Overview

Dataset statistics

Number of variables29
Number of observations69
Missing cells667
Missing cells (%)33.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory246.9 B

Variable types

Categorical7
Text7
DateTime5
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-20044/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신구분 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
인허가취소일자 has 67 (97.1%) missing valuesMissing
폐업일자 has 67 (97.1%) missing valuesMissing
휴업시작일자 has 69 (100.0%) missing valuesMissing
휴업종료일자 has 69 (100.0%) missing valuesMissing
재개업일자 has 69 (100.0%) missing valuesMissing
전화번호 has 69 (100.0%) missing valuesMissing
소재지우편번호 has 69 (100.0%) missing valuesMissing
업태구분명 has 69 (100.0%) missing valuesMissing
비상시설위치 has 25 (36.2%) missing valuesMissing
시설명_건물명 has 25 (36.2%) missing valuesMissing
해제일자 has 69 (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 07:01:22.362196
Analysis finished2024-05-11 07:01:23.159211
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
3170000
69 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 69
100.0%

Length

2024-05-11T16:01:23.614932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:23.786438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 69
100.0%

관리번호
Text

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T16:01:24.080869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1242
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

Unique69 ?
Unique (%)100.0%

Sample

1st row3170000-S200900015
2nd row3170000-S201400001
3rd row3170000-S201100010
4th row3170000-S201100005
5th row3170000-S200500022
ValueCountFrequency (%)
3170000-s200900015 1
 
1.4%
3170000-s200500021 1
 
1.4%
3170000-s202300001 1
 
1.4%
3170000-s200900013 1
 
1.4%
3170000-s201200001 1
 
1.4%
3170000-s201200002 1
 
1.4%
3170000-s202400001 1
 
1.4%
3170000-s200900012 1
 
1.4%
3170000-s200900007 1
 
1.4%
3170000-s200900008 1
 
1.4%
Other values (59) 59
85.5%
2024-05-11T16:01:24.694465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 615
49.5%
1 162
 
13.0%
2 83
 
6.7%
3 82
 
6.6%
7 75
 
6.0%
- 69
 
5.6%
S 69
 
5.6%
9 37
 
3.0%
5 23
 
1.9%
8 10
 
0.8%
Other values (2) 17
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1104
88.9%
Dash Punctuation 69
 
5.6%
Uppercase Letter 69
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 615
55.7%
1 162
 
14.7%
2 83
 
7.5%
3 82
 
7.4%
7 75
 
6.8%
9 37
 
3.4%
5 23
 
2.1%
8 10
 
0.9%
4 10
 
0.9%
6 7
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1173
94.4%
Latin 69
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 615
52.4%
1 162
 
13.8%
2 83
 
7.1%
3 82
 
7.0%
7 75
 
6.4%
- 69
 
5.9%
9 37
 
3.2%
5 23
 
2.0%
8 10
 
0.9%
4 10
 
0.9%
Latin
ValueCountFrequency (%)
S 69
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 615
49.5%
1 162
 
13.0%
2 83
 
6.7%
3 82
 
6.6%
7 75
 
6.0%
- 69
 
5.6%
S 69
 
5.6%
9 37
 
3.0%
5 23
 
1.9%
8 10
 
0.8%
Other values (2) 17
 
1.4%

인허가일자
Date

Distinct39
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum1990-01-08 00:00:00
Maximum2024-01-26 00:00:00
2024-05-11T16:01:25.060817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:25.276870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

인허가취소일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing67
Missing (%)97.1%
Memory size684.0 B
Minimum2023-07-27 00:00:00
Maximum2023-09-14 00:00:00
2024-05-11T16:01:25.435747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:25.561898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
1
67 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 67
97.1%
4 2
 
2.9%

Length

2024-05-11T16:01:25.747366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:25.924779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 67
97.1%
4 2
 
2.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
영업/정상
67 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length5.2608696
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 67
97.1%
취소/말소/만료/정지/중지 2
 
2.9%

Length

2024-05-11T16:01:26.114808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:26.296774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 67
97.1%
취소/말소/만료/정지/중지 2
 
2.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
18
67 
19
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
18 67
97.1%
19 2
 
2.9%

Length

2024-05-11T16:01:26.489659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:26.651248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 67
97.1%
19 2
 
2.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
사용중
67 
사용중지
 
2

Length

Max length4
Median length3
Mean length3.0289855
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 67
97.1%
사용중지 2
 
2.9%

Length

2024-05-11T16:01:26.829068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:27.008898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 67
97.1%
사용중지 2
 
2.9%

폐업일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing67
Missing (%)97.1%
Memory size684.0 B
Minimum2023-07-27 00:00:00
Maximum2023-09-14 00:00:00
2024-05-11T16:01:27.194335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:27.365694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

소재지면적
Real number (ℝ)

