Overview

Dataset statistics

Number of variables26
Number of observations33
Missing cells114
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory222.0 B

Variable types

Categorical12
Numeric4
DateTime3
Unsupported1
Text6

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),점포구분명
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18719/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (80.4%)Imbalance
휴업종료일자 is highly imbalanced (80.4%)Imbalance
재개업일자 is highly imbalanced (80.4%)Imbalance
인허가취소일자 has 33 (100.0%) missing valuesMissing
폐업일자 has 27 (81.8%) missing valuesMissing
소재지면적 has 4 (12.1%) missing valuesMissing
소재지우편번호 has 25 (75.8%) missing valuesMissing
지번주소 has 2 (6.1%) missing valuesMissing
도로명우편번호 has 19 (57.6%) missing valuesMissing
좌표정보(X) has 2 (6.1%) missing valuesMissing
좌표정보(Y) has 2 (6.1%) missing valuesMissing
관리번호 has unique valuesUnique
전화번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 2 (6.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:50:01.386383
Analysis finished2024-05-11 06:50:01.999940
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
3170000
33 

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 33
100.0%

Length

2024-05-11T15:50:02.134567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:02.298184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 33
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0045897 × 1018
Minimum1.973317 × 1018
Maximum2.024317 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-05-11T15:50:02.497371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.973317 × 1018
5-th percentile1.979117 × 1018
Q12.002317 × 1018
median2.007317 × 1018
Q32.012317 × 1018
95-th percentile2.020917 × 1018
Maximum2.024317 × 1018
Range5.1000019 × 1016
Interquartile range (IQR)1.0000008 × 1016

Descriptive statistics

Standard deviation1.3063007 × 1016
Coefficient of variation (CV)0.006516549
Kurtosis0.22122741
Mean2.0045897 × 1018
Median Absolute Deviation (MAD)5.0000038 × 1015
Skewness-0.9108362
Sum-7.6355149 × 1018
Variance1.7064216 × 1032
MonotonicityStrictly increasing
2024-05-11T15:50:02.787470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1973317006707500006 1
 
3.0%
2013317014207500001 1
 
3.0%
2008317010507500002 1
 
3.0%
2011317014207500001 1
 
3.0%
2012317014207500001 1
 
3.0%
2012317014207500002 1
 
3.0%
2012317014207500003 1
 
3.0%
2012317014207500004 1
 
3.0%
2013317014207500002 1
 
3.0%
1977317006707500009 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1973317006707500006 1
3.0%
1977317006707500009 1
3.0%
1980317006707500013 1
3.0%
1982317006707500014 1
3.0%
1987317006707500016 1
3.0%
1987317006707500017 1
3.0%
1993317006707500023 1
3.0%
2002317006707500001 1
3.0%
2002317006707500002 1
3.0%
2002317006707500003 1
3.0%
ValueCountFrequency (%)
2024317025707500001 1
3.0%
2023317025707500001 1
3.0%
2019317019007500001 1
3.0%
2018317019007500001 1
3.0%
2017317017407500001 1
3.0%
2015317017407500001 1
3.0%
2013317014207500002 1
3.0%
2013317014207500001 1
3.0%
2012317014207500004 1
3.0%
2012317014207500003 1
3.0%

인허가일자
Date

Distinct30
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum1973-09-12 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T15:50:03.009653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:03.243859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
24 
3
6 
2
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 24
72.7%
3 6
 
18.2%
2 3
 
9.1%

Length

2024-05-11T15:50:03.483817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:03.680386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
72.7%
3 6
 
18.2%
2 3
 
9.1%

영업상태명
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
영업/정상
24 
폐업
6 
휴업
3 

Length

Max length5
Median length5
Mean length4.1818182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 24
72.7%
폐업 6
 
18.2%
휴업 3
 
9.1%

Length

2024-05-11T15:50:03.894887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:04.088131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 24
72.7%
폐업 6
 
18.2%
휴업 3
 
9.1%

상세영업상태코드
Categorical

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
20 
3
6 
BBBB
3 
2
3 
5
 
1

Length

Max length4
Median length1
Mean length1.2727273
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 20
60.6%
3 6
 
18.2%
BBBB 3
 
9.1%
2 3
 
9.1%
5 1
 
3.0%

Length

2024-05-11T15:50:04.300643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:04.494431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
60.6%
3 6
 
18.2%
bbbb 3
 
9.1%
2 3
 
9.1%
5 1
 
3.0%

상세영업상태명
Categorical

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
정상영업
20 
폐업처리
6 
<NA>
3 
휴업처리
3 
영업개시전
 
1

Length

Max length5
Median length4
Mean length4.030303
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 20
60.6%
폐업처리 6
 
