Overview

Dataset statistics

Number of variables29
Number of observations104
Missing cells1135
Missing cells (%)37.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.1 KiB
Average record size in memory247.3 B

Variable types

Categorical8
Text7
DateTime4
Unsupported6
Numeric4

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),비상시설위치,시설구분명,시설명_건물명,해제일자
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-20036/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신구분 has constant value ""Constant
비상시설위치 has constant value ""Constant
시설구분명 has constant value ""Constant
시설명_건물명 has constant value ""Constant
영업상태코드 is highly imbalanced (81.1%)Imbalance
영업상태명 is highly imbalanced (81.1%)Imbalance
상세영업상태코드 is highly imbalanced (81.1%)Imbalance
상세영업상태명 is highly imbalanced (81.1%)Imbalance
데이터갱신일자 is highly imbalanced (84.9%)Imbalance
해제일자 is highly imbalanced (92.2%)Imbalance
인허가취소일자 has 101 (97.1%) missing valuesMissing
폐업일자 has 101 (97.1%) missing valuesMissing
휴업시작일자 has 104 (100.0%) missing valuesMissing
휴업종료일자 has 104 (100.0%) missing valuesMissing
재개업일자 has 104 (100.0%) missing valuesMissing
전화번호 has 104 (100.0%) missing valuesMissing
소재지우편번호 has 104 (100.0%) missing valuesMissing
업태구분명 has 104 (100.0%) missing valuesMissing
비상시설위치 has 103 (99.0%) missing valuesMissing
시설구분명 has 103 (99.0%) missing valuesMissing
시설명_건물명 has 103 (99.0%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
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
전화번호 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

Reproduction

Analysis started2024-05-11 05:46:11.783393
Analysis finished2024-05-11 05:46:12.940827
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
3090000
104 

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 104
100.0%

Length

2024-05-11T05:46:13.451163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:13.861926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 104
100.0%

관리번호
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-05-11T05:46:14.361623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1872
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)100.0%

Sample

1st row3090000-S202200001
2nd row3090000-S202300002
3rd row3090000-S202300003
4th row3090000-S202300001
5th row3090000-S202100001
ValueCountFrequency (%)
3090000-s202200001 1
 
1.0%
3090000-s202300002 1
 
1.0%
3090000-s199600012 1
 
1.0%
3090000-s199600010 1
 
1.0%
3090000-s199600006 1
 
1.0%
3090000-s199600025 1
 
1.0%
3090000-s199600009 1
 
1.0%
3090000-s199700003 1
 
1.0%
3090000-s199700001 1
 
1.0%
3090000-s199600007 1
 
1.0%
Other values (94) 94
90.4%
2024-05-11T05:46:15.343794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1037
55.4%
9 191
 
10.2%
3 130
 
6.9%
2 117
 
6.2%
- 104
 
5.6%
S 104
 
5.6%
1 103
 
5.5%
5 25
 
1.3%
6 21
 
1.1%
4 18
 
1.0%
Other values (2) 22
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1664
88.9%
Dash Punctuation 104
 
5.6%
Uppercase Letter 104
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1037
62.3%
9 191
 
11.5%
3 130
 
7.8%
2 117
 
7.0%
1 103
 
6.2%
5 25
 
1.5%
6 21
 
1.3%
4 18
 
1.1%
7 11
 
0.7%
8 11
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1768
94.4%
Latin 104
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1037
58.7%
9 191
 
10.8%
3 130
 
7.4%
2 117
 
6.6%
- 104
 
5.9%
1 103
 
5.8%
5 25
 
1.4%
6 21
 
1.2%
4 18
 
1.0%
7 11
 
0.6%
Latin
ValueCountFrequency (%)
S 104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1037
55.4%
9 191
 
10.2%
3 130
 
6.9%
2 117
 
6.2%
- 104
 
5.6%
S 104
 
5.6%
1 103
 
5.5%
5 25
 
1.3%
6 21
 
1.1%
4 18
 
1.0%
Other values (2) 22
 
1.2%

인허가일자
Date

Distinct76
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum1986-12-31 00:00:00
Maximum2023-08-31 00:00:00
2024-05-11T05:46:15.886364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:46:16.510925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing101
Missing (%)97.1%
Memory size964.0 B
Minimum2023-06-13 00:00:00
Maximum2023-12-13 00:00:00
2024-05-11T05:46:16.988659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:46:17.493879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
1
101 
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 101
97.1%
4 3
 
2.9%

Length

2024-05-11T05:46:18.103209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:18.643282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 101
97.1%
4 3
 
2.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
영업/정상
101 
취소/말소/만료/정지/중지
 
3

Length

Max length14
Median length5
Mean length5.2596154
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 101
97.1%
취소/말소/만료/정지/중지 3
 
2.9%

Length

2024-05-11T05:46:19.108918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:19.581192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 101
97.1%
취소/말소/만료/정지/중지 3
 
