Overview

Dataset statistics

Number of variables33
Number of observations44
Missing cells544
Missing cells (%)37.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.3 KiB
Average record size in memory287.0 B

Variable types

Categorical11
Numeric4
DateTime3
Unsupported10
Text5

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),업무구분,건축물명,건축물연면적,건축물상태명,청소대상시작일자,청소대상종료일자,휴업폐지사유,업무구분명
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-19486/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (84.4%)Imbalance
휴업종료일자 is highly imbalanced (84.4%)Imbalance
인허가취소일자 has 44 (100.0%) missing valuesMissing
폐업일자 has 30 (68.2%) missing valuesMissing
재개업일자 has 44 (100.0%) missing valuesMissing
전화번호 has 8 (18.2%) missing valuesMissing
소재지면적 has 44 (100.0%) missing valuesMissing
소재지우편번호 has 44 (100.0%) missing valuesMissing
도로명주소 has 7 (15.9%) missing valuesMissing
도로명우편번호 has 27 (61.4%) missing valuesMissing
업태구분명 has 44 (100.0%) missing valuesMissing
건축물명 has 44 (100.0%) missing valuesMissing
건축물연면적 has 44 (100.0%) missing valuesMissing
건축물상태명 has 44 (100.0%) missing valuesMissing
청소대상시작일자 has 44 (100.0%) missing valuesMissing
청소대상종료일자 has 44 (100.0%) missing valuesMissing
휴업폐지사유 has 32 (72.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물상태명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
청소대상시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
청소대상종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:48:04.263418
Analysis finished2024-05-11 06:48:04.831288
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
3090000
44 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 44
100.0%

Length

2024-05-11T15:48:04.936837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:05.106548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 44
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0900003 × 1017
Minimum3.0900003 × 1017
Maximum3.0900003 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T15:48:05.311713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0900003 × 1017
5-th percentile3.0900003 × 1017
Q13.0900003 × 1017
median3.0900003 × 1017
Q33.0900003 × 1017
95-th percentile3.0900003 × 1017
Maximum3.0900003 × 1017
Range2400003
Interquartile range (IQR)675008

Descriptive statistics

Standard deviation620660.08
Coefficient of variation (CV)2.0086085 × 10-12
Kurtosis0.12048278
Mean3.0900003 × 1017
Median Absolute Deviation (MAD)450016
Skewness-0.72109183
Sum-4.8507427 × 1018
Variance3.8521893 × 1011
MonotonicityStrictly increasing
2024-05-11T15:48:05.565084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
309000031199800001 1
 
2.3%
309000031201600002 1
 
2.3%
309000031201600004 1
 
2.3%
309000031201600005 1
 
2.3%
309000031201600006 1
 
2.3%
309000031201600007 1
 
2.3%
309000031201600008 1
 
2.3%
309000031201600009 1
 
2.3%
309000031201600010 1
 
2.3%
309000031201600011 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
309000031199800001 1
2.3%
309000031199800002 1
2.3%
309000031200200001 1
2.3%
309000031200300003 1
2.3%
309000031200600001 1
2.3%
309000031200700001 1
2.3%
309000031200700003 1
2.3%
309000031200800001 1
2.3%
309000031200800002 1
2.3%
309000031200800003 1
2.3%
ValueCountFrequency (%)
309000031202200004 1
2.3%
309000031202200003 1
2.3%
309000031202200002 1
2.3%
309000031202200001 1
2.3%
309000031202100003 1
2.3%
309000031202100002 1
2.3%
309000031202100001 1
2.3%
309000031201900001 1
2.3%
309000031201800002 1
2.3%
309000031201800001 1
2.3%

인허가일자
Date

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum1995-02-08 00:00:00
Maximum2024-01-19 00:00:00
2024-05-11T15:48:05.803941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:48:06.035173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

영업상태코드
Categorical

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
1
28 
3
12 
4
 
2
2
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
63.6%
3 12
27.3%
4 2
 
4.5%
2 1
 
2.3%
5 1
 
2.3%

Length

2024-05-11T15:48:06.261216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:06.452816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
63.6%
3 12
27.3%
4 2
 
4.5%
2 1
 
2.3%
5 1
 
2.3%

영업상태명
Categorical

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
영업/정상
28 
폐업
12 
취소/말소/만료/정지/중지
 
2
휴업
 
1
제외/삭제/전출
 
1

Length

Max length14
Median length5
Mean length4.5909091
Min length2

Unique

Unique2 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 28
63.6%
폐업 12
27.3%
취소/말소/만료/정지/중지 2
 
4.5%
휴업 1
 
2.3%
제외/삭제/전출 1
 
2.3%

Length

2024-05-11T15:48:06.693216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:06.893595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 28
63.6%
폐업 12
27.3%
취소/말소/만료/정지/중지 2
 
