Overview

Dataset statistics

Number of variables29
Number of observations56
Missing cells564
Missing cells (%)34.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 KiB
Average record size in memory247.4 B

Variable types

Categorical8
Text7
DateTime4
Unsupported7
Numeric3

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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-20032/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (69.9%)Imbalance
영업상태명 is highly imbalanced (69.9%)Imbalance
상세영업상태코드 is highly imbalanced (69.9%)Imbalance
상세영업상태명 is highly imbalanced (69.9%)Imbalance
데이터갱신구분 is highly imbalanced (87.1%)Imbalance
인허가취소일자 has 53 (94.6%) missing valuesMissing
폐업일자 has 53 (94.6%) missing valuesMissing
휴업시작일자 has 56 (100.0%) missing valuesMissing
휴업종료일자 has 56 (100.0%) missing valuesMissing
재개업일자 has 56 (100.0%) missing valuesMissing
전화번호 has 56 (100.0%) missing valuesMissing
소재지우편번호 has 56 (100.0%) missing valuesMissing
업태구분명 has 56 (100.0%) missing valuesMissing
비상시설위치 has 33 (58.9%) missing valuesMissing
시설명_건물명 has 33 (58.9%) missing valuesMissing
해제일자 has 56 (100.0%) 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
해제일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:11:00.188414
Analysis finished2024-05-11 06:11:01.016124
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
3050000
56 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 56
100.0%

Length

2024-05-11T15:11:01.141671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:01.303782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 56
100.0%

관리번호
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-11T15:11:01.557872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1008
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

Unique56 ?
Unique (%)100.0%

Sample

1st row3050000-S202200007
2nd row3050000-S202200002
3rd row3050000-S202200001
4th row3050000-S200600008
5th row3050000-S200400259
ValueCountFrequency (%)
3050000-s202200007 1
 
1.8%
3050000-s202200002 1
 
1.8%
3050000-s200900010 1
 
1.8%
3050000-s201700001 1
 
1.8%
3050000-s201700002 1
 
1.8%
3050000-s201200003 1
 
1.8%
3050000-s201100003 1
 
1.8%
3050000-s201100010 1
 
1.8%
3050000-s202400001 1
 
1.8%
3050000-s201000002 1
 
1.8%
Other values (46) 46
82.1%
2024-05-11T15:11:02.057850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 564
56.0%
2 84
 
8.3%
3 73
 
7.2%
5 60
 
6.0%
- 56
 
5.6%
S 56
 
5.6%
1 52
 
5.2%
4 21
 
2.1%
9 19
 
1.9%
8 9
 
0.9%
Other values (2) 14
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 896
88.9%
Dash Punctuation 56
 
5.6%
Uppercase Letter 56
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 564
62.9%
2 84
 
9.4%
3 73
 
8.1%
5 60
 
6.7%
1 52
 
5.8%
4 21
 
2.3%
9 19
 
2.1%
8 9
 
1.0%
7 7
 
0.8%
6 7
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 952
94.4%
Latin 56
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 564
59.2%
2 84
 
8.8%
3 73
 
7.7%
5 60
 
6.3%
- 56
 
5.9%
1 52
 
5.5%
4 21
 
2.2%
9 19
 
2.0%
8 9
 
0.9%
7 7
 
0.7%
Latin
ValueCountFrequency (%)
S 56
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 564
56.0%
2 84
 
8.3%
3 73
 
7.2%
5 60
 
6.0%
- 56
 
5.6%
S 56
 
5.6%
1 52
 
5.2%
4 21
 
2.1%
9 19
 
1.9%
8 9
 
0.9%
Other values (2) 14
 
1.4%

인허가일자
Date

Distinct32
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum1999-08-23 00:00:00
Maximum2024-02-21 00:00:00
2024-05-11T15:11:02.278698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:11:02.511712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

인허가취소일자
Date

MISSING 

Distinct2
Distinct (%)66.7%
Missing53
Missing (%)94.6%
Memory size580.0 B
Minimum2023-11-20 00:00:00
Maximum2024-02-21 00:00:00
2024-05-11T15:11:02.700493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:11:02.877854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
53 
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 53
94.6%
4 3
 
5.4%

Length

2024-05-11T15:11:03.126285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:03.279856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 53
94.6%
4 3
 
5.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
영업/정상
53 
취소/말소/만료/정지/중지
 
3

Length

Max length14
Median length5
Mean length5.4821429
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 53
94.6%
취소/말소/만료/정지/중지 3
 
5.4%

Length

2024-05-11T15:11:03.450933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:03.615163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 53
94.6%
취소/말소/만료/정지/중지 3
 
5.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
18
53 
19
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
18 53
94.6%
19 3
 
5.4%

Length

2024-05-11T15:11:03.790469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:03.940786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 53
94.6%
19 3
 
5.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
사용중
53 
사용중지
 
3

Length

Max length4
Median length3
Mean length3.0535714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 53
94.6%
사용중지 3
 
5.4%

Length

2024-05-11T15:11:04.106185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:04.266744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 53
94.6%
사용중지 3
 
