Overview

Dataset statistics

Number of variables29
Number of observations111
Missing cells1113
Missing cells (%)34.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.8 KiB
Average record size in memory247.2 B

Variable types

Categorical7
Text6
DateTime5
Unsupported7
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-20045/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (62.6%)Imbalance
영업상태명 is highly imbalanced (62.6%)Imbalance
상세영업상태코드 is highly imbalanced (62.6%)Imbalance
상세영업상태명 is highly imbalanced (62.6%)Imbalance
데이터갱신구분 is highly imbalanced (92.6%)Imbalance
인허가취소일자 has 103 (92.8%) missing valuesMissing
폐업일자 has 103 (92.8%) missing valuesMissing
휴업시작일자 has 111 (100.0%) missing valuesMissing
휴업종료일자 has 111 (100.0%) missing valuesMissing
재개업일자 has 111 (100.0%) missing valuesMissing
전화번호 has 111 (100.0%) missing valuesMissing
소재지우편번호 has 111 (100.0%) missing valuesMissing
업태구분명 has 111 (100.0%) missing valuesMissing
비상시설위치 has 65 (58.6%) missing valuesMissing
시설명_건물명 has 65 (58.6%) missing valuesMissing
해제일자 has 111 (100.0%) missing valuesMissing
관리번호 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 started2024-04-06 10:29:24.244963
Analysis finished2024-04-06 10:29:25.248934
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
3180000
111 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 111
100.0%

Length

2024-04-06T19:29:25.327800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:25.459491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 111
100.0%

관리번호
Text

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-04-06T19:29:25.698777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1998
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

Unique111 ?
Unique (%)100.0%

Sample

1st row3180000-S202100003
2nd row3180000-S200300082
3rd row3180000-S201300006
4th row3180000-S200900001
5th row3180000-S200300033
ValueCountFrequency (%)
3180000-s202100003 1
 
0.9%
3180000-s200300037 1
 
0.9%
3180000-s202300004 1
 
0.9%
3180000-s200300051 1
 
0.9%
3180000-s201300001 1
 
0.9%
3180000-s200300055 1
 
0.9%
3180000-s201300009 1
 
0.9%
3180000-s200900030 1
 
0.9%
3180000-s200900032 1
 
0.9%
3180000-s201000009 1
 
0.9%
Other values (101) 101
91.0%
2024-04-06T19:29:26.232781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1019
51.0%
3 193
 
9.7%
1 179
 
9.0%
2 157
 
7.9%
8 129
 
6.5%
- 111
 
5.6%
S 111
 
5.6%
9 30
 
1.5%
5 20
 
1.0%
7 18
 
0.9%
Other values (2) 31
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1776
88.9%
Dash Punctuation 111
 
5.6%
Uppercase Letter 111
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019
57.4%
3 193
 
10.9%
1 179
 
10.1%
2 157
 
8.8%
8 129
 
7.3%
9 30
 
1.7%
5 20
 
1.1%
7 18
 
1.0%
4 17
 
1.0%
6 14
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1887
94.4%
Latin 111
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019
54.0%
3 193
 
10.2%
1 179
 
9.5%
2 157
 
8.3%
8 129
 
6.8%
- 111
 
5.9%
9 30
 
1.6%
5 20
 
1.1%
7 18
 
1.0%
4 17
 
0.9%
Latin
ValueCountFrequency (%)
S 111
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019
51.0%
3 193
 
9.7%
1 179
 
9.0%
2 157
 
7.9%
8 129
 
6.5%
- 111
 
5.6%
S 111
 
5.6%
9 30
 
1.5%
5 20
 
1.0%
7 18
 
0.9%
Other values (2) 31
 
1.6%

인허가일자
Date

Distinct53
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2003-05-15 00:00:00
Maximum2024-02-16 00:00:00
2024-04-06T19:29:26.471323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:29:26.735096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct7
Distinct (%)87.5%
Missing103
Missing (%)92.8%
Memory size1020.0 B
Minimum2023-08-28 00:00:00
Maximum2023-11-23 00:00:00
2024-04-06T19:29:26.939353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:29:27.112035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
1
103 
4
 
8

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 (%)
1 103
92.8%
4 8
 
7.2%

Length

2024-04-06T19:29:27.380619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:27.547068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 103
92.8%
4 8
 
7.2%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
영업/정상
103 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length5.6486486
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 103
92.8%
취소/말소/만료/정지/중지 8
 
7.2%

Length

2024-04-06T19:29:27.721556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:27.917780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 103
92.8%
취소/말소/만료/정지/중지 8
 
7.2%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
18
103 
19
 
8

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 (%)
18 103
92.8%
19 8
 
7.2%

Length

2024-04-06T19:29:28.126092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:28.324619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 103
92.8%
19 8
 
7.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
사용중
103 
사용중지
 
8

Length

Max length4
Median length3
Mean length3.0720721
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 103
92.8%
사용중지 8
 
7.2%

Length

2024-04-06T19:29:28.544034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:28.733715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 103
92.8%
사용중지 8
 