2.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
18
101 
19
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19
2nd row18
3rd row18
4th row18
5th row18

Common Values

ValueCountFrequency (%)
18 101
97.1%
19 3
 
2.9%

Length

2024-05-11T05:46:20.148352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:20.612844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 101
97.1%
19 3
 
2.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
사용중
101 
사용중지
 
3

Length

Max length4
Median length3
Mean length3.0288462
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사용중지
2nd row사용중
3rd row사용중
4th row사용중
5th row사용중

Common Values

ValueCountFrequency (%)
사용중 101
97.1%
사용중지 3
 
2.9%

Length

2024-05-11T05:46:21.106666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:21.415608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 101
97.1%
사용중지 3
 
2.9%

폐업일자
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing101
Missing (%)97.1%
Memory size964.0 B
Minimum2023-06-13 00:00:00
Maximum2023-12-13 00:00:00
2024-05-11T05:46:21.783022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:46:22.446420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

소재지면적
Real number (ℝ)

Distinct102
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9272.0551
Minimum330.58
Maximum106030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T05:46:23.102793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330.58
5-th percentile914.438
Q12522.75
median5042.5
Q38605.75
95-th percentile33431.45
Maximum106030
Range105699.42
Interquartile range (IQR)6083

Descriptive statistics

Standard deviation15147.549
Coefficient of variation (CV)1.6336777
Kurtosis20.259883
Mean9272.0551
Median Absolute Deviation (MAD)2702.5
Skewness4.1346416
Sum964293.73
Variance2.2944825 × 108
MonotonicityNot monotonic
2024-05-11T05:46:23.795956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992.0 3
 
2.9%
362.36 1
 
1.0%
914.0 1
 
1.0%
21117.0 1
 
1.0%
6525.0 1
 
1.0%
62191.0 1
 
1.0%
7110.0 1
 
1.0%
6485.98 1
 
1.0%
4363.0 1
 
1.0%
3696.0 1
 
1.0%
Other values (92) 92
88.5%
ValueCountFrequency (%)
330.58 1
 
1.0%
340.0 1
 
1.0%
362.36 1
 
1.0%
448.0 1
 
1.0%
697.5 1
 
1.0%
914.0 1
 
1.0%
916.92 1
 
1.0%
965.0 1
 
1.0%
975.0 1
 
1.0%
992.0 3
2.9%
ValueCountFrequency (%)
106030.0 1
1.0%
76570.0 1
1.0%
62191.0 1
1.0%
46712.04 1
1.0%
36614.0 1
1.0%
34088.0 1
1.0%
29711.0 1
1.0%
27607.0 1
1.0%
25810.0 1
1.0%
21117.0 1
1.0%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

지번주소
Text

Distinct101
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-05-11T05:46:24.420126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length21.548077
Min length16

Characters and Unicode

Total characters2241
Distinct characters94
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)95.2%

Sample

1st row서울특별시 도봉구 창동 347-5 창1동 주민센터
2nd row서울특별시 도봉구 창동 819 태영창동데시앙
3rd row서울특별시 도봉구 창동 1-28 씨드큐브 창동
4th row서울특별시 도봉구 쌍문동 507-1 에드가쌍문
5th row서울특별시 도봉구 창동 504-21
ValueCountFrequency (%)
서울특별시 104
22.1%
도봉구 104
22.1%
방학동 34
 
7.2%
창동 30
 
6.4%
쌍문동 23
 
4.9%
도봉동 16
 
3.4%
1호 11
 
2.3%
신동아1단지아파트 5
 
1.1%
272 3
 
0.6%
720번지 3
 
0.6%
Other values (128) 137
29.1%
2024-05-11T05:46:25.652198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
368
16.4%
도 128
 
5.7%
봉 124
 
5.5%
동 114
 
5.1%
시 106
 
4.7%
서 104
 
4.6%
구 104
 
4.6%
울 104
 
4.6%
별 104
 
4.6%
특 104
 
4.6%
Other values (84) 881
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1496
66.8%
Space Separator 368
 
16.4%
Decimal Number 363
 
16.2%
Dash Punctuation 10
 
0.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 128
 
8.6%
봉 124
 
8.3%
동 114
 
7.6%
시 106
 
7.1%
서 104
 
7.0%
구 104
 
7.0%
울 104
 
7.0%
별 104
 
7.0%
특 104
 
7.0%
지 95
 
6.4%
Other values (70) 409
27.3%
Decimal Number
ValueCountFrequency (%)
1 70
19.3%
7 52
14.3%
2 50
13.8%
5 40
11.0%
8 31
8.5%
3 31
8.5%
6 30
8.3%
0 23
 
6.3%
4 21
 
5.8%
9 15
 
4.1%
Space Separator
ValueCountFrequency (%)
368
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1496
66.8%
Common 745
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 128
 