5.4%

폐업일자
Date

MISSING 

Distinct2
Distinct (%)66.7%
Missing53
Missing (%)94.6%
Memory size580.0 B
Minimum2023-11-20 00:00:00
Maximum2024-02-21 00:00:00
2024-05-11T15:11:04.380059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:11:04.555488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

소재지면적
Real number (ℝ)

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14390.786
Minimum621
Maximum45160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-11T15:11:04.829264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum621
5-th percentile2019.75
Q16587.25
median11800.5
Q318716
95-th percentile41173.5
Maximum45160
Range44539
Interquartile range (IQR)12128.75

Descriptive statistics

Standard deviation11195.991
Coefficient of variation (CV)0.77799718
Kurtosis1.3481387
Mean14390.786
Median Absolute Deviation (MAD)5559
Skewness1.3070009
Sum805884
Variance1.2535021 × 108
MonotonicityNot monotonic
2024-05-11T15:11:05.068074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21514 2
 
3.6%
13258 1
 
1.8%
11085 1
 
1.8%
40710 1
 
1.8%
9479 1
 
1.8%
18688 1
 
1.8%
11580 1
 
1.8%
10410 1
 
1.8%
5384 1
 
1.8%
22368 1
 
1.8%
Other values (45) 45
80.4%
ValueCountFrequency (%)
621 1
1.8%
700 1
1.8%
1752 1
1.8%
2109 1
1.8%
2179 1
1.8%
2248 1
1.8%
3001 1
1.8%
3100 1
1.8%
3944 1
1.8%
5298 1
1.8%
ValueCountFrequency (%)
45160 1
1.8%
43538 1
1.8%
42564 1
1.8%
40710 1
1.8%
38955 1
1.8%
32982 1
1.8%
25216 1
1.8%
24800 1
1.8%
22368 1
1.8%
21514 2
3.6%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

지번주소
Text

Distinct54
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-11T15:11:05.573070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length22.428571
Min length18

Characters and Unicode

Total characters1256
Distinct characters84
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)92.9%

Sample

1st row서울특별시 동대문구 용두동 794 용두롯데캐슬리치
2nd row서울특별시 동대문구 전농동 694 서울시립대학교
3rd row서울특별시 동대문구 용두동 253-1 e편한세상 청계센트럴포레 아파트
4th row서울특별시 동대문구 제기동 252번지
5th row서울특별시 동대문구 제기동 65번지
ValueCountFrequency (%)
서울특별시 56
22.0%
동대문구 56
22.0%
답십리동 9
 
3.5%
전농동 8
 
3.1%
휘경동 8
 
3.1%
용두동 8
 
3.1%
1호 7
 
2.7%
장안동 7
 
2.7%
제기동 5
 
2.0%
5호 5
 
2.0%
Other values (73) 86
33.7%
2024-05-11T15:11:06.323286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
199
15.8%
동 113
 
9.0%
문 61
 
4.9%
대 59
 
4.7%
시 58
 
4.6%
서 57
 
4.5%
울 57
 
4.5%
특 56
 
4.5%
별 56
 
4.5%
구 56
 
4.5%
Other values (74) 484
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 867
69.0%
Space Separator 199
 
15.8%
Decimal Number 185
 
14.7%
Dash Punctuation 4
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 113
13.0%
문 61
 
7.0%
대 59
 
6.8%
시 58
 
6.7%
서 57
 
6.6%
울 57
 
6.6%
특 56
 
6.5%
별 56
 
6.5%
구 56
 
6.5%
지 48
 
5.5%
Other values (61) 246
28.4%
Decimal Number
ValueCountFrequency (%)
1 29
15.7%
9 25
13.5%
2 21
11.4%
5 20
10.8%
6 19
10.3%
3 18
9.7%
7 17
9.2%
0 16
8.6%
4 10
 
5.4%
8 10
 
5.4%
Space Separator
ValueCountFrequency (%)
199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 867
69.0%
Common 388
30.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 113
13.0%
문 61
 
7.0%
대 59
 
6.8%
시 58
 
6.7%
서 57
 
6.6%
울 57
 
6.6%
특 56
 
6.5%
별 56
 
6.5%
구 56
 
6.5%
지 48
 
5.5%
Other values (61) 246
28.4%
Common
ValueCountFrequency (%)
199
51.3%
1 29
 
7.5%
9 25
 
6.4%
2 21
 
5.4%
5 20
 
5.2%
6 19
 
4.9%
3 18
 
4.6%
7 17
 
4.4%
0 16
 
4.1%
4 10
 
2.6%
Other values (2) 14
 
3.6%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 867
69.0%
ASCII 389
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
199
51.2%
1 29
 