7.2%

폐업일자
Date

MISSING 

Distinct7
Distinct (%)87.5%
Missing103
Missing (%)92.8%
Memory size1020.0 B
Minimum2023-08-28 00:00:00
Maximum2023-11-23 00:00:00
2024-04-06T19:29:28.901931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:29:29.136426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

소재지면적
Real number (ℝ)

Distinct110
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10811.263
Minimum240.8
Maximum87849.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:29:29.409639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240.8
5-th percentile663.905
Q12330.5
median5940
Q39995.115
95-th percentile46126.1
Maximum87849.09
Range87608.29
Interquartile range (IQR)7664.615

Descriptive statistics

Standard deviation16202.134
Coefficient of variation (CV)1.4986347
Kurtosis9.6881175
Mean10811.263
Median Absolute Deviation (MAD)3760
Skewness3.0308499
Sum1200050.2
Variance2.6250916 × 108
MonotonicityNot monotonic
2024-04-06T19:29:29.695562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6669.48 2
 
1.8%
68748.95 1
 
0.9%
9700.0 1
 
0.9%
37120.35 1
 
0.9%
6191.0 1
 
0.9%
6158.71 1
 
0.9%
1007.0 1
 
0.9%
2290.0 1
 
0.9%
5404.0 1
 
0.9%
5268.0 1
 
0.9%
Other values (100) 100
90.1%
ValueCountFrequency (%)
240.8 1
0.9%
284.3 1
0.9%
297.0 1
0.9%
470.9 1
0.9%
552.64 1
0.9%
660.81 1
0.9%
667.0 1
0.9%
705.0 1
0.9%
737.84 1
0.9%
806.62 1
0.9%
ValueCountFrequency (%)
87849.09 1
0.9%
85144.0 1
0.9%
68748.95 1
0.9%
60500.0 1
0.9%
51398.0 1
0.9%
46206.0 1
0.9%
46046.2 1
0.9%
42778.83 1
0.9%
40010.0 1
0.9%
37120.35 1
0.9%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

지번주소
Text

Distinct108
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-04-06T19:29:30.120544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length28.171171
Min length19

Characters and Unicode

Total characters3127
Distinct characters171
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)95.5%

Sample

1st row서울특별시 영등포구 신길동 4969 힐스테이트 클래시안
2nd row서울특별시 영등포구 대림동 993-75
3rd row서울특별시 영등포구 당산동3가 560 영등포구 별관청사
4th row서울특별시 영등포구 당산동3가 385번지
5th row서울특별시 영등포구 당산동3가 270-1 영등포구청역
ValueCountFrequency (%)
서울특별시 111
 
19.0%
영등포구 111
 
19.0%
신길동 31
 
5.3%
대림동 17
 
2.9%
여의도동 8
 
1.4%
당산동3가 6
 
1.0%
영등포동 6
 
1.0%
문래동6가 5
 
0.9%
영등포동3가 4
 
0.7%
문래동3가 4
 
0.7%
Other values (239) 281
48.1%
2024-04-06T19:29:30.816258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
 
15.1%
영 146
 
4.7%
포 145
 
4.6%
등 144
 
4.6%
동 134
 
4.3%
구 116
 
3.7%
시 116
 
3.7%
서 113
 
3.6%
별 112
 
3.6%
울 111
 
3.5%
Other values (161) 1517
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2158
69.0%
Space Separator 473
 
15.1%
Decimal Number 436
 
13.9%
Dash Punctuation 54
 
1.7%
Uppercase Letter 5
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 146
 
6.8%
포 145
 
6.7%
등 144
 
6.7%
동 134
 
6.2%
구 116
 
5.4%
시 116
 
5.4%
서 113
 
5.2%
별 112
 
5.2%
울 111
 
5.1%
특 111
 
5.1%
Other values (145) 910
42.2%
Decimal Number
ValueCountFrequency (%)
1 84
19.3%
3 60
13.8%
6 51
11.7%
4 49
11.2%
5 41
9.4%
9 38
8.7%
2 35
8.0%
7 29
 
6.7%
8 26
 
6.0%
0 23
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
G 2
40.0%
N 1
20.0%
Space Separator
ValueCountFrequency (%)
473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2157
69.0%
Common 964
30.8%
Latin 5
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 146
 
6.8%
포 145
 
6.7%
등 144
 
6.7%
동 134
 
6.2%
구 116
 
5.4%
시 116
 
5.4%
서 113
 
5.2%
별 112
 
5.2%
울 111
 
5.1%
특 111
 
5.1%
Other values (144) 909
42.1%
Common
ValueCountFrequency (%)
473
49.1%
1 84
 
8.7%
3 60
 
6.2%
- 54
 
5.6%
6 51
 
5.3%
4 49
 
5.1%
5 41
 
4.3%
9 38
 
3.9%
2 35
 
3.6%
7 29
 
3.0%
Other values (3) 50
 
5.2%
Latin
ValueCountFrequency (%)
S 2
40.0%
G 2
40.0%
N 1
20.0%
Han
ValueCountFrequency (%)
新 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2157
69.0%
ASCII 969
31.0%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
48.8%
1 84
 