4.5%
휴업 1
 
2.3%
제외/삭제/전출 1
 
2.3%

상세영업상태코드
Categorical

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
11
28 
2
12 
4
 
2
1
 
1
5
 
1

Length

Max length2
Median length2
Mean length1.6363636
Min length1

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st row11
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
11 28
63.6%
2 12
27.3%
4 2
 
4.5%
1 1
 
2.3%
5 1
 
2.3%

Length

2024-05-11T15:48:07.122945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:07.321809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 28
63.6%
2 12
27.3%
4 2
 
4.5%
1 1
 
2.3%
5 1
 
2.3%

상세영업상태명
Categorical

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
정상
28 
폐업
12 
폐쇄
 
2
휴업
 
1
제외사항
 
1

Length

Max length4
Median length2
Mean length2.0454545
Min length2

Unique

Unique2 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
정상 28
63.6%
폐업 12
27.3%
폐쇄 2
 
4.5%
휴업 1
 
2.3%
제외사항 1
 
2.3%

Length

2024-05-11T15:48:07.557929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:07.768703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 28
63.6%
폐업 12
27.3%
폐쇄 2
 
4.5%
휴업 1
 
2.3%
제외사항 1
 
2.3%

폐업일자
Date

MISSING 

Distinct14
Distinct (%)100.0%
Missing30
Missing (%)68.2%
Memory size484.0 B
Minimum2009-03-19 00:00:00
Maximum2023-11-08 00:00:00
2024-05-11T15:48:07.953555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:48:08.151308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
43 
20201105
 
1

Length

Max length8
Median length4
Mean length4.0909091
Min length4

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
97.7%
20201105 1
 
2.3%

Length

2024-05-11T15:48:08.380742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:08.593736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
97.7%
20201105 1
 
2.3%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
43 
20211105
 
1

Length

Max length8
Median length4
Mean length4.0909091
Min length4

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
97.7%
20211105 1
 
2.3%

Length

2024-05-11T15:48:08.791049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:09.004717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
97.7%
20211105 1
 
2.3%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

전화번호
Text

MISSING 

Distinct35
Distinct (%)97.2%
Missing8
Missing (%)18.2%
Memory size484.0 B
2024-05-11T15:48:09.313203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.861111
Min length8

Characters and Unicode

Total characters391
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row02-992-2403
2nd row02-998-8375
3rd row029001486
4th row02-2649-4386
5th row955-1687
ValueCountFrequency (%)
02-930-2911 2
 
5.6%
02-995-0160 1
 
2.8%
02-929-2580 1
 
2.8%
02-955-0612 1
 
2.8%
02-991-8839 1
 
2.8%
02-991-7393 1
 
2.8%
02-900-9487 1
 
2.8%
02-999-3110 1
 
2.8%
02-538-3080 1
 
2.8%
029835472 1
 
2.8%
Other values (25) 25
69.4%
2024-05-11T15:48:09.880473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62
15.9%
- 62
15.9%
9 62
15.9%
2 50
12.8%
3 28
7.2%
1 26
6.6%
8 24
 
6.1%
5 21
 
5.4%
7 20
 
5.1%
4 19
 
4.9%
Other values (3) 17
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 326
83.4%
Dash Punctuation 62
 
15.9%
Math Symbol 2
 
0.5%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
19.0%
9 62
19.0%
2 50
15.3%
3 28
8.6%
1 26
8.0%
8 24
 
7.4%
5 21
 
6.4%
7 20
 
6.1%
4 19
 
5.8%
6 14
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62
15.9%
- 62
15.9%
9 62
15.9%
2 50
12.8%
3 28
7.2%
1 26
6.6%
8 24
 
6.1%
5 21
 
5.4%
7 20
 
5.1%
4 19
 
4.9%
Other values (3) 17
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62
15.9%
- 62
15.9%
9 62
15.9%
2 50
12.8%
3 28
7.2%
1 26
6.6%
8 24
 
6.1%
5 21
 
5.4%
7 20
 
5.1%
4 19
 
4.9%
Other values (3) 17
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

지번주소
Text

Distinct36
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-05-11T15:48:10.209996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length36
Mean length22.136364
Min length14

Characters and Unicode

Total characters974
Distinct characters54
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

Unique31 ?
Unique (%)70.5%

Sample

1st row서울특별시 도봉구 쌍문동 *** (*층)
2nd row서울특별시 도봉구 방학동 683-23
3rd row서울특별시 도봉구 도봉동 569-2
4th row서울특별시 도봉구 도봉동 641 서원아파트
5th row서울특별시 도봉구 창동 756-206
ValueCountFrequency (%)
서울특별시 44
22.0%
도봉구 44
22.0%
19
9.5%
쌍문동 14
 