7.5%
9 25
 
6.4%
2 21
 
5.4%
5 20
 
5.1%
6 19
 
4.9%
3 18
 
4.6%
7 17
 
4.4%
0 16
 
4.1%
4 10
 
2.6%
Other values (3) 15
 
3.9%
Hangul
ValueCountFrequency (%)
동 113
13.0%
문 61
 
7.0%
대 59
 
6.8%
시 58
 
6.7%
서 57
 
6.6%
울 57
 
6.6%
특 56
 
6.5%
별 56
 
6.5%
구 56
 
6.5%
지 48
 
5.5%
Other values (61) 246
28.4%

도로명주소
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-11T15:11:06.721052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length37
Mean length32.392857
Min length23

Characters and Unicode

Total characters1814
Distinct characters149
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

Unique54 ?
Unique (%)96.4%

Sample

1st row서울특별시 동대문구 한빛로 73(용두동, 용두롯데캐슬리치)
2nd row서울특별시 동대문구 서울시립대로 163, 서울시립대학교 (전농동)
3rd row서울특별시 동대문구 무학로 91(용두동, e편한세상 청계센트럴포레 아파트)
4th row서울특별시 동대문구 왕산로23길 89 (제기동, 이수브라운스톤)
5th row서울특별시 동대문구 왕산로 지하 93 (제기동, 제기동역)
ValueCountFrequency (%)
서울특별시 56
 
17.3%
동대문구 56
 
17.3%
답십리동 9
 
2.8%
전농동 8
 
2.5%
휘경동 7
 
2.2%
제기동 5
 
1.5%
장안동 5
 
1.5%
용두동 5
 
1.5%
서울시립대로 5
 
1.5%
회기동 4
 
1.2%
Other values (130) 163
50.5%
2024-05-11T15:11:07.467062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
267
 
14.7%
동 123
 
6.8%
대 73
 
4.0%
시 67
 
3.7%
문 65
 
3.6%
서 64
 
3.5%
울 64
 
3.5%
별 56
 
3.1%
특 56
 
3.1%
구 56
 
3.1%
Other values (139) 923
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1222
67.4%
Space Separator 267
 
14.7%
Decimal Number 164
 
9.0%
Open Punctuation 56
 
3.1%
Close Punctuation 56
 
3.1%
Other Punctuation 43
 
2.4%
Dash Punctuation 5
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 123
 
10.1%
대 73
 
6.0%
시 67
 
5.5%
문 65
 
5.3%
서 64
 
5.2%
울 64
 
5.2%
별 56
 
4.6%
특 56
 
4.6%
구 56
 
4.6%
로 56
 
4.6%
Other values (123) 542
44.4%
Decimal Number
ValueCountFrequency (%)
1 40
24.4%
2 22
13.4%
3 17
10.4%
5 17
10.4%
6 15
 
9.1%
0 14
 
8.5%
4 12
 
7.3%
7 10
 
6.1%
8 9
 
5.5%
9 8
 
4.9%
Space Separator
ValueCountFrequency (%)
267
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1222
67.4%
Common 591
32.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 123
 
10.1%
대 73
 
6.0%
시 67
 
5.5%
문 65
 
5.3%
서 64
 
5.2%
울 64
 
5.2%
별 56
 
4.6%
특 56
 
4.6%
구 56
 
4.6%
로 56
 
4.6%
Other values (123) 542
44.4%
Common
ValueCountFrequency (%)
267
45.2%
( 56
 
9.5%
) 56
 
9.5%
, 43
 
7.3%
1 40
 
6.8%
2 22
 
3.7%
3 17
 
2.9%
5 17
 
2.9%
6 15
 
2.5%
0 14
 
2.4%
Other values (5) 44
 
7.4%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1222
67.4%
ASCII 592
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
267
45.1%
( 56
 
9.5%
) 56
 
9.5%
, 43
 
7.3%
1 40
 
6.8%
2 22
 
3.7%
3 17
 
2.9%
5 17
 
2.9%
6 15
 
2.5%
0 14
 
2.4%
Other values (6) 45
 
7.6%
Hangul
ValueCountFrequency (%)
동 123
 
10.1%
대 73
 
6.0%
시 67
 
5.5%
문 65
 
5.3%
서 64
 
5.2%
울 64
 
5.2%
별 56
 
4.6%
특 56
 
4.6%
구 56
 
4.6%
로 56
 
4.6%
Other values (123) 542
44.4%

도로명우편번호
Text

Distinct52
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-11T15:11:07.897908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.8928571
Min length4

Characters and Unicode

Total characters274
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

Unique48 ?
Unique (%)85.7%

Sample

1st row02577
2nd row02504
3rd row02587
4th row2575
5th row2568
ValueCountFrequency (%)
02613 2
 
3.6%
02450 2
 
3.6%
02565 2
 
3.6%
02582 2
 
3.6%
02536 1
 
1.8%
02535 1
 
1.8%
02577 1
 
1.8%
02434 1
 
1.8%
2570 1
 
1.8%
02521 1
 
1.8%
Other values (42) 42
75.0%
2024-05-11T15:11:08.543363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 62
22.6%
0 54
19.7%
5 48
17.5%
4 25
9.1%
3 19
 