8.7%
3 60
 
6.2%
- 54
 
5.6%
6 51
 
5.3%
4 49
 
5.1%
5 41
 
4.2%
9 38
 
3.9%
2 35
 
3.6%
7 29
 
3.0%
Other values (6) 55
 
5.7%
Hangul
ValueCountFrequency (%)
영 146
 
6.8%
포 145
 
6.7%
등 144
 
6.7%
동 134
 
6.2%
구 116
 
5.4%
시 116
 
5.4%
서 113
 
5.2%
별 112
 
5.2%
울 111
 
5.1%
특 111
 
5.1%
Other values (144) 909
42.1%
CJK
ValueCountFrequency (%)
新 1
100.0%

도로명주소
Text

Distinct107
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-04-06T19:29:31.242017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length35.36036
Min length24

Characters and Unicode

Total characters3925
Distinct characters181
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)93.7%

Sample

1st row서울특별시 영등포구 신길로28길 9(신길동, 힐스테이트 클래시안)
2nd row서울특별시 영등포구 시흥대로 613(대림동)
3rd row서울특별시 영등포구 선유동1로 80, 영등포구 별관청사 (당산동3가)
4th row서울특별시 영등포구 당산로27길 12 (당산동3가)
5th row서울특별시 영등포구 당산로 지하121, 영등포구청역 (당산동3가)
ValueCountFrequency (%)
서울특별시 111
 
17.2%
영등포구 111
 
17.2%
신길동 11
 
1.7%
지하1층 8
 
1.2%
여의도동 8
 
1.2%
영등포로 6
 
0.9%
당산동3가 6
 
0.9%
국회대로 4
 
0.6%
도림로 4
 
0.6%
당산로 4
 
0.6%
Other values (294) 373
57.7%
2024-04-06T19:29:31.924251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
 
13.6%
영 162
 
4.1%
포 155
 
3.9%
등 154
 
3.9%
동 139
 
3.5%
시 119
 
3.0%
서 118
 
3.0%
구 116
 
3.0%
로 113
 
2.9%
별 112
 
2.9%
Other values (171) 2202
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2645
67.4%
Space Separator 535
 
13.6%
Decimal Number 404
 
10.3%
Close Punctuation 111
 
2.8%
Open Punctuation 111
 
2.8%
Other Punctuation 110
 
2.8%
Uppercase Letter 5
 
0.1%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 162
 
6.1%
포 155
 
5.9%
등 154
 
5.8%
동 139
 
5.3%
시 119
 
4.5%
서 118
 
4.5%
구 116
 
4.4%
로 113
 
4.3%
별 112
 
4.2%
울 111
 
4.2%
Other values (152) 1346
50.9%
Decimal Number
ValueCountFrequency (%)
1 77
19.1%
2 64
15.8%
3 54
13.4%
4 49
12.1%
5 37
9.2%
7 32
7.9%
6 31
7.7%
9 20
 
5.0%
0 20
 
5.0%
8 20
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
G 2
40.0%
N 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 109
99.1%
/ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
535
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2644
67.4%
Common 1275
32.5%
Latin 5
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 162
 
6.1%
포 155
 
5.9%
등 154
 
5.8%
동 139
 
5.3%
시 119
 
4.5%
서 118
 
4.5%
구 116
 
4.4%
로 113
 
4.3%
별 112
 
4.2%
울 111
 
4.2%
Other values (151) 1345
50.9%
Common
ValueCountFrequency (%)
535
42.0%
) 111
 
8.7%
( 111
 
8.7%
, 109
 
8.5%
1 77
 
6.0%
2 64
 
5.0%
3 54
 
4.2%
4 49
 
3.8%
5 37
 
2.9%
7 32
 
2.5%
Other values (6) 96
 
7.5%
Latin
ValueCountFrequency (%)
S 2
40.0%
G 2
40.0%
N 1
20.0%
Han
ValueCountFrequency (%)
新 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2644
67.4%
ASCII 1280
32.6%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
41.8%
) 111
 
8.7%
( 111
 
8.7%
, 109
 
8.5%
1 77
 
6.0%
2 64
 
5.0%
3 54
 
4.2%
4 49
 
3.8%
5 37
 
2.9%
7 32
 
2.5%
Other values (9) 101
 
7.9%
Hangul
ValueCountFrequency (%)
영 162
 
6.1%
포 155
 
5.9%
등 154
 
5.8%
동 139
 
5.3%
시 119
 
4.5%
서 118
 
4.5%
구 116
 
4.4%
로 113
 
4.3%
별 112
 
4.2%
울 111
 
4.2%
Other values (151) 1345
50.9%
CJK
ValueCountFrequency (%)
新 1
100.0%

도로명우편번호
Real number (ℝ)

Distinct83
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7321.7658
Minimum7055
Maximum7448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:29:32.177195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7055
5-th percentile7212
Q17264
median7318
Q37378.5
95-th percentile7433
Maximum7448
Range393
Interquartile range (IQR)114.5