7.0%
도봉동 13
 
6.5%
창동 11
 
5.5%
방학동 6
 
3.0%
호 4
 
2.0%
103-25 3
 
1.5%
세정빌딩 2
 
1.0%
Other values (37) 40
20.0%
2024-05-11T15:48:10.750254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
18.2%
* 97
 
10.0%
도 58
 
6.0%
봉 58
 
6.0%
동 47
 
4.8%
시 46
 
4.7%
서 45
 
4.6%
울 44
 
4.5%
특 44
 
4.5%
별 44
 
4.5%
Other values (44) 314
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 535
54.9%
Space Separator 177
 
18.2%
Decimal Number 124
 
12.7%
Other Punctuation 97
 
10.0%
Dash Punctuation 38
 
3.9%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 58
10.8%
봉 58
10.8%
동 47
8.8%
시 46
8.6%
서 45
8.4%
울 44
8.2%
특 44
8.2%
별 44
8.2%
구 44
8.2%
쌍 15
 
2.8%
Other values (28) 90
16.8%
Decimal Number
ValueCountFrequency (%)
2 24
19.4%
1 20
16.1%
6 17
13.7%
0 13
10.5%
3 13
10.5%
5 11
8.9%
4 8
 
6.5%
8 7
 
5.6%
9 6
 
4.8%
7 5
 
4.0%
Space Separator
ValueCountFrequency (%)
177
100.0%
Other Punctuation
ValueCountFrequency (%)
* 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 535
54.9%
Common 438
45.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 58
10.8%
봉 58
10.8%
동 47
8.8%
시 46
8.6%
서 45
8.4%
울 44
8.2%
특 44
8.2%
별 44
8.2%
구 44
8.2%
쌍 15
 
2.8%
Other values (28) 90
16.8%
Common
ValueCountFrequency (%)
177
40.4%
* 97
22.1%
- 38
 
8.7%
2 24
 
5.5%
1 20
 
4.6%
6 17
 
3.9%
0 13
 
3.0%
3 13
 
3.0%
5 11
 
2.5%
4 8
 
1.8%
Other values (5) 20
 
4.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 535
54.9%
ASCII 439
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
40.3%
* 97
22.1%
- 38
 
8.7%
2 24
 
5.5%
1 20
 
4.6%
6 17
 
3.9%
0 13
 
3.0%
3 13
 
3.0%
5 11
 
2.5%
4 8
 
1.8%
Other values (6) 21
 
4.8%
Hangul
ValueCountFrequency (%)
도 58
10.8%
봉 58
10.8%
동 47
8.8%
시 46
8.6%
서 45
8.4%
울 44
8.2%
특 44
8.2%
별 44
8.2%
구 44
8.2%
쌍 15
 
2.8%
Other values (28) 90
16.8%

도로명주소
Text

MISSING 

Distinct34
Distinct (%)91.9%
Missing7
Missing (%)15.9%
Memory size484.0 B
2024-05-11T15:48:11.147079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length36
Mean length29.918919
Min length24

Characters and Unicode

Total characters1107
Distinct characters74
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

Unique32 ?
Unique (%)86.5%

Sample

1st row서울특별시 도봉구 도봉로***길 *, *층 (쌍문동)
2nd row서울특별시 도봉구 마들로 684-19 (도봉동, 서원아파트)
3rd row서울특별시 도봉구 시루봉로 ***-* (도봉동)
4th row서울특별시 도봉구 해등로**길 **, ***호 (쌍문동)
5th row서울특별시 도봉구 노해로69길 15, 세정빌딩 702-2호 (창동)
ValueCountFrequency (%)
서울특별시 37
17.1%
도봉구 37
17.1%
19
 
8.8%
쌍문동 13
 
6.0%
도봉동 11
 
5.1%
창동 9
 
4.1%
도봉로***길 7
 
3.2%
호 6
 
2.8%
층 5
 
2.3%
도봉로 4
 
1.8%
Other values (60) 69
31.8%
2024-05-11T15:48:11.783419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
16.3%
* 107
 
9.7%
도 73
 
6.6%
봉 72
 
6.5%
동 41
 
3.7%
시 41
 
3.7%
서 38
 
3.4%
특 37
 
3.3%
별 37
 
3.3%
구 37
 
3.3%
Other values (64) 444
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
55.6%
Space Separator 180
 
16.3%
Other Punctuation 129
 
11.7%
Decimal Number 101
 
9.1%
Open Punctuation 37
 
3.3%
Close Punctuation 37
 
3.3%
Dash Punctuation 7
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 73
11.9%
봉 72
11.7%
동 41
 
6.7%
시 41
 
6.7%
서 38
 
6.2%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 36
 
5.9%
Other values (47) 166
27.0%
Decimal Number
ValueCountFrequency (%)
1 21
20.8%
0 14
13.9%
2 12
11.9%
5 11
10.9%
9 11
10.9%
7 8
 