Distinct68
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7274.7293
Minimum194
Maximum71638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T16:01:27.545418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194
5-th percentile331.2
Q1630.87
median2133
Q35554
95-th percentile30847.6
Maximum71638
Range71444
Interquartile range (IQR)4923.13

Descriptive statistics

Standard deviation12896.67
Coefficient of variation (CV)1.7728042
Kurtosis11.135095
Mean7274.7293
Median Absolute Deviation (MAD)1684
Skewness3.1101585
Sum501956.32
Variance1.6632411 × 108
MonotonicityNot monotonic
2024-05-11T16:01:27.777749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 2
 
2.9%
2944.0 1
 
1.4%
32934.0 1
 
1.4%
3552.0 1
 
1.4%
1446.71 1
 
1.4%
2209.0 1
 
1.4%
350.0 1
 
1.4%
1451.0 1
 
1.4%
918.0 1
 
1.4%
2989.0 1
 
1.4%
Other values (58) 58
84.1%
ValueCountFrequency (%)
194.0 1
1.4%
286.0 1
1.4%
330.0 2
2.9%
333.0 1
1.4%
350.0 1
1.4%
362.0 1
1.4%
363.0 1
1.4%
396.0 1
1.4%
412.0 1
1.4%
449.0 1
1.4%
ValueCountFrequency (%)
71638.0 1
1.4%
56311.0 1
1.4%
36620.0 1
1.4%
32934.0 1
1.4%
27718.0 1
1.4%
24631.0 1
1.4%
21291.0 1
1.4%
20988.0 1
1.4%
20816.0 1
1.4%
18665.0 1
1.4%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

지번주소
Text

Distinct67
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T16:01:28.223512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length22
Min length18

Characters and Unicode

Total characters1518
Distinct characters60
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

Unique65 ?
Unique (%)94.2%

Sample

1st row서울특별시 금천구 시흥동 268번지 46호
2nd row서울특별시 금천구 시흥동 1026번지
3rd row서울특별시 금천구 독산동 1028번지
4th row서울특별시 금천구 독산동 1139번지
5th row서울특별시 금천구 시흥동 220번지 2호
ValueCountFrequency (%)
서울특별시 69
21.5%
금천구 69
21.5%
시흥동 34
 
10.6%
독산동 31
 
9.7%
4호 6
 
1.9%
2호 5
 
1.6%
가산동 4
 
1.2%
1호 4
 
1.2%
1066번지 2
 
0.6%
13호 2
 
0.6%
Other values (88) 95
29.6%
2024-05-11T16:01:28.870452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
16.6%
시 103
 
6.8%
금 71
 
4.7%
천 71
 
4.7%
구 70
 
4.6%
1 70
 
4.6%
서 69
 
4.5%
특 69
 
4.5%
별 69
 
4.5%
울 69
 
4.5%
Other values (50) 605
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 970
63.9%
Decimal Number 291
 
19.2%
Space Separator 252
 
16.6%
Dash Punctuation 3
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 103
10.6%
금 71
 
7.3%
천 71
 
7.3%
구 70
 
7.2%
서 69
 
7.1%
특 69
 
7.1%
별 69
 
7.1%
울 69
 
7.1%
동 69
 
7.1%
번 61
 
6.3%
Other values (36) 249
25.7%
Decimal Number
ValueCountFrequency (%)
1 70
24.1%
9 35
12.0%
0 33
11.3%
3 32
11.0%
2 27
 
9.3%
8 26
 
8.9%
4 22
 
7.6%
6 22
 
7.6%
7 14
 
4.8%
5 10
 
3.4%
Space Separator
ValueCountFrequency (%)
252
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 970
63.9%
Common 548
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 103
10.6%
금 71
 
7.3%
천 71
 
7.3%
구 70
 
7.2%
서 69
 
7.1%
특 69
 
7.1%
별 69
 
7.1%
울 69
 
7.1%
동 69
 
7.1%
번 61
 
6.3%
Other values (36) 249
25.7%
Common
ValueCountFrequency (%)
252
46.0%
1 70
 
12.8%
9 35
 
6.4%
0 33
 
6.0%
3 32
 
5.8%
2 27
 
4.9%
8 26
 
4.7%
4 22
 
4.0%
6 22
 
4.0%
7 14
 
2.6%
Other values (4) 15
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 970
63.9%
ASCII 548
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
46.0%
1 70
 
12.8%
9 35
 
6.4%
0 33
 
6.0%
3 32
 
5.8%
2 27
 
4.9%
8 26
 
4.7%
4 22
 
4.0%
6 22
 
4.0%
7 14
 
2.6%
Other values (4) 15
 
2.7%
Hangul
ValueCountFrequency (%)
시 103
10.6%
금 71
 
7.3%
천 71
 
7.3%
구 70
 
7.2%
서 69
 
7.1%
특 69
 
7.1%
별 69
 
7.1%
울 69
 
7.1%
동 69
 
7.1%
번 61
 
6.3%
Other values (36) 249
25.7%

도로명주소
Text

Distinct67
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T16:01:29.311192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length31.15942
Min length23