Descriptive statistics

Standard deviation73.284496
Coefficient of variation (CV)0.010009129
Kurtosis0.15286032
Mean7321.7658
Median Absolute Deviation (MAD)58
Skewness-0.33380007
Sum812716
Variance5370.6174
MonotonicityNot monotonic
2024-04-06T19:29:32.463026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7362 4
 
3.6%
7260 3
 
2.7%
7306 3
 
2.7%
7250 3
 
2.7%
7282 2
 
1.8%
7445 2
 
1.8%
7428 2
 
1.8%
7264 2
 
1.8%
7361 2
 
1.8%
7236 2
 
1.8%
Other values (73) 86
77.5%
ValueCountFrequency (%)
7055 1
0.9%
7204 1
0.9%
7205 1
0.9%
7206 1
0.9%
7208 1
0.9%
7210 1
0.9%
7214 2
1.8%
7217 1
0.9%
7219 1
0.9%
7221 1
0.9%
ValueCountFrequency (%)
7448 2
1.8%
7445 2
1.8%
7441 1
0.9%
7437 1
0.9%
7429 1
0.9%
7428 2
1.8%
7426 1
0.9%
7420 1
0.9%
7415 1
0.9%
7411 1
0.9%

사업장명
Text

Distinct110
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-04-06T19:29:32.965648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length16.225225
Min length6

Characters and Unicode

Total characters1801
Distinct characters179
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

Unique109 ?
Unique (%)98.2%

Sample

1st row신길동 힐스테이트클래시안 아파트 지하주차장 B2~B4층
2nd row안국약품빌딩 지하1층 주차장
3rd row영등포구청별관 지하1층
4th row당산근린공원 지하1~2층 주차장
5th row지하철 2호선 영등포구청역 지하1~2층 역사
ValueCountFrequency (%)
지하1층 44
 
14.7%
주차장 25
 
8.3%
1층 14
 
4.7%
지하1~2층 12
 
4.0%
지하 12
 
4.0%
지하주차장 10
 
3.3%
아파트 9
 
3.0%
지하철 4
 
1.3%
지하1층~지하3층 4
 
1.3%
1~2층 4
 
1.3%
Other values (138) 162
54.0%
2024-04-06T19:29:33.725858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
10.5%
지 147
 
8.2%
하 138
 
7.7%
층 110
 
6.1%
1 105
 
5.8%
아 62
 
3.4%
트 60
 
3.3%
차 58
 
3.2%
파 58
 
3.2%
장 45
 
2.5%
Other values (169) 829
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1349
74.9%
Decimal Number 191
 
10.6%
Space Separator 189
 
10.5%
Math Symbol 37
 
2.1%
Open Punctuation 14
 
0.8%
Close Punctuation 14
 
0.8%
Uppercase Letter 5
 
0.3%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 147
 
10.9%
하 138
 
10.2%
층 110
 
8.2%
아 62
 
4.6%
트 60
 
4.4%
차 58
 
4.3%
파 58
 
4.3%
장 45
 
3.3%
주 45
 
3.3%
역 23
 
1.7%
Other values (150) 603
44.7%
Decimal Number
ValueCountFrequency (%)
1 105
55.0%
2 41
 
21.5%
3 19
 
9.9%
5 9
 
4.7%
9 5
 
2.6%
4 4
 
2.1%
6 3
 
1.6%
7 3
 
1.6%
0 2
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
S 1
20.0%
G 1
20.0%
N 1
20.0%
Space Separator
ValueCountFrequency (%)
189
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1349
74.9%
Common 447
 
24.8%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 147
 
10.9%
하 138
 
10.2%
층 110
 
8.2%
아 62
 
4.6%
트 60
 
4.4%
차 58
 
4.3%
파 58
 
4.3%
장 45
 
3.3%
주 45
 
3.3%
역 23
 
1.7%
Other values (150) 603
44.7%
Common
ValueCountFrequency (%)
189
42.3%
1 105
23.5%
2 41
 
9.2%
~ 37
 
8.3%
3 19
 
4.3%
( 14
 
3.1%
) 14
 
3.1%
5 9
 
2.0%
9 5
 
1.1%
4 4
 
0.9%
Other values (5) 10
 
2.2%
Latin
ValueCountFrequency (%)
B 2
40.0%
S 1
20.0%
G 1
20.0%
N 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1349
74.9%
ASCII 452
 
25.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
41.8%
1 105
23.2%
2 41
 
9.1%
~ 37
 
8.2%
3 19
 
4.2%
( 14
 
3.1%
) 14
 
3.1%
5 9
 
2.0%
9 5
 
1.1%
4 4
 
0.9%
Other values (9) 15
 
3.3%
Hangul
ValueCountFrequency (%)
지 147
 
10.9%
하 138
 
10.2%
층 110
 
8.2%
아 62
 
4.6%
트 60
 
4.4%
차 58
 
4.3%
파 58
 
4.3%
장 45
 
3.3%
주 45
 
3.3%
역 23
 
1.7%
Other values (150) 603
44.7%

최종수정일자
Date

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2023-01-04 21:26:09
Maximum2024-02-22 10:17:11
2024-04-06T19:29:34.033191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:29:34.269508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
U
110 
I
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
U 110
99.1%
I 1
 