7.9%
3 7
 
6.9%
6 7
 
6.9%
4 7
 
6.9%
8 3
 
3.0%
Other Punctuation
ValueCountFrequency (%)
* 107
82.9%
, 22
 
17.1%
Space Separator
ValueCountFrequency (%)
180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
55.6%
Common 491
44.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 73
11.9%
봉 72
11.7%
동 41
 
6.7%
시 41
 
6.7%
서 38
 
6.2%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 36
 
5.9%
Other values (47) 166
27.0%
Common
ValueCountFrequency (%)
180
36.7%
* 107
21.8%
( 37
 
7.5%
) 37
 
7.5%
, 22
 
4.5%
1 21
 
4.3%
0 14
 
2.9%
2 12
 
2.4%
5 11
 
2.2%
9 11
 
2.2%
Other values (6) 39
 
7.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
55.6%
ASCII 492
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
36.6%
* 107
21.7%
( 37
 
7.5%
) 37
 
7.5%
, 22
 
4.5%
1 21
 
4.3%
0 14
 
2.8%
2 12
 
2.4%
5 11
 
2.2%
9 11
 
2.2%
Other values (7) 40
 
8.1%
Hangul
ValueCountFrequency (%)
도 73
11.9%
봉 72
11.7%
동 41
 
6.7%
시 41
 
6.7%
서 38
 
6.2%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 36
 
5.9%
Other values (47) 166
27.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)94.1%
Missing27
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean1377.0588
Minimum1304
Maximum1480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T15:48:11.978368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1304
5-th percentile1305.6
Q11318
median1348
Q31448
95-th percentile1464
Maximum1480
Range176
Interquartile range (IQR)130

Descriptive statistics

Standard deviation66.547418
Coefficient of variation (CV)0.048325763
Kurtosis-1.8013167
Mean1377.0588
Median Absolute Deviation (MAD)42
Skewness0.30435391
Sum23410
Variance4428.5588
MonotonicityNot monotonic
2024-05-11T15:48:12.146687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1318 2
 
4.5%
1321 1
 
2.3%
1304 1
 
2.3%
1389 1
 
2.3%
1453 1
 
2.3%
1480 1
 
2.3%
1308 1
 
2.3%
1460 1
 
2.3%
1324 1
 
2.3%
1432 1
 
2.3%
Other values (6) 6
 
13.6%
(Missing) 27
61.4%
ValueCountFrequency (%)
1304 1
2.3%
1306 1
2.3%
1308 1
2.3%
1318 2
4.5%
1321 1
2.3%
1324 1
2.3%
1328 1
2.3%
1348 1
2.3%
1389 1
2.3%
1414 1
2.3%
ValueCountFrequency (%)
1480 1
2.3%
1460 1
2.3%
1459 1
2.3%
1453 1
2.3%
1448 1
2.3%
1432 1
2.3%
1414 1
2.3%
1389 1
2.3%
1348 1
2.3%
1328 1
2.3%

사업장명
Text

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-05-11T15:48:12.463059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length6.8409091
Min length4

Characters and Unicode

Total characters301
Distinct characters108
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)93.2%

Sample

1st row트래져건설(주)
2nd row고려종합환경
3rd row익제건설산업(주)
4th row(주)성광씨앤씨
5th row대명환경
ValueCountFrequency (%)
대한환경공사 3
 
6.5%
주식회사 2
 
4.3%
엠에스씨엔이(주 1
 
2.2%
광호이엔씨 1
 
2.2%
금보씨앤씨(주 1
 
2.2%
주)이산아이엔씨 1
 
2.2%
주)코너스톤티엠에스 1
 
2.2%
부림기업 1
 
2.2%
청수환경개발 1
 
2.2%
임천토건㈜ 1
 
2.2%
Other values (33) 33
71.7%
2024-05-11T15:48:12.955190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 19
 
6.3%
) 17
 
5.6%
( 17
 
5.6%
환 15
 
5.0%
경 15
 
5.0%
이 8
 
2.7%
씨 7
 
2.3%
대 6
 
2.0%
엔 6
 
2.0%
업 6
 
2.0%
Other values (98) 185
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
85.0%
Close Punctuation 17
 
5.6%
Open Punctuation 17
 
5.6%
Uppercase Letter 5
 
1.7%
Other Symbol 4
 
1.3%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 19
 
7.4%
환 15
 
5.9%
경 15
 
5.9%
이 8
 
3.1%
씨 7
 
2.7%
대 6
 
2.3%
엔 6
 
2.3%
업 6
 
2.3%
설 6
 
2.3%
건 6
 
2.3%
Other values (89) 162
63.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
20.0%
W 1
20.0%
A 1
20.0%
S 1
20.0%
H 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
86.4%
Common 36
 