Characters and Unicode

Total characters2150
Distinct characters161
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

Unique65 ?
Unique (%)94.2%

Sample

1st row서울특별시 금천구 금하로30길 34 (시흥동, 탑스빌아파트)
2nd row서울특별시 금천구 시흥대로 165 (시흥동)
3rd row서울특별시 금천구 시흥대로112길 6 (독산동, 대덕트윈빌)
4th row서울특별시 금천구 두산로11길 22 (독산동, 청광플러스원아파트)
5th row서울특별시 금천구 탑골로3길 50 (시흥동)
ValueCountFrequency (%)
서울특별시 69
17.2%
금천구 69
17.2%
시흥동 34
 
8.5%
독산동 31
 
7.8%
시흥대로 14
 
3.5%
금하로 9
 
2.2%
가산동 4
 
1.0%
독산로78다길 3
 
0.8%
독산로 3
 
0.8%
22 3
 
0.8%
Other values (147) 161
40.2%
2024-05-11T16:01:29.966245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
331
 
15.4%
시 135
 
6.3%
금 89
 
4.1%
동 74
 
3.4%
천 73
 
3.4%
( 70
 
3.3%
구 70
 
3.3%
) 70
 
3.3%
서 69
 
3.2%
특 69
 
3.2%
Other values (151) 1100
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1384
64.4%
Space Separator 331
 
15.4%
Decimal Number 238
 
11.1%
Open Punctuation 70
 
3.3%
Close Punctuation 70
 
3.3%
Other Punctuation 55
 
2.6%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 135
 
9.8%
금 89
 
6.4%
동 74
 
5.3%
천 73
 
5.3%
구 70
 
5.1%
서 69
 
5.0%
특 69
 
5.0%
별 69
 
5.0%
울 69
 
5.0%
로 69
 
5.0%
Other values (136) 598
43.2%
Decimal Number
ValueCountFrequency (%)
1 36
15.1%
2 34
14.3%
5 28
11.8%
3 26
10.9%
6 23
9.7%
7 22
9.2%
4 19
8.0%
8 19
8.0%
0 16
6.7%
9 15
6.3%
Space Separator
ValueCountFrequency (%)
331
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1384
64.4%
Common 766
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 135
 
9.8%
금 89
 
6.4%
동 74
 
5.3%
천 73
 
5.3%
구 70
 
5.1%
서 69
 
5.0%
특 69
 
5.0%
별 69
 
5.0%
울 69
 
5.0%
로 69
 
5.0%
Other values (136) 598
43.2%
Common
ValueCountFrequency (%)
331
43.2%
( 70
 
9.1%
) 70
 
9.1%
, 55
 
7.2%
1 36
 
4.7%
2 34
 
4.4%
5 28
 
3.7%
3 26
 
3.4%
6 23
 
3.0%
7 22
 
2.9%
Other values (5) 71
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1384
64.4%
ASCII 766
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
43.2%
( 70
 
9.1%
) 70
 
9.1%
, 55
 
7.2%
1 36
 
4.7%
2 34
 
4.4%
5 28
 
3.7%
3 26
 
3.4%
6 23
 
3.0%
7 22
 
2.9%
Other values (5) 71
 
9.3%
Hangul
ValueCountFrequency (%)
시 135
 
9.8%
금 89
 
6.4%
동 74
 
5.3%
천 73
 
5.3%
구 70
 
5.1%
서 69
 
5.0%
특 69
 
5.0%
별 69
 
5.0%
울 69
 
5.0%
로 69
 
5.0%
Other values (136) 598
43.2%

도로명우편번호
Text

Distinct53
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T16:01:30.310027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.5217391
Min length4

Characters and Unicode

Total characters312
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

Unique38 ?
Unique (%)55.1%

Sample

1st row08645
2nd row153-031
3rd row08580
4th row8524
5th row153-860
ValueCountFrequency (%)
08645 3
 
4.3%
8652 2
 
2.9%
8536 2
 
2.9%
08556 2
 
2.9%
08655 2
 
2.9%
08646 2
 
2.9%
8607 2
 
2.9%
153-031 2
 
2.9%
08647 2
 
2.9%
8623 2
 
2.9%
Other values (43) 48
69.6%
2024-05-11T16:01:30.800751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 75
24.0%
5 58
18.6%
6 46
14.7%
0 40
12.8%
3 22
 
7.1%
1 18
 
5.8%
4 17
 
5.4%
2 12
 
3.8%
9 10
 
3.2%
7 10
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 308
98.7%
Dash Punctuation 4
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 75
24.4%
5 58
18.8%
6 46
14.9%
0 40
13.0%
3 22
 