0.9%

Length

2024-04-06T19:29:34.506110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:34.668405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 110
99.1%
i 1
 
0.9%

데이터갱신일자
Date

Distinct34
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2022-10-30 23:05:00
Maximum2023-12-01 23:08:00
2024-04-06T19:29:34.827788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:29:35.029612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

좌표정보(X)
Real number (ℝ)

Distinct106
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191457.19
Minimum189574.96
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:29:35.262875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189574.96
5-th percentile189816.98
Q1190626.5
median191362.38
Q3192240.01
95-th percentile193355.67
Maximum194632.53
Range5057.5643
Interquartile range (IQR)1613.5011

Descriptive statistics

Standard deviation1066.1192
Coefficient of variation (CV)0.0055684469
Kurtosis-0.18487484
Mean191457.19
Median Absolute Deviation (MAD)751.67051
Skewness0.44926586
Sum21251748
Variance1136610.1
MonotonicityNot monotonic
2024-04-06T19:29:35.534130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191741.345847708 3
 
2.7%
192445.378088921 2
 
1.8%
191614.68614355 2
 
1.8%
193471.519357881 2
 
1.8%
190039.883757935 1
 
0.9%
189784.908763399 1
 
0.9%
190397.469045157 1
 
0.9%
189849.04538548 1
 
0.9%
192265.443772766 1
 
0.9%
190867.232885013 1
 
0.9%
Other values (96) 96
86.5%
ValueCountFrequency (%)
189574.962072527 1
0.9%
189600.906705305 1
0.9%
189659.894354143 1
0.9%
189713.985064015 1
0.9%
189734.544016734 1
0.9%
189784.908763399 1
0.9%
189849.04538548 1
0.9%
189887.928482279 1
0.9%
190026.251961332 1
0.9%
190039.883757935 1
0.9%
ValueCountFrequency (%)
194632.526367463 1
0.9%
193964.752865597 1
0.9%
193753.311604119 1
0.9%
193471.519357881 2
1.8%
193389.462376889 1
0.9%
193321.876375444 1
0.9%
193281.875201994 1
0.9%
193099.563598351 1
0.9%
192986.02636243 1
0.9%
192906.74356222 1
0.9%

좌표정보(Y)
Real number (ℝ)

Distinct106
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean445728.48
Minimum442710.66
Maximum448656.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:29:35.740652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442710.66
5-th percentile443419.7
Q1444735.04
median445970.31
Q3446825.41
95-th percentile447725.33
Maximum448656.73
Range5946.0646
Interquartile range (IQR)2090.3664

Descriptive statistics

Standard deviation1396.8685
Coefficient of variation (CV)0.0031339
Kurtosis-0.61437475
Mean445728.48
Median Absolute Deviation (MAD)1051.838
Skewness-0.19995786
Sum49475862
Variance1951241.6
MonotonicityNot monotonic
2024-04-06T19:29:35.986711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445970.307641467 3
 
2.7%
444797.921491577 2
 
1.8%
446322.714550678 2
 
1.8%
446781.847318935 2
 
1.8%
446606.364795612 1
 
0.9%
446328.212964956 1
 
0.9%
446868.965497642 1
 
0.9%
447015.142373045 1
 
0.9%
446037.779788579 1
 
0.9%
445041.625294905 1
 
0.9%
Other values (96) 96
86.5%
ValueCountFrequency (%)
442710.662421803 1
0.9%
442777.411153359 1
0.9%
442799.782649239 1
0.9%
442812.211045947 1
0.9%
443068.008897212 1
0.9%
443410.445545064 1
0.9%
443428.957251776 1
0.9%
443590.409601982 1
0.9%
443622.930580757 1
0.9%
443643.389854344 1
0.9%
ValueCountFrequency (%)
448656.726986041 1
0.9%
448534.504128423 1
0.9%
448479.826813757 1
0.9%
448247.571890076 1
0.9%
447979.869952928 1
0.9%
447750.192654125 1
0.9%
447700.474958924 1
0.9%
447646.154949604 1
0.9%
447538.877092648 1
0.9%
447452.686098735 1
0.9%

비상시설위치
Text

MISSING 

Distinct46
Distinct (%)100.0%
Missing65
Missing (%)58.6%
Memory size1020.0 B
2024-04-06T19:29:36.801636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length28.478261
Min length23

Characters and Unicode

Total characters1310
Distinct characters124
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 대림동 695 우성아파트
2nd row서울특별시 영등포구 여의도동 3 여의도역 지하층
3rd row서울특별시 영등포구 여의도동 5-6 샛강역 지하층
4th row서울특별시 영등포구 양평동5가 66-1 선유도역
5th row서울특별시 영등포구 신길동 4955 신길센트럴아이파크
ValueCountFrequency (%)
서울특별시 46
18.3%
영등포구 45
17.9%
신길동 20
 