6.9%
1 17
 
6.2%
6 14
 
5.1%
7 13
 
4.7%
8 11
 
4.0%
- 6
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 268
97.8%
Dash Punctuation 6
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 62
23.1%
0 54
20.1%
5 48
17.9%
4 25
9.3%
3 19
 
7.1%
1 17
 
6.3%
6 14
 
5.2%
7 13
 
4.9%
8 11
 
4.1%
9 5
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 62
22.6%
0 54
19.7%
5 48
17.5%
4 25
9.1%
3 19
 
6.9%
1 17
 
6.2%
6 14
 
5.1%
7 13
 
4.7%
8 11
 
4.0%
- 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 62
22.6%
0 54
19.7%
5 48
17.5%
4 25
9.1%
3 19
 
6.9%
1 17
 
6.2%
6 14
 
5.1%
7 13
 
4.7%
8 11
 
4.0%
- 6
 
2.2%

사업장명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-05-11T15:11:09.011016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length22.410714
Min length13

Characters and Unicode

Total characters1255
Distinct characters151
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

Unique56 ?
Unique (%)100.0%

Sample

1st row용두동롯데캐슬리치지하주차장 지하1,2층
2nd row서울시립대운동장 지하주차장 1,2,3구역
3rd row용신e편한세상센트럴포레 지하주차장 지하 1,2,3층
4th row제기 이수브라운아파트 지하주차장 지하1,2층
5th row1호선 제기동역 지하 1층, 2층
ValueCountFrequency (%)
지하주차장 39
16.9%
지하 27
 
11.7%
1,2층 16
 
6.9%
지하1,2층 15
 
6.5%
1층 13
 
5.6%
답십리 9
 
3.9%
2층 8
 
3.5%
아파트 5
 
2.2%
휘경 4
 
1.7%
지하1층 3
 
1.3%
Other values (83) 92
39.8%
2024-05-11T15:11:09.866528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
14.0%
지 96
 
7.6%
하 93
 
7.4%
층 63
 
5.0%
1 60
 
4.8%
, 57
 
4.5%
2 53
 
4.2%
장 53
 
4.2%
차 48
 
3.8%
주 48
 
3.8%
Other values (141) 508
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 893
71.2%
Space Separator 176
 
14.0%
Decimal Number 124
 
9.9%
Other Punctuation 57
 
4.5%
Uppercase Letter 2
 
0.2%
Lowercase Letter 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 96
 
10.8%
하 93
 
10.4%
층 63
 
7.1%
장 53
 
5.9%
차 48
 
5.4%
주 48
 
5.4%
트 35
 
3.9%
아 31
 
3.5%
파 28
 
3.1%
동 18
 
2.0%
Other values (128) 380
42.6%
Decimal Number
ValueCountFrequency (%)
1 60
48.4%
2 53
42.7%
3 6
 
4.8%
0 2
 
1.6%
4 2
 
1.6%
5 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 893
71.2%
Common 359
28.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 96
 
10.8%
하 93
 
10.4%
층 63
 
7.1%
장 53
 
5.9%
차 48
 
5.4%
주 48
 
5.4%
트 35
 
3.9%
아 31
 
3.5%
파 28
 
3.1%
동 18
 
2.0%
Other values (128) 380
42.6%
Common
ValueCountFrequency (%)
176
49.0%
1 60
 
16.7%
, 57
 
15.9%
2 53
 
14.8%
3 6
 
1.7%
0 2
 
0.6%
4 2
 
0.6%
5 1
 
0.3%
) 1
 
0.3%
( 1
 
0.3%
Latin
ValueCountFrequency (%)
K 1
33.3%
e 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 893
71.2%
ASCII 362
28.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
48.6%
1 60
 
16.6%
, 57
 
15.7%
2 53
 
14.6%
3 6
 
1.7%
0 2
 
0.6%
4 2
 
0.6%
K 1
 
0.3%
e 1
 
0.3%
5 1
 
0.3%
Other values (3) 3
 
0.8%
Hangul
ValueCountFrequency (%)
지 96
 
10.8%
하 93
 
10.4%
층 63
 
7.1%
장 53
 
5.9%
차 48
 
5.4%
주 48
 
5.4%
트 35
 
3.9%
아 31
 
3.5%
파 28
 
3.1%
동 18
 
2.0%
Other values (128) 380
42.6%

최종수정일자
Date

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2023-04-10 14:44:45
Maximum2024-02-21 13:13:58
2024-05-11T15:11:10.177480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:11:10.418567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
U
55 
I
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
U 55
98.2%
I 1
 
1.8%

Length

2024-05-11T15:11:10.620983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:10.771626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 55
98.2%
i 1
 
1.8%

데이터갱신일자
Categorical

Distinct11
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-11-30 22:07:00.0
18 
2023-07-13 02:40:00.0
15 
2023-07-09 02:40:00.0
7 
2022-10-31 22:02:00.0
4 
2022-11-01 00:03:00.0
3 
Other values (6)
9 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique3 ?
Unique (%)5.4%