7.1%
1 18
 
5.8%
4 17
 
5.5%
2 12
 
3.9%
9 10
 
3.2%
7 10
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 75
24.0%
5 58
18.6%
6 46
14.7%
0 40
12.8%
3 22
 
7.1%
1 18
 
5.8%
4 17
 
5.4%
2 12
 
3.8%
9 10
 
3.2%
7 10
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 75
24.0%
5 58
18.6%
6 46
14.7%
0 40
12.8%
3 22
 
7.1%
1 18
 
5.8%
4 17
 
5.4%
2 12
 
3.8%
9 10
 
3.2%
7 10
 
3.2%

사업장명
Text

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T16:01:31.110167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length15.84058
Min length9

Characters and Unicode

Total characters1093
Distinct characters173
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

Unique69 ?
Unique (%)100.0%

Sample

1st row탑스빌 아파트 지하1층
2nd row남서울힐스테이트아파트 1단지 지하1~2층
3rd row대덕트윈빌 101동 지하주차장 1~2층
4th row청광플러스원아파트 지하주차장 지하1층
5th row구현대아파트 지하1층
ValueCountFrequency (%)
지하1층 34
 
18.4%
지하주차장 20
 
10.8%
101동 6
 
3.2%
아파트 4
 
2.2%
지하1~3층 4
 
2.2%
지하1~2층 4
 
2.2%
2층 3
 
1.6%
3
 
1.6%
1층 3
 
1.6%
주차장 2
 
1.1%
Other values (97) 102
55.1%
2024-05-11T16:01:31.599894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
10.6%
지 92
 
8.4%
1 90
 
8.2%
하 79
 
7.2%
층 68
 
6.2%
트 43
 
3.9%
아 41
 
3.8%
파 40
 
3.7%
장 25
 
2.3%
주 24
 
2.2%
Other values (163) 475
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 777
71.1%
Decimal Number 149
 
13.6%
Space Separator 116
 
10.6%
Math Symbol 21
 
1.9%
Close Punctuation 11
 
1.0%
Open Punctuation 11
 
1.0%
Other Punctuation 6
 
0.5%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 92
 
11.8%
하 79
 
10.2%
층 68
 
8.8%
트 43
 
5.5%
아 41
 
5.3%
파 40
 
5.1%
장 25
 
3.2%
주 24
 
3.1%
차 24
 
3.1%
동 22
 
2.8%
Other values (146) 319
41.1%
Decimal Number
ValueCountFrequency (%)
1 90
60.4%
2 20
 
13.4%
0 17
 
11.4%
3 11
 
7.4%
4 3
 
2.0%
5 3
 
2.0%
6 2
 
1.3%
9 1
 
0.7%
8 1
 
0.7%
7 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
116
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 777
71.1%
Common 314
28.7%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 92
 
11.8%
하 79
 
10.2%
층 68
 
8.8%
트 43
 
5.5%
아 41
 
5.3%
파 40
 
5.1%
장 25
 
3.2%
주 24
 
3.1%
차 24
 
3.1%
동 22
 
2.8%
Other values (146) 319
41.1%
Common
ValueCountFrequency (%)
116
36.9%
1 90
28.7%
~ 21
 
6.7%
2 20
 
6.4%
0 17
 
5.4%
) 11
 
3.5%
( 11
 
3.5%
3 11
 
3.5%
, 6
 
1.9%
4 3
 
1.0%
Other values (5) 8
 
2.5%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 777
71.1%
ASCII 316
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
36.7%
1 90
28.5%
~ 21
 
6.6%
2 20
 
6.3%
0 17
 
5.4%
) 11
 
3.5%
( 11
 
3.5%
3 11
 
3.5%
, 6
 
1.9%
4 3
 
0.9%
Other values (7) 10
 
3.2%
Hangul
ValueCountFrequency (%)
지 92
 
11.8%
하 79
 
10.2%
층 68
 
8.8%
트 43
 
5.5%
아 41
 
5.3%
파 40
 
5.1%
장 25
 
3.2%
주 24
 
3.1%
차 24
 
3.1%
동 22
 
2.8%
Other values (146) 319
41.1%

최종수정일자
Date

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2023-04-10 10:34:23
Maximum2024-01-31 08:08:27
2024-05-11T16:01:31.891703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:32.132245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
U
69 

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 69
100.0%

Length

2024-05-11T16:01:32.356415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:32.521043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 69
100.0%

데이터갱신일자
Date

Distinct13
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2022-10-30 22:06:00
Maximum2023-12-02 00:02:00
2024-05-11T16:01:32.625657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:32.778393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

좌표정보(X)
Real number (ℝ)

Distinct66
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191315.09
Minimum189514.73
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T16:01:32.968097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189514.73
5-th percentile190369.67
Q1190879.92
median191226.29
Q3191713.55
95-th percentile192524.94
Maximum192754.35
Range3239.6162
Interquartile range (IQR)833.63743