8.0%
대림동 11
 
4.4%
여의도동 7
 
2.8%
지하층 3
 
1.2%
지하1층 3
 
1.2%
여의도역 2
 
0.8%
3 2
 
0.8%
양평동5가 2
 
0.8%
Other values (108) 110
43.8%
2024-04-06T19:29:37.525015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
205
 
15.6%
동 57
 
4.4%
포 50
 
3.8%
영 49
 
3.7%
등 49
 
3.7%
서 46
 
3.5%
특 46
 
3.5%
별 46
 
3.5%
시 46
 
3.5%
구 46
 
3.5%
Other values (114) 670
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 902
68.9%
Space Separator 205
 
15.6%
Decimal Number 180
 
13.7%
Dash Punctuation 23
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
 
6.3%
포 50
 
5.5%
영 49
 
5.4%
등 49
 
5.4%
서 46
 
5.1%
특 46
 
5.1%
별 46
 
5.1%
시 46
 
5.1%
구 46
 
5.1%
울 46
 
5.1%
Other values (102) 421
46.7%
Decimal Number
ValueCountFrequency (%)
1 35
19.4%
6 24
13.3%
4 23
12.8%
5 18
10.0%
7 17
9.4%
9 17
9.4%
3 15
8.3%
8 12
 
6.7%
0 10
 
5.6%
2 9
 
5.0%
Space Separator
ValueCountFrequency (%)
205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 901
68.8%
Common 408
31.1%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
 
6.3%
포 50
 
5.5%
영 49
 
5.4%
등 49
 
5.4%
서 46
 
5.1%
특 46
 
5.1%
별 46
 
5.1%
시 46
 
5.1%
구 46
 
5.1%
울 46
 
5.1%
Other values (101) 420
46.6%
Common
ValueCountFrequency (%)
205
50.2%
1 35
 
8.6%
6 24
 
5.9%
4 23
 
5.6%
- 23
 
5.6%
5 18
 
4.4%
7 17
 
4.2%
9 17
 
4.2%
3 15
 
3.7%
8 12
 
2.9%
Other values (2) 19
 
4.7%
Han
ValueCountFrequency (%)
新 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 901
68.8%
ASCII 408
31.1%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
205
50.2%
1 35
 
8.6%
6 24
 
5.9%
4 23
 
5.6%
- 23
 
5.6%
5 18
 
4.4%
7 17
 
4.2%
9 17
 
4.2%
3 15
 
3.7%
8 12
 
2.9%
Other values (2) 19
 
4.7%
Hangul
ValueCountFrequency (%)
동 57
 
6.3%
포 50
 
5.5%
영 49
 
5.4%
등 49
 
5.4%
서 46
 
5.1%
특 46
 
5.1%
별 46
 
5.1%
시 46
 
5.1%
구 46
 
5.1%
울 46
 
5.1%
Other values (101) 420
46.6%
CJK
ValueCountFrequency (%)
新 1
100.0%

시설구분명
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
65 
공공용시설
46 

Length

Max length5
Median length4
Mean length4.4144144
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 65
58.6%
공공용시설 46
41.4%

Length

2024-04-06T19:29:37.764883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:29:37.913422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
58.6%
공공용시설 46
41.4%

시설명_건물명
Text

MISSING 

Distinct46
Distinct (%)100.0%
Missing65
Missing (%)58.6%
Memory size1020.0 B
2024-04-06T19:29:38.251623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length15.26087
Min length6

Characters and Unicode

Total characters702
Distinct characters118
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row우성2차아파트 지하1층
2nd row9호선여의도역
3rd row9호선샛강역
4th row지하철9호선선유도역
5th row신길센트럴아이파크아파트 지하1~2층
ValueCountFrequency (%)
지하1층 19
 
17.0%
주차장 5
 
4.5%
지하1~2층 4
 
3.6%
1층 4
 
3.6%
양평2동 3
 
2.7%
아파트 3
 
2.7%
지하주차장 3
 
2.7%
지하1~3층 2
 
1.8%
신길1동 2
 
1.8%
지하 2
 
1.8%
Other values (63) 65
58.0%
2024-04-06T19:29:38.903773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
9.4%
지 54
 
7.7%
하 51
 
7.3%
층 43
 
6.1%
1 43
 
6.1%
아 28
 
4.0%
파 28
 
4.0%
트 27
 
3.8%
차 17
 
2.4%
2 15
 
2.1%
Other values (108) 330
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 529
75.4%
Decimal Number 77
 
11.0%
Space Separator 66
 
9.4%
Math Symbol 13
 
1.9%
Open Punctuation 8
 
1.1%
Close Punctuation 8
 
1.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 54
 
10.2%
하 51
 
9.6%
층 43
 
8.1%
아 28
 
5.3%
파 28
 
5.3%
트 27
 
5.1%
차 17
 
3.2%
신 14
 
2.6%
주 12
 
2.3%
선 11
 
2.1%
Other values (96) 244
46.1%
Decimal Number
ValueCountFrequency (%)
1 43
55.8%
2 15
 
