (5) 6
 
1.7%
(Missing) 166
47.7%
ValueCountFrequency (%)
0 14
 
4.0%
1 28
8.0%
2 43
12.4%
3 49
14.1%
4 19
 
5.5%
5 10
 
2.9%
6 1
 
0.3%
7 3
 
0.9%
8 4
 
1.1%
9 2
 
0.6%
ValueCountFrequency (%)
22 1
 
0.3%
16 1
 
0.3%
15 3
 
0.9%
11 1
 
0.3%
10 3
 
0.9%
9 2
 
0.6%
8 4
 
1.1%
7 3
 
0.9%
6 1
 
0.3%
5 10
2.9%
Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
247 
0
90 
1
 
10
2
 
1

Length

Max length4
Median length4
Mean length3.1293103
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 247
71.0%
0 90
 
25.9%
1 10
 
2.9%
2 1
 
0.3%

Length

2024-05-11T03:58:14.146974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:14.516288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
71.0%
0 90
 
25.9%
1 10
 
2.9%
2 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
253 
0
85 
1
 
9
2
 
1

Length

Max length4
Median length4
Mean length3.1810345
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 253
72.7%
0 85
 
24.4%
1 9
 
2.6%
2 1
 
0.3%

Length

2024-05-11T03:58:14.910155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:15.247100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 253
72.7%
0 85
 
24.4%
1 9
 
2.6%
2 1
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
185 
<NA>
163 

Length

Max length4
Median length1
Mean length2.4051724
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 185
53.2%
<NA> 163
46.8%

Length

2024-05-11T03:58:15.604477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:16.002465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 185
53.2%
na 163
46.8%

양실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
185 
<NA>
163 

Length

Max length4
Median length1
Mean length2.4051724
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 185
53.2%
<NA> 163
46.8%

Length

2024-05-11T03:58:16.405021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:16.757747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 185
53.2%
na 163
46.8%

욕실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
185 
<NA>
163 

Length

Max length4
Median length1
Mean length2.4051724
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 185
53.2%
<NA> 163
46.8%

Length

2024-05-11T03:58:17.134883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:17.463008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 185
53.2%
na 163
46.8%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing89
Missing (%)25.6%
Memory size828.0 B
False
259 
(Missing)
89 
ValueCountFrequency (%)
False 259
74.4%
(Missing) 89
 
25.6%
2024-05-11T03:58:17.686003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
185 
<NA>
163 

Length

Max length4
Median length1
Mean length2.4051724
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 185
53.2%
<NA> 163
46.8%

Length

2024-05-11T03:58:18.005428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:18.343236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 185
53.2%
na 163
46.8%

조건부허가신고사유
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
340 
공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물만 청소
 
8

Length

Max length43
Median length4
Mean length4.8965517
Min length4

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> 340
97.7%
공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물만 청소 8
 
2.3%

Length

2024-05-11T03:58:18.834054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:19.158711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 340
84.2%
공중위생관리법시행령 8
 
2.0%
제3조제1호의 8
 
2.0%
규정에 8
 
2.0%
의한 8
 
2.0%
건축물규모 8
 
2.0%
이하의 8
 
2.0%
건축물만 8
 
2.0%
청소 8
 
2.0%

조건부허가시작일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing340
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean20060580
Minimum20060316
Maximum20060928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:19.457780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060316
5-th percentile20060316
Q120060319
median20060467
Q320060909
95-th percentile20060925
Maximum20060928
Range612
Interquartile range (IQR)590.25

Descriptive statistics

Standard deviation288.17873
Coefficient of variation (CV)1.4365424 × 10-5
Kurtosis-2.1993359
Mean20060580
Median Absolute Deviation (MAD)151
Skewness0.44969794
Sum1.6048464 × 108
Variance83046.982
MonotonicityIncreasing
2024-05-11T03:58:19.832099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20060316 2
 