8.6%
봉 124
 
8.3%
동 114
 
7.6%
시 106
 
7.1%
서 104
 
7.0%
구 104
 
7.0%
울 104
 
7.0%
별 104
 
7.0%
특 104
 
7.0%
지 95
 
6.4%
Other values (70) 409
27.3%
Common
ValueCountFrequency (%)
368
49.4%
1 70
 
9.4%
7 52
 
7.0%
2 50
 
6.7%
5 40
 
5.4%
8 31
 
4.2%
3 31
 
4.2%
6 30
 
4.0%
0 23
 
3.1%
4 21
 
2.8%
Other values (4) 29
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1496
66.8%
ASCII 745
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
368
49.4%
1 70
 
9.4%
7 52
 
7.0%
2 50
 
6.7%
5 40
 
5.4%
8 31
 
4.2%
3 31
 
4.2%
6 30
 
4.0%
0 23
 
3.1%
4 21
 
2.8%
Other values (4) 29
 
3.9%
Hangul
ValueCountFrequency (%)
도 128
 
8.6%
봉 124
 
8.3%
동 114
 
7.6%
시 106
 
7.1%
서 104
 
7.0%
구 104
 
7.0%
울 104
 
7.0%
별 104
 
7.0%
특 104
 
7.0%
지 95
 
6.4%
Other values (70) 409
27.3%

도로명주소
Text

Distinct103
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-05-11T05:46:26.413527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length32.961538
Min length19

Characters and Unicode

Total characters3428
Distinct characters175
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

Unique102 ?
Unique (%)98.1%

Sample

1st row서울특별시 도봉구 해등로 46, 창1동 주민센터 (창동)
2nd row서울특별시 도봉구 도봉로110다길 51 (창동, 태영창동데시앙)
3rd row서울특별시 도봉구 마들로13길 61, 씨드큐브 창동 (창동)
4th row서울특별시 도봉구 삼양로 602 (쌍문동, 에드가쌍문)
5th row서울특별시 도봉구 우이천로4길 24-11, 창제3동 제1공영주차장 (창동)
ValueCountFrequency (%)
서울특별시 104
 
16.8%
도봉구 104
 
16.8%
방학동 34
 
5.5%
창동 31
 
5.0%
쌍문동 23
 
3.7%
도봉동 16
 
2.6%
마들로 12
 
1.9%
방학로 6
 
1.0%
시루봉로 6
 
1.0%
해등로 5
 
0.8%
Other values (228) 279
45.0%
2024-05-11T05:46:27.684955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
516
 
15.1%
봉 166
 
4.8%
도 164
 
4.8%
동 137
 
4.0%
시 119
 
3.5%
서 106
 
3.1%
울 106
 
3.1%
구 105
 
3.1%
별 104
 
3.0%
1 104
 
3.0%
Other values (165) 1801
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2163
63.1%
Space Separator 516
 
15.1%
Decimal Number 430
 
12.5%
Close Punctuation 104
 
3.0%
Open Punctuation 104
 
3.0%
Other Punctuation 91
 
2.7%
Dash Punctuation 17
 
0.5%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 166
 
7.7%
도 164
 
7.6%
동 137
 
6.3%
시 119
 
5.5%
서 106
 
4.9%
울 106
 
4.9%
구 105
 
4.9%
별 104
 
4.8%
특 104
 
4.8%
로 102
 
4.7%
Other values (147) 950
43.9%
Decimal Number
ValueCountFrequency (%)
1 104
24.2%
6 54
12.6%
3 52
12.1%
0 43
10.0%
2 43
10.0%
5 37
 
8.6%
4 34
 
7.9%
7 26
 
6.0%
8 22
 
5.1%
9 15
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
516
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Other Punctuation
ValueCountFrequency (%)
, 91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2163
63.1%
Common 1262
36.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 166
 
7.7%
도 164
 
7.6%
동 137
 
6.3%
시 119
 
5.5%
서 106
 
4.9%
울 106
 
4.9%
구 105
 
4.9%
별 104
 
4.8%
특 104
 
4.8%
로 102
 
4.7%
Other values (147) 950
43.9%
Common
ValueCountFrequency (%)
516
40.9%
1 104
 
8.2%
) 104
 
8.2%
( 104
 
8.2%
, 91
 
7.2%
6 54
 
4.3%
3 52
 
4.1%
0 43
 
3.4%
2 43
 
3.4%
5 37
 
2.9%
Other values (5) 114
 
9.0%
Latin
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
e 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2163
63.1%
ASCII 1265
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
516
40.8%
1 104
 
8.2%
) 104
 
8.2%
( 104
 
8.2%
, 91
 
7.2%
6 54
 
4.3%
3 52
 
4.1%
0 43
 
3.4%
2 43
 
3.4%
5 37
 
2.9%
Other values (8) 117
 
9.2%
Hangul
ValueCountFrequency (%)
봉 166
 
7.7%
도 164
 
7.6%
동 137
 
6.3%
시 119
 
5.5%
서 106
 
4.9%
울 106
 
4.9%
구 105
 
4.9%
별 104
 
4.8%
특 104
 
4.8%
로 102
 
4.7%
Other values (147) 950
43.9%

도로명우편번호
Real number (ℝ)