Descriptive statistics

Standard deviation678.64732
Coefficient of variation (CV)0.0035472755
Kurtosis-0.039918146
Mean191315.09
Median Absolute Deviation (MAD)444.07507
Skewness0.13228541
Sum13200741
Variance460562.18
MonotonicityNot monotonic
2024-05-11T16:01:33.193320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192754.34619252 2
 
2.9%
191004.699476472 2
 
2.9%
191190.614295546 2
 
2.9%
190735.437651179 1
 
1.4%
191823.026849977 1
 
1.4%
191492.24806341 1
 
1.4%
191002.911243202 1
 
1.4%
191674.753605156 1
 
1.4%
191261.43301181 1
 
1.4%
191107.710302267 1
 
1.4%
Other values (56) 56
81.2%
ValueCountFrequency (%)
189514.72996753 1
1.4%
190023.426907798 1
1.4%
190232.47138241 1
1.4%
190352.36451174 1
1.4%
190395.636689928 1
1.4%
190399.10207033 1
1.4%
190464.852860798 1
1.4%
190469.82773312 1
1.4%
190565.170337192 1
1.4%
190641.951025262 1
1.4%
ValueCountFrequency (%)
192754.34619252 2
2.9%
192742.326147617 1
1.4%
192554.656815107 1
1.4%
192480.368331844 1
1.4%
192365.151762912 1
1.4%
192313.512604628 1
1.4%
192297.91598261 1
1.4%
192051.219347087 1
1.4%
192027.596002409 1
1.4%
192024.601513857 1
1.4%

좌표정보(Y)
Real number (ℝ)

Distinct66
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean439808.49
Minimum437680.11
Maximum442253.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T16:01:33.422971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437680.11
5-th percentile438346.43
Q1438827.14
median439863.9
Q3440728.38
95-th percentile441625.1
Maximum442253.57
Range4573.4544
Interquartile range (IQR)1901.2385

Descriptive statistics

Standard deviation1138.8002
Coefficient of variation (CV)0.0025893093
Kurtosis-1.004782
Mean439808.49
Median Absolute Deviation (MAD)1003.8346
Skewness0.12704042
Sum30346786
Variance1296866
MonotonicityNot monotonic
2024-05-11T16:01:33.647211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
438827.143732711 2
 
2.9%
440576.060451649 2
 
2.9%
438410.522111193 2
 
2.9%
441619.623664517 1
 
1.4%
438834.378061101 1
 
1.4%
438767.071314515 1
 
1.4%
439772.050942544 1
 
1.4%
440382.586544955 1
 
1.4%
440475.567477615 1
 
1.4%
439893.760903697 1
 
1.4%
Other values (56) 56
81.2%
ValueCountFrequency (%)
437680.1128998 1
1.4%
437795.951394135 1
1.4%
437914.06299827 1
1.4%
438303.705016298 1
1.4%
438410.522111193 2
2.9%
438423.909374917 1
1.4%
438436.109390506 1
1.4%
438458.097193512 1
1.4%
438460.667319682 1
1.4%
438525.414482503 1
1.4%
ValueCountFrequency (%)
442253.567254569 1
1.4%
441773.697708438 1
1.4%
441658.029270556 1
1.4%
441628.746231551 1
1.4%
441619.623664517 1
1.4%
441558.884070546 1
1.4%
441545.208758244 1
1.4%
441227.949108174 1
1.4%
441198.666922659 1
1.4%
441196.233806636 1
1.4%

비상시설위치
Text

MISSING 

Distinct43
Distinct (%)97.7%
Missing25
Missing (%)36.2%
Memory size684.0 B
2024-05-11T16:01:34.020509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length22.090909
Min length18

Characters and Unicode

Total characters972
Distinct characters55
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

Unique42 ?
Unique (%)95.5%

Sample

1st row서울특별시 금천구 시흥동 1026번지
2nd row서울특별시 금천구 독산동 1139번지
3rd row서울특별시 금천구 시흥동 1026번지
4th row서울특별시 금천구 독산동 983번지 16호
5th row서울특별시 금천구 시흥동 870번지 27호
ValueCountFrequency (%)
서울특별시 44
21.6%
금천구 44
21.6%
독산동 24
11.8%
시흥동 20
 
9.8%
2호 3
 
1.5%
4호 3
 
1.5%
293번지 2
 
1.0%
1066번지 2
 
1.0%
13호 2
 
1.0%
983번지 2
 
1.0%
Other values (57) 58
28.4%
2024-05-11T16:01:34.707262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
16.5%
시 64
 
6.6%
천 46
 
4.7%
금 46
 
4.7%
구 45
 
4.6%
동 44
 
4.5%
울 44
 
4.5%
서 44
 
4.5%
별 44
 
4.5%
특 44
 
4.5%
Other values (45) 391
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 622
64.0%
Decimal Number 186
 