0.6%
20060320 1
 
0.3%
20060410 1
 
0.3%
20060524 1
 
0.3%
20060906 1
 
0.3%
20060919 1
 
0.3%
20060928 1
 
0.3%
(Missing) 340
97.7%
ValueCountFrequency (%)
20060316 2
0.6%
20060320 1
0.3%
20060410 1
0.3%
20060524 1
0.3%
20060906 1
0.3%
20060919 1
0.3%
20060928 1
0.3%
ValueCountFrequency (%)
20060928 1
0.3%
20060919 1
0.3%
20060906 1
0.3%
20060524 1
0.3%
20060410 1
0.3%
20060320 1
0.3%
20060316 2
0.6%

조건부허가종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing340
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean20248080
Minimum20060320
Maximum20360928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:20.215662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060320
5-th percentile20095319
Q120160316
median20260912
Q320360438
95-th percentile20360787
Maximum20360928
Range300608
Interquartile range (IQR)200122.5

Descriptive statistics

Standard deviation112747.86
Coefficient of variation (CV)0.0055683234
Kurtosis-0.99018795
Mean20248080
Median Absolute Deviation (MAD)99813.5
Skewness-0.49050182
Sum1.6198464 × 108
Variance1.2712079 × 1010
MonotonicityNot monotonic
2024-05-11T03:58:20.650663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20160316 2
 
0.6%
20060320 1
 
0.3%
20360410 1
 
0.3%
20360524 1
 
0.3%
20260906 1
 
0.3%
20260919 1
 
0.3%
20360928 1
 
0.3%
(Missing) 340
97.7%
ValueCountFrequency (%)
20060320 1
0.3%
20160316 2
0.6%
20260906 1
0.3%
20260919 1
0.3%
20360410 1
0.3%
20360524 1
0.3%
20360928 1
0.3%
ValueCountFrequency (%)
20360928 1
0.3%
20360524 1
0.3%
20360410 1
0.3%
20260919 1
0.3%
20260906 1
0.3%
20160316 2
0.6%
20060320 1
0.3%
Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
256 
임대
85 
자가
 
7

Length

Max length4
Median length4
Mean length3.4712644
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> 256
73.6%
임대 85
 
24.4%
자가 7
 
2.0%

Length

2024-05-11T03:58:21.136092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:21.532630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 256
73.6%
임대 85
 
24.4%
자가 7
 
2.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
179 
<NA>
169 

Length

Max length4
Median length1
Mean length2.4568966
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 (%)
0 179
51.4%
<NA> 169
48.6%

Length

2024-05-11T03:58:21.937343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:22.297483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 179
51.4%
na 169
48.6%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
279 
0
52 
1
 
9
2
 
5
3
 
2

Length

Max length4
Median length4
Mean length3.4051724
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 279
80.2%
0 52
 
14.9%
1 9
 
2.6%
2 5
 
1.4%
3 2
 
0.6%
4 1
 
0.3%

Length

2024-05-11T03:58:22.610715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:22.975209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 279
80.2%
0 52
 
14.9%
1 9
 
2.6%
2 5
 
1.4%
3 2
 
0.6%
4 1
 
0.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)12.3%
Missing267
Missing (%)76.7%
Infinite0
Infinite (%)0.0%
Mean1.962963
Minimum0
Maximum22
Zeros40
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-11T03:58:23.447569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7
Maximum22
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.2536305
Coefficient of variation (CV)1.6575099
Kurtosis17.32332
Mean1.962963
Median Absolute Deviation (MAD)1
Skewness3.3962231
Sum159
Variance10.586111
MonotonicityNot monotonic
2024-05-11T03:58:24.143968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 40
 
11.5%
1 13
 
3.7%
5 8
 
2.3%
3 7
 
2.0%
4 5
 
1.4%
7 3
 
0.9%
2 2
 
0.6%
10 1
 
0.3%
8 1
 
0.3%
22 1
 
0.3%
(Missing) 267
76.7%
ValueCountFrequency (%)
0 40
11.5%
1 13
 
3.7%
2 2
 
0.6%
3 7
 
2.0%
4 5
 
1.4%
5 8
 
2.3%
7 3
 
0.9%
8 1
 
0.3%
10 1
 
0.3%
22 1
 
0.3%
ValueCountFrequency (%)
22 1
 
0.3%
10 1
 
0.3%
8 1
 
0.3%
7 3
 
0.9%
5 8
 
2.3%
4 5
 
1.4%
3 7
 
2.0%
2 2
 
0.6%
1 13
 
3.7%
0 40
11.5%

회수건조수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
179 
0
169 

Length

Max length4
Median length4
Mean length2.5431034
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> 179
51.4%
0 169
48.6%