Distinct76
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1384.5481
Minimum1301
Maximum1488
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T05:46:28.301036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1301
5-th percentile1316.3
Q11336.75
median1382.5
Q31415.25
95-th percentile1471.55
Maximum1488
Range187
Interquartile range (IQR)78.5

Descriptive statistics

Standard deviation50.175784
Coefficient of variation (CV)0.036239828
Kurtosis-0.84065636
Mean1384.5481
Median Absolute Deviation (MAD)39
Skewness0.23825682
Sum143993
Variance2517.6093
MonotonicityNot monotonic
2024-05-11T05:46:28.857532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1318 4
 
3.8%
1359 4
 
3.8%
1382 3
 
2.9%
1320 3
 
2.9%
1322 3
 
2.9%
1335 3
 
2.9%
1409 3
 
2.9%
1332 3
 
2.9%
1394 2
 
1.9%
1361 2
 
1.9%
Other values (66) 74
71.2%
ValueCountFrequency (%)
1301 1
 
1.0%
1302 1
 
1.0%
1303 1
 
1.0%
1306 1
 
1.0%
1314 1
 
1.0%
1316 1
 
1.0%
1318 4
3.8%
1320 3
2.9%
1321 1
 
1.0%
1322 3
2.9%
ValueCountFrequency (%)
1488 1
1.0%
1487 1
1.0%
1482 1
1.0%
1481 2
1.9%
1472 1
1.0%
1469 1
1.0%
1465 1
1.0%
1462 1
1.0%
1461 1
1.0%
1459 1
1.0%

사업장명
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-05-11T05:46:29.492216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length19.605769
Min length8

Characters and Unicode

Total characters2039
Distinct characters162
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

Unique104 ?
Unique (%)100.0%

Sample

1st row창1동 주민센터 지하주차장 1층
2nd row창동 데시앙 아파트 지하주차장 1~2층
3rd row씨드큐브 창동 지하주차장 1층~7층
4th row에드가 쌍문 아파트 지하주차장 1~2층
5th row창제3동 제1공영주차장 지하1층
ValueCountFrequency (%)
지하주차장 91
25.2%
1층 48
 
13.3%
1층~2층 36
 
10.0%
아파트 20
 
5.5%
1층~3층 7
 
1.9%
지하 7
 
1.9%
지하1층 6
 
1.7%
신동아 5
 
1.4%
방학동 5
 
1.4%
1~2층 4
 
1.1%
Other values (122) 132
36.6%
2024-05-11T05:46:30.547570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
257
 
12.6%
층 149
 
7.3%
지 124
 
6.1%
1 120
 
5.9%
하 110
 
5.4%
차 110
 
5.4%
주 98
 
4.8%
장 98
 
4.8%
아 94
 
4.6%
파 85
 
4.2%
Other values (152) 794
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1464
71.8%
Space Separator 257
 
12.6%
Decimal Number 216
 
10.6%
Math Symbol 49
 
2.4%
Open Punctuation 21
 
1.0%
Close Punctuation 21
 
1.0%
Uppercase Letter 10
 
0.5%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 149
 
10.2%
지 124
 
8.5%
하 110
 
7.5%
차 110
 
7.5%
주 98
 
6.7%
장 98
 
6.7%
아 94
 
6.4%
파 85
 
5.8%
트 84
 
5.7%
동 60
 
4.1%
Other values (135) 452
30.9%
Decimal Number
ValueCountFrequency (%)
1 120
55.6%
2 57
26.4%
3 19
 
8.8%
4 8
 
3.7%
5 4
 
1.9%
0 3
 
1.4%
7 3
 
1.4%
6 1
 
0.5%
8 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S 4
40.0%
E 3
30.0%
A 3
30.0%
Space Separator
ValueCountFrequency (%)
257
100.0%
Math Symbol
ValueCountFrequency (%)
~ 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1464
71.8%
Common 564
 
27.7%
Latin 11
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 149
 
10.2%
지 124
 
8.5%
하 110
 
7.5%
차 110
 
7.5%
주 98
 
6.7%
장 98
 
6.7%
아 94
 
6.4%
파 85
 
5.8%
트 84
 
5.7%
동 60
 
4.1%
Other values (135) 452
30.9%
Common
ValueCountFrequency (%)
257
45.6%
1 120
21.3%
2 57
 
10.1%
~ 49
 
8.7%
( 21
 
3.7%
) 21
 
3.7%
3 19
 
3.4%
4 8
 
1.4%
5 4
 
0.7%
0 3
 
0.5%
Other values (3) 5
 
0.9%
Latin
ValueCountFrequency (%)
S 4
36.4%
E 3
27.3%
A 3
27.3%
e 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1464
71.8%
ASCII 575
 