18.2%
<NA> 3
 
9.1%
휴업처리 3
 
9.1%
영업개시전 1
 
3.0%

Length

2024-05-11T15:50:04.705541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:04.957303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 20
60.6%
폐업처리 6
 
18.2%
na 3
 
9.1%
휴업처리 3
 
9.1%
영업개시전 1
 
3.0%

폐업일자
Date

MISSING 

Distinct6
Distinct (%)100.0%
Missing27
Missing (%)81.8%
Memory size396.0 B
Minimum2012-11-23 00:00:00
Maximum2023-07-01 00:00:00
2024-05-11T15:50:05.190753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:05.398351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
32 
20120130
 
1

Length

Max length8
Median length4
Mean length4.1212121
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
97.0%
20120130 1
 
3.0%

Length

2024-05-11T15:50:05.641858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:05.859181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
97.0%
20120130 1
 
3.0%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
32 
20120624
 
1

Length

Max length8
Median length4
Mean length4.1212121
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
97.0%
20120624 1
 
3.0%

Length

2024-05-11T15:50:06.101138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:06.293133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
97.0%
20120624 1
 
3.0%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
32 
20120625
 
1

Length

Max length8
Median length4
Mean length4.1212121
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
97.0%
20120625 1
 
3.0%

Length

2024-05-11T15:50:06.470756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:06.661638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
97.0%
20120625 1
 
3.0%

전화번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-05-11T15:50:06.890462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.363636
Min length8

Characters and Unicode

Total characters342
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row02 8035052
2nd row02 8034878
3rd row02-2243-0190
4th row02 8060123
5th row02 8057180
ValueCountFrequency (%)
02 10
 
21.3%
802-5601 1
 
2.1%
776-7049 1
 
2.1%
02-808-1522 1
 
2.1%
895 1
 
2.1%
2080 1
 
2.1%
2292-5853 1
 
2.1%
895-8585 1
 
2.1%
856-8545 1
 
2.1%
02-2109-7013 1
 
2.1%
Other values (28) 28
59.6%
2024-05-11T15:50:07.598665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78
22.8%
2 56
16.4%
8 39
11.4%
5 32
9.4%
- 27
 
7.9%
1 21
 
6.1%
3 19
 
5.6%
9 19
 
5.6%
18
 
5.3%
7 13
 
3.8%
Other values (2) 20
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 297
86.8%
Dash Punctuation 27
 
7.9%
Space Separator 18
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 78
26.3%
2 56
18.9%
8 39
13.1%
5 32
10.8%
1 21
 
7.1%
3 19
 
6.4%
9 19
 
6.4%
7 13
 
4.4%
4 12
 
4.0%
6 8
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 342
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 78
22.8%
2 56
16.4%
8 39
11.4%
5 32
9.4%
- 27
 
7.9%
1 21
 
6.1%
3 19
 
5.6%
9 19
 
5.6%
18
 
5.3%
7 13
 
3.8%
Other values (2) 20
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78
22.8%
2 56
16.4%
8 39
11.4%
5 32
9.4%
- 27
 
7.9%
1 21
 
6.1%
3 19
 
5.6%
9 19
 
5.6%
18
 
5.3%
7 13
 
3.8%
Other values (2) 20
 
5.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)96.6%
Missing4
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean15543.573
Minimum0
Maximum98983
Zeros2
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-05-11T15:50:07.858588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.24
Q12258.01
median11464
Q324253.99
95-th percentile32379.514
Maximum98983
Range98983
Interquartile range (IQR)21995.98

Descriptive statistics

Standard deviation19360.434
Coefficient of variation (CV)1.2455588
Kurtosis12.140245
Mean15543.573
Median Absolute Deviation (MAD)9914
Skewness2.9917987
Sum450763.62
Variance3.7482641 × 108
MonotonicityNot monotonic
2024-05-11T15:50:08.096666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 2
 
6.1%
14972.0 1
 
3.0%
18020.0 1
 
3.0%
4288.0 1
 
3.0%
31618.0 1
 
3.0%
11464.0 1
 
3.0%
8815.59 1
 
3.0%
24253.99 1
 
3.0%
25015.45 1
 
3.0%
32887.19 1
 
3.0%
Other values (18) 18
54.5%
(Missing) 4
 
12.1%
ValueCountFrequency (%)
0.0 2
6.1%
175.6 1
3.0%
243.5 1
3.0%
244.9 1
3.0%
699.7 1
3.0%
2063.0 1
3.0%
2258.01 1
3.0%
3745.05 1
3.0%
4079.41 1
3.0%
4288.0 1
3.0%
ValueCountFrequency (%)
98983.0 1
3.0%
32887.19 1
3.0%
31618.0 1
3.0%
29885.04 1
3.0%
26776.55 1
3.0%
26776.0 1
3.0%
25015.45 1
3.0%
24253.99 1
3.0%
21378.0 1
3.0%
18020.0 1
3.0%