19.1%
Space Separator 160
 
16.5%
Dash Punctuation 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 64
 
10.3%
천 46
 
7.4%
금 46
 
7.4%
구 45
 
7.2%
동 44
 
7.1%
울 44
 
7.1%
서 44
 
7.1%
별 44
 
7.1%
특 44
 
7.1%
번 38
 
6.1%
Other values (31) 163
26.2%
Decimal Number
ValueCountFrequency (%)
1 43
23.1%
9 27
14.5%
3 21
11.3%
0 19
10.2%
8 17
 
9.1%
6 14
 
7.5%
2 13
 
7.0%
4 12
 
6.5%
5 10
 
5.4%
7 10
 
5.4%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 622
64.0%
Common 350
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 64
 
10.3%
천 46
 
7.4%
금 46
 
7.4%
구 45
 
7.2%
동 44
 
7.1%
울 44
 
7.1%
서 44
 
7.1%
별 44
 
7.1%
특 44
 
7.1%
번 38
 
6.1%
Other values (31) 163
26.2%
Common
ValueCountFrequency (%)
160
45.7%
1 43
 
12.3%
9 27
 
7.7%
3 21
 
6.0%
0 19
 
5.4%
8 17
 
4.9%
6 14
 
4.0%
2 13
 
3.7%
4 12
 
3.4%
5 10
 
2.9%
Other values (4) 14
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 622
64.0%
ASCII 350
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
45.7%
1 43
 
12.3%
9 27
 
7.7%
3 21
 
6.0%
0 19
 
5.4%
8 17
 
4.9%
6 14
 
4.0%
2 13
 
3.7%
4 12
 
3.4%
5 10
 
2.9%
Other values (4) 14
 
4.0%
Hangul
ValueCountFrequency (%)
시 64
 
10.3%
천 46
 
7.4%
금 46
 
7.4%
구 45
 
7.2%
동 44
 
7.1%
울 44
 
7.1%
서 44
 
7.1%
별 44
 
7.1%
특 44
 
7.1%
번 38
 
6.1%
Other values (31) 163
26.2%

시설구분명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
공공용시설
44 
<NA>
25 

Length

Max length5
Median length5
Mean length4.6376812
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용시설 44
63.8%
<NA> 25
36.2%

Length

2024-05-11T16:01:34.926188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:35.076195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용시설 44
63.8%
na 25
36.2%

시설명_건물명
Text

MISSING 

Distinct44
Distinct (%)100.0%
Missing25
Missing (%)36.2%
Memory size684.0 B
2024-05-11T16:01:35.334876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length15.886364
Min length9

Characters and Unicode

Total characters699
Distinct characters142
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

Unique44 ?
Unique (%)100.0%

Sample

1st row남서울힐스테이트아파트 1단지 지하1~2층
2nd row청광플러스원아파트 지하주차장 지하1층
3rd row남서울힐스테이트아파트 2단지 지하1~2층
4th row신한은행 독산동지점 지하1층
5th row시흥중앙교회 지하1층
ValueCountFrequency (%)
지하1층 26
22.2%
지하주차장 5
 
4.3%
101동 5
 
4.3%
지하1~2층 4
 
3.4%
3
 
2.6%
남서울힐스테이트아파트 2
 
1.7%
아파트 2
 
1.7%
지하1~3층 2
 
1.7%
주차장 2
 
1.7%
삼익아파트 2
 
1.7%
Other values (64) 64
54.7%
2024-05-11T16:01:35.863346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
10.4%
1 67
 
9.6%
지 54
 
7.7%
하 48
 
6.9%
층 42
 
6.0%
트 26
 
3.7%
파 25
 
3.6%
아 23
 
3.3%
동 17
 
2.4%
~ 15
 
2.1%
Other values (132) 309
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
69.1%
Decimal Number 106
 
15.2%
Space Separator 73
 
10.4%
Math Symbol 15
 
2.1%
Close Punctuation 8
 
1.1%
Open Punctuation 8
 
1.1%
Other Punctuation 4
 
0.6%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 54
 
11.2%
하 48
 
9.9%
층 42
 
8.7%
트 26
 
5.4%
파 25
 
5.2%
아 23
 
4.8%
동 17
 
3.5%
장 10
 
2.1%
빌 10
 
2.1%
스 9
 
1.9%
Other values (115) 219
45.3%
Decimal Number
ValueCountFrequency (%)
1 67
63.2%
0 15
 
14.2%
2 9
 
8.5%
3 7
 
6.6%
5 2
 
1.9%
4 2
 
1.9%
9 1
 
0.9%
8 1
 
0.9%
7 1
 
0.9%
6 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
73
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
69.1%
Common 214
30.6%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 54
 