28.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
257
44.7%
1 120
20.9%
2 57
 
9.9%
~ 49
 
8.5%
( 21
 
3.7%
) 21
 
3.7%
3 19
 
3.3%
4 8
 
1.4%
S 4
 
0.7%
5 4
 
0.7%
Other values (7) 15
 
2.6%
Hangul
ValueCountFrequency (%)
층 149
 
10.2%
지 124
 
8.5%
하 110
 
7.5%
차 110
 
7.5%
주 98
 
6.7%
장 98
 
6.7%
아 94
 
6.4%
파 85
 
5.8%
트 84
 
5.7%
동 60
 
4.1%
Other values (135) 452
30.9%

최종수정일자
Date

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum2023-06-13 16:57:53
Maximum2024-02-01 17:54:38
2024-05-11T05:46:30.978310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:46:31.505636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
U
104 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 104
100.0%

Length

2024-05-11T05:46:32.114879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:32.536147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 104
100.0%

데이터갱신일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-11-30 22:06:00.0
99 
2023-06-15 02:40:00.0
 
1
2022-10-30 23:08:00.0
 
1
2022-10-30 23:09:00.0
 
1
2022-11-01 23:05:00.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique5 ?
Unique (%)4.8%

Sample

1st row2023-06-15 02:40:00.0
2nd row2023-11-30 22:06:00.0
3rd row2023-11-30 22:06:00.0
4th row2023-11-30 22:06:00.0
5th row2023-11-30 22:06:00.0

Common Values

ValueCountFrequency (%)
2023-11-30 22:06:00.0 99
95.2%
2023-06-15 02:40:00.0 1
 
1.0%
2022-10-30 23:08:00.0 1
 
1.0%
2022-10-30 23:09:00.0 1
 
1.0%
2022-11-01 23:05:00.0 1
 
1.0%
2023-12-02 00:03:00.0 1
 
1.0%

Length

2024-05-11T05:46:33.019836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:33.405801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 99
47.6%
22:06:00.0 99
47.6%
2022-10-30 2
 
1.0%
2023-06-15 1
 
0.5%
02:40:00.0 1
 
0.5%
23:08:00.0 1
 
0.5%
23:09:00.0 1
 
0.5%
2022-11-01 1
 
0.5%
23:05:00.0 1
 
0.5%
2023-12-02 1
 
0.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

좌표정보(X)
Real number (ℝ)

Distinct101
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203271.87
Minimum201130.17
Maximum204506.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T05:46:34.163062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201130.17
5-th percentile202010.26
Q1202546.19
median203418.07
Q3203996.91
95-th percentile204300.19
Maximum204506.92
Range3376.7535
Interquartile range (IQR)1450.7167

Descriptive statistics

Standard deviation805.16089
Coefficient of variation (CV)0.003961005
Kurtosis-0.77206981
Mean203271.87
Median Absolute Deviation (MAD)660.07766
Skewness-0.432105
Sum21140274
Variance648284.06
MonotonicityNot monotonic
2024-05-11T05:46:34.989060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202552.06293165 3
 
2.9%
202283.960974223 2
 
1.9%
203797.644696207 1
 
1.0%
202466.119176743 1
 
1.0%
204169.847670316 1
 
1.0%
204031.968329866 1
 
1.0%
203026.922988592 1
 
1.0%
202474.809554554 1
 
1.0%
202251.82567775 1
 
1.0%
204169.765708943 1
 
1.0%
Other values (91) 91
87.5%
ValueCountFrequency (%)
201130.167615522 1
1.0%
201154.262049252 1
1.0%
201806.68786033 1
1.0%
201849.092906033 1
1.0%
201977.577531987 1
1.0%
202005.697295149 1
1.0%
202036.087461095 1
1.0%
202159.200013942 1
1.0%
202223.981996739 1
1.0%
202251.82567775 1
1.0%
ValueCountFrequency (%)
204506.921108086 1
1.0%
204439.232870479 1
1.0%
204426.390184764 1
1.0%
204404.601245349 1
1.0%
204322.735946107 1
1.0%
204313.906829097 1
1.0%
204222.46195029 1
1.0%
204214.210632572 1
1.0%
204192.915094501 1
1.0%
204178.603486457 1
1.0%

좌표정보(Y)
Real number (ℝ)

Distinct101
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean461973.32
Minimum458954.55
Maximum465158.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T05:46:35.738614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum458954.55
5-th percentile459902
Q1461111.14
median461973.23
Q3462486.58
95-th percentile464702.59
Maximum465158.8
Range6204.2505
Interquartile range (IQR)1375.4424

Descriptive statistics

Standard deviation1367.4685
Coefficient of variation (CV)0.0029600594
Kurtosis0.1906378
Mean461973.32
Median Absolute Deviation (MAD)703.86355
Skewness0.33639239
Sum48045226
Variance1869970
MonotonicityNot monotonic
2024-05-11T05:46:36.203654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462071.049647988 3
 