12.0%
Latin 5
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 19
 
7.3%
환 15
 
5.8%
경 15
 
5.8%
이 8
 
3.1%
씨 7
 
2.7%
대 6
 
2.3%
엔 6
 
2.3%
업 6
 
2.3%
설 6
 
2.3%
건 6
 
2.3%
Other values (90) 166
63.8%
Latin
ValueCountFrequency (%)
K 1
20.0%
W 1
20.0%
A 1
20.0%
S 1
20.0%
H 1
20.0%
Common
ValueCountFrequency (%)
) 17
47.2%
( 17
47.2%
2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
85.0%
ASCII 41
 
13.6%
None 4
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 19
 
7.4%
환 15
 
5.9%
경 15
 
5.9%
이 8
 
3.1%
씨 7
 
2.7%
대 6
 
2.3%
엔 6
 
2.3%
업 6
 
2.3%
설 6
 
2.3%
건 6
 
2.3%
Other values (89) 162
63.3%
ASCII
ValueCountFrequency (%)
) 17
41.5%
( 17
41.5%
2
 
4.9%
K 1
 
2.4%
W 1
 
2.4%
A 1
 
2.4%
S 1
 
2.4%
H 1
 
2.4%
None
ValueCountFrequency (%)
㈜ 4
100.0%

최종수정일자
Date

Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2015-01-05 21:07:09
Maximum2024-01-22 09:02:21
2024-05-11T15:48:13.195419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:48:13.427312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
U
35 
I
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 35
79.5%
I 9
 
20.5%

Length

2024-05-11T15:48:13.584984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:14.049990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 35
79.5%
i 9
 
20.5%

데이터갱신일자
Categorical

Distinct16
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
2022-12-03 00:03:00.0
11 
2020-10-09 02:40:00.0
10 
2018-08-31 23:59:59.0
9 
2022-10-30 22:07:00.0
2 
2020-01-17 02:40:00.0
 
1
Other values (11)
11 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique12 ?
Unique (%)27.3%

Sample

1st row2022-12-03 00:03:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2020-10-09 02:40:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2022-12-03 00:03:00.0 11
25.0%
2020-10-09 02:40:00.0 10
22.7%
2018-08-31 23:59:59.0 9
20.5%
2022-10-30 22:07:00.0 2
 
4.5%
2020-01-17 02:40:00.0 1
 
2.3%
2022-10-31 23:01:00.0 1
 
2.3%
2020-11-06 02:40:00.0 1
 
2.3%
2021-10-30 23:05:00.0 1
 
2.3%
2020-11-15 02:40:00.0 1
 
2.3%
2018-10-10 02:37:31.0 1
 
2.3%
Other values (6) 6
13.6%

Length

2024-05-11T15:48:14.203094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 14
15.9%
2022-12-03 11
12.5%
00:03:00.0 11
12.5%
2020-10-09 10
11.4%
2018-08-31 9
10.2%
23:59:59.0 9
10.2%
2022-10-30 3
 
3.4%
22:05:00.0 2
 
2.3%
22:07:00.0 2
 
2.3%
2022-10-31 2
 
2.3%
Other values (15) 15
17.0%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

좌표정보(X)
Real number (ℝ)

Distinct38
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203464.52
Minimum202139.5
Maximum204488.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T15:48:14.378231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202139.5
5-th percentile202823.17
Q1203114.6
median203378.48
Q3203838.39
95-th percentile204373.2
Maximum204488.65
Range2349.1534
Interquartile range (IQR)723.79546

Descriptive statistics

Standard deviation519.1671
Coefficient of variation (CV)0.0025516346
Kurtosis-0.24967428
Mean203464.52
Median Absolute Deviation (MAD)413.30012
Skewness0.021890937
Sum8952438.9
Variance269534.48
MonotonicityNot monotonic
2024-05-11T15:48:14.544202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
202823.174373122 4
 
9.1%
203378.483575907 2
 
4.5%
204035.063229754 2
 
4.5%
204397.004135761 2
 
4.5%
203523.40741937 1
 
2.3%
203178.306638511 1
 
2.3%
203416.357247408 1
 
2.3%
203205.640915578 1
 
2.3%
202139.497291582 1
 
2.3%
203948.554991818 1
 
2.3%
Other values (28) 28
63.6%
ValueCountFrequency (%)
202139.497291582 1
 
2.3%
202735.759318719 1
 
2.3%
202823.174373122 4
9.1%
202940.779948154 1
 
2.3%
202960.838283538 1
 
2.3%
202969.528630363 1
 
2.3%
203046.605642133 1
 
2.3%
203092.044284656 1
 
2.3%
203122.115130691 1
 
2.3%
203178.306638511 1
 
2.3%
ValueCountFrequency (%)
204488.650732578 1
2.3%
204397.004135761 2
4.5%
204238.33386129 1
2.3%
204172.527806715 1
2.3%
204086.827227653 1
2.3%
204035.063229754 2
4.5%
203948.554991818 1
2.3%
203860.575624964 1
2.3%
203848.772422951 1
2.3%
203834.933037296 1
2.3%