19.5%
3 9
 
11.7%
9 4
 
5.2%
7 3
 
3.9%
5 2
 
2.6%
6 1
 
1.3%
Space Separator
ValueCountFrequency (%)
66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 529
75.4%
Common 173
 
24.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 54
 
10.2%
하 51
 
9.6%
층 43
 
8.1%
아 28
 
5.3%
파 28
 
5.3%
트 27
 
5.1%
차 17
 
3.2%
신 14
 
2.6%
주 12
 
2.3%
선 11
 
2.1%
Other values (96) 244
46.1%
Common
ValueCountFrequency (%)
66
38.2%
1 43
24.9%
2 15
 
8.7%
~ 13
 
7.5%
3 9
 
5.2%
( 8
 
4.6%
) 8
 
4.6%
9 4
 
2.3%
7 3
 
1.7%
5 2
 
1.2%
Other values (2) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 529
75.4%
ASCII 173
 
24.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
38.2%
1 43
24.9%
2 15
 
8.7%
~ 13
 
7.5%
3 9
 
5.2%
( 8
 
4.6%
) 8
 
4.6%
9 4
 
2.3%
7 3
 
1.7%
5 2
 
1.2%
Other values (2) 2
 
1.2%
Hangul
ValueCountFrequency (%)
지 54
 
10.2%
하 51
 
9.6%
층 43
 
8.1%
아 28
 
5.3%
파 28
 
5.3%
트 27
 
5.1%
차 17
 
3.2%
신 14
 
2.6%
주 12
 
2.3%
선 11
 
2.1%
Other values (96) 244
46.1%

해제일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031800003180000-S2021000032021-08-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>68748.95<NA>서울특별시 영등포구 신길동 4969 힐스테이트 클래시안서울특별시 영등포구 신길로28길 9(신길동, 힐스테이트 클래시안)7388신길동 힐스테이트클래시안 아파트 지하주차장 B2~B4층2024-01-22 13:37:48U2023-11-30 22:04:00.0<NA>192143.319862444660.996604<NA><NA><NA><NA>
131800003180000-S2003000822003-05-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>667.0<NA>서울특별시 영등포구 대림동 993-75서울특별시 영등포구 시흥대로 613(대림동)7445안국약품빌딩 지하1층 주차장2023-09-12 15:04:21U2022-12-08 23:04:00.0<NA>191486.816475442812.211046<NA><NA><NA><NA>
231800003180000-S2013000062013-05-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>737.84<NA>서울특별시 영등포구 당산동3가 560 영등포구 별관청사서울특별시 영등포구 선유동1로 80, 영등포구 별관청사 (당산동3가)7256영등포구청별관 지하1층2024-02-22 10:17:11U2023-12-01 22:04:00.0<NA>190591.14769447361.752018<NA><NA><NA><NA>
331800003180000-S2009000012009-02-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6183.66<NA>서울특별시 영등포구 당산동3가 385번지서울특별시 영등포구 당산로27길 12 (당산동3가)7260당산근린공원 지하1~2층 주차장2024-02-22 10:15:02U2023-12-01 22:04:00.0<NA>190716.718576447035.571697<NA><NA><NA><NA>
431800003180000-S2003000332003-05-19<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>7414.91<NA>서울특별시 영등포구 당산동3가 270-1 영등포구청역서울특별시 영등포구 당산로 지하121, 영등포구청역 (당산동3가)7260지하철 2호선 영등포구청역 지하1~2층 역사2024-02-22 10:12:45U2023-12-01 22:04:00.0<NA>190813.392542447019.435119<NA><NA><NA><NA>
531800003180000-S2019000012019-01-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1800.0<NA>서울특별시 영등포구 대림동 695 우성아파트서울특별시 영등포구 도림로47길 1(대림동, 우성아파트)7410우성2차아파트 지하1층2023-06-16 13:25:58U2023-06-18 02:40:00.0<NA>191088.099791443718.459773서울특별시 영등포구 대림동 695 우성아파트공공용시설우성2차아파트 지하1층<NA>
631800003180000-S2003000012003-05-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>552.64<NA>서울특별시 영등포구 당산동3가 385-1 영등포구청서울특별시 영등포구 당산로 123, 영등포구청 (당산동3가)7260영등포구청 지하2~3층2024-02-22 10:11:30U2023-12-01 22:04:00.0<NA>190733.030903447118.969319<NA><NA><NA><NA>
731800003180000-S2003000762003-05-262023-11-234취소/말소/만료/정지/중지19사용중지2023-11-23<NA><NA><NA><NA>297.0<NA>서울특별시 영등포구 신길동 1351-3 천록빌딩서울특별시 영등포구 여의대방로61길 2, 천록빌딩 (신길동)7319천록빌딩 지하1층2023-11-23 22:15:31U2022-10-31 22:05:00.0<NA>193389.462377445790.101524<NA><NA><NA><NA>