2.9%
462055.400993005 2
 
1.9%
460667.157423177 1
 
1.0%
460394.329853007 1
 
1.0%
464814.717432497 1
 
1.0%
461333.59735433 1
 
1.0%
460743.186962052 1
 
1.0%
462204.722701223 1
 
1.0%
460685.528657519 1
 
1.0%
461930.191335537 1
 
1.0%
Other values (91) 91
87.5%
ValueCountFrequency (%)
458954.54912126 1
1.0%
458970.742207528 1
1.0%
459009.265716602 1
1.0%
459499.0514426 1
1.0%
459820.359926529 1
1.0%
459897.751470537 1
1.0%
459926.076574936 1
1.0%
460001.081136921 1
1.0%
460062.635181775 1
1.0%
460363.949873774 1
1.0%
ValueCountFrequency (%)
465158.799624502 1
1.0%
465025.246646886 1
1.0%
464905.033086911 1
1.0%
464814.717432497 1
1.0%
464804.016663922 1
1.0%
464709.524245203 1
1.0%
464663.321565455 1
1.0%
464472.810888981 1
1.0%
464460.396523556 1
1.0%
464346.259785555 1
1.0%

비상시설위치
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing103
Missing (%)99.0%
Memory size964.0 B
2024-05-11T05:46:36.621752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters27
Distinct characters21
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

Unique1 ?
Unique (%)100.0%

Sample

1st row서울특별시 도봉구 창동 347-5 창1동 주민센터
ValueCountFrequency (%)
서울특별시 1
16.7%
도봉구 1
16.7%
창동 1
16.7%
347-5 1
16.7%
창1동 1
16.7%
주민센터 1
16.7%
2024-05-11T05:46:37.503566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
18.5%
동 2
 
7.4%
창 2
 
7.4%
4 1
 
3.7%
센 1
 
3.7%
민 1
 
3.7%
주 1
 
3.7%
1 1
 
3.7%
5 1
 
3.7%
- 1
 
3.7%
Other values (11) 11
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
59.3%
Space Separator 5
 
18.5%
Decimal Number 5
 
18.5%
Dash Punctuation 1
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2
12.5%
창 2
12.5%
센 1
 
6.2%
민 1
 
6.2%
주 1
 
6.2%
서 1
 
6.2%
울 1
 
6.2%
구 1
 
6.2%
봉 1
 
6.2%
도 1
 
6.2%
Other values (4) 4
25.0%
Decimal Number
ValueCountFrequency (%)
4 1
20.0%
1 1
20.0%
5 1
20.0%
7 1
20.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
59.3%
Common 11
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2
12.5%
창 2
12.5%
센 1
 
6.2%
민 1
 
6.2%
주 1
 
6.2%
서 1
 
6.2%
울 1
 
6.2%
구 1
 
6.2%
봉 1
 
6.2%
도 1
 
6.2%
Other values (4) 4
25.0%
Common
ValueCountFrequency (%)
5
45.5%
4 1
 
9.1%
1 1
 
9.1%
5 1
 
9.1%
- 1
 
9.1%
7 1
 
9.1%
3 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
59.3%
ASCII 11
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
45.5%
4 1
 
9.1%
1 1
 
9.1%
5 1
 
9.1%
- 1
 
9.1%
7 1
 
9.1%
3 1
 
9.1%
Hangul
ValueCountFrequency (%)
동 2
12.5%
창 2
12.5%
센 1
 
6.2%
민 1
 
6.2%
주 1
 
6.2%
서 1
 
6.2%
울 1
 
6.2%
구 1
 
6.2%
봉 1
 
6.2%
도 1
 
6.2%
Other values (4) 4
25.0%

시설구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing103
Missing (%)99.0%
Memory size964.0 B
2024-05-11T05:46:37.865885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row공공용시설
ValueCountFrequency (%)
공공용시설 1
100.0%
2024-05-11T05:46:38.652284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 2
40.0%
용 1
20.0%
시 1
20.0%
설 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 2
40.0%
용 1
20.0%
시 1
20.0%
설 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 2
40.0%
용 1
20.0%
시 1
20.0%
설 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 2
40.0%
용 1
20.0%
시 1
20.0%
설 1
20.0%

시설명_건물명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing103
Missing (%)99.0%
Memory size964.0 B
2024-05-11T05:46:39.027782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row창1동 주민센터 지하주차장 1층
ValueCountFrequency (%)
창1동 1
25.0%
주민센터 1
25.0%
지하주차장 1
25.0%
1층 1
25.0%
2024-05-11T05:46:39.829849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
17.6%
1 2
11.8%
주 2
11.8%
창 1
 
5.9%
동 1
 
5.9%
민 1
 
5.9%
센 1
 
5.9%
터 1
 
5.9%
지 1
 
5.9%
하 1
 
5.9%
Other values (3) 3
17.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
70.6%
Space Separator 3
 