소재지우편번호
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing25
Missing (%)75.8%
Memory size396.0 B
2024-05-11T15:50:08.402317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length6.5
Min length6

Characters and Unicode

Total characters52
Distinct characters8
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

Unique6 ?
Unique (%)75.0%

Sample

1st row153010
2nd row153-031
3rd row153011
4th row153859
5th row153-801
ValueCountFrequency (%)
153-023 2
25.0%
153010 1
12.5%
153-031 1
12.5%
153011 1
12.5%
153859 1
12.5%
153-801 1
12.5%
153801 1
12.5%
2024-05-11T15:50:08.883535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
26.9%
3 11
21.2%
5 9
17.3%
0 8
15.4%
- 4
 
7.7%
8 3
 
5.8%
2 2
 
3.8%
9 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
92.3%
Dash Punctuation 4
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
29.2%
3 11
22.9%
5 9
18.8%
0 8
16.7%
8 3
 
6.2%
2 2
 
4.2%
9 1
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
26.9%
3 11
21.2%
5 9
17.3%
0 8
15.4%
- 4
 
7.7%
8 3
 
5.8%
2 2
 
3.8%
9 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
26.9%
3 11
21.2%
5 9
17.3%
0 8
15.4%
- 4
 
7.7%
8 3
 
5.8%
2 2
 
3.8%
9 1
 
1.9%

지번주소
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing2
Missing (%)6.1%
Memory size396.0 B
2024-05-11T15:50:09.232664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length24.741935
Min length18

Characters and Unicode

Total characters767
Distinct characters49
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

Unique29 ?
Unique (%)93.5%

Sample

1st row서울특별시 금천구 시흥동 831번지 6호
2nd row서울특별시 금천구 시흥동 884번지 5호
3rd row서울특별시 금천구 시흥동 956호
4th row서울특별시 금천구 시흥동 1002번지 1호
5th row서울특별시 금천구 시흥동 966호
ValueCountFrequency (%)
서울특별시 31
19.5%
금천구 31
19.5%
시흥동 12
 
7.5%
독산동 11
 
6.9%
가산동 6
 
3.8%
60번지 5
 
3.1%
외 4
 
2.5%
6호 3
 
1.9%
5호 3
 
1.9%
291번지 3
 
1.9%
Other values (42) 50
31.4%
2024-05-11T15:50:09.878138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
20.3%
시 45
 
5.9%
천 35
 
4.6%
금 35
 
4.6%
서 31
 
4.0%
동 31
 
4.0%
구 31
 
4.0%
울 31
 
4.0%
별 31
 
4.0%
특 31
 
4.0%
Other values (39) 310
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
61.4%
Space Separator 156
 
20.3%
Decimal Number 135
 
17.6%
Dash Punctuation 3
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 45
 
9.6%
천 35
 
7.4%
금 35
 
7.4%
서 31
 
6.6%
동 31
 
6.6%
구 31
 
6.6%
울 31
 
6.6%
별 31
 
6.6%
특 31
 
6.6%
지 25
 
5.3%
Other values (25) 145
30.8%
Decimal Number
ValueCountFrequency (%)
9 21
15.6%
1 20
14.8%
2 19
14.1%
6 14
10.4%
5 13
9.6%
7 12
8.9%
0 12
8.9%
8 12
8.9%
4 8
 
5.9%
3 4
 
3.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
61.4%
Common 296
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 45
 
9.6%
천 35
 
7.4%
금 35
 
7.4%
서 31
 
6.6%
동 31
 
6.6%
구 31
 
6.6%
울 31
 
6.6%
별 31
 
6.6%
특 31
 
6.6%
지 25
 
5.3%
Other values (25) 145
30.8%
Common
ValueCountFrequency (%)
156
52.7%
9 21
 
7.1%
1 20
 
6.8%
2 19
 
6.4%
6 14
 
4.7%
5 13
 
4.4%
7 12
 
4.1%
0 12
 
4.1%
8 12
 
4.1%
4 8
 
2.7%
Other values (4) 9
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
61.4%
ASCII 296
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
52.7%
9 21
 