좌표정보(Y)
Real number (ℝ)

Distinct38
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean462009.25
Minimum459130.89
Maximum465042.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T15:48:14.714683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum459130.89
5-th percentile459906.13
Q1460544.35
median461658.08
Q3463312.01
95-th percentile464739.77
Maximum465042.49
Range5911.5997
Interquartile range (IQR)2767.6557

Descriptive statistics

Standard deviation1593.8248
Coefficient of variation (CV)0.0034497683
Kurtosis-0.99474621
Mean462009.25
Median Absolute Deviation (MAD)1318.9515
Skewness0.28041994
Sum20328407
Variance2540277.6
MonotonicityNot monotonic
2024-05-11T15:48:14.927276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
460470.534272629 4
 
9.1%
461658.084175108 2
 
4.5%
465042.493324016 2
 
4.5%
461175.40204195 2
 
4.5%
463361.090695995 1
 
2.3%
461715.702573753 1
 
2.3%
463089.352123743 1
 
2.3%
460568.959523177 1
 
2.3%
460872.911491549 1
 
2.3%
463353.420877618 1
 
2.3%
Other values (28) 28
63.6%
ValueCountFrequency (%)
459130.893656814 1
 
2.3%
459746.924430501 1
 
2.3%
459857.218303243 1
 
2.3%
460183.287772488 1
 
2.3%
460197.003767157 1
 
2.3%
460259.892791501 1
 
2.3%
460294.478333338 1
 
2.3%
460470.534272629 4
9.1%
460568.959523177 1
 
2.3%
460847.228621157 1
 
2.3%
ValueCountFrequency (%)
465042.493324016 2
4.5%
464769.943318963 1
2.3%
464568.775185456 1
2.3%
464186.380359292 1
2.3%
464092.187505065 1
2.3%
463804.941164456 1
2.3%
463621.090034536 1
2.3%
463449.540298026 1
2.3%
463361.090695995 1
2.3%
463353.420877618 1
2.3%

업무구분
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
31
24 
<NA>
20 

Length

Max length4
Median length2
Mean length2.9090909
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row31
3rd row31
4th row31
5th row31

Common Values

ValueCountFrequency (%)
31 24
54.5%
<NA> 20
45.5%

Length

2024-05-11T15:48:15.152367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:15.352909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31 24
54.5%
na 20
45.5%

건축물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

건축물연면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

건축물상태명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

청소대상시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

청소대상종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

휴업폐지사유
Text

MISSING 

Distinct10
Distinct (%)83.3%
Missing32
Missing (%)72.7%
Memory size484.0 B
2024-05-11T15:48:15.576911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.75
Min length4

Characters and Unicode

Total characters81
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)66.7%

Sample

1st row강북구이전
2nd row영업부진
3rd row사업장 타구 이전
4th row영업부진
5th row타구이전
ValueCountFrequency (%)
사업장 6
27.3%
이전 4
18.2%
영업부진 2
 
9.1%
강북구이전 1
 
4.5%
타구 1
 
4.5%
타구이전 1
 
4.5%
새올에 1
 
4.5%
이중입력 1
 
4.5%
폐쇄 1
 
4.5%
사업부진 1
 
4.5%
Other values (3) 3
13.6%
2024-05-11T15:48:15.944909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 10
12.3%
10
12.3%
사 8
 
9.9%
이 7
 
8.6%
장 6
 
7.4%
전 6
 
7.4%
부 4
 
4.9%
진 4
 
4.9%
구 4
 
4.9%
영 2
 
2.5%
Other values (19) 20
24.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
85.2%
Space Separator 10
 
12.3%
Close Punctuation 1
 
1.2%
Open Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 10
14.5%
사 8
11.6%
이 7
10.1%
장 6
 
8.7%
전 6
 
8.7%
부 4
 
5.8%
진 4
 
5.8%
구 4
 
5.8%
영 2
 
2.9%
타 2
 
2.9%
Other values (16) 16
23.2%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
85.2%
Common 12
 
14.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 10
14.5%
사 8
11.6%
이 7
10.1%
장 6
 
8.7%
전 6
 
8.7%
부 4
 
5.8%
진 4
 
5.8%
구 4
 
5.8%
영 2
 
2.9%
타 2
 
2.9%
Other values (16) 16
23.2%
Common
ValueCountFrequency (%)
10
83.3%
) 1
 
8.3%
( 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
85.2%
ASCII 12
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 10
14.5%
사 8
11.6%
이 7
10.1%
장 6
 