Length

2024-05-11T03:58:24.798372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:25.409446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 179
51.4%
0 169
48.6%

침대수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
184 
0
164 

Length

Max length4
Median length4
Mean length2.5862069
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> 184
52.9%
0 164
47.1%

Length

2024-05-11T03:58:26.273136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:26.646386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 184
52.9%
0 164
47.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing86
Missing (%)24.7%
Memory size828.0 B
False
262 
(Missing)
86 
ValueCountFrequency (%)
False 262
75.3%
(Missing) 86
 
24.7%
2024-05-11T03:58:26.927962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031700003170000-206-1991-0163719910522<NA>3폐업2폐업20020308<NA><NA><NA>02 8512327.00153823서울특별시 금천구 독산동 954-0<NA><NA>세명용역(주)2003-03-10 00:00:00I2018-08-31 23:59:59.0건물위생관리업191018.503783441704.188253건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131700003170000-206-1993-0162519931030<NA>3폐업2폐업20050316<NA><NA><NA>0232816961270.60153010서울특별시 금천구 독산동 286-8 ,13 성빌딩 302호<NA><NA>국제공신(주)2005-03-16 00:00:00I2018-08-31 23:59:59.0건물위생관리업190941.875019440840.345127건물위생관리업31<NA>3<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231700003170000-206-1994-0162719940225<NA>3폐업2폐업19981209<NA><NA><NA>02 8053527.00153858서울특별시 금천구 시흥동 904-22<NA><NA>기우실업2002-01-13 00:00:00I2018-08-31 23:59:59.0건물위생관리업191368.522097438529.363086건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331700003170000-206-1994-0162819940225<NA>3폐업2폐업19981030<NA><NA><NA>02 8053527.00153858서울특별시 금천구 시흥동 904-14<NA><NA>기우실업2002-01-13 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431700003170000-206-1995-0162419950412<NA>1영업/정상1영업<NA><NA><NA><NA>02 894200555.00153755서울특별시 금천구 시흥동 984 유통상가 16동 211호서울특별시 금천구 시흥대로 97, 16동 211호 (시흥동,유통상가)8639(주)대천종합관리2019-11-08 10:19:11U2019-11-10 02:40:00.0건물위생관리업191226.287379437914.062998건물위생관리업31<NA>3<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531700003170000-206-1995-0162919950919<NA>3폐업2폐업19981202<NA><NA><NA>02 804152241.40153856서울특별시 금천구 시흥동 840-61<NA><NA>대일실업2002-01-13 00:00:00I2018-08-31 23:59:59.0건물위생관리업191568.013608439074.745048건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631700003170000-206-1996-0163019960813<NA>3폐업2폐업20030403<NA><NA><NA>02 8661700.00153825서울특별시 금천구 독산동 990-12<NA><NA>삼성환경용역(주)2003-04-09 00:00:00I2018-08-31 23:59:59.0건물위생관리업191348.450842441218.951255건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731700003170000-206-1996-0163119960327<NA>3폐업2폐업20030403<NA><NA><NA>02 8623540.00153813서울특별시 금천구 독산동 296-16<NA><NA>(주)새로한2003-04-09 00:00:00I2018-08-31 23:59:59.0건물위생관리업190804.003574441018.620016건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831700003170000-206-1996-016321996-12-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 8688381119.00153-830서울특별시 금천구 독산동 1031 용구빌딩서울특별시 금천구 시흥대로 368, 용구빌딩 6층 601호 (독산동)8616(주)푸른환경코리아2024-01-10 11:08:50U2023-11-30 23:02:00.0건물위생관리업190912.168726440461.875991<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931700003170000-206-1997-0000119970607<NA>3폐업2폐업20160616<NA><NA><NA>02 854079014.00153802서울특별시 금천구 가산동 345-9 sk트윈테크타워 B동 103호서울특별시 금천구 가산디지털1로 119, B동 103호 (가산동, sk트윈테크타워)8589(주)엘리트시스템2014-07-01 14:29:24I2018-08-31 23:59:59.0건물위생관리업189575.815288441503.181731건물위생관리업4112<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