Sample

1st row2023-11-30 22:07:00.0
2nd row2022-11-01 00:04:00.0
3rd row2023-11-30 22:07:00.0
4th row2023-07-13 02:40:00.0
5th row2023-07-13 02:40:00.0

Common Values

ValueCountFrequency (%)
2023-11-30 22:07:00.0 18
32.1%
2023-07-13 02:40:00.0 15
26.8%
2023-07-09 02:40:00.0 7
 
12.5%
2022-10-31 22:02:00.0 4
 
7.1%
2022-11-01 00:03:00.0 3
 
5.4%
2023-12-01 22:03:00.0 2
 
3.6%
2022-12-06 22:03:00.0 2
 
3.6%
2022-12-07 22:00:00.0 2
 
3.6%
2022-11-01 00:04:00.0 1
 
1.8%
2023-04-12 02:40:00.0 1
 
1.8%

Length

2024-05-11T15:11:10.926221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 23
20.5%
2023-11-30 18
16.1%
22:07:00.0 18
16.1%
2023-07-13 15
13.4%
2023-07-09 7
 
6.2%
2022-10-31 4
 
3.6%
22:02:00.0 4
 
3.6%
2022-11-01 4
 
3.6%
22:03:00.0 4
 
3.6%
00:03:00.0 3
 
2.7%
Other values (8) 12
10.7%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

좌표정보(X)
Real number (ℝ)

Distinct52
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204645.89
Minimum202223.67
Maximum206590.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-11T15:11:11.113707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202223.67
5-th percentile202529.62
Q1203428.49
median204906.83
Q3205692.1
95-th percentile206294.34
Maximum206590.05
Range4366.3732
Interquartile range (IQR)2263.6151

Descriptive statistics

Standard deviation1264.8091
Coefficient of variation (CV)0.0061804765
Kurtosis-1.0387532
Mean204645.89
Median Absolute Deviation (MAD)898.85349
Skewness-0.37576524
Sum11460170
Variance1599742.1
MonotonicityNot monotonic
2024-05-11T15:11:11.654734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205232.466600533 2
 
3.6%
204469.209049094 2
 
3.6%
202223.67297276 2
 
3.6%
205114.830839822 2
 
3.6%
202666.663570798 1
 
1.8%
206329.142312404 1
 
1.8%
205790.569535899 1
 
1.8%
202716.197281758 1
 
1.8%
203388.646669062 1
 
1.8%
203113.876168187 1
 
1.8%
Other values (42) 42
75.0%
ValueCountFrequency (%)
202223.67297276 2
3.6%
202445.161387692 1
1.8%
202557.766413515 1
1.8%
202666.663570798 1
1.8%
202716.197281758 1
1.8%
202748.961554668 1
1.8%
202941.025851356 1
1.8%
203113.876168187 1
1.8%
203129.791436447 1
1.8%
203254.005800283 1
1.8%
ValueCountFrequency (%)
206590.046202018 1
1.8%
206586.572428103 1
1.8%
206329.142312404 1
1.8%
206282.745291263 1
1.8%
206179.384647281 1
1.8%
206166.46259278 1
1.8%
206101.9138443 1
1.8%
206009.495097994 1
1.8%
205997.604547856 1
1.8%
205980.772169045 1
1.8%

좌표정보(Y)
Real number (ℝ)

Distinct52
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean453178.45
Minimum451575.88
Maximum455275.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-05-11T15:11:11.885590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451575.88
5-th percentile451866.13
Q1452464.94
median452950.32
Q3454080.46
95-th percentile454953.95
Maximum455275.84
Range3699.9579
Interquartile range (IQR)1615.5223

Descriptive statistics

Standard deviation1015.519
Coefficient of variation (CV)0.0022408811
Kurtosis-0.90275892
Mean453178.45
Median Absolute Deviation (MAD)659.62996
Skewness0.46048115
Sum25377993
Variance1031278.8
MonotonicityNot monotonic
2024-05-11T15:11:12.119578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453459.554170353 2
 
3.6%
454934.047367752 2
 
3.6%
452685.182716824 2
 
3.6%
455013.644655621 2
 
3.6%
452981.373965337 1
 
1.8%
451575.878006889 1
 
1.8%
454211.953899577 1
 
1.8%
452561.486238062 1
 
1.8%
454069.152283609 1
 
1.8%
452562.228628963 1
 
1.8%
Other values (42) 42
75.0%
ValueCountFrequency (%)
451575.878006889 1
1.8%
451628.940827769 1
1.8%
451806.846262685 1
1.8%
451885.894862749 1
1.8%
451893.093734117 1
1.8%
451896.756025119 1
1.8%
451953.64664235 1
1.8%
452155.691148899 1
1.8%
452195.522783718 1
1.8%
452206.2713086 1
1.8%
ValueCountFrequency (%)
455275.835949587 1
1.8%
455013.644655621 2
3.6%
454934.047367752 2
3.6%
454719.205565844 1
1.8%
454592.910090539 1
1.8%
454588.888984242 1
1.8%
454580.041253386 1
1.8%
454366.301642229 1
1.8%
454303.798144764 1
1.8%
454211.953899577 1
1.8%