8.7%
전 6
 
8.7%
부 4
 
5.8%
진 4
 
5.8%
구 4
 
5.8%
영 2
 
2.9%
타 2
 
2.9%
Other values (16) 16
23.2%
ASCII
ValueCountFrequency (%)
10
83.3%
) 1
 
8.3%
( 1
 
8.3%

업무구분명
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
저수조청소업
24 
<NA>
20 

Length

Max length6
Median length6
Mean length5.0909091
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
저수조청소업 24
54.5%
<NA> 20
45.5%

Length

2024-05-11T15:48:16.121634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:16.265173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저수조청소업 24
54.5%
na 20
45.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업무구분건축물명건축물연면적건축물상태명청소대상시작일자청소대상종료일자휴업폐지사유업무구분명
030900003090000311998000012009-11-16<NA>1영업/정상11정상<NA><NA><NA><NA>02-992-2403<NA><NA>서울특별시 도봉구 쌍문동 *** (*층)서울특별시 도봉구 도봉로***길 *, *층 (쌍문동)<NA>트래져건설(주)2023-02-28 15:21:42U2022-12-03 00:03:00.0<NA>203378.483576461658.084175<NA><NA><NA><NA><NA><NA><NA><NA>
1309000030900003119980000220100326<NA>3폐업2폐업20100326<NA><NA><NA><NA><NA><NA>서울특별시 도봉구 방학동 683-23<NA><NA>고려종합환경2015-01-05 21:07:09I2018-08-31 23:59:59.0<NA>203583.662399462535.50513331<NA><NA><NA><NA><NA>강북구이전저수조청소업
2309000030900003120020000120130329<NA>3폐업2폐업20130329<NA><NA><NA>02-998-8375<NA><NA>서울특별시 도봉구 도봉동 569-2<NA><NA>익제건설산업(주)2016-08-18 18:07:51I2018-08-31 23:59:59.0<NA>203834.933037464769.94331931<NA><NA><NA><NA><NA>영업부진저수조청소업
3309000030900003120030000320090319<NA>3폐업2폐업20090319<NA><NA><NA>029001486<NA><NA>서울특별시 도봉구 도봉동 641 서원아파트서울특별시 도봉구 마들로 684-19 (도봉동, 서원아파트)1324(주)성광씨앤씨2020-10-07 11:01:09U2020-10-09 02:40:00.0<NA>204172.527807463449.54029831<NA><NA><NA><NA><NA>사업장 타구 이전저수조청소업
4309000030900003120060000120080430<NA>3폐업2폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 도봉구 창동 756-206<NA><NA>대명환경2015-01-05 21:07:09I2018-08-31 23:59:59.0<NA>204488.650733460197.00376731<NA><NA><NA><NA><NA>영업부진저수조청소업
530900003090000312007000012009-08-07<NA>1영업/정상11정상<NA><NA><NA><NA>02-2649-4386<NA><NA>서울특별시 도봉구 방학동 ***-**서울특별시 도봉구 시루봉로 ***-* (도봉동)<NA>(주)다수환경개발2023-02-28 15:22:39U2022-12-03 00:03:00.0<NA>203092.044285462940.306044<NA><NA><NA><NA><NA><NA><NA><NA>
6309000030900003120070000320090413<NA>3폐업2폐업20090413<NA><NA><NA>955-1687<NA><NA>서울특별시 도봉구 도봉동 623-32<NA><NA>(주)대송스카이파워2015-01-05 21:07:09I2018-08-31 23:59:59.0<NA>203860.575625463298.2049731<NA><NA><NA><NA><NA>타구이전저수조청소업
730900003090000312008000012022-04-15<NA>1영업/정상11정상<NA><NA><NA><NA>02-990-5119<NA><NA>서울특별시 도봉구 쌍문동 *** ***호서울특별시 도봉구 해등로**길 **, ***호 (쌍문동)1432월드환경2023-02-28 15:24:40U2022-12-03 00:03:00.0<NA>203306.556907461561.615484<NA><NA><NA><NA><NA><NA><NA><NA>
8309000030900003120080000220080717<NA>1영업/정상11정상<NA><NA><NA><NA>02-930-2911<NA><NA>서울특별시 도봉구 창동 10-3 세정빌딩서울특별시 도봉구 노해로69길 15, 세정빌딩 702-2호 (창동)1414대한환경공사2020-10-07 11:09:00U2020-10-09 02:40:00.0<NA>204397.004136461175.40204231<NA><NA><NA><NA><NA><NA>저수조청소업