7.1%
1 20
 
6.8%
2 19
 
6.4%
6 14
 
4.7%
5 13
 
4.4%
7 12
 
4.1%
0 12
 
4.1%
8 12
 
4.1%
4 8
 
2.7%
Other values (4) 9
 
3.0%
Hangul
ValueCountFrequency (%)
시 45
 
9.6%
천 35
 
7.4%
금 35
 
7.4%
서 31
 
6.6%
동 31
 
6.6%
구 31
 
6.6%
울 31
 
6.6%
별 31
 
6.6%
특 31
 
6.6%
지 25
 
5.3%
Other values (25) 145
30.8%

도로명주소
Text

Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-05-11T15:50:10.275321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length38
Mean length26.606061
Min length14

Characters and Unicode

Total characters878
Distinct characters65
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

Unique29 ?
Unique (%)87.9%

Sample

1st row서울특별시 금천구 금하로 705 (시흥동)
2nd row서울특별시 금천구 시흥대로52길 70 (시흥동)
3rd row서울특별시 금천구 시흥대로18길 16 (시흥동)
4th row서울특별시 금천구 시흥대로47길 43 (시흥동)
5th row서울특별시 금천구 시흥대로 46 (시흥동)
ValueCountFrequency (%)
서울특별시 33
19.2%
금천구 32
18.6%
시흥대로 13
 
7.6%
독산동 11
 
6.4%
시흥동 10
 
5.8%
가산동 7
 
4.1%
201 3
 
1.7%
벚꽃로 3
 
1.7%
디지털로 3
 
1.7%
391 3
 
1.7%
Other values (50) 54
31.4%
2024-05-11T15:50:10.886736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
15.9%
시 65
 
7.4%
금 39
 
4.4%
천 36
 
4.1%
서 33
 
3.8%
( 33
 
3.8%
로 33
 
3.8%
울 33
 
3.8%
별 33
 
3.8%
특 33
 
3.8%
Other values (55) 400
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 551
62.8%
Space Separator 140
 
15.9%
Decimal Number 112
 
12.8%
Open Punctuation 33
 
3.8%
Close Punctuation 33
 
3.8%
Other Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 65
 
11.8%
금 39
 
7.1%
천 36
 
6.5%
서 33
 
6.0%
로 33
 
6.0%
울 33
 
6.0%
별 33
 
6.0%
특 33
 
6.0%
구 32
 
5.8%
흥 32
 
5.8%
Other values (41) 182
33.0%
Decimal Number
ValueCountFrequency (%)
1 23
20.5%
2 17
15.2%
0 14
12.5%
7 12
10.7%
3 10
8.9%
9 10
8.9%
8 8
 
7.1%
4 7
 
6.2%
6 6
 
5.4%
5 5
 
4.5%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 551
62.8%
Common 327
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 65
 
11.8%
금 39
 
7.1%
천 36
 
6.5%
서 33
 
6.0%
로 33
 
6.0%
울 33
 
6.0%
별 33
 
6.0%
특 33
 
6.0%
구 32
 
5.8%
흥 32
 
5.8%
Other values (41) 182
33.0%
Common
ValueCountFrequency (%)
140
42.8%
( 33
 
10.1%
) 33
 
10.1%
1 23
 
7.0%
2 17
 
5.2%
0 14
 
4.3%
7 12
 
3.7%
3 10
 
3.1%
9 10
 
3.1%
, 9
 
2.8%
Other values (4) 26
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 551
62.8%
ASCII 327
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
42.8%
( 33
 
10.1%
) 33
 
10.1%
1 23
 
7.0%
2 17
 
5.2%
0 14
 
4.3%
7 12
 
3.7%
3 10
 
3.1%
9 10
 
3.1%
, 9
 
2.8%
Other values (4) 26
 
8.0%
Hangul
ValueCountFrequency (%)
시 65
 
11.8%
금 39
 
7.1%
천 36
 
6.5%
서 33
 
6.0%
로 33
 
6.0%
울 33
 
6.0%
별 33
 
6.0%
특 33
 
6.0%
구 32
 
5.8%
흥 32
 
5.8%
Other values (41) 182
33.0%

도로명우편번호
Text

MISSING 

Distinct11
Distinct (%)78.6%
Missing19
Missing (%)57.6%
Memory size396.0 B
2024-05-11T15:50:11.144939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length5.7142857
Min length5

Characters and Unicode

Total characters80
Distinct characters10
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

Unique9 ?
Unique (%)64.3%

Sample

1st row153813
2nd row08584
3rd row08639
4th row153832
5th row153-804
ValueCountFrequency (%)
08608 3
21.4%
153-801 2
14.3%
153813 1
 
7.1%
08584 1
 
7.1%
08639 1
 
7.1%
153832 1
 
7.1%
153-804 1
 
7.1%
153859 1
 
7.1%
153801 1
 
7.1%
08513 1
 
7.1%
2024-05-11T15:50:11.652714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 18
22.5%
0 14
17.5%
1 12
15.0%
3 12
15.0%
5 10
12.5%
6 5
 