비상시설위치
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing33
Missing (%)58.9%
Memory size580.0 B
2024-05-11T15:11:12.450668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length21.043478
Min length18

Characters and Unicode

Total characters484
Distinct characters43
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

Unique21 ?
Unique (%)91.3%

Sample

1st row서울특별시 동대문구 제기동 252번지
2nd row서울특별시 동대문구 제기동 65번지
3rd row서울특별시 동대문구 휘경동 106번지
4th row서울특별시 동대문구 이문동 311번지
5th row서울특별시 동대문구 휘경동 366번지
ValueCountFrequency (%)
서울특별시 23
23.5%
동대문구 23
23.5%
전농동 7
 
7.1%
제기동 4
 
4.1%
답십리동 4
 
4.1%
5호 3
 
3.1%
회기동 3
 
3.1%
1번지 2
 
2.0%
휘경동 2
 
2.0%
용두동 2
 
2.0%
Other values (25) 25
25.5%
2024-05-11T15:11:12.902094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
15.5%
동 46
 
9.5%
문 24
 
5.0%
서 23
 
4.8%
특 23
 
4.8%
별 23
 
4.8%
시 23
 
4.8%
대 23
 
4.8%
구 23
 
4.8%
울 23
 
4.8%
Other values (33) 178
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
69.4%
Space Separator 75
 
15.5%
Decimal Number 72
 
14.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 46
13.7%
문 24
 
7.1%
서 23
 
6.8%
특 23
 
6.8%
별 23
 
6.8%
시 23
 
6.8%
대 23
 
6.8%
구 23
 
6.8%
울 23
 
6.8%
번 22
 
6.5%
Other values (21) 83
24.7%
Decimal Number
ValueCountFrequency (%)
1 12
16.7%
9 11
15.3%
6 10
13.9%
5 10
13.9%
0 8
11.1%
3 6
8.3%
2 5
6.9%
8 4
 
5.6%
7 3
 
4.2%
4 3
 
4.2%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
69.4%
Common 148
30.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 46
13.7%
문 24
 
7.1%
서 23
 
6.8%
특 23
 
6.8%
별 23
 
6.8%
시 23
 
6.8%
대 23
 
6.8%
구 23
 
6.8%
울 23
 
6.8%
번 22
 
6.5%
Other values (21) 83
24.7%
Common
ValueCountFrequency (%)
75
50.7%
1 12
 
8.1%
9 11
 
7.4%
6 10
 
6.8%
5 10
 
6.8%
0 8
 
5.4%
3 6
 
4.1%
2 5
 
3.4%
8 4
 
2.7%
7 3
 
2.0%
Other values (2) 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 336
69.4%
ASCII 148
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
50.7%
1 12
 
8.1%
9 11
 
7.4%
6 10
 
6.8%
5 10
 
6.8%
0 8
 
5.4%
3 6
 
4.1%
2 5
 
3.4%
8 4
 
2.7%
7 3
 
2.0%
Other values (2) 4
 
2.7%
Hangul
ValueCountFrequency (%)
동 46
13.7%
문 24
 
7.1%
서 23
 
6.8%
특 23
 
6.8%
별 23
 
6.8%
시 23
 
6.8%
대 23
 
6.8%
구 23
 
6.8%
울 23
 
6.8%
번 22
 
6.5%
Other values (21) 83
24.7%

시설구분명
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
33 
공공용시설
23 

Length

Max length5
Median length4
Mean length4.4107143
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 33
58.9%
공공용시설 23
41.1%

Length

2024-05-11T15:11:13.114157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:11:13.271629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
58.9%
공공용시설 23
41.1%

시설명_건물명
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing33
Missing (%)58.9%
Memory size580.0 B
2024-05-11T15:11:13.557724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length22.782609
Min length13

Characters and Unicode

Total characters524
Distinct characters97
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

Unique23 ?
Unique (%)100.0%

Sample

1st row제기 이수브라운아파트 지하주차장 지하1,2층
2nd row1호선 제기동역 지하 1층, 2층
3rd row휘경미소지움아파트 지하주차장 지하 1층
4th row이문 래미안2차아파트 지하주차장 지하1,2층
5th row휘경 동일스위트리버 지하주차장 지하 1,2층
ValueCountFrequency (%)
지하주차장 17
17.3%
지하 11
 
11.2%
지하1,2층 9
 
9.2%
1,2층 8
 
8.2%
답십리 4
 
4.1%
아파트 3
 
3.1%
1층 3
 
3.1%
2층 3
 
3.1%
지하1층 2
 
2.0%
경희의료원 2
 
2.0%
Other values (35) 36
36.7%
2024-05-11T15:11:14.196560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
14.3%
지 42
 
8.0%
하 39
 
7.4%
1 26
 
5.0%
층 25
 
4.8%
2 23
 
4.4%
, 22
 
4.2%
차 19
 
3.6%
주 18
 
3.4%
장 17
 
3.2%
Other values (87) 218
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 377
71.9%
Space Separator 75
 