9309000030900003120080000320080714<NA>4취소/말소/만료/정지/중지4폐쇄20200828<NA><NA><NA>02-930-2911<NA><NA>서울특별시 도봉구 창동 10-3 세정빌딩 7층2-2호<NA><NA>대한환경공사2020-10-07 11:10:01U2020-10-09 02:40:00.0<NA>204397.004136461175.40204231<NA><NA><NA><NA><NA>새올에 이중입력저수조청소업
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업무구분건축물명건축물연면적건축물상태명청소대상시작일자청소대상종료일자휴업폐지사유업무구분명
3430900003090000312018000012018-08-08<NA>1영업/정상11정상<NA><NA><NA><NA>02-929-2580<NA><NA>서울특별시 도봉구 도봉동 ***-**서울특별시 도봉구 도봉로***길 **, ***호 (도봉동)1328(주)코너스톤티엠에스2023-10-25 09:35:18U2022-10-30 22:07:00.0<NA>203948.554992463353.420878<NA><NA><NA><NA><NA><NA><NA><NA>
35309000030900003120180000220201209<NA>1영업/정상11정상<NA><NA><NA><NA>02-994-7584<NA><NA>서울특별시 도봉구 창동 624-1 북한산현대홈시티서울특별시 도봉구 도봉로106길 23, 102동 507호 (창동, 북한산현대홈시티)1459에스에이치종합건설(주)2021-03-25 15:33:08U2021-03-27 02:40:00.0<NA>202940.779948460294.47833331<NA><NA><NA><NA><NA><NA>저수조청소업
36309000030900003120190000120190306<NA>1영업/정상11정상<NA><NA><NA><NA>02-3494-2740<NA><NA>서울특별시 도봉구 도봉동 595 럭키아파트 상가 106동 204호서울특별시 도봉구 도봉로 851, 럭키아파트 상가 106동 2층 204호 (도봉동)1306(주)태은환경2020-10-07 11:27:04U2020-10-09 02:40:00.0<NA>203848.772423464092.18750531<NA><NA><NA><NA><NA><NA>저수조청소업
3730900003090000312021000012021-03-31<NA>1영업/정상11정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 도봉구 도봉동 **-***서울특별시 도봉구 도봉로***길 ** (도봉동)1321명인종합설비2023-02-28 15:41:56U2022-12-03 00:03:00.0<NA>204086.827228464186.380359<NA><NA><NA><NA><NA><NA><NA><NA>
3830900003090000312021000022021-04-29<NA>1영업/정상11정상<NA><NA><NA><NA>02-981-3730<NA><NA>서울특별시 도봉구 창동 ***-** 북한산현대홈시티 ***동 ****호서울특별시 도봉구 도봉로***길 **-**, ***동 **층 ****호 (창동, 북한산현대홈시티)1460기경건설2023-10-23 14:10:25U2022-10-30 22:05:00.0<NA>202960.838284460183.287772<NA><NA><NA><NA><NA><NA><NA><NA>
3930900003090000312021000032021-03-01<NA>1영업/정상11정상<NA><NA><NA><NA>02-973-0942<NA><NA>서울특별시 도봉구 도봉동 ***-**서울특별시 도봉구 도봉로 ***, *층 (도봉동)1308신일공영설비2023-02-21 18:12:14U2022-12-01 22:03:00.0<NA>203831.16766463621.090035<NA><NA><NA><NA><NA><NA><NA><NA>
4030900003090000312022000012023-02-28<NA>1영업/정상11정상<NA><NA><NA><NA>029993766<NA><NA>서울특별시 도봉구 창동 ***-**서울특별시 도봉구 덕릉로**길 ***-*, *층 (창동)1480광호이엔씨 주식회사2023-02-28 13:05:16U2022-12-03 00:03:00.0<NA>203727.005123459130.893657<NA><NA><NA><NA><NA><NA><NA><NA>
4130900003090000312022000022023-01-31<NA>4취소/말소/만료/정지/중지4폐쇄2023-01-31<NA><NA><NA>02-538-3080<NA><NA>서울특별시 도봉구 창동 ***-**서울특별시 도봉구 도봉로 ***-* (창동)1453엠에스씨엔이(주)2023-02-02 09:50:59U2022-12-02 00:04:00.0<NA>203122.115131460847.228621<NA><NA><NA><NA><NA><NA><NA><NA>
4230900003090000312022000032024-01-19<NA>1영업/정상11정상<NA><NA><NA><NA>029835472<NA><NA>서울특별시 도봉구 방학동 ***-**서울특별시 도봉구 방학로*길 ** (방학동)1389(주)이산아이엔씨2024-01-22 09:02:21U2023-11-30 22:04:00.0<NA>203229.484816462215.331326<NA><NA><NA><NA><NA><NA><NA><NA>
4330900003090000312022000042022-07-25<NA>1영업/정상11정상<NA><NA><NA><NA>02-3296-0407<NA><NA>서울특별시 도봉구 도봉동 ***-**서울특별시 도봉구 도봉산*길 **, *층 (도봉동)1304뿌리엔지니어링(주)2023-10-25 09:43:22U2022-10-30 22:07:00.0<NA>203755.994707464568.775185<NA><NA><NA><NA><NA><NA><NA><NA>