831800003180000-S2003000712003-05-262023-11-234취소/말소/만료/정지/중지19사용중지2023-11-23<NA><NA><NA><NA>705.0<NA>서울특별시 영등포구 신길동 1300서울특별시 영등포구 영등포로 422(신길동)7354정오빌딩 지하1층2023-11-23 22:14:54U2022-10-31 22:05:00.0<NA>193281.875202445570.814215<NA><NA><NA><NA>
931800003180000-S2009000222009-09-17<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9370.0<NA>서울특별시 영등포구 여의도동 3 여의도역 지하층서울특별시 영등포구 여의나루로 지하40, 여의도역 지하1층 (여의도동)73279호선여의도역2023-03-29 17:27:25U2023-03-31 02:40:00.0<NA>193471.519358446781.847319서울특별시 영등포구 여의도동 3 여의도역 지하층공공용시설9호선여의도역<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
10131800003180000-S2023000062023-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4217.0<NA>서울특별시 영등포구 문래동6가 10 GS강서타워서울특별시 영등포구 선유로 75, GS강서타워 (문래동6가)7280지에스강서타워 지하 1~2층2024-01-24 13:37:57U2023-11-30 22:06:00.0<NA>190119.734955446513.394643<NA><NA><NA><NA>
10231800003180000-S2003000432003-05-202023-08-284취소/말소/만료/정지/중지19사용중지2023-08-28<NA><NA><NA><NA>4310.76<NA>서울특별시 영등포구 문래동3가 73 시립문래청소년센터서울특별시 영등포구 문래로 110, 시립문래청소년센터 (문래동3가)7296문래청소년회관 지하1층2023-08-28 17:36:39U2022-12-07 21:00:00.0<NA>190562.176987446302.898506<NA><NA><NA><NA>
10331800003180000-S2003000872003-05-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1230.84<NA>서울특별시 영등포구 대림동 762-1 우성아파트서울특별시 영등포구 도림로 187(대림동, 우성아파트)7410우성아파트 1동, 2동 지하1층2023-08-31 17:19:22U2022-12-09 00:02:00.0<NA>191166.735605443801.507863<NA><NA><NA><NA>
10431800003180000-S2003000612003-05-21<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4850.0<NA>서울특별시 영등포구 신길동 4933 신길우성5차아파트서울특별시 영등포구 도신로 100(신길동, 신길우성5차아파트)7382우성5차아파트 지하1층2023-11-01 15:22:27U2022-11-01 00:03:00.0<NA>191400.331095444951.568358<NA><NA><NA><NA>
10531800003180000-S2023000072023-09-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2532.0<NA>서울특별시 영등포구 양평동1가 5-1 GS강서N타워서울특별시 영등포구 선유로 82, GS강서N타워 지하2층 (양평동1가)7291GS강서N타워(지하주차장 2층)2024-01-29 10:15:38U2023-11-30 21:01:00.0<NA>190236.12357446564.317727<NA><NA><NA><NA>
10631800003180000-S2009000262009-12-09<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>15905.0<NA>서울특별시 영등포구 영등포동8가 91 당산 푸르지오서울특별시 영등포구 영중로 154(영등포동8가, 당산 푸르지오)7226당산푸르지오아파트 지하 1층 주차장2024-01-25 17:01:55U2023-11-30 22:07:00.0<NA>191651.788886447538.877093<NA><NA><NA><NA>
10731800003180000-S2003000042003-05-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1402.44<NA>서울특별시 영등포구 영등포동3가 31 영등포시장지하도상가서울특별시 영등포구 영등포로 지하221, 영등포시장지하도상가 (영등포동3가)7250영등포시장 지하쇼핑센터 지하 1층2024-01-25 17:00:45U2023-11-30 22:07:00.0<NA>191614.686144446322.714551<NA><NA><NA><NA>
10831800003180000-S2003000052003-05-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1979.49<NA>서울특별시 영등포구 영등포동3가 32 영등포로터리지하도상가서울특별시 영등포구 영중로 지하20, 영등포로터리지하도상가 (영등포동3가)7302영등포로터리 지하쇼핑센터 지하 1층2024-01-25 16:59:51U2023-11-30 22:07:00.0<NA>191628.171471446158.036795<NA><NA><NA><NA>
10931800003180000-S2003000082003-05-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5448.0<NA>서울특별시 영등포구 영등포동5가 62-1 영등포시장역서울특별시 영등포구 양산로 지하200, 영등포시장역 (영등포동5가)7250지하철 5호선 영등포시장역 지하 1~3층2024-01-25 16:45:56U2023-11-30 22:07:00.0<NA>191592.536217446670.024333<NA><NA><NA><NA>
11031800003180000-S2003000072003-05-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>7476.0<NA>서울특별시 영등포구 영등포동1가 35번지서울특별시 영등포구 경인로114가길 지하 9 (영등포동1가, 신길역)7308지하철 5호선 신길역 지하 1~2층2024-01-25 17:01:03U2023-11-30 22:07:00.0<NA>192372.484394446168.373274<NA><NA><NA><NA>