6.2%
- 3
 
3.8%
4 2
 
2.5%
9 2
 
2.5%
2 2
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
96.2%
Dash Punctuation 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 18
23.4%
0 14
18.2%
1 12
15.6%
3 12
15.6%
5 10
13.0%
6 5
 
6.5%
4 2
 
2.6%
9 2
 
2.6%
2 2
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 18
22.5%
0 14
17.5%
1 12
15.0%
3 12
15.0%
5 10
12.5%
6 5
 
6.2%
- 3
 
3.8%
4 2
 
2.5%
9 2
 
2.5%
2 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 18
22.5%
0 14
17.5%
1 12
15.0%
3 12
15.0%
5 10
12.5%
6 5
 
6.2%
- 3
 
3.8%
4 2
 
2.5%
9 2
 
2.5%
2 2
 
2.5%

사업장명
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-05-11T15:50:12.134468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length10.575758
Min length4

Characters and Unicode

Total characters349
Distinct characters107
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st row시흥중앙시장
2nd row대명합동시장
3rd row박미종합시장
4th row럭키남서울상가
5th row시흥중앙철재상가
ValueCountFrequency (%)
금천점 4
 
6.6%
시흥점 3
 
4.9%
롯데쇼핑(주 3
 
4.9%
삼성테스코(주)홈플러스 2
 
3.3%
골드파크 2
 
3.3%
독산점 2
 
3.3%
가산점 2
 
3.3%
마리오아울렛 2
 
3.3%
홈플러스(주)익스프레스 2
 
3.3%
롯데캐슬 2
 
3.3%
Other values (35) 37
60.7%
2024-05-11T15:50:12.746468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
8.0%
시 15
 
4.3%
스 14
 
4.0%
주 13
 
3.7%
( 12
 
3.4%
) 12
 
3.4%
점 12
 
3.4%
데 9
 
2.6%
롯 9
 
2.6%
플 8
 
2.3%
Other values (97) 217
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 287
82.2%
Space Separator 28
 
8.0%
Open Punctuation 12
 
3.4%
Close Punctuation 12
 
3.4%
Decimal Number 7
 
2.0%
Uppercase Letter 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 15
 
5.2%
스 14
 
4.9%
주 13
 
4.5%
점 12
 
4.2%
데 9
 
3.1%
롯 9
 
3.1%
플 8
 
2.8%
산 8
 
2.8%
홈 8
 
2.8%
흥 7
 
2.4%
Other values (84) 184
64.1%
Decimal Number
ValueCountFrequency (%)
9 1
14.3%
4 1
14.3%
3 1
14.3%
1 1
14.3%
2 1
14.3%
0 1
14.3%
6 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
I 1
33.3%
V 1
33.3%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 287
82.2%
Common 59
 
16.9%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 15
 
5.2%
스 14
 
4.9%
주 13
 
4.5%
점 12
 
4.2%
데 9
 
3.1%
롯 9
 
3.1%
플 8
 
2.8%
산 8
 
2.8%
홈 8
 
2.8%
흥 7
 
2.4%
Other values (84) 184
64.1%
Common
ValueCountFrequency (%)
28
47.5%
( 12
20.3%
) 12
20.3%
9 1
 
1.7%
4 1
 
1.7%
3 1
 
1.7%
1 1
 
1.7%
2 1
 
1.7%
0 1
 
1.7%
6 1
 
1.7%
Latin
ValueCountFrequency (%)
C 1
33.3%
I 1
33.3%
V 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 287
82.2%
ASCII 62
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
45.2%
( 12
19.4%
) 12
19.4%
9 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
1 1
 
1.6%
2 1
 
1.6%
0 1
 
1.6%
6 1
 
1.6%
Other values (3) 3
 
4.8%
Hangul
ValueCountFrequency (%)
시 15
 
5.2%
스 14
 
4.9%
주 13
 
4.5%
점 12
 
4.2%
데 9
 
3.1%
롯 9
 
3.1%
플 8
 
2.8%
산 8
 
2.8%
홈 8
 
2.8%
흥 7
 
2.4%
Other values (84) 184
64.1%

최종수정일자
Date

Distinct24
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2007-07-07 11:59:15
Maximum2024-04-29 15:44:46
2024-05-11T15:50:12.947825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:13.175423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
I
19 
U
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 19
57.6%
U 14
42.4%

Length

2024-05-11T15:50:13.366549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:13.556108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 19
57.6%
u 14
42.4%