11.2%
하 48
 
9.9%
층 42
 
8.7%
트 26
 
5.4%
파 25
 
5.2%
아 23
 
4.8%
동 17
 
3.5%
장 10
 
2.1%
빌 10
 
2.1%
스 9
 
1.9%
Other values (115) 219
45.3%
Common
ValueCountFrequency (%)
73
34.1%
1 67
31.3%
~ 15
 
7.0%
0 15
 
7.0%
2 9
 
4.2%
) 8
 
3.7%
( 8
 
3.7%
3 7
 
3.3%
, 4
 
1.9%
5 2
 
0.9%
Other values (5) 6
 
2.8%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
69.1%
ASCII 216
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
33.8%
1 67
31.0%
~ 15
 
6.9%
0 15
 
6.9%
2 9
 
4.2%
) 8
 
3.7%
( 8
 
3.7%
3 7
 
3.2%
, 4
 
1.9%
5 2
 
0.9%
Other values (7) 8
 
3.7%
Hangul
ValueCountFrequency (%)
지 54
 
11.2%
하 48
 
9.9%
층 42
 
8.7%
트 26
 
5.4%
파 25
 
5.2%
아 23
 
4.8%
동 17
 
3.5%
장 10
 
2.1%
빌 10
 
2.1%
스 9
 
1.9%
Other values (115) 219
45.3%

해제일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031700003170000-S2009000152009-11-202023-09-144취소/말소/만료/정지/중지19사용중지2023-09-14<NA><NA><NA><NA>2944.0<NA>서울특별시 금천구 시흥동 268번지 46호서울특별시 금천구 금하로30길 34 (시흥동, 탑스빌아파트)08645탑스빌 아파트 지하1층2023-09-14 08:15:58U2022-12-08 23:06:00.0<NA>192480.368332438525.414483<NA><NA><NA><NA>
131700003170000-S2014000012014-02-12<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>24631.0<NA>서울특별시 금천구 시흥동 1026번지서울특별시 금천구 시흥대로 165 (시흥동)153-031남서울힐스테이트아파트 1단지 지하1~2층2023-04-10 11:08:31U2023-04-12 02:40:00.0<NA>191190.614296438410.522111서울특별시 금천구 시흥동 1026번지공공용시설남서울힐스테이트아파트 1단지 지하1~2층<NA>
231700003170000-S2011000102011-03-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3773.0<NA>서울특별시 금천구 독산동 1028번지서울특별시 금천구 시흥대로112길 6 (독산동, 대덕트윈빌)08580대덕트윈빌 101동 지하주차장 1~2층2024-01-26 14:13:25U2023-11-30 22:08:00.0<NA>191004.699476440576.060452<NA><NA><NA><NA>
331700003170000-S2011000052011-03-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2756.0<NA>서울특별시 금천구 독산동 1139번지서울특별시 금천구 두산로11길 22 (독산동, 청광플러스원아파트)8524청광플러스원아파트 지하주차장 지하1층2023-04-10 10:34:23U2023-04-12 02:40:00.0<NA>190565.170337441012.947963서울특별시 금천구 독산동 1139번지공공용시설청광플러스원아파트 지하주차장 지하1층<NA>
431700003170000-S2005000222005-01-012023-07-274취소/말소/만료/정지/중지19사용중지2023-07-27<NA><NA><NA><NA>286.0<NA>서울특별시 금천구 시흥동 220번지 2호서울특별시 금천구 탑골로3길 50 (시흥동)153-860구현대아파트 지하1층2023-07-28 15:19:20U2022-12-06 21:00:00.0<NA>192313.512605439052.896966<NA><NA><NA><NA>
531700003170000-S2011000082011-03-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1083.0<NA>서울특별시 금천구 독산동 184번지 3호서울특별시 금천구 독산로78다길 22 (독산동, 아셈그린힐)08557아셈그린힐 지하주차장 지하1층2023-10-24 17:05:54U2022-10-30 22:06:00.0<NA>191543.972553440797.858288<NA><NA><NA><NA>
631700003170000-S2014000022014-02-12<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>56311.0<NA>서울특별시 금천구 시흥동 1026번지서울특별시 금천구 시흥대로 165 (시흥동)153-031남서울힐스테이트아파트 2단지 지하1~2층2023-04-10 11:08:53U2023-04-12 02:40:00.0<NA>191190.614296438410.522111서울특별시 금천구 시흥동 1026번지공공용시설남서울힐스테이트아파트 2단지 지하1~2층<NA>
731700003170000-S2005000182005-04-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>635.0<NA>서울특별시 금천구 독산동 983번지 16호서울특별시 금천구 시흥대로 446 (독산동)153-013신한은행 독산동지점 지하1층2023-07-11 13:19:35U2023-07-13 02:40:00.0<NA>190979.133292441227.949108서울특별시 금천구 독산동 983번지 16호공공용시설신한은행 독산동지점 지하1층<NA>