33831700003170000-206-2023-000032023-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.86153-755서울특별시 금천구 시흥동 984 시흥유통상가서울특별시 금천구 시흥대로 97, 시흥유통상가 16동 323호 (시흥동)8639깨공2023-04-11 13:58:52I2022-12-03 23:03:00.0건물위생관리업191226.287379437914.062998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33931700003170000-206-2023-000042023-08-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>89.10153-802서울특별시 금천구 가산동 345-29 대륭테크노타운19차서울특별시 금천구 가산디지털2로 70, 대륭테크노타운19차 6층 602호 (가산동)8589주식회사 케이티링스2023-08-03 13:40:47I2022-12-08 00:05:00.0건물위생관리업189504.258704441390.73856<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34031700003170000-206-2023-000052023-10-31<NA>1영업/정상1영업<NA><NA><NA><NA>031 48185623.30153-801서울특별시 금천구 가산동 60-17 백상스타타워1차서울특별시 금천구 디지털로9길 65, 백상스타타워1차 1동 15층 1508호 (가산동)8511종은 주식회사2023-10-31 17:04:18I2022-11-01 00:02:00.0건물위생관리업189790.323887442017.867458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34131700003170000-206-2023-000062023-11-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.86153-755서울특별시 금천구 시흥동 984 시흥유통상가서울특별시 금천구 시흥대로 97, 시흥유통상가 6동 3층 326호 (시흥동)8639백두 E&C2023-11-20 15:17:06I2022-10-31 22:02:00.0건물위생관리업191226.287379437914.062998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34231700003170000-206-2023-000072023-12-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.00153-768서울특별시 금천구 가산동 371-16 IT캐슬2차서울특별시 금천구 가산디지털1로 137, IT캐슬2차 19층 1901-비-32호 (가산동)8506주식회사 대종시스템2023-12-20 13:19:51I2022-11-01 22:03:00.0건물위생관리업189497.040985441728.270598<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34331700003170000-206-2023-000082023-12-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.63153-030서울특별시 금천구 시흥동 1009 시흥목련아파트서울특별시 금천구 금하로3길 26, 상가동 지하103호 (시흥동, 시흥목련아파트)8615주식회사 더블유제이코리아2023-12-22 15:46:32I2022-11-01 22:04:00.0건물위생관리업 기타190875.716929439163.851308<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34431700003170000-206-2024-000012024-02-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.90153-030서울특별시 금천구 시흥동 1013-7 벽산중심상가서울특별시 금천구 금하로 763, 벽산중심상가 2층 205-7호 (시흥동)8656유앤아이클린2024-02-16 14:11:21I2023-12-01 23:08:00.0건물위생관리업192368.437649438690.814038<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34531700003170000-206-2024-000022024-02-22<NA>1영업/정상1영업<NA><NA><NA><NA>022102030079.80153-802서울특별시 금천구 가산동 327-5서울특별시 금천구 가산디지털2로 34, 지밸리더리브스마트타워 404, 405호 (가산동)8592주식회사 에코유2024-02-22 17:02:48I2023-12-01 22:04:00.0건물위생관리업189622.332386441057.177316<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34631700003170000-206-2024-000032024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.86153-755서울특별시 금천구 시흥동 984 시흥유통상가서울특별시 금천구 시흥대로 97, 시흥유통상가 8동 327호 (시흥동)8639클린크린2024-04-17 11:02:08I2023-12-03 23:09:00.0건물위생관리업191226.287379437914.062998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34731700003170000-206-2024-000042024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.10153-801서울특별시 금천구 가산동 60-18 한신IT 타워2차서울특별시 금천구 디지털로9길 47, 한신IT 타워2차 704-1(53호)호 (가산동)8511(주)코지몬홈케어2024-04-18 14:59:01I2023-12-03 22:00:00.0건물위생관리업189834.383376441938.326057<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>