데이터갱신일자
Categorical

Distinct13
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Memory size396.0 B
2018-08-31 23:59:59.0
17 
2021-12-04 23:02:00.0
2 
2023-12-03 00:06:00.0
2 
2022-12-03 00:03:00.0
2 
2021-12-24 02:40:00.0
2 
Other values (8)
8 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique8 ?
Unique (%)24.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2021-06-11 02:40:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 17
51.5%
2021-12-04 23:02:00.0 2
 
6.1%
2023-12-03 00:06:00.0 2
 
6.1%
2022-12-03 00:03:00.0 2
 
6.1%
2021-12-24 02:40:00.0 2
 
6.1%
2021-06-11 02:40:00.0 1
 
3.0%
2022-12-07 00:07:00.0 1
 
3.0%
2023-12-03 22:00:00.0 1
 
3.0%
2021-02-20 02:40:00.0 1
 
3.0%
2023-12-02 22:04:00.0 1
 
3.0%
Other values (3) 3
 
9.1%

Length

2024-05-11T15:50:13.742812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 17
25.8%
23:59:59.0 17
25.8%
02:40:00.0 4
 
6.1%
2023-12-03 3
 
4.5%
00:03:00.0 3
 
4.5%
2021-12-04 2
 
3.0%
23:02:00.0 2
 
3.0%
00:06:00.0 2
 
3.0%
2022-12-03 2
 
3.0%
2021-12-24 2
 
3.0%
Other values (12) 12
18.2%

업태구분명
Categorical

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
그 밖의 대규모점포
15 
대형마트
7 
쇼핑센터
7 
구분없음
4 

Length

Max length10
Median length4
Mean length6.7272727
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row그 밖의 대규모점포
2nd row그 밖의 대규모점포
3rd row그 밖의 대규모점포
4th row그 밖의 대규모점포
5th row그 밖의 대규모점포

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 15
45.5%
대형마트 7
21.2%
쇼핑센터 7
21.2%
구분없음 4
 
12.1%

Length

2024-05-11T15:50:13.975943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:14.198685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 15
23.8%
밖의 15
23.8%
대규모점포 15
23.8%
대형마트 7
11.1%
쇼핑센터 7
11.1%
구분없음 4
 
6.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)83.9%
Missing2
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean190899.85
Minimum189722.18
Maximum191917.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-05-11T15:50:14.446014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189722.18
5-th percentile189845.11
Q1190636.16
median191026.64
Q3191244.45
95-th percentile191823.03
Maximum191917.45
Range2195.2716
Interquartile range (IQR)608.29306

Descriptive statistics

Standard deviation597.76691
Coefficient of variation (CV)0.0031313115
Kurtosis-0.37352733
Mean190899.85
Median Absolute Deviation (MAD)263.94522
Skewness-0.47880262
Sum5917895.5
Variance357325.28
MonotonicityNot monotonic
2024-05-11T15:50:14.694321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
191152.432649234 3
 
9.1%
190809.507840375 3
 
9.1%
191823.026849977 2
 
6.1%
191390.785127877 1
 
3.0%
190901.481378795 1
 
3.0%
189930.50790426 1
 
3.0%
190567.418315661 1
 
3.0%
189722.178532426 1
 
3.0%
189943.234285288 1
 
3.0%
190119.463375612 1
 
3.0%
Other values (16) 16
48.5%
(Missing) 2
 
6.1%
ValueCountFrequency (%)
189722.178532426 1
3.0%
189759.713050655 1
3.0%
189930.50790426 1
3.0%
189943.234285288 1
3.0%
189997.455663258 1
3.0%
190119.463375612 1
3.0%
190527.918536528 1
3.0%
190567.418315661 1
3.0%
190704.904312713 1
3.0%
190771.595589599 1
3.0%
ValueCountFrequency (%)
191917.450107657 1
3.0%
191823.026849977 2
6.1%
191497.590452952 1
3.0%
191390.785127877 1
3.0%
191384.606290141 1
3.0%
191290.582375374 1
3.0%
191262.621370792 1
3.0%
191226.287379467 1
3.0%
191224.607415902 1
3.0%
191210.51770388 1
3.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)83.9%
Missing2
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean440056.46
Minimum437280.57
Maximum441920.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-05-11T15:50:14.897181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437280.57
5-th percentile437738.15
Q1438849.77
median440515.67
Q3441510.63
95-th percentile441799.18
Maximum441920.97
Range4640.3986
Interquartile range (IQR)2660.8593

Descriptive statistics

Standard deviation1464.8054
Coefficient of variation (CV)0.0033286761
Kurtosis-1.3085216
Mean440056.46
Median Absolute Deviation (MAD)1267.95
Skewness-0.29584829
Sum13641750
Variance2145655
MonotonicityNot monotonic
2024-05-11T15:50:15.131292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
438865.160717275 3
 