831700003170000-S2004000012004-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1564.0<NA>서울특별시 금천구 시흥동 870번지 27호서울특별시 금천구 시흥대로72길 13 (시흥동, 시흥중앙교회(세나유치원))8624시흥중앙교회 지하1층2023-04-10 11:06:58U2023-04-12 02:40:00.0<NA>191104.505483439455.843301서울특별시 금천구 시흥동 870번지 27호공공용시설시흥중앙교회 지하1층<NA>
931700003170000-S2005000262005-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2133.0<NA>서울특별시 금천구 시흥동 912번지 20호서울특별시 금천구 금하로 720 (시흥동)08644에벤에셀프라자(지하1~2층)2024-01-26 14:54:28U2023-11-30 22:08:00.0<NA>191917.450108438699.774609<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
5931700003170000-S2023000022023-06-20<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4476.98<NA>서울특별시 금천구 가산동 234-46 가산삼익아파트서울특별시 금천구 두산로9길 56 (가산동, 가산삼익아파트)08521가산삼익아파트(지하1층~2층)2024-01-31 08:08:03U2023-12-02 00:02:00.0<NA>190464.852861441196.233807<NA><NA><NA><NA>
6031700003170000-S2022000012022-11-17<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>27718.0<NA>서울특별시 금천구 독산동 1156 금천롯데캐슬골드파크4차서울특별시 금천구 시흥대로 315, 금천롯데캐슬골드파크4차 (독산동)8608금천롯데캐슬골드파크4차 골드파크타워 960 지하3~52023-04-11 09:12:23U2023-04-13 02:40:00.0<NA>190799.832999439885.941303서울특별시 금천구 독산동 1156 금천롯데캐슬골드파크4차공공용시설금천롯데캐슬골드파크4차 골드파크타워 960 지하3~5<NA>
6131700003170000-S2011000062011-03-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4243.0<NA>서울특별시 금천구 독산동 371번지 2호서울특별시 금천구 독산로54길 188 (독산동)08556금천문화체육센터 지하주차장 지하1,2층2023-10-24 17:07:18U2022-10-30 22:06:00.0<NA>191726.600363440888.699596<NA><NA><NA><NA>
6231700003170000-S2011000112011-03-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>194.0<NA>서울특별시 금천구 독산동 1019번지 23호서울특별시 금천구 독산로 237 (독산동, 주는교회)08578주는교회 지하주차장 지하1층2023-10-24 17:06:27U2022-10-30 22:06:00.0<NA>191241.457996440653.257976<NA><NA><NA><NA>
6331700003170000-S2009000192009-11-20<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6597.0<NA>서울특별시 금천구 시흥동 1017번지서울특별시 금천구 금하로24나길 48 (시흥동)08647관악산 신도브래뉴 아파트 지하주차장 1층2024-01-25 09:36:04U2023-11-30 22:07:00.0<NA>192024.601514438423.909375<NA><NA><NA><NA>
6431700003170000-S2005000252005-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1650.0<NA>서울특별시 금천구 시흥동 209번지서울특별시 금천구 금하로23라길 31 (시흥동)08571신현대아파트 지하1층2024-01-25 09:33:17U2023-11-30 22:07:00.0<NA>192027.596002439099.897861<NA><NA><NA><NA>
6531700003170000-S1997000031997-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4324.0<NA>서울특별시 금천구 독산동 183번지 1호서울특별시 금천구 독산로78다길 52 (독산동, 독산동동아아파트)08556동아아파트 지하주차장 지하1,2층2024-01-25 10:55:30U2023-11-30 22:07:00.0<NA>191643.543153440867.731615<NA><NA><NA><NA>
6631700003170000-S2011000132011-03-28<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>12552.0<NA>서울특별시 금천구 가산동 468번지 4호서울특별시 금천구 벚꽃로 309 (가산동, 가산디지털단지역)08510가산디지털단지역 지하1~3층2024-01-31 08:08:27U2023-12-02 00:02:00.0<NA>189514.729968442253.567255<NA><NA><NA><NA>
6731700003170000-S2005000132005-06-28<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>18665.0<NA>서울특별시 금천구 가산동 769번지서울특별시 금천구 가산로 99 (가산동, 두산위브아파트)08520두산위브아파트 지하1~3층2024-01-31 08:07:08U2023-12-02 00:02:00.0<NA>190352.364512441545.208758<NA><NA><NA><NA>
6831700003170000-S2005000122005-06-28<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>495.0<NA>서울특별시 금천구 가산동 148번지 1호서울특별시 금천구 시흥대로151길 45 (가산동, 가산덕산아파트)08532덕산아파트 지하1층2024-01-31 08:07:34U2023-12-02 00:02:00.0<NA>190735.437651441619.623665<NA><NA><NA><NA>