14.3%
Decimal Number 50
 
9.5%
Other Punctuation 22
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 42
 
11.1%
하 39
 
10.3%
층 25
 
6.6%
차 19
 
5.0%
주 18
 
4.8%
장 17
 
4.5%
아 15
 
4.0%
트 15
 
4.0%
파 13
 
3.4%
리 8
 
2.1%
Other values (82) 166
44.0%
Decimal Number
ValueCountFrequency (%)
1 26
52.0%
2 23
46.0%
0 1
 
2.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 377
71.9%
Common 147
 
28.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 42
 
11.1%
하 39
 
10.3%
층 25
 
6.6%
차 19
 
5.0%
주 18
 
4.8%
장 17
 
4.5%
아 15
 
4.0%
트 15
 
4.0%
파 13
 
3.4%
리 8
 
2.1%
Other values (82) 166
44.0%
Common
ValueCountFrequency (%)
75
51.0%
1 26
 
17.7%
2 23
 
15.6%
, 22
 
15.0%
0 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 377
71.9%
ASCII 147
 
28.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
51.0%
1 26
 
17.7%
2 23
 
15.6%
, 22
 
15.0%
0 1
 
0.7%
Hangul
ValueCountFrequency (%)
지 42
 
11.1%
하 39
 
10.3%
층 25
 
6.6%
차 19
 
5.0%
주 18
 
4.8%
장 17
 
4.5%
아 15
 
4.0%
트 15
 
4.0%
파 13
 
3.4%
리 8
 
2.1%
Other values (82) 166
44.0%

해제일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
030500003050000-S2022000072022-12-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>13258<NA>서울특별시 동대문구 용두동 794 용두롯데캐슬리치서울특별시 동대문구 한빛로 73(용두동, 용두롯데캐슬리치)02577용두동롯데캐슬리치지하주차장 지하1,2층2024-01-25 15:30:10U2023-11-30 22:07:00.0<NA>202666.663571452981.373965<NA><NA><NA><NA>
130500003050000-S2022000022022-07-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>11085<NA>서울특별시 동대문구 전농동 694 서울시립대학교서울특별시 동대문구 서울시립대로 163, 서울시립대학교 (전농동)02504서울시립대운동장 지하주차장 1,2,3구역2023-11-02 16:32:14U2022-11-01 00:04:00.0<NA>205232.466601453459.55417<NA><NA><NA><NA>
230500003050000-S2022000012022-07-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>42564<NA>서울특별시 동대문구 용두동 253-1 e편한세상 청계센트럴포레 아파트서울특별시 동대문구 무학로 91(용두동, e편한세상 청계센트럴포레 아파트)02587용신e편한세상센트럴포레 지하주차장 지하 1,2,3층2024-01-25 15:38:16U2023-11-30 22:07:00.0<NA>202557.766414452206.271309<NA><NA><NA><NA>
330500003050000-S2006000082006-11-08<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>14992<NA>서울특별시 동대문구 제기동 252번지서울특별시 동대문구 왕산로23길 89 (제기동, 이수브라운스톤)2575제기 이수브라운아파트 지하주차장 지하1,2층2023-07-11 15:14:30U2023-07-13 02:40:00.0<NA>202941.025851453322.642769서울특별시 동대문구 제기동 252번지공공용시설제기 이수브라운아파트 지하주차장 지하1,2층<NA>
430500003050000-S2004002592004-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6701<NA>서울특별시 동대문구 제기동 65번지서울특별시 동대문구 왕산로 지하 93 (제기동, 제기동역)25681호선 제기동역 지하 1층, 2층2023-07-11 15:06:53U2023-07-13 02:40:00.0<NA>203363.795782452919.261029서울특별시 동대문구 제기동 65번지공공용시설1호선 제기동역 지하 1층, 2층<NA>
530500003050000-S2000000082000-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5298<NA>서울특별시 동대문구 휘경동 106번지서울특별시 동대문구 망우로 105 (휘경동, 휘경미소지움아파트)2436휘경미소지움아파트 지하주차장 지하 1층2023-07-07 16:44:58U2023-07-09 02:40:00.0<NA>205656.734024454366.301642서울특별시 동대문구 휘경동 106번지공공용시설휘경미소지움아파트 지하주차장 지하 1층<NA>
630500003050000-S2009000112009-11-06<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>16262<NA>서울특별시 동대문구 이문동 311번지서울특별시 동대문구 이문로12길 3-10 (이문동, 래미안이문2차아파트)2442이문 래미안2차아파트 지하주차장 지하1,2층2023-07-11 15:35:08U2023-07-13 02:40:00.0<NA>205239.623092454580.041253서울특별시 동대문구 이문동 311번지공공용시설이문 래미안2차아파트 지하주차장 지하1,2층<NA>
730500003050000-S2009000152009-10-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>19052<NA>서울특별시 동대문구 휘경동 366번지서울특별시 동대문구 한천로 300 (휘경동, 동일스위트리버)2511휘경 동일스위트리버 지하주차장 지하 1,2층2023-07-11 15:36:37U2023-07-13 02:40:00.0<NA>205997.604548453902.53168서울특별시 동대문구 휘경동 366번지공공용시설휘경 동일스위트리버 지하주차장 지하 1,2층<NA>