17.6%
Decimal Number 2
 
11.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2
16.7%
창 1
8.3%
동 1
8.3%
민 1
8.3%
센 1
8.3%
터 1
8.3%
지 1
8.3%
하 1
8.3%
차 1
8.3%
장 1
8.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
70.6%
Common 5
29.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2
16.7%
창 1
8.3%
동 1
8.3%
민 1
8.3%
센 1
8.3%
터 1
8.3%
지 1
8.3%
하 1
8.3%
차 1
8.3%
장 1
8.3%
Common
ValueCountFrequency (%)
3
60.0%
1 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
70.6%
ASCII 5
29.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
60.0%
1 2
40.0%
Hangul
ValueCountFrequency (%)
주 2
16.7%
창 1
8.3%
동 1
8.3%
민 1
8.3%
센 1
8.3%
터 1
8.3%
지 1
8.3%
하 1
8.3%
차 1
8.3%
장 1
8.3%

해제일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
<NA>
103 
20230613
 
1

Length

Max length8
Median length4
Mean length4.0384615
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row20230613
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 103
99.0%
20230613 1
 
1.0%

Length

2024-05-11T05:46:40.302330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:46:40.662497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 103
99.0%
20230613 1
 
1.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
030900003090000-S2022000012022-06-142023-06-134취소/말소/만료/정지/중지19사용중지2023-06-13<NA><NA><NA><NA>362.36<NA>서울특별시 도봉구 창동 347-5 창1동 주민센터서울특별시 도봉구 해등로 46, 창1동 주민센터 (창동)1421창1동 주민센터 지하주차장 1층2023-06-13 16:57:53U2023-06-15 02:40:00.0<NA>203797.644696460667.157423서울특별시 도봉구 창동 347-5 창1동 주민센터공공용시설창1동 주민센터 지하주차장 1층20230613
130900003090000-S2023000022023-06-22<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>34088.0<NA>서울특별시 도봉구 창동 819 태영창동데시앙서울특별시 도봉구 도봉로110다길 51 (창동, 태영창동데시앙)1461창동 데시앙 아파트 지하주차장 1~2층2024-01-24 10:01:44U2023-11-30 22:06:00.0<NA>202877.428165460062.635182<NA><NA><NA><NA>
230900003090000-S2023000032023-08-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>46712.04<NA>서울특별시 도봉구 창동 1-28 씨드큐브 창동서울특별시 도봉구 마들로13길 61, 씨드큐브 창동 (창동)1413씨드큐브 창동 지하주차장 1층~7층2024-01-24 10:01:04U2023-11-30 22:06:00.0<NA>204313.906829461347.878668<NA><NA><NA><NA>
330900003090000-S2023000012023-06-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4283.0<NA>서울특별시 도봉구 쌍문동 507-1 에드가쌍문서울특별시 도봉구 삼양로 602 (쌍문동, 에드가쌍문)1366에드가 쌍문 아파트 지하주차장 1~2층2024-01-24 10:02:08U2023-11-30 22:06:00.0<NA>201154.262049461576.90605<NA><NA><NA><NA>
430900003090000-S2021000012021-05-17<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2541.45<NA>서울특별시 도봉구 창동 504-21서울특별시 도봉구 우이천로4길 24-11, 창제3동 제1공영주차장 (창동)1482창제3동 제1공영주차장 지하1층2024-01-24 10:02:29U2023-11-30 22:06:00.0<NA>203589.704451458970.742208<NA><NA><NA><NA>
530900003090000-S2020000172020-09-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2499.07<NA>서울특별시 도봉구 도봉동 62-43 도봉투웨니퍼스트2단지서울특별시 도봉구 도봉로180길 28, 도봉투웨니퍼스트2단지 (도봉동)1320도봉투웨니퍼스트2단지 지하주차장 1층2024-01-24 10:02:54U2023-11-30 22:06:00.0<NA>204120.986291464460.396524<NA><NA><NA><NA>
630900003090000-S2020000162020-09-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2677.2<NA>서울특별시 도봉구 도봉동 62-3 도봉투웨니퍼스트1단지서울특별시 도봉구 도봉로180길 20, 도봉투웨니퍼스트1단지 (도봉동)1320도봉투웨니퍼스트1단지 지하주차장 1층2024-01-24 10:03:16U2023-11-30 22:06:00.0<NA>204081.38615464472.810889<NA><NA><NA><NA>
730900003090000-S2005000052005-06-222023-10-164취소/말소/만료/정지/중지19사용중지2023-10-16<NA><NA><NA><NA>2395.0<NA>서울특별시 도봉구 도봉동 555번지서울특별시 도봉구 도봉산길 35 (도봉동)1302서울가든아파트 지하 1층2023-10-16 16:08:20U2022-10-30 23:08:00.0<NA>203602.695971464905.033087<NA><NA><NA><NA>