9.1%
440728.382273075 3
 
9.1%
438834.378061101 2
 
6.1%
437280.574150819 1
 
3.0%
441536.391463324 1
 
3.0%
441616.460710064 1
 
3.0%
439569.401459017 1
 
3.0%
441920.972770099 1
 
3.0%
441784.247518723 1
 
3.0%
441716.684586176 1
 
3.0%
Other values (16) 16
48.5%
(Missing) 2
 
6.1%
ValueCountFrequency (%)
437280.574150819 1
 
3.0%
437562.242368734 1
 
3.0%
437914.06299827 1
 
3.0%
437986.940834791 1
 
3.0%
438699.77460936 1
 
3.0%
438701.205634976 1
 
3.0%
438834.378061101 2
6.1%
438865.160717275 3
9.1%
439137.99206467 1
 
3.0%
439247.719038249 1
 
3.0%
ValueCountFrequency (%)
441920.972770099 1
3.0%
441814.115920983 1
3.0%
441784.247518723 1
3.0%
441768.833867706 1
3.0%
441716.684586176 1
3.0%
441687.841171831 1
3.0%
441616.460710064 1
3.0%
441536.391463324 1
3.0%
441484.865931033 1
3.0%
441203.919968343 1
3.0%

점포구분명
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
23 
대규모점포
7 
준대규모점포
3 

Length

Max length6
Median length4
Mean length4.3939394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
69.7%
대규모점포 7
 
21.2%
준대규모점포 3
 
9.1%

Length

2024-05-11T15:50:15.382550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:15.984332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
69.7%
대규모점포 7
 