830500003050000-S2009000162009-10-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>15052<NA>서울특별시 동대문구 휘경동 57번지서울특별시 동대문구 한천로 248 (휘경동)02512휘경 주공아파트 지하주차장 지하 1,2층2023-11-20 17:31:02U2022-10-31 22:02:00.0<NA>206179.384647453411.742857<NA><NA><NA><NA>
930500003050000-S2009000132009-11-062024-02-214취소/말소/만료/정지/중지19사용중지2024-02-21<NA><NA><NA><NA>2109<NA>서울특별시 동대문구 이문동 270번지 1호서울특별시 동대문구 이문로 107 (이문동)02450한국외국어대 교수학습개발원 지하1층2024-02-21 13:13:58U2023-12-01 22:03:00.0<NA>205114.83084455013.644656<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
4630500003050000-S2009000182009-10-23<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>21514<NA>서울특별시 동대문구 장안동 329번지 3호서울특별시 동대문구 장안벚꽃로 167 (장안동, 래미안장안2차아파트)02524장안삼성래미안2차 지하주차장 지하 1,2층2024-01-25 17:52:37U2023-11-30 22:07:00.0<NA>206590.046202452410.619465<NA><NA><NA><NA>
4730500003050000-S2009000022009-10-21<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3100<NA>서울특별시 동대문구 용두동 47번지 1호서울특별시 동대문구 천호대로 지하 129 (용두동)025652호선 용두역 지하 1층, 2층2024-01-25 16:06:54U2023-11-30 22:07:00.0<NA>203322.734698452572.376924<NA><NA><NA><NA>
4830500003050000-S2004003022004-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3001<NA>서울특별시 동대문구 신설동 76번지 5호서울특별시 동대문구 왕산로 지하 1 (신설동, 신설동역)025822호선 신설동역 지하 1층, 2층2024-01-25 16:12:04U2023-11-30 22:07:00.0<NA>202223.672973452685.182717<NA><NA><NA><NA>
4930500003050000-S2004003012004-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6248<NA>서울특별시 동대문구 신설동 76번지 5호서울특별시 동대문구 왕산로 지하 1 (신설동, 신설동역)025821호선 신설동역 지하 1층, 2층2024-01-25 16:12:33U2023-11-30 22:07:00.0<NA>202223.672973452685.182717<NA><NA><NA><NA>
5030500003050000-S2004002052004-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>24800<NA>서울특별시 동대문구 답십리동 10번지서울특별시 동대문구 한천로11길 10-1 (답십리동, 동아아파트)02612답십리 동아아파트 지하주차장 지하 1,2층2024-01-25 16:13:52U2023-11-30 22:07:00.0<NA>205381.986112451896.756025<NA><NA><NA><NA>
5130500003050000-S2004003642004-10-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2248<NA>서울특별시 동대문구 답십리동 990번지 1호서울특별시 동대문구 답십리로56길 21-1 (답십리동, 두산아파트)02613답십리 두산임대아파트 지하주차장 1층2024-01-25 16:08:00U2023-11-30 22:07:00.0<NA>205172.763733451885.894863<NA><NA><NA><NA>
5230500003050000-S2003000102003-03-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>700<NA>서울특별시 동대문구 답십리동 990번지서울특별시 동대문구 답십리로56길 21 (답십리동, 두산아파트)02613답십리 두산아파트 지하주차장 지하 1층2024-01-25 15:29:27U2023-11-30 22:07:00.0<NA>205247.577384451893.093734<NA><NA><NA><NA>
5330500003050000-S2003000112003-03-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>18800<NA>서울특별시 동대문구 답십리동 80번지서울특별시 동대문구 전농로10길 20 (답십리동, 답십리청솔우성아파트)02536답십리 청솔우성아파트 지하주차장 지하 1,2층2024-01-25 15:29:08U2023-11-30 22:07:00.0<NA>205208.16745452466.868526<NA><NA><NA><NA>
5430500003050000-S1999000031999-10-13<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3944<NA>서울특별시 동대문구 답십리동 989번지 1호서울특별시 동대문구 답십리로59길 33 (답십리동, 우성그린아파트)02535답십리 우성그린아파트 지하주차장 지하 1층2024-01-25 15:27:51U2023-11-30 22:07:00.0<NA>205762.994263452510.004743<NA><NA><NA><NA>
5530500003050000-S2004003402004-06-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6258<NA>서울특별시 동대문구 장안동 555번지 1호서울특별시 동대문구 사가정로 245-3 (장안동, 한신아파트)02515장안 한신아파트 지하주차장 지하1,2층2024-01-31 15:53:29U2023-12-02 00:02:00.0<NA>206282.745291453027.766626<NA><NA><NA><NA>