830900003090000-S2020000152020-08-20<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4611.91<NA>서울특별시 도봉구 도봉동 51-12 중흥에스 클래스서울특별시 도봉구 도봉로180가길 32 (도봉동, 중흥에스 클래스)1318도봉중흥S클래스 지하주차장 1층2024-01-24 10:03:37U2023-11-30 22:06:00.0<NA>204089.583059464709.524245<NA><NA><NA><NA>
930900003090000-S2020000142020-08-13<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3803.46<NA>서울특별시 도봉구 도봉동 642 현대성우아파트서울특별시 도봉구 마들로 735-8 (도봉동, 현대성우아파트)1322성우현대아파트(도봉2동) 지하주차장 1층~2층2024-01-24 10:03:56U2023-11-30 22:06:00.0<NA>204135.386164463763.240795<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
9430900003090000-S1995000101995-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10527.0<NA>서울특별시 도봉구 창동 45번지서울특별시 도봉구 노해로66길 21 (창동, 삼성아파트)1422삼성 레미안아파트(창1동) 지하주차장 1층2024-01-24 09:31:52U2023-11-30 22:06:00.0<NA>204214.210633460746.553676<NA><NA><NA><NA>
9530900003090000-S1994000031994-12-13<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6028.0<NA>서울특별시 도봉구 방학동 701번지 15호서울특별시 도봉구 도당로 116 (방학동, 거성학마을아파트)1339거성학마을아파트 지하주차장 1층~2층2024-01-24 09:27:58U2023-11-30 22:06:00.0<NA>203426.335451462682.390999<NA><NA><NA><NA>
9630900003090000-S1994000021994-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2157.0<NA>서울특별시 도봉구 쌍문동 50번지서울특별시 도봉구 시루봉로6길 53 (쌍문동, 현대2차아파트)1387쌍문4동 현대2차아파트 지하주차장 1층2024-01-24 09:27:38U2023-11-30 22:06:00.0<NA>202624.188568461879.867047<NA><NA><NA><NA>
9730900003090000-S1994000011994-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3710.0<NA>서울특별시 도봉구 쌍문동 158번지서울특별시 도봉구 해등로25길 41 (쌍문동, 한양7차아파트)1433한양7차아파트 지하 주차장 1층2024-01-24 09:26:38U2023-11-30 22:06:00.0<NA>202917.884538461515.316767<NA><NA><NA><NA>
9830900003090000-S1993000021993-05-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2112.41<NA>서울특별시 도봉구 방학동 730번지서울특별시 도봉구 시루봉로11길 25-5 (방학동, 극동아파트)1316방학 극동아파트 지하 주차장 1~2층2024-01-24 09:26:09U2023-11-30 22:06:00.0<NA>202294.549439462455.465294<NA><NA><NA><NA>
9930900003090000-S1990000011990-01-24<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>992.0<NA>서울특별시 도봉구 방학동 271-1 신동아1단지아파트서울특별시 도봉구 시루봉로 107 (방학동, 신동아1단지아파트)1362신동아 30동 아파트 지하주차장 1층2024-01-24 09:25:28U2023-11-30 22:06:00.0<NA>202283.960974462055.400993<NA><NA><NA><NA>
10030900003090000-S1989000011989-07-18<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>965.0<NA>서울특별시 도봉구 방학동 272 신동아1단지아파트서울특별시 도봉구 방학로 193, 17동 (방학동, 신동아1단지아파트)1382신동아 17동 아파트 지하주차장 1층2024-01-24 09:25:10U2023-11-30 22:06:00.0<NA>202552.062932462071.049648<NA><NA><NA><NA>
10130900003090000-S1988000021988-07-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>992.0<NA>서울특별시 도봉구 방학동 271-1 신동아1단지아파트서울특별시 도봉구 시루봉로 107 (방학동, 신동아1단지아파트)1362신동아 28동 아파트 지하주차장 1층2024-01-24 09:24:38U2023-11-30 22:06:00.0<NA>202283.960974462055.400993<NA><NA><NA><NA>
10230900003090000-S1987000021987-07-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>992.0<NA>서울특별시 도봉구 방학동 272 신동아1단지아파트서울특별시 도봉구 방학로 193, 13동 (방학동, 신동아1단지아파트)1382신동아 13동 아파트 지하주차장 1층2024-01-24 09:24:21U2023-11-30 22:06:00.0<NA>202552.062932462071.049648<NA><NA><NA><NA>
10330900003090000-S1986000011986-12-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>975.0<NA>서울특별시 도봉구 방학동 272 신동아1단지아파트서울특별시 도봉구 방학로 193, 2동 (방학동, 신동아1단지아파트)1382신동아 2동 아파트 지하주차장 1층2024-01-24 09:23:36U2023-11-30 22:06:00.0<NA>202552.062932462071.049648<NA><NA><NA><NA>