21.2%
준대규모점포 3
 
9.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03170000197331700670750000619730912<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>02 80350522063.0<NA>서울특별시 금천구 시흥동 831번지 6호서울특별시 금천구 금하로 705 (시흥동)<NA>시흥중앙시장2007-07-07 11:59:15I2018-08-31 23:59:59.0그 밖의 대규모점포191823.02685438834.378061<NA>
13170000197731700670750000919771210<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8034878<NA><NA>서울특별시 금천구 시흥동 884번지 5호서울특별시 금천구 시흥대로52길 70 (시흥동)<NA>대명합동시장2007-07-07 11:59:15I2018-08-31 23:59:59.0그 밖의 대규모점포191262.621371439137.992065<NA>
23170000198031700670750001319800913<NA>3폐업3폐업처리20170630<NA><NA><NA>02-2243-01902258.01<NA>서울특별시 금천구 시흥동 956호서울특별시 금천구 시흥대로18길 16 (시흥동)<NA>박미종합시장2021-06-09 10:15:22U2021-06-11 02:40:00.0그 밖의 대규모점포191497.590453437562.242369대규모점포
33170000198231700670750001419820114<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8060123<NA><NA>서울특별시 금천구 시흥동 1002번지 1호서울특별시 금천구 시흥대로47길 43 (시흥동)<NA>럭키남서울상가2007-07-07 11:59:15I2018-08-31 23:59:59.0그 밖의 대규모점포191026.637158438701.205635<NA>
43170000198731700670750001619870331<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 80571800.0<NA>서울특별시 금천구 시흥동 966호서울특별시 금천구 시흥대로 46 (시흥동)<NA>시흥중앙철재상가2014-12-01 16:05:50I2018-08-31 23:59:59.0그 밖의 대규모점포191390.785128437280.574151대규모점포
53170000198731700670750001719870626<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8081522<NA><NA>서울특별시 금천구 시흥동 984번지 6호서울특별시 금천구 시흥대로 109 (시흥동)<NA>시흥산업용재유통센타2007-07-07 11:59:15I2018-08-31 23:59:59.0그 밖의 대규모점포191384.60629437986.940835<NA>
63170000199331700670750002319940314<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8934527<NA><NA>서울특별시 금천구 독산동 293번지 5호서울특별시 금천구 범안로 1209 (독산동)<NA>유창상가2007-07-07 11:59:15I2018-08-31 23:59:59.0그 밖의 대규모점포190771.59559440515.669035<NA>
73170000200231700670750000120020618<NA>1영업/정상1정상영업<NA>20120130201206242012062502 2145850012561.0<NA>서울특별시 금천구 독산동 295번지 10 호 외 5서울특별시 금천구 두산로 71 (독산동)153813롯데쇼핑(주) VIC 마켓 금천점2022-05-10 14:27:50U2021-12-04 23:02:00.0대형마트190704.904313440940.384414<NA>
83170000200231700670750000220020618<NA>2휴업2휴업처리<NA><NA><NA><NA>023016150014972.02<NA>서울특별시 금천구 시흥동 992번지 47호 외 1서울특별시 금천구 시흥대로 201 (시흥동,외 1)<NA>(주)이랜드리테일 홈에버 시흥점2007-07-07 11:59:15I2018-08-31 23:59:59.0대형마트191152.432649438865.160717<NA>
93170000200231700670750000320021024<NA>3폐업3폐업처리20121123<NA><NA><NA>0289050158642.24<NA>서울특별시 금천구 시흥동 831번지 6호서울특별시 금천구 금하로 705 (시흥동)<NA>플라자 카멜리아2012-11-26 16:39:00I2018-08-31 23:59:59.0그 밖의 대규모점포191823.02685438834.378061대규모점포
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
233170000201231701420750000320120507<NA>3폐업3폐업처리20161226<NA><NA><NA>802-5601699.7153859서울특별시 금천구 시흥5동 912번지 20호서울특별시 금하로 720153859롯데쇼핑(주)롯데슈퍼 시흥점2016-12-29 17:48:42I2018-08-31 23:59:59.0구분없음191917.450108438699.774609준대규모점포
24317000020123170142075000042012-09-13<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2109-701332887.19153-801서울특별시 금천구 가산동 60번지 20호서울특별시 금천구 벚꽃로 266 (가산동)<NA>마리오아울렛 3관2023-02-28 21:05:56U2022-12-03 00:03:00.0쇼핑센터189759.713051441814.115921<NA>
25317000020133170142075000012013-03-19<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2136-223325015.45153-023서울특별시 금천구 가산동 60번지 8호서울특별시 금천구 디지털로10길 9 (가산동)153-801현대아울렛2023-05-01 14:20:32U2022-12-05 00:03:00.0쇼핑센터190119.463376441716.684586<NA>
26317000020133170142075000022013-09-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2109-700024253.99153-023서울특별시 금천구 가산동 60번지 22호서울특별시 금천구 디지털로 185 (가산동)153-801마리오아울렛 1관2023-02-28 20:56:47U2022-12-03 00:03:00.0쇼핑센터189943.234285441784.247519<NA>
273170000201531701740750000120151229<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3397-30008815.59153801서울특별시 금천구 가산동 60번지 19호서울특별시 금천구 벚꽃로 278 (가산동)153801롯데쇼핑(주) 아울렛 가산점2015-12-29 14:34:03I2018-08-31 23:59:59.0쇼핑센터189722.178532441920.97277대규모점포
283170000201731701740750000120171205<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-802-883511464.0<NA>서울특별시 금천구 독산동 1150번지 금천롯데캐슬골드파크2차서울특별시 금천구 벚꽃로 30 (독산동, 금천롯데캐슬골드파크2차)08608롯데캐슬 골드파크 2차 마르쉐도르2021-12-22 17:11:19U2021-12-24 02:40:00.0그 밖의 대규모점포190567.418316439569.401459대규모점포
293170000201831701900750000120180430<NA>1영업/정상1정상영업<NA><NA><NA><NA>022145800031618.0<NA>서울특별시 금천구 독산동 1155 금천롯데캐슬골드파크3차서울특별시 금천구 시흥대로 291(독산동, 금천롯데캐슬골드파크3차)08608롯데쇼핑(주) 금천 독산점2022-05-10 14:29:30U2021-12-04 23:02:00.0쇼핑센터<NA><NA><NA>
303170000201931701900750000120190410<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-809-99574288.0<NA>서울특별시 금천구 독산동 1156번지 금천롯데캐슬골드파크4차서울특별시 금천구 시흥대로 315, 금천롯데캐슬골드파크4차 (독산동)08608롯데캐슬 골드파크 4차 마르쉐도르 9602021-12-22 17:07:46U2021-12-24 02:40:00.0그 밖의 대규모점포<NA><NA>대규모점포
31317000020233170257075000012023-12-29<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-422-031018020.0<NA>서울특별시 금천구 가산동 60-26서울특별시 금천구 디지털로 178 (가산동)08513가산퍼블릭 상업시설2023-12-29 17:39:40I2022-11-01 21:01:00.0그 밖의 대규모점포189930.507904441616.46071<NA>
32317000020243170257075000012024-04-29<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-890-81220.0<NA>서울특별시 금천구 시흥동 992-47 홈플러스테스테스코(주)시흥점서울특별시 금천구 시흥대로 201, 홈플러스테스테스코(주)시흥점 (시흥동)08632홈플러스 주식회사2024-04-29 15:44:46I2023-12-05 00:01:00.0대형마트191152.432649438865.160717<NA>